Engineered receptor binding domain immunogens elicit pan-coronavirus neutralizing antibodies
Hauser, B. M.; Sangesland, M.; Lam, E. C.; Feldman, J.; Yousif, A. S.; Caradonna, T. M.; Balazs, A. B.; Lingwood, D.; Schmidt, A. G.
Show abstract
Effective countermeasures are needed against emerging coronaviruses of pandemic potential, similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Designing immunogens that elicit broadly neutralizing antibodies to conserved viral epitopes on the major surface glycoprotein, spike, such as the receptor binding domain (RBD) is one potential approach. Here, we report the generation of homotrimeric RBD immunogens from different sarbecoviruses using a stabilized, immune-silent trimerization tag. In mice, we find that a cocktail of these homotrimeric sarbecovirus RBDs elicits antibodies to conserved viral epitopes outside of the ACE2 receptor binding motif (RBM). Importantly, these responses neutralize all sarbecovirus components even in context of prior SARS-CoV-2 imprinting. We further show that a substantial fraction of the neutralizing antibodies elicited after vaccination in humans also engages non-RBM epitopes on the RBD. Collectively, our results suggest a strategy for eliciting broadly neutralizing responses leading to a pan-sarbecovirus vaccine. Author summaryImmunity to SARS-CoV-2 in the human population will be widespread due to natural infection and vaccination. However, another novel coronavirus will likely emerge in the future and may cause a subsequent pandemic. Humoral responses induced by SARS-CoV-2 infection and vaccination provide limited protection against even closely related coronaviruses. We show immunization with a cocktail of trimeric coronavirus receptor binding domains induces a neutralizing antibody response that is broadened to related coronaviruses with pandemic potential. Importantly, this broadening occurs in context of an initial imprinted SARS-CoV-2 spike immunization showing that preexisting immunity can be expanded to recognize other related coronaviruses. Our immunogens focused the serum antibody response to conserved epitopes on the receptor binding domain outside of the ACE2 receptor binding motif; this contrasts with current SARS-CoV-2 therapeutic antibodies, which predominantly target the receptor binding motif.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- The SARS-CoV-2 mRNA-1273 vaccine elicits more RBD-focused neutralization, but with broader antibody binding within the RBD 98%
- Robust immune responses after one dose of BNT162b2 mRNA vaccine dose in SARS-CoV-2 experienced individuals 97%
- A human antibody reveals a conserved site on beta-coronavirus spike proteins and confers protection against SARS-CoV-2 infection 97%
Similar papers in this journal
- Memory B cell Development in Response to mRNA SARS-CoV-2 and Nanoparticle Immunization in Mice 97%
- Conversion of monoclonal IgG to dimeric and secretory IgA restores neutralizing ability and prevents infection of Omicron lineages 97%
- Efficacy and breadth of adjuvanted SARS-CoV-2 receptor-binding domain nanoparticle vaccine in macaques 97%
Similar papers in this journal
- A Broadly Neutralizing Macaque Monoclonal Antibody Against the HIV-1 V3-Glycan Patch 97%
- Identification of a conserved neutralizing epitope present on spike proteins from all highly pathogenic coronaviruses 95%
- A Remarkable Genetic Shift in a Transmitted/Founder Virus Broadens Antibody Responses Against HIV-1 95%
Similar papers in this journal
- CD4-binding site immunogens elicit heterologous anti-HIV-1 neutralizing antibodies in transgenic and wildtype animals 97%
- Omicron BA.2 breakthrough infection enhances cross-neutralization of BA.2.12.1 and BA.4/BA.5 96%
- High-affinity, neutralizing antibodies to SARS-CoV-2 can be made in the absence of T follicular helper cells 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.