Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Dual role of the peptide-loading complex as proofreader and limiter of MHC-I presentation

doi: 10.1073/pnas.2321600121

Figure Lengend Snippet: Deletion of PLC components reduces MHC-I surface levels and changes the MHC-I surface composition. MHC-I surface levels of HAP1 cells with single knockouts of PLC components (wt, gray; ΔHLA, red; ΔTAP1, dark blue; ΔTAP2, light blue; ΔTSN, orange; ΔCRT, yellow; ΔERp57, green; ΔERAP1, purple). Flow cytometric analysis of total MHC-I (W6/32), A*02:01 (BB7.2), and B*40:01 (JOAN-1) surface levels was performed by using the respective primary antibody and Nb AF647 . Exemplary histograms and surface quantity of total MHC-I ( A ), A*02:01 ( B ), and B*40:01 ( C ) molecules per cell. The number of MHC-I surface molecules was determined by using Quantum TM AF647 MESF microspheres and normalizing to ΔHLA cells (mean ± SD, n = 4). Proportion of A*02:01 ( D ), B*40:01 ( E ), and the sum of A*02:01 and B*40:01 proportions ( F ) of the total MHC-I molecules (mean ± SD, n = 4). Dark and light colors correspond to A*02:01 and B*40:01 molecules, displayed in ( D ) and ( E ), respectively. The black dashed line represents the value of wt cells. Welch ANOVA comparing ΔTAP1, ΔTAP2, ΔTSN, ΔCRT, ΔERp57, and ΔERAP1 with HAP1 wt cells was performed (ns, nonsignificant; * P < 0.05; ** P < 0.01; *** P < 0.001).

Article Snippet: HAP1 wt cell line (HLA allomorphs A*02:01, B*40:01, C*03:04) and HAP1 knockout cell lines (ΔHLA with knockouts of HLA-A, -B, -C, and -G, ΔTAP1, ΔTSN, ΔCRT, ΔERp57, ΔERAP1) were kindly provided by Robbert Spaapen (Sanquin Research, Netherlands) ( ).

Techniques:

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Dual role of the peptide-loading complex as proofreader and limiter of MHC-I presentation

doi: 10.1073/pnas.2321600121

Figure Lengend Snippet: Knockout of PLC components increases the ratio of suboptimally loaded A*02:01 surface complexes. Flow cytometric analyses of extracellular peptide exchange on HAP1 wt cells and HAP1 cells with knockouts of individual components of the antigen-processing machinery after pulsing with ELA ( Top ) or TQV ( Bottom ) peptide (1 µM each). ELA and TQV peptide were used crosswise for background correction. ( A ) Activation of the reporter T cells DMF5 NFκB::eGFP ( Top ) and 1G4 NFκB::eGFP ( Bottom ) upon coculture with pulsed HAP1 cells. T cell activation was determined by eGFP median fluorescence intensity (MFI) and normalized to coculture with HAP1 wt cells (mean ± SD, n = 4). ( B ) Number of ELA-A2*02:01 ( Top ) and TQV-A2*02:01 complexes ( Bottom ) per cell was determined by using the enhanced-affinity sTCRs MEL5 Spy-AF647 and 1G4 Spy-AF647 , respectively, and Quantum TM AF647 MESF microspheres (mean ± SD, n = 4). ( C ) Presentation of ELA-A2*02:01 ( Top ) and TQV-A2*02:01 complexes ( Bottom ) in relation to A*02:01 levels and HAP1 wt cells, illustrating the relative peptide exchange (mean ± SD, n = 4). The black dashed line represents the value of HAP1 wt cells. Welch ANOVA comparing ΔTAP1, ΔTAP2, ΔTSN, ΔCRT, ΔERp57, and ΔERAP1 with HAP1 wt cells was performed (ns, nonsignificant; * P < 0.05; ** P < 0.01; *** P < 0.001).

Article Snippet: HAP1 wt cell line (HLA allomorphs A*02:01, B*40:01, C*03:04) and HAP1 knockout cell lines (ΔHLA with knockouts of HLA-A, -B, -C, and -G, ΔTAP1, ΔTSN, ΔCRT, ΔERp57, ΔERAP1) were kindly provided by Robbert Spaapen (Sanquin Research, Netherlands) ( ).

