EMBO/soda-nel huggingface dataset:
MITOL prevents ER stress-induced apoptosis by IRE1α ubiquitylation at ER-mitochondria contact sites (2019)
Figure 6

Figure 6. MAM is required for IRE1α ubiquitylation by MITOL

(A) Accumulations of MITOL and IRE1α in the MAM fraction. Each organelle fraction was isolated from MEFs by percoll density-gradient centrifugation, followed by immunoblotting with indicated antibodies. mito: pure mitochondria, micro: microsome, cyto: pure cytosol.

(B) High solubility of MITOL and IRE1α in the low dose digitonin. Raft-like structure including MAM was solubilized from the crude mitochondrial fraction of MEFs with indicated concentration of digitonin. S: supernatant, P: pellet.

(C, D) IRE1α regulation by MITOL occurred in the MAM-rich mitochondrial fraction. Crude mitochondrial fraction containing MAM (Mito plus MAM) and the cytosolic fraction containing ER (Cyto plus ER) were isolated from HEK293 cells transfected with indicated vector and subsequently immunoprecipitation assay was performed to detect the interaction between MITOL and IRE1α (C) or the level of IRE1α ubiquitylation (D).

(E) Knockdown of PACS2 impaired the interaction of MITOL with IRE1α. HEK293 cells were transfected with either scramble RNA or siPACS2 and indicated vectors for 24 hours prior to immunoprecipitation assay.

(F, G) Knockdown of PACS2 or Mfn2 inhibited IRE1α ubiquitylation by MITOL. HEK293 cells were transfected with either scramble RNA, siPACS2 or siMfn2 and indicated vectors 24 hours prior to immunoprecipitation assay.
MITOL prevents ER stress-induced apoptosis by IRE1α ubiquitylation at ER-mitochondria contact sites (2019)
Figure 7

Figure 7. IRE1α hyper-activation accompanying with apoptosis in the MITOL-KO spinal cord under ER stress

(A) MITOL ubiquitylated IRE1α in the spinal cord of mice. Lysates of the spinal cord in mice were immunoprecipitated with anti-IRE1α antibody, followed by immunoblotting with indicated antibodies. WT: MITOLF/F mice, MITOLnestin: MITOLF/F, Nestin-Cre mice.

(B) Loss of MITOL led to hyper-oligomerization of IRE1α in the spinal cord under ER stress. 3 month-old WT or MITOLnestin mice were treated with 1 mg/kg Tu for 24 hours. Spinal cord was solubilized with NP-40 lysis buffer and separated by sucrose-density gradient centrifugation.

(C-E) MITOL deletion resulted in hyper-activation of IRE1α RNase in ER stress. WT or MITOLnestin mice were injected with Tu for 24 hours and spinal cord was analyzed by qRT-PCR. Error bars represent SD (n=3). *p<0.05, **p<0.01 (Student's t test).

(F, G) Increased ER stress-induced apoptosis in the MITOL-KO spinal cord. 3 month-old WT or MITOLnestin mice were treated with Tu for 24 hours and each spinal cord was stained using TUNEL and hoechst (F) or cresyl violet (G). The right panels show 2-fold magnification images of the boxed regions. Arrowheads indicate the representative neurons. Scale bar represents 50 µm (F) or 20 µm (G). Error bars represent SD (n=3). *p<0.05 (Student's t test).

Expanded view Figure legends
Pseudouridylation of 7SK snRNA promotes 7SK snRNP formation to suppress HIV-1 transcription and escape from latency (2016)
Figure 1

Figure 1. Most cellular 7SK RNA including those bound to P-TEFb are pseudouridylated at U250.

A. 7SK was divided into 6 non-overlapping fragments and in vitro transcribed in the presence of 32p-UTP for use in an in vitro modification assay. U250 in fragment 5 is highlighted in red. B. In vitro modification reactions containing the six fragments and HeLa NE were performed. After nuclease P1 digestion, the products were analyzed by 1D-TLC with pU and pΨ as controls. C. WT and mutant 7SK fragment 5 containing U250G were analyzed as in B. D. Outline of the biotin-facilitated extraction and analysis of the modification status of site-specifically labeled nucleotides in 7SK by 1D-TLC. E. 7SK RNA, generated by either in vitro transcription (IVT) or purified from HeLa total RNA and then site-specifically labeled at the indicated positions by the procedure in D, was analyzed by 1D-TLC. F. Cyber Gold staining of 7SK obtained by either IVT or immunoprecipitation (IP) with the indicated antibodies. G. 2D-TLC analysis of 32p-labeled mononucleotides derived from IVT or CDK9-bound 7SK RNA, with the first panel depicting a schematic migration pattern of the indicated 5’-phosphorylated mononucleotides. H. 7SK RNA, obtained by either IVT or anti-CDK9 IP and then site-specifically labeled at the indicated positions by the procedure in D, was analyzed by 1D-TLC.
Pseudouridylation of 7SK snRNA promotes 7SK snRNP formation to suppress HIV-1 transcription and escape from latency (2016)
Figure 2

Figure 2. Ψ250 in 7SK RNA is critical for 7SK RNP formation.

