PROJECT SUMMARY The purpose of this Project is to apply advanced multi-omics techniques to comprehensively analyze humoral immune responses to promising HIV vaccine immunogens. Our mission is to advance vaccine development by extracting as much information as possible from each immunization trial to best inform the optimal design, composition and delivery of a cohesive immunogen matrix that reliably induces broad, protective HIV immunity. We have devised three Specific Aims which outline the steps necessary to accomplish these goals. Successful completion of these Aims will require indispensable contributions from every component of the MOVE Consortium. In Aim 1, we will deeply characterize the immune response to priming immunogens designed to activate bnAb precursors of one or more specificities (Project 1). While many aspects of this Aim are designed to evaluate the extent to which immunogens are working as designed, equally important is identifying specific genetic and structural features which need improvement during subsequent rounds of refinement and re- evaluation (Structural Proteomics Core). In Aim 2, we will evaluate the human immunogenicity of candidate priming immunogens by isolating immunogen-specific mAbs from HIV-naive humans. This is a critically important aspect of our vaccine development process, as these mAbs are most accurate representation, short of a human clinical trial, of the humoral immune response that will be triggered in actual human vaccine recipients. These mAbs will also be used to create humanized animal models for more thorough vaccine evaluation (Animal Models Core). In Aim 3, we will use our single cell immune multi-omics platform to rapidly evaluate the immune response to sequential vaccine immunogens in near real-time, using the resulting B cell profiles of specificity and function to inform selection of optimal candidates for subsequent boosts. Seamless data sharing between MOVE components and sophisticated tools for visualization and analysis (Data Management & Bioinformatics Core) will allow these analyses to occur within the normal time interval between sequential immunizations. We can then dynamically adjust the parameters of each immunization experiment to maximize our likelihood of success by focusing our experimental resources on the most promising immunogen designs.