Antibody attributes that predict the neutralization and effector function of polyclonal responses to SARS-CoV-2

Harini Natarajan, Shiwei Xu, Andrew R. Crowley, Savannah E. Butler, Joshua A. Weiner, Evan M. Bloch, Kirsten Littlefield, Sarah E. Benner, Ruchee Shrestha, Olivia Ajayi, Wendy Wieland-Alter, David Sullivan, Shmuel Shoham, Thomas C. Quinn, Arturo Casadevall, Andrew Pekosz, Andrew D. Redd, Aaron A.R. Tobian, Ruth I. Connor, Peter F. WrightMargaret E. Ackerman

Research output: Contribution to journalArticlepeer-review

Abstract

Background: While antibodies can provide significant protection from SARS-CoV-2 infection and disease sequelae, the specific attributes of the humoral response that contribute to immunity are incompletely defined. Methods: We employ machine learning to relate characteristics of the polyclonal antibody response raised by natural infection to diverse antibody effector functions and neutralization potency with the goal of generating both accurate predictions of each activity based on antibody response profiles as well as insights into antibody mechanisms of action. Results: To this end, antibody-mediated phagocytosis, cytotoxicity, complement deposition, and neutralization were accurately predicted from biophysical antibody profiles in both discovery and validation cohorts. These models identified SARS-CoV-2-specific IgM as a key predictor of neutralization activity whose mechanistic relevance was supported experimentally by depletion. Conclusions: Validated models of how different aspects of the humoral response relate to antiviral antibody activities suggest desirable attributes to recapitulate by vaccination or other antibody-based interventions.

Original languageEnglish (US)
Article number7
JournalBMC Immunology
Volume23
Issue number1
DOIs
StatePublished - Dec 2022

Keywords

  • Effector function
  • IgA
  • IgG
  • IgM
  • Neutralization
  • SARS-CoV-2

ASJC Scopus subject areas

  • Immunology

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