LAUSR

T cells are able to recognize and eliminate a wide variety of immunologic threats while maintaining self-tolerance. Pathogen recognition and clearance is ensured by a process called V(D)J recombination, during which a T cell obtains a unique set of V, D and J gene segments for all the chains (α and β or γ and δ) that make up its T cell receptor (TCR). Each recombined TCR detects a specific disease-associated antigen peptide, which triggers the appropriate adaptive immune response. Understanding the relationship between TCR sequences (clonotypes) and T cell activation during disease pathogenesis and progression can assist in the development of next-generation therapeutics with more favorable and sustainable outcomes. Recent advances in single-cell sequencing allowed for simultaneous profiling of TCRs and full transcriptomes leading to the characterization of key T cell populations with pathogen recognition and disease clearance capabilities. Despite their success, these methods rely on microfluidics devices or plate-based protocols with limited sensitivity and throughput (1,000s-10,000s of cells) making the study of disease-relevant T cells time consuming and costly. To overcome these limitations, we have extended our split pool combinatorial barcoding technology to simultaneously characterize the TCRs alongside the full transcriptomes of up to 1 million T cells. As a proof of concept experiment, we applied our method to primary T cells from 8 healthy human donors to characterize their TCR diversity. From the 920,000 T cells assayed we were able to recover TCR sequences from at least one chain in 88% of T cells (807,000 cells) and detected hundreds of thousands of unique alpha and beta chains across all donors. Furthermore we found that most of these chains represent rare clonotypes found in 1 or 2 cells. Lastly, we performed transcriptome-based clustering analyses to identify all major T cell subsets and discovered donor and subset-specific hyper-expanded clonotypes that could help us reconstruct each donor’s recent history of infection. In summary, we report on the extension of our highly flexible and scalable combinatorial barcoding technology to allow researchers to profile up to 1 million of T cells in a single experiment and investigate their functional responses during infection, cancer, autoimmunity, or therapeutic interventions. Citation Format: Efthymia Papalexi, Grace Kim, Bryan Hariadi, Sarah Schroeder, Peter Matulich, Vuong Tran, Daniel Diaz, Charles Roco, Alexander Rosenberg. Using combinatorial barcoding to simultaneously profile the transcriptome and immune repertoire of 1 million T cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 248.