Tailoring the resolution of single-cell RNA sequencing for primary cytotoxic T cells

Kristiyan Kanev (), Patrick Roelli, Ming Wu, Christine Wurmser, Mauro Delorenzi, Michael W. Pfaffl and Dietmar Zehn ()
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Kristiyan Kanev: Technical University of Munich
Patrick Roelli: Technical University of Munich
Ming Wu: Technical University of Munich
Christine Wurmser: Technical University of Munich
Mauro Delorenzi: University of Lausanne
Michael W. Pfaffl: Technical University of Munich
Dietmar Zehn: Technical University of Munich

Nature Communications, 2021, vol. 12, issue 1, 1-11

Abstract: Abstract Single-cell RNA sequencing in principle offers unique opportunities to improve the efficacy of contemporary T-cell based immunotherapy against cancer. The use of high-quality single-cell data will aid our incomplete understanding of molecular programs determining the differentiation and functional heterogeneity of cytotoxic T lymphocytes (CTLs), allowing for optimal therapeutic design. So far, a major obstacle to high depth single-cell analysis of CTLs is the minute amount of RNA available, leading to low capturing efficacy. Here, to overcome this, we tailor a droplet-based approach for high-throughput analysis (tDrop-seq) and a plate-based method for high-performance in-depth CTL analysis (tSCRB-seq). The latter gives, on average, a 15-fold higher number of captured transcripts per gene compared to droplet-based technologies. The improved dynamic range of gene detection gives tSCRB-seq an edge in resolution sensitive downstream applications such as graded high confidence gene expression measurements and cluster characterization. We demonstrate the power of tSCRB-seq by revealing the subpopulation-specific expression of co-inhibitory and co-stimulatory receptor targets of key importance for immunotherapy.

Date: 2021
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DOI: 10.1038/s41467-020-20751-7

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