Selectivity in Small Molecule Splicing Modulation - ACS Chemical

Aug 8, 2016 - Deepak Kumar†∥, Manoj K. Kashyap†∥, James J. La Clair‡, Reymundo Villa‡, Ide Spaanderman†, Stephen Chien†, Laura Z. Rass...
0 downloads 0 Views 3MB Size
Download PDF
Articles pubs.acs.org/acschemicalbiology

Selectivity in Small Molecule Splicing Modulation Deepak Kumar,†,∥ Manoj K. Kashyap,†,∥ James J. La Clair,‡ Reymundo Villa,‡ Ide Spaanderman,† Stephen Chien,† Laura Z. Rassenti,†,§ Thomas J. Kipps,†,§ Michael D. Burkart,*,‡ and Januario E. Castro*,†,§ †

The Moores Cancer Center, University of California San Diego, La Jolla, California 92093, United States Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093-0358, United States § CLL Research Consortium, and Department of Medicine, University of California, San Diego, La Jolla, California 92093-0358, United States ‡

S Supporting Information *

ABSTRACT: The dysregulation of RNA splicing is a molecular hallmark of disease, including different and often complex cancers. While gaining recognition as a target for therapeutic discovery, understanding the complex mechanisms guiding RNA splicing remains a challenge for chemical biology. The discovery of small molecule splicing modulators has recently enabled an evaluation of the mechanisms of aberrant splicing. We now report on three unique features within the selectivity of splicing modulators. First, we provide evidence that structural modifications within a splicing modulator can alter the splicing of introns in specific genes differently. These studies indicate that structure activity relationships not only have an effect on splicing activity but also include specificity for specific introns within different genes. Second, we find that these splicing modulators also target the mRNAs encoding components of the spliceosome itself. Remarkably, this effect includes the genes for the SF3B complex, a target of pladienolide B and related splicing modulators. Finally, we report on the first observation of a temporal phenomenon associated with small molecule splicing modulation. Combined, these three observations provide an important new perspective for the exploration of splicing modulation in terms of both future medicinal chemistry programs as well as understanding the key facets underlying its timing.

O

properties, often with half-lives of less than 30 min. For instance, FD-895 (1) undergoes rapid hydrolysis in aqueous media to afford a mixture of spliceosome inactive seco-acids even when buffered at pH 7.18,26 Despite this shortcoming, some of these compounds show potent activity both in vitro at the cellular level and in vivo in animal models, indicating a rapid and committed response to these compounds.1−11,33 Early on, we recognized that this metabolic stability can pose serious concerns associated with the inability to effectively dose the compound, as well as complications associated with off-target effects from the resulting metabolic products. Through years of effort, we synthesized cyclopropane analog 3 (Figure 1)26 as a

ver the past decade, a panel of natural products, represented in part by FD-895 (1),1 pladienolide B (2),2,3 herboxidiene,4 and spliceostatin A,5 have been identified, offering new tools to probe the spliceosome.6 As shown in Figure 1, each of these materials are related through a common structural motif displayed around a central diene. Since 2007, a series of investigations identified,7,8 and subsequently validated,9−11 the targeting of these materials to the splicing factor SF3B1 (SAP155),12 resulting in splicing modulation and nuclear export of intron-bearing precursors. This discovery was further expanded through medicinal chemistry efforts, whereby total synthesis13−22 played a key role in structural validation and expanded structure−activity relationship (SAR) studies.23−32 Still, many if not all of the SF3B1-targeting splicing modulatory natural products suffer from poor pharmacological © XXXX American Chemical Society

Received: July 24, 2015 Accepted: July 19, 2016

A

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology

Figure 1. Structures of natural product splicing modulators spliceostatin A, herboxidiene, FD-895 (1), and pladienolide B (2). Each of these compounds shares a consensus motif around a central diene unit (yellow highlight). In addition, we have developed a stabilized analog cyclopropane 3 that offers improved metabolic stability, therein reducing the potential for off target responses. Analog 3 was optimized by replacement of the epoxide at C18−C19 with a cyclopropane (green) and altering the stereochemical arrangement at C16−C17 to offer enhanced activity (orange).

Figure 2. Variations in splicing programs. There are different modes of alternative splicing modulation. (a) Constitutive splicing is most common, where as part of the normal processing of transcription, the spliceosome removes intronic (non-coding) portions of pre-mRNA. In diseased or abnormal cells, other pathways such as (b) aberrant splicing machinery-like mutations in the SF3B1 gene could lead to mutually exclusive splicing. Additional events such as (c) exon skipping or (d) intron retention can also occur as part of normal splicing or in cells treated with splice modulators.

modulator that can be used to explore the long-term effects of splicing modulation without compound degradation.

■

alterations in the splicing of their spliceosome components, including SF3B1, the target of 1, 2, and 3. Using genes selected from this group (inset, Figure 3b), we applied qRT-PCR (Figure 4) and RT-PCR (Supporting Information Figure S1) to quantify the response to 1, 2, and 3 in primary CLL-B cells,33 mantle cell lymphoma (MCL-B) primary cells, and in an established MCL cell line (JeKo-1). Our goal was to collect analytical data reflecting the effects of different compounds on specific introns of the selected genes. We began by using RNU6A or H2A as a control for RNA isolation and RT-PCR analyses (Supporting Information Figure S2). We also repeatedly found that certain genes that possess introns, such as housekeeping genes including GAPDH, lacked IR after treatment with 1, 2, or 3 (Supporting Information Figure S1). Further, we found that these effects were not observed even under the supra-physiological concentrations of chemotherapy, as illustrated by the lack of IR in F-ara-A (F, Figure 4) or etoposide treated cells (E, Figure 4). As shown in Figure 4, we found that some genes underwent comparable levels of IR in response to modulators 1−3 (PRPF4, RIOK3, and ZRSR2), while others showed enhanced IR response when subjected to 1 (ARF-4, BRD2, PRPF4B, SRSF6, Figure 4), 2 (SF-1, SF3A1, SF3B1, SF3B2, SF3B3, SF3B4, Figure 4), and 3 (SF3A3, Figure 4). This observation identified an unexpected, but reproducible, intron-based selectivity on select genes. While we explored one intron per gene, we note that it is also possible that further selectivity appears for different introns within each gene. We also observed that certain genes, such as MCL-1 (Figure 5), underwent AS marked by a downregulation of the

