Protein glycosylation and its function
Protein modifications are chemical changes proteins undergo during (co-translational) or after (post-translational) their synthesis. These modifications play critical roles in the regulation of protein function, localization, stability, and interactions, and consequently in fundamental biological processes. Glycosylation is one of the most prevalent but complex forms of protein modifications. It involved the covalent attachment of sugar moieties (glycans) to serine/threonine (O-linked) or asparagine (N-linked) residues. The glycosylation process is non-templated and encompasses co-translational modifications (specifically in N-glycosylation) and post-translational modifications (in both N- and O-glycosylation) regulated by key enzymes including glycosyltransferases (GTFs), oligosaccharyltransferases (OSTs) and glycosidases. The intricate interplay among these enzymes fine-tunes glycan structures and modulates the protein folding, stability, distribution, and cell-cell interactions, thereby regulating glycoprotein functionality within cells. Aberrations in protein glycosylation are increasingly recognized as contributing factors in the pathogenesis of various diseases, including infection, inflammation, and cancers. Many studies aiming at biomarker discovery have reported dysregulation of glycosyltransferases, and linking alterations in glycosylation to immune response against tumour cells, treatment resistance and survival.
Protein glycosylation in lymphoma
Lymphoma is a clinically heterogeneous cancer with deep molecular profiling achieved by omics studies like genomics, transcriptomics and proteomics. Several glycoproteomics studies have evidenced the clustering of differentiation glycoproteins in lymphoma prognosis. Unique glycoprotein biomarkers were also identified in classifying the lymphoma subtypes. Nevertheless, these studies solely uncovered the peptides’ glycosylation sites or the overall released glycans. In our pilot study in lymphoma proteomics, we have revealed alterations in glycosylation machinery in different immunoglobulin heavy variable (IGHV) mutational status, indicating the potential change of glycosylation. A comprehensive and precise profile of intact glycopeptides in lymphoma is thus necessary to gain mechanistic insight.
Lymphoma glycoproteomics profiling with liquid chromatography coupled mass spectrometry (LS-MS)
Liquid chromatography coupled mass spectrometry has emerged as a powerful analytical tool for characterization of glycoproteome. In contrast to the proteomics study, profiling of glycoproteomics on the intact glycopeptides’ level encounters challenges including poor ionisation, structural complexity and low stoichiometry of individual glycopeptide forms due to the inherent heterogeneity. Recent advancements of MS instruments (scanning speed, resolution and fragmentation technology), sample preparation (enrichment of glycopeptides from regular peptides) and database searching tools (robust identification of complex modifications) have shed light on the deep and comprehensive characterization of glycoproteomics. To facilitate our knowledge in lymphoma, we are establishing and optimising an in-house sample preparation and data-dependent acquisition (DDA)-based MS measurement pipeline for deep lymphoma glycoproteomics profiling. Such glycoproteome mapping could lead to the clustering of potential subtypes, identification of biomarkers and thus therapeutic targets, and a deeper understanding of mechanisms in lymphoma pathogenesis.
Novel MS methods and database searching tool for fast, reproducible and quantifiable glycoproteome
Based on the glycoproteome profiling with DDA MS methods, we are also working on the development of data-independent acquisition (DIA) MS method for lymphoma glycoproteome characterization. Contrary to the cutting-edge proteomics study that mainly applied the DIA MS method that ensures high throughput, reproducibility and precise quantification (in a label-free manner), the current measurement of glycopeptides is mainly based on DDA MS strategy due to the complexity of MS raw data for database searching. In our previous study, we successfully extracted the retention time and glycopeptide mass using the oxonium ions (diagnostic glycopeptide fragments) in a DIA run and applied these indexes for a DDA run. Still, the search for these glycopeptides was based on DDA spectra. Parallel to the measurement of lymphoma glycoproteome with DDA-MS pipeline, we are also developing a novel database searching tool for DIA glycoproteomics that enables high throughput, reproducible and quantifiable glycoproteome profiling.