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phospho junb  (OriGene)


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    Structured Review

    OriGene phospho junb
    Primer sets used for PCR and targeted sequences for knockdown studies
    Phospho Junb, supplied by OriGene, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/junb/JUNB+pSer79+Rabbit+Polyclonal+Antibody/pmc06960458-111-52-54
    Average 90 stars, based on 1 article reviews
    phospho junb - by Bioz Stars, 2026-11
    90/100 stars

    Images

    1) Product Images from "Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas"

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas

    Journal: Blood Advances

    doi: 10.1182/bloodadvances.2019000947

    Primer sets used for PCR and targeted sequences for knockdown studies
    Figure Legend Snippet: Primer sets used for PCR and targeted sequences for knockdown studies

    Techniques Used: Knockdown, Cloning

    TF expression, activation, and the impact of PAX5 on HCK transcription in MYD88-mutated lymphoma cells. (A) Western blot studies depicting protein expression levels of PAX5, STAT3, NF-kB (NF-κB-p65), and AP-1 complex members (JunB, c-Jun, JunD) predicted by TF promoter-binding assay and PROMO analysis as HCK promoter binding TFs in MYD88-mutated WM and ABC-DLBCL cell lines (BCWM.1, MWCL-1, TMD-8, HBL-1, OCI-Ly3, and SU-DHL-2) and MYD88 wild-type B-cell lymphoma (OCI-Ly7, OCI-Ly19, Ramos) and myeloma cells (RPMI-8226, MM.1S). The HCK protein expression levels and the phosphorylation levels of mutated MYD88–directed TFs STAT3, NF-κB-p65, and AP-1 complex members (JunB, c-Jun) were also detected. GAPDH protein expression was used to demonstrate uniform protein loading. (B) The regulation of HCK transcription by PAX5 was assessed by lentiviral knockdown of PAX5 with 2 distinct shRNAs in MYD88-mutated BCWM.1 and TMD-8 cells and compared with scrambled control vector. Quantitative RT-PCR was performed after day 5 of lentiviral transduction. HCK protein levels and knockdown efficiencies for PAX5 were analyzed by western blot at the same time as the sample collection for HCK mRNA quantification. GAPDH was used for loading control. (C) The regulation of PAX5 by mutated MYD88 was assessed by lentiviral-mediated knockdown of MYD88 in MYD88-mutated BCWM.1 and TMD-8 cells using 2 distinct shRNAs and compared with scrambled control vector. Protein levels of PAX5 are shown, and GADPH served as a protein loading control. (D) Transcriptome analysis depicting PAX5 transcript levels in CD19-selected bone marrow LPCs from MYD88-mutated WM patients, and MYD88 wild-type WM patients; peripheral CD19-selected B cells and CD19- and CD27-selected memory B cells from healthy donors; and CD138-selected bone marrow plasma cells from healthy donors. ***P < .001.
    Figure Legend Snippet: TF expression, activation, and the impact of PAX5 on HCK transcription in MYD88-mutated lymphoma cells. (A) Western blot studies depicting protein expression levels of PAX5, STAT3, NF-kB (NF-κB-p65), and AP-1 complex members (JunB, c-Jun, JunD) predicted by TF promoter-binding assay and PROMO analysis as HCK promoter binding TFs in MYD88-mutated WM and ABC-DLBCL cell lines (BCWM.1, MWCL-1, TMD-8, HBL-1, OCI-Ly3, and SU-DHL-2) and MYD88 wild-type B-cell lymphoma (OCI-Ly7, OCI-Ly19, Ramos) and myeloma cells (RPMI-8226, MM.1S). The HCK protein expression levels and the phosphorylation levels of mutated MYD88–directed TFs STAT3, NF-κB-p65, and AP-1 complex members (JunB, c-Jun) were also detected. GAPDH protein expression was used to demonstrate uniform protein loading. (B) The regulation of HCK transcription by PAX5 was assessed by lentiviral knockdown of PAX5 with 2 distinct shRNAs in MYD88-mutated BCWM.1 and TMD-8 cells and compared with scrambled control vector. Quantitative RT-PCR was performed after day 5 of lentiviral transduction. HCK protein levels and knockdown efficiencies for PAX5 were analyzed by western blot at the same time as the sample collection for HCK mRNA quantification. GAPDH was used for loading control. (C) The regulation of PAX5 by mutated MYD88 was assessed by lentiviral-mediated knockdown of MYD88 in MYD88-mutated BCWM.1 and TMD-8 cells using 2 distinct shRNAs and compared with scrambled control vector. Protein levels of PAX5 are shown, and GADPH served as a protein loading control. (D) Transcriptome analysis depicting PAX5 transcript levels in CD19-selected bone marrow LPCs from MYD88-mutated WM patients, and MYD88 wild-type WM patients; peripheral CD19-selected B cells and CD19- and CD27-selected memory B cells from healthy donors; and CD138-selected bone marrow plasma cells from healthy donors. ***P < .001.

