EMBO/soda-nel huggingface dataset:
CDK12 drives breast tumor initiation and trastuzumab resistance via WNT and IRS1-ErbB-PI3K signaling (2019)
Figure 2

Figure 2. CDK12 regulates cancer stemness and response to trastuzumab therapy in HER2+ breast cancer.

A FACS analysis of the percentages of CD44+/CD24−/ESA+ breast CSC-like populations in CDK12-overexpressing ZR-75-30 and HCC-1419 cells and CDK12-siRNA-transfected BT474 and HCC-1954 cells. Top, representative dot plot of CD44-APC versus CD24-PE expression for viable cells (red) and ESA-positive cells (blue) from the viable cells. Bottom, the percentage of CD44+/CD24-/ESA+ cell population (blue dots at lower right quadrant in the plots) was quantified in the indicated cell lines. Mean ± s.d. of three independent samples. P-values were based on two-tailed Student's t-test (ZR-75-30 and HCC-1419 cells) and one-way ANOVA with a post-hoc LSD test (BT474 and HCC-1954 cells). Amp, amplification; non-amp, non-amplification; Trz, trastuzumab.

B ALDEFLUOR assay for analysing cell population with a high ALDH activity in the indicated cell lines. Cells either treated with ALDH inhibitor DEAB (with DEAB; negative control) or untreated (without DEAB) were incubated with ALDEFLURO substrate (BAAA). In the FACS analysis, the percentage of ALDEFLUOR-positive population was determined based on the shift of fluorescent cells seen in the dot plots in the absence of DEAB. Mean ± s.d. . P-values were calculated based on a two-tailed Student's t-test

C The self-renewal of CSCs in the indicated stable cell lines was analysed using a tumorsphere-formation assay. The number of tumorsphere cells (> 100 μm in diameter) was counted after 3, 5, and 7 days. Data represent the mean ± s.d. (n = 3). P-value was calculated based on a two-tailed Student's t-test (ZR-75-30 and HCC-1419 cells) or ANOVA with a post-hoc LSD test (BT474 and HCC-1954 cells).

D Cell growth of the indicated stable cell lines treated with trastuzumab (Trz) or vehicle (veh) as measured by SRB assay. Trastuzumab-sensitive HER2+ breast cancer cell lines (S) and trastuzumab-insensitive HER2+ breast cancer cell lines (partial responsive, PR; resistant, R) were treated with 1 µg/mL or 100 µg/mL trastuzumab, respectively. Data represent the mean ± s.d. P-values were calculated using RM ANOVA with a post-hoc LSD test.

E Analysis of the effect of CDK12 deficiency on the in vivo trastuzumab response of HER2+ breast cancer. Mice were orthotopically xenografted with the indicated HER2+ breast cancer cells and treated with 20 mg/kg trastuzumab. The growth curve of each group was analysed twice weekly for 5 to 6 weeks (n = 8/group; mean ± s.e.m.). P-values were calculated using one-way ANOVA with a post-hoc LSD test for the last day of tumor measurement.

In B-E, cell line information was indicated as follows: a/a, CDK12-amplified/HER2-amplified cells; n/a, CDK12 non-amplified/HER2-amplified cells; R, trastuzumab-resistant; PR, trastuzumab-partial responsive; S, trastuzumab-sensitive.

Source data are available online for this figure.
CDK12 drives breast tumor initiation and trastuzumab resistance via WNT and IRS1-ErbB-PI3K signaling (2019)
Figure 3

Figure 3. Targeting CDK12 kinase activity inhibits the expression of activators of multiple oncogenic signaling cascades and tumor growth in HER2+ breast cancer.

A Heatmap presents the alteration of gene expression (≥1.5-fold) between control (CON) and CDK12-overexpressing (CDK12) ZR-75-30 cells obtained from RNA-seq analysis.

B GSEA displaying correlations of the gene-expression profiles between control and CDK12-overexpressing cells based on RNA-seq results.

C Venn diagram presenting the number of common genes from RNA-seq results as compared with dinaciclib-target genes (GSE8882226[]) and the PolII ChIP-seq results (GSE7202328[]).

D The CDK12-target genes identified by RNA-seq were validated in CDK12-overexpressing ZR-75-30 cells using qRT-PCR analysis. Mean ± s.d. (n = 3). P-values by two-tailed Student's t-test.