RESULTS AND DISCUSSION Recently, our laboratories have been exploring the use of these agents to modulate the normal course of splicing (Figure 2). In particular, we have been intrigued by the means through which splicing modulators divert normal splicing patterns (Figure 2a) toward different modes of alternative splicing (AS), such as mutually exclusive splicing (Figure 2b), exon skipping (ES, Figure 2c), or intron retention (IR, Figure 2d). In this study, we adapted a combination of systems-wide and targeted gene analysis approaches to evaluate the roles in which these splicing modulators alter components of the spliceosome. Comparative bioinformatics analyses of RNAseq data sets (Figure 3a)33 derived from chronic lymphocytic leukemia B (CLL-B) cells indicated that treatment with 1 induced IR in >82% of the total genes (Figure 3b). A significant fraction of these genes encoded proteins that were directly involved in mRNA processing and splicing. This was an intriguing observation, as it implied that while 1 targeted the spliceosome, it had an immediate effect not only on the spliceosome but also on the subsequent splicing of spliceosome components. Interestingly, treatment with 1 led to induction of >30% of the total genes associated with the spliceosome complex, as compared to other pathways associated with metabolism (16%), cellular processes (10%), signal transduction (5%), localization (5%), apoptosis (5%), ER stress (4%), and immunity/immunoresponse (4%). This enrichment of spliceosome genes as compared to other gene groups by 2- to 5-fold indicated that cells treated with 1 underwent significant B

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology

cells treated with 1 versus untreated and selected unchanged non-spliceosomal genes, as shown in a scatter plot (Supporting Information Figure S3). We selected SIDT2, ITGB7, and ATP5L genes based on the fold-change for IR between treated and untreated CLL cells (Supporting Information Figure S3). Splicing modulators 1, 2, and 3 do not induce IR in nonspliceosomal genes SIDT2, ITGB7, and ATP5L (Supporting Information Figure S3). Next, we wanted to explore if the effects on modulating the splicing of genes associated with the spliceosome had effects at the protein level. While this appears to be a straightforward task addressed by Western blot analyses, it is complicated by the fact that splicing modulation events occur rapidly, while the conversion from RNA into protein occurs slowly. This would have an impact on a variety of feedback systems if not properly addressed. For instance, post-translational modifications such as phosphorylation would complicate these studies in general, as splicing modulation could alter the normal splicing of the associated kinases/phosphatases. We were also concerned that levels of a given protein lost by IR or ES could be replaced by feedback-regulated increases in gene expression. Additionally, one of the primary concerns associated with this time differential arises from the fact that cells at different stages of the cell cycle would experience rapid changes of mRNA levels, while their effects at the protein level may not be seen until later. To evaluate the first point, we examined the levels of phosphorylation of SF3B136 after treatment with 2. As shown in Figure 7, we observed a loss in phosphorylated SF3B1 (pSF3B1) and total SF3B1, indicating that splicing modulation by 2 observed at the gene level in Figure 7 did indeed lead to a reduction of translated SF3B1 protein. To examine the role of timing, we turned our attention to study the effects on proteins that are made during specific stages of the cell cycle. By using synchronized cells, we were able to specifically monitor the effects of splicing modulation at a distinct time point. We focused our efforts to study a protein whose expression is directly regulated during the short G2/M phase, thereby reducing the time possible for recovery from splicing modulation and feedback regulation in protein expression (Figure 8a). We chose polo-like kinase 1 (PLK1),37 a protein that has been shown to have low expression at G1 and undergo enhanced expression at the G2/M phase. As illustrated in Scheme 1, we began by treating G1-synchronized JeKo-1 cells with 100 nM 3 for 2 h, a state that had low PLK1 expression (Figure 8a). After this treatment (step 1, Scheme 1), the cells were washed to remove 3 and then further cultured in media lacking 3 through the S phase, until they began to enter the G2/M phase at ∼14 h (step 2, Scheme 1). LC-MS analyses confirmed the presence of 3 during treatment and a lack of 3 after washing (Supporting Information Figure S4), indicating that the treatment occurred correctly. The cells were then harvested at the G2/M phase (step 3, Scheme 1), the stage where PLK1 is expressed (Figure 8a). We evaluated the levels of compound 3 via LC-MS analysis, PLK1 mRNA by RT-PCR, and PLK1 protein by Western blot analyses,38 in parallel on cells collected at distinct points during the cell cycle. We determined that while 3 was no longer detected (LC/MS detection limit for 3 was 20 pg/g of cell pellet) in the cells at the G2/M phase (Supporting Information Figure S4), the IR of PLK1 was observed in cells treated with ≥0.3 μM 3 when compared to control genes (Figure 8b). This

Figure 3. FD−895 (1) induces IR in CLL-B cells. (a) RNAseq analyses. A depiction of selected genes in CLL-B cells bearing IR after treatment with 100 nM FD-895 (1) for 2 h.33 A “−” denotes negative control run under identical conditions but in the absence of 1. (b) Bioinformatics analyses depicting gene types with their statistical significance in CLL treated with 1 as compared to control CLL: the smallest bubbles have a Bonferroni p value of 0.01, and the largest circles have a p value of 1 × 10−42. The total number of processes tested was ∼7000. (Inset) A list of the top spliceosome and RNA splicing related genes that contained IR upon treatment with 1.