    Techniques Used: Expressing, Activation Assay, Western Blot, Binding Assay, Phospho-proteomics, Knockdown, Control, Plasmid Preparation, Quantitative RT-PCR, Transduction, Clinical Proteomics

    ChIP studies assessing STAT3, NF-kB, and AP-1 TF binding to the HCK promoter. The fold enrichments of HCK promoter-specific sequence assessed by quantitative PCR following ChIP with ChIP grade antibodies to STAT3, NF-kB-p65, JunB, and c-Jun in MYD88-mutated WM (BCWM.1, MWCL-1) and ABC-DLBCL (TMD-8, HBL-1, OCI-Ly3) cells, and MYD88 wild-type lymphoma cells (OCI-Ly7, OCI-Ly19). Antibody to GAPDH was used as control antibody.
    Figure Legend Snippet: ChIP studies assessing STAT3, NF-kB, and AP-1 TF binding to the HCK promoter. The fold enrichments of HCK promoter-specific sequence assessed by quantitative PCR following ChIP with ChIP grade antibodies to STAT3, NF-kB-p65, JunB, and c-Jun in MYD88-mutated WM (BCWM.1, MWCL-1) and ABC-DLBCL (TMD-8, HBL-1, OCI-Ly3) cells, and MYD88 wild-type lymphoma cells (OCI-Ly7, OCI-Ly19). Antibody to GAPDH was used as control antibody.

    Techniques Used: Binding Assay, Sequencing, Real-time Polymerase Chain Reaction, ChIP-chip, Control

    The regulation of JunB by TLR/MYD88 signaling and the impact of JunB on HCK transcription. The phosphorylation of JunB (Ser79) and c-Jun (Ser63) was assessed following TLR4 (by LPS-EB) and TLR9 (by ODN-2006) stimulation (A) as well as the lentiviral cells (C). HCK overexpression of MYD88 L265P mutant vs MYD88 WT (B) in both MYD88-mutated BCWM.1 cells and MYD88 wild-type Ramos cells. The phosphorylation of JunB (Ser79) and c-Jun (Ser63) was determined following MYD88 knockdown in MYD88-mutated BCWM.1 protein levels detected following lentiviral mediated knockdown of JunB in MYD88-mutated BCWM.1 and TMD-8 cells using 2 distinct shRNAs and compared with scrambled control vector (D). Protein levels of MYD88, JunB, c-Jun, and GADPH served as protein expression, knockdown efficiency, and loading controls.
    Figure Legend Snippet: The regulation of JunB by TLR/MYD88 signaling and the impact of JunB on HCK transcription. The phosphorylation of JunB (Ser79) and c-Jun (Ser63) was assessed following TLR4 (by LPS-EB) and TLR9 (by ODN-2006) stimulation (A) as well as the lentiviral cells (C). HCK overexpression of MYD88 L265P mutant vs MYD88 WT (B) in both MYD88-mutated BCWM.1 cells and MYD88 wild-type Ramos cells. The phosphorylation of JunB (Ser79) and c-Jun (Ser63) was determined following MYD88 knockdown in MYD88-mutated BCWM.1 protein levels detected following lentiviral mediated knockdown of JunB in MYD88-mutated BCWM.1 and TMD-8 cells using 2 distinct shRNAs and compared with scrambled control vector (D). Protein levels of MYD88, JunB, c-Jun, and GADPH served as protein expression, knockdown efficiency, and loading controls.

    Techniques Used: Phospho-proteomics, Over Expression, Mutagenesis, Knockdown, Control, Plasmid Preparation, Expressing

    Related Articles

    Western Blot:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Phospho-proteomics:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Expressing:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Cell Stimulation:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Over Expression:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Knockdown:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Cloning:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Activation Assay:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Binding Assay:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Control:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Plasmid Preparation:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Quantitative RT-PCR:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Transduction:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Clinical Proteomics:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Sequencing:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Real-time Polymerase Chain Reaction:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    ChIP-chip:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.

