Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses

Sahana Jayaraman; Janelle M Montagne; Thomas R Nirschl; Emily Marcisak; Jeanette Johnson; Amanda Huff; Meng-Hsuan Hsiao; Julie Nauroth; Thatcher Heumann; Jelani C Zarif; Elizabeth M Jaffee; Nilo Azad; Elana J Fertig; Neeha Zaidi; H Benjamin Larman

doi:10.1016/j.crmeth.2023.100600

Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses

Cell Rep Methods. 2023 Oct 23;3(10):100600. doi: 10.1016/j.crmeth.2023.100600. Epub 2023 Sep 29.

Authors

Affiliations

¹ Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
² Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Bloomberg Kimmel Immunology Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Division of Quantitative Sciences, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
³ Pathobiology Graduate Program, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Bloomberg∼Kimmel Institute for Cancer Immunotherapy, Johns Hopkins Medicine Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD 21205, USA.
⁴ Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
⁵ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Immunology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁶ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Bloomberg Kimmel Immunology Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁷ Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
⁸ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁹ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Division of Hematology Oncology, Vanderbilt-Ingram Comprehensive Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
¹⁰ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Bloomberg∼Kimmel Institute for Cancer Immunotherapy, Johns Hopkins Medicine Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD 21205, USA.
¹¹ Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Division of Quantitative Sciences, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD 21218, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
¹² Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA. Electronic address: hlarman1@jhmi.edu.

Abstract

Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4⁺ and CD8⁺ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.

Keywords: CP: Immunology; CP: Systems biology; adaptive immunity; antigen receptors; mutant KRAS; repertoire sequencing.

MeSH terms

CD8-Positive T-Lymphocytes
Humans
Leukocytes, Mononuclear*
Receptors, Antigen, T-Cell / genetics
Receptors, Antigen, T-Cell, alpha-beta / genetics
Reverse Transcription*

Substances

Receptors, Antigen, T-Cell
Receptors, Antigen, T-Cell, alpha-beta

Abstract

MeSH terms

Substances

Grants and funding