The overarching theme of this HIVRAD proposal is to utilize the SHIV/rhesus macaque (RM) model to understand the virus-antibody coevolutionary pathways leading to the development of broadly neutralizing antibodies (bNAbs), and then to translate what we learn into the design of an effective HIV-1 vaccine. SHIVs that have been generated in the Shaw laboratory have been pre-selected as good candidates for V1V2 or V3 glycan bNAb induction; they will enable systematic and rigorous characterization of the evolutionary pathways to bNAb breadth taken by different Envs in RMs and humans. We will characterize what is common, versus what is distinctive, in bNAb development and HIV-1 Envelope (Env) evolution between human and rhesus macaques (RMs), as well as between different RMs infected by the same SHIV. Our preliminary work shows that in at least some cases, we can expect evolutionary pathways to coincide. In Core C, we will use bioinformatics and analytical and statistical tools to map the extent to which Env and antibody (Ab) co- evolutionary pathways are shared between hosts in early infection and throughout the course of SHIV infections as neutralization breadth emerges. We will begin by testing for patterns of immunologically relevant mutations in both the Ab lineages and Env quasispecies as they co-evolve. We will help in down-selection of specific Envs and Abs from large sequence sets to provide a rational means of reagent selection for cloning and immunological characterization. We will provide statistical comparisons of immune response data, linking experimental immunological data to both Env and antibody sequence data, and perform signature analysis to resolve which mutations are critical in terms of changing the immunological phenotype of a protein (e.g. antibody sensitivity). This will provide data needed to make an informed selection regarding which Env candidates to take forward as vaccine immunogens. We will use computational methods to help resolve the B cell clonal activities that are contributing to polyclonal serological responses. We will help design polyvalent sets of Env vaccines for a lineage-based approach. Finally, we will provide statistical support throughout the project, including comparisons of vaccine group outcomes, and, if protection is observed, we will help define the correlates of immune protection. We will deposit sequences with linked meta-data to relevant databases upon publication, and make novel code written for this project publicly available.
