Defining and Manipulating B Cell Immunodominance Hierarchies to Elicit Broadly Neutralizing Antibody Responses against Influenza Virus
Name
nihms-1636713.pdf
Description
Accepted version
Size
3.28 MB
Format
Unknown
Checksum (MD5)
51803f6383dc361fceaf819cda8c1d42
Author(s)
Amitai, Assaf
Sangesland, Maya
Barnes, Ralston M
Rohrer, Daniel
Lonberg, Nils
Lingwood, Daniel
Chakraborty, Arup K
Date Issued
October 2020
Journal
Cell Systems
Publisher
Elsevier BV
Citation
Amitai, Assaf, Sangesland, Maya, Barnes, Ralston M, Rohrer, Daniel, Lonberg, Nils et al. 2020. "Defining and Manipulating B Cell Immunodominance Hierarchies to Elicit Broadly Neutralizing Antibody Responses against Influenza Virus." Cell Systems, 11 (6).
Version
Author's final manuscript
Abstract
© 2020 Elsevier Inc. The antibody repertoire possesses near-limitless diversity, enabling the adaptive immune system to accommodate essentially any antigen. However, this diversity explores the antigenic space unequally, allowing some pathogens like influenza virus to impose complex immunodominance hierarchies that distract antibody responses away from key sites of virus vulnerability. We developed a computational model of affinity maturation to map the patterns of immunodominance that evolve upon immunization with natural and engineered displays of hemagglutinin (HA), the influenza vaccine antigen. Based on this knowledge, we designed immunization protocols that subvert immune distraction and focus serum antibody responses upon a functionally conserved, but immunologically recessive, target of human broadly neutralizing antibodies. We tested in silico predictions by vaccinating transgenic mice in which antibody diversity was humanized to mirror clinically relevant humoral output. Collectively, our results demonstrate that complex patterns in antibody immunogenicity can be rationally defined and then manipulated to elicit engineered immunity.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Ragon Institute of MGH, MIT and Harvard
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Chemistry
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.CELS.2020.09.005
