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Journal of Visualized Experiments : JoVE Jun 2012Epigenetics encompasses all heritable and reversible modifications to chromatin that alter gene accessibility, and thus are the primary mechanisms for regulating gene...
Epigenetics encompasses all heritable and reversible modifications to chromatin that alter gene accessibility, and thus are the primary mechanisms for regulating gene transcription. DNA methylation is an epigenetic modification that acts predominantly as a repressive mark. Through the covalent addition of a methyl group onto cytosines in CpG dinucleotides, it can recruit additional repressive proteins and histone modifications to initiate processes involved in condensing chromatin and silencing genes. DNA methylation is essential for normal development as it plays a critical role in developmental programming, cell differentiation, repression of retroviral elements, X-chromosome inactivation and genomic imprinting. One of the most powerful methods for DNA methylation analysis is bisulfite mutagenesis. Sodium bisulfite is a DNA mutagen that deaminates cytosines into uracils. Following PCR amplification and sequencing, these conversion events are detected as thymines. Methylated cytosines are protected from deamination and thus remain as cytosines, enabling identification of DNA methylation at the individual nucleotide level. Development of the bisulfite mutagenesis assay has advanced from those originally reported towards ones that are more sensitive and reproducible. One key advancement was embedding smaller amounts of DNA in an agarose bead, thereby protecting DNA from the harsh bisulfite treatment. This enabled methylation analysis to be performed on pools of oocytes and blastocyst-stage embryos. The most sophisticated bisulfite mutagenesis protocol to date is for individual blastocyst-stage embryos. However, since blastocysts have on average 64 cells (containing 120-720 pg of genomic DNA), this method is not efficacious for methylation studies on individual oocytes or cleavage-stage embryos. Taking clues from agarose embedding of minute DNA amounts including oocytes, here we present a method whereby oocytes are directly embedded in an agarose and lysis solution bead immediately following retrieval and removal of the zona pellucida from the oocyte. This enables us to bypass the two main challenges of single oocyte bisulfite mutagenesis: protecting a minute amount of DNA from degradation, and subsequent loss during the numerous protocol steps. Importantly, as data are obtained from single oocytes, the issue of PCR bias within pools is eliminated. Furthermore, inadvertent cumulus cell contamination is detectable by this method since any sample with more than one methylation pattern may be excluded from analysis. This protocol provides an improved method for successful and reproducible analyses of DNA methylation at the single-cell level and is ideally suited for individual oocytes as well as cleavage-stage embryos.
Topics: Animals; DNA Methylation; Female; Humans; Mice; Mutagenesis; Oocytes; Sepharose; Sulfites
PubMed: 22782232
DOI: 10.3791/4046 -
BMC Genomic Data Apr 2022Breast cancer is one of the most commonly diagnosed cancers. It is associated with DNA methylation, an epigenetic event with a methyl group added to a cytosine paired...
BACKGROUND
Breast cancer is one of the most commonly diagnosed cancers. It is associated with DNA methylation, an epigenetic event with a methyl group added to a cytosine paired with a guanine, i.e., a CG site. The methylation levels of different genes in a genome are correlated in certain ways that affect gene functions. This correlation pattern is known as co-methylation. It is still not clear how different genes co-methylate in the whole genome of breast cancer samples. Previous studies are conducted using relatively small datasets (Illumina 27K data). In this study, we analyze much larger datasets (Illumina 450K data).
RESULTS
Our key findings are summarized below. First, normal samples have more highly correlated, or co-methylated, CG pairs than tumor samples. Both tumor and normal samples have more than 93% positive co-methylation, but normal samples have significantly more negatively correlated CG sites than tumor samples (6.6% vs. 2.8%). Second, both tumor and normal samples have about 94% of co-methylated CG pairs on different chromosomes, but normal samples have 470 million more CG pairs. Highly co-methylated pairs on the same chromosome tend to be close to each other. Third, a small proportion of CG sites' co-methylation patterns change dramatically from normal to tumor. The percentage of differentially methylated (DM) sites among them is larger than the overall DM rate. Fourth, certain CG sites are highly correlated with many CG sites. The top 100 of such super-connector CG sites in tumor and normal samples have no overlaps. Fifth, both highly changing sites and super-connector sites' locations are significantly different from the genome-wide CG sites' locations. Sixth, chromosome X co-methylation patterns are very different from other chromosomes. Finally, the network analyses of genes associated with several sets of co-methylated CG sites identified above show that tumor and normal samples have different patterns.
CONCLUSIONS
Our findings will provide researchers with a new understanding of co-methylation patterns in breast cancer. Our ability to thoroughly analyze co-methylation of large datasets will allow researchers to study relationships and associations between different genes in breast cancer.
