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<t>CRISPR</t> knockout screen identifies common host factors required for rVSV-CCHFV pseudovirus infection. ( A ). Bubble plot of genes significantly enriched in a genome-wide CRISPR knockout screen in wild-type A549 (A549-WT) cells challenged with rVSV-CCHFV pseudovirus. The virus-resistant A549-WT cells were collected for analysis, and genes were ranked according to the MAGeCK score. ( B ) KEGG (Kyoto Encyclopedia of Genes and Genomes) and Go (Gene Ontology) analysis of top 100 enriched genes. ( C and D ) Flow cytometry ( C ) and fluorescence imaging ( D ) analysis of A549-WT and A549-BAT (B3GAT3, AXL, and TIM-1 triple-knockout cells) infected with rVSV-CCHFV (MOI 3). The percentage of GFP-positive cells was analyzed at indicated time points using flow cytometer, and images were taken using fluorescence microscope at 24 h post-infection (hpi). Scale bar, 400 µm. Two-way ANOVA with Sidak’s multiple-comparison test. **** P < 0.0001.
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FIGURE 1. <t>CRISPR</t> activation screen identifies novel regulators of PD-L1 expression. (A) Schematic setup of the screen. MelJuSo melanoma cells stably expressing MS2-p65-HSF1 were transduced with a pooled gRNA library containing dCAS9 and sorted by FACS for cells displaying high levels of PD-L1. (B) Genes for which at least two different gRNAs were significantly enriched (greater than fourfold) in the sorted population versus control population in both replicate sorts. Plotted are p val- ues based on RSA analysis. (C) MelJuSo MPH cells stably expressing the SAM vector with or without the indicated activation gRNAs were analyzed for cell surface expression of PD-L1 and MHC class I (HLA-ABC). Data represent three independent experiments (1SD), and statistical significance was determined by paired Student t test (*p < 0.05, **p < 0.01). (D) MelJuSo cells stably expressing FLAG (EV), GATA2-FLAG, or FLAG-VGLL3 were analyzed for cell surface expression of PD-L1 using flow cytometry. (E) MelJuSo cells as in D were either stimulated or not with IFN-g for 48 h, and cell surface expression of PD-L1 and PD-L2 was mea- sured using flow cytometry. (F) MelJuSo cells as in D were either stimulated or not with IFN-g for 24 h, and expression of the indicated proteins was determined by Western blot analysis. (G) MelJuSo cells as in D were treated with IFN-g for 24 h when indicated, and mRNA levels of the indicated genes were analyzed using quanti- tative real-time PCR and normalized to GAPDH. All data represent three independent experiments (1SD), and statistical significance was determined by ANOVA using Dunnett’s multiple comparison test (*p < 0.05, **p < 0.01).
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FIGURE 1. <t>CRISPR</t> activation screen identifies novel regulators of PD-L1 expression. (A) Schematic setup of the screen. MelJuSo melanoma cells stably expressing MS2-p65-HSF1 were transduced with a pooled gRNA library containing dCAS9 and sorted by FACS for cells displaying high levels of PD-L1. (B) Genes for which at least two different gRNAs were significantly enriched (greater than fourfold) in the sorted population versus control population in both replicate sorts. Plotted are p val- ues based on RSA analysis. (C) MelJuSo MPH cells stably expressing the SAM vector with or without the indicated activation gRNAs were analyzed for cell surface expression of PD-L1 and MHC class I (HLA-ABC). Data represent three independent experiments (1SD), and statistical significance was determined by paired Student t test (*p < 0.05, **p < 0.01). (D) MelJuSo cells stably expressing FLAG (EV), GATA2-FLAG, or FLAG-VGLL3 were analyzed for cell surface expression of PD-L1 using flow cytometry. (E) MelJuSo cells as in D were either stimulated or not with IFN-g for 48 h, and cell surface expression of PD-L1 and PD-L2 was mea- sured using flow cytometry. (F) MelJuSo cells as in D were either stimulated or not with IFN-g for 24 h, and expression of the indicated proteins was determined by Western blot analysis. (G) MelJuSo cells as in D were treated with IFN-g for 24 h when indicated, and mRNA levels of the indicated genes were analyzed using quanti- tative real-time PCR and normalized to GAPDH. All data represent three independent experiments (1SD), and statistical significance was determined by ANOVA using Dunnett’s multiple comparison test (*p < 0.05, **p < 0.01).
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FIGURE 1. <t>CRISPR</t> activation screen identifies novel regulators of PD-L1 expression. (A) Schematic setup of the screen. MelJuSo melanoma cells stably expressing MS2-p65-HSF1 were transduced with a pooled gRNA library containing dCAS9 and sorted by FACS for cells displaying high levels of PD-L1. (B) Genes for which at least two different gRNAs were significantly enriched (greater than fourfold) in the sorted population versus control population in both replicate sorts. Plotted are p val- ues based on RSA analysis. (C) MelJuSo MPH cells stably expressing the SAM vector with or without the indicated activation gRNAs were analyzed for cell surface expression of PD-L1 and MHC class I (HLA-ABC). Data represent three independent experiments (1SD), and statistical significance was determined by paired Student t test (*p < 0.05, **p < 0.01). (D) MelJuSo cells stably expressing FLAG (EV), GATA2-FLAG, or FLAG-VGLL3 were analyzed for cell surface expression of PD-L1 using flow cytometry. (E) MelJuSo cells as in D were either stimulated or not with IFN-g for 48 h, and cell surface expression of PD-L1 and PD-L2 was mea- sured using flow cytometry. (F) MelJuSo cells as in D were either stimulated or not with IFN-g for 24 h, and expression of the indicated proteins was determined by Western blot analysis. (G) MelJuSo cells as in D were treated with IFN-g for 24 h when indicated, and mRNA levels of the indicated genes were analyzed using quanti- tative real-time PCR and normalized to GAPDH. All data represent three independent experiments (1SD), and statistical significance was determined by ANOVA using Dunnett’s multiple comparison test (*p < 0.05, **p < 0.01).
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Figure 1. Genome-wide <t>CRISPR-Cas9</t> screen identifies host-encoded regulators of SARS-CoV-2 frameshifting (A) Schematic of the SARS-CoV-2 genome. Dotted box indicates close up of region shown in (B) harboring the coronavirus frameshifting element (FSE). (B) Secondary structure of the SARS-CoV-2 FSE containing the slippery sequence and three-stemmed pseudoknot. Based on structural data from Bhatt et al.13
Paper N A Recombinant Dna Human Crispr Knockout Pooled Library Brunello, supplied by Addgene inc, used in various techniques. Bioz Stars score: 98/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Figure 1. Genome-wide <t>CRISPR-Cas9</t> screen identifies host-encoded regulators of SARS-CoV-2 frameshifting (A) Schematic of the SARS-CoV-2 genome. Dotted box indicates close up of region shown in (B) harboring the coronavirus frameshifting element (FSE). (B) Secondary structure of the SARS-CoV-2 FSE containing the slippery sequence and three-stemmed pseudoknot. Based on structural data from Bhatt et al.13
Human Crispr Knockout Pooled Library Brunello Doench, supplied by Addgene inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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A. Workflow of the genome-wide <t>CRISPR</t> screening. A549-ACE2 or HeLa cells expressing the Cas9 were transduced with a CRISPR knockout sgRNA library, followed by infection with coronaviruses expressing fluorescent protein reporter. Infected reporter-positive cells were sorted for genomic extraction and sgRNA sequence analysis. B-D. Genes identified from the CRISPR screens in A549-ACE cells using SARS-CoV-2 trVLP-GFP (B) , HCoV-OC43-mGreen (C) , or PEDV-GFP (D) at an MOI of 0.1 for 24 h. The genes were analyzed by MAGeCK software and sorted based on the -log 10 (MAGeCK score). E-G. KEGG pathway analysis of 100 top-ranked genes from the screens in B-D .
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Fig. 1 <t>Kinome-wide</t> <t>CRISPR-Cas9</t> knockout screens reveal a cohort of kinases essential for human osteosarcoma cells. A Workflow of CRISPR-Cas9 knockout screen using human kinome CRISPR knockout library (Brunello) in U2OS, Saos-2 and OS-732 osteosarcoma cancer cell lines. Two infection replicates for each cell line was carried out. B Heatmap of Pearson correlation coefficients of gene beta scores across cell lines as well as replicates. Beta score was calculated using MAGeCK MLE algorithm. Top essential genes in knockout screen of U2OS (C), Saos-2 (D), and OS-732 cells (E). F Top essential genes of osteosarcoma, which used U2OS, Saos-2 and OS-732 cells as biological replicates. G Pathway enrichment of the essential genes using Metascape database. H Frequency histograms of sgRNA beta scores showing essentiality of PLK1 in three osteosarcoma cells as biological replicates. Lines representing the beta scores of individual sgRNAs targeting PLK1 are marked red.
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Receptor-ligand <t>CRISPR-Cas9</t> activation screen reveals that CD55 interacts with HLA-C∗07:01-VRIG tetramers (A) Schematic of the receptor ligand CRISPR-Cas9 activation screen. K562 cells transduced with a genome-wide activation library were stained with a pool of three HLA tetramers (HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, and HLA-C∗07:01-VRIG), and enriched gRNAs in stained cells were identified using NGS. (B) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and top hits are annotated. (C) K562 cells stably expressing dCas9 and transduced with a gRNA upregulating CD55 or a control guide were stained with the HLA-A, -B, -C, or tetramers as in (A) or with HLA-E∗01:01-VMAP tetramers and analyzed by flow cytometry. (D) In vitro co-immunoprecipitation of recombinant CD55-Fc with HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, HLA-C∗07:01-VRIG, or HLA-E∗01:01-VMAP tetramers. (E) Three different cell lines (HeLa, PC-3M, or SiHa) that express CD55 endogenously were stained for CD55 (top) or with HLA-C∗07:01-VRIG tetramers (bottom) and analyzed by flow cytometry. (F) HeLa wild-type or HeLa CD55 KO cells were stained with αCD55 or HLA-C∗07:01-VRIG tetramers and analyzed by flow cytometry. All data except (B) represent at least three independent experiments. CRISPRa, CRISPR activation screen; TMs, tetramers; WT, wild-type; KO, knockout. Related to <xref ref-type=Figure S1 and Table S1 . " width="250" height="auto" />
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Receptor-ligand <t>CRISPR-Cas9</t> activation screen reveals that CD55 interacts with HLA-C∗07:01-VRIG tetramers (A) Schematic of the receptor ligand CRISPR-Cas9 activation screen. K562 cells transduced with a genome-wide activation library were stained with a pool of three HLA tetramers (HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, and HLA-C∗07:01-VRIG), and enriched gRNAs in stained cells were identified using NGS. (B) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and top hits are annotated. (C) K562 cells stably expressing dCas9 and transduced with a gRNA upregulating CD55 or a control guide were stained with the HLA-A, -B, -C, or tetramers as in (A) or with HLA-E∗01:01-VMAP tetramers and analyzed by flow cytometry. (D) In vitro co-immunoprecipitation of recombinant CD55-Fc with HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, HLA-C∗07:01-VRIG, or HLA-E∗01:01-VMAP tetramers. (E) Three different cell lines (HeLa, PC-3M, or SiHa) that express CD55 endogenously were stained for CD55 (top) or with HLA-C∗07:01-VRIG tetramers (bottom) and analyzed by flow cytometry. (F) HeLa wild-type or HeLa CD55 KO cells were stained with αCD55 or HLA-C∗07:01-VRIG tetramers and analyzed by flow cytometry. All data except (B) represent at least three independent experiments. CRISPRa, CRISPR activation screen; TMs, tetramers; WT, wild-type; KO, knockout. Related to <xref ref-type=Figure S1 and Table S1 . " width="250" height="auto" />
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A) CRISPR-Cas9 knockout screening was performed using the <t>Brunello</t> whole-genome library, covering 19,000+ guides, ∼2000 non-targeting controls, and 4 sgRNAs per gene. A DMSO-treated population was compared to a TMZ-treated population, and guides were sequenced at d0 and d14. B) Comparison of d14 versus day 0 revealed segments of guides that were enriched and depleted. C) TMZ-sensitivity and TMZ-resistance genes identified and pursued were filtered with multiple CRISPR-appropriate analysis algorithms D) Specific genes were then examined for enrichment and depletion at day 0 and day 14. Known TMZ-resistance genes were depleted at d14, reflecting the validity of our screen. Key TMZ-sensitivity genes were identified as enriched ( MLH1, MSH6, PMS2, MSH2 ), further reflecting validity of the screen. E) Enrichment mapping identified key pathways across identified TMZ-sensitivity and TMZ-resistance genes. Enrichment mapping was performed in the Enrichr application. F) Of the 5966 genes identified as TMZ-resistance genes, 150 were significant by DESeq2 and MAGeCK algorithms. 34 were filtered based on novelty, ability to study, and clinical significance. 4 were finally chosen for validation to reflect critical pathways from the screen. Analysis was performed in Prism 8, using ANOVA to compare row-means to determine significance or using log-rank tests to determine survival significance *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; ns, not significant.
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Image Search Results


