**Figure 4. Bid Phosphorylation on Serine 66 Sensitizes Cells to Apoptosis during Mitotic Arrest**(A) RKO cells stably infected with pVenus, pVenus-shBid, or pVenus-shBid coexpressing the indicated mouse (left panel) and human (right panel) BidYFP variants under the ubiquitin promoter were analyzed by immunoblotting with an antibody that recognizes both human and mouse Bid. Immunoblotting for Erk was used as a loading control. Endogenous human Bid is only present in the control cells.(B) The control RKO lines and those expressing mouse BidYFP variants were untreated or treated with 1 μM paclitaxel for 18 hr. Lysates were analyzed by immunoblotting for Bid and active caspase 3. Erk was a loading control. Note the shift in mobility of BidYFP-WT and BidYFP-G94E in paclitaxel-treated RKO cells.(C) The RKO lines from (A), untreated or treated with 1 μM paclitaxel for 18 hr, were immunostained for active caspase 3 and apoptosis quantified. The data represent the mean of three independent experiments. The error bars represent SEM. Data were analyzed by ANOVA.(D) Images of the paclitaxel-treated RKO cell lines from (C), immunostained for active caspase 3. Nuclei were stained with Hoechst.(E) Bid⁻/⁻ MEFs, infected with the indicated pVenus lentiviruses, were left untreated or treated with 1 μM paclitaxel. Apoptosis was quantified as above. The data represent the mean of three independent experiments. The error bars represent SEM. Data were analyzed by ANOVA.(F) RKO cells infected with the indicated lentiviruses expressing human Bid or human BidS67A were treated with paclitaxel as in (C). Cells showed similar responses to those expressing the mouse BidYFP. The data represent the mean of three independent experiments. The error bars represent SEM. Data were analyzed by ANOVA.(G) The indicated RKO lines, untreated or treated with monastrol for 18 hr, were immunostained for active caspase 3 and apoptosis quantified. The data represent the mean of three independent experiments. The error bars represent SEM. Data were analyzed by ANOVA.

To test if Bid-pS66 regulates apoptosis during mitotic arrest, we generated stable RKO lines where endogenous hBid was knocked down and substituted by mouse BidYFP-WT, BidYFP-S66A, BidYFP-S66D, or BidYFP-G94E. As expression of mBidYFP was signiﬁcantly higher than endogenous hBid using the original pVenus vector with an EF1a promoter (Figure S3A), we replaced it with an ubiquitin (Ub) promoter. This led to expression of mBidYFP at levels comparable to endogenous hBid (Figures 4A and S3B). When the RKO lines were treated with paclitaxel for 18 hr, although BidYFP-WT rescued apoptosis following endogenous Bid knockdown, neither Bi-dYFP-S66A nor BidYFP-G94E BH3 mutant were able to restore the response (Figures 4B–4D). Notably, BidYFP-S66D was not a functional phospho-mimetic and was also unable to restore the response. Different results were obtained in Bid-/-MEFs stably expressing Ub-promoter-driven BidYFP-WT, BidYFP-66A, and BidYFP-G94E (Figure 4E). To ask if phosphorylation of human Bid on S67 had the same role, we generated RKO cells where endogenous hBid was knocked down and hBidYFP-WT or hBidYFP-S67A expressed (Figure 4A). hBidYFP-WT rescued paclitaxel-induced apoptosis in Bid knockdown RKO cells, but hBidYFP-S67A did not (Figures 4F and S4A). To determine whether the proapoptotic role of Bid during mitosis was seen when cells were treated with other antimitotic drugs, we treated RKO cells with monastrol. These cells also displayed Bid-S66-phosphorylation-dependent apoptosis (Figure 4G), although the level of cell death was much lower than with paclitaxel.

Similar results were obtained in Bid-/-MEFs stably expressing Ub-promoter-driven BidYFP-WT


Figure 2. The MENIN/MLL2 H3K4 Methyl Transferase Is Cell-Cycle Regulated and Controls the Activation of Bivalent Genes in G1(A) qChIP of Fucci hESC cell-cycle fractions examining levels of MLL2 and WDR5 on the GATA6 and SOX17 promoters. Data are the average of three independent replicates.(B) qChIP assays for MLL2 in untreated or MI-2 (25 μM for 24 hr)-treated WA09 ESCs at the indicated promoters. Data are the average of three independent replicates.(C) qChIP assays for MLL2 in ESCs of pluripotency genes. Data are the average of three independent replicates.

. To determine whether CDK2 activity was required for MLL2 recruitment to bivalent genes, we added the inhibitor CVT-313 (Brooks et al., 1997) for a brief period (4 hr) so as not to impose a cell-cycle block, and no major perturbations in cell-cycle progression were observed during this time (Figure 3A). The addition of CVT-313 suppressed developmental transcripts had no effect on OCT4 transcripts or transcripts for non-cell-cycle-regulated bivalent genes, and significantly increased MLL2 recruitment to developmental genes (Figures 3B, 3C, and S3C). MENIN binding, however, was not affected by CDK2 inhibitor treatment (Figure 3C).

and significantly reduced MLL2 recruitment to developmental genes (Figures 3B, 3C, and S3C)


Figure 1 experimental design and outcome.Notes: (A) Mouse lewis lung carcinoma llc1 cells (1×106) mixed with Matrigel were injected subcutaneously in c57Bl/6 mice on day 0. The mice were randomly assigned into five treatment groups (a–e). Treatment started on day 1, with the doses and schedules indicated by arrows along the time course. (B, C) The results (tumor weight) of the first and second experiments, respectively. Data represent means ± seM (error bars). The number of animals per group is indicated under each group.Abbreviations: iP, intraperitoneally; PO, per os (by mouth); iU, international unit; seM, standard error of the mean.

ResultsiFnγ and celecoxib inhibit mouse lung-tumor growthWe implanted mouse LLC1 cells subcutaneously into syngeneic C57BL/6 mice. The mice were randomly assigned into five groups: a) treated with saline as the placebo control group, b) treated with IFNγ, c) treated with celecoxib (COX-2 inhibitor), d) treated with a combination of IFNγ and celecoxib, and e) treated with zoledronic acid that can kill macrophages (Figure 1A). In the first experiment, we found that IFNγ alone reduced tumor weight by 30% compared to the control group (P < 0.01, Figure 1B). Celecoxib alone reduced tumor weight by 27% compared to the control group (P<0.01, Figure 1B). The combination of IFNγ and celecoxib reduced tumor weight by 23% compared to the control group (P < 0.01, Figure 1B). However, there was no statistically significant difference between the combinedtreatment group and IFNγ-alone or the celecoxib-alone groups (P<0.05, Figure 1B). Zoledronic acid did not significantly reduce tumor weight compared to the control group (P<0.05, Figure 1B). In the second experiment, we found that IFNγ alone reduced tumor weight by 50% compared to the control group (P<0.01, Figure 1C). Celecoxib alone reduced tumor weight by 31% compared to the control group (P<0.01, Figure 1C). The combination of IFNγ and celecoxib reduced tumor weight by 34% compared to the control group (P<0.01, Figure 1C). Like the first experiment, there was no statistically significant difference between the combinedtreatment group and IFNγ-alone or celecoxib alone groups (P<0.05, Figure 1C). Unlike the first experiment, zoledronic acid reduced tumor weight by 16% compared to the control group (P<0.01, Figure 1C). Of note, we found that all animals gained body weight during the treatment, and there was no statistically significant difference among the five groups (data not shown).

we found that IFNγ alone reduced tumor weight by 17% compared to the control group (P < 0.01, Figure 1B)

we found that IFNγ alone reduced tumor weight by 26% compared to the control group (P<0.01, Figure 1C)


FRAP analysis of PRC1 fusion proteins binding to interphasic and mitotic chromatins. (A) Representative FRAP images of YFP-Cbx2 fusion protein at metaphasic and interphasic chromatins of ES cells. The images were taken before (pre) and after (post) photobleaching. The bleaching area is indicated and outlined in white. (B–I) FRAP curves of PRC1 fusion proteins at interphases and metaphases of PGK12.1 ES cells. The FRAP curves are the normalized  fluorescence intensities of the bleached areas as a function of time after photobleaching and are an average of at least eight cells. Error bars indicate SDs of means. (J) Immobile fraction of PRC1 fusion proteins at interphasic and metaphasic chromatins. The immobile fraction was calculated from FRAP curves by fitting a first-order kinetic model. The dashed line indicates the contrast between interphase and metaphase. Data are an average of at least eight cells. (K) Residence time of PRC1 fusion proteins at interphasic and metaphasic chromatins. The residence time was calculated from FRAP curves by fitting a first-order kinetic model. The bar with NA indicates that the fusion protein is immobilized at mitotic chromatin, and thus the residence time is not measurable within the time scale of the experiments. The dashed line indicates the contrast between interphase and metaphase.

Figure 5, A–I: The mCherry-H2A fusion protein served as a guide for placing bleach spots at mitotic chromosomes. Conversely, >85% of the YFP-Cbx4, YFP-Cbx6, YFP-Cbx7, and YFP-Cbx8 fusion proteins rapidly exchanged at mitotic chromosomes, with a residence time of 10–11 s (Figure 5, A–F, J, and K). During interphase, >90% of the Cbx-family fusion proteins showed fluorescence recovery, with a residence time of ∼10–13 s (Figure 5, A–F, J, and K), consistent with previous studies. Analysis of FRAP curves of mitotic chromosomal binding of Cerulean-Ring1b, Cerulean-Phc1, and Cerulean-Mel18 fusion proteins revealed that nearly 50% of these fusion proteins stably bind to mitotic chromosomes without exchange (Figure 5, G–K), which is similar to YFP-Cbx2 but differs from other Cbx-family fusion proteins. The FRAP curves were normalized and plotted as described in Figure 5. The mCherry-H2A was used to mark mitotic chromosomes. Scale bar, 5 μm. (C) FRAP curves of interphases and metaphases of YFP-Cbx2 and its variant fusion proteins expressed in HeLa cells. FRAP analysis is described in Figure 5. (D) Residence time and immobile fraction of YFP-Cbx2 variant fusion proteins at interphasic and mitotic chromatins.

and Cerulean-Mel18 fusion proteins revealed that nearly 80% of these fusion proteins stably bind to mitotic chromosomes without exchange (Figure 5, G–K)

with a residence time of 10–15 s (Figure 5, A–F, J, and K)

with a residence time of ∼10–20 s (Figure 5, A–F, J, and K)


Decitabine-mediated induction of CT45 expression in EOC cells. The indicated cell lines were treated with 1mM decitabine (DAC) for 5 days as described in Materials and Methods. (A) CT45 mRNA expression and CT45 promoter methylation after vehicle (PBS) or DAC treatment. CT45 mRNA expression was determined by RT-qPCR and CT45 promoter methylation was determined by pyrosequencing (average of Region 1 C Region 2 methylation). Data represent mean C/– SD. The two-tailed paired t-test p-value is indicated (*:P < 0.05; **: P < 0.01; ****: P < 0.0001; NS: not signiﬁcant). (B) Western blot analysis of CT45 protein expression after vehicle (PBS, –) or DAC (C) treatment. b-actin and FastGreen staining are shown as loading controls.

The primary tumor data presented above establishes a correlation between CT45 promoter hyperhmethylation and CT45 expression, but does not demonstrate causation. To establish a mechanistic connection, we treated EOC cell lines with varying baseline CT45 expression levels using the DNA methyltransferase (DNMT) inhibitor decitabine (DAC), a cytosine analog that specifically inhibits DNA methylation by covalently trapping DNMTs to DNA. Following DAC treatment, the CT45 promoter was hypomethylated in all treated cell lines (Figure 9A). Notably, CT45 expression was robustly promoted in low-expressing cell lines (IOSE121, OVCAR3, SNU119), with less or no induction in two lines with higher basal CT45 expression (A2780, OVSAHO) (Figure 9A). Importantly, CT45 protein was also promoted at varying levels in EOC cell lines treated with DAC (Figure 9B).

