A cost-effective protocol for single-cell RNA sequencing of human skin

Single-cell RNA sequencing (scRNAseq) and flow cytometry studies in skin are methodologically complex and costly, limiting their accessibility to researchers worldwide. Ideally, RNA and protein-based analyses should be performed on the same lesion to obtain more comprehensive data. However, current...

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Veröffentlicht in:Frontiers in immunology 2024-10, Vol.15, p.1393017
Hauptverfasser: Khoshbakht, Saba, Albayrak, Özgür, Tiryaki, Ergün, Ağcaoğlu, Orhan, Öktem, Ayşe, Pınar Sun, Gizem, Er Gülbezer, Elif, Seda Ertekin, Sümeyre, Boyvat, Ayşe, Vural, Atay, Vural, Seçil
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Sprache:eng
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Zusammenfassung:Single-cell RNA sequencing (scRNAseq) and flow cytometry studies in skin are methodologically complex and costly, limiting their accessibility to researchers worldwide. Ideally, RNA and protein-based analyses should be performed on the same lesion to obtain more comprehensive data. However, current protocols generally focus on either scRNAseq or flow cytometry of healthy skin. We present a novel label-free sample multiplexing strategy, building on the souporcell algorithm, which enables scRNAseq analysis of paired blood and skin samples. Additionally, we provide detailed instructions for simultaneous flow cytometry analysis from the same sample, with necessary adaptations for both healthy and inflamed skin specimens. This tissue multiplexing strategy mitigates technical batch effects and reduces costs by 2-4 times compared to existing protocols. We also demonstrate the effects of varying enzymatic incubation durations (1, 3, and 16 hours, with and without enzyme P) on flow cytometry outcomes. Comprehensive explanations of bioinformatic demultiplexing steps and a detailed step-by-step protocol of the entire experimental procedure are included. The protocol outlined in this article will make scRNAseq and flow cytometry analysis of skin samples more accessible to researchers, especially those new to these techniques.
ISSN:1664-3224
1664-3224
DOI:10.3389/fimmu.2024.1393017