Human γδ T cell identification from single-cell RNA sequencing datasets by modular TCR expression
- 1. Institute of Systems Immunology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- 2. Hamburg Center for Translational Immunology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
Description
Accurately identifying γδ T cells in large single-cell RNA sequencing (scRNA-seq) datasets without additional single-cell γδ T cell receptor sequencing (sc-γδTCR-seq) or CITE-seq (cellular indexing of transcriptomes and epitopes sequencing) data remains challenging. In this study, we developed a TCR module scoring strategy for human γδ T cell identification (i.e. based on modular gene expression of constant and variable TRA/TRB and TRD genes). We evaluated our method using 5' scRNA-seq datasets comprising both sc-αβTCR-seq and sc-γδTCR-seq as references and demonstrated that it can identify γδ T cells in scRNA-seq datasets with high sensitivity and accuracy. We observed a stable performance of this strategy across datasets from different tissues and different subtypes of γδ T cells. Thus, we propose this analysis method, based on TCR gene module scores, as a standardized tool for identifying and reanalyzing γδ T cells from 5'-end scRNA-seq datasets.
Methods
Before sample collection, healthy donors provided written informed consent and the study was approved by the local ethics committee Hamburger Ärztekammer (PV5982).
Whole EDTA blood from 4 healthy female donors was collected. Peripheral blood mononuclear cells (PBMCs) were isolated via a density gradient centrifugation (Biocoll; Biochrom) and stored a nitrogen tank in 90% fetal calf serum and 10% DMSO (6–10 × 106 cells/mL). PBMCs were thawed and stained with Live/Death-PacO, Live/Death-APC-Cy7, and aCD3-BV650 (BioLegend). For each sample, live CD3+ T cells were sorted with the BD Aria Fusion, and 15,000 cells were then used for the preparation of single-cell libraries. The Chromium Next GEM Single Cell 5′ Library and Gel Bead Kit v1.1 (10x Genomics) were used. Upon completion of reverse transcription but prior to fragmentation, the single-cell barcoded full-length complementary DNA was divided into three parts. Each part was used separately to prepare the libraries for scRNA, sc-αβTCR, and sc-γδTCR. For the sc-αβTCR and scRNA libraries, we followed the manufacturer's instructions. For the sc-γδTCR libraries, we used custom primers to enrich γδTCR transcripts. During the first target enrichment, we used primers RV_TRG1: ATCCCAGAATCGTGTTGCTC and RV_TRD1: CCCACTGGGAGAGATGACAA. For the second target enrichment, we used RV_TRG2: GGGGAAACATCTGCATCAAG and RV_TRD2: GACAAAAACGGATGGTTTGG as custom primers. We sequenced each library, including scRNA, sc-αβTCR, and sc-γδTCR, on the Illumina NovaSeq6000.
The scRNA-seq reads were aligned to the human reference genome GRCh38-2020-A, and feature-barcode matrices were generated via the Cell Ranger pipeline (version 4.0.0; 10x Genomics).
Files
hd_rna_abtcr_gdtcr_SONG.zip
Files
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Additional details
Identifiers
Dates
- Accepted
-
2023-11-24
References
- Song Z, Henze L, Casar C, Schwinge D, Schramm C, Fuss J, Tan L, Prinz I. Human γδ T cell identification from single-cell RNA sequencing datasets by modular TCR expression. J Leukoc Biol. 2023 Nov 24;114(6):630-638. doi: 10.1093/jleuko/qiad069. PMID: 37437101.