Techniques: Knock-Out, Activation Assay, Fluorescence

Journal: Proceedings of the National Academy of Sciences of the United States of America

Article Title: Dual role of the peptide-loading complex as proofreader and limiter of MHC-I presentation

doi: 10.1073/pnas.2321600121

Figure Lengend Snippet: Deficiencies in the editing module lead to elevated presentation of abundant, high-affinity peptides. Flow cytometric analyses of ELA-A*02:01 and TQV-A*02:01 presentation by HAP1 wt cells and HAP1 cells with knockouts of individual components of the antigen-processing machinery upon transfection with plasmids encoding for peptide expression of either ELA ( Top ) or TQV ( Bottom ). ELA and TQV peptide were used crosswise for background correction. ( A ) Activation of DMF5 NFκB::eGFP ( Top ) and 1G4 NFκB::eGFP ( Bottom ) reporter T cells upon coculture with peptide-expressing HAP1 cells. T cell activation was determined by eGFP MFI and normalized to coculture with HAP1 wt cells (mean ± SD, n = 4). ( B ) Number of ELA-A2*02:01 ( Top ) and TQV-A2*02:01 complexes ( Bottom ) per peptide-expressing cell was determined by using enhanced-affinity sTCRs MEL5 Spy-AF647 and 1G4 Spy-AF647 , respectively, and Quantum TM AF647 MESF microspheres (mean ± SD, n = 4). ( C ) Presentation of ELA-A2*02:01 ( Top ) and TQV-A2*02:01 complexes ( Bottom ) in relation to A*02:01 levels in peptide-expressing HAP1 cells and HAP1 wt cells (mean ± SD, n = 4). The black dashed line represents the value of HAP1 wt cells. Welch ANOVA comparing ΔTAP1, ΔTAP2, ΔTSN, ΔCRT, ΔERp57, and ΔERAP1 with HAP1 wt cells was performed (ns, nonsignificant; * P < 0.05; ** P < 0.01; *** P < 0.001).

Article Snippet: HAP1 wt cell line (HLA allomorphs A*02:01, B*40:01, C*03:04) and HAP1 knockout cell lines (ΔHLA with knockouts of HLA-A, -B, -C, and -G, ΔTAP1, ΔTSN, ΔCRT, ΔERp57, ΔERAP1) were kindly provided by Robbert Spaapen (Sanquin Research, Netherlands) ( ).

Techniques: Transfection, Expressing, Activation Assay

Journal: Molecular Biology of the Cell

Article Title: Myosin IIA drives membrane bleb retraction

doi: 10.1091/mbc.E18-11-0752

Figure Lengend Snippet: MIIA but not MIIB is necessary for bleb retraction. (A) Laser-induced polar cortex ablation in control, MIIA- or MIIB-depleted HeLa cells. Representative control DIC montage shows the ablation ROI (magenta circle) used to create a membrane bleb (yellow arrow). Dotted yellow line represents ROI used to create kymographs. Representative kymographs for each condition are shown below. White arrows show the measurement method for calculating retraction rates. (B) Tukey plots comparing bleb retraction rates for controlled and spontaneous blebs in control vs. MIIA lo or MIIB lo cells. Controlled blebs: n = 25 control, 15 MIIA lo and 25 MIIB lo cells from three independent experiments. Spontaneous blebs: n = 18 control blebs from 9 cells, 15 MIIA lo blebs from 10 cells, 15 MIIB lo blebs from 10 cells over three independent experiments. (C) Representative time montage of HeLa cell coexpressing MIIA mApple and MIIB mEmerald showing the ablation ROI (magenta circle). Representative kymographs created using the solid white line show MIIA and MIIB recruitment to the bleb. Yellow ROI shows the region of the kymograph compared for recruitment (first 60 s). (D) Comparison of IIA and IIB recruitment to blebs in HeLa and HAP1 fibroblasts. n = 10 cells for each cell line over three independent experiments. Exact p values stated over respective bars. Solid black circles represent outliers. Scale bar: 10 µm.

