Identifying gene combinations for targeting innate immune cells to enhance T cells activation [DNA]

Genetic engineering of hematopoietic cells ex-vivo opens new opportunities for programming immune cells and improving their functionality in response to illness and infections. Molecular methods for genetic manipulation are constantly improving, but it is challenging to reveal which genes are the most beneficial to target and whether multiple genes tackling can further improve the desired outcome. Current screening methods are limited by scale, the number of perturbations, and low content readouts. We developed a hybrid platform called “high multiplicity of perturbations and cellular indexing of transcriptomes and epitopes by sequencing (HMPCITE-seq)” that allows for finding combinations of genes to target and improves desired cellular functions. We used antigen-presenting cells and performed two genome-wide CRISPR screens to enhance the activation and co-stimulation programs and restrict the suppressive programs. Five genes were found in both screens including Cebpb gene. We showed that targeting Cebpb in antigen-presenting cells enhances the expression of costimulatory molecules, does not attenuate cell migration and phagocytosis, improves T cell proliferation, and restricts tumor growth. To find the genetic interactions between validated targeted genes, and identify gene combinations for targeting, we performed high-order perturbations of validated genes from the screens with single-cell RNA-seq readouts. We found that targeting both Cebpb and Med12 genes shows a better phenotype compared to the single KOs. Thus, the HMPCITE-seq platform, starting from a genome-wide screen, allows the finding of gene combinations to target as demonstrated by functional experiments in-vitro and in-vivo. CD86 screens - two repeats of the genome-wide CRISPR screen and one repeat of the secondary screen were performed. PDL1 screens - one repeat of the genome-wide CRISPR screen and two repeats of the secondary screen were performed. In each screen, cells were sorted into two bins: 10% cells with highest CD86/PDL1 level and 10% cells with lowest CD86/PDL1 level. Genomic DNA was extracted from the sorted cells and sequenced in order to verify the enrichment of the gRNAs.