Significance: Many current vaccines seek to elicit protective antibody responses along precise evolutionary pathways, and a fundamental understanding of genetic, structural, and biophysical antibody development features will accelerate guided vaccine strategies. Here we determine the structural and biophysical features associated with improvement or fitness of an antibody targeting the HIV fusion peptide, a known vulnerable site on HIV-1. We show that around 1% of possible antibody mutations can improve virus recognition. Beneficial mutations were often clustered far from the binding interface and altered protein structure and dynamics, leading to reduced antibody thermal stability and higher binding affinity to the HIV envelope trimer. These data quantify the genetic and biophysical landscape for improvement of a vaccine-elicted antibody and provide a rational framework to guide HIV vaccines.

The monoclonal antibody CIS43 targets the Plasmodium falciparum circumsporozoite protein (PfCSP) and prevents malaria infection in humans for up to 9 mo following a single intravenous administration. To enhance the potency and clinical utility of CIS43, we used iterative site-saturation mutagenesis and DNA shuffling to screen precise gene-variant yeast display libraries for improved PfCSP antigen recognition. We identified several mutations that improved recognition, predominately in framework regions, and combined these to produce a panel of antibody variants. The most improved antibody, CIS43_Var10, had three mutations and showed approximately sixfold enhanced protective potency in vivo compared to CIS43. Co-crystal and cryo-electron microscopy structures of CIS43_Var10 with the peptide epitope or with PfCSP, respectively, revealed functional roles for each of these mutations. The unbiased site-directed mutagenesis and screening pipeline described here represent a powerful approach to enhance protective potency and to enable broader clinical use of antimalarial antibodies.

In vitro antibody evolution is a powerful technique for improving monoclonal antibodies. This can be achieved by generating artificial diversity on an antibody template, which can be done using different in vitro diversification techniques. The resulting libraries consist of single- or multimutant variants of a defined antibody template that are screened for improved function using antibody display. Here, we describe a bioinformatic protocol for tracking synthetic antibody variants using high-throughput sequencing across screening rounds, enabling efficient high-throughput interpretation of the function of individual mutations in sorted antibody display libraries. The protocol enables a user to achieve precision analysis and interpretation of clonal antibody variant data for discovery purposes, especially for high-throughput antibody engineering or optimization against target antigens.

Antibody functional screening studies and next-generation sequencing require careful processing and interpretation of sequence data for optimal results. Here, we provide a detailed protocol for the functional analysis of antibody gene data, including antibody repertoire quantification and functional mapping of high-throughput screening data based on enrichment ratio values, which are a simple way to determine the enrichment of each sequenced antibody after sorting a display library against desired antigens. This protocol enables a user to apply a set of simple yet powerful bioinformatic tools for high-throughput analysis and interpretation of antibody data that is especially well suited for display library screening and for antibody discovery applications.

A rapid and effective method to identify disease-specific antibodies from clinical patients is important for understanding autoimmune diseases and for the development of effective disease therapies. In neuromyelitis optica (NMO), the identification of antibodies targeting the aquaporin-4 (AQP4) membrane protein traditionally involves the labor-intensive and time-consuming process of single B-cell sorting, followed by antibody cloning, expression, purification, and analysis for anti-AQP4 activity. To accelerate patient-specific antibody discovery, we compared two unique approaches for screening anti-AQP4 antibodies from yeast antibody surface display libraries. Our first approach, cell-based biopanning, has strong advantages for its cell-based display of native membrane-bound AQP4 antigens and is inexpensive and simple to perform. Our second approach, FACS screening using solubilized AQP4 antigens, permits real-time population analysis and precision sorting for specific antibody binding parameters. We found that both cell-based biopanning and FACS screening were effective for the enrichment of AQP4-binding clones. These screening techniques will enable library-scale functional interrogation of large natively paired antibody libraries for comprehensive analysis of anti-AQP4 antibodies in clinical samples and for robust therapeutic discovery campaigns.