An In Vitro Protocol for Evaluating MicroRNA Levels, Functions, and Associated Target Genes in Tumor Cells
Summary
This protocol uses a probe-based real-time polymerase chain reaction (PCR), a sulforhodamine B (SRB) assay, 3’ untranslated regions (3’ UTR) cloning, and a luciferase assay to verify the target genes of a miRNA of interest and to understand the functions of miRNAs.
Abstract
MicroRNAs (miRNAs) are small regulatory RNAs which are recognized to modulate numerous intracellular signaling pathways in several diseases including cancers. These small regulatory RNAs mainly interact with the 3’ untranslated regions (3’ UTR) of their target messenger RNAs (mRNAs) ultimately resulting in the inhibition of decoding processes of mRNAs and the augmentation of target mRNA degradations. Based on the expression levels and intracellular functions, miRNAs are able to serve as regulatory factors of oncogenic and tumor-suppressive mRNAs. Identification of bona fide target genes of a miRNA among hundreds or even thousands of computationally predicted targets is a crucial step to discern the roles and basic molecular mechanisms of a miRNA of interest. Various miRNA target prediction programs are available to search possible miRNA-mRNA interactions. However, the most challenging question is how to validate direct target genes of a miRNA of interest. This protocol describes a reproducible strategy of key methods on how to identify miRNA targets related to the function of a miRNA. This protocol presents a practical guide on step-by-step procedures to uncover miRNA levels, functions, and related target mRNAs using the probe-based real-time polymerase chain reaction (PCR), sulforhodamine B (SRB) assay following a miRNA mimic transfection, dose-response curve generation, and luciferase assay along with the cloning of 3’ UTR of a gene, which is necessary for proper understanding of the roles of individual miRNAs.
Introduction
MicroRNAs (miRNAs) are the small regulatory RNAs that mainly modulate the process of translation and degradation of messenger RNAs (mRNAs) by reacting to the 3’ untranslated regions (3’ UTR) in bona fide target genes1. Expression of miRNAs can be regulated by transcriptional and post-transcriptional mechanisms. The imbalance of such regulatory mechanisms brings uncontrolled and distinctive miRNAs expression levels in numerous diseases including cancers2. A single miRNA can have multiple interactions with diverse mRNAs. Correspondingly, an individual mRNA can be controlled by various miRNAs. Therefore, intracellular signaling networks are intricately influenced by distinctively expressed miRNAs by which physiological disorders and diseases can be initiated and deteriorated2,3,4,5,6. Although the altered expression of miRNAs has been observed in various types of cancers, the molecular mechanisms that modulate the manners of cancer cells in conjunction with miRNAs are still largely unknown.
Accumulating evidence has been showing that the oncogenic or tumor-suppressive roles of miRNAs depend on the types of cancers. For example, by targeting forkhead box o3 (FOXO3), miR-155 promotes the cell proliferation, metastasis, and chemoresistance of colorectal cancer7,8. In contrast, the restriction of glioma cell invasion is induced by miR-107 via the regulation of neurogenic locus notch homolog protein 2 (NOTCH2) expression9. The assessment of miRNA-target interactions in connection with miRNA functions is an indispensable part to better understand how miRNAs regulate various biological processes in both healthy and diseased states10. In addition, the discovery of bona fide target(s) of miRNAs can further provide a fine-tuned strategy for a miRNA-based therapy with various anti-cancer drugs. However, the main challenge in the field of miRNAs is the identification of direct targets of miRNAs. Here, detailed methods are presented as reproducible experimental approaches for the miRNA target gene determination. Successful experimental design for the miRNA target identification involves various steps and considerations (Figure 1). Comparison of mature miRNA levels in tumor cells and normal cells can be one of the common procedures to select a miRNA of interest (Figure 1A). The functional study of a selected miRNA to detect the effects of a miRNA on cell proliferation is important to narrow down the list of best potential candidate targets of a miRNA of interest (Figure 1B). Based on the experimentally validated functions of miRNAs, a systematic review of literature and database in company with a miRNA target prediction program is required to search the most relevant information on gene functions (Figure 1C). The identification of real target genes of a miRNA of interest can be achieved by implementing experiments such as the luciferase assay along with the cloning of 3’ UTR of a gene, real-time PCR, and western blotting (Figure 1D). The goal of the current protocol is to provide comprehensive methods of key experiments, the probe-based real-time polymerase chain reaction (PCR), sulforhodamine B (SRB) assay following a miRNA mimic transfection, dose-response curve generation, and luciferase assay along with the cloning of 3’ UTR of a gene. The current protocol can be useful for a better understanding of the functions of individual miRNAs and the implication of a miRNA in cancer therapy.
