Prolonged evolution of the human B cell response to SARS-CoV-2 infection
Open accessAbstract
A comprehensive understanding of the kinetics and evolution of the human B cell response to SARS-CoV-2 infection will facilitate the development of next-generation vaccines and therapies. Here, we longitudinally profiled this response in mild and severe COVID-19 patients over a period of five months. Serum neutralizing antibody (nAb) responses waned rapidly but spike (S)-specific IgG + memory B cells (MBCs) remained stable or increased over time. Analysis of 1,213 monoclonal antibodies (mAbs) isolated from S-specific MBCs revealed a primarily de novo response that displayed increased somatic hypermutation, binding affinity, and neutralization potency over time, providing evidence for prolonged antibody affinity maturation. B cell immunodominance hierarchies were similar across donor repertoires and remained relatively stable as the immune response progressed. Cross-reactive B cell populations, likely re-called from prior endemic beta-coronavirus exposures, comprised a small but stable fraction of the repertoires and did not contribute to the neutralizing response. The neutralizing antibody response was dominated by public clonotypes that displayed significantly reduced activity against SARS-CoV-2 variants emerging in Brazil and South Africa that harbor mutations at positions 501, 484 and 417 in the S protein. Overall, the results provide insight into the dynamics, durability, and functional properties of the human B cell response to SARS-CoV-2 infection and have implications for the design of immunogens that preferentially stimulate protective B cell responses.
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The memory B cell compartment accumulates mutations and undergoes clonal evolution over the initial six months after infection.
“The memory B cell compartment accumulates mutations and undergoes clonal evolution over the initial six months after infection4,9,21,22.”
From Naturally enhanced neutralizing breadth against SARS-CoV-2 one year after infection (2021) · cites this paper as [22]
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- Authors
- Sakharkar, M., Rappazzo, C. G., Wieland-Alter, W. F., Hsieh, C.-L., Wrapp, D., Esterman, E. S., Kaku, C. I., Wec, A. Z., Geoghegan, J. C., McLellan, J. S., Connor, R. I., Wright, P. F., & Walker, L. M.
- Affiliations
- Adimab (United States) (US)
- Division of Infectious Disease and International Health, Dartmouth Hitchcock Medical Center, Lebanon, NH 03756, USA.
- The University of Texas at Austin (US)
- Dartmouth–Hitchcock Medical Center (US)
- Corresponding author
- Sakharkar, Mrunal
- Rappazzo, C. Garrett
- Walker, Laura M.
- ORCID
- Venue
- Science Immunology
- Published
- 2021-02-12
- Volume
- 6
- Issue
- 56
- ISSN
- 2470-9468 (ISSN-L)
- PMC
- PMC8128290
- OpenAlex
- W3129651179
- Cited by
- 174
- References
- 42
- Citations by year
- 2026: 4 · 2025: 14 · 2024: 21 · 2023: 36 · 2022: 53 · 2021: 46
- FWCI
- 12.34
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science Immunology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Bill and Melinda 406 Gates Foundation (OPP1104756)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- SARS-CoV-2, COVID-19 pandemic, B cell response, memory B cells, neutralizing antibodies, affinity maturation, somatic hypermutation, monoclonal antibodies, immunodominance hierarchy, betacoronaviruses, antibody waning, vaccine design
- MeSH terms
- COVID-19, SARS-CoV-2, Adult, Aged, Antibodies, Monoclonal, Antibodies, Viral, B-Lymphocytes, Binding Sites, Cross Reactions, Female, Humans, Immunologic Memory, Longitudinal Studies, Male, Middle Aged, Cohort Studies, Antibodies, Neutralizing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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