E ChIP-qPCR analysis displaying the fold-enrichment of the indicated proteins and histone H3 acetylation at the TSS of CDK12-target genes in the indicated cell lines. Mean ± s.d. (n = 3). P-values by two-tailed Student's t-test.

F Effect of CDK12 kinase inhibition on the expression of WNT1, WNT3, and IRS1. Cells were treated with different doses of dinaciclib for 12 h, and the expression of candidate targets of CDK12 were analysed by immunoblot and qRT-PCR Mean ± s.d. (n = 3). P-values by ANOVA with a post-hoc LSD test.

G Cell viability was measured by SRB assay in trastuzumab-sensitive BT474 cells and trastuzumab-resistant HCC-1954 cells treated with 1 µg/mL or 100 µg/mL trastuzumab (Trz) and/or 5 nM or 10 nM dinaciclib (Dina), respectively. Mean ± s.d. (n = 3). P-values, RM ANOVA with a post-hoc LSD test.

H Tumor growth curves for mice xenografted with the indicated HER2+ breast cancer cells treated with 20 mg/kg trastuzumab and/or 20 mg/kg dinaciclib (n = 8/group; mean ± s.e.m.). P-values, one-way ANOVA with a post-hoc LSD (BT474) or Dunnett T3 (HCC-1954) test for the last day of tumor measurement.

Cell line information: a/a, CDK12-amplified/HER2-amplified cells; n/a, CDK12 non-amplified/HER2-amplified cells; R, trastuzumab-resistant; S, trastuzumab-sensitive.

Source data are available online for this figure.
CDK12 drives breast tumor initiation and trastuzumab resistance via WNT and IRS1-ErbB-PI3K signaling (2019)
Figure 4

Figure 4. CDK12 regulates the WNT/β-catenin-signaling pathway via the upregulation of WNT ligands in HER2+ breast cancer.

A Western blot and qRT-PCR results showing phosphorylation levels of GSK-3β and WNT1 and WNT3 expression, respectively, in the indicated cell lines. Mean ± s.d. (n = 3). P-values by two-tailed Student's t-test. a/a, CDK12-amplified/HER2-amplified cells; n/a, CDK12 non-amplified/HER2-amplified cells; S, trastuzumab-sensitive

B, C Subcellular localization of β-catenin in the indicated stable cell lines were analysed by cellular fractionation (B) and immunofluorescence staining (C). Nuclear translocation of β-catenin in control, CDK12-overexpressing, and CDK12-knockdown stable cell lines was quantified by counting the cells harboring exclusively nuclear β-catenin (N) from the immunofluorescence image. Mean ± s.d. (n = 3). P-value was calculated using a two-tailed Student's t-test. M+C, cells containing membrane and/or cytoplasmic β-catenin; N, cells dominantly expressing nuclear β-catenin. Green, β-catenin staining; Blue, DAPI staining for visualization of nucleus; Scale bar = 10 μ. a/a, CDK12-amplified/HER2-amplified cells; n/a, CDK12 non-amplified/HER2-amplified cells; S, trastuzumab-sensitive.

D Luciferase-reporter assay measuring the TCF/ lymphoid enhancer-binding factor-promoter activity in the indicated cell lines. TOP, pTOP-flash (wild-type TCF-binding sites), FOP, pFOP-flash (mutant TCF-binding sites). Data represent the mean ± s.d. P-values were calculated using a two-tailed Student's t-test.

E The mRNA levels of the WNT/β-catenin/TCF-target genes in CDK12-overexpressing ZR-75-30 cells and CDK12-knockdown BT474 cells were analysed by qRT-PCR. Mean ± s.d. (n = 3). P-values were calculated using a two-tailed Student's t-test.

F Effect of WNT/ β-catenin/TCF pathway on the CDK12 regulation of breast CSCs. Cells were treated with DMSO (vehicle) or 10 nM FH535, a β-catenin/TCF inhibitor, for 24 h, and changes in the CD44+/CD24-/ESA+ cell population were measured using FACS analysis. Cells seen at lower right quadrant in the dot plots indicate CD44+/CD24- population (red) and CD44+/CD24-/ESA+ population (blue). Data represent the mean ± s.d. ofP-value was calculated using one-way ANOVA with a post-hoc LSD test.