    Mutagenesis:

    Article Title: Expression of the prosurvival kinase HCK requires PAX5 and mutated MYD88 signaling in MYD88-driven B-cell lymphomas
    Article Snippet: Transcriptome profiling was conducted by the Center for Cancer Computational Biology at the Dana-Farber Cancer Institute (Boston, MA) using the NEBNext Ultra RNA Library Prep Kit (New England BioLabs, Ipswich, MA) as previously described.



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    hdWGCNA analysis of gene co-expression modules and functional enrichment in Müller glial subpopulations cluster 0 and 1 in STZ and Ctrl groups. (A) Soft power threshold selection for the weighted network construction in the hierarchical clustering analysis of Müller glia subpopulations. The figure showed the correlation between the soft power threshold and model fit, as well as mean connectivity, median connectivity and max connectivity, with the optimal threshold indicated for constructing the network. The selected power (β = 5) represents the minimal value satisfying the scale-free topology criterion while preserving sufficient network connectivity for module detection. (B) Hierarchical clustering dendrogram of Müller glial subpopulations based on gene expression profiles. The tree showed clustering of the different gene modules identified in the analysis, with modules labeled Müller-M1 to Müller-M6. Each module represents a set of co-expressed genes associated with specific biological functions in Müller glial subpopulation. (C) Module feature plots showing the expression patterns of each module (M1-M6) within Müller cell subpopulations. For each module, cells were colored by module expression level (low to high), illustrating the distribution of module activity across Müller cell subpopulations. (D) The module membership (kME) for all genes was calculated, and the top-ranked 10 genes within each module were visualized using PlotKMEs. (E) Dot plots respectively showing the expression of distinct gene co-expression modules in Müller glial cell subpopulation and the module expression within subpopulations under different conditions. (F) Co-expression network comprising the top five hub genes from each co-expression module. (G) Network graphs showing hub-gene networks constructed from the top 25 core genes of modules 1 and 6; the inner ring denotes the top 10 hub genes and the outer ring denotes the remaining 15. (H, I) Bar charts showing functional enrichment terms for the top 100 genes from modules 1 and 6. (J) PPI network analysis of genes in Module 6, showing the top 10 hub genes selected based on connectivity scores. (K) Western blot validation of JUNB protein expression levels in the Ctrl and STZ groups (N = 3), confirming differential expression. * indicates p < 0.05.

    Journal: Frontiers in Immunology

    Article Title: Single cell transcriptomic analysis reveals pathogenic cell heterogeneity and candidate inflammatory-associated markers in STZ-induced diabetic mouse retina

    doi: 10.3389/fimmu.2026.1827122

    Figure Lengend Snippet: hdWGCNA analysis of gene co-expression modules and functional enrichment in Müller glial subpopulations cluster 0 and 1 in STZ and Ctrl groups. (A) Soft power threshold selection for the weighted network construction in the hierarchical clustering analysis of Müller glia subpopulations. The figure showed the correlation between the soft power threshold and model fit, as well as mean connectivity, median connectivity and max connectivity, with the optimal threshold indicated for constructing the network. The selected power (β = 5) represents the minimal value satisfying the scale-free topology criterion while preserving sufficient network connectivity for module detection. (B) Hierarchical clustering dendrogram of Müller glial subpopulations based on gene expression profiles. The tree showed clustering of the different gene modules identified in the analysis, with modules labeled Müller-M1 to Müller-M6. Each module represents a set of co-expressed genes associated with specific biological functions in Müller glial subpopulation. (C) Module feature plots showing the expression patterns of each module (M1-M6) within Müller cell subpopulations. For each module, cells were colored by module expression level (low to high), illustrating the distribution of module activity across Müller cell subpopulations. (D) The module membership (kME) for all genes was calculated, and the top-ranked 10 genes within each module were visualized using PlotKMEs. (E) Dot plots respectively showing the expression of distinct gene co-expression modules in Müller glial cell subpopulation and the module expression within subpopulations under different conditions. (F) Co-expression network comprising the top five hub genes from each co-expression module. (G) Network graphs showing hub-gene networks constructed from the top 25 core genes of modules 1 and 6; the inner ring denotes the top 10 hub genes and the outer ring denotes the remaining 15. (H, I) Bar charts showing functional enrichment terms for the top 100 genes from modules 1 and 6. (J) PPI network analysis of genes in Module 6, showing the top 10 hub genes selected based on connectivity scores. (K) Western blot validation of JUNB protein expression levels in the Ctrl and STZ groups (N = 3), confirming differential expression. * indicates p < 0.05.