A, B, G, and M. Sequence alternations in WT and 7SK RNA mutants mut1, mut2 and mut3, were shown in shaded boxes. U250 is marked in red. The tag refers to a 6-nt sequence replacement to enable discrimination from endogenous 7SK by primer extension. L. Alignment between the 7SK sequences (black) flanking U250 (red) and a portion of the box H/ACA snoRNA (blue) showing base-pairing between the two. The altered nucleotides in shaded boxes were introduced into 7SK to disrupt the base-pairing. C-F; H-K; and N-Q. The tagged WT or mutant 7SK RNA was co-transfected with the indicated Flag- or HA-tagged proteins into HeLa cells. Anti-Flag or –HA immunoprecipitates (IP) were analyzed by immunoblotting for the indicated proteins and primer extension for the bound 7SK RNA. R. The indicated 7SK were in vitro transcribed in the presence of 32p-UTP and subjected to in vitro modification reactions. The nuclease P1-digested products were analyzed by 1D-TLC with pU and pΨ as controls.
Pseudouridylation of 7SK snRNA promotes 7SK snRNP formation to suppress HIV-1 transcription and escape from latency (2016)
Figure 3

Figure 3. DKC1-H/ACA snoRNP is responsible for 7SK pseudouridylation and DKC1 KD releases P-TEFb from 7SK RNP to form Brd4-P-TEFb and Tat-SEC complexes.

A. Anti-V5 immunoprecipitates (IP) from HeLa cells expressing nothing (-) or V5-DKC1 were analyzed by immunoblotting for V5-DKC1 and qRT-PCR for the bound 7SK RNA. The error bars represent mean ± SD from three independent experiments. B. Anti-Flag IP from NE of HeLa or the HeLa-derived F1C2 cells expressing CDK9-F were analyzed by Western blotting (WB) for the indicated proteins and primer extension (PEx) for 7SK RNA. C. WB analysis of DKC1 and CDK9 levels in two HeLa clones inducibly expressing shDKC1 upon doxycycline (DOX) treatment for 5 days. D. The 7SK RNA levels in these two clones were detected by qRT-PCR before and after the DOX treatment and normalized to the GAPDH mRNA levels. The error bars represent mean ± SD from three independent experiments. E. 1D-TLC analysis of Ψ250 in 7SK RNA from inducible DKC1 KD clone 1 before and after the DOX treatment. F. NE and anti-CDK9 IP from NE of inducible DKC1 KD clone 1, which was untreated or treated with DOX, were analyzed by WB for the indicated proteins and PEx for 7SK RNA. G. Clone 1 was treated with DOX for 3 days and then transfected with the Tat-Flag cDNA (20 ug/150-mm dish). Two days later, NE and anti-Flag IP from NE were analyzed as in F.
Pseudouridylation of 7SK snRNA promotes 7SK snRNP formation to suppress HIV-1 transcription and escape from latency (2016)
Figure 4

Figure 4. DKC1 KD preferentially activates Tat-dependent HIV-1 transcription and latency reversal by increasing SEC binding to HIV-1 promoter.

A. Luciferase activities were measured in HeLa cells transfected with the indicated reporter constructs, an empty vector (-) or the Tat cDNA, and either siDKC1 or a non-target siRNA (siNT). For each reporter, the activity in cells expressing siNT was set to 1. B, C, and E. The mRNA levels of luciferase (B) or Tat (C & E) in cells expressing the indicated siRNAs were determined by qRT-PCR and normalized to the GAPDH mRNA and plotted. D. NH1 cells containing the integrated HIV-1 LTR-luciferase reporter and expressing Tat were transfected with siDKC1 or siNT. ChIP-qPCR analysis was performed to determine the levels of the indicated factors bound to the HIV-1 promoter. The signals were normalized to those of input and plotted. F. Western analysis of DKC1 and CDK9 levels in a Jurkat 2D10-derived clone inducibly expressing shDKC1 upon exposure to DOX. G and H. The inducible DKC1 KD clone, treated or untreated with DOX for 4 days, was incubated with the indicated concentrations of JQ1 (G) or prostratin (H) for 24 h. The GFP expression was measured by flow cytometry and expressed as percentages of GFP(+) cells of the entire population. The error bars in all panels represent mean ± SD from three independent experiments, and the p values determined by the Student’s t-test.
High-throughput metabolomics predicts drug-target relationships for eukaryotic proteins (2022)
Figure 2

