Functional Profiling of Antibody Immune Repertoires in Convalescent Zika Virus Disease Patients

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.

Immortalization and Functional Screening of Natively Paired Human T Cell Receptor Repertoires

“…As expected, small numbers of TCRβ sequences were shared among the repertories ( Fig. 2b ), each validated with a read count ≥2 to minimize the inclusion of amplification and sequencing errors in the final dataset 31–35 . Other recent studies included single-read TCRα:β sequences for repertoire-scale bioinformatic analyses 28 , and the corresponding outputs from our data are reported in the supplement to enable direct comparisons ( Supplementary Table 3 .…”

“…We previously described an emulsion-based technology for single-cell analysis of natively paired antibody heavy and light chains [30][31][32][33] , integrated with a cloning approach that allowed functional expression and screening of physically linked antibody heavy:light cDNAs [34][35][36] . Here, we modified these immune receptor display technologies to implement high-throughput screening and functional expression of natively paired TCRα:β sequences obtained from >10 6 individual T cells per sample.…”

Antibody screening at reduced pH enables preferential selection of potently neutralizing antibodies targeting SARS‐CoV‐2

“…We analyzed the plasmid DNAs encoded by yeast libraries across all sort conditions using 2 × 300 bp Illumina MiSeq NGS analysis to quantitatively track the prevalence of each antibody clone in the libraries across screening rounds 9,13,29,32,50 . We followed each clone in the libraries by CDR‐H3 amino acid sequences throughout the screening at all three pH values, calculating an ER for each clone (see Section 2).…”

“…Further rounds of PCR were used to add unique sample barcodes and Illumina adapters for analysis on a 2 × 300 bp MiSeq platform. Raw Illumina sequencing data in FASTQ format were quality filtered and analyzed as described previously 9,13,29,32 . Clone enrichment across each round of sorting was tracked based on CDR‐H3 amino acid sequences using enrichment ratios (ERs), which were calculated by determining the prevalence of a CDR‐H3 amino acid sequence in each round of sorting divided by its prevalence in the Fab‐expressing, or VL+, reference library 29,32 .…”

“… 9 , 13 , 29 , 32 Clone enrichment across each round of sorting was tracked based on CDR‐H3 amino acid sequences using enrichment ratios (ERs), which were calculated by determining the prevalence of a CDR‐H3 amino acid sequence in each round of sorting divided by its prevalence in the Fab‐expressing, or VL+, reference library. 29 , 32 We used both Round 2 and Round 3 data for selecting antibody clones, as previously reported. 13 , 29 , 32 …”