Article Snippet: To that end, we used a myh9 (MIIA) knockout HAP1 cell line we previously generated using CRISPR ( Fenix et al. , 2016 ), which expresses only MIIB (Supplemental Figure S1).

Techniques: Control, Membrane, Comparison

Journal: Molecular Biology of the Cell

Article Title: Myosin IIA drives membrane bleb retraction

doi: 10.1091/mbc.E18-11-0752

Figure Lengend Snippet: The motor domain and nonhelical tailpiece of MIIA are sufficient to drive bleb retraction. (A) Representative kymographs from HAP1 parental and myh9 KO cells following cortex ablation. n = 21 parental cells and 12 KO cells over three independent experiments. (B) Representative DIC and fluorescence images showing the localization of MII paralogues and mutants in HAP1 KO cells. (C) Representative kymographs from MIIA, MIIB, and MIIC expressing HAP1 KO cells following cortex ablation, as in . Tukey plots comparing retraction rates in HAP1 KO cells expressing MIIA, MIIB, or MIIC, and Cos7 cells expressing MIIA, MIIB, MIIC, or untransfected (UT). For HAP1 KO cells, n = 27 MIIA, 10 MIIB, and 15 MIIC expressing cells over more than three independent experiments. For Cos7 cells, n = 16 untransfected, 16 MIIA, 11 MIIB, and 10 MIIC expressing cells over three independent experiments. (D) Representative kymographs showing MIIA N93K, MIIA/B, MIIB/A, and MIIA/B/A expressing HAP1 KO cells following cortex ablation. (E) Retraction rates comparing mutants shown in D. n = 21 N93K, 18 MIIA/B, 8 MIIB/A, and 21 MIIA/B/A expressing cells over more than three independent experiments. MIIA bar is from the same data set as C and is displayed only for comparison. Exact p values stated over respective bars. Solid circles in Tukey plots represent outliers. Scale bar: 10 µm.

Article Snippet: To that end, we used a myh9 (MIIA) knockout HAP1 cell line we previously generated using CRISPR ( Fenix et al. , 2016 ), which expresses only MIIB (Supplemental Figure S1).

Techniques: Fluorescence, Expressing, Comparison

Journal: Molecular Biology of the Cell

Article Title: Myosin IIA drives membrane bleb retraction

doi: 10.1091/mbc.E18-11-0752

Figure Lengend Snippet: MIIA shows fast turnover compared with MIIB and MIIC at the cortex. (A) Representative time montages from two separate cells showing FRAP of MIIA and MIIB mEGFP expressed in HeLa cells. Inset shows an enlarged view of the yellow box. Dotted white box represents the bleaching region. (B) Averaged FRAP curves for MIIA and MIIB in HeLa cells. n = 15 cells each for MIIA and MIIB over three independent experiments. See Materials and Methods for the curve fitting method. (C, D) Averaged FRAP curves for MIIA and MIB mEGFP (C), and MIIC mEGFP (D) expressed in HAP1 KO cells. (E) Tukey plots showing time for half-maximal recovery for MIIA, MIIB, and MIIC in HAP1 KO cells. n = 11 MIIA, 13 MIIB, and 11 MIIC expressing cells over three independent experiments. (F) Tukey plots showing time for half-maximal recovery for MIIA, MIIB, and MIIC in Cos7 cells. n = 11 MIIA, 9 MIIB, and 10 MIIC expressing cells over three independent experiments. Exact p values stated over respective bars.

Article Snippet: To that end, we used a myh9 (MIIA) knockout HAP1 cell line we previously generated using CRISPR ( Fenix et al. , 2016 ), which expresses only MIIB (Supplemental Figure S1).

Techniques: Expressing

Journal: Molecular Biology of the Cell

Article Title: Myosin IIA drives membrane bleb retraction

doi: 10.1091/mbc.E18-11-0752

Figure Lengend Snippet: The motor domain and nonhelical piece of MIIA both contribute to turnover at the cortex. (A) Averaged FRAP curves for full-length MIIA (from ) and MIIA N93K mutant. (B) Tukey plots comparing time for half-maximal recovery for MIIA, MIIA N93K, MIIA/B, MIIB, and MIIA/B/A in HAP1 KO cells. n = 12 N93K, 10 MIIA/B, and 13 MIIA/B/A expressing cells over three independent experiments. The MIIA and MIIB data sets are the same as and are only shown for comparison. (C) Averaged FRAP curves for MIIA (from ), MIIA/B, and MIIA/B/A chimera. Exact p values stated over respective bars.