Fig. 2. Hit characterization for drug-target predictions

(A) For drug-gene comparisons with a logistic fit quality in the top 10% of all those compared for each gene, the maximum absolute Spearman correlation coefficient for each hit comparison is shown in descending order. The horizontal dashed line indicates the maximum absolute correlation coefficient for the comparison of the metabolome of cells treated with the STE2 agonist alpha factor to STE2 overexpression conditions. The position of a STE2 to alpha factor comparison is indicated with a yellow star.

(B) The number of metabolites that change significantly when wild-type yeast and mutants in the predicted target are treated with the indicated drugs at a concentration of 10 µM are shown. Drugs targeting GPR1 are written in black text, with drugs targeting SNF3 and RGT2 written in purple and green respectively. Orange filled bars are predicted antagonists for GPR1.

(C) The levels of trehalose compared to a DMSO treated control are shown for both wild-type yeast and gpr1 strains treated with predicted antagonists for GPR1. The bar height indicates mean values, and error bars indicate the standard deviation of the mean. Asterisks indicate a p-value of less than 0.05 from a two-sided student's T-test (n = 4 biological replicates) when comparing The WT and gpr1 reponses to the drug. Results are representative of 3 independent experiments.
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 1

Figure 1. miR-515-5p expression changes the tubulin cytoskeleton and inhibits migration of breast and lung cancer cells. (A) miR-515-5p expression increases the area of the tubulin cytoskeleton. Tubulin (green) and cell nucleus (blue). Objective x20. Bar: 200 µm. (B-C) miR-515-5p inhibits random (B) and directed (C) cell migration. The indicated cell lines were transfected with miR-515-5p for 48 h before time-lapse imaging was performed for 18 h (A) or transwell migration assays were performed for 9 h (C). (B-left panel) Plots show overlays of representative trajectories travelled. (B-right panel) The distance of migration was quantified and represented as the mean ± SEM of values normalised to the respective control condition. (C-left panel) Representative field of view from the bottom of the transwell chambers. Scale bar is 20 µm. (C-right panel) Data represent percentage of the average number migratory cells per field (n=5 fields per condition). Data are mean of three experiments ± SEM. (B-C) P values were calculated by t-test between miRNA (515-5p) values and their respective non-targeting control miR (NC) values (***, P<0.001). All data shown are representative of experiments performed at least in triplicate.
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 2

Figure 2. miR-515-5p regulates mRNAs involved in cell migration. (A) RNA-seq of MCF7 and MDA-MB-231 transfected with miR-515-5p revealed the down-regulation of five transcripts, NRAS, FZD4, CDC42BPA, PIK3C2B and MARK4. (B-D) The effect of miR-515-5p overexpression on NRAS, FZD4, CDC42BPA, PIK3C2B and MARK4 mRNA levels in MCF7 (B), MDA-MB-231(C), A549 and H1299 (D) was determined by qPCR 48 h following transfection of the indicated cell line with non-targeting control miR (NC) or miR-515-5p. Data is displayed as the normalised mean ± SEM. P values were calculated by t-test between miRNA conditions and their respective NC conditions (*, P<0.05; **, P<0.01; ***, P<0.001). (E-F) miR-515-5p directly interacts with NRAS, MARK4 and PI3KC2B’s 3’UTR. Relative luciferase activity levels were measured 24 h after co-transfection of MCF-7 (E) and MDA-MB-231 (F) with 3’UTR-luciferase reporter constructs and either with miR-515-5p or miR NC. Data shown are normalised mean of three independent experiments ± SEM. (B-F) P values were calculated by t-test between miRNA conditions and their respective NC conditions (*, P<0.05; **, P<0.01; ***, P<0.001).
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 3

Figure 3. MARK4 knockdown mimics the effect of miR-515-5p overexpression. MARK4 siRNA-mediated silencing increases the tubulin cytoskeletal area (A) and reduces random (B) and directed (C) migration in MDA-MB-231 (MDA), A549 and H1299 cells. (A) Data shown are representative of experiments performed in triplicate. Bar graph represents the average ± SEM of n ≥ 50 per technical replicate with 3 technical replicates per conditions. Cells were transfected either with siRNA targeting MARK4 (M4) or a non-targeting control (NC) for 48 h before time-lapse imaging was performed for 18 h (B) or transwell assay for 9h (C). (B-top panel) Plots show overlays of representative trajectories described. (B-bottom panel) The migration distance was quantified and represented as the normalised mean ± SEM. (C-top panel) Representative field of view from the bottom side of the transwell membrane. (C-bottom panel) Graphs indicate cell migration expressed as a percentage of the average of migratory cells per field (n=5 fields per condition). (B-C) Data are mean of three experiments ± SEM. (A-C) P values were calculated by t-test between the siRNA-transfected and the respective control condition (***P<0.001).
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 4

