The ability to profile T-cell receptor (TCR) expression at the single-cell level allows researchers to understand how particular alpha-beta (αβ) chain pairings contribute to the antigen specificity of individual TCRs. High-throughput single-cell TCR profiling is ideal because it provides a comprehensive view of T-cell heterogeneity and plasticity. However, since immune cell populations are complex and heterogeneous, it is also critical to dissect the cell types present in the profiled population to get a full understanding of the immune response. Towards this end, whole transcriptome analysis (WTA) can be used to aid in the identification of the different cell types—and even subtypes—present within a sample. We have developed a protocol (Figure 1) compatible with the ICELL8 Human TCR a/b Profiling and ICELL8 cx Human TCR a/b Profiling workflows that allows T-cell receptor (TCR) clonotype determination and 5'-end differential expression analysis from the same cell.
- ICELL8 technology overview
- ICELL8 cx technical specifications
- ICELL8 technical specifications (original system)
- ICELL8 system vs plate-seq
- Enhancing biomarker discovery with SMART-Seq Pro kit and ICELL8 cx system
- ICELL8 cx system target enrichment for fusions
- ICELL8 cx system reagent formulation and dispense guidelines
- Improved detection of gene fusions, SNPs, and alternative splicing
- Full-length transcriptome analysis
- High-throughput single-cell ATAC-seq
- Protocol: High-throughput single-cell ATAC-Seq
- Single-cell identification with CellSelect Software
- Single-cell analysis elucidates cardiomyocyte differentiation from iPSCs
- Combined TCR profiling and 5’ DE in single cells
- Automated, high-throughput TCR profiling
- Sample preparation protocols
- Video resources
- System & software notices
High-throughput TCR profiling with 5'-end differential analysis of single cells
- High-throughput, high sensitivity clonotype and immune-cell-type identification from >1,000 cells in a single experiment
- Use of negative and positive controls in the experiment provides more confidence in data
- Simple GUI-based scTCR analyzer and mappa bioinformatics tools to speed up your data analysis
Gene detection in different cell lines
For the experiments described below, 5'-DE libraries were generated for T cells and peripheral blood mononuclear cells (PBMCs) dispensed with the ICELL8 Single-Cell System using the 5'-DE protocol developed for the ICELL8 Human TCR a/b Profiling workflow (Figure 1). This method processes a portion of the barcoded full-length cDNA generated from oligo-dT priming during the on-chip RT-PCR to create libraries for 5' DE using Nextera® tagmentation and amplification of the 5'-end barcodes to create a whole transcriptome library. The on-chip cDNA amplification produces enough product to process another portion for clonotyping analysis in parallel. The same cDNA can also be processed using two rounds of gene-specific PCR to amplify cDNA sequences corresponding to the variable regions of TCRa and TCRb transcripts as described in our TCR profiling technical note.
Following sequencing of the pooled single-cell 5’-DE libraries, we assessed the number of reads obtained per barcode (Figure 2). Taking advantage of the ICELL8 system’s ability to include controls, 15 negative controls containing all the reaction components except the sample were included as part of this experiment. This data was then used to set a confident read threshold to ensure high-quality data for the experimental samples. Pooled single-cell 5’-DE libraries after Nextera (Figure 1) were sequenced on a NextSeq® system to generate an average of 30K reads per cell. At an average sequencing depth of 30K reads per cell, we detected a median of ~1,150 genes in the PBMCs and T cells. Reads from the positive control RNA are well aligned with the reads for the T-cell samples and show good separation from the negative controls which are representative of background noise.
Assessment of cell types present within a PBMC sample
We next confirmed that we could distinguish various cell types present within a PBMC sample, using the sequencing data obtained from single-cell 5'-DE libraries. Principal component analyses were performed based on the top 500 most variable genes. Interestingly, the tSNE plot, based on the top 500 expressed genes (Figure 3), identified four main clusters. Notably, in the largest cluster, there is representation of both the PBMC and T-cell samples. This overlap is expected given that T cells can make up an estimated 70–80% of PBMC populations.
In humans, the majority of PBMCs are lymphocytes (approximately 70–90% of total) with additional populations of monocytes and dendritic cells (~10–30% and 5–20% of all PBMCs, respectively). The lymphocyte population is further comprised of T cells (70–85%), B cells (5–20%), and NK cells (5–20%). We used different cell-specific markers based on published data (Palmer et al. 2006), to identify various populations of cells present within the PBMC sample (Figures 4). Consistent with reporting in the literature, T cells made up the largest percentage of the PBMCs, and the location of this cluster overlaps with the negatively selected T cells that were also profiled in these experiments. Furthermore, dendritic cells were the rarest cell type within the PBMC sample. We also identified B cell, monocyte, and NK cell populations using cell-specific markers expressed in these cell types.
The human TCR a/b profiling workflow with 5' differential expression for the ICELL8 systems can be used to generate Illumina sequencing libraries from thousands of single immune cells for the determination of TCR αß pairing as well as cell type information. This method is a highly sensitive and economical approach to identify clonotypes and cell types by using 5'-DE and TCR-specific priming on the same cDNA. The combination of this chemistry and the automated ICELL8 Single-Cell System or ICELL8 cx Single-Cell System enables profiling of >1,000 cells showcasing the general utility and scalability of this approach for studies investigating paired TCR clonotype diversity. Furthermore, the ability to set up positive and negative controls generates greater confidence in the data, especially when working with complex samples.
Nextera libraries for 5'-end differential expression analysis were generated using the 5'-DE workflow as described in the ICELL8 Human TCR a/b Profiling User Manual. For a positive control, Control Jurkat Total RNA (Takara Bio) was used. Isolated PBMCs (AllCells) were thawed in RPMI and washed once in media before staining the cells. T cells were isolated from whole blood using the EasySep Direct Human T Cell Isolation Kit (STEMCELL Technologies). Isolation was performed per manufacturer's recommendation. For sequencing, the final library was diluted to 1.8 pM, including a 20% PhiX Control v3 (Illumina) spike-in for sequencing. Sequencing was performed on an Illumina NextSeq sequencer using the 150-cycle NextSeq 550 System mid-output kit (Illumina) with paired-end, 2 x 75 base pair reads.
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