Article Snippet: To that end, we used a myh9 (MIIA) knockout HAP1 cell line we previously generated using CRISPR ( Fenix et al. , 2016 ), which expresses only MIIB (Supplemental Figure S1).

Techniques: Mutagenesis, Expressing, Comparison

Journal: Molecular Biology of the Cell

Article Title: Myosin IIA drives membrane bleb retraction

doi: 10.1091/mbc.E18-11-0752

Figure Lengend Snippet: Phosphorylation of the nonhelical tailpiece regulates turnover at the cortex. (A) Representative DIC and fluorescence images showing localization of MII mutants in HAP1 KO cells. (B) Tukey plots comparing time for half-maximal recovery for MIIA tail mutants. n = 10 MIIA Δtailpiece and 12 MIIA S1943A expressing cells over three independent experiments. The MIIA FRAP data set is the same as and is shown only for comparison. (C) Representative kymographs for MIIA Δtailpiece and MIIA S1943A following cortex ablation in HAP1 KO cells. (D) Tukey plots comparing bleb retraction rates in HAP1 KO cells for MIIA tail mutants. n = 17 MIIA Δtailpiece and 15 MIIA S1943A expressing cells over three independent experiments. The MIIA data set is the same as in and is shown only for comparison. (E) DIC image of Scr control M2 cell 5 h postplating. (F) Representative kymographs for bleb retraction in Scr vs. MIIA lo , MIIB lo , and MIIC lo M2 cells during interphase. (G) Tukey plots comparing bleb retraction rates for Scr vs. MIIA lo , MIIB lo , and MIIC lo M2 cells. Scale bars in A and E: 10 and 5 µm, respectively. Exact p values stated over respective bars. Solid circles represent outliers.

Article Snippet: To that end, we used a myh9 (MIIA) knockout HAP1 cell line we previously generated using CRISPR ( Fenix et al. , 2016 ), which expresses only MIIB (Supplemental Figure S1).

Techniques: Phospho-proteomics, Fluorescence, Expressing, Comparison, Control

Journal: BMC Biology

Article Title: Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library

doi: 10.1186/s12915-020-00905-1

Figure Lengend Snippet: Selected Cas9-expressing single cell clones show stronger editing efficiency compared to a Cas9 bulk population. a Workflow for the selection of Cas9 single-cell clones (SCCs). SCCs were sorted from the HAP1 Cas9 bulk population and further characterized. Cas9 editing was assessed by cell surface marker knockout followed by FACS staining and cell viability upon knockout of a core essential gene. Two highly editing single-cell clones (SCC11 and SCC12) were selected for further experiments. b HAP1 Cas9 bulk, Cas9 SCC11, and Cas9 SCC12 cells were transfected with the HDCRISPRv1 vector encoding an sgRNA targeting either the safe harbor locus AAVS1 as a control or the core essential gene RNA Polymerase 2 subunit E ( POLR2E ). Editing efficiency based on cell viability of sgPOLR2E-transfected cells in comparison to sgAAVS1 control cells was addressed by crystal violet staining. The number of surviving cells was strongly reduced in cells transfected with an sgRNA directed against POLR2E ( n = 3 for each cell line and sgRNA). c Editing efficiency was furthermore assessed upon transduction of HAP1 Cas9 bulk, Cas9 SCC11, and Cas9 SCC12 cells with the HDCRISPRv1 vector expressing sgRNAs targeting the surface marker CD46 , followed by FACS staining of residual CD46 protein to address knockout efficiency. Antibody staining of the non-edited cell lines was used as a control. Lines represent the mean of independent measurements ( n = 3 for each cell line and condition)

Article Snippet: The HAP1 cell line was authenticated using Multiplex Cell Authentication by Multiplexion (Heidelberg, Germany) as described recently [ ].