Protocol
Representative Results
Discussion
Strategies for the determination of bona fide miRNA targets with the functions of a miRNA of interest are indispensable for the understanding of multiple roles of miRNAs. Identification of miRNA target genes can be a guideline for interpreting the cell signaling events modulated by miRNAs in a cell. An unveiling of functionally important target genes of miRNAs can provide the fundamental knowledge to develop a miRNA-based therapy in cancer.
Several methods such as microarrays, small RNA librar…
Disclosures
The authors have nothing to disclose.
Acknowledgements
This study was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A3B03035662); and Hallym University Research Fund, 2017 (HRF-201703-003).
Materials
| 15 mL conical tube | SPL Life Sciences | 50015 | |
| 24-well plate | Thermo Scientific | 142475 | |
| 50 mL conical tube | SPL Life Sciences | 50050 | |
| 6-well plate | Falcon | 353046 | |
| 6X DNA loading dye | Real Biotech Corporation | RD006 | 1 mL |
| 8-cap strip | Applied Biosystems | N8010535 | For cDNA synthesis |
| 8-tube strip | Applied Biosystems | N8010580 | For cDNA synthesis |
| 96-well plate | Falcon | 353072 | |
| Acetic acid | Sigma | A6283-1L | 1 L |
| Agarose A | Bio Basic | D0012 | 500 g |
| Alkaline phosphatase | New England Biolabs | M0290S | 10,000 U/mL |
| Ampicillin | Bio basic Canada Inc | AB0028 | 25 g |
| AriaMx 96 tube strips | Agilent Technologies | 401493 | For real time PCR |
| AriaMx real-time PCR system | Agilent Technologies | G8830A | qPCR amplification, detection, and data analysis |
| AsiSI | New England Biolabs | R0630 | 10,000 units/mL |
| CAPAN-1 cells | ATCC | HTB-79 | |
| Cell culture hood | Labtech | Model: LCB-1203B-A2 | |
| Counting chambers with V-slash | Paul Marienfeld | 650010 | Cells counter |
| CutSmart buffer | New England Biolabs | B7204S | 10X concentration |
| DMEM | Gibco | 11965-092 | 500 mL |
| DNA gel extraction kit | Bionics | DN30200 | 200 prep |
| DNA ladder | NIPPON Genetics EUROPE | MWD1 | 1 Kb ladder |
| DNase I | Invitrogen | 18068015 | 100 units |
| Dual-luciferase reporter assay system | Promega | E1910 | 100 assays |
| Fetal bovine serum | Gibco | 26140-079 | 500 mL |
| HIT competent cells | Real Biotech Corporation(RBC) | RH617 | Competent cells |
| HPNE cells | ATCC | CRL-4023 | |
| LB agar broth | Bio Basic | SD7003 | 250 g |
| Lipofectamine 2000 | Invitrogen | 11668-027 | 0.75 mL |
| Lipofectamine RNAiMax | Invitrogen | 13778-075 | 0.75 mL |
| Luminometer | Promega | Model: E5311 | |
| Microcentrifuge tube | Eppendorf | 22431021 | |
| Microplate reader | TECAN | Infinite F50 | |
| miRNA control mimic | Ambion | 4464058 | 5 nmole |
| miRNA-107 mimic | Ambion | 4464066 | 5 nmole |
| miRNeasy Mini Kit | Qiagen | 217004 | 50 prep |
| Mupid-2plus (electrophoresis system) | TaKaRa | Model: AD110 | |
| NotI | New England Biolabs | R3189 | 20,000 units/mL |
| Oligo explorer program | GeneLink | For primer design | |
| Optical tube strip caps (8X Strip) | Agilent Technologies | 401425 | For real time PCR |
| Opti-MEM | Gibco | 31985-070 | 500 Ml |
| PANC-1 cells | ATCC | CRL-1469 | |
| Penicillin/streptomycin | Gibco | 15140-122 | 100 mL |
| Phosphate buffer saline | Gibco | 14040117 | 1000 mL |
| Plasmid DNA miniprep S& V kit | Bionics | DN10200 | 200 prep |
| PrimeSTAR GXL DNA polymerase | TaKaRa | R050A | 250 units |
