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A Combinatorial Enzymatic Approach for Identifying O-glycopeptides

ABSTRACT: Proteins glycosylation is primarily characterized as N-glycosylation or O-glycosylation. Recognition of the consensus N-glycosylation sequon (N-X-S/T/C) has enabled the mapping of the glycosite occupancy of intact glycopeptides, whereas O-glycosylation consensus sequons do not exit, making the characterization of O-glycosites challenging because of the different degrees of occupancy within a protein. Most O-glycosylation occurs via O-GalNAcylation, which is critical to diverse biological functions. However, only a small fraction of the O-glycosites and their glycan structures have been identified. We introduced a robust and reliable O-glycoproteomic workflow to achieve the long-standing goal of glycobiology—identifying novel O-glycosylation profiles on a large-scale. We developed and implemented a novel O-glycoproteomic workflow through the use of complementary digestion with O-glycoprotease (IMPa), trypsin, Asp-N, and Glu-C for enrichment of O-glycopeptides. The N-terminal of O-glycosylated serine or threonine residues cleaved using IMPa (95% of total PSMs) and over 99% of O-glycopeptides were enriched by the RAX column. Our O-glycoproteomic workflow involving peptide identification (using sceHCD-based MS/MS) and annotation (using FDR evaluation) enabled the identification of O-glycosylation of 189 O-glycosites carrying 379 glycan structures on 79 O-glycoproteins in human plasma. Of the O-glycan forms, 91.7% were distinctively and abundantly observed in core 1 and 2 structures. Importantly, we assessed five well-characterized native proteins purified from human plasma (kininogen-1, fetuin-A, fibrinogen, apolipoprotein E, and plasminogen) to validate the identification of O-glycosites with high confidence and confirm the presence of numerous novel glycosites. We believe that this combinatorial approach is broadly applicable for comprehensive characterization of O-glycoproteomes in biomedical research.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood

SUBMITTER: Akhilesh Pandey

LAB HEAD: Akhilesh Pandey

PROVIDER: PXD042701 | Pride | 2024-04-25

REPOSITORIES: Pride

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Project description:Influenza A virus (IAV) mutates rapidly, preventing a single seasonal vaccine from targeting more than one strain, and year-to-year vaccine effectiveness is low. One challenge in designing effective vaccines is that genetic mutations frequently cause amino acid variations in IAV envelope protein hemagglutinin (HA) that create new N-glycosylation sequons; resulting N-glycans cause antigenic shielding, allowing viral escape from adaptive immune responses. Vaccine candidate strain selection currently involves correlating antigenicity with HA protein sequence among circulating strains, but quantitative comparison of site-specific glycosylation information is likely to improve the ability to design vaccines with broader effectiveness against evolved strains. However, there is poor understanding of the influence of glycosylation on immunodominance, antigenicity, and immunogenicity of HA, and there are no well-tested methods for comparing glycosylation similarity among virus samples. Here, we present a method for statistically rigorous quantification of similarity between two related virus strains that considers the presence and abundance of glycopeptide glycoforms. We demonstrate the strength of our approach by determining that there was a quantifiable difference in glycosylation at the protein level between wild-type IAV HA from A/Switzerland/9715293/2013 (SWZ13) and a mutant strain of SWZ13, even though no N-glycosylation sequons were changed. We determined site-specifically that WT and mutant HA have varying similarity at the glycosylation sites of the head domain, reflecting competing pressures to evade host immune response while retaining viral fitness. To our knowledge, our results are the first to quantify changes in glycosylation state that occur in related proteins of considerable glycan heterogeneity. Our results provide a method for understanding how changes in glycosylation state are correlated with variations in protein sequence, which is necessary for improving IAV vaccine strain selection. Understanding glycosylation will be especially important as we find new expression vectors for vaccine production, as glycosylation state depends greatly on the host species.

Project description:The amino acid sequences of immunodominant domains of hemagglutinin (HA) on the surface of influenza A virus (IAV) evolve rapidly, producing viral variants. HA mediates receptor recognition, binding and cell entry, and serves as the target for IAV vaccines. Glycosylation, a post-translational modification that places large, branched polysaccharide molecules on proteins, can modulate the function of HA, and can shield antigenic regions allowing for viral evasion from immune responses. Our previous work showed that subtle changes in the HA protein sequence can have a measurable change in glycosylation. Thus, being able to measure quantitatively how glycosylation changes in viral variants is critical for understanding how HA function may change throughout viral evolution. Moreover, understanding quantitatively how the choice of viral expression systems affects glycosylation can help in the process of vaccine design and manufacture. Although IAV vaccines are most commonly expressed in chicken eggs, cell-based vaccines have many advantages and the adoption of more cell-based vaccines would be an important step in mitigating seasonal influenza and protecting against future pandemics. Here, we have investigated the use of data-independent acquisition (DIA) mass spectrometry for quantitative glycoproteomics. We found that DIA improved the sensitivity of glycopeptide detection for four variants of A/Switzerland/9715293/2013 IAV: WT and mutant, each expressed in chicken eggs and MDCK cells. We used the Tanimoto similarity metric to quantify changes in glycosylation between WT and mutant, and between egg-expressed and cell-expressed virus. Our DIA site-specific glycosylation similarity comparison of WT and mutant expressed in eggs confirmed our previous analysis while achieving greater depth of coverage. We found that sequence changes resulting from different viral expression systems affected distinct glycosylation sites of HA. Our methods can be applied to track glycosylation changes in circulating IAV variants to bolster the genomic surveillance already being done, for a more complete understanding of IAV evolution.

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A Combinatorial Enzymatic Approach for Identifying O-glycopeptides

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