CRISPR knockout screen identifies common host factors required for rVSV-CCHFV pseudovirus infection. ( A ). Bubble plot of genes significantly enriched in a genome-wide CRISPR knockout screen in wild-type A549 (A549-WT) cells challenged with rVSV-CCHFV pseudovirus. The virus-resistant A549-WT cells were collected for analysis, and genes were ranked according to the MAGeCK score. ( B ) KEGG (Kyoto Encyclopedia of Genes and Genomes) and Go (Gene Ontology) analysis of top 100 enriched genes. ( C and D ) Flow cytometry ( C ) and fluorescence imaging ( D ) analysis of A549-WT and A549-BAT (B3GAT3, AXL, and TIM-1 triple-knockout cells) infected with rVSV-CCHFV (MOI 3). The percentage of GFP-positive cells was analyzed at indicated time points using flow cytometer, and images were taken using fluorescence microscope at 24 h post-infection (hpi). Scale bar, 400 µm. Two-way ANOVA with Sidak’s multiple-comparison test. **** P < 0.0001.

Journal: mBio

Article Title: Soluble MFGE8 mediates cell entry of Crimean-Congo hemorrhagic fever virus

doi: 10.1128/mbio.01617-25

Figure Lengend Snippet: CRISPR knockout screen identifies common host factors required for rVSV-CCHFV pseudovirus infection. ( A ). Bubble plot of genes significantly enriched in a genome-wide CRISPR knockout screen in wild-type A549 (A549-WT) cells challenged with rVSV-CCHFV pseudovirus. The virus-resistant A549-WT cells were collected for analysis, and genes were ranked according to the MAGeCK score. ( B ) KEGG (Kyoto Encyclopedia of Genes and Genomes) and Go (Gene Ontology) analysis of top 100 enriched genes. ( C and D ) Flow cytometry ( C ) and fluorescence imaging ( D ) analysis of A549-WT and A549-BAT (B3GAT3, AXL, and TIM-1 triple-knockout cells) infected with rVSV-CCHFV (MOI 3). The percentage of GFP-positive cells was analyzed at indicated time points using flow cytometer, and images were taken using fluorescence microscope at 24 h post-infection (hpi). Scale bar, 400 µm. Two-way ANOVA with Sidak’s multiple-comparison test. **** P < 0.0001.