Source data are available online for this figure.
CDK12 drives breast tumor initiation and trastuzumab resistance via WNT and IRS1-ErbB-PI3K signaling (2019)
Figure 5

Figure 5. CDK12 activates EGFR-HER2-PI3K-AKT signaling by upregulating IRS1 expression. A Human phospho-RTK array displaying the activation of phosphokinase-related proteins in CDK12-knockdown BT474 cells. The bar graph shows the fold change of spot intensity.

B Immunoblots showing the levels of the indicated proteins in different types of HER2+ breast cancer stably expressing CDK12 or with CDK12 knocked down.

C Co-IP analysis showing the amounts of bindings between ErbB receptors. Cell lysates from CDK12-overexpressing ZR-75-30 cells were immunoprecipitated with anti-HER2 antibody and immunoblotted using the indicated antibodies. IgG, negative control.

D Western blot and qRT-PCR analysis of the phosphorylation levels and expression of IRS1, respectively, in the indicated cell lines. Mean ± s.d. (n = 3). P-values were calculated using a two-tailed Student's t-test.

E Co-IP analysis indicating the amounts of IRS1 protein interaction with ErbB receptors and p85 in CDK12-overexpressing ZR-75-30 cells.

F IRS1 effect on CDK12-induced phosphorylation of ErbB receptors. Lysates from cells treated with either control siRNA or IRS1 siRNA (siIRS1) for 24 h were subjected to immunoblotting with the indicated antibodies.

G Proposed model for the mechanism of action of CDK12 regulation of cancer stemness, cell growth, and trastuzumab response in HER2+ breast cancer.

Cell line information: a/a, CDK12-amplified/HER2-amplified cells; n/a, CDK12 non-amplified/HER2-amplified cells; R, trastuzumab-resistant; PR, trastuzumab-partial responsive; S, trastuzumab-sensitive.

Source data are available online for this figure.

Extended view figure legends
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy. (2015)
Figure 1

Genetic and molecular features of XRCC4-mutant patients

Pedigree. Black symbols designate affected subjects.

Schematic view of wild-type and mutant (R225*) XRCC4 proteins with their main domains and phosphorylation sites. The numbering refers to amino acids of refseq: NP_071801.1. CTR: C-terminal region.

Electropherograms of the XRCC4 genomic region encompassing the nucleotide substitutions in available members of the family.

Quantitative real-time PCR of XRCC4 relative to GAPDH mRNA in affected (II-1 and II-2) and control (CT1 and CT2) fibroblasts. Each value refers to the mean of three independent experiments performed in duplicate. Error bars indicate the standard deviation.

Immunoblot analysis of total lysates from fibroblasts (fbs) and of in vitro-synthesized proteins (i.v.p). fl: in vitro-translated full-length XRCC4 protein; ret.: reticulocyte lysate used for in vitro protein synthesis; 225*: in vitro-translated XRCC4 R225* truncated protein; Ct: lysate of control fbs; and II-1 and II-2: lysates of fbs from patient II-1 and II-2. α-XRCC4 (Abcam, 1:1,000) and α-GAPDH antibodies were used.

Immunoblot analysis of total lysates from fibroblasts using α-LIG4 (GeneTex, 1:1,000) and α-SDHA antibodies. Ct: lysate of control fbs; II-1 and II-2: lysates of fbs from patient II-1 and II-2. The position of the molecular weight (MW) marker proteins is indicated.
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy. (2015)
Figure 2

Analysis of γ-H2AX nuclear foci

γ-H2AX nuclear foci in XRCC4wt and mutant fibroblasts (XRCC4m/m1 and XRCC4m/m2) were determined at different times after irradiation with 0.5 Gy of γ-rays. Values, subtracted of their non-irradiated control (1.3 foci/nucleus in XRCC4wt cells and 1.4 and 0.9 foci/nucleus in XRCC4m/m1 and XRCC4m/m2 cells, respectively), are the mean ± SD of three independent experiments.

Percentages of γ-H2AX foci in XRCC4wt and XRCC4m/m fibroblasts (pooled values) remaining at the indicated time-points.

Immunofluorescence micrographs of γ-H2AX foci in XRCC4wt and XRCC4m/m fibroblasts.