Figure 4. MARK4 over-expression rescues the inhibitory effects of miR-515-5p on cell migration. (A-B) The indicated cell lines were transfected with either miR515-5p or a non-targeting miR (miR NC) together with a MARK4 expressing or an empty vector (EV) plasmid DNA. MARK4 over-expression rescues the inhibition by miR-515-5p of random (A) and directed (B) migration of the indicated cell lines. (A-left panel) Plots show overlays of representative trajectories described for MDA-MB-231 cells (n=30). (A-right panel) The migration distance was quantified and represented as the normalised mean ± SEM. (B-left panel) Representative field of view from the bottom side of the transwell membrane for MDA-MB-231. (B-right panel) Graphs indicate cell migration expressed as a percentage of the average of migratory cells per field (n=5 fields per condition). Data are mean of three experiments ± SEM. (A-C) P values were calculated by t-test between the transfected and the respective control condition (EV+miR-NC) (*,P<0.05; **,P<0.01; ***,P<0.001).
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 5

Figure 5. MARK4 expression levels increase during tumorigenesis and correlate poor patient prognosis. (A-B) Overall survival of ER-negative metastatic breast cancer (n=226) (A) and lung adenocarcinoma (n=719) (B) patients according to MARK4 mRNA levels found in their tumors was represented using the Kaplan Meier-plotter [25]. (C) A cDNA array for 24 matched lung cancers and surrounding normal tissue was analysed for MARK4 expression. Expression levels from tumors were normalised to their respective normal control and the percentage of cases for the indicated fold expression in the tumor represented as a pie-chart. (D-F) MARK4 protein expression was determined by histoimmunochemistry in (D-E) a tissue microarray comprising 90 lung tumor and 10 normal lung samples or (F) a home-made tissue microarray comprising 100 matched cases of primary and metastatic tumors. (D-E) The percentage of positivity for MARK4 staining in lung tumors versus normal lung samples (D) or in lung tumors according to their histological subtypes (E) is represented. (F) The percentage of cases with increased, decreased or unchanged levels of MARK4 in metastatic lesions as compared to the corresponding primary tumors is represented.
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 6

Figure 6. miR-515-5p expression is inversely correlated with breast cancer metastasis and correlates with good patient prognosis. (A-D) Low expression of miR-515-p is linked to survival in both Lung and Breast cancer. (A) Survival analysis of miR-515-5p from 195 lung adenocarcinoma samples from the TCGA. (B) Survival analysis of miR-515-p from 34 lung squamous cell carcinoma from the TCGA. (C) Survival analysis of miR-515-5p from 60 Breast cancer samples from the Lyng Ditzel Breast Study (GSE37405). (D) Survival analysis of miR-515-5p from 33 Breast cancer from the GSE7405 Breast study. Analysis and plot were obtained with SurvMicro http://bioinformatica.mty.itesm.mx:8080/Biomatec/Survmicro.jsp for (A-C) and with MIRUMIR for (D). (E) Comparison of miR-515-5p expression in 18 primary and matched metastatic lesions from breast cancer patients. miR-515-5p levels were quantified by TaqMan qRT-PCR. Absolute values were normalized to u6 snRNA values and displayed as a dot-plot. Bar; Mean, Whiskers; SEM. (F) MDA-MB-231 cells were inoculated into the mammary fat pads of nude mice and allowed to form metastatic deposits [22]. miR-515-5p and MARK4 levels were then determined in the primary and indicated secondary lesions. Data are average ± SEM of technical triplicates. (G) Luciferase-expressing A549 cells overexpressing miR-515-5p or a non-targeting control (miR-NC) were injected in the tail-vein of SCID mice and the development of tumor burden monitored by whole animal-imaging in response to luciferin administration at week 1 and 4 following injection. (G-left panel) Representative imaging of the same animals for the indicated conditions at week 1 and 4. (G-Right panel) The emitted photons were quantified and the signals normalised to the corresponding readings at week 1. Data represented are representative of three independent experiments. (E-G) P values were calculated by t-test (*, P<0.05; **, P<0.01; ***, P<0.001).
miR-515-5p controls cancer cell migration through MARK4 regulation (2016)
Figure 7

