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

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number100600
JournalCell Reports Methods
Volume3
Issue number10
DOIs
StatePublished - Oct 23 2023

Keywords

  • CP: Immunology
  • CP: Systems biology
  • adaptive immunity
  • antigen receptors
  • mutant KRAS
  • repertoire sequencing

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Genetics
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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