GSM8722820: Unstimulated Donor 122 Replicate 1; Homo sapiens; OTHER
RNA for TCR immunoprofiling was isolated from whole cultures or highly purified MART-1-specific CD8+ T cells sorted by. flow cytometry from two combined replicates. For unsorted samples, 2 × 10⁶ cells were harvested from cultures stimulated with 100 nM MART-1-IST, MART-1-peptide-loaded mDCs, or left untreated, and RNA was isolated using the RNeasy Plus Micro Kit (Qiagen, Cat# 74034).  For sorted MART-1-specific CD8+ T cells, 1 × 10⁷ cells from two wells with similar tetramer percentages were collected, washed, and resuspended in FACS buffer. Cells were incubated with FcR Blocking Reagent (1:50 dilution) for 10 minutes at room temperature, followed by a 15-minute incubation with MART-1-tetramer-BV421 (1:350 dilution). After washing and filtering through a cell strainer cap, approximately 2 million CD8+ MART-1-tetramer-positive cells were sorted using a BD FACSAria™ II sorter, and RNA was immediately isolated using the RNeasy Plus Micro Kit. DriverMap™ Multiplex PCR technology uses gene-specific primers which significantly reduce the level of non-specific binding and primer-dimer amplification products, and are designed to target only TCR/BCR isoforms. Unique Molecular Identifiers (UMIs) facilitate accurate quantitation of the copy number of cDNA or DNA molecules in amplification steps, as well as detection of low abundance clonotypes and correction of amplification biases and sequencing errors. Dual-index amplicon labeling strategy minimizes index hopping during NGS allowing for comprehensive readouts. Full profiles of the antigen-recognition CDR3 region enable assessment of CDR3 length distribution, V(D)J segment usage, isotype composition for BCRs, somatic mutations, and similar characteristics with immune receptor profiling software such as MiXCR (MiLabs). All RNA samples were shipped on dry ice to Cellecta, Inc. (Mountain View, CA) for TCR immunoprofiling analysis using the Cellecta DriverMap Adaptive Immune Receptor (AIR) system. DriverMap AIR sequencing reads quality were assessed using FastQC v0.11.9.