| Shaker | TECAN | Shaking platform | |
| Shaking incubator | Labtech | Model: LSI-3016A | |
| Sigmaplot 14 software | Systat Software Inc | For dose-response curve generation | |
| Sulforhodamine B powder | Sigma | S1402-5G | 5 g |
| SYBR green master mix | Smobio | TQ12001805401-3 | Binding fluorescent dye for dsDNA |
| T4 DNA ligase | TaKaRa | 2011A | 25,000 U |
| TaqMan master mix | Applied Biosystems | 4324018 | 200 reactions, no AmpErase UNG |
| TaqMan microRNA assay (hsa-miR-107) | Applied Biosystems | 4427975 | Assay ID: 000443 (50RT, 150 PCR rxns) |
| TaqMan microRNA assay (hsa-miR-301) | Applied Biosystems | 4427975 | Assay ID: 000528 (50RT, 150 PCR rxns) |
| TaqMan miR RT kit | Applied Biosystems | 4366597 | 1000 reactions |
| Thermo CO2 incubator (BB15) | ThermoFisher Scientific | 37 °C and 5% CO2 incubation | |
| Trichloroacetic acid | Sigma | 91228-100G | 100 g |
| Trizma base | Sigma | T4661-100G | 100 g |
| Ultrapure water | Invitrogen | 10977-015 | 500 mL |
| Veriti 96 well thermal cycler | Applied Biosystems | For amplification of DNA (or cDNA) | |
| XhoI | New England Biolabs | R0146 | 20,000 units/mL |
References
- He, L., Hannon, G. J. MicroRNAs: small RNAs with a big role in gene regulation. Nature Reviews Genetics. 5 (7), 522-531 (2004).
- Park, J. K., Doseff, A. I., Schmittgen, T. D. MicroRNAs Targeting Caspase-3 and -7 in PANC-1 Cells. International Journal of Molecular Sciences. 19 (4), (2018).
- Park, J. K., et al. MicroRNAs-103/107 coordinately regulate macropinocytosis and autophagy. Journal of Cell Biology. 215 (5), 667-685 (2016).
- Henry, J. C., et al. miR-199a-3p targets CD44 and reduces proliferation of CD44 positive hepatocellular carcinoma cell lines. Biochemical and Biophysical Research Communications. 403 (1), 120-125 (2010).
- Hoefert, J. E., Bjerke, G. A., Wang, D., Yi, R. The microRNA-200 family coordinately regulates cell adhesion and proliferation in hair morphogenesis. Journal of Cell Biology. 217 (6), 2185-2204 (2018).
- Anfossi, S., Fu, X., Nagvekar, R., Calin, G. A. MicroRNAs, Regulatory Messengers Inside and Outside Cancer Cells. Advances in Experimental Medicine and Biology. 1056, 87-108 (2018).
- Khoshinani, H. M., et al. Involvement of miR-155/FOXO3a and miR-222/PTEN in acquired radioresistance of colorectal cancer cell line. Japanese Journal of Radiology. 35 (11), 664-672 (2017).
- Gao, Y., et al. MicroRNA-155 increases colon cancer chemoresistance to cisplatin by targeting forkhead box O3. Oncology Letters. 15 (4), 4781-4788 (2018).
- Catanzaro, G., et al. Loss of miR-107, miR-181c and miR-29a-3p Promote Activation of Notch2 Signaling in Pediatric High-Grade Gliomas (pHGGs). International Journal of Molecular Sciences. 18 (12), (2017).
- Akbari Moqadam, F., Pieters, R., den Boer, M. L. The hunting of targets: challenge in miRNA research. Leukemia. 27 (1), 16-23 (2013).
- Brown, R. A. M., et al. Total RNA extraction from tissues for microRNA and target gene expression analysis: not all kits are created equal. BMC Biotechnology. 18 (1), (2018).
- Kim, Y. K., Yeo, J., Kim, B., Ha, M., Kim, V. N. Short structured RNAs with low GC content are selectively lost during extraction from a small number of cells. Molecular Cell. 46 (6), 893-895 (2012).
- Schmittgen, T. D., Livak, K. J. Analyzing real-time PCR data by the comparative C(T) method. Nature Protocols. 3 (6), 1101-1108 (2008).