Article Snippet: The human Brunello CRISPR knockout pooled library targeting 19,114 genes (Addgene #73178) or Calabrese activation pooled library targeting 18,885 genes (Addgene #92379) was a gift from David Root and John Doench ( ) and packaged in 293 FT cells after co-transfection with psPAX2 (Addgene #12260) and pMD2.G (Addgene #12259) using FugeneHD (Promega).

Techniques: CRISPR, Knock-Out, Infection, Genome Wide, Virus, Flow Cytometry, Fluorescence, Imaging, Triple Knockout, Microscopy, Comparison

CRISPR activation screen identifies MFGE8 as a proviral host factor for rVSV-CCHFV infection. ( A ) Identification of genes from CRISPR screen in A549-BAT cells. Cells transduced with the CRISPR activation library were infected with rVSV-CCHFV for 24 h. GFP-positive cells were sorted for sgRNA abundance analysis and ranked based on the MAGeCK score and P value. ( B and C ) Validation of MFGE8 gene. Gene expression was activated using two or representative sgRNAs in A549-BAT cells, followed by infection with rVSV-CCHFV (MOI 3, 18 h) ( B ) and rVSV (MOI 0.01, 15 h) ( C ). The percentage of GFP-positive cells were analyzed by flow cytometry. ( D ) Representative fluorescence images of A549-BAT cell infected with respective virus from ( B ) and ( C ) were taken before harvesting the cells. Scale bar, 400 µm. ( E ) Overexpression of MFGE8 enhances rVSV-CCHFV infection in A549-BAT cells. ( F ) Growth kinetics of rVSV-CCHFV in vector control and MFGE8-overexpressing cells. Cells were infected with rVSV-CCHFV at an MOI of 0.3, and viral titers in the supernatants at indicated time points were determined by plaque-forming assay. ( G–I ) Overexpression of MFGE8 enhances rVSV-CCHFV infection in A549-WT ( G ), Hela ( H ), and SW-13 ( I ) cells. The percentage of GFP-positive cells were analyzed by flow cytometry at 16 hpi. (J) Knockout of MFGE8 decreases the rVSV-CCHFV infection. A549-WT cells edited with two different nontargeting control or MFGE8 -specific sgRNAs were infected with rVSV-CCHFV, followed by flow cytometry analysis of GFP-positive cells at 16 hpi. Two-way ANOVA with Sidak’s multiple-comparison test. ns, not significant; *** P < 0.001; **** P < 0.0001.

Journal: mBio

Article Title: Soluble MFGE8 mediates cell entry of Crimean-Congo hemorrhagic fever virus

doi: 10.1128/mbio.01617-25

Figure Lengend Snippet: CRISPR activation screen identifies MFGE8 as a proviral host factor for rVSV-CCHFV infection. ( A ) Identification of genes from CRISPR screen in A549-BAT cells. Cells transduced with the CRISPR activation library were infected with rVSV-CCHFV for 24 h. GFP-positive cells were sorted for sgRNA abundance analysis and ranked based on the MAGeCK score and P value. ( B and C ) Validation of MFGE8 gene. Gene expression was activated using two or representative sgRNAs in A549-BAT cells, followed by infection with rVSV-CCHFV (MOI 3, 18 h) ( B ) and rVSV (MOI 0.01, 15 h) ( C ). The percentage of GFP-positive cells were analyzed by flow cytometry. ( D ) Representative fluorescence images of A549-BAT cell infected with respective virus from ( B ) and ( C ) were taken before harvesting the cells. Scale bar, 400 µm. ( E ) Overexpression of MFGE8 enhances rVSV-CCHFV infection in A549-BAT cells. ( F ) Growth kinetics of rVSV-CCHFV in vector control and MFGE8-overexpressing cells. Cells were infected with rVSV-CCHFV at an MOI of 0.3, and viral titers in the supernatants at indicated time points were determined by plaque-forming assay. ( G–I ) Overexpression of MFGE8 enhances rVSV-CCHFV infection in A549-WT ( G ), Hela ( H ), and SW-13 ( I ) cells. The percentage of GFP-positive cells were analyzed by flow cytometry at 16 hpi. (J) Knockout of MFGE8 decreases the rVSV-CCHFV infection. A549-WT cells edited with two different nontargeting control or MFGE8 -specific sgRNAs were infected with rVSV-CCHFV, followed by flow cytometry analysis of GFP-positive cells at 16 hpi. Two-way ANOVA with Sidak’s multiple-comparison test. ns, not significant; *** P < 0.001; **** P < 0.0001.

Article Snippet: The human Brunello CRISPR knockout pooled library targeting 19,114 genes (Addgene #73178) or Calabrese activation pooled library targeting 18,885 genes (Addgene #92379) was a gift from David Root and John Doench ( ) and packaged in 293 FT cells after co-transfection with psPAX2 (Addgene #12260) and pMD2.G (Addgene #12259) using FugeneHD (Promega).

Techniques: CRISPR, Activation Assay, Infection, Transduction, Biomarker Discovery, Gene Expression, Flow Cytometry, Fluorescence, Virus, Over Expression, Plasmid Preparation, Control, Knock-Out, Comparison

FIGURE 1. CRISPR activation screen identifies novel regulators of PD-L1 expression. (A) Schematic setup of the screen. MelJuSo melanoma cells stably expressing MS2-p65-HSF1 were transduced with a pooled gRNA library containing dCAS9 and sorted by FACS for cells displaying high levels of PD-L1. (B) Genes for which at least two different gRNAs were significantly enriched (greater than fourfold) in the sorted population versus control population in both replicate sorts. Plotted are p val- ues based on RSA analysis. (C) MelJuSo MPH cells stably expressing the SAM vector with or without the indicated activation gRNAs were analyzed for cell surface expression of PD-L1 and MHC class I (HLA-ABC). Data represent three independent experiments (1SD), and statistical significance was determined by paired Student t test (*p < 0.05, **p < 0.01). (D) MelJuSo cells stably expressing FLAG (EV), GATA2-FLAG, or FLAG-VGLL3 were analyzed for cell surface expression of PD-L1 using flow cytometry. (E) MelJuSo cells as in D were either stimulated or not with IFN-g for 48 h, and cell surface expression of PD-L1 and PD-L2 was mea- sured using flow cytometry. (F) MelJuSo cells as in D were either stimulated or not with IFN-g for 24 h, and expression of the indicated proteins was determined by Western blot analysis. (G) MelJuSo cells as in D were treated with IFN-g for 24 h when indicated, and mRNA levels of the indicated genes were analyzed using quanti- tative real-time PCR and normalized to GAPDH. All data represent three independent experiments (1SD), and statistical significance was determined by ANOVA using Dunnett’s multiple comparison test (*p < 0.05, **p < 0.01).

Journal: Journal of immunology (Baltimore, Md. : 1950)

Article Title: CRISPR Activation Screening Identifies VGLL3-TEAD1-RUNX1/3 as a Transcriptional Complex for PD-L1 Expression.

doi: 10.4049/jimmunol.2100917

Figure Lengend Snippet: FIGURE 1. CRISPR activation screen identifies novel regulators of PD-L1 expression. (A) Schematic setup of the screen. MelJuSo melanoma cells stably expressing MS2-p65-HSF1 were transduced with a pooled gRNA library containing dCAS9 and sorted by FACS for cells displaying high levels of PD-L1. (B) Genes for which at least two different gRNAs were significantly enriched (greater than fourfold) in the sorted population versus control population in both replicate sorts. Plotted are p val- ues based on RSA analysis. (C) MelJuSo MPH cells stably expressing the SAM vector with or without the indicated activation gRNAs were analyzed for cell surface expression of PD-L1 and MHC class I (HLA-ABC). Data represent three independent experiments (1SD), and statistical significance was determined by paired Student t test (*p < 0.05, **p < 0.01). (D) MelJuSo cells stably expressing FLAG (EV), GATA2-FLAG, or FLAG-VGLL3 were analyzed for cell surface expression of PD-L1 using flow cytometry. (E) MelJuSo cells as in D were either stimulated or not with IFN-g for 48 h, and cell surface expression of PD-L1 and PD-L2 was mea- sured using flow cytometry. (F) MelJuSo cells as in D were either stimulated or not with IFN-g for 24 h, and expression of the indicated proteins was determined by Western blot analysis. (G) MelJuSo cells as in D were treated with IFN-g for 24 h when indicated, and mRNA levels of the indicated genes were analyzed using quanti- tative real-time PCR and normalized to GAPDH. All data represent three independent experiments (1SD), and statistical significance was determined by ANOVA using Dunnett’s multiple comparison test (*p < 0.05, **p < 0.01).

