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A New Way of Exploring Immunity: Linking Highly Multiplexed Antigen Recognition to Immune Repertoire and Phenotype

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A New Way of Exploring Immunity: Linking Highly Multiplexed Antigen Recognition to Immune Repertoire and Phenotype APPLICATION NOTE 10x Genomics A new way of exploring immunity: linking highly multiplexed antigen recognition to immune repertoire and phenotype Introduction T cells, key components of the adaptive immune system, Highlights are involved in the initiation of the immune response We demonstrate the power of the Single Cell Immune mediated by specific antigen recognition. T-cell receptors Profiling Solution with Feature Barcode technology to: (TCRs), located on the surface of T cells, recognize and bind • Assess the binding specificities of over 150,000 CD8+ specific antigenic peptides presented by a major histocom- T cells from 4 human donors across a highly multiplexed patibility complex (MHC) on the surface of other cells (1). panel of 44 distinct, specific peptide–MHC (pMHC) multimers TCRs are heterodimeric proteins, commonly comprising an alpha and a beta chain. The heterodimers recognize • Uncover data at single cell resolution for gene and cell peptide–MHC (pMHC) through their complementari- surface protein expression, TCR–pMHC binding speci- ty-determining region (CDR) loops: CDR1, CDR2, and ficity, and paired aß T-cell receptor (TCR) sequences CDR3, such that each paired TCR can bind to a particular • Generate highly multiplexed binding data from many set of pMHCs. Since each T cell typically expresses a sin- different pMHC multimers in a single experiment gle paired TCR, sufficient TCR sequence diversity is • Enable the potential to develop novel experimental and essential across an individual’s entire repertoire to bind analytical approaches the broad spectrum of antigens that may be encountered. • Help facilitate a greater understanding of how the adap- Somatic V(D)J recombination of the TCR loci during T-cell tive immune system responds to immune insults and development gives rise to an enormous potential space of contribute to the development of therapeutics TCR sequences, resulting in TCR diversity (2). The amino acid sequence of the paired TCR directly training data. A generalizable understanding of TCR rec- determines its binding specificity. However, we do not yet ognition will require more extensive data with orders of have a complete understanding of the factors underlying magnitude more pMHC diversity. the recognition of pMHC complexes by their cognate TCRs. A generalized and predictive understanding of this The 10x Genomics Chromium Single Cell Immune Profiling interaction would enable entirely new approaches in basic Solution with Feature Barcode technology is particularly immunological research and in clinical practice; this well suited to generating the data required to address this would encompass areas such as TCR-based diagnostic question. Single cell–based methods are the only way to methods and the rational design of immunotherapies. directly observe antigen binding to T cells, while simulta- neously sequencing the paired and recombined alpha and Recent work has shown that it is possible to identify beta TCR genes. This is achieved by generating Single Cell shared motifs within TCRs that are specific to particular 5' libraries and V(D)J enriched libraries, which provide pMHCs (3, 4). These studies identified TCR sequences that TCR sequences, in combination with Feature Barcode bind a limited number of pMHCs and use the shared technology, which uses highly multiplexed pMHC multi- motifs to classify previously unseen TCRs according to mer reagents, each carrying a pMHC and a distinct their predicted ability to bind one of the pMHCs in the molecular barcode, to identify binding specifities. training data. These initial studies are extremely promis- ing but are limited by the amount and diversity of 10xgenomics.com A new way of exploring immunity: linking highly multiplexed antigen recognition to immune repertoire and phenotype Here, we demonstrate the use of a highly multiplexed to explore and draw further conclusions about the mech- panel of 44 distinct, specific pMHC multimers (dCODE anisms of TCR–pMHC interaction. Furthermore, this Dextramer reagents) to assess the binding specificities experiment serves as the next step on the path toward the of over 150,000 CD8+ T cells from four human donors. even larger-scale experiments that will be necessary to This large dataset contains data at single cell resolution fully comprehend the rules of antigen recognition in the on gene expression, expression of eleven surface proteins adaptive immune system. In addition, the experiment (using TotalSeq™-C antibodies with Feature Barcode allowed us to enhance our understanding of experimen- technology), pMHC binding, and paired aß TCR tal design and computational