- Livak, K. J., Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 25 (4), 402-408 (2001).
- Park, J. K., Seo, J. S., Lee, S. K., Chan, K. K., Kuh, H. J. Combinatorial Antitumor Activity of Oxaliplatin with Epigenetic Modifying Agents, 5-Aza-CdR and FK228, in Human Gastric Cancer Cells. Biomolecules & Therapeutics. 26 (6), 591-598 (2018).
- Xia, X., et al. Downregulation of miR-301a-3p sensitizes pancreatic cancer cells to gemcitabine treatment via PTEN. American Journal of Translational Research. 9 (4), 1886-1895 (2017).
- Lee, K. H., et al. Epigenetic silencing of MicroRNA miR-107 regulates cyclin-dependent kinase 6 expression in pancreatic cancer. Pancreatology. 9 (3), 293-301 (2009).
- van Tonder, A., Joubert, A. M., Cromarty, A. D. Limitations of the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay when compared to three commonly used cell enumeration assays. BMC Research Notes. 8, 47 (2015).
- Wang, P., Henning, S. M., Heber, D. Limitations of MTT and MTS-based assays for measurement of antiproliferative activity of green tea polyphenols. PloS One. 5 (4), e10202 (2010).
- Wu, L., Belasco, J. G. Let me count the ways: mechanisms of gene regulation by miRNAs and siRNAs. Molecular Cell. 29 (1), 1-7 (2008).
- Jin, Y., Chen, Z., Liu, X., Zhou, X. Evaluating the microRNA targeting sites by luciferase reporter gene assay. Methods in Molecular Biology. , 117-127 (2013).
- Ma, Z., et al. Gamma-synuclein binds to AKT and promotes cancer cell survival and proliferation. Tumour Biology. 37 (11), 14999-15005 (2016).
- Pan, Z. Z., Bruening, W., Giasson, B. I., Lee, V. M., Godwin, A. K. Gamma-synuclein promotes cancer cell survival and inhibits stress- and chemotherapy drug-induced apoptosis by modulating MAPK pathways. Journal of Biological Chemistry. 277 (38), 35050-35060 (2002).
- Martinez-Sanchez, A., Murphy, C. L. MicroRNA Target Identification-Experimental Approaches. Biology (Basel). 2 (1), 189-205 (2013).
- Lee, E. J., et al. Expression profiling identifies microRNA signature in pancreatic cancer. International Journal of Cancer. 120 (5), 1046-1054 (2007).
- Nuovo, G. J., et al. A methodology for the combined in situ analyses of the precursor and mature forms of microRNAs and correlation with their putative targets. Nature Protocols. 4 (1), 107-115 (2009).
- Schmittgen, T. D., et al. Real-time PCR quantification of precursor and mature microRNA. Methods. 44 (1), 31-38 (2008).
- Diederichs, S., Haber, D. A. Dual role for argonautes in microRNA processing and posttranscriptional regulation of microRNA expression. Cell. 131 (6), 1097-1108 (2007).
- Orellana, E. A., Kasinski, A. L. Sulforhodamine B (SRB) Assay in Cell Culture to Investigate Cell Proliferation. Bio Protocol. 6 (21), (2016).
- Lawrie, C. H. MicroRNAs in hematological malignancies. Blood Reviews. 27 (3), 143-154 (2013).
- Quah, B. J., Warren, H. S., Parish, C. R. Monitoring lymphocyte proliferation in vitro and in vivo with the intracellular fluorescent dye carboxyfluorescein diacetate succinimidyl ester. Nature Protocols. 2 (9), 2049-2056 (2007).
- Xing, Z., Li, D., Yang, L., Xi, Y., Su, X. MicroRNAs and anticancer drugs. Acta Biochimica et Biophysica Sinica. 46 (3), 233-239 (2014).
- Moeng, S., et al. MicroRNA-107 Targets IKBKG and Sensitizes A549 Cells to Parthenolide. Anticancer Research. 38 (11), 6309-6316 (2018).
- Chou, T. C. Drug combination studies and their synergy quantification using the Chou-Talalay method. 癌症研究. 70 (2), 440-446 (2010).
- Flamand, M. N., Gan, H. H., Mayya, V. K., Gunsalus, K. C., Duchaine, T. F. A non-canonical site reveals the cooperative mechanisms of microRNA-mediated silencing. Nucleic Acids Research. 45 (12), 7212-7225 (2017).