    Article Snippet: Membranes were blocked with 5% nonfat milk in TBST for 1 h at room temperature and incubated overnight at 4 °C with primary antibodies against JUNB (Abmart, T55894 , 1:2000), CEBPB (Abmart, T55276 , 1:2000), and β-actin (Affinity, AF7018, 1:20000).

    Techniques: Expressing, Functional Assay, Selection, Preserving, Gene Expression, Labeling, Activity Assay, Construct, Western Blot, Biomarker Discovery, Quantitative Proteomics

    (A) Log2(fold change) of the four guides targeting JunB (red) compared to the distribution of all sgRNA guides from the GM12878 and P3HR-1 Avana dropout screen. Fold change was calculated comparing abundance of sgRNA day 21 post selection versus input. (B) JunB sgRNA abundances in Brunello and Avana dropout screens. Log 2 JunB sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (C) c-Jun sgRNA abundances in Brunello and Avana dropout screens. Log 2 c-Jun sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (D) JunD sgRNA abundances in Brunello and Avana dropout screens. Log 2 JunD sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (E) JunB dependency across CRISPR DepMap lymphoid cell lines ( DepMap.org ). Gene dependency scores were calculated by comparing JunB sgRNA abundance in individual lymphoid cell lines 21 days post lentivirus library transduction and selection in comparison to input library abundance. Each circle indicates an individual lymphoid cell line. Circle size represents Log JunB reads from RNA-seq analysis (DepMap, Broad, DepMap Public 25Q3 (2025)) Green circles versus clear circles indicate DepMap Burkitt versus non-Burkitt lymphoid cell lines, respectively. P-values were determined by one-sided Fisher’s exact test. * p<0.05, **p<0.005, ***p<0.0005

    Journal: bioRxiv

    Article Title: CRISPR Screens Reveal Epstein-Barr Virus-activated JunB as a Key Lymphoblastoid B cell Dependency Factor that Represses Cyclin Dependent Kinase Inhibitor P18INK4c

    doi: 10.64898/2026.03.31.715635

    Figure Lengend Snippet: (A) Log2(fold change) of the four guides targeting JunB (red) compared to the distribution of all sgRNA guides from the GM12878 and P3HR-1 Avana dropout screen. Fold change was calculated comparing abundance of sgRNA day 21 post selection versus input. (B) JunB sgRNA abundances in Brunello and Avana dropout screens. Log 2 JunB sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (C) c-Jun sgRNA abundances in Brunello and Avana dropout screens. Log 2 c-Jun sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (D) JunD sgRNA abundances in Brunello and Avana dropout screens. Log 2 JunD sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (E) JunB dependency across CRISPR DepMap lymphoid cell lines ( DepMap.org ). Gene dependency scores were calculated by comparing JunB sgRNA abundance in individual lymphoid cell lines 21 days post lentivirus library transduction and selection in comparison to input library abundance. Each circle indicates an individual lymphoid cell line. Circle size represents Log JunB reads from RNA-seq analysis (DepMap, Broad, DepMap Public 25Q3 (2025)) Green circles versus clear circles indicate DepMap Burkitt versus non-Burkitt lymphoid cell lines, respectively. P-values were determined by one-sided Fisher’s exact test. * p<0.05, **p<0.005, ***p<0.0005

    Article Snippet: Antibodies against the following proteins were used in this study: JunB (Cell Signaling Technology, #3753), c-Jun (Cell Signaling Biotechnology, #9165), JunD (Cell Signaling Biotechnology, #5000), β-Actin (Biolegend, #664802), LMP1 (Abcam, ab78113), LMP2A (Abcam, ab59028), EBNA2 PE2 (a gift from Fred Wang), DDX1 (Bethyl, A300-521A-M), Myc (Santa Cruz Biotechnology, SC-40), p100/p52 (EMD Millipore, 05-361), TRAF1 (Cell Signaling Biotechnology, #4715S), HA tag antibody (Cell Signaling Technology, # 3724), BIM (Cell Signaling Biotechnology, #2933), CCND2 (Proteintech, 10934-1-AP), EBNA1 (a gift from Jaap Middeldorp), and EBNA3C A10 (hybridoma from Martin Rowe’s group[ ]).

