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Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

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Dataset ID Description Technology Samples
EGAD00001005141 Illumina HiSeq 2000 1
EGAD00001005142 Illumina HiSeq 2000 1
EGAD00001005143 Illumina HiSeq 2000 1
EGAD00001005144 Illumina HiSeq 2000 1
EGAD00001005145 Illumina HiSeq 2000 1
EGAD00001005146 Illumina HiSeq 2000 1
EGAD00001005147 Illumina HiSeq 2000 1
EGAD00001005148 Illumina HiSeq 2000 1
EGAD00001005149 Illumina HiSeq 2000 1
EGAD00001005150 Illumina HiSeq 2000 1
EGAD00001005151 Illumina HiSeq 2000 1
EGAD00001005152 Illumina HiSeq 2000 1
EGAD00001005153 Illumina HiSeq 2000 1
EGAD00001005154 Illumina HiSeq 2000 1
EGAD00001005155 Illumina HiSeq 2000 1
EGAD00001005156 Illumina HiSeq 2000 1
EGAD00001005157 Illumina HiSeq 2000 1
EGAD00001005158 Illumina HiSeq 2000 1
EGAD00001005159 Illumina HiSeq 2000 1
EGAD00001005160 Illumina HiSeq 2000 1
EGAD00001005161 Illumina HiSeq 2000 1
EGAD00001005162 Illumina HiSeq 2000 1
EGAD00001005163 Illumina HiSeq 2000 1
EGAD00001005164 Illumina HiSeq 2000 1
EGAD00001005165 Illumina HiSeq 2000 1
EGAD00001005166 Illumina HiSeq 2000 1
EGAD00001005167 Illumina HiSeq 2000 1
EGAD00001005168 Illumina HiSeq 2000 1
EGAD00001005169 Illumina HiSeq 2000 1
EGAD00001005170 Illumina HiSeq 2000 1
EGAD00001005171 Illumina HiSeq 2000 1
EGAD00001005172 Illumina HiSeq 2000 1
EGAD00001005173 Illumina HiSeq 2000 1
EGAD00001005174 Illumina HiSeq 2000 1
EGAD00001005175 Illumina HiSeq 2000 1
EGAD00001005176 Illumina HiSeq 2000 1
EGAD00001005177 Illumina HiSeq 2000 1
EGAD00001005178 Illumina HiSeq 2000 1
EGAD00001005179 Illumina HiSeq 2000 1
EGAD00001005180 Illumina HiSeq 2000 1
Publications Citations
Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses.
Genome Biol 20: 2019 210
104