Abstract 5662: Deep-mining the antibody repertoires of transgenic mouse models with high-throughput single cell BCR and whole transcriptome sequencing

Abstract Transgenic mouse models are excellent tools to model human antibody response against antigens or disease of choice, given their ability to undergo diversification, in vivo affinity maturation, clonal selection and clonal expansion in their natural immune environment. Current antibody discovery methods lack the scale required to fully screen the antibody repertoire of transgenic mouse models to uncover maximum desirable antibody hits per discovery campaign. Here, we demonstrate our novel combinatorial barcoding approach to enable high-throughput single cell BCR and whole transcriptome profiling of transgenic mouse samples with unprecedented sensitivity, scalability, and flexibility. As a proof of concept, we profiled over 1 million cells from multiple transgenic mice that were either naive or immunized with antigens of interest to obtain hundreds of thousands of paired BCR clonotypes. Using the whole transcriptome data, we detected all B cell subpopulations including plasma cells at single cell resolution. We then used the paired heavy and light chain BCR data to detect productive chains in the majority of B cells revealing both unique and expanded clonotypes. In the expanded clonotype pool we found specific patterns of VDJ utilization and amino acid motifs compared to the naive pool. This method paves the way for high throughput screening of antibody repertoires from transgenic mice to allow for deep mining of repertoires for antibody discovery and therapeutic outcomes. Citation Format: Ajay Sapre, Alec Salvino, Guillermo Gallareta-Olivares, Efi Papalexi, Jose Jacob, Ashwath Kumar, Charles Roco, Alexander Rosenberg. Deep-mining the antibody repertoires of transgenic mouse models with high-throughput single cell BCR and whole transcriptome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5662.