Article Snippet: For knockout screening, we used the human CRISPR Brunello genomewide knockout library, a gift from David Root and John Doench (Addgene, 73178).

Techniques: CRISPR, Activation Assay, Expressing, Stable Transfection, Transduction, Control, Plasmid Preparation, Flow Cytometry, Western Blot, Real-time Polymerase Chain Reaction, Comparison

FIGURE 4. VGLL3 cooperates with TEAD1 to drive PD-L1 expression. (A) Schematic setup of the screen. MelJuSo cells stably expressing FLAG- VGLL3 were transduced with the Brunello CRISPR knockout library and sorted by FACS twice for cells displaying low PD-L1 surface levels. (B) Results of the RSA analysis of the inserts from the biological duplicates, with three candidates indicated with gray dots. (C) Western blot validation of the knockout effi- ciency of the pooled MelJuSo VGLL3 knockout cells transduced with the indicated gRNAs. (D) MelJuSo FLAG-VGLL3 or FLAG-expressing cells were transduced with the indicated gRNAs, and pooled knockout lines were analyzed for surface PD-L1 expression using flow cytometry. (E) Left: Myc or Myc- TEAD1 were isolated from HEK293T cells using Myc-TRAP beads, and associated FLAG-VGLL3 or FLAG-VGLL3(vhfaaa) was detected by Western blot analysis. Right: MelJuSo cells transduced with the indicated expression constructs were analyzed for expression of PD-L1 using flow cytometry. (F) MelJuSo cells stably expressing FLAG or FLAG-VGLL3 were transfected with the indicated siRNAs and 3 d later were analyzed for PD-L1 expression using flow cytometry. (G) As in F, but 3 d after siRNA transfection. mRNA was isolated, and the expression of PD-L1 transcript was analyzed by qRT-PCR and normal- ized to GAPDH mRNA. All data represent three independent experiments (1SD); statistical significance was determined by ANOVA using Dunnett’s multi- ple comparison test (*p < 0.05, **p < 0.01).

Journal: Journal of immunology (Baltimore, Md. : 1950)

Article Title: CRISPR Activation Screening Identifies VGLL3-TEAD1-RUNX1/3 as a Transcriptional Complex for PD-L1 Expression.

doi: 10.4049/jimmunol.2100917

Figure Lengend Snippet: FIGURE 4. VGLL3 cooperates with TEAD1 to drive PD-L1 expression. (A) Schematic setup of the screen. MelJuSo cells stably expressing FLAG- VGLL3 were transduced with the Brunello CRISPR knockout library and sorted by FACS twice for cells displaying low PD-L1 surface levels. (B) Results of the RSA analysis of the inserts from the biological duplicates, with three candidates indicated with gray dots. (C) Western blot validation of the knockout effi- ciency of the pooled MelJuSo VGLL3 knockout cells transduced with the indicated gRNAs. (D) MelJuSo FLAG-VGLL3 or FLAG-expressing cells were transduced with the indicated gRNAs, and pooled knockout lines were analyzed for surface PD-L1 expression using flow cytometry. (E) Left: Myc or Myc- TEAD1 were isolated from HEK293T cells using Myc-TRAP beads, and associated FLAG-VGLL3 or FLAG-VGLL3(vhfaaa) was detected by Western blot analysis. Right: MelJuSo cells transduced with the indicated expression constructs were analyzed for expression of PD-L1 using flow cytometry. (F) MelJuSo cells stably expressing FLAG or FLAG-VGLL3 were transfected with the indicated siRNAs and 3 d later were analyzed for PD-L1 expression using flow cytometry. (G) As in F, but 3 d after siRNA transfection. mRNA was isolated, and the expression of PD-L1 transcript was analyzed by qRT-PCR and normal- ized to GAPDH mRNA. All data represent three independent experiments (1SD); statistical significance was determined by ANOVA using Dunnett’s multi- ple comparison test (*p < 0.05, **p < 0.01).

Article Snippet: For knockout screening, we used the human CRISPR Brunello genomewide knockout library, a gift from David Root and John Doench (Addgene, 73178).

Techniques: Expressing, Stable Transfection, Transduction, CRISPR, Knock-Out, Western Blot, Biomarker Discovery, Flow Cytometry, Isolation, Construct, Transfection, Quantitative RT-PCR, Comparison

Figure 1. Genome-wide CRISPR-Cas9 screen identifies host-encoded regulators of SARS-CoV-2 frameshifting (A) Schematic of the SARS-CoV-2 genome. Dotted box indicates close up of region shown in (B) harboring the coronavirus frameshifting element (FSE). (B) Secondary structure of the SARS-CoV-2 FSE containing the slippery sequence and three-stemmed pseudoknot. Based on structural data from Bhatt et al.13

Journal: Cell reports

Article Title: CRISPR screening reveals a dependency on ribosome recycling for efficient SARS-CoV-2 programmed ribosomal frameshifting and viral replication.

doi: 10.1016/j.celrep.2023.112076

Figure Lengend Snippet: Figure 1. Genome-wide CRISPR-Cas9 screen identifies host-encoded regulators of SARS-CoV-2 frameshifting (A) Schematic of the SARS-CoV-2 genome. Dotted box indicates close up of region shown in (B) harboring the coronavirus frameshifting element (FSE). (B) Secondary structure of the SARS-CoV-2 FSE containing the slippery sequence and three-stemmed pseudoknot. Based on structural data from Bhatt et al.13