Data information: ***P < 0.001; **P < 0.01; *P < 0.05 (XRCC4m/m vs. XRCC4wt cells), two-way ANOVA, Bonferroni post hoc test.
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy. (2015)
Figure 3

γ-H2AX nuclear foci formation in different cell cycle phases

A, B Percentages of γ-H2AX nuclear foci remaining in CENP-F-negative (A) and CENP-F-positive (B) cells at the indicated time-points after irradiation with 0.5 Gy of γ-rays. Values, subtracted of their non-irradiated controls, are the mean ± SD of three independent experiments. ***P < 0.001; *P < 0.05 (XRCC4m/m versus XRCC4wt cells), two-way ANOVA, Bonferroni post hoc test.

C Immunofluorescence micrographs of γ-H2AX foci in CENP-F-positive and negative fibroblasts at 2 h after irradiation. Arrow heads indicate the CENP-F-positive cells.
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy. (2015)
Figure 4

Involvement of homologous recombinations in repairing DNA DSBs

RAD51 foci in XRCC4wt and XRCC4m/m fibroblasts irradiated with 0.5 Gy of γ-rays. Values are the mean ± SD of three independent experiments. ***P < 0.001; **P < 0.01 (XRCC4m/m versus XRCC4wt cells), two-way ANOVA, Bonferroni post hoc test.

Immunofluorescence micrographs of RAD51 foci in XRCC4wt and XRCC4m/m fibroblasts. Arrowheads indicate the CENP-F-positive cells.
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy. (2015)
Figure 5

Analysis of PARP-1 inhibition on DSB repair

XRCC4wt and XRCC4m/m cells irradiated with 0.5 Gy of γ-rays were exposed to the PARP1 inhibitor 3′-AB or to solvent (DMSO). The γ-H2AX foci number is the mean ± SD of three independent experiments. *P < 0.05 (XRCC4m/m + 3′-AB versus XRCC4m/m + DMSO), ***P < 0.001 (XRCC4m/m + 3′-AB versus XRCC4wt + 3′-AB), two-way ANOVA, Bonferroni post hoc test.
A nonsense mutation of human XRCC4 is associated with adult-onset progressive encephalocardiomyopathy. (2015)
Figure 6

Quantification of alternative non-homologous end-joining (A-NHEJ) activity

A, B Percentages of DSBs repaired in increasing time intervals (0.5–2 h, 0.5–6 h, 0.5–24 h) were calculated in XRCC4wt (A) and XRCC4m/m (B) cells from the number of γ-H2AX foci in presence or absence of a PARP-1 inhibitor, 3′-AB. **P < 0.01 (XRCC4m/m + 3′-AB versus XRCC4m/m + DMSO), two-way ANOVA, Bonferroni post hoc test.
Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures (2018)
Figure 1

Figure 1. Characterization of acutely isolated CD11b+CD45int cells. (A) FACS gating strategy representative of 5 independent experiments adopted to sort CD11b+CD45int microglia distinctly from CD11b+CD45high resident macrophages and CD11b-CD45high lymphocytes. (B) Analysis of relative transcript levels of CD11b+CD45int FACS-sorted microglia compared with whole brain tissue by qPCR. Gene expression levels of microglia (Olfml3, Fcrls, Tmem119, Siglech, Gpr34, P2ry12), astrocyte (Gfap, Gjb6, Ntsr2, Aldh1l1), oligodendrocyte (Mobp, Mog, Cldn1), and neuron (Tubb3, Vglut1, NeuN) markers. Bars represent mean (n=4; pool of 1 female and 1 male per biological replicate) of relative expression (Gapdh as housekeeping gene) ± SEM (*p < 0.05; **p < 0.01 by two-tailed Student's test). N.D. not detected. (C) Representative quantification of CD206 expression in CD11b+CD45int microglia and CD11b+CD45high resident macrophages. Values denote the percentage of the mean ± SEM of 5 independent experiments. (D) Representative images of 2 independent experiments showing microglia, resident macrophages and lymphocytes acquired with ImageStream imaging cytometer (Amnis) based on CD45, CD11b and CD206 expression levels (scale bar represents 7 µm).
Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures (2018)
Figure 2