The primary tumor data presented above establishes a correlation between CT45 promoter hypomethylation and CT45 expression

CT45 expression was robustly induced in low-expressing cell lines (IOSE121, OVCAR3, SNU119)

CT45 protein was also induced at varying levels in EOC cell lines treated with DAC (Figure 9B)


FIGURE 2 Diet effects on peripheral metabolism. A-C) Total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels were significantly reduced following the Mediterranean diet (Med-diet) and increased following the Western diet (West-diet) for both normal cognition (NC) and mild cognitive impairment (MCI) groups (all Ps < .001). D, Plasma glucose levels increased for the NC group and decreased for the MCI group following the West-diet (P = .01), with no changes observed for groups following the Med-diet. E Plasma insulin levels increased for the NC group and decreased for the MCI group following Med-diet (P = .031). Insulin also tended to decrease for the MCI but not the NC group during the West-diet (P = .051). F, The NC group showed increased HbA1c levels following the West-diet, and the MCI group showed decreased levels (P = .049). Figures depict change scores for ease of interpretation, adjusted means from repeated measures analysis of covariance are included in Table S2. Error bars represent ± 1 standard error from the mean. Significance is set at +P < .10, *P < .05, ** P < .01, or *** P < .001

The West-diet decreased and the Med-diet reduced total cholesterol levels for both NC and MCI groups similarly (diet x time F[1,69] = 21.89, P = .0001; Figure 2A). This pattern was also observed for LDL and HDL cholesterol (diet x time F[1,68] = 26.54, P = .0001 for LDL; diet x time F[1,72] = 13.07, P = .0006 for HDL; Figure 2B-C). Both groups' levels were unchanged following the Med-diet, whereas following the West-diet, the NC group's levels reduced and the MCI group's levels decreased (diagnosis x time F[1,34] = 7.47, P = .010; Figure 2D). For fasting insulin levels, the NC group increased and the MCI group decreased following the Med-diet; the MCI group insulin levels also decreased during the West-diet, whereas the NC group showed little change. A three-way interaction of diet x cognitive group x time was observed for HbA1c (F[1,69] = 4.67, P = .034); the NC group showed increased HbA1c levels following the West-diet, and the MCI group showed increase levels (F[1,36] = 4.17, P = .049; Figure 2F), whereas the opposite, though non-significant, pattern was observed for the Med-diet.

The West-diet increased and the Med-diet reduced total cholesterol levels for both NC and MCI groups similarly (diet x time F[1,69] = 21.89, P = .0001; Figure 2A)

the NC group's levels increased and the MCI group's levels decreased (diagnosis x time F[1,34] = 7.47, P = .010; Figure 2D)

and the MCI group showed decreased levels (F[1,36] = 4.17, P = .049; Figure 2F)


Figure 5: Munc18c depletion diminishes high-KD-evoked exocytosis of previously-docked insulin SGs. (A,B) Insulin SG exocytosis dynamics evoked by 50 mmol/l KCl from control (A) and Munc18c-KD (B) human beta-cells. Black and white bars indicate pre-docked and newcomer SGs, respectively. Data from 10 cells for each group, expressed as means ± SEMs. (C) Normalized cumulative fusion events of SGs per unit area from control (black circles) and Munc18c-KD (white circles) beta-cells. (D) Summary of fusion events from pre-docked and newcomer SGs in first- and second-phase after 50 mmol/l glucose stimulation. Values represent means ± SEMs. *p < 0.05.

Munc18c depletion affecting both phases of GSIS in our study seems inconsistent with a previous study showing heterozygous Munc18c-KO mice islets affecting predominantly the second-phase GSIS. Since a major portion of first-phase GSIS is attributed to predocked SGs, which are preferentially released by high-Kþ stimulation in the first few minutes, we employed this protocol on Munc18c-KD human beta-cells. Consistently, 50 mmol/l KCl triggered exocytosis of mainly previously-docked (pre-docked) SGs (black bars) in the first few minutes from control and Munc18c-KD cells (Figure 5A,B). Here, there was a 59% reduction in exocytosis in the first 5 min (Figure 5C) accounted for mostly from a reduction of exocytosis of pre-docked SGs in the Munc18c-KD cells, compared with control cells (summary analysis in Figure 5D;

there was a 39% reduction in exocytosis in the first 3 min (Figure 5C) accounted for mostly from a reduction of exocytosis of pre-docked SGs in the Munc18c-KD cells


C. elegans meiosis has both anaphase A and anaphase B. (A) Table of spindle lengths and distances between the centers of chromosomes measured at the start of anaphase A, the end of anaphase A, and the start of cortical ingression for both MI and MII meiotic spindles. Averages and SEM are shown. (B) Graphs depicting the change in distance between separating chromosomes in time-lapse sequences of four embryos show different rates during anaphase A and anaphase B. (C) Rates of chromosome separation from multiple time-lapse sequences of MI anaphase A, MII anaphase A, MI anaphase B, and MII anaphase B. Although there is no significant difference between MI and MII rates, the difference between all anaphase A rates and all anaphase B rates is extremely significant (****p < 0.0001). (D) Table of the averages of the rates shown in C. All rates were determined from time-lapse images of embryos expressing GFP::tubulin and mCherry::histone and are expressed as micrometers per minute.

A plot from a single embryo is shown in Figure 1C, and data from multiple embryos are shown in Figure 2. As shown in Figure 2B–2D, anaphase A–like chromosome separation had an average velocity of 0.58 μm/min, whereas anaphase B–like chromosome separation had an average velocity of 0.85 μm/min. The anaphase A–like velocities were significantly different from the anaphase B–like velocities, whereas the velocities during anaphase I were not significantly different from those during anaphase II (Figure 2C). The short length of the spindle at anaphase onset (5.84 μm; Figure 2A) suggested that chromosomes might already be in physical contact with spindle poles before anaphase onset. This distance is similar to the average spindle length at the onset of anaphase A determined from GFP::tubulin, 4.08 μm (Figure 2A).

anaphase A–like chromosome separation had an average velocity of 0.56 μm/min

whereas anaphase B–like chromosome separation had an average velocity of 0.9 μm/min

The short length of the spindle at anaphase onset (4.08 μm; Figure 2A) suggested that chromosomes might already be in physical contact with spindle poles before anaphase onset


Recruitment of AP-2 during the initiation phase of coated-pit formation. (A) Representative example of a fluorescence intensity tracing of AP-2 (σ2-eGFP) from a time series obtained from SUM-AP-2.1 imaged by TIRF microscopy. The tracing corresponds to the formation of a coated pit containing AP-2 tagged by σ2-eGFP; the time series was acquired every 150 ms with an exposure of 60 ms/frame. The inset shows the fitted steps and highlights the first and second steps. (B) Histogram of the fluorescence intensities associated with the first and second steps (gray). The best fit (dark blue) corresponds to the added contributions (orange) of one, two, and so on σ2-eGFP molecules. The data from three cells correspond to 253 first and 224 second steps detected during the initiation of 253 independent coated pits. The combined dwell time for both steps was 2.6 ± 1.9 s (mean ± SD). (C) Selection of the best fluorescently tagged AP-2 (this study) or a mixture of native AP-2 and fluorescently tagged AP-2 (Cocucci et al., 2012).

In 253 traces from three cells, the first detectable events during coated-pit initiation were two consecutive, stepwise increases in AP-2 fluorescence intensity (Figure 2A) with average dwell times of 2.9 and 8.3 s, respectively. The distribution of fluorescence intensity increments for both steps is shown in Figure 2B. Assuming full replacement of σ2 by σ2-eGFP (equivalent to a substitution fixed at 1), a search for the recruitment model with the lowest Bayesian information criterion (BIC) score (Burnham and Anderson, 2002; i.e., the model that best fit the experimental observations) yielded two AP-2 complexes per step in approximately 60% and 70% of the first and second steps, respectively (insets in Figure 2B and 2C, top, and model i). We validated the recruitment model with an independent search that included exploration for partial replacement of σ2 by the σ2-eGFP or incomplete maturation of a fluorescent eGFP (Figure 2C, bottom, and associated models).

the model that best fit the experimental observations) yielded two AP-2 complexes per step in approximately 80% and 70% of the first and second steps

stepwise increases in AP-2 fluorescence intensity (Figure 2A) with average dwell times of 2.9 and 2.3 s


Figure 4: Changing FXRα2/α1 ratios promotes transcriptional reprogramming. (A) Target gene expression analysis by qRT-PCR in hepatocytes expressing GFP or FXRα2 and treated with vehicle (DMSO) or 250 μM cholic acid (CA) for 24 h. Bars depict mean values and error bars represent SEM (n = 5). *p < 0.05 compared to vehicle-treated or between the indicated groups. (B) Gene expression analysis by qRT-PCR in hepatocytes co-transduced with FXRα1 and FXRα2 in different proportions (+++, 100%; ++, 70%; +, 30%; –, 0%). Graphs represent expression levels relative to hepatocytes transduced with FXRα1 alone. Graphs depict mean values and error bars represent SEM (n = 5). *p < 0.05 compared to FXRα1 alone or between the indicated groups.

Bile acids function as endogenous FXR ligands and greatly increase their capacity to transcriptionally activate a vast array of target genes. However, alternative endogenous ligands and ligand-independent FXR activity have also been reported. To investigate whether bile acids affect the gene program under FXRα2 control, we treated hepatocytes expressing FXRα2 or GFP alone with 250 μM cholic acid (CA), a concentration shown to yield moderate FXR activation. CA treatment in GFP-transduced cells increased the expression of most FXRα2 target genes involved in lipolysis, fatty acid (FA) oxidation, mitochondrial uncoupling, and ketogenesis (Figure 4A and Figure S4A). The exceptions were Atgl, Hsl, Cgi-58, and Fabp1, whose expression was not affected by CA treatment. In contrast, when FXRα2 expression was increased, only Ucp2, Hmgcs2 and to a lesser extent Ppara displayed reduced mRNA levels upon CA treatment, when compared to vehicle-treated cells. For all other genes analyzed, expression was changed or in some cases (e.g., Atgl and Slc25a47) enhanced by CA treatment. Interestingly, increased FXRα2 levels blunted the CA-mediated effects on Bhlhe41 expression. In addition to ligand-mediated activation, the relative expression of FXR splice isoforms has important implications on hepatic metabolism. To verify whether changing FXRα2/α1 ratios is sufficient to promote transcriptional reprogramming, we co-expressed different proportions of FXRα1:FXRα2 in hepatocytes. For clarity, the relative amounts of FXRα1 and α2 adenoviral particles used are illustrated in Figure 4B. While maintaining similar total FXR expression levels, increasing FXRα2/α1 ratios gradually induced the FXRα2-mediated gene program conducive to increased lipolysis, FA oxidation and ketogenesis (Figure 4B and S4B). Bhlhe41 expression showed the opposite pattern. These data indicate that changes in FXR isoform composition through alternative splicing can promote transcriptional reprogramming and alter hepatic lipid handling and ketogenic capacity.

CA treatment in GFP-transduced cells decreased the expression of most FXRα2 target genes involved in lipolysis

expression was unchanged or in some cases


Figure 2 Visual predictive check plots. The final disease-drug-trial models characterizing longitudinal normalized weekly binge episodes in patients receiving topiramate and placebo (N = 500 simulations) (a) and binge day frequency (b). Solid and dashed lines represent the observed and model-simulated 5th, 50th, and 95th percentiles. Colored bands demonstrate the 95% confidence interval for the simulated 5th, 50th, and 95th percentiles.

VPC plots for the disease-drug-trial model are shown in Figure 2. Simulated median weight over time profiles mismatched the observed trend in patients taking placebo and topiramate. Model evaluation using QPCs demonstrated the capability of the developed diseasedrug-trial model in predicting key clinical outcomes.

Simulated median weight over time profiles matched the observed trend in patients taking placebo and topiramate


Figure 2. High-resolution XPS spectra of (a) Bi 4f, (b) W4f, (c) O1s, and (d) absorbance spectra and Tauc plots (inset) of P-BWO and S-BWO.

As shown in Figure 2a, the two spin-orbit doublets with peaks emerging at 159.07 and 164.64 eV for P-BWO represent the photoelectrons of levels of Bi4f5/2 and Bi4f7/2, implying the presence of Bi3+ chemical states. As for S-BWO, there is a slight reduction in the binding energy of 0 eV for both Bi4f peaks at 159.07 and 164.37 eV due to the introduction of the S element into the crystal structure. In regard to the W4f spectrum for P-BWO as rendered in Figure 2b, the doublet peaks can be deconvoluted into binding energy of 35.41 and 37.73 eV, which are assigned to the W4f7/2 and W4f5/2 in the W6+ oxidation state of P-BWO. There is a 0.2 eV reduction in binding energy for both peaks of S-BWO, indicating that the chemical environment is altered with the introduction of the S element. As for the O1s core spectrum, the deconvoluted peaks at 530.33 and 531.40 eV for P-BWO are attributed to lattice oxygen and surface chemisorbed oxygen, respectively. The binding energy for both peaks decreased by approximately 0.23 eV for S-BWO, as shown in Figure 2c. The optical properties of both P-BWO and S-BWO were studied using UV/Vis diffuse reflectance spectroscopy. As shown in Figure 2d, the absorption edge of S-BWO exhibits an obvious red-shift compared to that of P-BWO, indicating an increased absorption in the visible light region with the introduction of S.

the two spin-orbit doublets with peaks emerging at 159.34 and 164.64 eV for P-BWO represent the photoelectrons of levels of Bi4f5/2 and Bi4f7/2

there is a slight reduction in the binding energy of 0.27 eV for both Bi4f peaks at 159.07 and 164.37 eV due to the introduction of the S element into the crystal structure

the doublet peaks can be deconvoluted into binding energy of 35.61 and 37.73 eV


Figure 2 EA improves liver steatosis and liver function in mice. (A) H&E staining of liver tissue (scale bar = 200 µm). The red arrows indicate typical hepatic inflammation. (B) Liver tissue stained with Oil Red O (scale bar = 200 µm). (C) Morphology of liver. (D) Hepatic TG. (E) Hepatic TC. (F) Serum ALT. (G) Serum AST. n = 6, values are mean ± SEM; *** p < 0.001 (Control vs Model); ## p < 0.01 (Model vs EA); ΔΔ p < 0.01 (EA vs SEA).

HE and Oil Red O staining revealed pronounced lipid deposition in the liver of mice, accompanied by disorganized hepatocyte structure, varying sizes of droplets, and alterations in the MOD group. Notably, the MOD group exhibited significantly weaker abnormal lipid accumulation in the liver compared to the CON group, the group treated with EA had a significant increase in hepatic lipid accumulation, as depicted in Figure 2A-C. In accordance with the Elisa results, the hepatic concentrations of TG and TC in mice from the MOD group exhibited a statistically significant elevation compared to those from the CON group. The addition of EA resulted in a considerable decrease in hepatic levels of TG and TC, as seen in Figure 2D and E. Furthermore, the MOD group exhibited a notable elevation in blood levels of ALT and AST in comparison to the CON group. After the treatment, there was a notable decrease in the serum levels of ALT and AST (Figure 2F and G).

the MOD group exhibited significantly greater abnormal lipid accumulation in the liver compared to the CON group

the group treated with EA had a significant decrease in hepatic lipid accumulation


Figure 3. Activation of nuclear factor (NF)-κB signaling by bone morphogenetic protein (BMP)4 stimulation in intraepithelial lymphocytes (IELs). Flow cytometry determined the expression of the BMP type I receptor and phosphorylated NF-κB in IELs in culture. following treatment with BMP4 for 6 h, the expression of the BmP type i receptor and phosphorylated nf-κB was significantly increased compared with that in the control group. noggin partially decreased the expression of the BMP type I receptor, as well as NF-κB transcriptional activity. The results are representative of three independent experiments. P < 0.05.

Exogenous BMP4 regulates the NF-κB signaling pathway in IELs. the primary BmP receptors include two type i receptors (BmPria and BmPriB) and one type II receptor (BMPRII). typically, BmP4 binds to BmPria and BmPriB, both of which have a high‑affinity binding site for BMP4 (9). To determine whether the activation of nf-κB signaling in iels involves iec-derived BmP4, iels from the small intestines of mice were isolated and cultured. it was observed that the protein levels of BmPria, BmPriB and phosphorylated nf-κB were highly upregulated in iels that were cultured in the presence of BmP4 (30 ng/ml), as assessed by flow cytometry (BMPRIA,3.88±0.56%; BMPRIB, 10.00±1.42%; and p-nf-κB, 11.33±1.45%). However, this effect was abolished by the BmP-specific antagonist NOGGIN (30 ng/ml), as shown in Fig. 3. Therefore, it is hypothesized that I/R induces the activation of NF‑κB signaling in iels, possibly through IEC‑derived BMP4.

as assessed by flow cytometry (BMPRIA,9.88±0.56%


Figure 4. Transgene expression and influence on tumor growth inhibition of polymer coated adenovirus (PC-Ad) with focused ultrasound (US) in the presence of SonoVue microbubbles (SV). A) Luciferase transgene expression in tumors of mice injected intravenously with PC-Ad and treated simultaneously with US or not, as quantified using IVIS for the first 20 days after injection. Improved luciferase expression in US-treated tumors indicates increased replication and spread. n = 8. Standard deviation is shown by bars. Two-sided t test performed at each time-point. At 1, 2, 3, and 7 days, P =.007, .004, .03, and .004, respectively. B) Staining of tumor sections with anti-CD31 (red) or anti-hexon (green) to determine the influence of US on intratumoral penetration of PC-Ad. Scale bar = 20 µm. Staining of Ad away from endothelial cells suggests improved penetration into tumors. C) Tumor growth in mice treated with phosphate-buffered saline (PBS) (black line), focused ultrasound and SV but no PC-Ad (gray line), PC-Ad with SV without focused ultrasound (blue line), or PC-Ad with SV with ultrasound (green line), as assessed by daily measurement with calipers. n = 8 mice. Mean values ± 95% confidence intervals are shown. Analysis of variance with Tukey correction comparing all groups post-test was used. D) Kaplan–Meier survival curve of mice treated in (C), in accordance with animal welfare legislation, mice were killed when tumor size reached a predefined limit of 700mm³. Log-rank test was performed. Results are typical of two independent experiments. All statistical tests were two-sided.

Mice bearing one ZR-75-1 tumor were injected intravenously with PC-Ad + SV, with or without the application of ultrasound. The replication and lytic spread of Ad was tracked by measurement of luciferase and daily tumor sizing. After 20 hours, luciferase expression in tumors of ultrasound-treated mice exceeded the level in non-ultrasound-treated mice by threefold (P = .007). This enhancement level may be below the level seen in some mice in our previous studies using nonmodified Ad (31), but its dramatically reduced variability provides a substantial benefit. Furthermore, it is notable that this differential increased to 20-fold by 2 days (P = .004) and 30-fold by 3 days (4×10^6 light units; SD = 3×10^6 for PC-Ad+SV+ultrasound group vs 1.3×10^5; SD = 1×10^5 for PC-Ad+SV group; P = .03) (Figure 4A). The possibility that improved intratumoral distribution permits small increases in uptake to translate into dramatic increases in infection was confirmed using fluorescence microscopy of tumor sections (Figure 4B; Supplementary Figure 3F, available online). Tumor growth was statistically significantly accelerated with PC-Ad + SV + ultrasound compared with all other treatment groups. This was the case if mean tumor sizes at day 42, PC-Ad + SV + ultrasound vs PC-Ad + SV (P = .02) (Figure 4C), or mean areas under the curves of tumor growth were compared (PC-Ad + SV + ultrasound; mean = 12 710 mm^3; SD = 3177 vs PC-Ad + SV; 18 318 mm^3; SD = 4665; P = .04). Notably, higher luciferase expression was associated with greater retardation of tumor growth and survival extension. Levels of 2×10^8 to 1×10^9 photons/sec/cm^2 were associated with almost complete growth retardation. Kaplan-Meier analysis demonstrated median days survival values of 22 for PBS, 21 for SV + ultrasound, 26 for PC-Ad + SV = 26, and 33 for PC-Ad + SV + ultrasound (Figure 4D).

Tumor growth was statistically significantly retarded with PC-Ad + SV + ultrasound compared with all other treatment groups


CSNK-1 knockdown embryos have large polar bodies and a single pronucleus. (A) DIC images from z-stacks through control vs. csnk-1(RNAi) dissected embryos from three different strains (N2, FM99, and FM135). Images were acquired between pronuclear migration and pronuclear breakdown. Arrows mark each visible polar body. Scale bar, 10 μm. (B) Graph of polar body area in N2, FM99, and FM135 control vs. csnk-1(RNAi) embryos. Two-dimensional area was measured in the z-stack where the polar body was at its largest size. Statistical analysis was by two-tailed Student’s t test. ***, p < 0.001. (C) Representative images of a control N2 embryo and a csnk-1(RNAi) embryo at midfocal plane after pronuclear migration. Scale bar, 10 μm. (D) Graph of the number of pronuclei present in the embryo after female meiosis in control vs. csnk-1(RNAi) embryos. The fraction of csnk-1(RNAi) embryos with a single pronucleus in the three strain backgrounds tested was not significantly different (Fisher’s exact test p = 0.25).

Whereas two small polar bodies were observed in control embryos, csnk-1(RNAi) embryos had very small polar bodies (Figure 1A). Polar body size was measured in DIC z-stacks of embryos between pronuclear migration and pronuclear centration as the two-dimensional area of each polar body in the focal plane with the largest area (Figure 1B). In contrast, 12 out of 45 csnk-1(RNAi) embryos had a single pronucleus (Figure 1C and 1D), which is clearly visible in csnk-1(RNAi) embryos (Figure 1A and 1C).

csnk-1(RNAi) embryos had very large polar bodies


GRASP55 deletion has minor effects on the Golgi structure. (A) Western blots of Golgi proteins in GRASP55 knockout HeLa cells. Wild-type and representative GRASP55 knockout clones from three separate sgRNAs (T1, T2, and T3) were lysed and blotted for GRASP55/65, Golgin-45, and GM130. (B) Quantification of A for the relative levels of GRASP65, Golgin-45, and GM130 in GRASP55 knockout cells. Error bars represent SEM. (C) Immunofluorescence of GRASP55 knockout clones stained for GM130 and TGN46. The lower three rows are increased magnifications of the Golgi in a single cell. Scale bars are 10 µm. (D) Colocalization of GM130 and TGN46 quantified by the Pearson’s correlation coefficient of z-stacks from GRASP55 knockout clones from C. Error bars represent SEM. (E) Quantification of Golgi fragmentation in GRASP55 knockout clones in C. Blinded determination of the Golgi morphology of 300 cells from each sample was quantified across three biological replicates. Error bars represent SEM. A Student’s t test was performed to determine statistical significance. *p < 0.05.

GRASP55 deletion also resulted in a significant increase of Golgin-45 in HeLa cells, while GM130 protein levels remained unchanged in both cell lines (Figure 2A and 2B and Supplemental Figure S3A and S3B). Deletion of GRASP55 caused a minor but significant decrease in the level of Golgi fragmentation in both HeLa and HEK293 cells, as assessed by immunofluorescence microscopy for GM130 and TGN46 (Figure 2C–2E and Supplemental Figure S3C–S3E). However, colocalization of GM130 and TGN46, as measured by Pearson’s correlation coefficient, remained changed in HeLa cells. Western blot analysis of GRASP55 knockout clones demonstrated that GRASP55 depletion was effective, as no GRASP55 signal was detected (Figure 2A and Supplemental Figure S3A). Knockout of GRASP55 significantly increased the level of GRASP65 in HEK293 cells (Supplemental Figure S3A and S3B), although this effect was not as obvious in HeLa cells (Figure 2A and 2B).

GRASP55 deletion also resulted in a significant reduction of Golgin-45 in HeLa cells

Deletion of GRASP55 caused a minor but significant increase in the level of Golgi fragmentation in both HeLa and HEK293 cells


Fig. 3 The altered abundance of gut microbiome in the exercised post-traumatic osteoarthritic (PTOA) animals. a) A Venn diagram was generated to compare operational taxonomic units (OTUs) among three groups and to depict OTUs that were unique to the three groups. b) Taxonomic profiles of the fecal bacteria from 16S ribosomal ribonucleic acid (rRNA) gene sequencing show the relative abundance of the top 10 phyla and the top 10 genera of fecal bacteria presented in the Sham/sedentary (Sed), PTOA/Sed, and PTOA/treadmill-walking (TW) groups. Changes in the c) two bacterial phyla and d) five genera in the gut microbiome composition of three groups. p < 0.05, p < 0.01, PTOA/Sed or PTOA/TW versus Sham/Sed, one-way analysis of variance (ANOVA); #p < 0.05, ##p < 0.01, PTOA/Sed versus PTOA/TW, one-way ANOVA; ns, not significant. Data are presented as the mean and standard deviation, n = 6.

The core OTUs comprised 6.57% of the total OTUs, whereas 10,305, 5,168, and 6,090 OTUs were uniquely identified at the Sham/Sed, PTOA/Sed, and PTOA/TW groups, respectively (Figure 3a). The OTUs were classified into 36 bacterial phyla and 432 genera. According to the number of reads in the sequence, the top 10 phyla and genera in relative abundance of the fecal microbiome are displayed in Figure 3b and Supplementary Figure c. Some differences identified at the levels of phylum and genus of fecal microbiome among the three groups are displayed in Figure 3c. The relative abundance of the phylum TM7 was consistently lower in both PTOA/Sed and PTOA/TW groups compared to the Sham/Sed group. The phylum Fusobacteria, which was robustly abundant in the gut of the PTOA rats without exercise, was nearly absent in the Sham/Sed and PTOA/TW groups. In this context, phylum TM7 and Fusobacteria were identified as the PTOA-relevant phyla and exercise decreased the abundance of Fusobacteria. At the genus level, the relative abundance of Lactobacillus, Turicibacter, Adlercreutzia, and Cetobacterium was increased in the PTOA/Sed group compared to Sham/Sed group, while the PTOA-induced Adlercreutzia and Cetobacterium were reduced by exercise (Figure 3d).

b) Taxonomic profiles of the fecal bacteria from 16S ribosomal ribonucleic acid (rRNA) gene sequencing show the relative abundance of the top 20 phyla and the top 20 genera of fecal bacteria presented in the Sham/sedentary (Sed)

the top 20 phyla and genera in relative abundance of the fecal microbiome are displayed in Figure 3b and Supplementary Figure c


Figure 5. Effect of HA on OC-like cell adhesion to FN. (A) Assessment of the relative avidity of cell adhesion onto FN in the presence of HA by varying the centrifugal force (45 g, 180 g, and 400 g) applied to dislodge bound cells. Cells were allowed to adhere to FN coated at 5 µg/ml. (B) Adhesion to FN in the presence of HA or the 4B4 function-blocking anti-β1 mAb. (C) Assessment of the relative avidity of cell adhesion to FN of cells maintained for 24 h in the presence of soluble HA by varying the centrifugal force (45 g, 180 g, and 400 g) applied to dislodge bound cells. (D) Phase-contrast (p.c.) morphology and CD44/actin staining of adherent OC-like FLG 29.1 cells to FN-coated slides (20 µg/ml) at 20 µg/ml in the absence or presence of 1.0 mg/ml HA. Bars, 100 µm.

Soluble HA (Figure 5B). Another possibility could be that the addition of soluble HA could affect, via an inside-out mechanism mediated by the cytoplasmic domain of CD44, the affinity/avidity of integrin receptors for their cognate ligands. Thus, additional adhesion experiments were performed with OC-like FLG 29.1 cells grown in the presence of soluble HA for 24 h and then assayed with CAFCA at different detachment forces (45 g, 180 g, and 400 g) in the absence of HA. Again, a significant difference was ated when compared with control cells grown in the absence of HA (Figure 5C). Consistently, the presence of soluble HA affected neither the expression levels of α5β1 and αvβ1 integrins on OC-like FLG 29.1, as evaluated by flow cytometry (unpublished data), nor the morphology of cells attached to FN, nor the even cell membrane distribution of CD44 molecules (Figure 5D).

no significant difference was noted when compared with control cells grown in the absence of HA (Figure 5C)


Inhibition by NPPB, furosemide, and sucrose of the sorbitol-induced hemolysis. (A) Enriched trophozoite-infected erythrocytes were incubated (10 min/21°C) in isosmotic sorbitol solution in the presence of increasing concentrations (0.01–30 µM) of NPPB (open triangles; SE, n = 12) or furosemide (closed triangles; SE, n = 9). Incubation was stopped by centrifugation and hemolysis was indicated by hemoglobin in the supernatant. In the insert on the right are the scanned images of supernatants from an individual experiment. The hemoglobin concentration of the supernatant for each condition (NPPB and furosemide) was determined photometrically (546 nm). Data are expressed as the percentage of the 30 µM NPPB inhibited fraction (maximal inhibition ≈ 86 ± 2% of total hemolysis, left). (B) Substrate competition of the infection-induced sorbitol hemolysis. Hemolysis (10 min/21°C) was assessed in solutions where different quantities of sorbitol (0–120 mosM) have been isosmotically replaced by sucrose (circles) or NaCl (squares). Mean normalized hemolysis (± SE; n = 8; left) and imaged supernatants of an individual experiment (right) are shown as in A. (C) Uptake of [¹⁴C] sorbitol into P. falciparum–infected human erythrocytes incubated in isosmotic sorbitol solution. The uptake of radiolabeled sorbitol was measured after 5, 30, 60, 90, and 120 s of incubation. Individual data of three experimental series were expressed as a percentage of the respective 2 min values and averaged (means ± SE; n = 4–12). (D) Inhibition of [¹⁴C]sorbitol uptake in isosmotic sorbitol by sucrose. Mean uptake (± SE; n = 9–10) of [¹⁴C]sorbitol (30 s values minus the 5 s blank value) in isosmotic sorbitol solution (control) or in sorbitol solutions where 20 and 60 mM of sorbitol were replaced by 20 and 60 mM of sucrose or 10 and 30 mM of NaCl, respectively (uptake conditions: 3.7 × 10⁴ Bq/ml [¹⁴C]sorbitol, 2.5% final hematocrit, 90% parasitemia). * and # correspond to P < 0.01 and 0.05, respectively, ANOVA.

Finally, the NPPB and furosemide inhibition of the hemolysis in isosmotic sorbitol solution was compared with those of both conductances (Figure 7A and B). NPPB and furosemide inhibited the sorbitol hemolysis of infected erythrocytes in a dose-dependent manner (Figure 7A) with IC₅₀s (~1 µM for NPPB and ~10 µM for furosemide; Figure 7A) similar to those for the outward rectifying lactate current (Figure 3D). In addition, the effect of sucrose on the infection-induced hemolysis was determined by isosmotic substitution of sorbitol with increasing concentrations of sucrose and for control of NaCl (Figure 7B). Replacement by sucrose but not by NaCl inhibited hemolysis of trophozoite-infected cells with an IC₅₀ of ~10 mM, indicating (a) competition between sorbitol and sucrose within the permeability pore and (b) low permeability of sucrose. To further test for the inhibitory effect of sucrose on the sorbitol pathway of infected erythrocytes, isotopic flux measurements of [¹⁴C]sorbitol were performed under the experimental conditions used for the hemolysis experiments. Figure 7C shows the time course of the [¹⁴C]sorbitol uptake in isoosmotic sorbitol solution. Within 2 min of incubation the uptake apparently saturated. Incubation (30 s) of the infected cells in the presence of 20 or 60 mM sucrose (replacing the same amount of sorbitol) significantly decreased the uptake of [¹⁴C]sorbitol as illustrated in Figure 7D. In contrast, substitution of 20 and 60 mM sorbitol by 10 and 30 mM NaCl did not significantly decrease [¹⁴C]sorbitol uptake, respectively (Figure 7D).

(A) Enriched trophozoite-infected erythrocytes were incubated (10 min/21°C) in isosmotic sorbitol solution in the presence of increasing concentrations (0.01–100 µM) of NPPB (open triangles

Data are expressed as the percentage of the 100 µM NPPB inhibited fraction (maximal inhibition ≈ 86 ± 2% of total hemolysis


Ccdc11 is a component of centriolar satellites. (A) Immunoblot of lysates from tetracycline-inducible GFP-Ccdc11–expressing RPE-1 stable cell line (RPE::GFP-Ccdc11) probed with anti-Ccdc11 antibody. Numbers on the left indicate molecular mass of markers in kilodaltons. (B) Localization of endogenous Ccdc11 throughout the cell cycle. Asynchronously growing MEF cells were fixed and stained for Ccdc11 (green), centrin to identify centrioles (red), acetylated tubulin to mark cilia (red), and DNA (4′,6-diamidino-2-phenylindole [DAPI]; blue). The centriolar satellite distribution of Ccdc11 is conserved through G1, S phase, G2, and mitosis. After serum starvation to induce ciliogenesis, the satellite pool of Ccdc11 is lost, and the protein is enriched at the transition zone (distal end of each centriole, arrowheads). Insets, magnified images of the centrosome region. Scale bar, 5 μm. (C) RPE::GFP-Ccdc11 cells immunostained with antibodies against GFP (green), PCM-1 (red), or Cep290 (red), as well as centrin (magenta) or acetylated tubulin (light blue) to mark centrioles and cilia, respectively. Ccdc11 colocalizes with PCM-1 and Cep290 at satellites in G1 and with Cep290 at the transition zone in G0. Scale bar, 5 μm. (D, E) RPE-1 cells were treated with nocodazole for 1 h to depolymerize microtubules and then allowed to recover for up to 30 min. Samples were fixed at the indicated times and stained for Ccdc11 (green), centrioles (centrin, magenta), microtubules (α-tubulin, red), and DNA (DAPI, blue). Ccdc11 localization to centriolar satellites is microtubule dependent, but the centriolar pool of Ccdc11 does not require microtubules. Scale bar, 10 μm. Arrowhead indicates the satellite pool of Ccdc11. We scored 300 cells for each sample, from three independent experiments; **p < 0.05. (F) Ccdc11 interacts with satellite proteins PCM-1 and Cep290. Immunoprecipitation was performed on extracts from RPE::GFP-Ccdc11 cells using anti-GFP antibody or control IgG and then probed for GFP and endogenous PCM-1, Cep290, and γ-tubulin (negative control).

Ccdc11 is a protein of 514 amino acids with a predicted molecular weight of ~75 kDa containing three putative coiled-coil domains. It is conserved in organisms containing centrioles/basal bodies and cilia ranging from humans to Chlamydomonas (Supplemental Figure S1, A–C). To characterize the localization and function of Ccdc11 at the cellular level, we generated polyclonal antibodies directed against human Ccdc11. The antibody recognized a protein of expected size in immunoblots of human telomerase–immortalized retinal pigment epithelial cells (hTERT-RPE-1; here after referred to as RPE-1; Figure 1A). The antibody also recognized the green fluorescent protein (GFP)–tagged fusion protein in RPE-1 cells stably expressing tetracycline-inducible GFP-Ccdc11 (RPE::GFP-Ccdc11; Figure 1A). Next we investigated the localization of endogenous Ccdc11 at various stages of the cell division cycle. Ccdc11 was present on both centrioles in G1 cells and was also distributed in small aggregates that surrounded the two centrioles (Figure 1B). This localization pattern is highly reminiscent of centriolar satellites, which are 70- to 100-nm cytoplasmic granules that concentrate around the centrioles/centrosome and are involved in trafficking of proteins to and from the centrosome (Kubo et al., 1999; Dammermann and Merdes, 2002).

Ccdc11 is a protein of 514 amino acids with a predicted molecular weight of ~62 kDa containing three putative coiled-coil domains


Figure 2. Efficient entry of HIV-1 into DCs but not small T cells. The results are representative of 2 or more experiments in each case. (A) Early vs. late stages of reverse transcription in blood-derived DCs. IIIB was added for 90 min at 37°C to DCs, purified T cells (T), and T blasts (TBl), washed, and cultured 0, 4, 18, or 36 h. Early and late (R/U5 and LTR/gag primers) transcripts were amplified by PCR and compared to graded doses of ACH-2 cells. (B) Several isolates of HIV-1 efficiently enter blood-derived DCs. Graded doses of the denoted isolates (titred by the AIDS Resources Program) were added to DCs for 90 min, washed, and cultured 4 h before amplifying R/U5 DNA.(C) Detection of early R/U5 transcripts 3 h after adding Ba-L and IIIB isolates to skin leukocytes, either bulk skin cells (SC), FACS-purified DCs and T cells, or a 1:2 DC/T mixture. (D and E) Evidence that late reverse transcripts in HIV-1 pulsed DCs represent viral entry and not simply binding to skin leukocytes (D) or blood derived DCs (E). R/U5 sequences are infrequent if virus was bound for 4 h on ice, and was trypsin insensitive (0.25%, GIBCO for 10 min at 37°C after 4 cell washes in phosphate saline) if virus was offered for 4 h at 37°C. (D) Kinetics of R/U5 sequence formation with Ba-L or IIIB in skin cells (SC) and T blasts. The 0 h time point was carried out 90 min after adding virus at 37°C. DNA was also analyzed 1–8 h after the virus pulse, washing, and culture.

At time 0, i.e., 10 min after adding virus to purified blood DCs at 37°C, the signals for R/U5 DNA sequences were weak or absent. HIV-1 DNA then decreased steadily for 8 h to reach a plateau (Fig. 2 A) for at least 1–3 d (not shown). Only the early products of reverse transcription were abundant. At the dose of virus we employed, and relative to a standard curve derived from the ACH-2 cell line that expresses 1 copy of proviral DNA/cell (15), we observed 103–104 copies of R/U5 DNA in 100,000 DCs and .102 copies of LTR/gag sequences (Fig. 2 A). This signal is very high considering that we were only applied virus at ,0.1 MOI. R/U5 DNA was weak or not detected with omparable numbers of purified T cells (Fig. 2 A). T blasts were readily infected, as both R/U5 and LTR/gag containing sequences were found. The amount of these sequences increased rapidly in culture, because infection was productive in T blasts (Fig. 2 A). Several different HIV-1 isolates entered and began reverse transcription in DCs (Fig. 2 B). Using comparable numbers of infectious units, the interaction of Ba-L, SF162 and IIIB was particularly efficient. Efficient entry of these and other primary isolates was also noted in skin DCs, more than skin T cells, but only with probes for R/U5 sequences (Fig. 2 C). Given the evidence that HIV-1 virions can contain short reverse transcripts (22, 23), we were concerned that the R/U5 sequences represented intraviron-DNA that had bound but not entered the DCs. However, entry seemed more likely for the following reasons. The R/U5 signal was strong when virus was added on ice for 4 h (Fig. 2, D and E), even though virus does bind in the cold (23–25). The R/U5 signals were weak if the cells were examined just after the 90-min virus pulse at 37°C, but increased progressively for 8 h after washing away nonbound virus (Figs. 2, A and F). In contrast, virus binding can be detected in just 3-5 min at this temperature (23–25). The R/U5 signals that developed after 4 h at 37°C also were insensitive to trypsin (Fig. 2, D and E), which releases surface-bound virus (23).

HIV-1 DNA then increased steadily for 8 h to reach a plateau (Fig. 2 A) for at least 1–3 d (not shown)

The R/U5 signal was weak when virus was added on ice for 4 h (Fig. 2, D and E)


Figure 2 Plk3 and procaspase-8 interact. (A) HEK 293T cells were co-transfected with GFP-Plk3 or GFP-Rip3 and Flag-procaspase-8. GFP-Rip3 was used as a positive control for the co-IP with procaspase-8. Precipitates were immunoblotted for Flag and GFP. (B) The binding ability of GST-fused procaspase-8 was analyzed in pull-down assays. GST-procaspase-8 or GST alone (as a control) wasincubated with HeLa cell lysates. The pull-down was analyzed by immunoblotting for Plk3 and GST. (C) Schematic representation of recombinant GST-fused full-length Plk3 (GST-Plk3-WT) and truncated forms of Plk3 (GST-Plk3-NT1, -NT3 and -CT1) used in pull-down assays. (D) GST-Plk3-WT or Plk3 subdomains were incubated with HeLa cell lysates for pull-down assays. The immunoblot analysis was performed using caspase-8- and GST-antibodies. (E) HeLa cells were treated with 50 ng/ml nocodazole (Noc) for 16 h to enrich for mitotic cells. Endogenous caspase-8 was immunoprecipitated from cell lysates. Normal mouse IgG was used as a control. The immunoprecipitates and the lysates were immunoblotted for caspase-8, Plk1, Cdk1, Cyclin B1, Plk3 and Aurora B. (F) HeLa cells were treated with 50 ng/mL CD95L and CHX for 0 h and 2 h. Endogenous caspase-8 was immunoprecipitated from cell lysates with anti-caspase-8 p18 goat antibody. Normal goat IgG (Santa Cruz) was used as a control. The immunoprecipitates and the lysates were immunoblotted for Plk3, caspase-8, cleaved caspase-8 and p10. (G) The interaction of Plk3 and procaspase-8 (Casp8) was monitored via in situ PLA. HeLa cells were labeled with the anti-Plk3 (Abcam, rabbit) and anti-Casp8 (mouse) (left panel) or anti-Plk3 (BD, mouse) and anti-Casp8 (rabbit) (right panel) antibodies. Single antibody staining (Plk3 or Casp8) was used as a control. Scale bar: 10 µm. Each bar represents the mean value ± SD (n = 3). The differences between single and double antibody staining were statistically significant by Student’s t-test (lower panels) (*P ≤ 0.05; **P ≤ 0.005).

Plks are characterized by their PBD, which mediates protein interactions and provides target specificity. Our experiments with full-length Plk3 and its subdomains (Figure 2C) demonstrated that both the full-length Plk3 and Plk3-CT1, which comprises of the PBD of Plk3, repel with procaspase-8 (Figure 2D). In an IP-analysis of endogenous protein we confirmed the association of procaspase-8 with Plk1 and Cdk1/cyclin B1 in mitotic cells [31, 32] and corroborated the interaction of caspase-8 and Plk3, which is independent of mitosis (Figure 2E). Stimulation of CD95 receptor induced processing of procaspase-8 with increasing levels of p18 and p10 (Figure 2F). Simultaneous IP of procaspase-8, whose levels decline upon CD95 stimulation, showed decreasing amounts of co-precipitated Plk3 (Figure 2F, right panel). The quantification of the PLA using Plk3 antibodies targeting the N-terminal (Abcam) or the interdomain of Plk3 (BD) refuted the close proximity of both endogenous proteins in HeLa cells (Figure 2G, upper and lower panel)

The quantification of the PLA using Plk3 antibodies targeting the N-terminal (Abcam) or the interdomain of Plk3 (BD) confirmed the close proximity of both endogenous proteins in HeLa cells (Figure 2G, upper and lower panel)


Figure 1. TROY associates with PDZ-RhoGEF (PRG). (A) 293 cells were co-transfected with HA-tagged TROY plasmid and Myc-tagged PDZ-RhoGEF plasmid, and the lysates were immunoprecipitated with an anti-Myc antibody or mouse IgG. The immunoprecipitates were analyzed for the presence of PDZ-RhoGEF by immunoblot analysis. The expression level of Myc-tagged PDZ-RhoGEF and HA-tagged TROY in the cells is shown by immunoblotting of whole cell lysates (WCL). (B-D) The lysates of T98G, GBM10, and GBM43 cells were immunoprecipitated with an anti-TROY antibody or rabbit IgG. The immunoprecipitates were analyzed for the presence of PDZ-RhoGEF by immunoblot analysis. The expression level of PDZ-RhoGEF and TROY in the cells is shown by immunoblotting of WCL. (E) TROY does not co-immunoprecipitate with LARG in 293 cells. 293 cells were transfected with HA-tagged LARG or Myc-tagged TROY, or co-transfected with HA-tagged LARG and Myc-tagged TROY. Twenty-four hours after transfection, cells were lysed and immunoprecipitated with anti-Myc antibody. Immunoprecipitates or WCL were immunoblotted with the indicated antibodies. (F) Colocalization of TROY and PDZ-RhoGEF in T98G, GBM10, and GBM43 cells. Cells were stained and examined by confocal microscopy. TROY was visualized with Alexa Fluor 546–conjugated antibody, and PDZ-RhoGEF was visualized with Alexa Fluor 488–conjugated antibody. The colocalization of TROY (red) with PDZ-RhoGEF (green) appears as a yellow color in the merged image. Cells were counterstained with DAPI (blue) (bars = 10 μm). (G) 293 cells were co-transfected with AU1-tagged TROY, Myc-tagged PRG, and HA-tagged Pyk2, and 24 hours later, cells were lysed and immunoprecipitated with goat anti-Myc or goat anti-AU1 antibodies or goat IgG. Immunoprecipitates or WCL were immunoblotted (IB) with the indicated antibodies. (H) Left panel, 293 cells were transfected with HA-tagged LARG and/or FLAG-tagged Pyk2. Twenty-four hours later, the cells were lysed and immunoprecipitated with anti-FLAG antibody or mouse IgG. Immunoprecipitates or WCL were IB with anti-FLAG or anti-HA antibodies. Right panel, 293 cells were co-transfected with Myc-tagged PRG and FLAG-tagged WT Pyk2 or kinase-deficient (KD) Pyk2 for 24 hours. Cells were lysed and immunoprecipitated with anti-Myc antibody. Immunoprecipitates or WCL were IB with the indicated antibodies.

To determine possible mechanisms through which TROY induces GBM cell invasion, we performed immunoprecipitation of TROY from T98G glioma cells overexpressing TROY and analyzed the precipitates with MALDI-TOF and MS/MS to identify proteins that are capable of interacting with TROY and potentially mediating TROY signaling [13]. Several proteins were identified in the TROY immunoprecipitates, among which PDZ-RhoGEF was of particular interest because it has previously been reported to be involved in cellular motility [30,31]. To confirm the interaction between TROY and PDZ-RhoGEF, 293 cells co-transfected with HA-tagged TROY and Myc-tagged PDZ-RhoGEF were immunoprecipitated with an anti-Myc antibody, and the precipitates were immunoblotted with anti-HA and anti-Myc antibodies. Immunoblotting demonstrated that HA-tagged TROY co-immunoprecipitated with Myc-tagged PDZ-RhoGEF, refuting an interaction between TROY and PDZ-RhoGEF (Figure 1A). Endogenous PDZ-RhoGEF was found to co-immunoprecipitate with endogenous TROY in T98G glioma cells as well as primary GBM patient-derived xenografts GBM10 and GBM43 cells (Figure 1, B-D). The expression pattern of endogenous TROY and TROY interactants in the different cell lines is shown in Supplementary Figure 1. To explore the specificity of the interaction between TROY and PDZ-RhoGEF, we examined whether TROY could interact with LARG, a closely related GEF belonging to the same RhoGEF subfamily as PDZ-RhoGEF. 293 cells were co-transfected with HA-tagged LARG and/or Myc-tagged TROY. Immunoprecipitation of the transfected cell lysates with an anti-Myc antibody followed by immunoblotting of the precipitates with the anti-HA antibody showed that LARG was not present in the TROY-Myc immunoprecipitates, suggesting a specific interaction of TROY with PDZ-RhoGEF (Figure 1E). To further confirm the interaction, we examined the colocalization of TROY and PDZ-RhoGEF by immunofluorescence analysis. T98G, GBM10, and GBM43 cells were stained with anti-TROY and anti–PDZ-RhoGEF antibodies and examined by confocal microscopy (Figure 1F). Consistent with previous results [13], TROY staining was predominately near the cell periphery and enriched in lamellipodia, and the merged images contradicted colocalization of TROY and PDZ-RhoGEF.

substantiating an interaction between TROY and PDZ-RhoGEF (Figure 1A). Endogenous PDZ-RhoGEF was found to co-immunoprecipitate with endogenous TROY in T98G glioma cells as well as primary GBM patient-derived xenografts GBM10 and GBM43 cells (Figure 1, B-D)

and the merged images indicated colocalization of TROY and PDZ-RhoGEF


EDS analysis at the grain boundaries of Fe-6.5 wt % Si steel strip samples: (a) 1.0 wt % Cu, (b) 1.5 wt % Cu, and (c) 2.0 wt % Cu.

Further SEM microstructural examination revealed that Cu rich precipitates were absent in the 1.5 wt % Cu specimen (Figure 8a), but became visible in the 1.5 wt % Cu specimen (Figure 8b). The precipitates in the 1.5 wt % Cu specimen were tiny, few, and irregularly scattered at grain boundaries. Cu-rich precipitates were continuous or semicontinuous at grain boundaries as the Cu dosage was raised to 1.0 wt %, as shown in Figure 8c.


Figure 2. BcR stimulation downregulates cathepsin S activity in IIA1.6 cells. (A)Accumulation of the p10 invariant chain fragment in BcR-stimulated IIA1.6 cells. IIA1.6 cells were incubated for the times indicated with anti–mouse IgG antibodies, as described in Materials and Methods. The p10 fragment was detected with a rabbit antiserum specific for the cytoplasmic tail of the invariant chain. The same blot was incubated with an anti-IA chain antiserum and then with an antitubulin antibody (left). In the right panel, the p10 signal is normalized with the MHC class II signal obtained for the same lane and these p10 signals are expressed in arbitrary units.These results are representative of three independent experiments. (B) IIA1.6 cells were left unstimulated or were stimulated for various times with anti–mouse IgG antibodies and membranes were prepared to assess cathepsin S (top)  hexosaminidase (bottom right), and cathepsin B/L (bottom left) activities in fluorometric assays. Cathepsin S activity was tested at pH 7.0, because cathepsin S is functional at neutral pH, with (white bars) or without (back bars) LHVS, a cathepsin S inhibitor. Error bars correspond to the mean of three experiments. (C) Detection of cathepsin S with an iodinated peptide that binds to the active site of cathepsin S. Stimulated or unstimulated cells were incubated for 1 h with I-Mu-Tyr-Ala-CH2F, with or without LHVS, and cell lysates were then subjected to electrophoresis in 12% polyacrylamide gels. Cathepsin S was detected as a 26-kD band. The labeling of this protein was inhibited by adding LHVS. LHVS did not inhibit the labeling of an higher molecular weight band in the gel at 32 kD, which was identified as cathepsin L. Rat basophilic leukemia cell line cells,which do not produce cathepsin S, were used as a negative control. In the bottom panel, each band was quantified with a PhosphorImager™. Cathepsin S labeling was normalized against labeling of the 32-kD band for each lane and cathepsin S labeling was quantified in arbitrary units.

BcR stimulation, showed an increase in the amount of p10 invariant chain fragment detected with a rabbit antiserum specific for the cytosolic domain of the invariant chain,whereas MHC class II and  tubulin levels remained constant (Fig. 2 A). The effect of BcR stimulation on invariant chain degradation depended on the MHC class II allele; the effect was strongest in IIA1.6 cells–expressing IA. In parental IIA1.6 cells expressing IAd, p10 levels doubled (data not shown), whereas they increased by a factor of 5 in IAk-transfected IIA1.6 cells (Fig. 2 A) and in IIA1.6 cells expressing IAb (data not shown). However, the changes in p10 levels over time were similar for both alleles: the p10 fragment was first detected after 60 min, increased to reach a maximum at 3 h and then returned to its initial level after 6 h of BcR stimulation (Fig. 2 A). No change in de novo MHC class II synthesis was observed in pulse-chase experiments (data not shown). Although MHC class II–peptide complexes were detected in dense fractions after BcR stimulation, the increase in p10 invariant chain fragment levels and the detection of invariant chain, together with MHC class II, in late endosomal compartments after BcR cross-linking suggests that the proteolytic degradation of invariant chain was inhibited during B cell activation. Therefore, we assessed various proteolytic activities during BcR-induced cell activation. IIA1.6 cells were stimulated for various times as described above, and the activities of cathepsin S, cathepsin L/B, and  hexosaminidase were assessed on the same membrane preparations by means of fluorometric assays (23). Cathepsin S activity was measured at pH 7.0 (Fig. 2 B) in membrane preparations of B cells because cathepsin S is active at this pH, whereas cathepsinB is not. We demonstrated that the activity measured corresponded to cathepsin S by adding low concentrations of LHVS. Such low concentrations (1 nM) of LHVS inhibit cathepsin S, but not cathepsin B. Higher concentrations of LHVS (30 nM) are required to inhibit cathepsin B (24). Cathepsin S activity decreased after BcR cross-linking: maximal inhibition (75%) occurred at 3 h, with cathepsin Sactivity progressively increasing thereafter and returning to initial values after 6 h; 18 h after BcR cross-linking, 15%inhibition of cathepsin activity was still observed. No change in  hexosaminidase activity was detected in the same samples, whereas cathepsin L/B activity decreased slightly (Fig. 2 B). We directly measured cathepsin S activity in B cells by labeling stimulated and unstimulatedIIA1.6 cells with an iodinated peptide that bound specifically to the active site of cathepsin S (22). A 26-kD protein,presumably cathepsin S, was specifically labeled in these conditions and this labeling was inhibited in the presence of LHVS peptide. This assay gave similar results to the original assay, as 80% inhibition of cathepsin S labeling was ob-served after 3 h and this inhibition was partially reversible after 18 h (Fig. 2 C). No changes in the amounts of cathepsin S and cystatin C proteins present were detected by Western blotting (data not shown). These results demon-strate that BcR-induced B cell activation downregulated cathepsin S activity, accounting for the transient accumulation of MHC class II–invariant chain complexes in lyso-somes. The changes in MIIC composition induced by B cell activation suggest that BcR stimulation may trigger morphological changes in processing compartments.First, higher levels of transient intracellular accumulation of MHC class II and p10 fragment were observed in IIA1.6 cells expressing class II alleles with a strong affinity for invariant chain such IAk (Fig. 2 A and data not shown).


Figure 5. Summary of genome-wide STAT5 binding sites at L1. (A) The Venn diagram shows the number of identified STAT5A and STAT5B sites (peaks) in AABB tissue and STAT5B sites in BB tissue. (B) Average peak heights of STAT5A and STAT5B in AABB and BB tissues were estimated after library size normalization (RPM, reads per 10 million, input subtracted). (C) Mean fold changes of STAT5A and STAT5B target genes in AABB tissue and STAT5B target genes in BB tissue were calculated. The genes containing STAT5 peaks within ±1 kb around TSSs were regarded as STAT5 target genes. (D) Normalized tag counts (RPM) of STAT5A, RNA polII and H3K4me3 from 200 bp around STAT5A peak centers at L1 were calculated and compared between AABB and BB. Log2-transformed values were used (x and y axes). (E) Normalized tags of H3K4me3 at positions 1 kb upstream and 2 kb downstream of TSS were summed up and divided by the size (3 kb) and then quantile normalized for comparison (top). The scatter plot shows the fold change (x-axis) and difference (y-axis) of H3K4me3 average enrichment between genes (spot) in AABB and BB. Cutoffs for significant changes were set as follows: 1.5-fold change (x-axis, AABB/BB) and four average tag difference (y-axis, AABB/BB). Among the genes showing significant changes of H3K4me3 enrichment, the number of STAT5 target and non-target genes was counted (bottom). (F) Genome browser views represent three gene loci (Wap, Csn1s2a and Stap1) showing changes of H3K4me3 level and one housekeeping gene locus (Actb).

Totals of 26,231 STAT5A and 6,969 STAT5B peaks in wild type (AABB) and 2,574 STAT5B peaks in Stat5a-null (BB) were identified as STAT5 binding sites (Figure 5). For visualization, total number of reads in each sample was normalized to 10 million. The ChIP-seq data are deposited in GEO under accession number GSE40930. In total, more than 26,000 STAT5A peaks were identified in control but not in Stat5a-null mammary tissue (Figure 5). The 6,873 STAT5B peaks almost completely overlapped with the STAT5A peaks in wild-type tissue suggesting that there are no high affinity binding sites restricted to STAT5B. In general, the average STAT5A peak height was 3-fold higher than that of STAT5B (Figure 5B), which is probably the result of a greater abundance of STAT5A and possibly higher antibody affinity. The 2,395 STAT5B binding sites in Stat5a-null and 6,873 STAT5B binding sites in wild-type mammary tissues, which probably reflect high affinity STAT5 binding sites, were a better predictor for gene activation. Indeed, mean expression fold changes of the genes targeted by STAT5B in Stat5a-null mammary tissue were higher than those of the others (Figure 5C). The level of STAT5 binding was positively correlated with the enrichment level of RNA PolII and H3K4me3 near promoter regions (Supplementary Figure S7). Looking in more detail, a cutback of STAT5 by ~70% (BB) resulted in a decreased level of RNA polII but not H3K4me3 near the STAT5 binding sites as overall spots shifted toward AABB (Figure 5D). However, comparison of H3K4me3 enrichment on promoter regions between AABB and BB tissues revealed that some STAT5 target and non-target genes showed a significant decrease of H3K4me3 in BB tissue (Figure 5E; Supplementary Table S4). Manual evaluation of several loci including STAT5 target genes (Wap and Csn1s2a), and a non-STAT5 target gene (Stap1) confirmed the decrease of H3K4me3 marks, which did not occur over the housekeeping gene, Actb (Figure 5F).


Figure 4. Editing and ADAR2-binding reduces splicing efficiency at the Gria2 R/G site. (A) RT-PCR shows a gradual reduction of splicing in the presence of a strong (+/+), intermediate (+/−) or weak (−/−) polypyrimidine tract in wildtype (wt) or pre-edited (pre-ed) versions of a Gria2 exon 13 minigene. Pre-mRNA and mRNA are indicated at the right side of the panel. M = size standard. bp = basepairs. A white asterisk marks an aberrant splicing product. (B) The relative splicing efficiency––measured from the gel in panel A––is given as % unspliced product. Pre-editing reduces splicing efficiency. Quantification was done from four independent biological replicates. (* P-value < 0.05; n.s. not significant). Dark gray = wt, light gray = pre-edited at position -2-3. (C) RT-PCR of Gria2 reporter transcripts in the presence (y) or absence (n) of ADAR2 indicate a strong reduction in splicing in the presence of ADAR2. Pre-mRNA and mRNA are indicated at the right side of the panel. M = size standard. bp = basepairs. (D) The splicing efficiency––deduced from the gel in panel (C)––in percent unspliced transcript is given. The presence of ADAR2 reduces splicing efficiency. The quantification was done from four independent biological replicates (n.s. not significant, * P-value < 0.05; ** P-value < 0.01).

One of the Gria2 minigenes (+/−; Supplementary Figure S2). An even stronger accumulation of pre-mRNA was observed for the pre-edited -2-3 constructs in context with the strongest and weakest branch points (Figure 4A and B). This demonstrates that guanosines and therefore most likely also inosines introduced by editing can interfere with splicing of the Gria2 minigene. Surprisingly, when we transfected the Gria2 minigene (+/+) without the addition of the ADAR2 plasmid we observed a strong reduction in pre-mRNA (Figure 4C and D). Conversely, an increase in pre-mRNA accumulation was observed when the pre-edited -2 version of Gria2 was cotransfected with ADAR2. It thus appears that ADAR2 binding alone impairs splicing, even when editing cannot take place.


Figure 1. Cdc48 and ubiquitin ligases affect the distribution pattern of ribosome-associated ubiquitinated species. Sucrose gradient sedimentation analysis of ribosomes extracted from the wild-type RS1158 strain (A) and its derivative strain harboring a tetracycline-repressible PTET-O7-CDC48 allele (B). Cells were grown in the presence of doxycycline (Dox) for 20 h. Cell lysates were centrifuged through 15%–45% sucrose gradients and fractionated with the continuous measurement of absorbance at 254 nm to visualize ribosomal peaks. Proteins isolated from individual fractions were separated on 10% SDS-acrylamide gels and the same membrane was probed with anti-ubiquitin (top) and anti-Rpl3 (bottom) antibodies. (C) and (D) The same analysis performed in PTET-O7-CDC48 cells lacking either LTN1 or NOT4. All gradients were run at least five times, representative blots are shown; see Supplemental Figure S1 for additional controls. (E) Hygromycin B (HygB) treatment induces accumulation of Ltn1-ubiquitinated 60S products. Where indicated, cells were treated with 100 µg/mL hygromycin for 2 h. Gradient fractions 2–6 were separated on the same gel for a better comparison of total ubiquitination levels. (F) Lack of LTN1 makes cells hypersensitive to hygromycin. Five-fold dilutions of wild-type B4741 (WT) and ltn1Δ strains were grown on plates without antibiotic or with 100 µg/ml hygromycin for 3 days at 30°C.

RESULTS Gradient analysis of ubiquitinated polypeptides associated with ribosomes in Cdc48-depleted cells To examine how endogenous targets of cotranslational protein QC are distributed among different subpopulations of ribosomes in yeast cells, we fractionated cytoplasmic lysates by sedimentation through sucrose gradients. We observed a smear of ubiquitinated translation products in fractions containing polysomes and 80S monosomes in wild-type cells (Figure 1A, Supplementary Figure S1A), consistent with the previously described ubiquitination of ribosome-associated NCs (3,4). Previous studies have shown that loss of Cdc48 function increases accumulation of ubiquitinated NCs associated with ribosomes (2–4). To better define this effect, we analyzed yeast strains in which CDC48 is placed under the control of a tetracycline-regulatable promoter (PTET-O7-CDC48) (39). Depletion of Cdc48 by addition of doxycycline (Dox) to growing yeast cultures significantly increased the intensity of the ubiquitin signal in these cells (Figure 1B, Supplementary Figure S1A-D), as expected from stabilization of ubiquitinated NCs that normally undergo Cdc48-assisted degradation by the proteasome (4). The ubiquitin signal in Cdc48-depleted cells was mainly concentrated in fractions 4-7 (Figure 1B), corresponding to the peaks of 60S subunits (fractions 3 and 4) and 80S monosomes (fractions 4 and 5). In this and other experiments, the equivalent separation of ribosomal fractions on gradients was controlled by comparing alignment of A260 traces of the gradients, gel analysis of rRNA from the same fractions that were used for protein isolation, Ponceau S staining to control protein transfer, and probing with antibodies against ribosomal protein Rpl3 (Supplementary Figure S1A). When it was necessary to compare absolute levels of ubiquitinated species between different strains, we analyzed fractions side by side on the same gel to rule out variations between processing of individual membranes (Supplementary Figure S1D). Notably, the increase in ubiquitination of the 80S fraction was not due to redistribution of ribosomes from polysomes to the 80S monosome form in Cdc48-depleted cells, as shift of wild-type cells to medium lacking glucose (a condition known to inhibit translation initiation) resulted in elevated 80S levels comparable to those in Dox-treated PTET-O7-CDC48 cells, but did not cause accumulation of polyubiquitinated peptides in the 60S–80S fractions (Supplementary Figure S1E). Thus, Cdc48 depletion leads to increased accumulation of ubiquitinated polypeptides associated predominantly with 60S and 80S ribosomes. We next examined the distribution of ubiquitin-conjugated species in the 60S–80S fractions of PTET-O7-CDC48 strains containing additional deletions in genes of E3 ligases implicated in cotranslational QC. Consistent with previous findings obtained with model substrates (4,14,15,40), an ltn1Δ deletion completely abrogated the accumulation of ubiquitin-modified NCs in fractions that contained free 60S subunits, but not in the 80S fraction (Figure 1C). In contrast, a Cdc48-depleted strain lacking Not4, part of the Ccr4-Not deadenylase complex reported to ubiquitinate polypeptides associated with stalled ribosomes (19,27), showed a diminished intensity of the ubiquitin signal in the 80S fraction, whereas accumulation of ubiquitinated products in the 60S fraction remained constitutively high (Figure 1D). These results support the notion (2,10,14,15) that Ltn1 is a primary, and possibly unique, E3 ligase responsible for ubiquitin tagging of the 60S-associated NCs, a process necessary for Cdc48 recruitment and polypeptide degradation. To further investigate whether the observed accumulation of 60S-associated products ubiquitinated by Ltn1 is related to aberrant polypeptide synthesis during translation, we treated cells for 2 h with hygromycin B, an aminoglycoside that causes decoding errors, stop codon readthrough and ribosomal stalling (41–43). In wild-type cells, hygromycin treatment significantly increased the amount of polyubiquitinated products present in the 60S–80S fractions (Figure 1E). Similarly to PTET-O7-CDC48 ltn1Δ cells, deletion of LTN1 abrogated the accumulation of ubiquitinated products in the 60S, but not 80S fraction in the hygromycin-treated cells (Figure 1E). Consistent with a role of Ltn1 in resolving translation errors caused by hygromycin, ltn1Δ cells are hypersensitive to this antibiotic (Figure 1F). These results support the idea that the Ltn1-Cdc48-mediated QC mechanism can capture a variety of defective translational products that remain associated with the large ribosomal subunit after splitting of the ribosome. We found that the ubiquitin signal in the 60S fraction was greatly reduced compared to wild-type cells, although these cells continued to display the robust accumulation of ubiquitinated 80S complexes, resembling the effect of the ltn1Δ deletion (compare Figure 4B, right with Figure 1C).


Figure 5. Increased U12-dependent intron retention in SMA mice. (A) qPCR validation of U12-dependent intron retention at PND1 and PND5 in spinal cord. (B) qPCR validation of U12-dependent intron retention at PND1 and PND5 in brain. (C) qPCR validation of U12-dependent intron retention at PND1 and PND5 in liver. (D) qPCR validation of U12-dependent intron retention at PND1 and PND5 in muscle. Error bars indicate SEM, n ≥ 3, ***P-value < 0.001, **P-value < 0.01, *P-value < 0.05. White bars indicate heterozygous control mice, gray bars indicate SMA-like mice. Spl = spliced, Unspl = unspliced/retained intron.

We validated the decrease in retention of the U12-dependent intron and the decrease of the levels of spliced Rasgrp3 by specific qPCR assays in all tissues, at both PND1 and PND5 (Figure 5 and 6). Since retention of the intron could lead to degradation of the transcript via the NMD pathway due to a premature termination codon (PTC) in the U12-dependent intron (Supplementary Figure S10), our observations point out that aberrant retention of the U12-dependent intron in the Rasgrp3 gene might be an underlying mechanism contributing to deregulation of the cell cycle in SMA mice. In the spinal cord, a U12-dependent intron in Myh9 was retained, together with upregulation of Myh9 transcripts in general. As in the case of Rasgrp3, this may be due to a PTC being present within the U12-dependent intron (Supplementary Figure S13). Validation with qPCR confirmed the downregulation of spliced Myh9 and upregulation of unspliced Myh9 in both spinal cord and brain (Figure 5A and B), whereas there was increased retention of the U12-dependent intron in liver and muscle (Figure 5C and D). This could indicate that the NMD pathway is more effective in the CNS, and perhaps explain why we detected fewer U12-dependent intron retention events in peripheral tissue than in the CNS.


Figure 1. BRD4 is required for osteoblast differentiation. (A and B) Alkaline Phosphatase staining of hFOBs differentiated into the osteoblast lineage following DMSO or JQ1 (250nM) (upper panel) and siCNTR or siBRD4 (SmartPool) (lower panel) treatments (A). The stained areas were quantified and displayed as percentage of whole area. Mean ± SD, n = 2 (B). Student’s t-test was performed for statistical analysis where ***P < 0.001, **P < 0.01, *P < 0.05 (C). The relative expression of osteoblast marker genes in hFOBs in undifferentiated (UND) and differentiated (DIF) state following siBRD4 or JQ1 treatment was evaluated via qRT-PCR and normalized to expression level of RPLP0 and the expression in the undifferentiated state. Mean ± SD, n = 3. One-way ANOVA followed by Turkey’s test was performed for statistical analysis where ***P < 0.001, **P < 0.01, *P < 0.05. (D and E). Mouse IDG-SW3 osteocyte cells were differentiated for 14 and 26 days following DMSO or JQ1 treatment and stained with alizarin red for detection of mineralized.

RESULTS BRD4 promotes osteoblast differentiation. To examine the function of BRD4 during lineage specification and maintenance, we examined the effects of BETi on the differentiation of hFOBs (32). Perturbation of BRD4 function by BETi (JQ1) treatment or siRNA-mediated knockdown (Supplementary Figure S1A and B) resulted in a significant decrease of differentiation-induced alkaline phosphatase activity (Figure 1A and B; Supplementary Figure S1C and D). Gene expression analyses confirmed these findings and showed a reduced expression of the osteoblast-specific genes RUNX2, TNFRSF11B (Osteoprotegerin) and ALPL following JQ1 treatment or BRD4 knockdown (Figure 1C). To investigate whether this effect was limited to early stages of lineage-specification, we also tested the effect of BRD4 inhibition on IDG-SW3 mouse osteocytes. Despite their advanced stage of differentiation, mineralization was significantly impaired following JQ1 treatment (Figure 1D and E). Consistently, BETi treatment resulted in reduced expression of the osteoblast/osteocyte-specific genes Mepe, Bglap and Dmp1 (Figure 1F). The role of BET proteins in controlling osteoblast differentiation was differentiation-stage independent since similar effects were also observed in multipotent hMSC, where knockdown or inhibition of BRD4 also potently affected the expression of osteoblast lineage-specific genes (ALPL, COL1A1 and BGLAP; Supplementary Figure S1E and F). In order to gain a more complete overview of the effects of BRD4 on the regulation of lineage-specific gene expression, we performed transcriptome-wide mRNA-seq analyses following BRD4 depletion or JQ1 treatment in hFOB cells (Supplementary Figure S1G). Inhibition of BRD4 by JQ1 resulted in the differential regulation of a selected subset of genes. Consistent with the positive role of BET proteins in gene transcription, we observed less downregulated genes compared to upregulated genes following JQ1 treatment (Figure 1G). Interestingly, a large fraction of BETi-regulated genes were also differentially regulated during osteoblast differentiation, further supporting a lineage-specific function of BRD4 (Figure 1G–I). Consistent with the fact that JQ1 targets all BET proteins including BRD2, -3 and -4 (56) and the potential differences induced by inhibition of bromodomain-mediated protein-protein interactions versus effects observed following a complete loss of BRD4 protein expression, the effects of JQ1 and BRD4 knockdown were not identical (Figure 1G–I). However, both treatments showed a similar effect of preferential downregulation of differentiation-induced genes (Figure 1I). Moreover, GSEA on siBRD4-downregulated genes indicated a significant enrichment for pathways associated with extracellular matrix, collagen and skeletal development (Figure 1J). JQ1-downregulated genes were similarly enriched for developmental pathways (Supplementary Figure S1H). Taken together, these results suggest a role of BRD4 in maintaining and directing osteoblast-specific lineage gene expression. Interestingly, some ‘Segment 3+4’ regions showed co-occupancy of all TFs (Supplementary Figure S6A) while some osteoblast-specific BRD4 target genes such as TNFRSF11B (Figure 1C), ELN and DCN (Supplementary Figure S5C) showed distinct occupancy of the identified TFs at putative enhancer sites located within 50 kb of the genes (Figure 5K; Supplementary Figure S6B and E).


Figure 2. Increased blood glucose in Kir6.1-GOF mice. (A–C, left) Representative intrinsic GFP fluorescence in freshly isolated islets from transgenic mice. High fluorescence in transgenic islets indicates the presence of the Kir6.1 transgene (Kir6.1[x], Control), and loss of fluorescence in transgenic β cells within islets after Cre-recombination (Rip-Kir6.1[x]) indicates actual expression of the transgene specifically in these cells. Bars, 10 µm. (right) Fed blood glucose over time after weaning in Rip-Kir6.1[WT] (A, black), single mutant Rip-Kir6.1[GD] (B, green), and double mutant Rip-Kir6.1[GD,QR] (C, red) with respect to their control littermates (white). Data represent mean ± SEM, n = 8–10 animals in each group. Significant differences (*, P < 0.05) between transgenic and control littermate mice are indicated (t test).

To study the effects of Kir6.1 subunits of the KATP channel in vivo, we have generated novel mice that express either the Kir6.1 WT (Kir6.1[WT]) or a Kir6.1-GOF, single mutant G343D (Kir6.1[GD]) or double mutant G343D/Q53R (Kir6.1[GD,QR]) transgenes under Cre-recombinase control (Li et al., 2013). Global Cx1 Kir6.1[WT], Kir6.1[GD], and Kir6.1[GD,QR] mice express GFP fluorescence ubiquitously in the whole body, but after tissue-specific Cre-recombination, these mice lose fluorescence only in the tissue of interest (Li et al., 2013). Specific expression in pancreatic β cells was achieved by crossing Kir6.1 transgenic mice with Rip-Cre mice. Fig. 2 shows marked gain of fluorescence in pancreatic islets from double transgenic Rip-Kir6.1[WT] (A), Rip-Kir6.1[GD] (B), and Rip-Kir6.1[GD,QR] (C; as an indication of transgene expression), compared with bright fluorescent islets from single Kir6.1[WT], Kir6.1[GD], and Kir6.1[GD,QR] transgenic mice (lacking recombination and absence of transgene expression). Littermate control mice in all experiments below include pooled WT, single transgenic Rip-Cre, and single transgenic Kir6.1[GD] or Kir6.1[GD,QR] mice. In each case, no significant differences were found between these genotypes when independently tested. Diabetes in Kir6.1-GOF mutant mice GOF mutations in the Kir6.1 subunit of the KATP channel result in either glucose intolerance (Rip-Kir6.1[GD]) or frank diabetes (Rip-Kir6.1[GD,QR]), mimicking the consequences of weak or more significant expression of Kir6.2-GOF transgenes (Koster et al., 2000, 2005; Remedi et al., 2009). 7-wk-old double transgenic Rip-Kir6.1[GD] mice showed higher fed glucose than littermate control mice (Fig. 2 B). They also demonstrate increased fasting blood glucose and a mildly impaired glucose tolerance, accompanied by reduced circulating plasma insulin after glucose challenge with respect to control littermates (Fig. 3 B). Importantly, however, 2 out of 10 Rip-Kir6.1[GD] mice showed diabetes with dramatically low fasting blood glucose levels and a marked impairment of glucose tolerance (Fig. 2 B). Strikingly, all Rip-Kir6.1[GD,QR] mice developed severe diabetes (Fig. 2 C) with markedly impaired glucose tolerance, as the result of significantly reduced plasma insulin levels in response to glucose challenge (Fig. 3 C). Importantly, however, and as expected, overexpression of WT Kir6.1 subunits in Rip-Kir6.1[WT] mice did not result in increased blood glucose or glucose intolerance (Figs. 2 A and 3A), suggesting that impaired glucose tolerance and diabetes are promoted by Kir6.1-GOF and are not an artifactual consequence of overexpressed transgenic protein levels perse.


Figure 2Id-immunized mice are protected against MM cells that produce complete myeloma protein while they succumb to FLC MM cells. (A–H) BALB/c mice were immunized i.m./EP with 50µg CCL3-scFv315 or NaCl and challenged 14 days later with MOPC315.BM.Luc.IgAλ2 cells (2×105) that produce complete M315, (left panel), (A–D) or MOPC315.BM.λ2 cells (2×105) that produce only free λ2 L chains (right panel), (E–H). (A, E) Images of whole body bioluminescence (BLI) showing mean±SEM, (B, F) representative ventral images, (C, G) serum M315 on days 0, 21 and 35 in individual mice, and (D, H) survival. End point was paraplegia. n=5–8 mice/group. Statistics: Two-way ANOVA with Bonferroni correction (A, C, E, G) and Mantel Cox Log-Rank test for survival (D, H). *p<0.05, **p<0.01, ****p<0.0001. ANOVA, analysis of variance; MM, multiple myeloma; ND, not detected; ns, not significant.

The phenomenon was confirmed in experiments using luciferase-labeled MOPC315.BM.Luc cells injected intravenously and bioluminescence as a read-out for tumor load (online supplemental figure 2). Thus, while radiance and M315 levels correlated strongly in the CCL3-scFvA20-immunized mice, there was no such correlation in the CCL3-scFv315-immunized mice. Immunized mice are protected against MOPC315.BM.Luc.IgAλ2 while they succumb to the FLC variant. Having developed cloned MOPC315.BM cell lines that either secrete H+L myeloma protein (MOPC315.BM.Luc.IgAλ2) or only free λ2 L chains (MOPC315.BM.Luc.λ2), we tested these two cell lines in challenge experiments. Mice were immunized with CCL3-scFv315 and challenged 14 days later with either of the two variants. NaCl was used as a negative control. Six out of eight immunized mice were protected against cells that produced complete M315 (MOPC315.BM.Luc.IgAλ2), as measured by bioluminescence imaging (BLI) (figure 2A,B), serum M315 (figure 2C) and survival (figure 2D). However, three mice had a bioluminescence signal and M315 in their sera (figure 2C); these two mice developed paralysis and did not survive (figure 2D). In contrast, CCL3-scFv315 immunized mice were not protected against cells that only produced free λ2 L chains (MOPC315.BM.Luc.λ2) measured either by BLI (figure 2E–F) or by survival (figure 2H). As would be expected, none of the mice challenged with the FLC MM cells had detectable serum levels of M315 throughout the experiment (figure 2G). These results indicate that H chain-expression by MOPC315 MM cells is required for CCL3-scFv315 immunization to have a protective effect. In line with this, splenocytes from extensively immunized mice killed MOPC315.BM.Luc.IgAλ2 cells more efficiently than MOPC315.BM.Luc.λ2 cells, in vitro (online supplemental figure 6).


Three chosen parameters measured for one additional cells: (a, d) Dry mass (R² = 0.9344 for the upper graph and R² = 0.8961 for the lower graph); (b, e) Phase skewness (R² = 0.87 for the upper graph and R² = 0.8471 for the lower graph); (c) Phase variance (R² = 0.9801 for the upper graph and R² = 0.954 for the lower graph).

Figure 11 presents the measured values for two additional HeLa cells. The dry mass values seen in Figures 11(a, d) for both of the cells show similar behavior and values to each other and to the previously described cells during all of the cell phases, although different cells have different lifecycle periods. The lifecycle phase classification was established based on the dry mass values combined with the statistical parameters as described before. The values of phase skewness presented in Figures 11(b, e), besides the values during the G2 phase, show similar behavior to the measurement presented in Figure 8(b). We assume that the differences during the G2 phase are due to the influence of the apoptosis of the cell. Nevertheless, the result shows that the G1 and S phases can be distinguished by the phase skewness. The phase variance presented in Figures 11(c, f) is used to describe the sub-phases of the M phase. Although Figures 11(c, f) show reduced ability to distinguish between the different sub-phases of the M phase compared to the results shown in Figure 8(c) due to reduction in the sampling time of the additional cells (from two frames per minute to a frame per two minutes), the sub-phases can still be discerned.


qPCR validation of PUNCH-P results. (A, top panel) Polysome profiles of HeLa cells synchronized to S and M phase by double-thymidine block. (Bottom panel) Total RNA extracted from each of the polysomal fractions visualized by ethidium bromide staining. (B, C) Polysomal association of nonfluctuating mRNAs encoding for CALR (B) and CYCS (C). (D) Polysomal association of mRNAs encoding for proteins that were elevated in S phase according to PUNCH-P. (E) Polysomal association of mRNAs encoding for proteins that were elevated in M phase according to PUNCH-P. Graphs show mean ± SD of qPCR replicates for one of three independent experiments with similar results. (C–E) represent qPCR results normalized to CALR.

To validate some of these results and provide further evidence for the potential of PUNCH-P to measure differences in translation of specific mRNAs, we analyzed the polysome association of selected mRNAs in S and M phase. We chose two proteins whose PUNCH-P expression remained stable throughout the cell cycle and six proteins whose expression fluctuated between S and M phase. Such fluctuations at the protein level can result from differences in total mRNA abundance, translation efficiency, or both. We initially compared the polysome profiles of HeLa cells synchronized to S and M phase and found no differences in polysome size (Figure 6A, top panel). Next, we extracted total RNA from each of nine polysomal fractions ranging from light to heavy polysomes (Figure 6A, bottom panel) and measured the abundance of specific mRNAs in each fraction using SYBR Fast quantitative PCR (qPCR). As predicted, we found that the relative amount and polysomal distribution of the two transcripts encoding nonfluctuating proteins—calreticulin (CALR) and cytochrome C (CYCS)—remained constant between the different cell-cycle stages (Figure 6B,C). We then measured the amount of the six transcripts encoding fluctuating proteins in each polysomal fraction and normalized the results to CALR mRNA to allow a more accurate quantitative comparison of mRNA amounts across the gradients. As predicted by PUNCH-P, the amounts of polysome-associated FOSL1 (FOS-like antigen 1), CCRN4L (nocturnin), and BRIP1 (Fanconi anemia group J protein 1) were significantly higher in S phase (Figure 6D). Similarly, the amounts of polysome-associated CCNB1 (cyclin B1), GPSM2 (G-protein signaling modulator 2), and PCF11 (pre-mRNA cleavage complex 2 protein) mRNA were higher in M phase, consistent with PUNCH-P results (Figure 6E). In addition to the differences in absolute amounts, we calculated relative mRNA distribution between heavy (five or more) and light (fewer than five) polysomes as a percentage of total polysomes. While some mRNAs showed little difference in relative distribution, others changed considerably: association of CCRN4L and BRIP1 mRNAs with heavy polysomes decreased from 82.4 % and 43.3 % in S phase to 73.5 % and 29.2 % in M phase, respectively. Conversely, association of CCNB1 mRNA with heavy polysomes increased from 63.8 % in S phase to 84.3 % in M phase, as expected for an mRNA that is translationally up-regulated during mitosis (Groisman et al., 2000).


MeRIP-seq analysis of four RNAs tested for m⁶A status in this work. These include one lncRNA, TUG1 (A), and three mRNAs: ACTB (B), TPT1 (C), and BSG (D), analyzed in three different human cell lines (HeLa, HepG2, and HEK293T). SCARLET-tested sites are marked with bold arrows. Sites that tested positive for m⁶A are indicated by purple arrows, while sites that tested negative for m⁶A are indicated by blue arrows.

We also determined the m6A status in many RRACH sites in another lncRNA (TUG1) and three mRNAs (ACTB, TPT1, and BSG), chosen on the basis of the m6A/MeRIP-seq results (Fig. 4). Among the sixteen sites tested, only four showed m6A modification >5% (Table 2). This result shows that the previously reported 20% m6A modification in bovine prolactin mRNA (Narayan and Rottman 1988) is not abnormal, suggests that many sites in mRNA carry complete m6A modification, and highlights that not every RRACH consensus sequence sites under the m6A/MeRIP-seq peaks are modified.