    Techniques: Selection, Sequencing, CRISPR, Transduction, Comparison, RNA Sequencing

    (A) Validation of JunB CRISPR-Cas9 knockout in MUTU I and GM15892 cells. Immunoblot was performed on WCL from Cas9+ MUTU I and GM15892 cells transduced with control or JunB sgRNA seven days post-selection using indicated antibodies. (B) Mean ± SD live cell numbers of Cas9+ MUTU I or GM11830 cells expressing control or JunB targeting single guide RNAs (sgRNA) from n=3 replicates. Cells transduced with lentiviruses expressing the indicated sgRNAs were puromycin selected. Cell numbers two days following puromycin selection (defined as day 0 of the graph) were set to 1. Live cell numbers were quantitated by CellTiter-Glo assay (C) Investigation of impact of JunB on other Jun AP-1 transcription factors. Immunoblot analysis of WCL from Cas9+ GM12878 cells transduced with control or JunB sgRNAs, ten days post selection, with indicated antibodies. Densitometry ratios of JunB and JunD to β-Actin is shown. (D) Investigation of combinatorial impact of JunB and JunD on LCL growth. (Left) Mean ± SD live cell numbers of Cas9+ GM12878 cells expressing control, JunD, JunB, or JunB+JunD targeting single guide RNAs (sgRNA) from n=3 replicates. Cells transduced with lentiviruses expressing control or JunD sgRNA were Zeocin selected two days post transduction. After one week, cells were then transduced with a separate control or JunB sgRNA. Cell numbers two days following puromycin selection (defined as day 0 of the graph) were set to 1. Live cell numbers were quantitated by CellTiter-Glo assay. (Right) Immunoblot validation of JunB and JunD knockouts. WCL of GM12878 cells transduced with both zeocin and puromycin sgRNAs was extracted two days following puromycin selection and immunoblot was performed using indicate antibodies. (E) PI cell cycle stainin of GM12878 cells transduced with JunB sgRNA. Representative FACS cell cycle plots from n=3 replicates of GM12878 cells analyzed ten days post selection. P-values were determined by one-sided Fisher’s exact test. * p<0.05, **p<0.005, ***p<0.0005

    Journal: bioRxiv

    Article Title: CRISPR Screens Reveal Epstein-Barr Virus-activated JunB as a Key Lymphoblastoid B cell Dependency Factor that Represses Cyclin Dependent Kinase Inhibitor P18INK4c

    doi: 10.64898/2026.03.31.715635

    Figure Lengend Snippet: (A) Validation of JunB CRISPR-Cas9 knockout in MUTU I and GM15892 cells. Immunoblot was performed on WCL from Cas9+ MUTU I and GM15892 cells transduced with control or JunB sgRNA seven days post-selection using indicated antibodies. (B) Mean ± SD live cell numbers of Cas9+ MUTU I or GM11830 cells expressing control or JunB targeting single guide RNAs (sgRNA) from n=3 replicates. Cells transduced with lentiviruses expressing the indicated sgRNAs were puromycin selected. Cell numbers two days following puromycin selection (defined as day 0 of the graph) were set to 1. Live cell numbers were quantitated by CellTiter-Glo assay (C) Investigation of impact of JunB on other Jun AP-1 transcription factors. Immunoblot analysis of WCL from Cas9+ GM12878 cells transduced with control or JunB sgRNAs, ten days post selection, with indicated antibodies. Densitometry ratios of JunB and JunD to β-Actin is shown. (D) Investigation of combinatorial impact of JunB and JunD on LCL growth. (Left) Mean ± SD live cell numbers of Cas9+ GM12878 cells expressing control, JunD, JunB, or JunB+JunD targeting single guide RNAs (sgRNA) from n=3 replicates. Cells transduced with lentiviruses expressing control or JunD sgRNA were Zeocin selected two days post transduction. After one week, cells were then transduced with a separate control or JunB sgRNA. Cell numbers two days following puromycin selection (defined as day 0 of the graph) were set to 1. Live cell numbers were quantitated by CellTiter-Glo assay. (Right) Immunoblot validation of JunB and JunD knockouts. WCL of GM12878 cells transduced with both zeocin and puromycin sgRNAs was extracted two days following puromycin selection and immunoblot was performed using indicate antibodies. (E) PI cell cycle stainin of GM12878 cells transduced with JunB sgRNA. Representative FACS cell cycle plots from n=3 replicates of GM12878 cells analyzed ten days post selection. P-values were determined by one-sided Fisher’s exact test. * p<0.05, **p<0.005, ***p<0.0005

    Article Snippet: Antibodies against the following proteins were used in this study: JunB (Cell Signaling Technology, #3753), c-Jun (Cell Signaling Biotechnology, #9165), JunD (Cell Signaling Biotechnology, #5000), β-Actin (Biolegend, #664802), LMP1 (Abcam, ab78113), LMP2A (Abcam, ab59028), EBNA2 PE2 (a gift from Fred Wang), DDX1 (Bethyl, A300-521A-M), Myc (Santa Cruz Biotechnology, SC-40), p100/p52 (EMD Millipore, 05-361), TRAF1 (Cell Signaling Biotechnology, #4715S), HA tag antibody (Cell Signaling Technology, # 3724), BIM (Cell Signaling Biotechnology, #2933), CCND2 (Proteintech, 10934-1-AP), EBNA1 (a gift from Jaap Middeldorp), and EBNA3C A10 (hybridoma from Martin Rowe’s group[ ]).

