Humanized Immunoglobulin Mice: Models for HIV Vaccine Testing and Studying the Broadly Neutralizing Antibody Problem.

Published

Journal Article (Review)

A vaccine that can effectively prevent HIV-1 transmission remains paramount to ending the HIV pandemic, but to do so, will likely need to induce broadly neutralizing antibody (bnAb) responses. A major technical hurdle toward achieving this goal has been a shortage of animal models with the ability to systematically pinpoint roadblocks to bnAb induction and to rank vaccine strategies based on their ability to stimulate bnAb development. Over the past 6 years, immunoglobulin (Ig) knock-in (KI) technology has been leveraged to express bnAbs in mice, an approach that has enabled elucidation of various B-cell tolerance mechanisms limiting bnAb production and evaluation of strategies to circumvent such processes. From these studies, in conjunction with the wealth of information recently obtained regarding the evolutionary pathways and paratopes/epitopes of multiple bnAbs, it has become clear that the very features of bnAbs desired for their function will be problematic to elicit by traditional vaccine paradigms, necessitating more iterative testing of new vaccine concepts. To meet this need, novel bnAb KI models have now been engineered to express either inferred prerearranged V(D)J exons (or unrearranged germline V, D, or J segments that can be assembled into functional rearranged V(D)J exons) encoding predecessors of mature bnAbs. One encouraging approach that has materialized from studies using such newer models is sequential administration of immunogens designed to bind progressively more mature bnAb predecessors. In this review, insights into the regulation and induction of bnAbs based on the use of KI models will be discussed, as will new Ig KI approaches for higher-throughput production and/or altering expression of bnAbs in vivo, so as to further enable vaccine-guided bnAb induction studies.

Full Text

Duke Authors

Cited Authors

  • Verkoczy, L

Published Date

  • January 2017

Published In

Volume / Issue

  • 134 /

Start / End Page

  • 235 - 352

PubMed ID

  • 28413022

Pubmed Central ID

  • 28413022

Electronic International Standard Serial Number (EISSN)

  • 1557-8445

International Standard Serial Number (ISSN)

  • 0065-2776

Digital Object Identifier (DOI)

  • 10.1016/bs.ai.2017.01.004

Language

  • eng