Journal: Scientific Data

Article Title: Comprehensive genome-scale CRISPR knockout screening of CHO cells

doi: 10.1038/s41597-025-04438-6

Figure Lengend Snippet: Schematic illustration of a non-viral, genome-scale CRISPR screening platform in Chinese hamster ovary (CHO) cells. ( a ) Plasmid library construction. CHO genome-wide CRISPR guide RNA (gRNA) oligonucleotides were designed and synthesized. Recombinase mediated cassette exchange (RMCE) donor plasmid library was then constructed by cloning gRNA oligos into a backbone plasmid that contained a promoter-less puromycin resistance (PuroR) gene and gRNA scaffold, flanked by attB and mutant attB recombination sites. The plasmid library was verified using next-generation sequencing (NGS) analysis. ( b ) Workflow of cell library and knockout (KO) library development. The CHO-K1 host and recombinant cell-based master cell lines (MCLs) were established through CRISPR/Cas9-mediated site-specific integration (SSI) of the landing pad (LP) plasmid donor, which contained mCherry and hygromycin resistance (HygR) gene flanked by attP and mutant attP recombination sites. The host and recombinant cell libraries were generated through the Bxb1-att recombination system and puromycin selection. Promoter-trapping ensures the expression of a single gRNA per cell. The host and recombinant KO libraries were then generated through transient Cas9 expression and blasticidin semi-selection. The distribution of gRNAs in the pooled cell libraries and KO libraries was confirmed using NGS analysis. The KO libraries were also analyzed after long-term cultivation. ( c ) Functional genomic screens. Phenotypes of interest in the KO library can be enriched through reporter-based fluorescence-activated cell sorting (FACS) or pool selection under selective pressure. Highly productive recombinant cell populations were sorted in this study. The distribution of gRNAs was confirmed using NGS analysis. The screening hits are candidate targets for KO cell engineering.

Article Snippet: CRISPR screening data analysis is available at https://sourceforge.net/p/mageck/wiki/Home/#usage and http://pinapl-py.ucsd.edu .

Techniques: CRISPR, Plasmid Preparation, Genome Wide, Synthesized, Construct, Cloning, Mutagenesis, Next-Generation Sequencing, Knock-Out, Recombinant, Generated, Selection, Expressing, Functional Assay, Fluorescence, FACS

Journal: Scientific Data

Article Title: Comprehensive genome-scale CRISPR knockout screening of CHO cells

doi: 10.1038/s41597-025-04438-6

Figure Lengend Snippet: The development process of the cell and KO libraries using a non-viral genome-scale CRISPR screening platform. Entire profiles of ( a ) viability and ( b ) cell growth (VCD; viable cell density) during the generation of the cell (red solid lines) and KO (blue solid lines) libraries in both CHO-K1 host and recombinant cells. Arrows indicate the transfection of RMCE (red) and Cas9 (blue). Shaded areas denote periods of chemical treatment for cell library enrichment (red, puromycin) and KO library enrichment (blue, blasticidin). The pEGFP-c1 expression vector was used as the transfection control (green lines), while chemically untreated cells served as non-enriched controls (dotted lines). ( c ) The percentage of mCherry-negative populations in the CHO-K1 host (blue line) and recombinant cells (red line) during cell library development with and without puromycin selection. Dotted line indicates the threshold required to maintain 500 × gRNA coverage. The mCherry negativity in enriched populations indicated successful implementation of the genome-scale plasmid library into cells. ( d ) Bar plot showing the transfection efficiency of Cas9 in CHO-K1 host cells and recombinant cells as measured through 2 A peptide-linked reporter expression.

Article Snippet: CRISPR screening data analysis is available at https://sourceforge.net/p/mageck/wiki/Home/#usage and http://pinapl-py.ucsd.edu .

Techniques: CRISPR, Recombinant, Transfection, Expressing, Plasmid Preparation, Control, Selection

Journal: Nature Communications

Article Title: Epigenetic regulation of CD38/CD48 by KDM6A mediates NK cell response in multiple myeloma

doi: 10.1038/s41467-024-45561-z

Figure Lengend Snippet: a Schematic of genome-wide CRISPR screen in a MM cell line treated with Dara and human primary NK cells. b Top genes for enriched (red) and depleted (blue) sgRNAs from the screen. Candidate genes were plotted based on the beta score, computed by MaGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout) of sgRNAs normalized to control. c Schematic of the CRISPR assay to identify essential genes for Dara-NK-mediated ADCC. d TCGA RNA-seq data from 36 human cancer types were analyzed to obtain genes positively correlated with cytolytic (CYT) activity. The number of overlapped genes between our top candidates and CYT activity-related genes was quantified in each cancer type. e Heatmap showing the partitioning of the clusters of genes based on Pearson’s correlation coefficient values of CRISPR screen hits with CYT activity using pan-cancer TCGA data. Figure 1c was created with BioRender.com.

