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Region of interest methylation analysis: a comparison of MSP with MS-HRM and direct BSP

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Abstract

The aim of this study was to compare and contrast three DNA methylation methods of a specific region of interest (ROI): methylation-specific PCR (MSP), methylation-sensitive high resolution melting (MS-HRM) and direct bisulfite sequencing (BSP). The methylation of a CpG area in the promoter region of Estrogen receptor alpha (ESR1) was evaluated by these three methods with samples and standards of different methylation percentages. MSP data were neither reproducible nor sensitive, and the assay was not specific due to non-specific binding of primers. MS-HRM was highly reproducible and a step forward into categorizing the methylation status of the samples as percent ranges. Direct BSP was the most informative method regarding methylation percentage of each CpG site. Though not perfect, it was reproducible and sensitive. We recommend the use of either method depending on the research question and target amplicon, and provided that the designed primers and expected amplicons are within recommendations. If the research question targets a limited number of CpG sites and simple yes/no results are enough, MSP may be attempted. For short amplicons that are crowded with CpG sites and of single melting domain, MS-HRM may be the method of choice though it only indicates the overall methylation percentage of the entire amplicon. Although the assay is highly reproducible, being semi-quantitative makes it of lesser interest to study ROI methylation of samples with little methylation differences. Direct BSP is a step forward as it gives information about the methylation percentage at each CpG site.

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References

  1. Romagnolo DF, Daniels KD, Grunwald JT, Ramos SA, Propper CR, Selmin OI (2016) Epigenetics of breast cancer: modifying role of environmental and bioactive food compounds. Mol Nutr Food Res 60(6):1310–1329

    Article  CAS  PubMed  Google Scholar 

  2. Ushijima T, Herceg Z (2014) Epigenetics. In: Stewart BW, Wild CP (eds) World Cancer Reports 2014. International Agency for Research on Cancer, Lyon, pp 214–221

    Google Scholar 

  3. Hernandez HG, Tse MY, Pang SC, Arboleda H, Forero DA (2013) Optimizing methodologies for PCR-based DNA methylation analysis. Biotechniques 55(4):181–197

    Article  CAS  PubMed  Google Scholar 

  4. Esteller M (2007) Cancer epigenomics: DNA methylomes and histone-modification maps. Nat Rev Genet 8(4):286–298

    Article  CAS  PubMed  Google Scholar 

  5. Fukushige S, Horii A (2013) DNA methylation in cancer: a gene silencing mechanism and the clinical potential of its biomarkers. Tohoku J Exp Med 229(3):173–185

    Article  CAS  PubMed  Google Scholar 

  6. Bhattacharjee D, Shenoy S, Bairy KL (2016) DNA Methylation and chromatin remodeling: the blueprint of cancer epigenetics. Scientifica 2016:6072357

    Article  PubMed  PubMed Central  Google Scholar 

  7. Khanam IA, Kodamullil AT, Gundel M, Hofmann-Apitius M (2015) Computational modelling approaches on epigenetic factors in neurodegenerative and autoimmune diseases and their mechanistic analysis. J Immunol Res 2015:737168

    Google Scholar 

  8. Zhang BK, Lai X, Jia SJ (2015) Epigenetics in atherosclerosis: a clinical perspective. Discov Med 19(103):73–80

    PubMed  Google Scholar 

  9. Vecchio L, Seke Etet PF, Kipanyula MJ, Krampera M, Nwabo Kamdje AH (2013) Importance of epigenetic changes in cancer etiology, pathogenesis, clinical profiling, and treatment: what can be learned from hematologic malignancies? Biochim Biophys Acta 1836(1):90–104

    CAS  PubMed  Google Scholar 

  10. Zhang Y, Jeltsch A (2010) The application of next generation sequencing in DNA methylation analysis. Genes 1(1):85–101

    Article  PubMed  PubMed Central  Google Scholar 

  11. Licchesi JD, Herman JG (2009) Methylation-specific PCR. Methods Mol Biol 507:305–323

    Article  CAS  PubMed  Google Scholar 

  12. Wong EM, Dobrovic A (2011) Assessing gene-specific methylation using HRM-based analysis. Methods Mol Biol 687:207–217

    Article  CAS  PubMed  Google Scholar 

  13. Umer M, Herceg Z (2013) Deciphering the epigenetic code: an overview of DNA methylation analysis methods. Antioxid Redox Signal 18(15):1972–1986

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lapidus RG, Nass SJ, Butash KA, Parl FF, Weitzman SA, Graff JG et al (1998) Mapping of ER gene CpG island methylation-specific polymerase chain reaction. Cancer Res 58(12):2515–2519

    CAS  PubMed  Google Scholar 

  15. Wojdacz TK, Dobrovic A, Hansen LL (2008) Methylation-sensitive high-resolution melting. Nat Protoc 3(12):1903–1908

    Article  CAS  PubMed  Google Scholar 

  16. Slatko BE, Albright LM, Tabor S, Ju J (2011) DNA sequencing by the dideoxy method. Curr Protoc Mol Biol. doi:10.1002/0471142727.mb0704as47

  17. Jiang M, Zhang Y, Fei J, Chang X, Fan W, Qian X et al (2010) Rapid quantification of DNA methylation by measuring relative peak heights in direct bisulfite-PCR sequencing traces. Lab Invest 90(2):282–290

    Article  CAS  PubMed  Google Scholar 

  18. Lorente A, Mueller W, Urdangarin E, Lazcoz P, von DA, Castresana JS (2008) Detection of methylation in promoter sequences by melting curve analysis-based semiquantitative real time PCR. BMC Cancer 8:61

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hattermann K, Mehdorn HM, Mentlein R, Schultka S, Held-Feindt J. (2008) A methylation-specific and SYBR-green-based quantitative polymerase chain reaction technique for O6-methylguanine DNA methyltransferase promoter methylation analysis. Anal Biochem 377(1):62–71

    Article  CAS  PubMed  Google Scholar 

  20. Candiloro IL, Mikeska T, Hokland P, Dobrovic A (2008) Rapid analysis of heterogeneously methylated DNA using digital methylation-sensitive high resolution melting: application to the CDKN2B (p15) gene. Epigenetics Chromatin 1(1):7

    Article  PubMed  PubMed Central  Google Scholar 

  21. Abtahi H, Sadeghi MR, Shabani M, Edalatkhah H, Hadavi R, Akhondi MM et al (2011) Causes of bimodal melting curve: assymetric guanine-cytosine (GC) distribution causing two peaks in melting curve and affecting their shapes. Afr J Biotechnol 10(50):10196–10203

    Article  CAS  Google Scholar 

  22. Sant KE, Nahar MS, Dolinoy DC (2012) DNA methylation screening and analysis. Methods Mol Biol 889:385–406

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

American University of Beirut Faculty of Medicine (AUBFM) Medical Practice Plan (MPP) fund and AUBFM Core facilities.

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Correspondence to Nathalie K. Zgheib.

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Akika, R., Awada, Z., Mogharbil, N. et al. Region of interest methylation analysis: a comparison of MSP with MS-HRM and direct BSP. Mol Biol Rep 44, 295–305 (2017). https://doi.org/10.1007/s11033-017-4110-7

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  • DOI: https://doi.org/10.1007/s11033-017-4110-7

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