pro-survival, long form (L) of MCL-1, indicating that the response was not limited to IR but also included AS.33−35 Overall, these data identified a unique structure−activity relationship (SAR) that appeared in an intron-specific gene manner (Figure 4). To further characterize this response, we turned to RT-PCR analysis to identify concentration and/or time dependence. Using PRPF4 (Figure 6), we found that increasing the concentration of 3 made it possible to return and even increase its efficacy over 1 or 2 (Figure 6a), suggesting that the effect for those genes was, in part, dose dependent. This, however, was not the only variable that altered the response. As noted by comparing Figure 6a to b, time also played a key role in regulating the selectivity. While each of the three splicing modulators showed similar activity at 0.3 μM at 3 h, compound 3, the more stable analog, showed reduced activity at 0.3 μM at 6 h, indicating a complex but important correlation with the time of treatment. Further, we evaluated RNAseq data sets for identification of non-spliceosomal genes to study whether those genes undergo IR. To accomplish this, we analyzed RNAseq data from CLL-B C

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology

Figure 4. qRT-PCR analysis of IR in response to modulators 1−3. MCL-B cells were treated with 100 nM 1, 100 nM 2, 100 nM 3, 10 μM F-ara-A (F), or 30 μM of etoposide (E) for 4 h. After treatment, the levels of expression of unspliced mRNA of different spliceosome genes were evaluated by qRT-PCR. Splicing modulators 1, 2, and 3 increased the levels of the unspliced form of different spliceosome genes, while there was no change in these genes by either F or E in treated MCL-B cells. While all genes depicted were evaluated in the same sets of cDNA samples after their respective treatments, different levels of IR were obtained for each compound. For some genes, the levels were comparable for all three modulators 1−3 (gene names in black). For others, increased levels were observed for 1 (gene names in red), 2 (gene names in blue), 3 (genes name in green), or 2−3 (gene names in aqua). All qRT-PCR experiments were conducted in triplicate using qRT-PCR technical replicates. Data are presented as mean ± SD. Statistical significance has been determined between control versus MCL-B samples after treatment with 1, 2, and 3 using a one-way ANOVA test, and the differences are presented (****p < 0.0001, ***p < 0.001, **p < 0.01, or *p < 0.05). Data from parallel RT-PCR data can be found in Supporting Information Figure S1.

Figure 5. Analysis of alternative splicing. MCL-B cells were treated with 100 nM 1, 100 nM 2, 100 nM 3, 10 μM F-ara-A (F), or 30 μM etoposide (E). After treatment for 4 h, the levels of spliced and unspliced gene expression were evaluated by RT-PCR analysis. AS was not observed in the control (GAPDH) or samples treated with F or E, even at supra-physiological concentrations. The same sample of cell lysate was used for all PCR reactions depicted in this figure and was consistent after replication on different samples of cell lysates. Figure 6. Splicing modulator 3 induces IR in a concentration- and time-dependent manner. JeKo-1 cells were treated with 0.1−3.0 μM 1, 0.1−3.0 μM 2, or 0.1−3.0 μM 3 for (a) 3 h or (b) 6 h. Untreated cells considered as control. After treatment, cells were harvested followed by transcript level evaluation of PRPF4 using RT-PCR. M denotes the 100 bp DNA ladder. Levels depicted above the lanes denote the percentage of spliced RNA within each lane as determined by analysis via ImageJ.

observation suggested that while 3 induced effects on RNA associated with proteins within the spliceosome during treatment, the IR in PLK1 arose due to events that occurred long after 3 was removed from the media. As IR retained PLK1 translated into PLK1 protein, one would expect that this observation would be accompanied by a loss in PLK1 protein. As shown in Figure 8c, the effects were marked by dosedependent loss in PLK1 protein. Interestingly, these studies not only demonstrated an increase in IR in PLK1 splicing and reduction in PLK1 protein upon treatment with 3 but also indicated that this reduction arises at a time well after the effects of 3 on the cell. The fact that the levels of spliced PLK1 remain consistent upon treatment with 3 (Figure 8b) may suggest that other factors such as the regulation of additional components within the cell like nonsense-mediated mRNA decay (NMD), mRNA metabolism, and translation termination may also partake in the reduction of PLK1. Alternatively, this response could have arisen due to the splicing modulators not being removed from the cells due to covalent modification of the spliceosome. Overall, this study identifies the critical

importance of temporal effects on the efficacy of splicing modulators, as well as illustrating a need for tools that can accurately access the levels of protein levels at distinct points after a splicing event.

■

CONCLUSION Prior reports have indicated that the knockdown of SF3B1, a component of the SF3B complex, led to differential splicing modulation of isoforms of certain proteins.39 As indicated herein, treatment with 1, 2, and 3 may not directly mirror knockdown experiments, as different responses were obtained in cells treated with modulators 1, 2, or 3. This differential activity suggests a unique selectivity within small molecule D

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology Scheme 1. Timed Treatmenta

Figure 7. Pladienolide B (2) regulates the level of SF3B1 phosphorylation. JeKo-1 cells were treated with 100 nM 2 for 6, 12, or 24 h. Untreated cells grown for 24 h were considered as control (C). a

Clock diagrams denote the experimental timing as given as follows: (Step 1) Synchronized JeKo-1 cells were treated 1 h after release from starvation (start, s) with 3. (Step 2) After incubation (treatment, t, red), the medium was removed, the cells were washed with media lacking 3, and the cells were cultured (incubation, i, purple) for an additional 12 h without 3. (Step 3) The cells were collected (harvest, h, blue) and evaluated.

