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Molecular Biology, Pathobiology, and Genetics |
1 Asuragen Inc., and 2 Division of Pharmacology and Toxicology, College of Pharmacy, University of Texas at Austin, Austin, Texas
Requests for reprints: Dmitriy Ovcharenko, Institute for Cellular and Molecular Biology, University of Texas at Austin, 1 University Station A4800, Austin, TX 78712. Phone: 512-350-0302; Fax: 512-651-0601; E-mail: ovcharenko{at}mail.utexas.edu.
| Abstract |
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| Introduction |
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Many apoptotic pathway components, including those involved in TNF-induced apoptosis, have been identified using gene silencing methods (11, 12). The recent development of unbiased functional genomics approaches using small interfering RNA (siRNA) libraries (13–17) has enabled high-throughput experimentation. These approaches have uncovered multiple novel genes involved TRAIL-induced apoptosis in vitro (13, 18). It is conceivable, however, that cell type–specific genes may also be involved in TRAIL signaling, so these pathways need to be explored over a number of cells types and their developmental and proliferative states. Additionally, non–protein-coding gene-regulatory elements may also influence these signaling pathways, and screening for these is also highly amenable to high-throughput methods. Consequently, discovery-based investigations into TRAIL signaling are still capable of yielding new and interesting hypotheses about the actions and regulation of this pathway.
The influence of regulatory noncoding RNA molecules on apoptotic cell signaling has not been extensively explored, but increasing evidence points to a role for microRNAs (miRNA) in the control of intrinsic developmental and proliferative cell programs and ligand-induced cell signaling (19–21). miRNAs are newly identified, highly conserved small RNA molecules up to 22 nucleotides in length, which are encoded in plant and animal genomes (22). miRNAs regulate the gene expression by binding to the 3'-untranslated regions (3'-UTR) of specific mRNAs. A single miRNA can regulate anywhere from a few genes to hundreds of genes, and because over 200 miRNA genes are present in higher eukaryotes, this gene-regulatory miRNA network impacts diverse cellular functions (23–25).
To further characterize the genes and gene networks regulating apoptosis in mammalian cells, MDA-MB-453 breast cancer cells were transfected with more than 17,000 unique siRNAs and nearly 200 synthetic miRNAs. Screening of phenotypic defects in these cells revealed that up to 2% of siRNAs and more than 20% of miRNAs significantly affected TRAIL-induced caspase-3 activation. These results uncovered novel regulators of TRAIL-induced apoptotic signaling and point to a role for miRNA in apoptosis regulation.
| Materials and Methods |
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Oligonucleotide synthesis. Single-stranded RNA oligonucleotides were synthesized and high-performance liquid chromatography purified (>90% purity as analyzed by mass spectrometry). Single-stranded RNA oligonucleotides were annealed to generate the double-stranded siRNAs and miRNA precursor molecules that were used for transfection. Annealed oligonucleotides were analyzed by nondenaturing PAGE (Ambion).
siRNA and miRNA controls. Silencer negative control siRNA 1, 2, and 3 (Ambion) were employed as non-silencing siRNA controls. Pre-miR negative control miRNA 1 and 2 (Ambion) were employed as random sequence precursor miRNA controls. All data were normalized to the mean value from three non-silencing siRNAs or from two random sequence miRNAs.
Chemical transfection. In preparation for transfection, cells were harvested by incubation with 0.05% trypsin-EDTA/PBS (Invitrogen) for 5 min at 37°C, and trypsin was inactivated by the addition of serum-containing growth medium. Cell viability was assessed by trypan blue (Invitrogen) exclusion, and the cell suspension was stored at 37°C in polypropylene tubes for no longer than 1 h until transfection.
The large-scale RNAi screen was done in 384-well black plates (BD Biosciences) with an automatic liquid handling system (Evolution P3, Perkin-Elmer). Transfection complexes containing 30 nmol/L siRNA and 0.3 µL siPORT NeoFX transfection reagent (Ambion) were allowed to form in OptiMEM serum-free media (Invitrogen), in a total volume of 18 µL, for 20 min. MDA-MB-453 cells (5,500 cells in 60 µL of complete growth medium per well) were then overlaid onto transfection complexes, and plates were sealed with free-gas exchange lids (Axygen) to prevent water evaporation. A total of 17,280 siRNAs targeting 5,760 genes were transfected in duplicate. Cells were treated at 48 h post-transfection with 100 ng/mL TRAIL (Sigma).
