Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies
- Harvard University, United States
- Massachusetts Institute of Technology, United States
- Stanford University, United States
- École Normale Supérieure, France
Abstract
Over the past two decades, several broadly neutralizing antibodies (bnAbs) that confer protection against diverse influenza strains have been isolated. Structural and biochemical characterization of these bnAbs has provided molecular insight into how they bind distinct antigens. However, our understanding of the evolutionary pathways leading to bnAbs, and thus how best to elicit them, remains limited. Here, we measure equilibrium dissociation constants of combinatorially complete mutational libraries for two naturally isolated influenza bnAbs (CR9114, 16 heavy-chain mutations; CR6261, 11 heavy-chain mutations), reconstructing all possible evolutionary intermediates back to the unmutated germline sequences. We find that these two libraries exhibit strikingly different patterns of breadth: while many variants of CR6261 display moderate affinity to diverse antigens, those of CR9114 display appreciable affinity only in specific, nested combinations. By examining the extensive pairwise and higher-order epistasis between mutations, we find key sites with strong synergistic interactions that are highly similar across antigens for CR6261 and different for CR9114. Together, these features of the binding affinity landscapes strongly favor sequential acquisition of affinity to diverse antigens for CR9114, while the acquisition of breadth to more similar antigens for CR6261 is less constrained. These results, if generalizable to other bnAbs, may explain the molecular basis for the widespread observation that sequential exposure favors greater breadth, and such mechanistic insight will be essential for predicting and eliciting broadly protective immune responses.
Data availability
Data and code used for this study are available at https://github.com/klawrence26/bnab-landscapes. CR9114 data are also available in an interactive data browser at https://yodabrowser.netlify.app/yoda_browser/.FASTQ files from high-throughput sequencing have been deposited in the NCBI BioProject database with accession number PRJNA741613, and will be publicly released upon acceptance.
Article and author information
Author details
Aleksandra M Walczak
Funding
Howard Hughes Medical Institute (Hanna H. Gray Postdoctoral Fellowship)
- Angela M Phillips
International Human Frontier Science Program Organization
- Thomas Dupic
The NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard (1764269)
- Katherine R Lawrence
Hertz Foundation (Graduate Fellowship Award)
- Katherine R Lawrence
National Science Foundation (Graduate Research Fellowship Program)
- Katherine R Lawrence
National Science Foundation (Graduate Research Fellowship Program)
- Milo S Johnson
National Science Foundation (Graduate Research Fellowship Program)
- Jeffrey Chang
European Research Council (COG 724208)
- Thierry Mora
- Aleksandra M Walczak
National Institutes of Health (GM104239)
- Michael M Desai
National Science Foundation (PHY-1914916)
- Michael M Desai
Stanford University (Stanford Science Fellowship)
- Ivana Cvijovic
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Phillips et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,293
- views
-
- 571
- downloads
-
- 57
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 57
- citations for umbrella DOI https://doi.org/10.7554/eLife.71393
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Binding affinity landscapes constrain the evolution of broadly neutralizing anti-influenza antibodies
eLife 10:e71393.
https://doi.org/10.7554/eLife.71393
