Long Read Sequencing of The CpG Island from The Promoter of O6-Methylguanine-DNA Methyltransferase Provides Insights into The Mechanism of De Novo Methylation Of G/C-Rich Regions

Background: The methylation of cytosine residues at CpG sites within the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a key biomarker in glioblastoma therapy. Single-molecule nanopore sequencing enables direct detection of methylation patterns across the genome. Our study investigates how potential G-quadruplex-forming sequences (PQS) in the MGMT promoter CpG island influence the activity of de novo DNA methyltransferase Dnmt3a and the accuracy of methylation pattern detection via nanopore sequencing. Methods: Nanopore sequencing was employed to analyze the methylation of 97 clinically significant CpG sites in the human MGMT promoter (MGMTp) using an in vitro de novo methylation system. Circular dichroism spectroscopy was used to identify G-quadruplex (G4) structures within the MGMTp CpG island. Interactions between the catalytic domain of Dnmt3a and the PQS from the MGMTp were examined by biolayer interferometry. Results: Guanine-rich DNA strands of the PQSs in the MGMTp were hypomethylated, while the complementary cytosine-rich strands were methylated by DNA methyltransferase Dnmt3a with higher efficiency. The accuracy of detecting modified bases in the PQS was significantly lower compared to surrounding sequences. Single-stranded guanine-rich DNA sequences from the MGMTp exhibited strong binding to Dnmt3a-CD, with an affinity approximately 10 times higher than their cytosine-rich complements (Kd = 3 × 10⁻⁸ M and 3 × 10⁻⁷ M, respectively). By binding to Dnmt3a, G4-forming oligonucleotides from MGMTp effectively inhibited the methylation reaction (IC50 6·10-7 M). Conclusions: The obtained data indicate the role of PQSs in establishing de novo the methylation of the MGMT promoter and highlight the challenges of sequencing guanine-rich regions using nanopore sequencing as well as impact of specific pattern of de novo methylation in the clinical data interpretation.