Infectious diseases caused by viruses such as influenza A virus (IAV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pose major threats to human health. Glycosylation, a post-translational modification critical for biological functions including receptor recognition and binding, cell adhesion, and protein folding, is a key mediator of the interaction between viruses and host cells. IAV and SARS-CoV-2 recognize and bind to glycans on host cells prior to uptake by the cells; by the same token, the glycoproteins hemagglutinin of IAV and the spike protein of SARS-CoV-2 are the targets of both host immune molecules and vaccines. The diversity of glycans, structures made up of oligosaccharide residues in complex, branched configurations, can in part be attributed to the push and pull of evolutionary pressures from infectious disease agents such as these viral pathogens. Evolving host glycans may gain the ability to evade recognition by viruses, and likewise, the evolution of viral glycans may result in viral evasion from immune responses. Thus, for a complete understanding of host-pathogen interactions, detailed characterization of glycoproteins that quantitatively measures changes in glycosylation is necessary. However, a number of factors makes quantitative characterization of glycoproteins difficult. Firstly, glycans are highly heterogeneous with dozens of possible glycans at a given glycosylation site and different occupancy levels at each site. Secondly, a particular glycoform may have very low abundance, making the signals difficult to detect. Thirdly, it is difficult to achieve deep, quantitative measurement of glycoprotein glycans using conventional liquid chromatography-mass spectrometry experiments. The usual mass spectrometry methods are not adequate because they are biased towards selecting higher abundance precursors, which leave many glycopeptide glycoforms undetected.
This dissertation begins with an assessment of the current state-of-the-art of glycoproteomics using mass spectrometry to give context to our primary research discussed in subsequent chapters. Chapter 2 describes the use of a modified Tanimoto similarity coefficient to quantify the glycosylation similarity between two variants of a strain of IAV, wild-type and mutant, both expressed in embryonated chicken eggs. Our results indicate that even subtle changes in the amino acid sequence of hemagglutinin can result in measurably distinct glycosylation. Chapter 3 expands the number of comparisons of IAV strains made in the previous chapter to include strains produced in a mammalian expression vector, Madin-Darby canine kidney cells. We show that the choice of expression system can change the population of glycoforms at some but not necessarily all glycosylation sites. In addition, we explore data-independent acquisition mass spectrometry to improve upon sensitivity and selectivity of glycopeptide identification. In Chapter 4, this data-independent acquisition method is applied to the quantitative characterization of SARS-CoV-2 spike protein. The work presented here provides a significant contribution toward improving the confident detection and assignment of site-specific glycopeptides. Furthermore, understanding how to measure changes in glycosylation in related viral glycoprotein variants offers opportunities to include consideration of specific glycosylations in the design of vaccines to potentially improve efficacy against continually evolving viruses.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/44016 |
| Date | 13 March 2022 |
| Creators | Chang, Deborah |
| Contributors | Zaia, Joseph |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nd/4.0/ |
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