Article Snippet: REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data CRISPR screening data This paper GEO: GSE206101 Experimental models: Cell lines HCT116 ATCC CCL-247; RRID: CVCL_0291 HEK293T ATCC CRL-3216; RRID: CVCL_0063 VeroE6 ATCC CRL-1586; RRID: CVCL_0574 HCT116-SARS-CoV-2-PRF-1 reporter cell line 1 This paper N/A HCT116-SARS-CoV-2-PRF-1 reporter cell line 2 This paper N/A HCT116-SARS-CoV-2-PRF-0 reporter cell line 1 This paper N/A HCT116-SARS-CoV-2-PRF-0 reporter cell line 2 This paper N/A HCT116-ACE2-Blast cell line 1 This paper N/A HCT116-ACE2-Blast cell line 2 This paper N/A Oligonucleotides Sequences of oligonucleotides used in this study are provided in Table S2 This paper N/A Recombinant DNA Human CRISPR Knockout Pooled Library (Brunello) Addgene (David Root, John Doench) Cat# 73179; RRID: Addgene_73179 lentiCas9-Blast Addgene (Feng Zhang) Cat# 52962; RRID: Addgene_52962 lentiCRISPR v2 Addgene (Feng Zhang) Cat# 52961; RRID: Addgene_52961 pMD2.G Addgene (Didier Trono) Cat# 12259; RRID: Addgene_12259 psPAX2 Addgene (Didier Trono) Cat# 12260; RRID: Addgene_12260 pSCRBBL-ACE2-Blasticidin John Schoggins lab N/A lenti-mCh-HIV-PRF-1-P2A-eGFP This paper N/A lenti-mCh-HIV-PRF-0-P2A-eGFP This paper N/A lenti-mCh-SARS-CoV2-PRF-1-P2A-eGFP This paper N/A lenti-mCh-SARS-CoV2-PRF-0-P2A-eGFP This paper N/A lenti-nLuc-HKU1-PRF-1-ffLuc This paper N/A lenti-nLuc-HKU1-PRF-0-ffLuc This paper N/A lenti-nLuc-OC43-PRF-1-ffLuc This paper N/A lenti-nLuc-OC43-PRF-0-ffLuc This paper N/A lenti-nLuc-SARS-CoV1-PRF-1-ffLuc This paper N/A lenti-nLuc-SARS-CoV1-PRF-0-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-PRF-1-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-PRF-0-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-UUA-PRF-1-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-UUA-PRF-0-ffLuc This paper N/A lentiCRISPR-v2-sgRNA-hsa-ABCE1-1 This paper N/A lentiCRISPR-v2-sgRNA-hsa-ABCE1-2 This paper N/A lentiCRISPR-v2-sgRNA-hsa-DENR-1 This paper N/A lentiCRISPR-v2-sgRNA-hsa-DENR-2 This paper N/A lentiCRISPR-v2-gRNA-hsa-DOHH This paper N/A lentiCRISPR-v2-gRNA-hsa-DPH1 This paper N/A lentiCRISPR-v2-gRNA-hsa-DPH3 This paper N/A lentiCRISPR-v2-gRNA-hsa-EIF2D This paper N/A lentiCRISPR-v2-gRNA-hsa-EIF5A Manjunath et al.53 N/A lentiCRISPR-v2-gRNA-hsa-POLR3K This paper N/A lentiCRISPR-v2-sgRNA-hsa-ORAOV1 This paper N/A lentiCRISPR-v2-sgRNA-hsa-YAE1D1 This paper N/A (Continued on next page) Cell Reports 42, 112076, February 28, 2023 15

Techniques: Genome Wide, CRISPR, Sequencing

Figure 6. Loss of ribosome recycling factors inhibits SARS-CoV-2 replication and reduces ribosomal frameshifting during infection (A) Experimental workflow for testing the effect of ribosome recycling on SARS-CoV-2 replication. (1) Lentiviral expression of ACE2 in HCT116 cells. (2) CRISPR- Cas9-mediated knockout of ABCE1 or DENR. (3) Infection with SARS-CoV-2. (4) Sample collection 7 h post-infection and qRT-PCR analysis of nucleocapsid (N) expression. (B) Immunoblotting of ABCE1 and DENR in HCT116-ACE2 CRISPR knockout pools. (C and D) qRT-PCR measurement of nucleocapsid mRNA expression 7 h after SARS-CoV-2 infection in cells transduced with non-target control sgRNA (sgNeg) or sgRNAs targeting ABCE1 (C) or DENR (D). Two distinct sgRNAs were used per gene in two independent ACE2-expressing HCT116 cell lines (ACE2-1 and ACE2-2). Nucleocapsid expression was normalized to host GAPDH expression. (E) Schematic of SARS-CoV-2 ORF1a and ORF1b non-structural proteins (NSPs). Antibody symbols indicate upstream (NSP1) and downstream (NSP16) NSPs that were detected by immunoblotting to assess relative frameshifting rate. (F) Representative western blot for NSP1, NSP16, and nucleocapsid from uninfected cells, infected control cells (sgNeg) and infected ABCE1 knockout pools generated with two independent sgRNAs (sgABCE1-1 and sgABCE1-2). (G) Quantification of NSP1, NSP16, and nucleocapsid protein levels, normalized to host GAPDH expression, from three independent experiments. Data are represented as the mean ± SD with individual replicates plotted. The p values for qRT-PCR experiments were calculated by two-way ANOVA with Dunnett’s multiple comparisons test. The p values for the immunoblotting results were calculated by two-way ANOVA with Tukey’s multiple comparisons test; **p % 0.01, ***p % 0.001; n = 3 biological replicates for all experiments.

Journal: Cell reports

Article Title: CRISPR screening reveals a dependency on ribosome recycling for efficient SARS-CoV-2 programmed ribosomal frameshifting and viral replication.

doi: 10.1016/j.celrep.2023.112076

Figure Lengend Snippet: Figure 6. Loss of ribosome recycling factors inhibits SARS-CoV-2 replication and reduces ribosomal frameshifting during infection (A) Experimental workflow for testing the effect of ribosome recycling on SARS-CoV-2 replication. (1) Lentiviral expression of ACE2 in HCT116 cells. (2) CRISPR- Cas9-mediated knockout of ABCE1 or DENR. (3) Infection with SARS-CoV-2. (4) Sample collection 7 h post-infection and qRT-PCR analysis of nucleocapsid (N) expression. (B) Immunoblotting of ABCE1 and DENR in HCT116-ACE2 CRISPR knockout pools. (C and D) qRT-PCR measurement of nucleocapsid mRNA expression 7 h after SARS-CoV-2 infection in cells transduced with non-target control sgRNA (sgNeg) or sgRNAs targeting ABCE1 (C) or DENR (D). Two distinct sgRNAs were used per gene in two independent ACE2-expressing HCT116 cell lines (ACE2-1 and ACE2-2). Nucleocapsid expression was normalized to host GAPDH expression. (E) Schematic of SARS-CoV-2 ORF1a and ORF1b non-structural proteins (NSPs). Antibody symbols indicate upstream (NSP1) and downstream (NSP16) NSPs that were detected by immunoblotting to assess relative frameshifting rate. (F) Representative western blot for NSP1, NSP16, and nucleocapsid from uninfected cells, infected control cells (sgNeg) and infected ABCE1 knockout pools generated with two independent sgRNAs (sgABCE1-1 and sgABCE1-2). (G) Quantification of NSP1, NSP16, and nucleocapsid protein levels, normalized to host GAPDH expression, from three independent experiments. Data are represented as the mean ± SD with individual replicates plotted. The p values for qRT-PCR experiments were calculated by two-way ANOVA with Dunnett’s multiple comparisons test. The p values for the immunoblotting results were calculated by two-way ANOVA with Tukey’s multiple comparisons test; **p % 0.01, ***p % 0.001; n = 3 biological replicates for all experiments.

