Reduced Bisulfite Sequencing: Quantitative Base-Resolution Sequencing of 5-Formylcytosine

Correlation of ChREBP Gene Methylation with Pathological Characteristics of Type 2 Diabetes Mellitus

The objective of this study is to investigate the expression of the carbohydrate response element binding protein (ChREBP) gene in type 2 diabetes mellitus (T2DM) and its correlation with pathological features. For obtaining and exploring the pathological features in patients, sixty T2DM patients (the research group) and thirty healthy controls (the control group) presented to our hospital between January 2019 and June 2019 were selected as the research participants. After DNA extraction from peripheral blood mononuclear cells (PBMCs) and modification of target gene methylation with bisulfite, differences in methylation were verified, and the correlation of ChREBP methylation level with T2DM pathological features and single nucleotide polymorphism (SNP) typing was discussed. According to the prediction results of UCSC Genome Browser Home, there were two CpG islands in the promoter region of the ChREBP gene, and the first exon was selected for research. The ChREBP methylation rate was statistically higher in the research group versus the control group (P < 0.05). Age, FPG, TC, and TG were confirmed by the multiple linear regression analysis to be correlated with the ChREBP methylation rate (P < 0.05). Finally, there was no difference in ChREBP methylation level between CT- and CC-type patients at rs17145750 and rs1051921 loci (P > 0.05). Peripheral blood ChREBP methylation is elevated in T2DM patients and is closely related to age, blood glucose, and blood-lipid level, which is expected to be a new direction for future T2DM diagnosis and treatment.

Reconstruction of cell-specific models capturing the influence of metabolism on DNA methylation in cancer

The imbalance of epigenetic regulatory mechanisms such as DNA methylation, which can promote aberrant gene expression profiles without affecting the DNA sequence, may cause the deregulation of signaling, regulatory, and metabolic processes, contributing to a cancerous phenotype. Since some metabolites are substrates and cofactors of epigenetic regulators, their availability can be affected by characteristic cancer cell metabolic shifts, feeding cancer onset and progression through epigenetic deregulation. Hence, there is a need to study the influence of cancer metabolic reprogramming in DNA methylation to design new effective treatments. In this study, a generic Genome-Scale Metabolic Model (GSMM) of a human cell, integrating DNA methylation or demethylation reactions, was obtained and used for the reconstruction of Genome-Scale Metabolic Models enhanced with Enzymatic Constraints using Kinetic and Omics data (GECKOs) of 31 cancer cell lines. Furthermore, cell-line-specific DNA methylation levels were included in the models, as coefficients of a DNA composition pseudo-reaction, to depict the influence of metabolism over global DNA methylation in each of the cancer cell lines. Flux simulations demonstrated the ability of these models to provide simulated fluxes of exchange reactions similar to the equivalent experimentally measured uptake/secretion rates and to make good functional predictions. In addition, simulations found metabolic pathways, reactions and enzymes directly or inversely associated with the gene promoter methylation. Two potential candidates for targeted cancer epigenetic therapy were identified.