Engineering mRNA antigen for enhanced surface display and immunogenicity

The success of COVID mRNA vaccines has spurred the development of other mRNA vaccines. Although most of mRNA antigens in clinical trials are immunodominant, there is a large category of viral antigens that are immunodominant on viral particles but elicit poor antibody response when expressed alone via lipid nanoparticle (LNP) mRNAs. As antibody producing immune cells primarily recognize antigens in extracellular space, I hypothesize that antibody response mediated by mRNA antigen is associated with antigen expression level on cell surface and can be improved by replacing and enhancing its cell surface translocation (CST) signal. To test this hypothesis, we want to ask 1) what are the deterministic signals to translocate membrane proteins or any proteins to cell surface; 2) whether these CST signals can be grafted to mRNA antigens to improve their surface expression; 3) how will these signals alter immune response to mRNA antigens. To answer these questions, this proposal aims to 1) establish a modular cloning platform for rapid assembly and optimization of mRNA antigens recombined with various CST sequences from human proteome; 2) screen and identify the recombined mRNA antigens that show enhanced expression on cell surface; 3) characterize in vivo immune response to mRNA antigens identified in the screen; 4) build a practical model to map and predict the intricate relationship between mRNA antigen sequence, CST signal strength, and immunogenicity. The significance of this proposal includes 1) it is the first study to systemically compile and screen CST sequences for mRNA antigen optimization; 2) it enables rapid modular cloning, one-step assembly, parental GFP dropout selection and generalizable optimization of mRNA antigens and can be repurposed to display any protein of interest to cell surface; 3) it explores fundamental principles that determine which CST signals best improve surface expression and immunogenicity of a given mRNA antigen.