Discovering Selected Antibodies From Deep-Sequenced Phage-Display Antibody Library Using ATTILA

Abstract

Phage display is a powerful technique to select high-affinity antibodies for different purposes, including biopharmaceuticals. Next-generation sequencing (NGS) presented itself as a robust solution, making it possible to assess billions of sequences of the variable domains from selected sublibraries. Handling this process, a central difficulty is to find the selected clones. Here, we present the AutomaTed Tool For Immunoglobulin Analysis (ATTILA), a new tool to analyze and find the enriched variable domains throughout a biopanning experiment. The ATTILA is a workflow that combines publicly available tools and in-house programs and scripts to find the fold-change frequency of deeply sequenced amplicons generated from selected VH and VL domains. We analyzed the same human Fab library NGS data using ATTILA in 5 different experiments, as well as on 2 biopanning experiments regarding performance, accuracy, and output. These analyses proved to be suitable to assess library variability and to list the more enriched variable domains, as ATTILA provides a report with the amino acid sequence of each identified domain, along with its complementarity-determining regions (CDRs), germline classification, and fold change. Finally, the methods employed here demonstrated a suitable manner to combine amplicon generation and NGS data analysis to discover new monoclonal antibodies (mAbs).

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

“…Several simple metrics have been used in the past, such as frequency, or the abundance of an antibody sequence found after selection, which assumes that variants with the highest affinities become most prevalent during the sorting process ( Ravn et al 2010 , 2013 , D’Angelo et al 2014 , Hu et al 2015 , Lopez et al 2017 , Barreto et al 2019 , Ferrara et al 2020 ). Another common metric used to select antibody variants is the enrichment ratio (ER), which is the frequency of the variant in the output of the selection divided by the frequency of the same variant in the original library ( Maranhão et al 2020 , Kelil et al 2021 ). However, both methods are limited because they disregard the vast majority of the information in the deep sequencing datasets and solely rely on the frequencies of each antibody variant of interest.…”

New Anti-Flavivirus Fusion Loop Human Antibodies with Zika Virus-Neutralizing Potential

“…The amplicons of VH and VL were sequenced using the Miseq system, with 2 × 250 bp readout from the Illumina platform. The quality of the reads was verified with the FASTQC program, and the sequencing results were analyzed with the automated immunoglobulin analysis tool, ATTILA, developed by the molecular immunology group at the University of Brasília [ 48 ]. In this tool, V(D)J signatures were determined, and the frequency variation of each sequence (fold-change) during selection was evaluated.…”

New broad-spectrum anti-Flavivirus human antibodies with Zika virus-neutralizing potential

“…The amplicons of VH and VL were sequenced using the Miseq system, with a 2×250 bp readout from the Illumina platform. The quality of the reads was verified with the FASTQC program, and the sequencing results were analysed with the automated immunoglobulin analysis tool, ATTILA, developed by the Molecular Immunology group at the University of Brasília [20]. In this tool, V(D)J signatures were determined, and the frequency variation of each sequence (fold-change) during selection was evaluated.…”