Article Snippet: REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data CRISPR screening data This paper GEO: GSE206101 Experimental models: Cell lines HCT116 ATCC CCL-247; RRID: CVCL_0291 HEK293T ATCC CRL-3216; RRID: CVCL_0063 VeroE6 ATCC CRL-1586; RRID: CVCL_0574 HCT116-SARS-CoV-2-PRF-1 reporter cell line 1 This paper N/A HCT116-SARS-CoV-2-PRF-1 reporter cell line 2 This paper N/A HCT116-SARS-CoV-2-PRF-0 reporter cell line 1 This paper N/A HCT116-SARS-CoV-2-PRF-0 reporter cell line 2 This paper N/A HCT116-ACE2-Blast cell line 1 This paper N/A HCT116-ACE2-Blast cell line 2 This paper N/A Oligonucleotides Sequences of oligonucleotides used in this study are provided in Table S2 This paper N/A Recombinant DNA Human CRISPR Knockout Pooled Library (Brunello) Addgene (David Root, John Doench) Cat# 73179; RRID: Addgene_73179 lentiCas9-Blast Addgene (Feng Zhang) Cat# 52962; RRID: Addgene_52962 lentiCRISPR v2 Addgene (Feng Zhang) Cat# 52961; RRID: Addgene_52961 pMD2.G Addgene (Didier Trono) Cat# 12259; RRID: Addgene_12259 psPAX2 Addgene (Didier Trono) Cat# 12260; RRID: Addgene_12260 pSCRBBL-ACE2-Blasticidin John Schoggins lab N/A lenti-mCh-HIV-PRF-1-P2A-eGFP This paper N/A lenti-mCh-HIV-PRF-0-P2A-eGFP This paper N/A lenti-mCh-SARS-CoV2-PRF-1-P2A-eGFP This paper N/A lenti-mCh-SARS-CoV2-PRF-0-P2A-eGFP This paper N/A lenti-nLuc-HKU1-PRF-1-ffLuc This paper N/A lenti-nLuc-HKU1-PRF-0-ffLuc This paper N/A lenti-nLuc-OC43-PRF-1-ffLuc This paper N/A lenti-nLuc-OC43-PRF-0-ffLuc This paper N/A lenti-nLuc-SARS-CoV1-PRF-1-ffLuc This paper N/A lenti-nLuc-SARS-CoV1-PRF-0-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-PRF-1-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-PRF-0-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-UUA-PRF-1-ffLuc This paper N/A lenti-nLuc-SARS-CoV2-UUA-PRF-0-ffLuc This paper N/A lentiCRISPR-v2-sgRNA-hsa-ABCE1-1 This paper N/A lentiCRISPR-v2-sgRNA-hsa-ABCE1-2 This paper N/A lentiCRISPR-v2-sgRNA-hsa-DENR-1 This paper N/A lentiCRISPR-v2-sgRNA-hsa-DENR-2 This paper N/A lentiCRISPR-v2-gRNA-hsa-DOHH This paper N/A lentiCRISPR-v2-gRNA-hsa-DPH1 This paper N/A lentiCRISPR-v2-gRNA-hsa-DPH3 This paper N/A lentiCRISPR-v2-gRNA-hsa-EIF2D This paper N/A lentiCRISPR-v2-gRNA-hsa-EIF5A Manjunath et al.53 N/A lentiCRISPR-v2-gRNA-hsa-POLR3K This paper N/A lentiCRISPR-v2-sgRNA-hsa-ORAOV1 This paper N/A lentiCRISPR-v2-sgRNA-hsa-YAE1D1 This paper N/A (Continued on next page) Cell Reports 42, 112076, February 28, 2023 15

Techniques: Infection, Expressing, CRISPR, Knock-Out, Quantitative RT-PCR, Western Blot, Transduction, Control, Generated

A. Workflow of the genome-wide CRISPR screening. A549-ACE2 or HeLa cells expressing the Cas9 were transduced with a CRISPR knockout sgRNA library, followed by infection with coronaviruses expressing fluorescent protein reporter. Infected reporter-positive cells were sorted for genomic extraction and sgRNA sequence analysis. B-D. Genes identified from the CRISPR screens in A549-ACE cells using SARS-CoV-2 trVLP-GFP (B) , HCoV-OC43-mGreen (C) , or PEDV-GFP (D) at an MOI of 0.1 for 24 h. The genes were analyzed by MAGeCK software and sorted based on the -log 10 (MAGeCK score). E-G. KEGG pathway analysis of 100 top-ranked genes from the screens in B-D .

Journal: bioRxiv

Article Title: Glycosylphosphatidylinositol biosynthesis restricts coronavirus infection via the regulation of LY6E

doi: 10.1101/2025.02.08.637211

Figure Lengend Snippet: A. Workflow of the genome-wide CRISPR screening. A549-ACE2 or HeLa cells expressing the Cas9 were transduced with a CRISPR knockout sgRNA library, followed by infection with coronaviruses expressing fluorescent protein reporter. Infected reporter-positive cells were sorted for genomic extraction and sgRNA sequence analysis. B-D. Genes identified from the CRISPR screens in A549-ACE cells using SARS-CoV-2 trVLP-GFP (B) , HCoV-OC43-mGreen (C) , or PEDV-GFP (D) at an MOI of 0.1 for 24 h. The genes were analyzed by MAGeCK software and sorted based on the -log 10 (MAGeCK score). E-G. KEGG pathway analysis of 100 top-ranked genes from the screens in B-D .

Article Snippet: The human Brunello CRISPR knockout pooled library encompassing 76,441 different sgRNAs targeting 19,114 genes was a gift from David Root and John Doench (Addgene #73178) and was packaged in HEK293T cells after co-transfection with psPAX2 and pMD2.G at a ratio of 2:2:1 using Fugene ® HD (Promega).

Techniques: Genome Wide, CRISPR, Expressing, Transduction, Knock-Out, Infection, Extraction, Sequencing, Software

A. Genes identified from the CRISPR knockout screen in HeLa cells using PEDV-GFP. The genes were analyzed by MAGeCK software and sorted based on the -log 10 (MAGeCK score). B. Validation of the 50 top-ranked genes from the screen in HeLa cells. Two independent sgRNAs per gene were used, and cells were infected with PEDV (MOI 0.5, 24 h) and infection was assessed by flow cytometry. Data shown are pooled from three independent experiments, and each performed in duplicate.

Journal: bioRxiv

Article Title: Glycosylphosphatidylinositol biosynthesis restricts coronavirus infection via the regulation of LY6E

doi: 10.1101/2025.02.08.637211

Figure Lengend Snippet: A. Genes identified from the CRISPR knockout screen in HeLa cells using PEDV-GFP. The genes were analyzed by MAGeCK software and sorted based on the -log 10 (MAGeCK score). B. Validation of the 50 top-ranked genes from the screen in HeLa cells. Two independent sgRNAs per gene were used, and cells were infected with PEDV (MOI 0.5, 24 h) and infection was assessed by flow cytometry. Data shown are pooled from three independent experiments, and each performed in duplicate.

Article Snippet: The human Brunello CRISPR knockout pooled library encompassing 76,441 different sgRNAs targeting 19,114 genes was a gift from David Root and John Doench (Addgene #73178) and was packaged in HEK293T cells after co-transfection with psPAX2 and pMD2.G at a ratio of 2:2:1 using Fugene ® HD (Promega).

Techniques: CRISPR, Knock-Out, Software, Biomarker Discovery, Infection, Flow Cytometry

A. The sequence traces of the gene locus of WT (upper) and PIGA-, PIGV -, or GPAA1 -knockout (bottom) HeLa cells. The sgRNA target site is indicated, and knockout efficiency was determined using Inference of CRISPR Edits (ICE) analysis.

Journal: bioRxiv

Article Title: Glycosylphosphatidylinositol biosynthesis restricts coronavirus infection via the regulation of LY6E

doi: 10.1101/2025.02.08.637211

Figure Lengend Snippet: A. The sequence traces of the gene locus of WT (upper) and PIGA-, PIGV -, or GPAA1 -knockout (bottom) HeLa cells. The sgRNA target site is indicated, and knockout efficiency was determined using Inference of CRISPR Edits (ICE) analysis.

Article Snippet: The human Brunello CRISPR knockout pooled library encompassing 76,441 different sgRNAs targeting 19,114 genes was a gift from David Root and John Doench (Addgene #73178) and was packaged in HEK293T cells after co-transfection with psPAX2 and pMD2.G at a ratio of 2:2:1 using Fugene ® HD (Promega).

Techniques: Sequencing, Knock-Out, CRISPR

A. Schematic of focused CRISPR knockout screen of known or predicted GPI-AP genes. The sub-library of 772 sgRNAs targeting 193 known or predicted GPI-AP genes was generated, and the screens were conducted in A549-ACE2 cells infected with SARS-CoV-2 trVLP-GFP, HCoV-OC43-mGreen, HCoV-229E-mGreen, or PEDV-GFP at an MOI 0.5 for 24 h. Infected GFP-positive cells were sorted for genomic extraction, sequencing, and sgRNA analysis with MAGeCK software. B. The results of focused CRISPR knockout screening with four coronaviruses. The genes were ranked based on the -log 10 (MAGeCK score). C. Venn diagram analysis of the 10 top-ranked genes from each screen. D-G. Validation of the 11 genes combined from the 5 top-ranked genes from each infection screen in A549-ACE2 cells. Cells were infected with SARS-CoV-2 trVLP-Nluc (MOI 1, 15 h), HCoV-OC43 (MOI 0.5, 48 h), HCoV-229E (MOI 0.75, 48 h), or PEDV (MOI 1, 48 h), followed by flow cytometry analysis. Data shown are from four independent experiments. D-G, two-way ANOVA with Dunnett’s test; the mean of two sgRNAs was compared with the control sgRNA; mean ± s.d.; *P < 0.05; ****P < 0.0001; ns, not significant.