Figure 7. miR-515-5p overexpression or siRNA-mediated MARK4 silencing prevents A549 cell metastasis to the lung. A549-Luc cells transfected either with miR-515-5p precursor (miR), siRNAs to MARK4 (siMARK4) or the corresponding control sequences (C and NT, respectively) were injected in Scid mice through the tail vein. 4 weeks later, the mice were sacrificed, their lungs extracted and fixed prior to staining for Luciferase expression. (A) Representative pictures showing the presence of A549-Luc cells in the lungs of NT mice either as single cells (upper panel) or as a tumour mass (lower panel). (B) Percentage of the area covered by tumour cells on randomly observed fields of views. Quantification was performed using Photoshop CS4. Each spot corresponds to quantification of an individual 1 mm x 1.5 mm field. Transversal bar; Median. Statistics: Student t-test. *, p≤0.05. (C) Schematic summary. Increase in MARK4 expression is the main reason for miR-515-5p-down-regulated cells to show increased metastatic abilities in breast and lung cancer. The down-regulation of miR-515-5p de-represses MARK4 translation in individual cells from the primary tumour promoting their metastatic dissemination through the blood or lymphatic circulation and reducing patients’ survival.
CUEDC2 modulates cardiomyocytes oxidative capacity by regulating GPX1 stability (2016)
Figure 1

Figure 1. CUEDC2 degradation was induced by ischemia-reperfusion in cardiac tissue.

A CUEDC2 protein levels in mouse tissues. Adult (12-week-old) mouse was sacrifices and total protein was extracted from the liver, kidney, lung, spleen, heart, stomach, intestine, prostate, testis, brain, and thymus.

B (top) In vivo cardiac ischemia-reperfusion model protocol (30-minute ischemia followed by indicated times of reperfusion). (bottom) Mice were subjected to reversible ischemia in vivo for 30 minutes and reperfused for different time period. Protein was extracted from the area at risk of heart at the indicated time points and subjected to immunoblot analysis of CUEDC2 and CUEDC1. Representative results were shown from 2 mice at each time point, and experiments were repeated for three times.

C Isolated primary rat neonatal cardiomyocytes were treated to hypoxia with serum free-medium for 6h and reoxygenated accompanying adding serum back for different time period in vitro and the protein level of CUEDC2 was tested at different time points during reoxygenation. Each experiment was repeated for three times.

D CUEDC2 protein level was plotted using the immunohistochemical scores as described in methods. (left) Plot of CUEDC2 scores in each BZ and DZ (n = 9 patients). (right) Representative images from immunohistochemical staining for CUEDC2 in tissues from patients who suffered acute myocardial infarctions. The boxed areas in the left images are magnified in the middle and right images. DZ, distant zone; BZ, border zone. Scale bars, 250 μm (left), 50 μm (middle and right). * p = 0.001.

Data information: Data were shown as mean ± SEM and analyzed by paired t-test.
CUEDC2 modulates cardiomyocytes oxidative capacity by regulating GPX1 stability (2016)
Figure 2

Figure 2. Ablation of CUEDC2 promotes cardiomyocytes survival by enhancing antioxidant capacity.

A Primary mouse cardiomyocytes were treated with H2O2 (1 mM) for 3 hours and cardiomyocyte viability was determined by flow cytometry. Representative results of flow cytometry analysis.

B Quantitative analysis of PI-positive cells treated with H2O2 was shown (42.9 ± 3.1% in wild-type group vs. 10.1 ± 4.4% in Cuedc2-/- group, * p = 0.0004, n = 5 wells per group and repeated for three times).

C Neonatal mouse cardiomyocytes were subjected to hypoxia for 6 hours and then reoxygenation for 30 minutes. Cardiomyocytes were then stained with 5 μM CellROX® Deep Red Reagent and analyzed by flow cytometry. Representative results of flow cytometry analysis are shown, and all experiments were repeated for three times.

D ROS levels were quantitated and summarized. * p = 0.0108, n = 3 wells per group and repeated for three times.

E HPLC detection of a superoxide probe oxidized dihydroethidium (DHE) product in sham and I/R injury heart tissue (30-min ischemia followed by 30-min reperfusion), 2-hydroxyethidium (EOH), a specific product for superoxide anion radical. *p < 0.0001, n = 5 in each group.

F In the same samples of (E), HPLC detection of ethidium (E), oxidized by other reactive oxygen species such as H2O2 (mainly) and ONOO. *p = 0.0001, n = 5 in each group.

Data information: Data were shown as mean ± SEM and analyzed by unpaired t-test.