As demonstrated in Figure 8 and Scheme 1, we are able to specifically tailor splicing modulation to occur at specific times within the cell cycle and monitor these effects at both the RNA and protein levels at discrete time points. Using synchronized cells and a marker with a specific expression profile, we found that levels of IR and protein regulation due to splicing modulation arise well after treatment with a splicing modulator. This evidence suggests that the effects of a splicing modulator may be retained well after its removal from media. This observation in part explains why metabolically unstable materials such as FD-895 (1), pladienolide B (2), spliceostatins, or herboxidienes may maintain sufficient activity in vivo and in vitro cell models. These data clearly indicate that there are multiple levels of response in cells whose normal splicing has been modulated by a small molecule. For now, our data provide a strong indication that small molecules such as 3 significantly modulate the splicing of RNA associated with protein components of the spliceosome. This modulation can have a number of downstream effects, including inducing additional levels of splicing modulation based on gene selectivity, access to post-translational modifications, as well as selectivity with regard to temporal expression. These observations begin to suggest a complex network associated with splicing modulation. Finally, this evidence further suggests how a rapidly degraded natural product such as FD-895 (1) or pladienolide B (2) could imprint lethal modifications in RNA splicing well past its functional state within the cell. This observation also suggests, contrary to most medicinal chemistry efforts, which rapidly metabolized splicing modulators may be beneficial for selectivity. Altogether, these findings provide important details to inform an increased interest in splicing as a potential target for cancer therapy.40−44

Figure 8. Timing of splicing modulation. (a) Western blot analyses of lysates from cells treated with 3 and collected either after treatment (t) or harvest (h). PLK1 expression arises as cells enter the G2/M transition during harvest and not at G1 during treatment. This blot confirms the increase of protein at the state of harvest (h), indicating that the cells were at G2/M. (b) RT-PCR analysis evaluated the levels of PLK1 in JeKo-1 cells treated (t) with 3, washed, and collected at harvest (h). IR was observed for PLK1 after treatment with 3. RT-PCR analysis was conducted using GAPDH, RNU6A (RNA isolation and RT-PCR activity), and H2A (RNA isolation and RT-PCR activity) as controls. (c) Western blot analyses of cells treated with 3 and collected at harvest (h). This blot confirms a dose-dependent reduction in the levels of PLK1 protein in cells exposed to 3 relative to controls. For the blots in a or c, the levels of PLK1 are presented according to loading control (β-actin). All experiments in this figure as well as the LC/MS analysis for the levels of 3 (Supporting Figure S3) were conducted on the same batch of cells.

splicing modulation. First, we found that structural modifications within the splicing modulator led to a different selectivity in splicing at the level of select introns with different genes. As shown in Figure 4 and Supporting Information Figure S1, the activity of 1 and 2 remained comparable yet different than that obtained by cyclopropane analog 3. This effect was not uniform for each gene examined, implicating a more complex intronexon selectivity that arises during modulation by agents that target SF3B. While the effects from 3 could be rescued in a dose dependent manner for some genes, analog 3 also generated responses at a gene level different than that from 1 or 2. This begins to suggest a means to selectively target the splicing of specific introns with select genes or sets of genes.

■

METHODS

Compounds. FD-895 (1)18 and cyclopropane 326 were prepared by total synthesis in our laboratories. Pladienolide B (2) was obtained as a gift from Merlion Pharmaceuticals or purchased from Santa Cruz E

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology Biotechnology. Fludarabine phosphate (F-ara-A)45 and etoposide were obtained from Sigma-Aldrich. All oligonucleotides were purchased via custom synthesis (Integrated DNA Technologies). Cell Culture. The JeKo-1 cell line was obtained from ATCC and maintained in RPMI supplemented with 10% fetal bovine serum (FBS), 2 mM L-glutamine, and 100 U mL−1 of penicillin and 100 μg mL−1 of streptomycin at 37 °C in an atmosphere of 5% CO2. Primary Chronic Lymphocytic Leukemia (CLL-B) and Mantle Cell Lymphoma (MCL-B) Cells. Peripheral blood mononuclear cells (PBMC) from CLL/MCL patients were obtained from the CLL Research Consortium (CRC) tissue bank. After CLL/MCL diagnosis was confirmed, patients provided written informed consent for blood sample collection on a protocol approved by the Institutional Review Board (IRB) of UC San Diego, in accordance with the Declaration of Helsinki (WMA Declaration of HelsinkiEthical Principles for Medical Research Involving Human Subjects as described online http://www.wma.net/en/30publications/10policies/b3/index. html%5D). All patients fulfilled diagnostic criteria for CLL/MCL. Mononuclear cells were isolated by the standard Ficoll−Hypaque gradient centrifugation and viably frozen in a solution of heat inactivated FBS supplemented with 10% DMSO. More than 90% of the isolated blood mononuclear cells from patients with CLL and MCL were CD19+/CD5+ cells and CD5+/cyclinD1+ cells, respectively, as assessed by using flow cytometry. After thawing, viable cells derived from CLL-B/MCL-B patients’ cells were maintained in RPMI 1640 medium supplemented with 10% FBS, 2 mM L-glutamine, 100 U mL−1 of penicillin, and 100 μg mL−1 of streptomycin at 37 °C in an atmosphere containing 5% CO2. Normal B Cells Isolation. Normal B cells were purified from healthy donor buffy-coat blood samples obtained from the San Diego Blood Bank (SDBB). Peripheral blood mononuclear cells (PBMCs) were first isolated by a Ficoll−Hypaque gradient centrifugation and suspended in RPMI medium. B cells were then isolated using RosetteSep B-cell enrichment cocktail (Stemcell Technologies). The purity of isolated B cells was more than 90% as assessed by flow cytometry using fluorochrome-conjugated anti-CD19 mAb/anti-CD20 mAb and their corresponding isotype controls. RNAseq Analyses. RNA isolation, cDNA preparation, RT-PCR, and qRT-PCR were done for CLL-B cells after treatment with 100 nM FD-895 or untreated for 2 h as described previously.33 Samples from two CLL patients, one male and one female, were examined. Total RNA was extracted using a mirVana miRNA isolation kit (Life Technologies). The RNA was treated with DNase on column. Purified RNA was checked for quality control (QC), and RNA sequencing (RNAseq) was performed using HiSeq reading (Illumina) at Otogenetics Corporation. One-hundred-basepair paired-end RNAseq reads were mapped to the hg19 RefSeq assembly of the human genome using a fast sequence mapper/aligner Bowtie2.46 A separate alignment was used for detecting misspliced reads that contain retained introns. The relative abundances of intron-retaining reads and conventional splice-site spanning reads across all known exon boundaries were used to estimate the rate of misspliced isoforms generated at each genetic locus. We used a maximum likelihood expectation estimator.47 In addition to the novel misspliced variants, we quantified differential exon usage and potential alternative splicing/exon usage for selected genes using the statistical algorithm DEXSeq.48 Finally, we used genelevel counts as inputs for differential expression analyses at the level of a gene locus, using DESeq2 (differential expression analysis for sequence count data).49 Both DESeq and DEXSeq use a negative binomial distribution to model the gene/exon read counts and shrinkage estimators to estimate per-gene dispersion. Each statistical test results in a p value. We adjusted the p value for multiple testing using the concept of false discovery rate (FDR)50 and posterior error probabilities (local false discovery rates) as implemented in the R package fdrtool.51 Gene lists sorted by significance in the pairwise comparisons between treatments were analyzed for statistically significantly regulated biological processes and pathways using the Gene Set Enrichment Analysis Algorithm (GSEA) software and Molecular Signature Database (MSigDB).52 We also analyzed RNAseq

