Dataset Information

Influenza A virus- integrated glycomics, proteomics and glycoproteomics

ABSTRACT: This study describes how site-specific glycosylation of Influenza A virus changes in response to pressures from the host immune system, thereby allowing the virus to evolve and escape neutralization. We compared the glycosylation patterns of different virus strains as they evolve and correlated this information with changes in biological activity. Furthermore, modelling and molecular dynamics studies were performed to understand the basis for glycan microheterogeneity and interactions of the virions with host-immune molecules.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human) Orthomyxoviridae

TISSUE(S): Blood Serum

DISEASE(S): Influenza

SUBMITTER: Kshitij Khatri

LAB HEAD: Joseph Zaia

PROVIDER: PXD003498 | Pride | 2016-04-26

REPOSITORIES: Pride

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Publications

Integrated Omics and Computational Glycobiology Reveal Structural Basis for Influenza A Virus Glycan Microheterogeneity and Host Interactions.

Khatri Kshitij K Klein Joshua A JA White Mitchell R MR Grant Oliver C OC Leymarie Nancy N Woods Robert J RJ Hartshorn Kevan L KL Zaia Joseph J

Molecular & cellular proteomics : MCP 20160316 6

Despite sustained biomedical research effort, influenza A virus remains an imminent threat to the world population and a major healthcare burden. The challenge in developing vaccines against influenza is the ability of the virus to mutate rapidly in response to selective immune pressure. Hemagglutinin is the predominant surface glycoprotein and the primary determinant of antigenicity, virulence and zoonotic potential. Mutations leading to changes in the number of HA glycosylation sites are often ...[more]

PMID: 26984886

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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: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.

Dataset Information

Influenza A virus- integrated glycomics, proteomics and glycoproteomics

Publications

Integrated Omics and Computational Glycobiology Reveal Structural Basis for Influenza A Virus Glycan Microheterogeneity and Host Interactions.

Similar Datasets

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