Figure 2. LPS stimulation induces an intrinsic loss of the microglia homeostatic signature. (A-D) Three-four months old BL/6 mice were treated with an acute dose of LPS (4 µg/g body) or vehicle (saline). Microglia (pool of 2 mice per group per replicate; 1 female and 1 male) were FACS-sorted 24 hours later. (A) Gene expression levels of microglia homeostatic (Olfml3, Fcrls, Tmem119, Siglech, Gpr34, P2ry12, Mef2c), phagocytic (Tyrobp, Trem2), and inflammatory (Il1β, Tnf, Ccl2, Mrc1, Arg1) markers were analyzed by qPCR. Bars represent mean of relative expression (% of saline; Gapdh as housekeeping gene) ± SEM (*p < 0.05; **p < 0.01 by two-tailed Student's test; n=4). (B) Representative multicolour flow cytometry analysis of 5 independent experiments showing CD11b and CD45 positive populations in single viable cells in saline or LPS-injected mouse brains. (C) Representative multicolour flow cytometry analysis showing the percentage of the mean ± SEM of 5 independent experiments of Ly6C and CD206 expressing cells in CD11b+CD45int cells from saline or LPS-injected mice. (D) Gene expression levels of the monocytic markers Ly6c1 and Ccr2 in purified microglia (n=4) and isolated bone marrow monocytes (n=2) by qPCR. Bars represent mean of relative expression (Gapdh as housekeeping gene) ± SEM (**p < 0.01 by two-tailed Student's test). (E) Primary adult microglia were cultivated in the presence of TGF-β (50 μg/ml) and M-CSF (10 ng/ml), while neonatal cells were stimulated for 24 hours with TGF-β (50 μg/ml) followed by 6 hours stimulation with LPS (1 ng/mL) or left untreated. Expression levels of microglia homeostatic (Olfml3, Tmem119, Gpr34) and inflammatory (Il1β, Tnf, Ccl2) genes were analysed by qPCR. Bars represent mean of relative expression (Gapdh as housekeeping gene) ± SEM (**p < 0.01 by two-tailed Student's test; n=3).
Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures (2018)
Figure 3

Figure 3. Characterization of microglia activation at the single-cell level. (A) Heatmap showing clustering analysis of 1,247 single cells, featuring 100 most variable genes (FDR<0.05). Single-cell RNA-seq results are obtained from 2 mice per group (1 female and 1 male each). (B) 2D-tSNE representation of all single cells included in the study (n = 1,247) depicting the separation of microglia isolated from LPS-injected mice (770 cells in red) and steady state (477 cells in blue) in 2 main clusters. (C) Expression of specific homeostatic (Tmem119, P2ry12, Siglech) and inflammatory (Ccl2, Gpr84) genes overlaid on the 2D-tSNE space. Bars represent log2 (Count+1). (D) Representative multicolour flow cytometry analysis of 2 independent experiments showing TMEM119 and P2RY12 expression levels in CD11b+CD45int microglia of saline or LPS-injected mouse brains. For the unconjugated TMEM119 antibody, negative stands for primary antibody without secondary antibody. For P2RY12 antibody, negative represents isotype PE control.
Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures (2018)
Figure 4

Figure 4. Identification of microglia subpopulations under inflammatory conditions. (A) 2D-tSNE representation of 1,247 single cells isolated from naïve (blue) and LPS-treated mice showing two distinct subpopulations among the 770 cells isolated from LPS-injected mice (n = 703, red; n = 67, yellow). (B) Venn diagram showing 732 genes uniquely upregulated in the "main LPS" cluster (red) and 241 genes exclusively increased in the "subset LPS" (yellow) compared to their corresponding controls (blue) (FDR<0.05). A total of 274 genes were shared between the two LPS populations. (C) Venn diagram showing 1055 genes uniquely downregulated in the "main LPS" cluster (red) and 29 genes exclusively decreased in the "subset LPS" (yellow) compared to their corresponding controls (blue) (FDR<0.05). A total of 87 genes were shared between the two LPS populations. (D) Heatmap showing examples of specific genes mainly up-regulated in "main LPS" (Manf) or "subset LPS" (Ash1l) and down-regulated in "main LPS" (Mef2c) or "subset LPS" (Lamp1) overlaid on the 2D-tSNE space. Bars represent log2 (Count+1). (E) Gene set enrichment analysis (GO, top 10 biological processes) of 99 down-regulated and 397 up-regulated genes distinguishing cells in "subset LPS" versus "main LPS" (FDR<0.05).
Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures (2018)
Figure 5