data to study the pathways enriched after Bonferroni correction and p < 0.01. Reverse Transcription PCR (RT-PCR). MCL-B cells (106 cells/ well) were treated either with 100 nM 1, 100 nM 2, 100 nM 3, 10 μM fludarabine (F-ara-A), or 30 μM etoposide for 4 h. Untreated cells were considered as control. Total RNA was isolated using a mirVana miRNA isolation kit (Life Technology). A 200 ng sample of RNA was subjected to DNaseI from a TURBO DNA-free kit (Life Technology). The cDNA was prepared by using a SuperScript III reverse transcriptase kit (Life Technology), and the PCR reaction was performed in 25 μL of reaction volume of high fidelity platinum PCR supermix (Invitrogen) using gene specific primers (Supporting Information Table 2). PCR conditions were as follows: 95 °C for 3 min; 35 cycles of 95 °C for 30 s, 55−58 °C (gene-dependent) for 30 s, and 72 °C for 45 s; followed by 72 °C for 5 min using a PTC-100 thermocycler (MJ Research). PCR products were separated on a 2% agarose gel and stained with ethidium bromide. A percentage change in splicing was reported for the lanes in Figure 6. This was determined by image analysis using ImageJ. The reported data reflects the overall percentage of the band from the unspliced band versus the total band intensity. Quantitative Reverse Transcription-PCR (qRT-PCR). cDNA was prepared using identical methods as used for RT-PCR analysis. The amount of unspliced RNA for different genes was determined using Power SYBR Green PCR master mix (Applied Biosystems) by qRT-PCR using specific primers designed for the detection of the intron of each gene (Supporting Information Table 3). PCR using 5 pM of each primer was performed on 20 ng of the obtained cDNA. PCR conditions were as follows: 50 °C for 10 min for one cycle, 95 °C for 15 s, and 60 °C for 20 s for 40 cycles and concluding by a dissociation step using a 7900 HT Fast Real Time PCR System (Applied Biosystems). RNA levels were calculated using the 2−ΔΔCT method.53 GAPDH was used as a control for normalization. LC-MS Analyses. Cell pellets were extracted by soaking in 1 mL of EtOH for 1 h at rt. The material was centrifuged at 1100 rpm for 2 min. The supernatant was collected, dried via airflow, and redissolved in 100 μL of CH3CN for analysis. For each analysis, 20 μL of material was injected per LC-MS run. LC-MS analyses were conducted on a 1260 liquid chromatograph (Agilent) system coupled with a LCQdeca mass spectrometer (Thermo Fisher Scientific). LC-MS analysis using positive ion mode electrospray ionization (ESI) as the ion source with source voltage of 5 kV, sheath gas flow rate of 80 units, auxiliary gas flow rate of 20 units, and capillary temperature of 250 °C. A Capcell MG III C-18 column (ID 2.0 mm × length 100 mm, particle size 3 μm) with guard column was employed for LC separation using 2.5% CH3CN in H2O with 0.1% formic acid as the mobile phase A and pure CH3CN with 0.1% formic acid as the mobile phase B. The LC flow rate was set at 0.30 mL min−1. The LC gradient increased from 5% to 95% mobile phase B in 10 min, held at 95% B for 7 min, returned to 5% B in 1 min, and then held at 5% B for 7 min. The instrument was standardized using a gradient of 3 from 0.001 nM to 10 nM. This standardization indicated that the detection limit of the method was 0.2 pg/injection. Intron Retention in PLK1. JeKo-1 cells were cultured in a 25 cm2 flask at 5 × 106 cells per flask and starved overnight after washing three times with PBS. The cells were centrifuged after each wash at 1100 rpm for 5 min at RT. Post-washing, cells were serum starved in RPMI1640 (2 mM L-glutamine, 100 U mL−1 of penicillin and 100 μg mL−1 of streptomycin) over 16 h. The cells were collected by centrifugation and resuspended in complete RPMI (10% FBS, 2 mM L-glutamine, 100 U mL−1 of penicillin, and 100 μg mL−1 of streptomycin) for recovery. After 1 h of recovery, cells were treated with either 0.1 μM 3, 0.3 μM 3, or 1.0 μM 3 for 2 h. Untreated cells were used as a negative control. The cells were collected by centrifugation at 1100 rpm for 5 min, the supernatant removed, and the cells further washed three times with 5 mL of complete RPMI to remove 3. The cells were then incubated further for another 12 h; at that point, half of cells (∼50 mg of wet mass) were saved for LC-MS analyses for the presence of 3. The remaining cells were collected for Western blot or RNA isolation and RT-PCR analyses. F