Journal: bioRxiv

Article Title: Glycosylphosphatidylinositol biosynthesis restricts coronavirus infection via the regulation of LY6E

doi: 10.1101/2025.02.08.637211

Figure Lengend Snippet: A. Schematic of focused CRISPR knockout screen of known or predicted GPI-AP genes. The sub-library of 772 sgRNAs targeting 193 known or predicted GPI-AP genes was generated, and the screens were conducted in A549-ACE2 cells infected with SARS-CoV-2 trVLP-GFP, HCoV-OC43-mGreen, HCoV-229E-mGreen, or PEDV-GFP at an MOI 0.5 for 24 h. Infected GFP-positive cells were sorted for genomic extraction, sequencing, and sgRNA analysis with MAGeCK software. B. The results of focused CRISPR knockout screening with four coronaviruses. The genes were ranked based on the -log 10 (MAGeCK score). C. Venn diagram analysis of the 10 top-ranked genes from each screen. D-G. Validation of the 11 genes combined from the 5 top-ranked genes from each infection screen in A549-ACE2 cells. Cells were infected with SARS-CoV-2 trVLP-Nluc (MOI 1, 15 h), HCoV-OC43 (MOI 0.5, 48 h), HCoV-229E (MOI 0.75, 48 h), or PEDV (MOI 1, 48 h), followed by flow cytometry analysis. Data shown are from four independent experiments. D-G, two-way ANOVA with Dunnett’s test; the mean of two sgRNAs was compared with the control sgRNA; mean ± s.d.; *P < 0.05; ****P < 0.0001; ns, not significant.

Article Snippet: The human Brunello CRISPR knockout pooled library encompassing 76,441 different sgRNAs targeting 19,114 genes was a gift from David Root and John Doench (Addgene #73178) and was packaged in HEK293T cells after co-transfection with psPAX2 and pMD2.G at a ratio of 2:2:1 using Fugene ® HD (Promega).

Techniques: CRISPR, Knock-Out, Generated, Infection, Extraction, Sequencing, Software, Biomarker Discovery, Flow Cytometry, Control

Fig. 1 Kinome-wide CRISPR-Cas9 knockout screens reveal a cohort of kinases essential for human osteosarcoma cells. A Workflow of CRISPR-Cas9 knockout screen using human kinome CRISPR knockout library (Brunello) in U2OS, Saos-2 and OS-732 osteosarcoma cancer cell lines. Two infection replicates for each cell line was carried out. B Heatmap of Pearson correlation coefficients of gene beta scores across cell lines as well as replicates. Beta score was calculated using MAGeCK MLE algorithm. Top essential genes in knockout screen of U2OS (C), Saos-2 (D), and OS-732 cells (E). F Top essential genes of osteosarcoma, which used U2OS, Saos-2 and OS-732 cells as biological replicates. G Pathway enrichment of the essential genes using Metascape database. H Frequency histograms of sgRNA beta scores showing essentiality of PLK1 in three osteosarcoma cells as biological replicates. Lines representing the beta scores of individual sgRNAs targeting PLK1 are marked red.

Journal: Cell death discovery

Article Title: Kinome-wide CRISPR-Cas9 knockout screens revealed PLK1 as a therapeutic target for osteosarcoma.

doi: 10.1038/s41420-023-01526-7

Figure Lengend Snippet: Fig. 1 Kinome-wide CRISPR-Cas9 knockout screens reveal a cohort of kinases essential for human osteosarcoma cells. A Workflow of CRISPR-Cas9 knockout screen using human kinome CRISPR knockout library (Brunello) in U2OS, Saos-2 and OS-732 osteosarcoma cancer cell lines. Two infection replicates for each cell line was carried out. B Heatmap of Pearson correlation coefficients of gene beta scores across cell lines as well as replicates. Beta score was calculated using MAGeCK MLE algorithm. Top essential genes in knockout screen of U2OS (C), Saos-2 (D), and OS-732 cells (E). F Top essential genes of osteosarcoma, which used U2OS, Saos-2 and OS-732 cells as biological replicates. G Pathway enrichment of the essential genes using Metascape database. H Frequency histograms of sgRNA beta scores showing essentiality of PLK1 in three osteosarcoma cells as biological replicates. Lines representing the beta scores of individual sgRNAs targeting PLK1 are marked red.

Article Snippet: Cell Death Discovery (2023) 9:231 transfection reagent (Neofect, TF201201) at the following ratio, Human kinome CRISPR knockout library (Brunello, Addgene Cat# 1000000083): psPax2 (Addgene Cat# 12260, RRID: Addgene_12260): pMD2.G (Addgene Cat# 12259, RRID: Addgene_12259)= 7: 5: 2.

Techniques: CRISPR, Knock-Out, Infection

Receptor-ligand CRISPR-Cas9 activation screen reveals that CD55 interacts with HLA-C∗07:01-VRIG tetramers (A) Schematic of the receptor ligand CRISPR-Cas9 activation screen. K562 cells transduced with a genome-wide activation library were stained with a pool of three HLA tetramers (HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, and HLA-C∗07:01-VRIG), and enriched gRNAs in stained cells were identified using NGS. (B) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and top hits are annotated. (C) K562 cells stably expressing dCas9 and transduced with a gRNA upregulating CD55 or a control guide were stained with the HLA-A, -B, -C, or tetramers as in (A) or with HLA-E∗01:01-VMAP tetramers and analyzed by flow cytometry. (D) In vitro co-immunoprecipitation of recombinant CD55-Fc with HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, HLA-C∗07:01-VRIG, or HLA-E∗01:01-VMAP tetramers. (E) Three different cell lines (HeLa, PC-3M, or SiHa) that express CD55 endogenously were stained for CD55 (top) or with HLA-C∗07:01-VRIG tetramers (bottom) and analyzed by flow cytometry. (F) HeLa wild-type or HeLa CD55 KO cells were stained with αCD55 or HLA-C∗07:01-VRIG tetramers and analyzed by flow cytometry. All data except (B) represent at least three independent experiments. CRISPRa, CRISPR activation screen; TMs, tetramers; WT, wild-type; KO, knockout. Related to <xref ref-type=Figure S1 and Table S1 . " width="100%" height="100%">

Journal: iScience

Article Title: CRISPR-Cas9 screening reveals a distinct class of MHC-I binders with precise HLA-peptide recognition

doi: 10.1016/j.isci.2024.110120

Figure Lengend Snippet: Receptor-ligand CRISPR-Cas9 activation screen reveals that CD55 interacts with HLA-C∗07:01-VRIG tetramers (A) Schematic of the receptor ligand CRISPR-Cas9 activation screen. K562 cells transduced with a genome-wide activation library were stained with a pool of three HLA tetramers (HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, and HLA-C∗07:01-VRIG), and enriched gRNAs in stained cells were identified using NGS. (B) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and top hits are annotated. (C) K562 cells stably expressing dCas9 and transduced with a gRNA upregulating CD55 or a control guide were stained with the HLA-A, -B, -C, or tetramers as in (A) or with HLA-E∗01:01-VMAP tetramers and analyzed by flow cytometry. (D) In vitro co-immunoprecipitation of recombinant CD55-Fc with HLA-A∗02:01-NLVP, HLA-B∗07:02-TPRV, HLA-C∗07:01-VRIG, or HLA-E∗01:01-VMAP tetramers. (E) Three different cell lines (HeLa, PC-3M, or SiHa) that express CD55 endogenously were stained for CD55 (top) or with HLA-C∗07:01-VRIG tetramers (bottom) and analyzed by flow cytometry. (F) HeLa wild-type or HeLa CD55 KO cells were stained with αCD55 or HLA-C∗07:01-VRIG tetramers and analyzed by flow cytometry. All data except (B) represent at least three independent experiments. CRISPRa, CRISPR activation screen; TMs, tetramers; WT, wild-type; KO, knockout. Related to Figure S1 and Table S1 .

