Genetic delivery of computationally designed protein nanoparticle immunogens

Abstract

mRNA vaccines and computationally designed protein nanoparticle vaccines were both clinically derisked and licensed for the first time during the COVID-19 pandemic. These vaccine modalities have complementary immunological benefits that provide strong motivation for their combination. In this dissertation, I developed, characterized, and evaluated “computationally designed mRNA-launched protein nanoparticle immunogens” as an integrated vaccine platform. First, I used SARS-CoV-2 as a model system to demonstrate the superiority of our vaccine platform as compared with mimics of state-of-the-art COVID-19 vaccines. Next, I used the SARS-CoV-1, BtKY72, and Omicron BA.5 sarbecoviruses to evaluate whether our vaccine platform was amenable to multivalent formulations. Finally, I investigated the relationships between the displayed antigen, nanoparticle scaffold, in vitro secretion, and in vivo immunogenicity. In doing so, I uncovered fundamental rules governing the secretion of protein nanoparticle immunogens that will undoubtedly guide future developments of our vaccine platform. Collectively, I demonstrated how computational protein design can be a useful tool for genetic vaccination strategies by optimizing the immunogenicity of the encoded protein.