Figure 5. Pseudotime analysis. (A) Branching analysis of LPS-activated microglia by Monocle 2 leads to 9 distinct clusters in a two-dimensional state space inferred by generalized regression modelling (see Materials and Methods) showing the major difference of "subset LPS" (in yellow) compared to the other clusters corresponding to "main LPS" (in red). (B) Monocle estimated a pseudotime for each cell along the inferred cell trajectory within the state space showing a delayed activation pattern of "subset LPS" compared to the other fractions. (C) Pseudotime dynamics of inflammatory (Ccl12, Ccl2, Gpr84) and homeostatic (Mef2c, P2ry12, Siglech) genes in dependence on inferred cell states.

TABLES AND THEIR LEGENDS

Table 1. List of top differentially expressed genes unique to "main LPS" or "subset LPS" versus PBS (FDR<0.05; upregulated genes, Log2FC≥3; downregulated genes, Log2FC≤-3).

EXPANDED VIEW FIGURE LEGENDS
Parkin inhibits BAK and BAX apoptotic function by distinct mechanisms during mitophagy (2018)
Figure 1

Figure 1 Parkin inhibits BAX-mediated apoptosis by indirect ubiquitination.

(A) Schematic of potential effects of activated Parkin on the BCL-2 family of apoptosis regulators.

(B) BAX/BAK-deficient HeLa cells reconstituted with BAX and where indicated HA-Parkin were treated with antimycin A and oligomycin (AO) for 2 h and then 1 µM of each of the BH3 mimetics ABT-737 and S63485 for 6 h. Cell death was assessed at the indicated times by LDH assay. Data is mean +/- SD of four independent experiments.

(C) BAX/BAK-deficient HeLa cells ectopically expressing BAX and Parkin were treated with antimycin A and oligomycin (AO, 3 h), MG132 (20 µM, 3.5 h) and BH3 mimetics (1 µM of each of ABT-737 and S63485, 1 h). Cytosol and membrane fractions were immunoblotted as indicated. Graph shows densitometric analysis of non-ubiquitinated membrane proteins (top, relative to untreated control) or cytochrome c release (bottom; cytosol/cytosol+membrane, relative to untreated controls) from three independent experiments. Error bars represent mean +/- SD.

(D) BAX/BAK-deficient HeLa cells ectopically expressing BAX were treated and analysed as in (C).

(E) UBA pull-down of ubiquitinated proteins following antimycin A and oligomycin (AO) treatment of BAX/BAK-deficient HeLa cells ectopically expressing HA-Parkin and BAX for 3 h. Representative immunoblot from two independent experiments.
Parkin inhibits BAK and BAX apoptotic function by distinct mechanisms during mitophagy (2018)
Figure 2

Figure 2 Parkin ubiquitinates BAK on a conserved lysine in the hydrophobic groove.

(A) Subcellular fractionation of cytosol and membrane fractions of HeLa cells expressing HA-Parkin following 2 h of antimycin A and oligomycin (AO) treatment.

(B) Immunoblotting of whole cell lysates immunoblotted following treatment with antimycin A and oligomycin (AO) for 3 h with MG132 (20 µM). Graph shows densitometric analysis of non-ubiquitinated proteins relative to untreated control from three independent experiments. Error bars represent mean +/- SD.

(C) UBA pull-down of ubiquitinated proteins following antimycin A and oligomycin (AO) treatment for 3 h and treatment with the non-specific DUB USP2 for 30 min at 37°C, representative immunoblot from two independent experiments. (D) Structure of human BAK (PDB 2IMS) with the hydrophobic binding groove comprising α-helices 3-5 highlighted in blue. The ubiquitination site, K113, (red) resides in the binding groove. A modelled transmembrane anchor (α9) and the C-terminal K210 localised to the inter-membrane space is based on evidence that the BAK transmembrane anchor spans the mitochondrial outer membrane (Iyer et al CDD, 2014). The orientation of the soluble portion (α-helices 1-8) of BAK with respect to the mitochondrial outer membrane is hypothetical.

(E) Whole cell lysates of HA-Parkin and BAK variant-expressing HeLa cells following 3 h antimycin A and oligomycin (AO) treatment with 30 min pre-treatment with MG132 (20 µM), representative immunoblots from three independent experiments.