Techniques: Expressing, Clone Assay, Selection, Marker, Knock-Out, Staining, Transfection, Plasmid Preparation, Control, Comparison, Transduction

Journal: BMC Biology

Article Title: Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library

doi: 10.1186/s12915-020-00905-1

Figure Lengend Snippet: The HD CRISPR library efficiently identifies core, non- and context-dependent essential genes. a Workflow of a pilot screen conducted with the HD CRISPR library in HAP1 cells. The screen was performed in parallel in the Cas9-expressing bulk population and two highly editing single cell clones for both libraries independently. Successfully transduced cells were selected with puromycin for 48 h and then split into two independent replicates. The screen was performed for a duration of 14 days. b Core essential genes were strongly depleted over the course of screening with either of the two libraries, HD CRISPR libraries A and B, in contrast to nonessential genes. Stronger depletion was observed in the two single cell clones with high Cas9 editing efficiency. c Empirical cumulative distribution function for viability screens conducted with different HAP1 Cas9 cell lines and both HD CRISPR sub-libraries. Shown are results for sgRNAs targeting genes from core essential or nonessential gene sets or representing non-targeting controls. d Area under the curve (AUC) values for individual replicates of the empirical cumulative distribution functions shown in c . e Comparison of HAP1 essential genes as identified with the HD CRISPR library, a gene trap screen by Blomen et al. and two CRISPR screens using either the TKOv1 or TKOv3 library by Hart et al. . f Number of essential genes detected with increasing number of sgRNAs per gene using BAGEL (left; BF > 6) or MAGeCK RRA (right; FDR < 5%). sgRNAs were subsampled from the combined HD CRISPR library (sub-libraries A and B). Each data point represents the average of 5 samples. Error bars are ±1 s.e.m

Article Snippet: The HAP1 cell line was authenticated using Multiplex Cell Authentication by Multiplexion (Heidelberg, Germany) as described recently [ ].

Techniques: CRISPR, Expressing, Clone Assay, Comparison

Journal: BMC Biology

Article Title: Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library

doi: 10.1186/s12915-020-00905-1

Figure Lengend Snippet: CRISPR screens conducted at a high dynamic range predict the cutting efficiency of sgRNAs based on mild viability phenotypes. a A mixture model was used to divide control sgRNAs of the HD CRISPR library A in the single cell clone SCC12 screen into three groups: (1) sgRNAs with a target-dependent viability phenotype (red), (2) sgRNAs with a small target-independent phenotype likely caused by a double-strand break (blue), and (3) sgRNAs with no phenotype due to a lack of DNA cutting (yellow). Log2 fold change distributions of targeting and non-targeting control sgRNAs are indicated as dashed and solid curves, respectively. b Number of sgRNAs targeting nonessential HAP1 genes associated with each phenotype group. Nonessential genes were determined using MAGeCK which requires no prior knowledge for analysis. sgRNAs are stratified based on their design: “empirical essential” sgRNAs target context-specific essential genes and were selected for the HD CRISPR library based on their previous on-target phenotypes. “Empirical nonessential” sgRNAs are part of previously published libraries and target broadly nonessential genes. They were selected based on their lack of outlier phenotypes. De novo sgRNAs were designed using the software cld

Article Snippet: The HAP1 cell line was authenticated using Multiplex Cell Authentication by Multiplexion (Heidelberg, Germany) as described recently [ ].

Techniques: CRISPR, Control, Software

Journal: BMC Biology

Article Title: Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library

doi: 10.1186/s12915-020-00905-1

Figure Lengend Snippet: HAP1 cells are highly dependent on Yamanaka factors and the Fanconi anemia pathway. a HAP1 context-dependent essential genes are enriched for genes comprising the Fanconi anemia pathway as well as factors known to induce pluripotency. The y -axis provides an estimate of the percentage of essentiality in other cell lines previously screened. Fanconi anemia pathway genes are highlighted in red, Yamanaka factors are shown in blue. HAP1-specific nonessential genes are highlighted in green. nt ctrl = non-targeting control. b Crystal violet staining of HAP1 cells treated with various siRNAs targeting SOX2 , POU5F1 , and KLF4 and a non-targeting control. Shown is a representative result of three independent experiments. c Essentiality of known cancer drivers, Fanconi anemia pathway genes, and pluripotency factors across cell lines representing different cancer cell types in comparison to HAP1 cells and human embryonic stem cells

Article Snippet: The HAP1 cell line was authenticated using Multiplex Cell Authentication by Multiplexion (Heidelberg, Germany) as described recently [ ].

