Eliciting HIV-1-specific broadly neutralizing antibodies (bNAbs) remains a challenge for vaccine development, and the potential of passively delivered bNAbs for prophylaxis and therapeutics is being explored. We used neutralization data from four large virus panels to comprehensively map viral signatures associated with bNAb sensitivity, including amino acids, hypervariable region characteristics, and clade effects across four different classes of bNAbs. The bNAb signatures defined for the variable loop 2 (V2) epitope region of HIV-1 Env were then employed to inform immunogen design in a proof-of-concept exploration of signature-based epitope targeted (SET) vaccines. V2 bNAb signature-guided mutations were introduced into Env 459C to create a trivalent vaccine, and immunization of guinea pigs with V2-SET vaccines resulted in increased breadth of NAb responses compared with Env 459C alone. These data demonstrate that bNAb signatures can be utilized to engineer HIV-1 Env vaccine immunogens capable of eliciting antibody responses with greater neutralization breadth.
Keywords: HIV-1; V2-apex antibodies; broadly neutralizing antibodies; hypervariable regions; machine learning; signature analysis; vaccine design.
Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.