Topics: Breast Neoplasms; Cytosine; DNA Methylation; Epigenomics; Female; Humans
PubMed: 35428183
DOI: 10.1186/s12863-022-01046-w -
Molecular Microbiology Aug 2007Methylation is one of the most common protein modifications. Many different prokaryotic and eukaryotic proteins are methylated, including proteins involved in... (Review)
Review
Methylation is one of the most common protein modifications. Many different prokaryotic and eukaryotic proteins are methylated, including proteins involved in translation, including ribosomal proteins (RPs) and translation factors (TFs). Positions of the methylated residues in six Escherichia coli RPs and two Saccharomyces cerevisiae RPs have been determined. At least two RPs, L3 and L12, are methylated in both organisms. Both prokaryotic and eukaryotic elongation TFs (EF1A) are methylated at lysine residues, while both release factors are methylated at glutamine residues. The enzymes catalysing methylation reactions, protein methyltransferases (MTases), generally use S-adenosylmethionine as the methyl donor to add one to three methyl groups that, in case of arginine, can be asymetrically positioned. The biological significance of RP and TF methylation is poorly understood, and deletions of the MTase genes usually do not cause major phenotypes. Apparently methylation modulates intra- or intermolecular interactions of the target proteins or affects their affinity for RNA, and, thus, influences various cell processes, including transcriptional regulation, RNA processing, ribosome assembly, translation accuracy, protein nuclear trafficking and metabolism, and cellular signalling. Differential methylation of specific RPs and TFs in a number of organisms at different physiological states indicates that this modification may play a regulatory role.
Topics: Methylation; Methyltransferases; Protein Biosynthesis; Proteins; Ribosomal Proteins; Transcription Factors
PubMed: 17610498
DOI: 10.1111/j.1365-2958.2007.05831.x -
Epigenetics Dec 2023Pregnancy can exacerbate or prompt the onset of stress-related disorders, such as post-traumatic stress disorder (PTSD). PTSD is associated with heightened stress...
Pregnancy can exacerbate or prompt the onset of stress-related disorders, such as post-traumatic stress disorder (PTSD). PTSD is associated with heightened stress responsivity and emotional dysregulation, as well as increased risk of chronic disorders and mortality. Further, maternal PTSD is associated with gestational epigenetic age acceleration in newborns, implicating the prenatal period as a developmental time period for the transmission of effects across generations. Here, we evaluated the associations between PTSD symptoms, maternal epigenetic age acceleration, and infant gestational epigenetic age acceleration in 89 maternal-neonatal dyads. Trauma-related experiences and PTSD symptoms in mothers were assessed during the third trimester of pregnancy. The MethylationEPIC array was used to generate DNA methylation data from maternal and neonatal saliva samples collected within 24 h of infant birth. Maternal epigenetic age acceleration was calculated using Horvath's multi-tissue clock, PhenoAge and GrimAge. Gestational epigenetic age was estimated using the Haftorn clock. Maternal cumulative past-year stress (GrimAge: = 3.23e-04, PhenoAge: = 9.92e-03), PTSD symptoms (GrimAge: = 0.019), and difficulties in emotion regulation (GrimAge: = 0.028) were associated with accelerated epigenetic age in mothers. Maternal PTSD symptoms were associated with lower gestational epigenetic age acceleration in neonates ( = 0.032). Overall, our results suggest that maternal cumulative past-year stress exposure and trauma-related symptoms may increase the risk for age-related problems in mothers and developmental problems in their newborns.
Topics: Female; Humans; Infant, Newborn; Pregnancy; Acceleration; DNA Methylation; Emotions; Epigenesis, Genetic; Hispanic or Latino; Mothers; Stress Disorders, Post-Traumatic; Aging
PubMed: 37433036
DOI: 10.1080/15592294.2023.2231722 -
JAMA Network Open Apr 2023The Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE) measure is a newly constructed DNA methylation (DNAm) biomarker associated with morbidity,...
IMPORTANCE
The Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE) measure is a newly constructed DNA methylation (DNAm) biomarker associated with morbidity, mortality, and adverse childhood experiences in several cohorts with European ancestry. However, there are few studies of the DunedinPACE measure among socioeconomically and racially diverse cohorts with longitudinal assessments.
OBJECTIVE
To investigate the association of race and poverty status with DunedinPACE scores in a socioeconomically diverse middle-aged cohort of African American and White participants.
DESIGN, SETTING, AND PARTICIPANTS
This longitudinal cohort study used data from the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS) study. HANDLS is a population-based study of socioeconomically diverse African American and White adults aged 30 to 64 years at baseline in Baltimore, Maryland, with follow-up approximately every 5 years. The current study was restricted to 470 participants with blood samples at 2 time points: August 14, 2004, to June 22, 2009 (visit 1), and June 23, 2009, to September 12, 2017 (visit 2). Genome-wide DNAm was assessed at visit 1 (chronological age, 30-64 years) and visit 2. Data were analyzed from March 18, 2022, to February 9, 2023.
