4.2 Article

Diverse antiviral IgG effector activities are predicted by unique biophysical antibody features

Journal

RETROVIROLOGY
Volume 18, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12977-021-00579-9

Keywords

IgG; Antibody; Effector function; HIV; Vaccine

Categories

Funding

  1. Bill and Melinda Gates Foundation's Collaboration for AIDS Vaccine Discovery (CAVD) [OPP1032817, OPP1114729, OPP1032144, OPP1033109]
  2. NIAID [R01 AI131975, P01 AI120756]

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This study conducted various Fc-mediated effector function assays and biophysical antibody profiling assays on samples from HIV-1 infected and vaccinated subjects. The results showed that biophysical antibody profiles could predict diverse IgG effector functions accurately, and unique antibody features were identified as primary contributing factors to these effector functions. The study provided a clearer understanding of the diversity and complexity of effector function assays, which could inform future HIV-1 treatment and vaccination strategies.
Background The critical role of antibody Fc-mediated effector functions in immune defense has been widely reported in various viral infections. These effector functions confer cellular responses through engagement with innate immune cells. The precise mechanism(s) by which immunoglobulin G (IgG) Fc domain and cognate receptors may afford protection are poorly understood, however, in the context of HIV/SHIV infections. Many different in vitro assays have been developed and utilized to measure effector functions, but the extent to which these assays capture distinct antibody activities has not been fully elucidated. Results In this study, six Fc-mediated effector function assays and two biophysical antibody profiling assays were performed on a common set of samples from HIV-1 infected and vaccinated subjects. Biophysical antibody profiles supported robust prediction of diverse IgG effector functions across distinct Fc-mediated effector function assays. While a number of assays showed correlated activities, supervised machine learning models indicated unique antibody features as primary contributing factors to the associated effector functions. Additional experiments established the mechanistic relevance of relationships discovered using this unbiased approach. Conclusions In sum, this study provides better resolution on the diversity and complexity of effector function assays, offering a clearer perspective into this family of antibody mechanisms of action to inform future HIV-1 treatment and vaccination strategies.

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