Article Snippet: CRISPR screen sequencing data, RNA-seq, ChIP-seq and ATAC-seq data generated in this study are deposited in the National Institute of Health Gene Expression Omnibus (GEO) database ( GSE228771 ). are provided with this paper.

Techniques: Genome Wide, CRISPR, Knock-Out, Control, RNA Sequencing, Activity Assay

Journal: Nature Communications

Article Title: Epigenetic regulation of CD38/CD48 by KDM6A mediates NK cell response in multiple myeloma

doi: 10.1038/s41467-024-45561-z

Figure Lengend Snippet: a Schematic of the second genome-wide CRISPR screen in a MM cell line. Five percent of cells with the lowest expression of CD38 were collected for next-generation sequencing. b Top genes for enriched (red) and depleted (blue) gRNAs from the screen. c Venn diagram showing the overlapped enriched genes between the two CRISPR screens. d Western blot of CD38 protein levels in MM cell lines with CRISPR-mediated knock (KO) of KDM6A . e q-RT-PCR for CD38 mRNA in MM cell lines transfected with indicated sgRNAs. Data were normalized against GAPDH (mean ± SEM, n = 3 biologically independent experiments). *** p < 0.001; **** p < 0.0001 (two-sided student’s t test). f Representa t ive flow cytometry analysis of CD38 expression in H929 single clones transfected with indicated sgRNAs. g Western blotting of CD38 protein levels after ectopic overexpression of KDM6A in KDM6A -KO H929 cells. OE, overexpression. Three independent experiments were performed and similar results were obtained. h Representative flow cytometry analysis of CD38 expression level after ectopic overexpression of KDM6A in KDM6A -KO H929 cells. Source data are provided as a Source Data file.

Article Snippet: CRISPR screen sequencing data, RNA-seq, ChIP-seq and ATAC-seq data generated in this study are deposited in the National Institute of Health Gene Expression Omnibus (GEO) database ( GSE228771 ). are provided with this paper.

Techniques: Genome Wide, CRISPR, Expressing, Next-Generation Sequencing, Western Blot, Reverse Transcription Polymerase Chain Reaction, Transfection, Flow Cytometry, Clone Assay, Over Expression

Journal: Nature Communications

Article Title: Epigenetic regulation of CD38/CD48 by KDM6A mediates NK cell response in multiple myeloma

doi: 10.1038/s41467-024-45561-z

Figure Lengend Snippet: a Normalized lysis percentage of KDM6A WT or KO H929 cells after co-culture with primary NK cells at different E:T ratios with IL-2 for 6 hours (mean ± SEM, n = 3 biologically independent experiments). * p < 0.05; ** p < 0.01; *** p < 0.001 (two-sided student’s t test). b Intracellular IFN-γ s t aining of primary NK cells co-cultured with KDM6A WT or KO H929 cells with IL-2 for 6 hours (mean ± SEM, n = 3 biologically independent experiments). ** p < 0.01 (two-sided student’s t test). c Volcano plot of differentially expressed genes in KDM6A KO H929 cells compared with WT cells assessed by RNA-seq. d Venn diagram showing the overlapped enriched genes between the CRISPR screen and RNA-seq. e , Representative flow cytometry analysis of CD48 expression in H929 transfected with indicated sgRNAs. f q-RT-PCR for CD48 mRNA in H929 cells transfected with indicated sgRNAs. Data were normalized against GAPDH (mean ± SEM, n = 3 biologically independent experiments). **** p < 0.0001 (two-sided student’s t test). g , ChIP-seq density profiles for H3K27me3 on t he CD48 gene in KDM6A WT and KO H929 cells. h , H3K27me3 ChIP-qPCR analysis at the CD48 gene in KDM6A WT and KO H929 cells (mean ± SEM, n = 3 biologically independent experiments). *** p < 0.001 (two-sided student’s t test). i , ATAC-seq density profiles at the CD48 promoter region in KDM6A WT and KO H929 cells. j q-RT-PCR for CD48 mRNA in newly diagnosed (N/D) ( n = 7) and Dara-resistant (R/R) ( n = 12) patient samples. Data were normalized against GAPDH (mean ± SEM). * p < 0.05 (two-sided student’s t test). Source data are provided as a Source Data file.

Article Snippet: CRISPR screen sequencing data, RNA-seq, ChIP-seq and ATAC-seq data generated in this study are deposited in the National Institute of Health Gene Expression Omnibus (GEO) database ( GSE228771 ). are provided with this paper.

Techniques: Lysis, Co-Culture Assay, Cell Culture, RNA Sequencing, CRISPR, Flow Cytometry, Expressing, Transfection, Reverse Transcription Polymerase Chain Reaction, ChIP-sequencing, ChIP-qPCR