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology Western Blot Analyses. Cells from the procedure above were pelleted by centrifugation, washed twice with PBS, and lysed with modified RIPA buffer (150 mM NaCl, 50 mM Tris·HCl pH 7.4, 1% NP-40, 0.25% sodium deoxycholate, 1 mM EDTA, 1 mM sodium orthovanadate, 10 mM NaF, 10 mM glycerophosphate, 5 mM sodium pyrophosphate) containing 1% of a human protease inhibitor cocktail (Sigma-Aldrich) at 4 °C. The protein content of the whole cell lysates was quantified using a detergent compatible (DC) protein assay (BioRad). Lysates in sample buffer comprised of 720 mM 2mercaptoethanol, 0.001% bromophenol blue, 2% SDS, 10% glycerol, and 80 mM Tris·HCl at pH 6.8 were denatured at 95 °C for 5 min. Total cellular proteins (30 μg) were subjected to SDS-polyacrylamide gel electrophoresis (PAGE) using a 4−20% Criterion precast gel (BioRad) followed by transfer to polyvinylidene difluoride (PVDF) membrane (Millipore). After blocking with 5% bovine serum albumin (BSA) for 1 h in 25 mL of Tris-buffered saline with Tween 20 (TBST) comprised of 20 mM Tris·HCl, 137 mM NaCl, and 0.1% Tween-20 at pH 7.6, the membrane was incubated with a primary antibody overnight at 4 °C. The primary antibodies included a rabbit anti-PLK1 (4535, Cell Signaling Technology), rabbit anti-SF3B1 (ab172634, Abcam), rabbit anti-phospho-SF3B1 (25009, Cell Signaling), and a mouse anti-β-actin (3700, Cell Signaling). All primary antibodies were used at a 1:1000 dilution in TBST containing 5% BSA. After washing three times with 25 mL of TBST, the membranes were incubated with HRP-labeled anti-rabbit (sc-2030, Santa Cruz Biotechnology) or HRPlabeled anti-mouse (sc-2031, Santa Cruz Biotechnology) secondary antibodies with a dilution of 1:5000 TBST containing 5% BSA for 40 min at rt. The membranes were washed three times with TBST, and protein−antibody complex signals were detected by exposing the Xray films after treatment with an enhanced chemiluminescence (ECL) kit (Thermo Scientific). The PLK1 blots, and associated β-actin control, were developed by treatment with BCIP/NBT color development substrate (34042, Pierce or S3771, Promega) according to the manufacturer’s protocols. BCIP/NBT stained blots were imaged on a conventional flatbed scanner (1260, Epson).

