| Literature DB >> 33732238 |
Ahmed S Fahad1, Morgan R Timm2, Bharat Madan1, Katherine E Burgomaster3, Kimberly A Dowd3, Erica Normandin2, Matías F Gutiérrez-González1, Joseph M Pennington1, Matheus Oliveira De Souza1, Amy R Henry2, Farida Laboune2, Lingshu Wang2, David R Ambrozak2, Ingelise J Gordon2, Daniel C Douek2, Julie E Ledgerwood2, Barney S Graham2, Leda R Castilho4, Theodore C Pierson3, John R Mascola2, Brandon J DeKosky1,5.
Abstract
The re-emergence of Zika virus (ZIKV) caused widespread infections that were linked to Guillain-Barré syndrome in adults and congenital malformation in fetuses, and epidemiological data suggest that ZIKV infection can induce protective antibody responses. A more detailed understanding of anti-ZIKV antibody responses may lead to enhanced antibody discovery and improved vaccine designs against ZIKV and related flaviviruses. Here, we applied recently-invented library-scale antibody screening technologies to determine comprehensive functional molecular and genetic profiles of naturally elicited human anti-ZIKV antibodies in three convalescent individuals. We leveraged natively paired antibody yeast display and NGS to predict antibody cross-reactivities and coarse-grain antibody affinities, to perform in-depth immune profiling of IgM, IgG, and IgA antibody repertoires in peripheral blood, and to reveal virus maturation state-dependent antibody interactions. Repertoire-scale comparison of ZIKV VLP-specific and non-specific antibodies in the same individuals also showed that mean antibody somatic hypermutation levels were substantially influenced by donor-intrinsic characteristics. These data provide insights into antiviral antibody responses to ZIKV disease and outline systems-level strategies to track human antibody immune responses to emergent viral infections.Entities:
Keywords: B cells; Zika virus (ZIKV); antiviral antibodies; next-generation sequencing; yeast display
Year: 2021 PMID: 33732238 PMCID: PMC7959826 DOI: 10.3389/fimmu.2021.615102
Source DB: PubMed Journal: Front Immunol ISSN: 1664-3224 Impact factor: 7.561