MAIN OUTCOMES AND MEASURES
DunedinPACE scores were estimated for each participant at 2 visits. DunedinPACE scores are values scaled to a mean of 1, interpretable with reference to a rate of 1 year of biological aging per 1 year of chronological aging. Linear mixed-model regression analysis was used to examine the trajectories of DunedinPACE scores by chronological age, race, sex, and poverty status.
RESULTS
Among 470 participants, the mean (SD) chronological age at visit 1 was 48.7 (8.7) years. Participants were balanced by sex (238 [50.6%] were men and 232 [49.4%] were women), race (237 [50.4%] African American and 233 [49.6%] White), and poverty status (236 [50.2%] living below poverty level and 234 [49.8%] living above poverty level). The mean (SD) time between visits was 5.1 (1.5) years. Overall, the mean (SD) DunedinPACE score was 1.07 (0.14), representing a 7% faster pace of biological aging than chronological aging. Linear mixed-effects regression analysis revealed an association between the 2-way interaction between race and poverty status (White race and household income below poverty level: β = 0.0665; 95% CI, 0.0298-0.1031; P < .001) and significantly higher DunedinPACE scores and an association between quadratic age (age squared: β = -0.0113; 95% CI, -0.0212 to -0.0013; P = .03) and significantly higher DunedinPACE scores.
CONCLUSIONS AND RELEVANCE
In this cohort study, household income below poverty level and African American race were associated with higher DunedinPACE scores. These findings suggest that the DunedinPACE biomarker varies with race and poverty status as adverse social determinants of health. Consequently, measures of accelerated aging should be based on representative samples.
Topics: Middle Aged; Adult; Male; Humans; Female; DNA Methylation; Longitudinal Studies; Cohort Studies; Poverty; Biomarkers; White
PubMed: 37027157
DOI: 10.1001/jamanetworkopen.2023.6340 -
International Journal of Molecular... Feb 2024Lysine methylation is a major post-translational protein modification that occurs in both histones and non-histone proteins. Emerging studies show that the methylated... (Review)
Review
Lysine methylation is a major post-translational protein modification that occurs in both histones and non-histone proteins. Emerging studies show that the methylated lysine residues in non-histone proteins provide a proteolytic signal for ubiquitin-dependent proteolysis. The SET7 (SETD7) methyltransferase specifically transfers a methyl group from S-Adenosyl methionine to a specific lysine residue located in a methylation degron motif of a protein substrate to mark the methylated protein for ubiquitin-dependent proteolysis. LSD1 (Kdm1a) serves as a demethylase to dynamically remove the methyl group from the modified protein. The methylated lysine residue is specifically recognized by L3MBTL3, a methyl-lysine reader that contains the malignant brain tumor domain, to target the methylated proteins for proteolysis by the CRL4 ubiquitin ligase complex. The methylated lysine residues are also recognized by PHF20L1 to protect the methylated proteins from proteolysis. The lysine methylation-mediated proteolysis regulates embryonic development, maintains pluripotency and self-renewal of embryonic stem cells and other stem cells such as neural stem cells and hematopoietic stem cells, and controls other biological processes. Dysregulation of the lysine methylation-dependent proteolysis is associated with various diseases, including cancers. Characterization of lysine methylation should reveal novel insights into how development and related diseases are regulated.
Topics: Humans; Proteolysis; Lysine; Methylation; Protein Processing, Post-Translational; Histones; Brain Neoplasms; Ubiquitins; Histone-Lysine N-Methyltransferase; Chromosomal Proteins, Non-Histone
PubMed: 38396925
DOI: 10.3390/ijms25042248 -
ACS Chemical Biology Jul 2020The methylation of amide nitrogen atoms can improve the stability, oral availability, and cell permeability of peptide therapeutics. Chemical -methylation of peptides is...
The methylation of amide nitrogen atoms can improve the stability, oral availability, and cell permeability of peptide therapeutics. Chemical -methylation of peptides is challenging. Omphalotin A is a ribosomally synthesized, macrocylic dodecapeptide with nine backbone -methylations. The fungal natural product is derived from the precursor protein, OphMA, harboring both the core peptide and a SAM-dependent peptide α--methyltransferase domain. OphMA forms a homodimer and its α--methyltransferase domain installs the methyl groups on the hydrophobic core dodecapeptide and some additional C-terminal residues of the protomers. These post-translational backbone -methylations occur in a processive manner from the N- to the C-terminus of the peptide substrate. We demonstrate that OphMA can methylate polar, aromatic, and charged residues when these are introduced into the core peptide. Some of these amino acids alter the efficiency and pattern of methylation. Proline, depending on its sequence context, can act as a tunable stop signal. Crystal structures of OphMA variants have allowed rationalization of these observations. Our results hint at the potential to control this fungal α--methyltransferase for biotechnological applications.
Topics: Agaricales; Amino Acid Sequence; Fungal Proteins; Methylation; Methyltransferases; Mutation; Peptides, Cyclic; Protein Domains; Protein Precursors; Protein Processing, