Genome-wide CRISPR/Cas9 library screening identifies genes regulating the IFN signalling pathways.

Innate immunity is a non-specific host immune response against pathogen invasion. It exists widely in most of cells and is considered as the first line of defense against pathogen infection. Upon virus infection, the natural immune system is activated to generate immune response, thereby exerting the antiviral effect and effectively inhibiting the spread of virus in the body. With recent decades of research, people have found and identified the key regulatory factors of the natural immune response and the signal transduction. However the regulatory mechanisms of the factors are still unclear and need to be further explored. Our work used the CRISPR/Cas9 library to perform large-scale genome-wide, unbiased screening in immune cells, and discovered some novel genes involved in the regulation of type I IFN responses. First, we constructed a lentiviral vector encoding a fluorescence reporter (EGFP, enhanced green fluorescent protein) driven by the IFN-β promoter. Then, the reporter system was stably integrated into A549 cells. The stable clones were selected with puromycin and the capacity of EGFP-induction of the clones were examined by the infection of SeV. The clone with high homogeneity was chosen as the IFN-β-EGFP reporter cell line. The GeCKO library (#1000000048, Addgene) was amplified in Stbl3 bacteria and packaged into lentivirus in HEK293T cells. The reporter cells were transduced with lentivirus carrying the GeCKO library for 4 h, and the medium was replaced with fresh medium. Forty-eight hours post transduction, the cells were selected for 7 days with the treatment of puromycin. The GeCKO library-containing reporter cells were infected with SeV for 10 h and then subjected to flow cytometry sorting. Cells with drastically either enhanced or decreased fluorescence intensities of EGFP were collected for genomic DNA extraction. CRISPR library guides were amplified by PCR and then deep sequenced. After alignment, the differentially expressed sgRNAs were calculated and the corresponding genes are ranked.