analysis, both essential for sequences (Figure 1). single cell–based immunology research. From an initial analysis of the dataset, we have identified 64,755 cells and 15,214 distinct paired TCR Methods sequences with apparent specificity for at least one pMHC within the panel. This single dataset has the Cell samples potential to account for a significantly larger amount We obtained CD8+ T cells from four healthy donors from of knowledge regarding paired human TCR specificities AllCells and STEMCELL Technologies (Reference Table than has been generated to date. 1). Donors were chosen to ensure each HLA allele in the pMHC panel was present in at least one donor. Cytomega- Within our data, we observed TCRs with cognate antigens lovirus (CMV) and Epstein Barr Virus (EBV) serostatus that had been reported previously, while also identifying was known for Donors 3 and 4. entirely new TCR–pMHC interactions. In addition, we observed specific expanded non-naïve T-cell clones along Peptide–MHC multimers with Feature Barcode technology with more diverse binding in the naïve compartment. We used a panel of 44 dCODE™ Dextramer® reagents This rich and large dataset illustrates the power and scal- (Immudex, Reference Table 2) with antigenic peptides ability of the 10x Genomics Chromium Single Cell derived from different viruses (CMV, EBV, influenza, Immune Profiling Solution with Feature Barcode technol- HTLV, HPV and HIV) and known cancer antigens. ogy and presents an exciting opportunity for researchers Sample Prep cDNA Cleanup & QC TCR Target Enrichment d) SPRI Supernatant SPRI Pellet ’ CD8+ Cell Labeling Cell TotalSeq-C 7-AAD Dead Cell Fluorescent dCODE (cont T cells Antibodies Marker Antibodies Dextramer panel FACS Cells Sheath Single Cell 5’ Cell Surface Protein 5’ Gene Expression TCR Fluid Library Construction Library Construction Library Construction Leukocytes Live Cells Pan T Cells CD8+ T Cells Dextramer + T Cells Library Construction Library SSC-A SSC-A P5 Read 1 10x UMI TSO Feature Read 2N Sample P7 P5 Read 1 10x UMI TSO Insert Read 2Sample P7 P5 Read 1 10x UMI TSO V D J C Barcode Barcoding Index Barcode Index Barcode Dextramer CD4 T-Cell B-Cell (CD19) B-Cell Sequence Cell Sorting Cell Laser FSC-A 7AAD Monocytes CD8 T Cell CD8 T Cell (CD14,15,16) Sequencing Libraries Sequencing Libraries Sequencing Libraries GEM Generation & Barcoding Pool Collect RT Remove Oil Sequencing Cell Ranger for CellVDJ Ranger Cell Ranger Cell Ranger for Feature Barcode for Gene Expression for V(D)J 10x Barcoded Gel Beads Enzyme, Oil Labeled Cells Single Cell 10x Barcoded 10x Barcoded Analysis GEMs cDNA cDNA Library Construction Library cDNA Amplification Loupe Browser and Custom Analysis Figure 1. Experimental approach for generating high-throughput, highly multiplexed TCR–antigen binding data. CD8+ T cells from healthy human donors were labeled with fluorescent antibodies, TotalSeq™-C antibodies, and dCODE™ Dextramer® reagents. Dextramer® positive CD8+ T cells were sorted by flow cytometry and used as input for the 10x Genomics Chromium Single Cell Immune Profiling Solution with Feature Barcode technology. Libraries were prepared to characterize gene expression, cell surface protein expression, paired TCR sequences, and TCR–pMHC binding in each single cell. 2 10xgenomics.com 10x Genomics Each Dextramer® reagent included a distinct nucleic acid sorting, 7-AAD viability staining solution (BioLegend, barcode, along with a phycoerythrin (PE) fluorophore. Cat# 420403) was added at 1:200 dilution. See our Demon- strated Protocols CG000149 and CG000203 for full details. The panel also contained 6 dCODE Dextramer® reagents with irrelevant negative control peptides to assist in the Cell sorting detection of non-specific binding events. Cells were sorted using a MA900 Multi-Application Cell Just prior to labeling, 2 µl of each Dextramer® reagent was Sorter (Sony Biotechnology) with 100 µm flow cell chip. combined for a total volume of 100 µl. Cells were sorted into 55.9 µl Reaction Mix containing RT Reagent Mix and Poly dT RT primers in 8 wells of a chilled Surface marker antibodies with Feature Barcode 96-well plate. We targeted a cell yield of 9000 cells per well. technology Cells were gated using the Sony MA900 system software to We used a panel of eleven TotalSeq™-C antibodies (Bio- obtain single (FSH/BSC, FSW/BSC), live (7-AAD-), CD8+ cells Legend, Reference Table 3) that were chosen to enable whilst excluding CD14+/CD15+/CD16+/CD19+/CD4+ cells. discrimination between CD8+ T cell (CD8A+/CD3+) subpop- We then selected all Dextramer®-positive cells within the ulations, such as naïve (CD45RA+/CD45RO−/CCR7+), CD8+ T-cell population. After sorting, 5 µl water and a total effector (TEF, CD45RA+/CD45RO+/CCR7−), effector memory 12.4 µl of Additive A (2.4 µl) and RT Enzyme Mix B (10 µl) (TEM, CD45RA−/CD45RO+/CCR7−), exhausted (PD-1+), were added to each well to complete the Reaction Mix, central
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