Date of Award
12-7-2023
Degree Name
Doctor of Philosophy (PhD)
Degree Type
Dissertation
Abstract
Neutralization assays like the plaque reduction neutralization test (PRNT) and focus reduction neutralization test (FRNT) are the most specific ways to measure neutralizing antibodies, which provide a good estimate of protection for RNA viruses. However, these assays are time-consuming, labor-intensive, and low-throughput. Alternative methods that are faster and convenient are necessary to quantify antibody responses in large-scale studies. In this dissertation, I develop a mix of computational and experimental methods to quantify antibody responses to dengue viruses (DENV) and SARS-CoV-2. DENV is the most significant mosquito-borne viral infection in humans. Four serotypes of DENV exist. Traditionally, infection with one serotype has been thought to confer life-long protection to strains of that serotype. Vaccine formulations are therefore tetravalent to stimulate robust immunity to all four DENV serotypes. However, recent studies show that envelope protein variation within serotypes impacts neutralization to polyclonal immune serum. We developed computational methods to quantify antigenic similarity between DENV strains. A neural network model is developed that incorporates envelope protein amino acid sequence data and structural information to predict the antigenic distance between DENV strains. The model is trained using a large panel of neutralization titers. We identified amino acid positions in the envelope protein most responsible for strain divergence, primarily located in the domain II and domain I/II hinge. The success of current vaccine formulations is predicted by estimating the antigenic similarity of vaccine strains to recently circulating DENV strains. Additionally, we developed separate computational tools to identify the antigenic similarity of DENV-4 strains to a phylogenetically distinct strain of DENV, DKE-121. Sera from mice, non-human primates, and humans were generated to DENV-4 and/or DKE-121 strains. Neutralization titers between sera and challenge viruses were established and used to create antigenic maps. Antigenic maps use multi-dimensional scaling techniques position sera and challenge viruses in two dimensions, resulting in visualization of antigenic relationships and quantification of distance between sera and challenge strains. Finally, we developed an accurate single-point ELISA to perform large sero-serveys to estimate the seroprevalence of IgG antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This work began in April 2020, early in the SARS-CoV-2 pandemic, when few serological tests for SARS-CoV-2 existed. Serological responses of convalescent COVID-19 patients were assessed to eight CoV antigens and three unrelated antigens. We then develop protocols for an in-house ELISA based on spike and nucleoprotein, as IgG responses to these antigens correlate with neutralization titers. The resulting spike IgG ELISA had 98.2% sensitivity and 98.7% specificity, while the NP IgG ELISA had 86.5% sensitivity and 93.1% specificity. The assays were then used to estimate the seroprevalence of SARS-CoV-2 in the St. Louis metropolitan area at four timepoints throughout the pandemic. In summary, we develop tools to assess serological responses to DENV and SARS-CoV-2. The computational DENV tools quantify the antigenic similarity between strains, identify antigenically divergent strains, and predict DENV vaccine success against recently circulating strains. A single point ELISA is also developed to estimate the seroprevalence of SARS-CoV-2 antibodies throughout the pandemic. Together, the tools we develop further our understanding of serological responses to RNA viruses.
Language
English (en)
Chair and Committee
Daved Fremont
Recommended Citation
Smith, Brittany Kaye, "Development of computational and experimental approaches for RNA virus serology" (2023). Arts & Sciences Electronic Theses and Dissertations. 3196.
https://openscholarship.wustl.edu/art_sci_etds/3196