■

(2) Mizui, Y., Sakai, T., Iwata, M., Uenaka, T., Okamoto, K., Shimizu, H., Yamori, T., Yoshimatsu, K., and Asada, M. (2004) Pladienolides, new substances from culture of Streptomyces platensis Mer-11107. III. In vitro and in vivo antitumor activities. J. Antibiot. 57, 188−196. (3) Asai, N., Kotake, Y., Niijima, J., Fukuda, Y., Uehara, T., and Sakai, T. (2007) Stereochemistry of pladienolide B. J. Antibiot. 60, 364−369. (4) Miller-Wideman, M., Makkar, N., Tran, M., Isaac, B., Biest, N., and Stonard, R. (1992) Herboxidiene, a new herbicidal substance from Streptomyces chromof uscus A7847. Taxonomy, fermentation, isolation, physico-chemical and biological properties. J. Antibiot. 45, 914−921. (5) Nakajima, H., Takase, S., Terano, H., and Tanaka, H. (1997) New antitumor substances, FR901463, FR901464 and FR901465. III. Structures of FR901463, FR901464 and FR901465. J. Antibiot. 50, 96− 99. (6) Webb, T. R., Joyner, A. S., and Potter, P. M. (2013) The development and application of small molecule modulators of SF3b as therapeutic agents for cancer. Drug Discovery Today 18, 43−49. (7) Kotake, Y., Sagane, K., Owa, T., Mimori-Kiyosue, Y., Shimizu, H., Uesugi, M., Ishihama, Y., Iwata, M., and Mizui, Y. (2007) Splicing factor SF3b as a target of the antitumor natural product pladienolide. Nat. Chem. Biol. 3, 570−575. (8) Kaida, D., Motoyoshi, H., Tashiro, E., Nojima, T., Hagiwara, M., Ishigami, K., Watanabe, H., Kitahara, T., Yoshida, T., Nakajima, H., Tani, T., Horinouchi, S., and Yoshida, M. (2007) Spliceostatin A targets SF3b and inhibits both splicing and nuclear retention of premRNA. Nat. Chem. Biol. 3, 576−583. (9) Folco, E. G., Coil, K. E., and Reed, R. (2011) The anti-tumor drug E7107 reveals an essential role for SF3b in remodeling U2 snRNP to expose the branch point-binding region. Genes Dev. 25, 440−444. (10) Sato, M., Muguruma, N., Nakagawa, T., Okamoto, K., Kimura, T., Kitamura, S., Yano, H., Sannomiya, K., Goji, T., Miyamoto, H., Okahisa, T., Mikasa, H., Wada, S., Iwata, M., and Takayama, T. (2014) High antitumor activity of pladienolide B and its derivative in gastric cancer. Cancer Sci. 105, 110−116. (11) Yokoi, A., Kotake, Y., Takahashi, K., Kadowaki, T., Matsumoto, Y., Minoshima, Y., Sugi, N. H., Sagane, K., Hamaguchi, M., Iwata, M., and Mizui, Y. (2011) Biological validation that SF3b is a target of the antitumor macrolide pladienolide. FEBS J. 278, 4870−4880. (12) Hasegawa, M., Miura, T., Kuzuya, K., Inoue, A., Won Ki, S., Horinouchi, S., Yoshida, T., Kunoh, T., Koseki, K., Mino, K., Sasaki, R., Yoshida, M., and Mizukami, T. (2011) Identification of SAP155 as the target of GEX1A (Herboxidiene), an antitumor natural product. ACS Chem. Biol. 6, 229−233. (13) Kanada, R. M., Itoh, D., Nagai, M., Niijima, J., Asai, N., Mizui, Y., Abe, S., and Kotake, Y. (2007) Total synthesis of the potent antitumor macrolides pladienolide B and D. Angew. Chem., Int. Ed. 46, 4350−4355. (14) Zhang, Y., and Panek, J. S. (2007) Total synthesis of herboxidiene/GEX 1A. Org. Lett. 9, 3141−3143. (15) Gao, Y., Vogt, A., Forsyth, C. J., and Koide, K. (2013) Comparison of splicing factor 3b inhibitors in human cells. ChemBioChem 14, 49−52. (16) Murray, T. J., and Forsyth, C. J. (2008) Total synthesis of GEX1A. Org. Lett. 10, 3429−3431. (17) Pellicena, M., Krämer, K., Romea, P., and Urpí, F. (2011) Total synthesis of (+)-herboxidiene from two chiral lactate-derived ketones. Org. Lett. 13, 5350−5353. (18) Villa, R., Mandel, A. L., Jones, B. D., La Clair, J. J., and Burkart, M. D. (2012) Structure of FD-895 revealed through total synthesis. Org. Lett. 14, 5396−5399. (19) Ghosh, A. K., Ma, N., Effenberger, K. A., and Jurica, M. S. (2014) Total synthesis of GEX1Q1, assignment of C-5 stereoconfiguration and evaluation of spliceosome inhibitory activity. Org. Lett. 16, 3154−3157. (20) Ghosh, A. K., Chen, Z. H., Effenberger, K. A., and Jurica, M. S. (2014) Enantioselective total syntheses of FR901464 and spliceostatin A and evaluation of splicing activity of key derivatives. J. Org. Chem. 79, 5697−5709.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acschembio.6b00399. Figures S1−S4, Tables S1−S3 (PDF)

■

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. Author Contributions ∥

These authors contributed equally.

Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was supported by a grant from the Lymphoma Research Foundation (#285871), the National Institutes of Health (PO1-CA081534), the UC San Diego Foundation Blood Cancer Research Fund, and the Bennett Family Foundation.

■

REFERENCES

(1) Seki-Asano, M., Okazaki, T., Yamagishi, M., Sakai, N., Takayama, Y., Hanada, K., Morimoro, S., Takatsuki, A., and Mizoue, K. (1994) Isolation and characterization of a new 12-membered macrolide FD895. J. Antibiot. 47, 1395−1401. G

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX

Articles

ACS Chemical Biology

repressor serves as a molecular switch for c-myc gene expression. Mol. Cancer Res. 10, 787−799. (40) van Alphen, R. J., Wiemer, E. A., Burger, H., and Eskens, F. A. (2009) The spliceosome as target for anticancer treatment. Br. J. Cancer 100, 228−232. (41) Bonnal, S., Vigevani, L., and Valcárcel, J. (2012) The spliceosome as a target of novel antitumor drugs. Nat. Rev. Drug Discovery 11, 847−859. (42) Salton, M., and Misteli, T. (2016) Small molecule modulators of pre-mRNA splicing in cancer therapy. Trends Mol. Med. 22, 28−37. (43) Dehm, S. M. (2013) Test-firing ammunition for spliceosome inhibition in cancer. Clin. Cancer Res. 19, 6064−6066. (44) Tazi, J., Durand, S., and Jeanteur, P. (2005) The spliceosome: a novel multi-faceted target for therapy. Trends Biochem. Sci. 30, 469− 478. (45) McLaughlin, P., Robertson, L. E., and Keating, M. J. (1997) Fludarabine phosphate in lymphoma: an important new therapeutic agent. Cancer Treat. Res. 85, 3−14. (46) Langmead, B., and Salzberg, S. L. (2012) Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357−359. (47) Xing, Y., Yu, T., Wu, Y. N., Roy, M., Kim, J., and Lee, C. (2006) An expectation-maximization algorithm for probabilistic reconstructions of full-length isoforms from splice graphs. Nucleic Acids Res. 34, 3150−3160. (48) Anders, S., Reyes, A., and Huber, W. (2012) Detecting differential usage of exons from RNA-seq data. Genome Res. 22, 2008− 2017. (49) Anders, S., and Huber, W. (2010) Differential expression analysis for sequence count data. Genome Biol. 11, R106. (50) Benjamini, Y., and Hochberg, Y. J. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. Royal Stat. Soc. Series B 57, 289−300. (51) Strimmer, K. (2008) Fdrtool: a versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics 24, 1461−1462. (52) Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., and Mesirov, J. P. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. U. S. A. 102, 15545−15550. (53) Livak, K. J., and Schmittgen, T. D. (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(Delta Delta C(T)) Method. Methods 25, 402−408.