Secondary siRNA and miRNA screens were done in 96-well plates with MDA-MB-453 or HeLa cells (10,000 cells in 120 µL of complete growth medium per well). For the preparation of transfection complexes, 30 nmol/L of siRNA or miRNA was combined with 0.3 µL siPORT NeoFX transfection reagent (Ambion) and incubated in a total volume of 30 µL (in OptiMEM) for 20 min. Transfections were done in triplicate. Cells were treated at 48 h post-transfection with 100 to 200 ng/mL TRAIL.
Caspase-3/7 assay. Sixteen hours after TRAIL (Sigma) treatment, cells were assayed for caspase-3/7 activity assay. Caspase lysis/activity buffer (80 µL per well) contained 30 µmol/L fluorescent AC-DEVD-AFC substrate (Bachem), 0.5% NP40, and 0.3 nmol/L EDTA. 7-Amino-4-trifluoromethylcoumarin (AFC) fluorescence was measured (excitation: 400 nm; emission: 505 nm) in black plates using a Spectramax Gemini XS Microplate Spectrofluorometer (Molecular Devices). All measurements were background corrected. For assay of caspase-3/7 activity as part of secondary screens, the Apo-ONE Homogeneous Caspase-3/7 Assay (Promega) was employed according to the manufacturer's recommended protocol.
miRNA target prediction method. Both miRBase Targets v4.0 and miRAID targets prediction software (Asuragen) were employed to predict miRNA/mRNA pairs. The former uses the miRBase algorithm to identify potential binding sites for a given miRNA in genomic sequences (26). The latter uses a technique based on PicTar (27). In brief, the miRAID algorithm parses sets of 3-UTR sequences into overlapping 30 nucleotide segments. Each of these segments is then tested for target sites based on the following strict criteria. First, a minimum of seven out of eight consecutive nucleotides must exhibit Watson-Crick complementarity to the 5' miRNA "seed" sequence (nucleotides 1–7, 2–8). Moreover, the seven nucleotide region must have been conserved across multiple alignments of five genomes (i.e., human, chimpanzee, mouse, rat, and dog), which were extracted from multiple alignments of 16 vertebrate genomes with the human genome (UCSC release hg18). Second, the optimal free energy (mfe) of the miRNA/mRNA duplexes, calculated using RNAhybrid 2.1 (with the –s3utr_human option for vertebrate sequences), could not exceed –16 kcal/mol. The final rank of miRNA/mRNA pairs was based on multiple predicted target sites, optimal free energy, and multi-genome alignment conservation. The predicted miRNA/mRNA pairs were cross-checked with siRNA screen hits and genes known to be involved in the TRAIL signaling pathway. The overlapping results between computational prediction methods and combined siRNA screen data are reported in Supplementary Table S1.
Real-time reverse transcription-PCR analysis. Total RNA from siRNA-transfected cells was isolated using the MagMAX96 Total RNA Isolation Kit (Ambion). Purified, DNase-treated RNA was reverse transcribed with random decamers using the RETROscript Kit (Ambion). Gene expression levels were determined by real-time PCR on the ABI Prism 7900 Sequence Detection System (Applied Biosystems) using SuperTaq reagents (Ambion) and SYBR Green (Molecular Probes). GAPDH data were collected using a human primer set (forward: 5'-GAAGGTGAAGGTCGGAGT-3'; reverse: 5'-GAAGATGGTGATGGGATTTC-3'). As an additional control, 18S rRNA was amplified (forward: 5'-TTGACTCAACACGGGAAACCT-3', reverse: 5'-AGAAAGAGCTATCAATCTGTCAATCCT-3') to adjust for well-to-well variances in the amount of starting template. All corrected values were normalized to those obtained for non-silencing siRNA-transfected samples.
