Search

Abstract Low affinity is common for germline B cell receptors (BCR) seeding development of broadly neutralizing antibodies (bnAbs) that engage hypervariable viruses, including HIV. Antibody affinity selection is also non-homogenizing, insuring the survival of low affinity B cell clones. To explore whether this provides a natural window for expanding human B cell lineages against conserved vaccine targets, we deploy transgenic mice mimicking human antibody diversity and somatic hypermutation (SHM) and immunize with simple monomeric HIV glycoprotein envelope immunogens. We report an immunization regimen that focuses B cell memory upon the conserved CD4 binding site (CD4bs) through both conventional affinity maturation and reproducible expansion of low affinity BCR clones with public patterns in SHM. In the latter instance, SHM facilitates target acquisition by decreasing binding strength. This suggests that permissive B cell selection enables the discovery of antibody epitopes, in this case an HIV bnAb site.

The ligand-binding surface of the B cell receptor (BCR) is formed by encoded and non-encoded antigen complementarity determining regions (CDRs). Genetically reproducible or ‘public’ antibodies can arise when the encoded CDRs play deterministic roles in antigen recognition, notably within human broadly neutralizing antibodies against HIV and influenza virus. We sought to exploit this by engineering virus-like-particle (VLP) vaccines that harbor multivalent affinity against gene-encoded moieties of the BCR antigen binding site. As proof of concept, we deployed a library of RNA bacteriophage VLPs displaying random peptides to identify a multivalent antigen that selectively triggered germline BCRs using the human VH gene IGVH1-2*02. This VLP selectively primed IGHV1-2*02 BCRs that were present within a highly diversified germline antibody repertoire within humanized mice. Our approach thus provides methodology to generate antigens that engage specific BCR configurations of interest, in the absence of structure-based information.