Article Snippet: Genome-wide mouse CRISPR Brunello knockout library , Dr. D Root and Dr. J Doench , Addgene cat: 73178.

Techniques: CRISPR, Activation Assay, Transduction, Genome Wide, Staining, Stable Transfection, Expressing, Control, Flow Cytometry, In Vitro, Immunoprecipitation, Recombinant, Knock-Out

CRISPR-Cas9 activation and KO screens identify an interaction between HLA-C∗07:02-YRFR and heparan sulfate chains (A) HeLa cells were stained with a variety of HLA-C∗07:02 tetramers loaded with different peptides and analyzed by flow cytometry. (B) The indicated cell lines were stained with HLA-C∗07:02-YRFR tetramers and analyzed by flow cytometry. Staining is normalized to unstained levels of that cell line. (C) Schematic of CRISPR-Cas9 KO screen in MelJuSo cells. Cells were stained with HLA-C∗07:02-YRFR, and enriched gRNAs in non-binding cells were identified using NGS. (D) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and genes involved in the heparan sulfate biosynthesis pathway are depicted in purple. Hits used for further validation are annotated. (E) Schematic of the CRISPR-Cas9 activation screen. K562 cells stably expressing dCas9 transduced with a genome-wide activation library were stained with HLA-C YRFR∗07:02 tetramers, and enriched gRNAs in positive cells were identified. (F) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and top hits are annotated. Proteoglycans of interest are depicted in purple. CRISPRa, Crispr activation screen. Related to <xref ref-type=Figure S3 , Table S1 and . " width="100%" height="100%">

Journal: iScience

Article Title: CRISPR-Cas9 screening reveals a distinct class of MHC-I binders with precise HLA-peptide recognition

doi: 10.1016/j.isci.2024.110120

Figure Lengend Snippet: CRISPR-Cas9 activation and KO screens identify an interaction between HLA-C∗07:02-YRFR and heparan sulfate chains (A) HeLa cells were stained with a variety of HLA-C∗07:02 tetramers loaded with different peptides and analyzed by flow cytometry. (B) The indicated cell lines were stained with HLA-C∗07:02-YRFR tetramers and analyzed by flow cytometry. Staining is normalized to unstained levels of that cell line. (C) Schematic of CRISPR-Cas9 KO screen in MelJuSo cells. Cells were stained with HLA-C∗07:02-YRFR, and enriched gRNAs in non-binding cells were identified using NGS. (D) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and genes involved in the heparan sulfate biosynthesis pathway are depicted in purple. Hits used for further validation are annotated. (E) Schematic of the CRISPR-Cas9 activation screen. K562 cells stably expressing dCas9 transduced with a genome-wide activation library were stained with HLA-C YRFR∗07:02 tetramers, and enriched gRNAs in positive cells were identified. (F) SigmaFC scores of genes from two replicate screens. SigmaFC scores were calculated using PinAplPy, and top hits are annotated. Proteoglycans of interest are depicted in purple. CRISPRa, Crispr activation screen. Related to Figure S3 , Table S1 and .

Article Snippet: Genome-wide mouse CRISPR Brunello knockout library , Dr. D Root and Dr. J Doench , Addgene cat: 73178.

Techniques: CRISPR, Activation Assay, Staining, Flow Cytometry, Binding Assay, Biomarker Discovery, Stable Transfection, Expressing, Transduction, Genome Wide

Journal: iScience

Article Title: CRISPR-Cas9 screening reveals a distinct class of MHC-I binders with precise HLA-peptide recognition

doi: 10.1016/j.isci.2024.110120

Figure Lengend Snippet:

Article Snippet: Genome-wide mouse CRISPR Brunello knockout library , Dr. D Root and Dr. J Doench , Addgene cat: 73178.

Techniques: Virus, Recombinant, Blocking Assay, Genome Wide, Activation Assay, CRISPR, Knock-Out, Mutagenesis, Plasmid Preparation, Software, Imaging

A) CRISPR-Cas9 knockout screening was performed using the Brunello whole-genome library, covering 19,000+ guides, ∼2000 non-targeting controls, and 4 sgRNAs per gene. A DMSO-treated population was compared to a TMZ-treated population, and guides were sequenced at d0 and d14. B) Comparison of d14 versus day 0 revealed segments of guides that were enriched and depleted. C) TMZ-sensitivity and TMZ-resistance genes identified and pursued were filtered with multiple CRISPR-appropriate analysis algorithms D) Specific genes were then examined for enrichment and depletion at day 0 and day 14. Known TMZ-resistance genes were depleted at d14, reflecting the validity of our screen. Key TMZ-sensitivity genes were identified as enriched ( MLH1, MSH6, PMS2, MSH2 ), further reflecting validity of the screen. E) Enrichment mapping identified key pathways across identified TMZ-sensitivity and TMZ-resistance genes. Enrichment mapping was performed in the Enrichr application. F) Of the 5966 genes identified as TMZ-resistance genes, 150 were significant by DESeq2 and MAGeCK algorithms. 34 were filtered based on novelty, ability to study, and clinical significance. 4 were finally chosen for validation to reflect critical pathways from the screen. Analysis was performed in Prism 8, using ANOVA to compare row-means to determine significance or using log-rank tests to determine survival significance *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; ns, not significant.

Journal: bioRxiv

Article Title: ARF4-mediated Retrograde Trafficking Drives Chemoresistance in Glioblastoma

doi: 10.1101/2021.07.18.451328

Figure Lengend Snippet: A) CRISPR-Cas9 knockout screening was performed using the Brunello whole-genome library, covering 19,000+ guides, ∼2000 non-targeting controls, and 4 sgRNAs per gene. A DMSO-treated population was compared to a TMZ-treated population, and guides were sequenced at d0 and d14. B) Comparison of d14 versus day 0 revealed segments of guides that were enriched and depleted. C) TMZ-sensitivity and TMZ-resistance genes identified and pursued were filtered with multiple CRISPR-appropriate analysis algorithms D) Specific genes were then examined for enrichment and depletion at day 0 and day 14. Known TMZ-resistance genes were depleted at d14, reflecting the validity of our screen. Key TMZ-sensitivity genes were identified as enriched ( MLH1, MSH6, PMS2, MSH2 ), further reflecting validity of the screen. E) Enrichment mapping identified key pathways across identified TMZ-sensitivity and TMZ-resistance genes. Enrichment mapping was performed in the Enrichr application. F) Of the 5966 genes identified as TMZ-resistance genes, 150 were significant by DESeq2 and MAGeCK algorithms. 34 were filtered based on novelty, ability to study, and clinical significance. 4 were finally chosen for validation to reflect critical pathways from the screen. Analysis was performed in Prism 8, using ANOVA to compare row-means to determine significance or using log-rank tests to determine survival significance *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; ns, not significant.

Article Snippet: H4 human GBM cells were infected with the whole-genome knockout Brunello library (Addgene, Cambridge, MA, USA), which included ∼19,000 genes with 4 sgRNAs per gene and 10,000 sgRNA non-targeting controls.

Techniques: CRISPR, Knock-Out, Comparison, Biomarker Discovery