Statistical analysis. Comparisons of group means (versus negative controls) were done using Welch's t tests. Values of P < 0.01 were accepted as significant.
| Results |
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Identification of genes that differentially influence TRAIL-induced apoptosis via siRNA library screening. To identify potential modulators of TRAIL-induced apoptosis, 17,280 siRNAs targeting 5,760 individual human genes (three distinct siRNAs per target gene) as well as positive and negative control siRNAs were transfected into breast cancer MDA-MB-453 cells. siRNAs targeting single genes were eliminated from the analysis because they likely represent off-target effects by the siRNAs (28). Forty-eight hours post-transfection, the cells were treated with 100 ng/mL TRAIL for 16 h. Cells were then selected based on their susceptibility to apoptosis, as measured by caspase-3 activity (29). TRAIL-induced caspase-3 activity was markedly altered by 264 different siRNAs (Fig. 1 ). In all cases, caspase-3 activity was induced at least 5-fold or reduced at least 3-fold.
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Identification of natural small RNAs regulating apoptosis via synthetic miRNA screening. miRNAs are naturally occurring small RNAs that regulate gene expression primarily at the translational level (23, 24). miRNAs have important regulatory functions in development, apoptosis, and metabolism (30, 31). Although a few miRNAs seem to impact apoptosis (32, 33), it is unclear if small RNAs may regulate apoptosis through death-receptor signal transduction. To test this possibility, MDA-MB-453 cells were transected with 187 individual synthetic miRNAs representing the majority of the human miRNAs that were known to exist at the time. Thirty-four of these miRNAs led to a differential caspase-3 activation phenotype (Table 2 ). To distinguish miRNAs that directly affect the TRAIL pathway from those that affect an unrelated pathway(s), hits from this TRAIL screen were compared with results from previous screens, in which we identified miRNAs exerting effects on caspase-3 activity independently of TRAIL (Table 3 ). Several miRNAs altered caspase activity in a TRAIL-independent manner. These included mir-10a, mir-28, mir-196a, and mir-337, which induced caspase-3 activity, and mir-96, mir-145, mir-150, mir-155, and mir-188, which blocked caspase-3 activation.
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We also used the miRBase Target database (Wellcome Trust Sanger Institute) to identify potential interactions between the miRNA and siRNA screen hits. Two miRNAs, mir-144 and mir-182, were predicted to directly target caspase-3. Although the activation of caspase-3 is typically achieved via proteolytic cleavage of procaspase-3, the transfection of these miRNAs 2 days before TRAIL treatment is likely sufficient to deplete the levels of procaspase-3 readily available for activation. This is supported by the observation that a siRNA targeting caspase-3 potently reduces the caspase-3 activity (Fig. 2 ). Mir-182 was also predicted to target FADD, a key adaptor molecule mediating death receptor–activated signaling. Mir-96 and mir-182 have highly homologous 5'-seed sequences (mir-96, UUUGGCACUAGCACAUUUUUGC; mir-182, UUUGGCAAUGGUAGAACUCACA), suggesting that mir-96 may also target caspase-3 and FADD. Mir-7 was predicted to target BAD, an inhibitor of the TRAIL pathway, and Let-7c was predicted to target RAS and FASLG. Putative miRNA target genes and their roles in apoptosis and cell cycle progression are depicted schematically in Fig. 3 .
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Involvement of CDK4 in TRAIL-mediated caspase-3 activation. siRNAs targeting CDK2, CDK4, and CDK9 siRNAs revealed potential interrelationships between cell cycle regulation and apoptosis signal transduction pathways. Indeed, siRNAs targeting CDK4 were some of the most potent in suppressing caspase-3 activation. Therefore, we characterized the role of each gene family member by silencing the expression of CDK1/CDC2, CDK2, CDK3, CDK4, CDK5, CDK6, CDK7, CDK8, CDK9 (with three siRNAs per gene) before TRAIL exposure (Fig. 2). As was observed in the initial screen, CDK2, CDK4, and CDK9 siRNAs reduced caspase-3 activity in treated cells, with CDK4 reducing caspase-3 activity by
75%. siRNAs targeting the other cyclin-dependent kinases had little effect on caspase activation, suggesting that there are direct ties between CDK2, CDK4, and CDK9 and the caspase cascade. Interestingly, silencing of CDK6, which not only shares a 71% amino acid sequence identity with CDK4, but also has the same cell cycle regulatory function (34), did not result in repression of apoptotic signaling. This result suggests that CDK4 may have an apoptosis-specific signaling role. In fact, CDK4 was recently found to be essential for the maintenance of breast tumor cell proliferation, whereas CDK6 did not impact initiation and growth of tumors (35).