Techniques: Control, Staining, Comparison

Journal: bioRxiv

Article Title: Targeting EIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer

doi: 10.1101/2023.09.28.559973

Figure Lengend Snippet: A, Immunoblotting analysis of tumors that were treated with vehicle or Zotatifin in vivo. n = 5 biological replicates per group. B and C, QPCR analysis for Sox4 ( B ) and Fgfr1 ( C ) mRNA expression in tumors that were treated with vehicle or Zotatifin in vivo. Data are presented as mean ± SEM and analyzed using two-tailed unpaired Student’s t -test. n=5 biological replicates per group. D, Immunoblotting analysis of 2153L cells that were treated with different concentrations of Zotatifin for 6 hrs in vitro. E, Immunoblotting analysis of 2153L cells that were treated with 40 nM Zotatifin for different time periods. F, Immunoblotting analysis of BT549 cells that were treated with 40 nM Zotatifin for different time periods. * denotes a non-specific band. In D - F , data are representative of three independent experiments. G, Immunoblotting analysis of HAP1 cells that were treated with 40 nM Zotatifin in vitro. Data are representative of two independent experiments. H, Illustration for polysome profiling analysis. I and J, Polysome profiling of 2153L cells that were treated with vehicle or 40 nM Zotatifin for 2 hrs. I, Representative polysome profiles from three biological replicates. J , Distribution of Sox4 and Fgfr1 mRNAs across the different fractions. Data are presented as mean ± SEM of three biological replicates.

Article Snippet: 4T1 and E0771 cells were acquired from Dr. Xiang Zhang’s laboratory at BCM ( ) and cultured in DMEM (GenDEPOT #CM002-050) supplemented with 10% FBS and 1X Antibiotic-Antimycotic, HAP1 cells were acquired from eFFECTOR therapeutics ( ) and cultured in IMDM (Thermo Fisher #12440046) supplemented with 10% FBS and 1X Antibiotic-Antimycotic.

Techniques: Western Blot, In Vivo, Expressing, Two Tailed Test, In Vitro

Journal: bioRxiv

Article Title: Targeting EIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer

doi: 10.1101/2023.09.28.559973

Figure Lengend Snippet: A, QPCR analysis of tumors that were treated with vehicle or Zotatifin in vivo. The mean mRNA levels of the vehicle groups were set as 1 and fold changes were calculated for each gene. n=5 biological replicates per group. B, QPCR analysis of 8 paired biopsies from pre-treatment (black) and on Zotatifin treatment (red) ER+ breast cancer patients. The mRNA levels of pre-treatment samples were set as 1 and fold changes were calculated for each paired sample. C, QPCR analysis of HAP1 cells that were treated with 40 nM Zotatifin for 6 hrs. D ata are representative of two independent experiments and are presented as mean ± SD of technical triplicates. D, QPCR analysis of 2153L cells that were transfected with negative control siRNA with or without Zotatifin treatment, or Sox4 siRNAs without Zotatifin treatment for 48 hrs. E, QPCR analysis of Zotatifin-induced gene fold changes in 2153L cells that were transfected with negative control siRNA or Sox4 siRNAs in the presence of vehicle or Zotatifin. In D and E , representative data from three biological replicates were shown, and data are presented as mean ± SD of technical duplicates.

Article Snippet: 4T1 and E0771 cells were acquired from Dr. Xiang Zhang’s laboratory at BCM ( ) and cultured in DMEM (GenDEPOT #CM002-050) supplemented with 10% FBS and 1X Antibiotic-Antimycotic, HAP1 cells were acquired from eFFECTOR therapeutics ( ) and cultured in IMDM (Thermo Fisher #12440046) supplemented with 10% FBS and 1X Antibiotic-Antimycotic.

Techniques: In Vivo, Transfection, Negative Control