Abstract
Multiplexed single-cell CRISPR screening has accelerated the systematic dissection of biological discoveries; however, the efficiency of CRISPR-based gene knockout has inherent limitations. Here, we present DoNick-seq, an advanced method for facilitating gene knockout and reducing off-target activity. We re-engineered two popular plasmid constructs suitable for use in pooled CRISPR screening of the single-cell transcriptome. We then used DoNick-seq to probe mTORC1 regulators and obtain genomic perturbation and transcriptome profiles from the same cell. Thus, DoNick-seq enabled us to simultaneously evaluate multiple gene interactions and the effect of amino acid depletion. By analyzing more than 20,000 cells from two cell lines, DoNick-seq efficiently identified gene targets, cell numbers, and cellular profiles. Our data also revealed the characteristics of mTORC1 negative and positive regulators, thereby shedding new insights into the mechanisms regulating cell growth and inhibition. We demonstrate that mTORC1 hyperactivation exhausts cellular free amino acids via increased proliferation ability. Furthermore, DoNick-seq identified the gene C19orf53, which mediates excessive cell proliferation, resulting in metabolic imbalance, and greatly enhances oxidative stress in response to toxins. Thus, our findings suggest that DoNick-seq facilitates high-throughput functional dissection of complex cellular responses at the single-cell level and increases the accuracy of CRISPR single-cell transcriptomics.
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All data generated or analyzed during this study are included in this published article (and its supplementary information files).
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This work was financially supported by the Innovation Team of Key areas of the Ministry of Science and Technology, Science and Technology Leadership Program of Hunan Province (2019RS3021); the Key R&D Program of Hunan Province (2019NK2161 and 2019NK2171); the Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process (ISA2020212); and the Natural Science Foundation of Guangxi (2020JJA130108).
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Yulong Tang, Yulong Yin and Bie Tan conceived and designed the experiments; Yulong Tang, Simeng Liao and Gugang Liu performed the experiments and analyzed, Yulong Tang, and Xiangfeng Kong hand data curation; Yulong Tang wrote original draft preparation. Xia Xiong, Hongnan Liu, Fengna Li and Zhiliang Tan provide administrative support and revision suggestion. All authors have read and agreed to the published version of the manuscript.
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Supplementary information
Supplemental Fig. 1.
The sequence of the DoNick-seq-PX462 vector. (a) gRNA sequences with restriction sites; (b) CBh promoter with restriction sites; (c) GFP-barcode (20 bp)-bGH polyA with restriction sites. (d) Comparison of the Gene Ontology enrichment between two cell lines with two gRNA pairs or a single gRNA. (PPTX 206 kb)
Supplemental Fig. 2.
Performance statistics across all DoNick-seq experiments. (a) HEK293T cells in complete medium. (b) HEK293T cells in arginine-free medium. (c) HEK293T cells in methionine-free medium. (d) HIEC cells in complete medium. (PPTX 703 kb)
Supplemental Fig. 3.
(a) Cluster dendrogram of all barcoded cells in different media and cell lines. The first principal component provided the best separation, and genes in the 99th percentile of loading contributions were selected for DoNick-seq. Principal component analysis of the median gene expression aggregated across cells expressing barcodes targeting the same gene between (b) complete and arginine-free medium, (c) complete medium and methionine-free medium, and (d) between the HEK293T and HIEC cell lines. (e) mTOR regulator gene signatures and their absolute loading values for the first principal component. Principal component analysis of median gene expression aggregated across cells expressing barcodes targeting the same gene for (f) HEK293T cells in complete medium, (g) HEK293T cells in arginine-free medium, (h) HEK293T cells in methionine-free medium, and (i) HIEC cells in complete medium. (PPTX 960 kb)
Supplemental Fig. 4.
Enriched gene ontology (GO) functions and KEGG pathways for the first principal component genes. (a) HEK293T cells in complete medium. (b) HEK293T cells in arginine-free medium. (c) HEK293T cells in methionine-free medium. (d) HIEC cells in complete medium. (e) Comparison of cells grown in complete and arginine-free medium. (f) Comparison of cells grown in complete and methionine-free medium. (g) Comparison of HEK293T and HIEC cells. (PPTX 640 kb)
Table 1.
Primer sequences for sgRNA cloning and validation. (PDF 110 kb)
Table 2.
The first principal component genes for all groups. (PDF 322 kb)
Table 3.
Significant changes in gene expression profiles of among the groups. (PDF 34 kb)
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Tang, Y., Liao, S., Liu, G. et al. Advanced single-cell pooled CRISPR screening identifies C19orf53 required for cell proliferation based on mTORC1 regulators. Cell Biol Toxicol 38, 43–68 (2022). https://doi.org/10.1007/s10565-021-09586-0
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DOI: https://doi.org/10.1007/s10565-021-09586-0