    Techniques: Biomarker Discovery, CRISPR, Knock-Out, Western Blot, Transduction, Control, Selection, Expressing, Glo Assay

    (A) CCND2 sgRNA abundances in Brunello P3HR-1 and GM12878 dropout screens. Log 2 CCND2 sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (B) CCND2 transcript levels during EBV-mediated B cell transformation. RNAseq was performed on primary B cells infected with B95-8 virus on indicated days post infection (dpi). Normalized reads for CCND2 are shown. (C) Immunoblot analysis of CCND2 levels in response to LMP1 expression. Daudi Burkitt cells harboring selectively inducible WT or transformation effector site (TES) mutant LMP1 cassettes were mock induced or treated with 250 ng / mL doxycycline for 24 hours. Cells were then harvested and lysates analyzed via immunoblot with indicated antibodies. (D) Effect of JunB knockout on CCND2 levels. Cas9+ P3HR-1, Jijoye, or GM12878 cells expressing control or JunB sgRNAs. Seven days post selection, WCL was extracted from cells and immunoblot performed using indicated antibodies. P-values were determined by one-sided Fisher’s exact test. * p<0.05, **p<0.005, ***p<0.0005

    Journal: bioRxiv

    Article Title: CRISPR Screens Reveal Epstein-Barr Virus-activated JunB as a Key Lymphoblastoid B cell Dependency Factor that Represses Cyclin Dependent Kinase Inhibitor P18INK4c

    doi: 10.64898/2026.03.31.715635

    Figure Lengend Snippet: (A) CCND2 sgRNA abundances in Brunello P3HR-1 and GM12878 dropout screens. Log 2 CCND2 sgRNA abundances from GM12878 (red) and P3HR-1 (blue) cells 21 days post library selection were determined via deep sequencing and compared to input library sgRNA abundance (green). (B) CCND2 transcript levels during EBV-mediated B cell transformation. RNAseq was performed on primary B cells infected with B95-8 virus on indicated days post infection (dpi). Normalized reads for CCND2 are shown. (C) Immunoblot analysis of CCND2 levels in response to LMP1 expression. Daudi Burkitt cells harboring selectively inducible WT or transformation effector site (TES) mutant LMP1 cassettes were mock induced or treated with 250 ng / mL doxycycline for 24 hours. Cells were then harvested and lysates analyzed via immunoblot with indicated antibodies. (D) Effect of JunB knockout on CCND2 levels. Cas9+ P3HR-1, Jijoye, or GM12878 cells expressing control or JunB sgRNAs. Seven days post selection, WCL was extracted from cells and immunoblot performed using indicated antibodies. P-values were determined by one-sided Fisher’s exact test. * p<0.05, **p<0.005, ***p<0.0005

    Article Snippet: Antibodies against the following proteins were used in this study: JunB (Cell Signaling Technology, #3753), c-Jun (Cell Signaling Biotechnology, #9165), JunD (Cell Signaling Biotechnology, #5000), β-Actin (Biolegend, #664802), LMP1 (Abcam, ab78113), LMP2A (Abcam, ab59028), EBNA2 PE2 (a gift from Fred Wang), DDX1 (Bethyl, A300-521A-M), Myc (Santa Cruz Biotechnology, SC-40), p100/p52 (EMD Millipore, 05-361), TRAF1 (Cell Signaling Biotechnology, #4715S), HA tag antibody (Cell Signaling Technology, # 3724), BIM (Cell Signaling Biotechnology, #2933), CCND2 (Proteintech, 10934-1-AP), EBNA1 (a gift from Jaap Middeldorp), and EBNA3C A10 (hybridoma from Martin Rowe’s group[ ]).

    Techniques: Selection, Sequencing, Transformation Assay, RNA sequencing, Infection, Virus, Western Blot, Expressing, Mutagenesis, Knock-Out, Control