| Discussion |
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Among the more interesting genes that were revealed to modulate apoptosis was CDK4, a cyclin-dependent kinase that is capable of inducing G1 arrest in response to the DNA damage sensor, p53. It is well established that CDK4 phosphorylates key regulatory substrates including retinoblastoma protein (pRb) to trigger G1-S cell cycle progression. CDK4 mutation and up-regulated expression are found in human tumors (36, 37). CDK4/CDK6 knock-out mice show normal organogenesis, and proliferation of most cell types is not inhibited, suggesting that alternative mechanisms can bypass the CDK-mediated cell cycle events (38, 39). In line with these findings, CDK4 kinase inhibitors may be ineffective as cancer therapeutics (40). In our study, down-regulation of CDK4 resulted in G1-S phase arrest and a failure to undergo apoptosis. Silencing of CDK6, which shares >70% of sequence homology with CDK4 and is believed to exert essential cell cycle function in CDK4–/– null mice, did not result in the repression of caspase-3 activation. This suggests that CDK4 modulates apoptosis independently of its cell cycle function. Moreover, among the CDK family members, CDK4 seems to be unique in its ability to regulate apoptosis.
The finding that miRNAs may affect TRAIL-induced apoptotic pathways significantly enhances the complexity of ligand-induced apoptosis. miRNAs enhancing caspase-3 activation can exert their action via targeting inhibitors of TRAIL pathway (mir-7 targeting BAD), or affecting other genes (let-7c targeting RAS and FASLG), therefore amplifying apoptosis induction. The collection of miRNAs that affect both TRAIL-induced and TRAIL-independent apoptosis include several small RNAs known to be differentially expressed in human cancers. Mir-15a and mir-16 are frequently down-regulated or deleted in B-cell chronic lymphocytic leukemia (32). Both miRNAs are capable of inducing apoptosis by negatively regulating BCL2 at the post-transcriptional level (41). Accordingly, overexpression of mir-15a and mir-16 in a leukemic cell line model potently induces apoptosis (32). We observed a similar phenotype of these miRNAs in TRAIL-independent apoptosis in human skin fibroblast BJ cells.
One group of miRNAs—mir-143, mir-145, and let-7—are all down-regulated in tumors from patients with several different cancers (25, 42, 43). It is worth contemplating whether dysregulation of one or more of these miRNAs may allow cells to bypass apoptotic pathways. Although overexpression of the let-7 family has been shown to induce apoptosis in multiple cell systems, it was extremely interesting that increased levels of miR-145 decreased the capacity of cells to respond to TRAIL. Mir-145 seems to be down-regulated in many cancer cells, providing a potential explanation as to why cancer cells respond more readily to TRAIL than untransformed cells.
A recent study showed that a transgenic mouse line overexpressing mir-155 developed lymphoproliferative disease and malignancy (44). Consistent with the ability of mir-155 overexpression to induce neoplastic disease, we found that mir-155 was one of the most potent miRNA suppressing apoptosis in MDA-MB-453 cells and T-cell leukemia Jurkat cells. This apoptosis-inhibiting effect of mir-155 is supported by the observation that mir-155 is overexpressed in breast, lung, and colon cancer tumors (44). The finding that overexpression of mir-145, mir-216, mir-182, and mir-96 miRNA reduced caspase-3 activation (Table 2) is particularly interesting in light of the fact that these miRNAs were predicted to interact with DR4/5 and FADD, both of which lie upstream of caspase-3 activation (Fig. 3). On the other hand, transfection of miRNAs (i.e., let-7, mir-7, mir-15a, and mir-16) that were predicted to interact with BCL2, BAD, BCL2L1 elicited an increase in caspase-3 activity. This finding strongly suggests that let-7, mir-7, mir-15a, and mir-16 do in fact target those genes. Most importantly, they point to a role for miRNA in apoptosis regulation.
| Acknowledgments |
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We thank L. Ford, C. Erickson, and J. Richburg for helpful discussions. We thank A. Ellington, T. Pappas, and K. Cole-Edwards for manuscript review. We are grateful to C. Trudell and C. Nannamore for providing siRNA libraries. We thank O. Ovcharenko for help with graphics.
| Footnotes |
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Received 4/24/07. Revised 8/15/07. Accepted 9/21/07.
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B pathway. Immunity 1997;7:821–30.[CrossRef][Medline]This article has been cited by other articles:
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