(21) Ghosh, A. K., and Chen, Z. H. (2013) Enantioselective syntheses of FR901464 and spliceostatin A: potent inhibitors of spliceosome. Org. Lett. 15, 5088−5091. (22) Ghosh, A. K., and Anderson, D. D. (2012) Enantioselective total synthesis of pladienolide B: a potent spliceosome inhibitor. Org. Lett. 14, 4730−4733. (23) Lagisetti, C., Yermolina, M. V., Sharma, L. K., Palacios, G., Prigaro, B. J., and Webb, T. R. (2014) Pre-mRNA splicing-modulatory pharmacophores: the total synthesis of herboxidiene, a pladienolideherboxidiene hybrid analog and related derivatives. ACS Chem. Biol. 9, 643−648. (24) Gundluru, M. K., Pourpak, A., Cui, X., Morris, S. W., and Webb, T. R. (2011) Design, synthesis and initial biological evaluation of a novel pladienolide analog scaffold. MedChemComm 2, 904−908. (25) Pham, D., and Koide, K. (2016) Discoveries, target identifications, and biological applications of natural products that inhibit splicing factor 3B subunit 1. Nat. Prod. Rep. 33, 637−647. (26) Villa, R., Kashyap, M. K., Kumar, D., Kipps, T. J., Castro, J. E., La Clair, J. J., and Burkart, M. D. (2013) Stabilized cyclopropane analogs of the splicing inhibitor FD-895. J. Med. Chem. 56, 6576−6582. (27) Mandel, A. L., Jones, B. D., La Clair, J. J., and Burkart, M. D. (2007) A synthetic entry to pladienolide B and FD-895. Bioorg. Med. Chem. Lett. 17, 5159−5164. (28) Kumar, V. P., and Chandrasekhar, S. (2013) Enantioselective synthesis of pladienolide B and truncated analogues as new anticancer agents. Org. Lett. 15, 3610−3613. (29) Müller, S., Mayer, T., Sasse, F., and Maier, M. E. (2011) Synthesis of a pladienolide B analogue with the fully functionalized core structure. Org. Lett. 13, 3940−3943. (30) Skaanderup, P. R., and Jensen, T. (2008) Synthesis of the macrocyclic core of (-)-pladienolide B. Org. Lett. 10, 2821−2824. (31) Effenberger, K. A., Anderson, D. D., Bray, W. M., Prichard, B. E., Ma, N., Adams, M. S., Ghosh, A. K., and Jurica, M. S. (2014) Coherence between cellular responses and in vitro splicing inhibition for the anti-tumor drug pladienolide B and its analogs. J. Biol. Chem. 289, 1938−1947. (32) Arai, K., Buonamici, S., Chan, B., Corson, L., Endo, A., Gerard, B., Hao, M. H., Karr, C., Kira, K., Lee, L., Liu, X., Lowe, J. T., Luo, T., Marcaurelle, L. A., Mizui, Y., Nevalainen, M., O’Shea, M. W., Park, E. S., Perino, S. A., Prajapati, S., Shan, M., Smith, P. G., Tivitmahaisoon, P., Wang, J. Y., Warmuth, M., Wu, K. M., Yu, L., Zhang, H., Zheng, G. Z., and Keaney, G. F. (2014) Total synthesis of 6-deoxypladienolide D and assessment of splicing inhibitory activity in a mutant SF3B1 cancer cell line. Org. Lett. 16, 5560−5563. (33) Kashyap, M. K., Kumar, D., Villa, R., La Clair, J. J., Sasik, R., Jones, H., Ghia, E. M., Rassenti, L. Z., Kipps, T. J., Burkart, M. D., Castro, J. E., and Benner, C. (2015) Targeting the spliceosome in chronic lymphocytic leukemia with the macrolides FD-895 and pladienolide-B. Haematologica 100, 945−954. (34) Gao, Y., and Koide, K. (2013) Chemical perturbation of Mcl-1 pre-mRNA splicing to induce apoptosis in cancer cells. ACS Chem. Biol. 8, 895−900. (35) Laetsch, T. W., Liu, X., Vu, A., Sliozberg, M., Vido, M., Elci, O. U., Goldsmith, K. C., and Hogarty, M. D. (2014) Multiple components of the spliceosome regulate Mcl1 activity in neuroblastoma. Cell Death Dis. 5, e1072. (36) de Graaf, K., Czajkowska, H., Rottmann, S., Packman, L. C., Lilischkis, R., Lüscher, B., and Becker, W. (2006) The protein kinase DYRK1A phosphorylates the splicing factor SF3b1/SAP155 at Thr434, a novel in vivo phosphorylation site. BMC Biochem. 7, 7. (37) Archambault, V., Lépine, G., and Kachaner, D. (2015) Understanding the Polo Kinase machine. Oncogene 34, 4799−4807. (38) Bruinsma, W., Raaijmakers, J. A., and Medema, R. H. (2012) Switching Polo-like kinase-1 on and off in time and space. Trends Biochem. Sci. 37, 534−542. (39) Matsushita, K., Kajiwara, T., Tamura, M., Satoh, M., Tanaka, N., Tomonaga, T., Matsubara, H., Shimada, H., Yoshimoto, R., Ito, A., Kubo, S., Natsume, T., Levens, D., Yoshida, M., and Nomura, F. (2012) SAP155-mediated splicing of FUSE-binding protein-interacting H

DOI: 10.1021/acschembio.6b00399 ACS Chem. Biol. XXXX, XXX, XXX−XXX