Abstract

Single cell RNA-seq (scRNA-seq) has recently been shown to provide a powerful method for the analysis of transcriptional heterogeneity in Chinese hamster ovary (CHO) cells. A potential drawback of current scRNA-seq platforms is that the cost can limit the complexity of experimental design and therefore the utility of the approach. In this manuscript, we report the use of oligonucleotide barcoding to perform multiplexed CHO cell scRNA-seq to study the impact of tunicamycin (TM), an inducer of the unfolded protein response (UPR). For this experiment, we treated a CHO-K1 GS cell line with 10g/ml tunicamycin and acquired samples at 1, 2, 4 and 8 hr post-treatment as well as a non-treated TM-control. We transfected cells with sample-specific polyadenylated ssDNA oligonucleotide barcodes enabling us to pool all cells for scRNA-seq. The sample from which each cell originated was subsequently determined by the oligonucleotide barcode sequence. Visualisation of the transcriptome data in a reduced dimensional space confirmed that cells were not only separable by sample but were also distributed according to time post-treatment. These data were subsequently utilised to perform weighted gene co-expression analysis (WGCNA) and uncovered groups of genes associated with TM treatment. For example, the expression of one group of coexpressed genes was found to increase over the time course and were enriched for biological processes associated with ER stress. The use of multiplexed single cell RNA-seq has the potential to reduce the cost associated with higher sample numbers and avoid batch effects for future studies of CHO cell biology. HighlightsO_LIPolyadenylated ssDNA oligonucleotide labelling is a viable strategy for multiplexed CHO cell scRNA-seq analysis. C_LIO_LITo demonstrate the effectiveness of the method we conducted an experiment to study the CHO cell response to tunicamycin treatment. C_LIO_LIscRNA-seq was carried out on an untreated control and at 4 time points post tunicamycin treatment. Cells from each sample were transfected with a unique oligonucleotide barcode and pooled for single cell transcriptomics. C_LIO_LIEach sample was demultiplexed post-sequencing and gene expression profiles of > 5,300 cells were obtained across the experiment. Following dimensionality reduction and visualisation, the cells were distributed according to sample identity. C_LIO_LIAnalysis of the resulting data enabled improved understanding of the transcriptional response to tunicamycin treatment. Three gene coexpression modules were found to be correlated with the tunicamycin time course. Gene set enrichment analysis revealed the over representation of genes related to biological processes associated with ER stress, and protein misfolding in one of these groups of coexpressed genes. C_LIO_LIFurther use of this approach will enable the CHO cell biology community to perform increasingly complex single cell experiments in a cost-effective manner. C_LI