Dataset Information

Influenza A hemagglutinin glycoproteomics similarity

ABSTRACT: 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.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human) Gallus Gallus (chicken) Viruses

TISSUE(S): Egg, Blood Serum

DISEASE(S): Influenza

SUBMITTER: Deborah Chang

LAB HEAD: Joseph Zaia

PROVIDER: PXD018920 | Pride | 2020-07-03

REPOSITORIES: Pride

ACCESS DATA

Publications

Measuring Site-specific Glycosylation Similarity between Influenza a Virus Variants with Statistical Certainty.

Chang Deborah D Hackett William E WE Zhong Lei L Wan Xiu-Feng XF Zaia Joseph J

Molecular & cellular proteomics : MCP 20200629 9

Influenza A virus (IAV) mutates rapidly, resulting in antigenic drift and poor year-to-year vaccine effectiveness. One challenge in designing effective vaccines is that genetic mutations frequently cause amino acid variations in IAV envelope protein hemagglutinin (HA) that create new <i>N</i>-glycosylation sequons; resulting <i>N</i>-glycans cause antigenic shielding, allowing viral escape from adaptive immune responses. Vaccine candidate strain selection currently involves correlating antigenic ...[more]

PMID: 32601173

Similar Datasets

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.

Project description:Glycobiology plays a central role in prostate cancer (PCa), as evidenced by the aberrant glycosylation in PCa-derived glycoproteins. Understanding the protein glycosylation changes underling PCa onset and progression may open opportunities for the discovery of novel biomarkers for PCa detection and stratification as well as targets for PCa metastasis. Advances in mass spectrometry-based glycomics and glycoproteomics have opened up exciting avenues for deep characterisation of the immensely, yet poorly understood complex glycoproteome. In this study, we have used integrated glycomics and glycoproteomics to explore the protein, cell and tumour-grade specific N- and O- glycosylation signatures in surgically-removed fresh PCa tissues grouped into five PCa disease grades and tissues from benign prostatic hyperplasia patients (BPH). Porous graphitised carbon–liquid chromatography (PGC–LC)-MS/MS analysis was used to profile the N-and O-glycome, revealing PCa grade specific N and O glycosylation changes, including oligomannosidic and paucimannosidic, bisecting-GlcNAc and highly branched tri- and tetra-antennary fucosylated and sialylated N-glycans as well as sialylated core 1 and 2 type O-glycans. High resolution LC-MS/MS was then employed to capture the micro and macroheterogeneity of 1,085 N-glycosites (>7,400 unique N-glycopeptides) from 540 N-glycoproteins and 360 O-glycosites (>500 unique O-glycopeptides) from 178 O-glycoproteins and reveal protein and cell specific N- and O- glycosylation changes associated with PCa progression. We also showed PCa grade-specific increase in the expression of oligosaccharyltransferase (OST) subunits that correlate with changes in the site occupancy of N-glycoproteins. In conclusion, this study shows that integrated glycomics and glycoproteomics can provide unprecedented insight into key molecular features and site-specific glycan heterogeneity contributing to the highly diverse tumour-microenvironment and allow us to deconstruct the regulation of the protein, cell and tumour-grade-specific glycosylation associated with PCa onset and development.

Dataset Information

Influenza A hemagglutinin glycoproteomics similarity

Publications

Measuring Site-specific Glycosylation Similarity between Influenza a Virus Variants with Statistical Certainty.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure