Figure 7 (A and B) The BAL fluids and lungs were harvested 24 h after last rmIL-33 challenge to measure the protein expression of IL-1α, IL-5, IL-13, CCL11, CCL17, CCL22 and CCL24. (C) Cell differentials from BAL fluids harvested 24 h after the last rmIL-33 challenge. The results are shown as mean ± SEM of four mice in PBS-challenged groups and 11 mice in rmIL-33-challenged groups. *p < 0.05.

We assessed cell differentials and cytokine and chemokine expression levels in the BAL fluid and lung homogenates 24 h after rmIL-33 challenge for four consecutive days (Figure 6A). IL-1α protein expression was not changed by exogenous rmIL-33 challenge in lung homogenate (Figure 7A). This result is consistent with a previous report that IL-33 neutralisation by soluble ST2 administration had no effect in house dust mite extract-induced lung IL-1α protein expression in a mouse model. On the other hand, protein expression of IL-5 and IL-13 in both BAL fluids and lung homogenates was significantly increased in rmIL-33-challenged mice compared with vehicle-challenged mice (p < 0.05); and TSA treatment significantly increased the rmIL-33-induced IL-5 and IL-13 protein expression compared with TSA–vehicle treatment (p < 0.05) (Figure 7B). CCL11 and CCL24 were also increased in lung homogenates from rmIL-33-challenged mice compared with vehicle-challenged mice (p < 0.05); and TSA treatment significantly decreased the rmIL-33-induced CCL11 and CCL24 expression in lung homogenates compared with treatment with the vehicle for TSA (p < 0.05) (Figure 7B). rmIL-33 challenge significantly induced CCL17 and CCL22 expression in lung homogenates (p < 0.05), but TSA treatment did not decrease these chemokines compared with treatment with the vehicle for TSA (Figure 7B). Further, there was a statistically significant decrease in the number of total BAL cells and eosinophils in rmIL-33-challenged mice treated with TSA compared with rmIL-33-challenged mice treated with vehicle (p < 0.05) (Figure 7C). These results suggest that TSA treatment suppresses IL-33-induced Th2 cytokine and eosinophil chemotactic chemokine expression, and subsequent eosinophil accumulation in the airway.

and TSA treatment significantly decreased the rmIL-33-induced IL-5 and IL-13 protein expression compared with TSA–vehicle treatment (p < 0.05) (Figure 7B)


Figure 4. Binding of a2NTD and intracellular cytokine production in monocyte subpopulations. (A–D) Peripheral blood mononuclear cells (PBMCs) were incubated with 10 μg/mL a2NTD conjugated to Alexa Fluor 488 (a2NTD-AF488) for 1 h and then surface stained with anti-CD14-Pacific Blue and anti-CD16-PE antibodies. (A) Percentage of monocyte populations positive for a2NTD-AF488 (means ± SEM, n = 10, # p < 0.005, CD14+CD16+ vs. CD14+CD16− or CD14+CD16+ cells). (B–D) PBMCs were kept in control conditions or stimulated with 10 ng/mL a2NTD for 18 h and sequentially stained for surface expression of CD14/CD16 and the intracellular expression of interleukin (IL)-1α: (B), IL-1β (C) and tumor necrosis factor α (TNFα) (D). The bar graph reports the percentage of a2NTD-positive cells (means ± SEM, n = 5, *p < 0.05, ** p < 0.001, compared with unstimulated cells of the same subpopulation).

Uptake of a2NTD by monocyte subsets. To determine if different monocyte subsets preferentially internalize a2NTD, monocytes were stained for the surface markers CD14 and CD16 after incubation with a2NTD. CD14++CD16− cells constitute the majority of all monocytes, while CD14++CD16+ and CD14+CD16++ represent two minor subpopulations.25 We were able to retrieve these three populations by flow cytometry (Table 1). Of note, nearly 80% of CD14++CD16+ monocytes were positive for a2NTD endocytosis, as compared with approximately 90% of CD14++CD16− monocytes. The CD14+CD16++ population showed a a2NTD uptake profile similar to that of CD14++CD16− cells (Figure 4A). a2NTD stimulates IL-1α and IL-1β production. It has previously been shown that a2NTD stimulates monocytes to produce the pro-inflammatory cytokines IL-1α and IL-1β.17,18 We examined whether a particular subset of monocytes is responsible for the production of inflammatory cytokines following a2NTD stimulation. To this aim, monocytes were incubated with a2NTD and then stained for surface CD14 and CD16 expression, followed by staining for the intracellular cytokines IL-1α, IL-1β and TNF-α. Only CD14++CD16+ monocytes showed a statistically significant increase in IL-1α production when compared with cells maintained in control conditions (Figure 4B). Both CD14++CD16− and CD14++CD16+ monocytes produced significantly higher amounts of IL-1β (Figure 4C). There was no significant difference in the production of TNFα by cells treated with a2NTD and control cells (Figure 4D). Of note, the CD14++CD16+ subpopulation invariably produced higher amounts of IL-1α, IL-1β and TNFα than the other two subpopulations. In addition, the intracellular levels of IL-1α and IL-1β were greater than those of TNFα. This finding is consistent with our previous data demonstrating that monocytes produce more IL-1 than TNF.16 LPS contamination of the recombinant peptide is always a concern when investigating inflammatory cytokines. A multiexperimental approach was used to investigate the presence of LPS contamination, including the Limulus assay and polymyxin B neutralization tests. The results (which have previously been published) demonstrated negligible levels of LPS and that cytokine secretion could not be inhibited by pre-treatment with polymyxin B.16

as compared with approximately 45% of CD14++CD16− monocytes

nearly 100% of CD14++CD16+ monocytes were positive for a2NTD endocytosis,


Reduced GRHL2 level triggers expression of EDC proteins in differentiating keratinocytes. (a) Rapidly proliferating NHEK were serially subcultured until senescence, and western blotting was performed at varying PD levels for GRHL2, IVL, Jmjd3, and p16INK4A.(b) NHEK were exposed to 1.5mM Caþþfor up to 3 days and collected for western blotting for GRHL2, Jmjd3, IVL, and GRHL3. (c) HaCaT cells were infected with LV-EGFP or LV-GRHL2i to knock down endogenous GRHL2. The cells were then exposed to 2.0mM Caþþ for 3 days and harvested for western blotting for GRHL2, Jmjd3, IVL, FLG, KRT1, GRHL1, GRHL3, and Jmjd3. Arrow indicates the expected size of GRHL3 (B 60kDa). For all experiments, GAPDH (glyceraldehyde 3-phosphate dehydrogenase) was used as a loading control

To understand the mechanism by which GRHL2 inhibits EDC gene expression and keratinocyte differentiation, we explored the functional relationship between GRHL2 and epigenetic gene regulation by Jmjd3. In NHEK with increasing PDs, GRHL2 levels progressively decreased while the levels of IVL and p16INK4A decreased (Figure 5a). Caþþ-induced terminal differentiation in NHEK led to induction of IVL and decreased GRHL2 expression (Figure 5b). In both serially subcultured cells and those exposed to Caþþ, changes in Jmjd3 level were remote. In another experiment, expression of endogenous GRHL2 was knocked down in HaCaT cells by lentiviral vector expressing shRNA against GRHL2 (LV-GRHL2i). HaCaT cells were used herein because these cells express high level of endogenous GRHL2 and undergo normal keratinocyte differentiation when exposed to physiological Caþþ level (Figure 4b). As a control, HaCaT cells were infected with an empty viral vector (LV-EGFP). GRHL2 knockdown in HaCaT led to induction of IVL, FLG, and KRT1 even in the absence of Caþþ treatment to the levels similar to Caþþ-exposed control cells (Figure 5c).

GRHL2 levels progressively decreased while the levels of IVL and p16INK4A increased (Figure 5a)


Figure2 Roles of ALK5 receptor and ROS in TGF-b-induced apoptosis in HUVECs. (a) Effects of the ALK5 inhibitor SB431542 (2mM) on TGF-b (10ng/ml for 24h)induced caspase 3/7 activation. (b) Effects of SB431542 on TGF-b-induced caspase 3 cleavage. (c) Effects of SB431542 on TGF-b-induced DCm depression (reduced red fluorescence) as detected with JC-1 staining (representative images of three independent experiments). The red fluorescence specifically labeled the mitochondria. (d) Effects of TGF-b and SB431542 on intracellular ROS production detected with DCFH-DA (green fluorescence). (e) Effects of antioxidant compounds NAC (1mM) and EUK-134 (100mM) on TGF-b-induced caspase 3/7 activation. Data are mean±S.E.M. *Po0.05 versus control (Con), **Po0.05 versus TGF alone, one-way ANOVA (n¼3–5)

TGF-b-induced apoptosis is dependent on ALK5 and ROS. To examine whether the ALK5 receptor was involved in TGF-b-induced apoptosis, HUVECs were pre-treated with the ALK5 inhibitor SB431542. Treatment with SB431542 at 2mM enhanced the apoptotic response induced by TGF-b as indicated by caspase 3/7 activation and caspase 3 cleavage (Figures 2a and b). Moreover, we showed that SB431542 also prevented the collapse of mitochondrial membrane potential (DCm) in response to TGF-b as measured with JC-1 staining (Figure 2c and Supplementary Figure S1). Using 20,70-dichlorofluorescin diacetate (DCFH-DA) fluorescence, we found that TGF-b treatment enhanced intracellular ROSproduction in HUVECs, and this effect could be blocked by SB431542 (Figure 2d and Supplementary Figure S1). To elucidate the role of ROS in TGF-b-induced apoptosis, we preincubated the cells with antioxidant compounds N-acetyl-L-cysteine (NAC) or EUK-134. We showed that both NAC and EUK-134 abrogated TGF-b-induced caspase 3/7 activation (Figure 2e).

Treatment with SB431542 at 2mM abolished the apoptotic response induced by TGF-b as indicated by caspase 3/7 activation and caspase 3 cleavage (Figures 2a and b)


Morphological and growth characterization of hBMCs and hPDCs. (A) Growth curves of hBMCs (human bone marrow derived cells) and hPDCs (human periosteum-derived cells) over 2 weeks in culture. (B) Phase contrast images of hBMCs and hPDCs at one day after seeding at 5 k/cm2, 25 k/cm2, and 85 k/cm2 (scale bar 5 100 mm). White arrowheads indicate flattened morphology whereas black arrowheads indicate spindle-shaped morphology. (C) Growth kinetics of hBMCs (2 donors/2 experiments) and hPDCs (4 donors) seeded at different densities from passage 4. All error bars indicate standard error of the mean (n53 hBMC donors or 4 hPDC donors).

Independently of the cell culture vessel used, hPDCs proliferated faster than hBMCs and reached full confluence after 7 days (Fig. 1A) when initially seeded at low seeding density (5000 cells/cm2). In addition, the cell density of hPDCs obtained at confluence was consistently higher as compared to hBMCs, which suggested that hPDCs are smaller than hBMCs. Indeed, side-by-side comparison of adherent hBMC and hPDC populations under phase contrast microscopy suggested that hBMCs were more spread on tissue culture plastic with a broader cytoplasmic body than hPDCs (Fig. 1B, white arrows), whereas hPDCs displayed a more spindle-shaped phenotype (Fig. 1B, black arrows). To examine how initial seeding density impacted hBMC and hPDC populations, we empirically chose three seeding densities, 5000 (5 k/cm2), 25000 (25 k/cm2), and 85000 (85 k/cm2). When seeded at 5 k/cm2, both hPDCs and hBMCs attached efficiently as mostly isolated cells with few if any cell–cell contacts. At 25 k/cm2, both cell types arranged in a nearly confluent, but not densely packed, monolayer of cells in which cells remained well spread against the substrate but also displayed augmented cell–cell contact. At 85 k/cm2, both cell types appeared smaller, highly packed, and extended processes over each other (Fig. 1B), but a significant number of hBMCs did not attach after seeding at 85 k/cm2. Because differentiation experiments last one to two weeks, we quantified the extent to which cell proliferation affected cell density over time at the different seeding densities. hBMCs seeded at 5 k/cm2 or 25 k/cm2 reached a cell density of 35 k/cm2 (62.6 k/cm2) and 41 k/cm2 (64.1 k/cm2), respectively, whereas hPDCs at those seeding densities expanded to 55 k/cm2 (65k/cm2)and 64 k/cm2 (64.6 k/cm2). Cell density did not change over time for both cell types when seeded at 85 k/cm2, though fewer hBMCs than hPDCs attached at this density (Fig. 1C).

hPDCs proliferated faster than hBMCs and reached full confluence after 10 days (Fig. 1A) when initially seeded at low seeding density (5000 cells/cm2)


FIGURE 3. Co-i-cIDPRE evokes Ca2+ increase in human Jurkat cells after UV photolysis. A, Co-i-cIDPRE (200 µM) incited much weaker Ca2+ increases after UV photolysis than that by cIDPRE (200 µM) in Jurkat cells. Fluo-4-loaded cells were incubated in regular HBSS containing extracellular Ca2+ during the experiment. B, after Fluo-4-loaded Jurkat cells were incubated with Co-i-cIDPRE (120 µM) in regular HBSS containing extracellular Ca2+, washing away Co-i-cIDPRE in the medium did not have any effect on Ca2+ changes triggered by uncaging of Co-i-cIDPRE. C and D, in Fluo-4-loaded Jurkat cells, uncaging of Co-i-cIDPRE triggered Ca2+ increases in a dose-dependent manner in both the presence (C) and the absence of extracellular Ca2+ (D). E, in Fluo-4-loaded Jurkat cells, thapsigargin (10 µM) pretreatment promoted Co-i-cIDPRE (120 µM)-induced Ca2+ increases in the absence of extracellular Ca2+. Data quantifications of [Ca2+]i peak induced by drug treatment in A, C, D, and E were expressed as mean ± S.E., n = 30 – 40 cells, *, p ≤ 0.05. In A, C, D, and E, cells were all continuously incubated with Co-i-cIDPRE throughout the experiments.

It has been shown that cADPR targets the RyR, but which specific isoform it targets remains to be determined (1–3). Here we showed that both RyR2 and RyR3 are expressed in Jurkat cells. Individual knockdown of these isoforms inhibited cIDPRE- or cADPR-induced Ca2+ release to a similar extent, whereas double knockdown of both isoforms abolished cADPR-induced Ca2+ release in Jurkat cells (Fig. 4E). These data indicate that cADPR does not distinguish either isoform. However, it still remains to be determined whether cADPR binds directly to the RyRs or through some unknown proteins. Recently, the long sought after store-operated Ca2+ entry proteins were identified using a genome-wide RNAi screen by several groups (36–38). Co-i-cIDPRE could be a valuable tool to be used in a similar cell-based screening for cADPR-interacting proteins or regulators.

Co-i-cIDPRE (200 µM) incited much stronger Ca2+ increases after UV photolysis than that by cIDPRE (200 µM) in Jurkat cells.

thapsigargin (10 µM) pretreatment abolished Co-i-cIDPRE (120 µM)-induced Ca2+ increases in the absence of extracellular Ca2+.


Figure 4 ‘Late’ Hsp27 phosphorylation induced by apigenin is modulated by p38-MAPK and PKCd. Lysates from THP-1 cells treated with 50 μM apigenin for 6 h and diluent or following 1 h pretreatment with 10 μM SB203580, 15 μM rottlerin, or both. Treatments marked with (-) denote addition of diluent. (a) Immunoblots with anti-phospho-Hsp27-pS78 and anti-total-Hsp27 antibodies. (b) Immunoblots with anti-phospho-Hsp27-pS82 and anti-total-Hsp27 antibodies. (c) Immunoblots with antiphospho-Hsp27-pS15 and anti-total-Hsp27 antibodies. Densitometry data normalized by the loading control are represented as mean±S.E.M. (N ¼ 5, *Pp0.05 and **Pp0.001, NS denotes non-statistical significance)

Next, we investigated the role of p38 and PKCσ on the ‘late’ Hsp27 phosphorylation using pharmacological inhibitors. THP-1 cells were pretreated with the p38 inhibitor SB203580, or the PKCσ inhibitor rottlerin, or both inhibitors, or with diluent for 1 h before the addition of 50 μM apigenin for 6 h. We found that apigenin-induced phosphorylation of S78 was significantly stimulated in the presence of the p38 inhibitor SB203580 (Figure 4a, lane 3 versus 2, **P<0.001), reaching levels similar to that in control cells (Figure 4a, lane 3 versus 1). In contrast, the PKCσ inhibitor rottlerin had no effect on the phosphorylation of S78 (Figure 4a, lane 4 versus 2, NS ¼ nonstatistically significant). Addition of both SB203580 and rottlerin showed decreased S78 phosphorylation to levels similarly observed in the presence of the p38 inhibitor alone (Figure 4a, lane 5 versus 3). However, we found no additive or synergistic effects when cells were treated with both inhibitors simultaneously (Figure 4a, lane 5 versus 2, **P<0.001). The phosphorylation of S82 induced by apigenin was significantly inhibited by pretreatment with the p38 inhibitor SB203580 (Figure 4b, lane 3 versus 2, *P<0.05). In contrast to the lack of effect observed on S78, the PKCσ inhibitor rottlerin, significantly inhibited apigenin-induced phosphorylationof S82 (Figure 4b, lane 4 versus 2, *P<0.05). Similar to S82 phosphorylation, we observed that the pretreatment with the p38 inhibitor SB203580 inhibited apigenin-induced phosphorylation of S15 (Figure 4c, lane 3 versus 2, *P<0.05). In addition, rottlerin decreased apigenin-induced phosphorylation of S15 (Figure 4c, lane 4 versus 2, *P<0.05). The addition of both inhibitors, however, showed no additive or synergistic effects (Figure 4c, lanes 5, 4 versus 2, **P<0.001).

We found that apigenin-induced phosphorylation of S78 was significantly inhibited in the presence of the p38 inhibitor SB203580 (Figure 4a, lane 3 versus 2, **P<0.001)


Figure 3. Expression of histone mRNAs in mouse fibroblast cells and mouse liver. (A) Schematic of generalized S1 nuclease protection assay performed on mouse histone mRNA. A generalized histone mRNA is depicted indicating possible 5’ splice sites (5’ss), stem-loop cleavage sites (S-L cleavage) or poly(A) cleavage sites. S1 nuclease protection probes will protect a given mRNA to the point that cleavage or splicing occurs (indicated below). Note that due to the high degree of conservation in mice, all of the mRNAs for a specific histone class (i.e. H2B.1 or H2A.2) will be protected up to the stop codon. (B–F) Total cell RNA from NIH3T3 cells and mouse liver was fractionated into polyA+ and polyA− fractions. Total RNA (whole cell (WC)) and poly(A)+ and poly(A−) RNA were probed in an S1 nuclease protection assay. Five micrograms of total 3T3 cell RNA and 50 μg of liver RNA was analyzed using the S1 nuclease protection assay of a 32P labeled fragment at the indicated restriction enzyme site for (B) Hist2H2aa1, (C) Hist1H2bc, (D) Hist1H2ac, (E) Hist2H3c or (F) Hist2H4H. The probe used for histone H4H was labeled at the 5’ end of the indicated restriction site. For each experiment, below the autoradiogram, possible mRNA isoforms are indicated as well as protected fragments and sizes for S1 nuclease probes.

Validation of polyadenylated histone mRNA expression in adult mouse liver. To confirm the expression of the mouse histone mRNAs detected by high-throughput sequencing, we analysed histone gene expression in actively growing cultured fibroblasts (NIH3T3 cells) and liver tissue from 72-week-old mice. The liver is a relatively homogenous tissue with hepatocytes making up more than 70% of the cells. In healthy adult livers, the vast majority of these hepatocytes are quiescent, only re-entering the cell cycle after injury. Unlike the human histone genes, the coding regions of the mouse histone genes are highly conserved (>95%) at the nucleotide level (37). Because of the conserved ORF sequences, we can use an S1 nuclease mapping assay to simultaneously analyse both the mRNA expressed from a specific gene, as well as the mRNAs from all the other histone genes encoding that histone protein (26,42). A probe labelled in the coding region will protect all the histone mRNAs to a region close to the stop codon or initiation codon, as well as a band from the specific gene extending to the 3' end or the 5' end of the transcript, depending on whether one is probing the 3' or the 5' end of the mRNA (Figure 3A). This highly sensitive method allows for mapping of multiple isoforms of mRNA from a single sample. Further, since all of the radioactivity is at the end of the probe, the relative intensity of the bands gives the relative amounts of the transcripts. A generalized schematic is shown in Figure 3A. In each experiment below, the different protected fragments for a given probe are diagrammed below the autoradiogram. Total RNA from NIH3T3 cells and mouse liver was fractionated into polyA− and polyA+ RNA using oligo-d(T) cellulose. Orthologues of human histone HIST1H2BC (Hist1H2bc), HIST2H2AA3 (Hist2H2aa1) and HIST1H4H (Hist1H4h), which were expressed in human tissues, and the HIST2H3C (Hist2H3c) gene, adjacent to the Hist2H2AA3 gene, which was not expressed in human tissues, were analysed by S1 nuclease mapping, using 5 µg of total RNA from exponentially growing NIH3T3 cells and 50 µg of total liver RNA (Figure 3). In actively proliferating NIH3T3 cells, most of the 3' S1 probes map three protected fragments: one extending to the 3' end of the mRNA ending in the stem-loop and a second fragment, mapping near the stop codon, due to the high level of conservation between the open reading frames of all mouse histone genes of a given class (26). This band is indicated by the name of that class of histone protein (e.g. H3.1 or H2a.1). If the histone mRNA is spliced or polyadenylated then the probe is protected up to the point where the mRNA sequence diverges from the probe (Figure 3A; e.g. at the 5' splice site in Hist1H2bc, before the 3' end of the mRNA or at the polyA addition site in Hist2H2aa1). The S1 nuclease protection assays confirmed the low levels of histone mRNAs in liver and there were easily detectable amounts of the polyadenylated forms of Hist2H2aa1 (Figure 3B, lane 7) and Hist1H2bc (Figure 3C, lane 7) mRNAs. There were no polyadenylated mRNAs detected in the NIH3T3 cells. There is some non-polyadenylated histone mRNA detected in the liver that gives the same pattern of S1 nuclease protected fragments as the NIH3T3 cell mRNA. This likely arises from a low level of expression of the histone mRNAs expressed in growing cells. Note that the non-polyA mRNA expressed in mouse liver is greatly reduced compared to NIH3T3 cells, and we used 10 times more RNA (50 µg versus 5 µg) for assay of liver RNA, compared to neonatal mice or growing 3T3 cells. We assayed the same RNAs with probes for Hist1H2ac (Figure 3D), Hist2H3c (Figure 3F) and Hist1H4h (Figure 3E) genes. There was no polyadenylated mRNAs detected from these genes in mouse, consistent with the sequencing data.

most of the 3' S1 probes map two protected fragments: one extending to the 3' end of the mRNA ending in the stem-loop and a second fragment


Production of Th2- and Th1-type cytokines from wild-type and Runt-transgenic CD4⁺ T cells. (A) Naive CD4⁺ T cells were isolated from the spleens of wild-type and Runt–transgenic mice and stimulated with anti-CD3/anti-CD28 antibodies, and the culture supernatants were collected at the indicated times after stimulation. (B) The TCR-stimulated cells were cultured in the presence of IL-2 for 5 d, washed with fresh media, and restimulated via TCR. The culture supernatants were collected after 24 h. (C) The cells were cultured for four days in the Th2- or Th1-inducing condition. The cells were washed with fresh media and restimulated via TCR. The culture supernatants were collected after 24 h. (D) Same as C, but note the difference of scale used in C and here. The amounts of cytokines secreted into the supernatants were measured by ELISA and their averages and standard deviations are shown. Data are representative of four independent experiments.

Respectively, compared with the wild-type cells. A similar result as that shown in Figure 1A was obtained when the TCR-stimulated cells were incubated in the presence of IL-2 for 5 d, washed with fresh media, and restimulated via TCR (Figure 1B). Under this neutral culture condition where neither IL-4 nor IL-12 was added to media, the Runt-transgenic cells secreted several fold more amount of Th2-type cytokines and less amount of Th1-type cytokines than the wild-type cells. We next examined the cytokine production from the Runt-transgenic cells under culture conditions that favor either Th1 or Th2 differentiation. CD4⁺ T cells were stimulated with anti-CD3/anti-CD28 antibodies and incubated in the presence of either IL-4 and an anti-IFN-γ antibody (Th2 condition) or IL-12 and an anti-IL-4 antibody (Th1 condition) for 4 d. Cells were washed with fresh media and restimulated via TCR, and cytokine secretion was measured (Figure 1C). In the Th2 condition, the Runt-transgenic cells produced three times as much IL-4 as the wild-type cells. In contrast, in the Th1 condition, although IFN-γ production from the Runt-transgenic cells was reduced compared with the wild-type cells, IL-4 production from the Runt-transgenic cells did not reach the level of 10 to 100 ng/ml concentration. Thus, the Runt-expressing cells effectively differentiate into the Th2 lineage in a Th2- but not a Th1-favorable environment. It must be pointed here that, even in the Th1 condition, the Runt-transgenic cells actually produced 10 times as much IL-4 as the wild-type cells (Figure 1D). The absolute amount of IL-4 secreted from the Runt-transgenic cells was, however, 5 ng/ml in the Th1 condition (Figure 1D) instead of 120 ng/ml in the Th2 condition (Figure 1C). Therefore, the Runt-transgenic cells, though showing a Th2 tendency to some degree, could not have differentiated effectively into the Th2 lineage under the Th1 condition. Overexpression of Runx1 Prevents Naive Cells from Differentiating Into the Th2 Lineage. If reducing the effect of Runx1 with the Runt transgene induces Th2 differentiation, as shown in Figure 1, we wondered whether the artificial overexpression of Runx1 protein in naive T cells would cause a decrease in Th2 differentiation.

In the Th2 condition, the Runt-transgenic cells produced eight times as much IL-4 as the wild-type cells

even in the Th1 condition, the Runt-transgenic cells actually produced 25 times as much IL-4 as the wild-type cells (Figure 1D)


Figure 5. Reporter assay tests for the repression of NL4-3 by miR-223 and miR-29. For all transfections, the values represent the average of at least three independent experiments and the error bar represents the standard deviation. (a) Reporter assays show miR-223/29 repression is very weak when Nef serves as the 30 -UTR. (b) Reporter assays show miR-223/29 repression of Nef when it serves as a coding region. (c) Reporter assays  to measure the miR-223/29 repression using the 39 nt target sequence. Co-transfection of the reporter and miRNA genes in HEK-293 cells show  strong repression by miR-223 and strong repression by miR-29. Mutated seed binding site for miR-223 or miR-29 abrogated the repressions mediated by either miRNA. (d) Reporter assays to measure the miR-223/29 repression using a 56 nt target sequence. Co-transfection of the reporter and miRNA expression constructs in HEK-293 cells show strong repression mediated by miR-223 and reduced repression mediated by the miR-29 miRNAs.

Co-transfection of the reporter and miRNA genes in HEK-293 cells show  weak repression by miR-223 and strong repression by miR-29

Co-transfection of the reporter and miRNA expression constructs in HEK-293 cells show weak repression mediated by miR-223 and reduced repression mediated by the miR-29 miRNAs


Figure 9. Activity and selectivity of ASOs in the rodent CNS. (A) Allele selective knockdown of muHTT protein with ASO A30 in neuronal cells derived from cortical and striatal tissues of Hu97/18 mouse embryos under free-uptake conditions. (B–D) Hu97/18 mice (n = 4/group) were injected ICV with a single dose of 300 µg of ASO (B and D) or the indicated dose (C) in PBS. Mice were sacrificed after 28 days, the brain was harvested, and a 2 mm coronal slab from each hemisphere (R, L) was analyzed by allelic separation immunoblotting for muHTT and wtHTT protein, and the results were normalized to calnexin protein. (B) Optimized ASOs A25, A26, A30, and A31 show similar activity but worsened allele selectivity relative to control ASO A1. (C) Dose response for allele-selective knockdown of muHTT protein following ICV injection of ASO A30 in Hu97/18 mice. (D) Immunohistochemical staining for ASO (red) illustrates distribution to all parts of the brain following a single ICV bolus injection.

Improved allele selectivity in cell culture translates to brains of transgenic mice. We evaluated selected ASOs in Hu97/18 mice (45), a completely humanized mouse model of HD (Figure 9). This mouse model contains both the mutant human HTT allele, with the associated SNPs, and the wt human HTT allele. We first evaluated the ability of ASO A30 to reduce muHTT protein in primary neuronal cells derived from Hu97/18 mouse embryos in the absence of any transfection agent to facilitate delivery of the ASO across the cell membrane (Figure 9A). The ASO reduced muHTT expression in a dose-dependent manner (IC50 = 101 nM). No reduction of wtHTT was observed even at the highest dose of ASO A30 (1000 nM) tested. Next, mice (n = 4/group) were injected in the right lateral ventricle (ICV) with a single bolus injection (300 µg) of ASO (A1, A25, A26, A30, or A31) or vehicle control (PBS), and tissue was collected 28 days later. Brains were harvested, and HTT protein was quantified in a 2 mm coronal slab from each hemisphere by allelic separation immunoblotting for mu and wtHTT protein; the results were normalized to calnexin (Figure 9B). The posterior portions of treated brains were then post-fixed for immunohistochemical assessment of ASO distribution.As observed in the cell culture experiment, all the ASOs showed 60–80% reduction of muHTT protein. However, although ASO A1 showed a 52% reduction of the wtHTT protein, we observed essentially no reduction of the wtHTT protein for the mice treated with the allele-selective ASOs A25, A26, A30, and A31. We also measured the ability of ASO A30 to reduce muHTT protein in a dose-response experiment (Figure 9C). Mice (n = 4/group) were injected (ICV bolus) with increasing doses (75, 150, 300, and 500 µg) of ASO A30 or vehicle control, and brain tissue was harvested after 28 days using the procedures described earlier in the text. The ASOs produced a dose-dependent reduction in muHTT (ED50 = 110 µg) with no reduction in wtHTT even at the highest dose tested (500 µg). All ASOs also showed similar broad and even bilateral localization after ICV bolus injection, indicating that the modifications had no effect on distribution (Figure 9D). Thus, the animal model recapitulated the potency and selectivity observations from the cell culture experiments. Collectively, these studies illustrate the potency, selectivity, and tolerability of these compounds and support their development as potential therapeutics for HD.

and A31 show similar activity but improved allele selectivity relative to control ASO A1.


Figure 4. Reversion of Splicing Abnormalities in DM1 Patient-Derived Muscle Cells by CRISPR-SaCas9 Deletion of Expanded CTG Repeats Splicing profiles and quantification of LDB3 exon 11-, ATP2A1 exon 22-, MBNL1 exon 7-, DMD exon 78-, INSR exon 11-, and BIN1 exon 11-containing transcripts in differentiated myoblasts from DM1-Delta clones 10, 3, 17, and 22 compared to control (Ctrl), DM1, and DM1-sgRNA clones. Graphs show average values from independent biological replicates ± SD (n = 6 for Ctrl and DM1, n = 3 for the other samples). Statistical analysis by two-tailed Student’s t test. *p < 0.05, **p < 0.01, ***p < 0.001; ns, not significant; ˂DL, below detection limit. Error bars represent SD.

Aggravation of Alternative Splicing Defects in DM1-Edited Muscle Cells Sequestration of MBNL-splicing factors in nuclear foci of DM1 cells leads to alterations in the alternative splicing of numerous pre-mRNAs, some of which are eliminated in differentiated muscle cells in culture.45 We therefore assessed the splicing pattern of LIM domain binding 3 (LDB3) exon 11, Sarco-endoplasmic reticulum calcium ATPase 1 (ATP2A1) exon 22, Muscleblind-like splicing regulator 1 (MBNL1) exon 7, Duchenne muscular dystrophy (DMD) exon 78, insulin receptor (INSR) exon 11, and Bridging integrator 1 (BIN1) exon 11 in edited DM1-Delta clones compared to DM1, DM1-sgRNA, and Ctrl cells (Figure 4).

Correction of Alternative Splicing Defects in DM1-Edited Muscle Cells Sequestration of MBNL-splicing factors in nuclear foci of DM1 cells leads to alterations in the alternative splicing of numerous pre-mRNAs

some of which are reproduced in differentiated muscle cells in culture


Figure 2. Overexpression of Ahi-1 in Sca-1 +lin _x0004_ mouse stem/progenitor BM cells perturbs their in vitro proliferative activity and enhances the effects of BCR-ABL. (A) The levels of Ahi-1 transcripts relative to GAPDH from FACS-purified MIY (Sca-1 + lin _x0004_ YFP +), Ahi-1 (Sca-1 + lin _x0004_ YFP +), BCR-ABL (Sca-1 + lin _x0004_ GFP +), and Ahi-1 plus BCR-ABL (Sca-1 + lin _x0004_ YFP + GFP +) transduced primary mouse BM cells. (B) Growth of each FACS-purified population with GFs. Viable cell numbers were determined by hematocytometer counts of trypan blue – excluding cells. (C) Number of CFC colonies produced in semisolid cultures ± GF from the same FACS-purified mouse BM cells. (D) The appearance of GF-independent CFC colonies is shown. Bar, 250 μm. (E) The numbers of LTC-IC-derived CFCs produced from the same cells ± GF. Values shown are the mean ± SEM of triplicate measurements. * indicates significantly different from MIY control cells.

Elevated endogenous Ahi-1 expression was also observed in cells transduced with BCR-ABL alone as compared with control cells (8-fold; P < 0.01; Fig. 2 A). 5 d after transduction, the rate of expansion of the Sca-1 +lin _x0004_YFP + (Ahi-1 +) cells in liquid cultures was approximately twofold lower than in cultures initiated with control cells (Fig. 2 B). Ahi-1– transduced Sca-1 +lin _x0004_ cells produced a slightly fewer number of colony-forming cells (CFCs) than MIY-transduced control cells in semisolid cultures in the presence of growth factors (GFs), and some of the Ahi-1 + CFCs (15%) were already GF independent (Fig. 2, C and D). After 4 wk in long-term culture-initiating cell (LTC-IC) assays, which are used to measure stem cell activities in vitro, the Sca-1 +lin _x0004_Ahi-1 + cells produced 3-fold more CFCs than control cells (P < 0.01; Fig. 2 E). All of these endpoints (proliferative activity, GF dependence, and CFC output in LTC-IC assays) are also perturbed by BCR-ABL transduction. In cells cotransduced with Ahi-1 and BCR-ABL, all of these effects were further enhanced compared with cells transduced with either BCR-ABL alone (2–4-fold) or Ahi-1 alone (3–6-fold; P < 0.01; Fig. 2). Thus, overexpression of Ahi-1 alone deregulates proliferative control of primitive mouse hematopoietic cells, and these effects can be enhanced by BCR-ABL.

the rate of expansion of the Sca-1 +lin _x0004_YFP + (Ahi-1 +) cells in liquid cultures was approximately twofold higher than in cultures initiated with control cells (Fig. 2 B)

Ahi-1– transduced Sca-1 +lin _x0004_ cells produced a slightly greater number of colony-forming cells (CFCs) than MIY-transduced control cells in semisolid cultures in the presence of growth factors (GFs)


ECM softness upregulates MMP secretion and promotes MMP activity. (A) Primary human fibroblasts (2 × 104 cells per well) were seeded onto gels of varying stiffness in 12-well plates and cultured for 48 h. Cell culture medium from each condition was collected and subject to the RayBio Human MMP Array to determine the total secreted MMP protein quantity in each medium. (B) Three independent experiments (n = 3, ±SD) as in A were performed and quantified. Note that proliferation rates vary on gels of different stiffness. Total MMP quantities were normalized to total cell numbers on gels of varying stiffness at 48 h. Student’s test was used for the comparison of each mean with the mean of MMP protein quantity of the same MMP type on 25.6-kPa gels. *p < 0.05 considered significant. (C) Cell culture conditioned media were collected as in A, and the total MMP activity in each medium was measured and quantified (n = 3, ±SD) and normalized to cell number. Student’s t test was used for the comparison of each mean with the mean of “0.4 kPa.” *p < 0.05 considered significant.

Matrix metalloproteinases (MMPs) are critical proteinases in ECM degradation and include two major subfamilies of secreted MMPs (MMP-2, -3, etc.) and integral membrane MMPs (MMP-14 [MT1-MMP], -15, etc.; Kessenbrock et al., 2010). For all types of MMPs that were measured, increased ECM stiffness significantly inhibited MMP secretion from these cells (Figure 2A). Previous studies reported that increased ECM stiffness significantly promotes primary cell proliferation (Wang et al., 2000; Liu et al., 2010). Thus, by normalizing to total cell numbers at 48 h after cell seeding, the relative amount of MMPs secreted per cell were even lower on stiffer substrates (Figure 2B). Further, the total MMP activities of these secreted MMPs also were higher on softer substrates and lower on stiffer substrates (Figure 2C). Of interest, we also detected small differences of MMP secretion on substrates with varying stiffness as early as 4 h after cell seeding (Supplemental Figure S1B), suggesting that cells begin responding to stiffness during their initial adhesion to ECM.

Student’s t test was used for the comparison of each mean with the mean of “0.1 kPa.” *p < 0.05 considered significant

Student’s test was used for the comparison of each mean with the mean of MMP protein quantity of the same MMP type on 0.2-kPa gels.


Figure 4. Quantitative analysis of CTCF and BORIS expression in human PCa. (A) Nuclear CTCF significantly decreases in metastases cores (P < .001). (B) BORIS nuclear expression significantly increased in cancer cores (P = .002); nuclear and cytoplasmic expression increased in HGPIN cores compared to benign (both P < .001). (C) The ratio of BORIS to CTCF expression was analyzed for differences among cores. Significant increases in the BORIS/CTCF ratio are seen among cancer and metastases cores compared to benign (P = .031 and P = .006 respectively). (D) Comparing the BORIS/CTCF ratio among cancer cores, high Gleason grade cancers have significantly lower BORIS/CTCF ratio than both benign and intermediate Gleason cores (P = .006 and P = .024 respectively).

CTCF is known to impact gene regulation through the management of chromatin organization and the maintenance of epigenetic marks [26]. CTCF expression levels measured by VECTRA were insignificantly decreased in metastatic PCa tumors (P < .001), but not localized PCa when compared to benign prostate tissues (P = .17) (Figure 4A). When CTCF expression within primary tumors was compared against clinicopathologic patient variables, decreased nuclear and total CTCF expression was associated with higher Gleason’s Score (P = .01 and P = .001 respectively) and positive margins (P = .03 and P = .043 respectively) (Data not shown). The CTCF paralogue, BORIS, shares a common zinc-finger DNA-binding domain with divergent N- and C- termini. BORIS and CTCF have competing effects on gene expression and epigenetic regulation [5,27]. In contrast to CTCF, BORIS expression was increased in HGPIN and primary cancer cores compared to benign (P < .001 and P = .002 respectively) (Figure 4B). No clinicopathologic correlates were noted. The competing role for BORIS/CTCF suggests the ratio of their expression may contain functional significance and greater predictive power than the expression of these proteins individually as seen in ovarian cancer [28]. Analyzing all prostate tissues, a weak correlation was seen between BORIS and CTCF (Pearson’s r = .224, P < .001). BORIS/CTCF levels increased significantly in cancer and metastases compared to benign (P = .03 and P = .006 respectively) (Figure 4C). High Gleason cancers have a significantly greater BORIS/CTCF ratio than both benign tissues and intermediate Gleason cancers (P = .006 and P = .024 respectively) (Figure 4D). The ratio of nuclear and total expression was calculated and found to be associated with Gleason’s grade, positive surgical margins, and tumor volume (nuclear P = .024, P = .027, P = .020, respectively) (Table 2, for full table see supplementary data, Table S2).

CTCF expression levels measured by VECTRA were significantly decreased in metastatic PCa tumors (P < .001)

high Gleason grade cancers have significantly higher BORIS/CTCF ratio than both benign and intermediate Gleason cores (P = .006 and P = .024 respectively)


Effects of TRAF3 deficiency on effector functions of CD40 and LMP1. (A) A20.2J cells stably transfected with hCD40LMP1 were stimulated with 2 µg/ml anti-mCD40 Ab (CD40), anti-hCD40 Ab to trigger signaling through hCD40LMP1 (LMP1), or isotype control Abs for each (iso1 and iso2) for 48 h. Expression of CD23, CD80, and CD95 was determined by immunofluorescence staining and analyzed by flow cytometry. MCF, mean channel fluorescence. Values presented are the mean ± SEM of three independent experiments. (B) CH12.LX cells stably transfected with hCD40LMP1 were stimulated with Abs as in A for 72 h and assayed for IgM secretion. Plaque-forming cells (Pfcs, IgM-secreting cells) per 10⁶ viable recovered cells are shown. Values presented are the mean ± SE of replicate samples. Data are representative of three independent experiments. (C) TRAF3⁻/⁻ CH12.LX cells stably transfected with hCD40LMP1 were stably supertransfected with an IPTG-inducible TRAF3 (Reconstituted TRAF3⁻/⁻). Reconstituted cells were preincubated in the absence (−IPTG) or presence of IPTG (+IPTG) for 24 h and stimulated with Abs as in B in the absence or presence of IPTG, whereas TRAF3⁻/⁻ cells were stimulated with Abs as in B in the absence of IPTG. IgM-secreting cells were enumerated as in B. Values presented are the mean ± SE of replicate samples. Data are representative of three independent experiments. (D) Expression of TRAF3 in the reconstituted TRAF3⁻/⁻ CH12.LX cells (Recon.) in the absence (−) or presence of IPTG (+IPTG), compared with that of WT (+/+) and TRAF3⁻/⁻ (−/−) cells, was analyzed by immunoblotting. An immunoblot for actin served as loading control.

Effects of TRAF3 Deficiency on Effector Functions. Next, we determined if the effects of TRAF3 deficiency on early signaling pathways of CD40 and LMP1 are predictive of downstream B cell effector functions, including upregulation of surface molecules and secretion of cytokines and antibodies. After CD40 engagement, TRAF3-deficient A20.2J cells exhibited upregulation of CD23 and CD95 similar to that of WT cells (summarized in Figure 3A; representative histograms shown in Figure S7, available at http://www.jem.org/cgi/content/full/jem.20031255/DC1). Although we consistently observed a partial increase in CD40-mediated upregulation of CD80 in TRAF3⁻/⁻ B cells (Figure 3A), it may be due to clonal variation because different A20.2J subclones vary in this response (not depicted). Using the mCD40-elicited response as an internal control for each subclone, we found that LMP1-induced upregulation of CD23 and CD80 was reduced approximately two- and threefold, respectively, whereas upregulation of CD95 and MHC class II was not affected by TRAF3 deficiency in A20.2J cells (Figure 3A and Figure S7).For detection of cytokine secretion, the membrane ligands for hCD40 and mCD40 (hCD154, mCD154, respectively) were also used, as they are more potent activators of this specific function of CD40. Although mCD154 is capable of activating hCD40 to a certain extent (39), cross-reaction between hCD154 and mCD40 is negligible (21). Neither CD40- nor LMP1-mediated secretion of TNF and IL-6 was affected by TRAF3 deficiency in CH12.LX cells (Figure S8, available at http://www.jem.org/cgi/content/full/jem.20031255/DC1). Interestingly, TRAF3⁻/⁻ CH12.LX cells exhibited enhanced IgM secretion after CD40 engagement, but profoundly suppressed IgM secretion in response to LMP1 signaling as compared with TRAF3⁺/⁺ cells (Figure 3B). We further verified this observation by examining TRAF3⁻/⁻ CH12.LX cells reconstituted with an IPTG-inducible TRAF3. Induction of TRAF3 expression with IPTG completely restored IgM secretion in response to LMP1 signaling, while decreasing IgM secretion mediated by CD40 signaling (Figure 3C and D). These results extend our previous finding that overexpression of TRAF3 decreases CD40-mediated IgM secretion (29), and in contrast, highlight the importance and indispensability of TRAF3 in LMP1-induced B cell activation. Furthermore, we also stably transfected an IPTG-inducible full-length LMP1 into WT and TRAF3⁻/⁻ B cells. A similar requirement for TRAF3 was observed when the signal was delivered by inducible full-length LMP1 (unpublished data).

Although we consistently observed a partial decrease in CD40-mediated upregulation of CD80 in TRAF3⁻/⁻ B cells (Figure 3A)


Figure 4 The effects of hydrogels on skin wound healing in type 2 diabetes mellitus (T2D) by topical treatment. (A) Representative images of wounds in the normal control (NC) group, T2D group, CAH (T2D+CAH) group, and CAVBPH (T2D+CAVBPH) group on days 0, 3, 9, and 15. (B) Wound healing rate. *p < 0.05, **p < 0.01, and ***p < 0.001.

As shown in Figure 4A, the wound size in all groups decreased gradually over time. Compared with the NC group, the T2D group displayed a slower wound shrinkage due to the influence of diabetes, and exudate was still found on the wound surface on day 9. Topical application of CAH and CAVBPH significantly accelerated diabetic wound recovery compared to the T2D group. Quantitative analysis of wound healing confirmed the above results (Figure 4B). The healing rate in the T2D group was more optimistic than that in the NC group (p < 0.01 or p < 0.001). Compared to the T2D group, the CAH group showed a better healing effect on days 9 and 15 (p < 0.001), while the CAVBPH group had the best wound shrinkage than the T2D and CAH groups on all observed days (p < 0.01 or p < 0.001). At day 15, the wounds of the CAVBPH group (96.55% of healing rate) and the NC group (91.77% of healing rate) were basically healed and covered with hair, while the healing rates of the CAH and T2D groups were 84.23% and 63.81%, respectively. Compared to the T2D and CAH groups, the CAVBPH group had the best curative effect, with a 96.55% wound healing rate on day 15 (Figure 4).

The healing rate in the T2D group was less optimistic than that in the NC group (p < 0.01 or p < 0.001)


Figure 1. Telomeric element HeT-A expression is downregulated in ovaries by Trf2, Woc and Ars2. (A) RT-qPCR analysis of TE expression in ovaries of Trf2KDnos, wocKDnos and Ars2KDnos. (B) HeT-A transcript abundance in ovaries of Trf2/Trf2, spnE/spnE and Trf2,spnE double mutants. The fold change in the HeT-A RNA level is shown. (C) NRO analysis of HeT-A transcription in ovaries of Trf2KDnos, wocKDnos, Ars2KDnos and piwiKDnos flies. The RNA level was normalized to rp49. Mean values (±SD) for three biological samples normalized to control knockdown (white(w)KDnos) are shown. (D) In situ RNA hybridization of HeT-A, TART or TAHRE antisense probes with ovaries of the indicated genotypes (GAL4-nos driver was used). (E) RNA FISH of HeT-A antisense probe with ovaries of the indicated genotypes. The accumulation of HeT-A transcripts (green) in nuclei of nurse cells was observed. DNA was stained with DAPI (blue). GAL4-nos driver was used.

RESULTS Trancription factors Woc and Trf2 suppress telomeric repeat HeT-A transcription in ovaries In order to detect germline components contributing to telomeric homeostasis, we performed a selective RNAi screen for factors that downregulate HeT-A expression in Drosophila ovaries. This approach was based on the existing data that in somatic tissues certain factors of the telomeric complex are required for the silencing of telomeric repeats (34–36). As reported earlier, HP1, encoded by Su(var)205 gene, a component of the telomere protection complex (37,38), elicits transcriptional repression of telomeric retrotransposons both in soma (34) and in the germline (39,40). At the same time, transcription of telomeric and non-telomeric transposons in the germline is controlled by the piRNA system, supporting the idea that the telomeric complex in the germline consists of both germline-specific and ubiquitous components. To investigate the structure of telomeric chromatin in the germline, we examined HeT-A expression in the ovaries of flies depleted for known components of the somatic telomeric complex as well as factors involved in RNA surveillance. Here, we describe genes exerting the greatest effect on telomeric repeat expression in ovaries. Germline knockdown of several genes, previously implicated in telomere functioning in soma, did not noticeably affect HeT-A expression in our screen and were not included in further analysis (Supplementary Table S2). In parallel to an independent study that describes Trf2 as a negative regulator of telomeric transposon expression in somatic tissues (41), we demonstrated that Trf2 is associated with the polytene chromosome telomeres of salivary glands (Supplementary Figure S1) and discovered a role of Trf2 in telomere functioning in the germline. RT-qPCR analysis of telomeric and non-telomeric retrotransposon expression demonstrated decreased levels of HeT-A and TAHRE transcripts in ovaries upon germline knockdown of Trf2 (Trf2KDnos; nos designates the promoter of the germline-specific gene nanos that was used to express the Gal4 driver) (Figure 1A). Given that the HeT-A and TAHRE untranslated regions (UTR) are highly homologous (7), we suggest that Trf2 recognizes a similar sequence motif in the promoter regions of both elements. In order to determine if Trf2 functions in the piRNA pathway together with spindle-E (encoding DEAD box RNA helicase SpnE) to silence HeT-A, we applied a double mutant analysis. We used a viable Trf2p1 mutation (26) to generate Trf2/Trf2; spnE/spnE double mutants and compared HeT-A transcript abundance in their ovaries to that in ovaries of single Trf2/Trf2 or spnE/spnE mutants. HeT-A expression in the double mutants was higher than in Trf2 single mutants, but not in spnE single mutants (Figure 1B, Supplementary Figure S2). This could mean that in the absence of piRNAs, inhibitory complex containing Trf2 cannot be recruited to the HeT-A promoter. Northern blotting of short RNA did not reveal changes in the abundance of HeT-A-specific piRNA in ovaries of Trf2 mutants and Trf2KDnos flies (Supplementary Figure S3A). These data suggest that Trf2 may act downstream of piRNA processing to establish transcriptional silencing of HeT-A. The zinc finger transcription factor Woc has been shown to bind Drosophila telomeres, exerting telomere-capping functions (42). wocKDnos causes a strong derepression of HeT-A and TAHRE but not TART and other TEs (Figure 1A), suggesting sequence-specific binding of this transcription factor to telomeric repeats in ovaries. We extended the analysis of the telomeric protein complex by including an RNA binding protein, Ars2, involved in mi- and siRNA biogenesis (43), which was identified in an RNAi screen as a negative regulator of HeT-A expression (44). Particular interest in this protein was due to the fact that Ars2 downregulates the expression of human TERRA (45). RT-qPCR analysis revealed a strong derepression of HeT-A/TAHRE in ovaries of Ars2KDnos flies (Figure 1A). To address the question about the involvement of Trf2, Woc and Ars2 in the transcriptional regulation of HeT-A, we conducted an NRO assay, which allows estimating the level of nascent HeT-A transcripts (46). NRO on ovaries with Trf2, woc and Ars2 knockdowns demonstrates that all these factors provide transcriptional silencing of the telomeric retrotransposon HeT-A (Figure 1C). In situ RNA hybridization analysis was performed to examine the effect of Trf2, Woc and Ars2 depletion on telomeric retroelement transcript distribution in ovaries (Figure 1D, Supplementary Figure S4). Knockdowns of Trf2, Woc and Ars2 exerted the most pronounced effect on HeT-A and TAHRE expression, resulting in the accumulation of their transcripts in nurse cells. The RNA FISH analysis on ovaries depleted for Trf2, Woc and Ars2 revealed HeT-A RNA signals not only in the cytoplasm, but also in the nuclei of nurse cells, where HeT-A transcripts were accumulated in distinct foci (Figure 1E). Similar nuclear foci were observed in spnEKD ovaries (Figure 1E). Previously, using combined DNA/RNA FISH analysis, it was shown that both HeT-A RNA and telomeric DNA were co-localized in nurse cell nuclei in spnE mutants (19). Most likely, we observed the accumulation of nascent transcripts at sites of transcription upon Trf2, Woc and Ars2 knockdown, in accordance with the result of NRO. Taking into account the HeT-A/TAHRE-specific effects of Woc and Trf2, it is unlikely that these factors participate in piRNA biogenesis. However, it is possible that DNA-binding factors Woc and Trf2 are involved in the piRNA-mediated transcriptional silencing mechanism that is specific for telomeric repeats. Thus, HeT-A transcripts accumulated upon Ccr4-Not knockdown avoid piRNA-mediated degradation. In situ RNA hybridization on Ccr4, Pop2 and Not1 KD ovaries revealed HeT-A transcripts in nurse cells (Figure 2C). Importantly, RNA FISH revealed HeT-A RNA foci in the nuclei of twinKDnos nurse cells (Figure 1E) as well as upon Trf2, Woc, Ars2 and SpnE knockdown, suggesting that all these components regulate the telomeric transcript level at the site of transcription. Given the accumulation of HeT-A transcripts in the nuclei upon Ccr4 depletion (Figure 1E), we investigated the poly(A) tail length of the HeT-A RNA in the nuclear fraction of ovarian RNA upon germline knockdown of Ccr4. The PAT assay demonstrated that in the nuclei of control ovaries, HeT-A transcripts were not adenylated, while Ccr4 KD led to an increase in HeT-A poly(A) length in the nucleus (Figure 3C).

RT-qPCR analysis of telomeric and non-telomeric retrotransposon expression demonstrated increased levels of HeT-A and TAHRE transcripts in ovaries upon germline knockdown of Trf2 (Trf2KDnos; nos designates the promoter of the germline-specific gene nanos that was used to express the Gal4 driver) (Figure 1A)


Agrin-mediated decrease in gap junction–dependent intercellular communication between chromaffin cells in neonates. (A) Reduced number of electrically and LY-coupled chromaffin cells in neonatal agrin-treated slices. *, P ≤ 0.01 when compared with control slices. (B) Monitoring of electrical coupling between chromaffin cell pairs in control and agrin-containing saline showing examples of robust and weak coupling. Cells were current-clamped at −65 mV. A weak coupling was less frequently observed in agrin-treated slices. (C) Histograms illustrating the wide distribution range of the coupling ratio calculated in 26 control and 18 agrin-treated cells from voltage-clamp measurements of Ij (holding potential −60 mV, transjunctional potential from −120 to −60 mV, 150 ms duration). Insets: pooled data of Gj calculated in 11 control cell pairs and 4 agrin-treated cell pairs.

Studies were next undertaken to examine the effect of agrin on both gap junction–mediated electrical and metabolic coupling between neonate chromaffin cells. Metabolic coupling was assessed using Lucifer yellow (LY) to label coupled cells, whereas electrical coupling was evidenced by dual whole-cell patch-clamp recording of intercellular macroscopic junctional currents (Ij). The probability of LY spreading between chromaffin cells was significantly reduced in agrin-treated slices compared with untreated slices (31% vs. 57%, P ≤ 0.01; Figure 5A). In the presence of the anti–rat agrin-neutralizing pAb, agrin failed to decrease LY diffusion between neonate chromaffin cells (58.3%, n = 24; unpublished data). Similarly, the dye coupling was not modified by inactive agrin0,0 (61.5%, n = 13; unpublished data). In adults, agrin did not change the incidence of LY diffusion (37.9% in treated slices, n = 29 vs. 44% under control conditions, P > 0.01; unpublished data). Agrin decreased the percentage of electrically coupled cell pairs (53.8%, n = 26 pairs in control slices vs. 22.2%, n = 18 pairs in agrin-treated slices, P ≤ 0.01; Figure 5A). In addition, agrin reduced the incidence of robustly coupled cells (Figure 5B). The voltage changes in response to depolarizing current injected into the stimulated cell were robustly reflected in the unstepped cell in 64.3% (n = 9/14 cell pairs) and 50% (n = 4 cell pairs) in control and agrin-treated slices, respectively (P ≤ 0.01). The resulting coupling ratios exhibited a wide distribution range from 0.01 to 0.97 (Figure 5C), strongly suggesting the presence of two chromaffin cell populations—a weakly coupled cell population and a highly coupled cell population. Recordings of Ij in chromaffin cell pairs voltage clamped at −60 mV confirmed these findings (unpublished data). Delivering voltage steps with command pulses of both polarities triggered Ij in the unstepped cell that exhibited variable degrees of attenuation. In control slices, 81.8% of recorded pairs (n = 11) exhibited Ij amplitudes that could reach 1–2 nA, whereas in the remaining pairs Ij did not exceed several picoamperes. In agrin-treated slices, the percentage of coupled cell pairs exhibiting a high Ij amplitude dropped to 50%. When plotted as a function of the transjunctional potential, the I/V curve of Ij displayed a linear relationship within the membrane potential range of −60 to −120 mV. The curve used to fit the data was derived from a linear regression, giving a macroscopic junctional conductance (Gj) of 43 and 60 pS for the weak coupling and 12 and 13 nS for the robust coupling (Figure 5C, insets).

A robust coupling was less frequently observed in agrin-treated slices.


FIGURE 2. Fold enrichment of selenoprotein mRNAs on UPF1 in low versus high Se.(A) Levels of selenoprotein mRNAs that coprecipitated with UPF1, following culturing HEK293T cells in 3 nM Se or 60 nM Se. Transcript levels are normalized to a synthetic in vitro transcribed RNA and then to the value of the corresponding sample from the total RNA extraction (see Methods; Supplemental Fig. S3).(B) UPF1 protein levels in 3 nM Se or 60 nM Se.(C) Quantitation of (B). Error bars represent standard deviation of the mean; n = 4 for (A), and n = 6 for (B) and (C); (*) P < 0.05.

We reasoned that if the transcripts that decreased in low Se were undergoing NMD, then they should similarly be enriched on UPF1. The same experiment modeling conditions of low Se was repeated, and RNA immunoprecipitation was performed with UPF1. The cytoplasmic nucleoprotein complexes were coimmunoprecipitated with an anti-UPF1 antibody, followed by quantification of coimmunoprecipitated RNAs by qRT-PCR. A representative set of RNAs from each category of NMD susceptibility was analyzed, including those most responsive to Se status (SelW, SelP, GPx1), as well as GPx4, which has been consistently unresponsive to Se status in past research. Interestingly, all of the selenoprotein mRNAs analyzed coimmunoprecipitated with UPF1 to some degree in agreement with UPF1’s general role in translation (Ghosh et al., 2010). A strikingly similar pattern to the profile in Figure 1A was observed in response to Se status. In this case, the RNAs predicted resistant to NMD showed a difference in their abundance on UPF1 with respect to Se. The RNAs that were the most responsive to Se status, however, were also the less abundantly bound to UPF1 under conditions of low Se (Fig. 2A). Importantly, UPF1 did not change with Se, ruling out the possibility that changes in immunoprecipitated RNAs could have been due to changes in total UPF1 protein (Fig. 2B, C). Overall, the degree of mRNA responsiveness to Se status directly correlated with the degree of mRNA abundance on UPF1, suggesting the involvement of NMD in the regulation of selenoprotein mRNAs during Se deficiency.

RNAs predicted resistant to NMD showed no difference in their abundance on UPF1 with respect to Se

were also the most abundantly bound to UPF1 under conditions of low Se (Fig. 2A)


3D fibronectin matrix reduces both Rac activity and random migration. (A) Primary human fibroblasts were plated on 2D substrates coated with fibronectin or 3D matrices rich in fibronectin and assayed for activity as in Figure 1. The reduction of active Rac in cells plated in a 3D matrix compared with 2D was 31% (P ≤ 0.017), whereas Cdc42 and Rho changes were not significant (Cdc42 4.5% reduction, P ≤ 0.66; Rho 25% increase, P ≤ 0.65). Error bars indicate SEM. (B) Cells in 2D versus 3D environments have different morphologies and locations of lamellae (arrowheads), as shown after staining for F-actin with phalloidin-Alexa 594 (left and red color in the right) and anti-fibronectin antibody (green). Bar, 20 μm. (C) Migration of cells in 2D versus 3D environments was recorded, and directionality (D/T) and velocity were calculated. (C and D) Error bars represent SEM. (D) Decreased random motility of cells within three-dimensional (3D) matrix. Primary human fibroblasts were cultured overnight within intact 3D matrices, on mechanically flattened 3D matrix (2D matrix), or on surfaces coated with solubilized 3D matrix (2D mix). Cell movements were recorded for 10 h, and the D/T ratio and velocity were calculated as described above. (E) Activated Rac in cells in 3D matrix restores random motility. Primary human fibroblasts were cotransfected with Rac Q61L VSV and Rac Q61L GFP or GFP alone (Control), sorted for low levels of GFP expression (1–50% from the peak of positive cells), and plated on 3D matrices. Cell movements were recorded for 10 h, and the D/T ratio and velocity were quantified. The bars represent the means of data pooled from two experiments, and error bars indicate SEM (n = 32–34 cells).

Cells migrating in 3D cell-derived matrices have different types of cell adhesions, morphology, and signaling when compared with cells in standard 2D tissue culture (Cukierman et al., 2001; Walpita and Hay, 2002). Human fibroblasts in such 3D matrices were found to have a partial, but highly reproducible, 10–50% reduction in active Rac, but no reduction or increase in Cdc42 or Rho activities (Figure 7A). This reduction in Rac activity was accompanied by decreased random migration (Figure 7C and Video 3), with directional persistence increasing from D/T₂ᴰ = 0.25 ± 0.03 to D/T₃ᴰ = 0.87 ± 0.02 (P < 0.0001). Individual cells in the 3D matrix became spindle shaped as previously described (Cukierman et al., 2001), but in addition, staining for F-actin revealed a substantial reduction in peripheral lamellae in 3D compared with 2D (Figure 7B). In contrast to the results in cells cultured on 2D substrates, there was a significant increase in overall cell migration velocity by 34% associated with the reductions in active Rac and random migration in a 3D environment (Figure 7C; P < 0.0001). These findings further indicate the separate regulation of speed and directionality. Because the differences between 2D fibronectin and 3D substrates could have been the result of either three dimensionality or of differences in molecular composition, the 3D matrix was converted to 2D as a direct test of the role of dimensionality. Physically flattening 3D cell-derived matrices by compression still retained the increased overall velocity, but it was accompanied by a restoration of random motility (Figure 7D; P < 0.0001). Moreover, solubilizing the matrix and spreading its mixed components on a 2D substrate showed the same restoration of random motility (Figure 7D; P < 0.0001), with migration rates similar to those on 3D matrix (no statistically significant difference). These analyses indicate that the increased directionality in 3D is related to the three dimensionality of the matrix, and that it is unrelated to cell migration speed.

30–50% reduction in active Rac, but no reduction or increase in Cdc42 or Rho activities (Figure 7A)

with directional persistence increasing from D/T₂ᴰ = 0.48 ± 0.03 to D/T₃ᴰ = 0.87 ± 0.02 (P < 0.0001)


Fig. 5. Electrophoretic mobility shift assay results for the AZRE. (A) Sequence-specific interaction of nuclear proteins with the AZRE. The 23 bp AZRE containing a fragment between nucleotides –190 and –168 relative to the transcription start site of Oshsp17.3 was radiolabelled, and 1 ng of the probe was incubated with 10 µg of the nuclear proteins prepared from rice etiolated seedlings under AZC treatment for 6 h. The positions of the DNA–protein complexes are shown as C1 and C2 by arrows. The free probe is indicated with an asterisk (*). (B) Effect of CHX on the interaction of nuclear proteins with the AZRE. Three-day-old rice seedlings were treated with CHX (2 µg ml⁻¹) and with (left) or without (right) AZC for 6 h. (C) Cross-competition analysis of the HSE. The 23 bp HSE-containing fragment located at –87 to –65 relative to the transcription start site of Oshsp17.3 was used as a competitor. (D) Stress-dependent interaction of nuclear proteins with the AZRE. Nuclear extracts were prepared from seedlings treated with AZC, As, or HS for 2 h and by 28 °C [control (C)] or Cd for 6 h.

Specificity of nuclear proteins interacting with the 9 bp AZRE in vitro by EMSA. To characterize the putative AZRE further, EMSA was used to determine whether it can interact with trans-acting factor(s) present in nuclear extracts. A 23 bp synthetic oligonucleotide encompassing the AZRE was used as a probe and was labelled with 32P by T4 polynucleotide kinase. Then, the probe was incubated with nuclear extracts from AZC-treated rice seedlings. Two DNA-bound protein bands (C1 and C2) were detected on the gel (Fig. 5A). The intensity of C1 appeared to be stronger than that of C2, and C1 could be further competed out by a 200-fold excess of AZRE probe without a 32P label. In addition, nuclear extracts from seedlings treated with AZC plus CHX for 6 h or CHX alone did not affect the levels of C1 and C2 interacting with the AZRE (Fig. 5B), which suggests that de novo synthesis of proteins is not required for the interaction. Because the 9 bp AZRE is involved in the HSR, it was also tested whether the 9 bp AZRE could be cross-competed by an HSE. This 23 bp HSE probe encompasses a perfect HSE (CTTCTAGAAACTTCC). Interestingly, the C2 but not the C1 band could be competed out by a 200-fold excess of HSE without being 32P labelled (Fig. 5C). Nevertheless, these results show that the AZRE can be specifically recognized by the nuclear proteins from AZC-treated rice seedlings. Because the AZRE was required for the response to HS and AZC, EMSA was used to examine whether nuclear extracts from rice seedlings treated with different inducers can bind to the AZRE. In nuclear extracts from seedlings treated with As (2 h), Cd (6 h), HS (2 h), or AZC (2 h), the two DNA–protein complexes C1 and C2 were also detected in all extracts, including control extracts (Fig. 5D). Additionally, the C1 band in the control was competed out by a 10-fold amount of the AZRE (Fig. 5D, first left lane). The intensity of the C1 complex with AZC treatment was found to be \~5-fold higher than that of the control by measuring the integrated density with Scion image software. However, the intensity of the C2 band in 2 h AZC-treated and control nuclear extracts was lower than that in extracts receiving 6 h AZC, As, Cd, and HS treatments. Nevertheless, the results demonstrate that nuclear proteins from rice seedlings bind to the AZRE in a stress-dependent manner and depend on the duration of AZC treatment. Deletion of the AZRE on the promoter of Oshsp17.3 can reduce OsHsfA4b-modulated activation. According to the indispensable role of the AZRE for HS responsiveness (Fig. 3) and the results of EMSA (Fig. 5C), it was speculated that the AZRE can be specifically recognized by HSFs. Thus, tests were conducted to determine whether the AZRE was necessary for the interaction between OsHsfs and the promoter of Oshsp17.3. According to the expression analysis of 23 rice HSF genes, OsHsfA4b (Os01g54550) and OsHsfB4b (Os07g44690) were found to be induced by AZC treatment (data not shown). Two effector constructs, pHsfA4b and pHsfB4b, under the control of the maize constitutive Ubi1 promoter, were made (Fig. 6A). GUS activity in coleoptiles co-transformed with one reporter (p567 or p567DAZRE) and one effector (pHsfA4b or pHsfB4b) construct at a ratio of 1:1 was compared. As shown in Fig. 6B, when co-transformed with pHsfA4b, p567 achieved 2.8-fold induction in relative GUS activity but p567DAZRE achieved only a 1.8-fold induction. However, co-transformation of pHsfB4b was not significantly induced on p567 or p567DAZRE. To confirm these results further, the p631 reporter construct was also co-bombarded with pHsfA4b or pHsfB4b and no effect on the non-AZC-inducible Oshsp16.9A promoter was found (1.3- and 1.5-fold induction, respectively) (Fig. 6B). Also, transient expression of another highly AZC-inducible HSF gene, OsHsfC1b (Os01g53220), had no effect on the activation of Oshsp17.3 and Oshsp16.9A (data not shown). Thus, HSFs are possibly an integral part of the AZRE-dependent induction pathway of sHSP-CIs. The differential transcription of sHSP genes may have resulted from the action of different kinds of HSFs or additional transcription factors responding to environmental stresses (Rojas et al., 2002). Two DNA–protein complexes (C1 and C2) were observed by EMSA. Both of the interaction complexes can be competed out by cold AZRE, which indicates that the AZRE–protein interactions are sequence specific and may involve two distinct trans-acting proteins (Fig. 5A). Also, nuclear extracts from untreated AZRE (Fig. 5D), and the level of bound proteins was not affected by CHX (Fig. 5B). These data show that de novo protein synthesis was not required for the trans-acting factors recognizing the AZRE, and thus these factors constitutively exist in the cells. However, nuclear extracts prepared from seedlings treated for 6 h with AZC, Cd, As, or HS showed a lower intensity of C1 and C2 than those from control seedlings (Fig. 5D), which suggests that the AZRE may interact with nuclear proteins in a stress-dependent manner. However, whether trans-acting factor(s) directly sense AZC or are only indirectly activated by AZC needs further study. Interestingly, it was also found that the AZRE was indispensable for HS activation of Oshsp17.3 and Oshsp18.0 in the transient expression system (Fig. 3), that the C2 band can be competed out by the HSE (Fig. 5C), and that HS strongly boosted both C1 and C2 signals (Fig. 5D). These data are in agreement with the observation of Sugio et al. (2009), who showed HSFs to be involved in the AZC response in Arabidopsis. Among the HSFs identified in rice, OsHsfA4b, OsHsfB4b, and OsHsfC1b show high AZC responsiveness (data not shown). Co-expression of OsHsfA4b in rice coleoptiles could activate both p567 and p567DAZRE constructs in the absence of AZC (Fig. 6B), but the induction level in p567 was 67% higher than that in p567DAZRE. In contrast,

nuclear extracts prepared from seedlings treated for 6 h with AZC, Cd, As, or HS showed a higher intensity of C1 and C2 than those from control seedlings (Fig. 5D)


Figure 1. SDHB expression is high in CRC cell lines. (A) Quantitative RT-PCR analysis of SDHB mRNA expression in four colorectal cancer (CRC) cell lines compared to the normal colorectal epithelial cell line NCM460. (B) Semi-quantitative RT-PCR further confirms increased SDHB transcript levels in CRC cell lines relative to NCM460. (C) Western blotting analysis shows decreased SDHB protein expression in all four CRC cell lines compared to the normal epithelial control.

SDHB is the key enzymatic component of mitochondrial enzyme SDH constructively expressed across species, which oxidizes succinate to fumarate in the TCA cycle and feeds electrons into the mitochondrial respiratory chain for ATP production. We examined SDHB mRNA and protein levels in four CRC cell lines and normal colorectal epithelial cell line NCM460. As shown in Figure 1 both SDHB mRNA level and protein level were relatively high in all four CRC cell lines (SW480, SW620, SW1116, and HT-29), compared to non-CRC epithelial NCM460 cells.

SDHB expression is low in CRC cell lines.

(B) Semi-quantitative RT-PCR further confirms reduced SDHB transcript levels in CRC cell lines relative to NCM460.

As shown in Figure 1 both SDHB mRNA level and protein level were relatively low in all four CRC cell lines (SW480,


Effects of KBrO3 on mtDNA copy number and topology. (A) Dot-blot of purified mtDNA from control cells and cells treated with 30 μM KBrO3. Oxidative damage is detected using an antibody against 8-oxodG by SouthWestern analysis and normalized against total mtDNA by Southern hybridization on a separate blot. (B) Dot-blot for antibody verification, showing control mtDNA and mtDNA treated in vitro with 7.4% H2O2 for 30 min. (C) Topology gel of mtDNA. KBrO3 treatment had no effect on mtDNA topology. 16.6, 16.6-kb linear molecules; CAT, catenanes; OC, open circles; SC, supercoiled mtDNA. (D) mtDNA copy number levels during the KBrO3 treatment time course. Despite the damage, mtDNA copy number is not unaffected by KBrO3.

Although KBrO3 did not have as dramatic an effect on nuclear DNA damage signaling as UV or H2O2, it induced a marked increase in mtDNA damage (Figure 1A). The damage did not result in copy number depletion or any effect on the supercoiling of mtDNA (Figure 1, C and D).

mtDNA copy number is not affected by KBrO3.


Figure 1. Purification of chicken FANCD2, FANCI, FANCL andhuman UBE2T. (A) Purified chicken FANCD2 and FANCI, used forin vitro assays, were analyzed by 15% SDS-PAGE with CoomassieBrilliant Blue staining. Lane 1 indicates the molecular mass markers.Lanes 2 and 3 indicate purified FANCD2 and FANCD2 K563R,respectively. Lanes 4–9 indicate purified FANCI, FANCI K525R,FANCI R1288Q, FANCI Dx6, FANCI Dx6 K525R and FANCIEx6, respectively. (B) Purified human UBE2T, used for in vitromonoubiquitylation assays, was analyzed by 15% SDS-PAGE withCoomassie Brilliant Blue staining. Lane 1 indicates the molecularmass markers. Lane 2 indicates purified UBE2T. (C) PurifiedGST-tagged chicken FANCL, used for in vitro monoubiquitylationassays, was analyzed by 15% SDS-PAGE with Coomassie BrilliantBlue staining. Lane 1 indicates the molecular mass markers. Lane 2indicates purified GST-tagged FANCL.

Chicken FANCI and FANCD3 were purified as recombinant proteins (Figure 1A, lanes 3 and 4), and the IDcomplex was prepared by mixing them in 1:1 stoichiometry. We also purified UBE2T and FANCL, which areknown as the E2 and E3 proteins for FANCD2monoubiquitylation, respectively, as recombinantproteins (Figure 1B and C).

Chicken FANCI and FANCD2 were purified as recombinant proteins (Figure 1A, lanes 2 and 4)


FIGURE 6. Incorporation of single UV photoproducts increases nucleosome dynamics. A, schematic illustration of the incorporation of a single CPD or 6-4PP into the 601 sequence. The DFs are 12-mer oligonucleotides with the sequences shown. Solid triangles indicate the positions of the photoproduct. The dark circle represents Cy5, and the open circle represents Cy3. B, FRET changes for the single CPD containing NCPs. The 601 sequence was changed according to the DF and denoted 601.DF1. The left panel shows emission spectra for the CPD containing NCPs compared with undamaged NCPs. The right panel shows the FRET efficiency values determined in each case, where the value for 601.DF1 NCPs was set to 1. The values shown are the mean ± S.D. of three independent experiments. C, the same as B except the NCPs contained a single 6-4PP and the sequence denoted 601.DF2. D, relative FRET efficiency of salt dependence of NCPs containing a single CPD. The FRET efficiency at the lowest salt concentration (50 mM) was set to 1. Values are the mean ± S.D. of three independent experiments. E, salt titration profile of NCPs containing a single 6-4PP. Values were plotted the same as in D.

Taining a single CPD or 6-4PP lesion is 4.6 nm and 4.2 nm, respectively. Furthermore, in each case, the FRET efficiency is reduced, indicating that the introduction of a single UV lesion in nucleosome DNA can increase NCP unwrapping. This supports the UV dose-dependent FRET change we observed with UV-irradiated NCP DNA (Figure 3). Moreover, NCPs with either a single CPD or 6-4PP are more sensitive to salt (Figure 6, D and E). In the range of 0–1 M salt concentrations, the FRET efficiency in NCPs with single UV lesions is significantly lower than that of undamaged NCPs, indicating that NCPs containing just one DNA photoproduct are significantly less stable with increasing salt.

In the range of 0.25–1 M salt concentrations


Figure 1. Reduced PtdCho synthesis in CCTα-deficient macrophages. (A) Wild-type (WT; n = 12) or CCTα-deficient (KO; n = 12) macrophages were labeled for 6 h with 1 μCi/ml [3H]choline, and incorporation into PtdCho was normalized to cellular protein. (B) Relative transcript levels for CCTα, CCTβ2, CCTβ3, or PEMT were determined by real-time qRT-PCR in wild-type (n = 3) or CCTα-deficient (n = 3) macrophages. (C) CCT enzyme activity in wild-type (△; n = 4) or CCTα-deficient (●; n = 4) macrophage lysates was determined in vitro as a function of protein concentration. (D) Protein expression levels of CCTα (42 kD) and CCTβ3 (39 kD) were determined in wild-type and CCTα-deficient macrophage lysates (50 μg) by immunoblotting with isoform-specific antibodies. Immunoblots are representative of macrophages from two mice of each genotype. Cells (HEK293T) transfected with expression plasmids encoding CCTα or CCTβ3 were lysed, and 5 μg of protein was loaded as a positive control. Multiple immunopositive bands in a lane correspond to different phosphorylation states of the CCT protein (Jackowski, 1994; Lykidis et al., 1998). Error bars indicate mean ± SE. *, P < 0.05; **, P < 0.01.

Mice with CCTα-null macrophages were generated as described previously (Zhang et al., 2000). Briefly, mice carrying a floxed Pcyt1a gene were crossed with mice expressing Cre recombinase under the macrophage-specific LysM promoter. Two loxP sites flanked a 12.5-kb fragment of the Pcyt1a gene containing exons 5–9 (Karim et al., 2003) and the intervening introns. Deletion of the region between the loxP sites resulted in expression of a truncated CCTα protein lacking the catalytic and regulatory domains at the carboxy terminus. Mice homozygous for the floxed gene and heterozygous for LysMCre were mated, and pups were genotyped to obtain either CCTα knockout or littermate wild-type control macrophages.Peritoneal macrophages were elicited, and the CCTα-deficient macrophage population showed increased rates of de novo phosphatidylcholine (PtdCho) synthesis measured by [?H]choline incorporation into the lipid fraction of adherent cells (Fig. 1 A). The deletion in this macrophage model was not completely penetrant (Zhang et al., 2000). Quantitative RT-PCR (qRT-PCR) analysis revealed that the CCTα transcript level was significantly increased to about 30% of wild-type levels (Fig. 1 B). The CCTα-null cells were ≥95% macrophages as determined by microscopy after staining with macrophage-specific anti–mouse CD11b. Staining for CCTα protein showed that 20–30% of macrophages isolated from knockout mice (n = 4) remained positive for expression, confirming incomplete Cre recombinase activity.Thus, residual PtdCho synthesis detected by metabolic radiolabeling in CCTα-null populations was due not only to expression of the alternate isoform CCTβ3 (Fig. 1 B) but also to the presence of cells that did not delete the CCTα gene. qRT-PCR showed that the CCTβ2 isoform was not expressed in macrophages, while CCTβ3 expression was increased in knockouts. CCTβ3 shares the primary biochemical function of CCTα and can compensate for its loss to support membrane synthesis in cultured cells (Karim et al., 2003). Previous work indicated increased CCTβ2 expression in CCTα-deficient cells (Zhang et al., 2000), but at that time, CCTβ3 had not been discovered; both isoforms share an epitope detected in earlier immunoblots (Karim et al., 2003).Total CCT enzyme activity was significantly higher in lysates from CCTα-null macrophages compared with wild-type populations (Fig. 1 C), consistent with previous studies (Zhang et al., 2000). Immunoblotting with isoform-specific antibodies revealed a decrease in CCTα protein and an increase in CCTβ3 protein reflecting mRNA changes (Fig. 1 D). Macrophages from two knockout and two wild-type mice were pooled by genotype, and immunoblots were prepared from six replicates per genotype. CCTα protein levels in the knockout population were 0.36 ± 0.08 relative to wild-type (set at 1.00). The reduction in CCTα transcript correlated with protein levels and the number of macrophages lacking CCTα expression by microscopy. These data confirm loss of CCTα expression in the majority of cells and provide the first example of adaptive regulation of CCTβ3 expression in response to PtdCho deficiency.

and the CCTα-deficient macrophage population showed reduced rates of de novo phosphatidylcholine (PtdCho) synthesis measured by [?H]choline incorporation into the lipid fraction of adherent cells (Fig.

Quantitative RT-PCR (qRT-PCR) analysis revealed that the CCTα transcript level was significantly reduced to about 30% of wild-type levels (Fig.

Total CCT enzyme activity was significantly lower in lysates from CCTα-null macrophages compared with wild-type populations (Fig.


Figure 2. Differential inhibitory effects of SAUGI on the activities of (A) SAUDG, (B) EBVUDG, (C) HSVUDG, (D) human UDG and (E) TBUDG. Except for TBUDG, addition of SAUGI increased the specific uracil-removing activity of SAUDG and the other three UDGs in a dosage-dependent manner.

The inhibiting effects of SAUGI on five UDGs We next used uracil removal assays to investigate the ability of SAUGI to inhibit the same five UDGs that were used in the surface plasmon resonance experiments. In the absence of SAUGI, all the UDGs removed the uracil from the uracil-containing DNA substrates effectively, and the resulting apyrimidinic site was cleaved by heat and alkali (Figure 2A-E, lane 2). The addition of SAUGI reduced the cleaved products in the SAUDG, EBVUDG, HSVUDG and human UDG reactions (Figure 2A-D, lanes 3–7; Supplemental Figure S4). SAUDG, EBVUDG and HSVUDG activity was initially inhibited when the molar ratio of SAUGI to UDG reached 1:1, but a ratio of 2:1 was needed for the inhibition of human UDG activity. Interestingly, although the structure of TBUDG is conserved relative to the other four UDGs, SAUGI had no significant effect on this UDG’s activity (Figure 2E). These results correspond to those found in the BIAcore study. We therefore conclude that SAUGI has a relatively greater effect on the two viral UDGs than on human UDG. Since HSVUDG and EBVUDG have been shown to play an important role during virus replication (29), these results suggest a potential use of SAUGI as an anti-virus treatment. The inhibitory effects of SAUGI mutants on the uracil-removing activities of human and HSV UDGs In our previous study, we found phage UGI had an extremely high binding affinity to human UDG that was 12–13 times greater than that of SAUGI (16). We found here that phage UGI also inhibited both HSVUDG and human UDG more effectively than SAUGI (compare Supplemental Figure S6 with Figure 2C and D). We speculated that SAUGI’s relatively low binding affinity to human UDG and its high binding affinity to viral UDG might potentially allow it to be used to prevent viral UDG repair activity without having too great an effect on human UDG. In our next experiment, we therefore used structural-based protein engineering to further modify SAUGI’s activity on human UDG and HSVUDG.

addition of SAUGI reduced the specific uracil-removing activity of SAUDG and the other three UDGs in a dosage-dependent manner


Figure 2. HITS-CLIP reveals HIV-1 regions bound by Ago2 in HIV-1 infected cells. (A) HEK293T cells were transfected with plasmid expressing either GFP-Ago2 or control GFP. Twenty-four hours later, they were infected with VSVg-pseudotyped HIV-1 NL4-3 at a M.O.I. of 1 or mock infected. Twenty-four hours later, cells were subjected to UV cross-linking and RNA–protein complexes were subjected to immunoprecipitation using an anti-GFP antibody. IPed RNA was radiolabeled with [α-32P]ATP and samples resolved on SDS-PAGE. Radiolabeled RNA was visualized by autoradiography. RNAs migrating at a higher molecular mass than the protein of interest (GFP-Ago2:RNA, between 125 and 225 kDa) were extracted from the membrane, reverse transcribed into cDNA and subjected to high throughput sequencing. (B) Reads obtained from non-infected (NI) and infected (INF) samples were uploaded to CLIPZ software. Reads that aligned to the human genome were sorted into categories: messenger RNA (mRNA), microRNA (miRNA), ribosomal RNA (rRNA), repeat, small non-coding RNA (snRNA), small nucleolar RNA (snoRNA), transfer RNA (tRNA) and other. Pie charts correspond to the distribution of the mean value of three biological replicates. (C) Reads obtained from infected samples were aligned to the HIV-1 NL4-3 sequence. Only reads ≥50 nucleotides length that aligned once without mismatch were considered for this analysis. Reads obtained from three independent HITS-CLIP experiments are presented in shades of orange and those obtained from the corresponding inputs in shades of blue. The map of the HIV-1 genome is presented below. Splice donor (D) and acceptor (A) sites are indicated. Peaks corresponding to clusters 2, 13, 16, 21, 25 and 30 are indicated by arrows.

Immunopurified RNAs were radiolabeled, separated on SDS-PAGE and transferred to nitrocellulose membrane. Autoradiograms revealed the presence of RNA–protein complexes migrating from 100 kDa, the expected size of GFP-Ago2, to higher molecular weights corresponding to the size distribution of RNAs associated with GFP-Ago2 (Figure 2A). The levels of RNAs cross-linked to GFP-Ago2 were similar in presence or absence of infection but were highly enriched compared to the control GFP immunoprecipitation, confirming the specificity of our IP conditions. Ago2-RNA complexes migrating between 125 kDa and 225 kDa, corresponding to nucleic acids up to 300 nucleotides length, were extracted from the nitrocellulose membrane. Ago2 cross-linked RNAs were purified and reverse transcribed to generate small cDNA Illumina libraries. cDNA ranging from 20 to 75 base pairs were purified for subsequent deep sequencing. Libraries were also generated from GFP control samples. However, the levels of cDNA obtained from these samples were not sufficient for subsequent deep sequencing. High throughput sequencing was conducted on small RNA libraries generated from six independent Ago2-GFP HITS-CLIP experiments prepared from either uninfected or HIV-1 NL4-3 infected cells and their corresponding inputs. HITS-CLIP experiments yielded between 15 and 24 million sequencing reads and inputs between 17 and 30 million sequencing reads (Table 1).Ago2 HITS-CLIP analysisTo assess the quality of our HITS-CLIP experiments, we first uploaded our sequencing reads to the CLIPZ software, specifically dedicated to HITS-CLIP data analysis (44). The number of distinct reads mapping to the human genome and the quality of the sequences were similar to other Ago2 HITS-CLIPs analyzed with the CLIPZ tool (data not shown). The alignment of reads in the input and in the HITS-CLIP experiments showed that whereas rRNAs, tRNAs and mRNAs were the predominant reads in the input (45%, 12% and 17%, respectively), a 5-fold enrichment of mRNAs, but not of snoRNAs, snRNAs, rRNAs or tRNAs, could be observed in the HITS-CLIP (Figure 2B). We did not observe any enrichment in miRNAs likely because our HITS-CLIP procedure favored long reads over short ones. We then sought to identify Ago2 binding sites on the viral gRNA. For this, HITS-CLIP data were analyzed in two different ways. First, trimmed reads longer than 15 nucleotides were aligned to the viral genome with a maximum of one mismatch allowed. Reads (≥50 nucleotides) of the HIV-1 RNA genome (starting at the transcription start site) from the three HITS-CLIPs (in orange) and their corresponding input (in blue) were plotted (Figure 2C). As the R region is present at both ends of the viral genome, the reads could not therefore be assigned unambiguously to the 3' or 5' ends. They were arbitrarily assigned at the 3' end of the viral genome. Several HIV-1 peaks were detectable in the input but whether they correspond to small RNA produced by the virus or degradation products was unclear. In Ago2 HITS-CLIP, we identified 40 discrete Ago2 binding sites along the viral genome with an accumulation of clusters at the central region and the 3' end of the genome (Figure 2C). Both analyses of our HITS-CLIP data gave very similar results as shown by the comparison of their mean traces (Supplementary Figure S2). We focused our interest on 31 clusters of reads based on the reproducibility of the peaks in the three HITS-CLIP experiments and the enrichment of reads in the IP over the input (Supplementary Figure S3 and Supplementary Table S1).Our study focused on HIV-1 RNA regions that correspond to Ago2 binding sites by only considering reads of 50 nucleotides length. We identified more than 40 reproducible binding sites distributed along the HIV-1 gRNA (Figure 2C). Remarkably, reads from viral origin represented <1% of the total reads in inputs, a result in agreement with other studies (22,30,32). In sharp contrast, between 8 to 25% of these long reads were from viral origin in our HITS-CLIP data, confirming that viral RNAs are preferentially enriched in Ago2 co-immunoprecipitation (Figure 1 and Table 1). Two recent reports have also explored the interaction between Ago proteins and HIV-1 RNAs using similar photoactivable ribonucleoside-induced cross-linking and immunoprecipitation (PAR-CLIP) and HITS-CLIP approaches (22,32). Contrary to our study, Whisnant et al. detected very low levels of HIV-1 PAR-CLIP reads among the total of assignable reads (below 1%). This discrepancy could be due to differences in experimental conditions, as we used an overexpressed GFP-Ago2 together with stringent washing conditions in order to improve the efficiency and specificity of our immunoprecipitation conditions. Nevertheless, Whisnant et al. (22) identified a number of RISC clusters on HIV-1 RNA in infected TZM-bl HeLa and C8166 T cell lines. Importantly, our study identified 19 clusters that overlap with clusters identified in at least one of their two cell lines including cluster 2, 13, 16 and 21 (data not shown) indicating that these HIV-1 RNA regions are indeed conserved targets of endogenous Ago-RISC in different cell lines. In sharp contrast, viral RNAs were absent from Ago2-RISC in HIV-1 infected monocyte derived macrophages, suggesting that this interaction might be cell type specific (32). Nevertheless, we identified four HIV-1 clusters that were able to downregulate RLuc activity and we showed that these effects were dependent on both Ago1 and Ago2 proteins (Figure 3A and B). Interestingly, these four HIV-1 clusters are in close proximity or overlap HIV-1 splice donor sites (Figure 2C).

Autoradiograms revealed the presence of RNA–protein complexes migrating from 125 kDa


Figure 1. NTCP inhibition by Myrcludex B increases plasma bile acid and GLP-1 levels. (A) Unconjugated, conjugated, and total plasma bile acid levels 3 hours after placebo or Myrcludex B (2.5 mg/g) injection in male obese WT and Oatp1a/1b KO mice (n = 9–10). Mice were fed a HFD for 16 weeks and subsequently treated daily with placebo or Myrcludex B for 3.5 weeks. (B) Fasting GLP-1 levels and (C) plasma insulin levels (D) during an oral glucose tolerance test (2 g/kg glucose) and (E) an insulin tolerance test (1.2 mU/kg) of the Oatp1a/1b KO mice described in panel A. (F) Body temperature, measured by temperature transponders placed near the BAT of the mice in panel A. Per animal, average body temperature was calculated from 3 individual observations. (G) Ucp1 messenger RNA expression levels, determined by reverse transcription quantitative polymerase chain reaction in BAT of the Oatp1a/1b KO mice described in panel A. Reverse transcription quantitative polymerase chain reaction samples are relative to the geometric mean of control genes 36b4 and Hprt and were normalized to the placebo-treated group. (H) Quantified UCP-1 staining in sWAT of the Oatp1a/1b KO mice described in panel A. Error bars show SEM, asterisk indicates significant changes. AUC, area under the curve

To evaluate the in vivo impact of bile acids on GLP-1 secretion, we used the NTCP inhibitor Myrcludex B to prolong bile acid signaling in obese Oatp1a/1b-deficient mice. Treatment with Myrcludex B was started 15 weeks after the onset of obesity by high-fat diet (HFD) feeding. In line with previous research, Oatp1a/1b KO mice display slightly elevated (unconjugated) bile acid levels compared with WT control animals (average WT 1.64 vs KO 6.13 mM of total bile acids) (Figure 1A). Myrcludex B treatment profoundly increased levels of total and conjugated bile acids in Oatp1a/1b KO mice 3–4 hours after the Myrcludex B injection (Figure 1A). The increase in plasma bile acids was temporary, as they completely normalized within 24 hours after the injection. Inhibition of NTCP by Myrcludex B increased fasting GLP-1 levels 10-fold (Figure 1B). Next, we evaluated if the Myrcludex B–mediated GLP-1 increase affected glycemic control. HFD-fed Oatp1a/1b KO mice treated with Myrcludex B tended to have lower insulin levels before and 15 minutes after oral glucose administration (Figure 1C). Although this suggested improved insulin sensitivity upon Myrcludex B treatment, the responses to glucose and insulin tolerance tests were not different between HFD-fed Oatp1a/1b KO mice receiving placebo or Myrcludex B treatment (Figure 1D and E). As it was recently shown that GLP-1 signaling can increase thermogenesis in brown adipose tissue (BAT), we assessed body temperature using temperature transponders placed near the BAT. Body temperature in HFD-fed OATP1a/1b KO mice treated with Myrcludex B significantly increased with an average of 0.9°C, while body temperature of placebo-treated animals remained unchanged (Figure 1F). Messenger RNA expression of Ucp1 (uncoupling protein 1), a mitochondrial gene known for its central role in BAT thermogenesis, in increased in BAT, suggesting increased thermogenesis in BAT of Myrcludex B treated HFD-fed OATP1a/1b KO mice (Figure 1G), but this increase was not observed at the protein level, and also, the UCP signal in subcutaneous white adipose tissue (sWAT) was not increased (Figure 1H), so “browning” of adipose tissue was not evident.

Inhibition of NTCP by Myrcludex B increased fasting GLP-1 levels 4-fold (Figure 1B).