Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 144-161). / Understanding structure-function relationships involved in development of disease is a critical component for the rational design of successful therapeutics, allowing researchers to target precise molecular mechanisms and to anticipate and address future challenges early in development. However, for many diseases and contexts, these precise relationships are unknown or poorly defined. In this thesis, I develop new tools and implement integrated approaches to explore structure-function relationships of disease in two biological contexts: i) the interactions of proteins with glycans that can modify disease susceptibility, and ii) the interactions of viral coat proteins with antibodies that neutralize and prevent viral infection. Section 1: Glycosylation, which is the addition of sugar moieties to proteins and peptides, is one of the most abundant post-translational modifications, modifying a diverse set of biological processes in both health and disease. However, the glycome, or ensemble of glycan structures produced by a cell, is difficult to study, given the low-affinity, high-avidity structural interactions of glycans with host proteins and their non-template-driven biosynthesis. In this section, I investigate how changes in glycomic composition affect disease, and develop and implement tools and approaches that address the aforementioned challenges. In the first part, I leverage a novel in vitro model of lung adenocarcinoma metastasis to study the changes in cell surface glycosylation that correspond with and may influence metastatic progression. Here, I implement and integrate tools, such as glycan biosynthesis gene expression analysis, glycan mass spectrometry analysis frameworks, and lectin binding arrays, to measure the changes in the glycome, identifying several key motifs and glycomic features of metastatic cells. In the second part, I leverage protein-glycan structural insights to understand and predict the susceptibility of a novel seal influenza virus, H3N8, to infect human populations. Here, we used a glycan array, an assay which measures a diversity of glycan binding motifs with biologically relevant avidity and presentation, to demonstrate that unlike human-adapted H3N2, H3N8 lacks the affinity for long a2,6-linked sialylated glycans, which have been shown to determine host specificity and tropism for humans. This result was compared to other experiments, including tissue staining and in vitro replication, to determine that this seal H3N8 virus is unlikely to infect and spread within human populations. These insights further our understanding of how complex ensembles of glycans can influence susceptibility to disease. Section 2: The neutralization of emergent viral pathogens, including Ebola and Zika viruses, by therapeutic antibodies offers the potential to prevent viral infection and to treat patients even after they have been infected. However, given the real-time nature of viral outbreaks, strategies are needed which reduce the development cycle by allowing rational design and selection of potent neutralizing antibodies with minimal susceptibility to antigen escape. Here, I develop a structural, network-based computational and experimental framework which uses information about the viral coat protein and antibodies to identify key features of epitope-paratope interactions. In the context of Ebola virus, I use this analytical framework to identify two novel epitopes on the surface of the trimeric coat glycoprotein which are highly constrained, such that antibodies targeting these regions are likely to be resistant to antigen escape. Furthermore, I use this framework to uncover key differentiators of the overlapping therapeutic antibodies 2G4, 4G7, and KZ52, and describe how these differences may affect their relative susceptibility to epitope escape mutations. In the context of Zika virus, I further develop and expand this analytical framework using a computational Zika E glycoprotein assembly, and use it to understand neutralizing epitopes on the Zika virus surface in the context of their quaternary structure. In doing so, I identify critical interface residues for the 3E31, ZV67, C8, C10, Z23 and Z3L1 antibodies, and use these insights to generate C867, a novel asymmetric IgG bispecific antibody against Zika virus. This antibody has high bispecific purity, maintains in vitro potency, and given its non-overlapping epitopes, has a higher requirement for antigen escape. Taken together, the tools, frameworks, and developments presented here are important additions to the preclinical antibody development toolkit, and enable rational design and faster response to emergent viral pathogens. / by Devin Scott Quinlan. / Ph. D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/119978 |
| Date | January 2018 |
| Creators | Quinlan, Devin Scott |
| Contributors | Ram Sasisekharan., Massachusetts Institute of Technology. Department of Biological Engineering., Massachusetts Institute of Technology. Department of Biological Engineering. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 161 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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