Development and characterization of the method for multilocus methylation sensitive real-time PCR

Background. The method of multiplex methylation sensitive quantitative real-time PCR (MS-qPCR) is used for the first time in the format of a multiplex system with TaqMan probes. The previously described approaches to MSRE-qPCR are insufficient for the implementation of the technique in studies of large samples of patients, which is due to the lack of a multiplex reaction format and internal controls. We propose an MS-qPCR method with the possibility of multiplexing and the presence of internal PCR controls. Aim: to characterize the analytical properties of the developed multiplex MS-qPCR method. Methods. DNA from lymphocytes from healthy donors was used as a material for the study. We have postulated that DNA undigested with methylation sensitive restriction enzyme is a model methylated template (undigested), while hydrolyzed DNA is a model unmethylated template. To determine the analytical sensitivity, mixtures of digested and undigested DNA were used. Development of the MS-qPCR panel was carried out taking into account the design requirements developed by the team: the inclusion of a positive internal control of the PCR efficiency and a control of digestion of genomic DNA by the methylation sensitive restriction enzyme. For the kinetic curves of the studied loci in all samples, Cy0 values were obtained using the qPCR package of the R programming language, and on the basis of these data, methylation levels were calculated, and box plots were presented. The analytical sensitivity of the method was determined by finding the Limit of Blank (LoB) and Limit of Detection (LoD) values. Results. The coefficient of determination (R2) for the normally non-methylated locus is 0.98, and for the locus with normal monoallelic methylation, 0.77. Analytical sensitivity of the MS-qPCR method is 5%; the relative error was 11.38%. Conclusions. Based on the results obtained, the analytical sensitivity of the MS-qPCR method is higher than that of the direct Sanger bisulfite sequencing, and comparable to bisulfite pyrosequencing. The use of TaqMan probes allows multiplexing of several target loci in one reaction, which is a fine solution to the problem of a small amount of available biological material.

quantitative PCR, DNA methylation, multiplex PCR, methylation sensitive restriction enzymes

1. Beikircher G., Pulverer W., Hofner M., et al. Multiplexed and sensitive DNA methylation testing using methylation-sensitive restriction enzymes “MSRE-qPCR”. Methods Mol Biol. 2018; 1708: 407-424. doi: 10.1007/978-1-4939-7481-8_21.

2. Radhakrishnan R., Kabekkodu S., Satyamoorthy K. DNA hypermethylation as an epigenetic mark for oral cancer diagnosis. Journal of Oral Pathology and Medicine 2011; 40(9): 665-676.

3. Kulis M., Esteller M. DNA Methylation and Cancer. Advances in Genetics 2010; 70: 27-56. doi: 10.1016/B978-0-12-380866-0.60002-2.

4. Yoo C.B., Jones P.A. Epigenetic therapy of cancer: past, present and future. Nat Rev Drug Discov. 2006; 5(1): 37-50.

5. Esteller M. Epigenetics in Cancer. NEJM 2008; 358(11): 1148-1159.

6. Tanaka K., Okamoto A. Degradation of DNA by bisulfite treatment. Bioorg Med Chem Lett. 2007 Apr 1; 17(7): 1912-5. doi: 10.1016/j.bmcl.2007.01.040.

7. Raizis A.M., Schmitt F., Jost J.P. A Bisulfite Method of 5-Methylcytosine Mapping That Minimizes Template Degradation. Anal Biochem. 1995; 226(1): 161-166.

8. Grunau C., Clark S.J., Rosenthal A. Bisulfite genomic sequencing: systematic investigation of critical experimental parameters. Nucleic Acids Res. 2001; 29(13): E65-5. doi: 10.1093/nar/29.13.e65.

9. Amenya H.Z., Tohyama C., Ohsako S. Dioxin induces Ahr-dependent robust DNA demethylation of the Cyp1a1 promoter via Tdg in the mouse liver. Sci Rep. 2016; 6: 34989. doi: 10.1038/srep34989.

10. Krygier M., Podolak-Popinigis, Limon J., et al. A simple modification to improve the accuracy of methylation-sensitive restriction enzyme quantitative polymerase chain reaction. Anal Biochem. 2016; 500: 88-90. doi: 10.1016/j.ab.2016.01.020.

11. Umer M., Herceg Z. Deciphering the epigenetic code: An overview of DNA methylation analysis methods. Antioxid Redox Signal. 2013; 18(15): 1972-86. doi: 10.1089/ars.2012.4923.

12. Pajares M.J., Palanca-Ballester C., Urtasun R., et al. Methods for analysis of specific DNA methylation status. Methods 2021; 187: 3-12. doi: 10.1016/j.ymeth.2020.06.021.

13. Dahl C., Guldberg P. DNA methylation analysis techniques. Biogerontology 2003; 4(4): 233-50. doi: 10.1023/a:1025103319328.

14. Lekanne Deprez R.H., Fijnvandraat A.C., Ruijter J.M., et al. Sensitivity and accuracy of quantitative real-time polymerase chain reaction using SYBR green I depends on cDNA synthesis conditions. Anal Biochem. 2002; 307(1): 63-69.

15. Huggett J.F., Cowen S., Foy C.A. Considerations for digital PCR as an accurate molecular diagnostic tool. Clin Chem. 2015; 61(1): 79-88.

16. Thomassin H., Kress C., Grange T. MethylQuant: a sensitive method for quantifying methylation of specific cytosines within the genome. Nucleic Acids Res. 2004; 32(21): e168. doi: 10.1093/nar/gnh166.

17. Köchl S., Niederstätter H., Parson W. DNA extraction and quantitation of forensic samples using the phenol-chloroform method and real-time PCR. Methods Mol Biol. 2005; 297: 13-30.

18. Tolstrup N., Nielsen P.S., Kolberg J.G., et al. OligoDesign: optimal design of LNA (locked nucleic acid) oligonucleotide capture probes for gene expression profiling. Nucleic Acids Res. 2003; 31(13): 3758-62. doi: 10.1093/nar/gkg580.

19. Mouritzen P., Nielsen A.T., Pfundheller H.M., et al. Single nucleotide polymorphism genotyping using locked nucleic acid (LNATM). Expert Rev Mol Diagn. 2003; 3(1): 27-38.

20. Guescini M., Sisti D., Rocchi M.B.L., et al. Accurate and Precise DNA Quantification in the Presence of Different Amplification Efficiencies Using an Improved Cy0 Method. PLoS One 2013; 8(7): e68481. doi: 10.1371/journal.pone.0068481.

21. Armbruster D.A., Pry T. Limit of blank, limit of detection and limit of quantitation. Clin Biochem Rev. 2008; 29 Suppl 1(Suppl 1): S49-52.

22. Ucar I., Pebesma E., Azcorra A. Measurement Errors in R. The R Journal. 2019; 10(2): 549-557.

23. Lebrón R., Gómez-Martín С., Carpena P., et al. NGSmethDB 2017: enhanced methylomes and differential methylation. Nucleic Acids Res. 2017; 45(D1): D97-D103.

24. Lewin J., Schmitt A.O., Adorján P., et al. Quantitative DNA methylation analysis based on four-dye trace data from direct sequencing of PCR amplificates. Bioinformatics 2004; 20(17): 3005-12. doi: 10.1093/bioinformatics/bth346.

25. Kurdyukov S, Bullock M. DNA methylation analysis: Choosing the right method. Biology (Basel) 2016; 5(1): 3. doi: 10.3390/biology5010003.