An Optimized Tissue Dissociation Protocol for Single-Cell RNA Sequencing Analysis of Fresh and Cultured Human Skin Biopsies

Abstract

We present an optimized dissociation protocol for preparing high-quality skin cell suspensions for in-depth single-cell RNA-sequencing (scRNA-seq) analysis of fresh and cultured human skin. Our protocol enabled the isolation of a consistently high number of highly viable skin cells from small freshly dissociated punch skin biopsies, which we use for scRNA-seq studies. We recapitulated not only the main cell populations of existing single-cell skin atlases, but also identified rare cell populations, such as mast cells. Furthermore, we effectively isolated highly viable single cells from ex vivo cultured skin biopsy fragments and generated a global single-cell map of the explanted human skin. The quality metrics of the generated scRNA-seq datasets were comparable between freshly dissociated and cultured skin. Overall, by enabling efficient cell isolation and comprehensive cell mapping, our skin dissociation-scRNA-seq workflow can greatly facilitate scRNA-seq discoveries across diverse human skin pathologies and ex vivo skin explant experimentations.

Revisiting the significance of keratin expression in complex epithelia

“…2A) reveals that large numbers of epidermal keratinocytes partition to a KRT14 high /KRT10 low subgroup (53% of the pool), consistent with a progenitor character, or to a KRT14 low /KRT10 high subgroup (37% of the pool), consistent with a differentiating character. The observation that KRT14 high /KRT10 low represent a larger group of cells in the sc-seq data is not surprising and could be due to methodological ease of obtaining single cells from the basal rather than the suprabasal differentiating compartment of epidermis (Kim et al 2020;Burja et al 2022). However, we note that the dataset contains a large fraction of cells expressing late-stage differentiation markers (such as KRT2; Fig.…”

A reference single-cell map of freshly dissociated human synovium in inflammatory arthritis with an optimized dissociation protocol for prospective synovial biopsy collection

“…40,000 - 50,000 reads/cell) at Functional Genomics Center Zurich, the University of Zurich and ETH Zurich, Switzerland. The sequencing of pooled scRNA-seq libraries was performed in multiple rounds; two library pools ( Table 1 ) combined synovial and skin scRNA-seq samples, the latter being part of the skin protocol optimization project 24 .…”

“…Additionally, one of the libraries from sample 26 was resequenced and combined with the corresponding sample data to obtain a similar sequencing depth across libraries and samples. Pooling synovial and skin scRNA-seq 24 samples led to a limited barcode swapping 31 with subsequent detection of a minor keratinocyte cluster in the synovial cell dataset. The swapped molecules and empty droplets were removed at the beginning of the analysis using the R package DropletUtils 32,33 .…”

“…The single cell omics study group at the Center of Experimental Rheumatology, University Hospital Zurich, Switzerland 24,25 investigates the pathobiology of human tissues affected by autoimmune diseases, with first research phase focusing on protocol optimization and establishment of tissue atlases. We have recently published an optimized dissociation protocol and scRNA-seq map of the fresh and cultured human skin 24 . In this paper, we present an optimized protocol for efficient dissociation of prospectively collected fresh synovial biopsies from patients with inflammatory arthritis.…”

Methanol fixation is the method of choice for droplet-based single-cell transcriptomics of neural cells

“…Despite the popularity of scRNA-seq methods, there are still several technical challenges unsolved. For instance, the dissociation of the cells from a tissue and the obtention of a good cell suspension, necessary for scRNA-seq, is highly tissue specific and may require the use of different strategies including enzymatic digestion, mechanical disgregation, fluorescence-activated cell sorting (FACS), and other technologies 8–12 . As a result, the preparation of samples for scRNA-seq can take several hours and makes it difficult to couple sample preparation with the acquisition of the transcriptomes of thousands of cells.…”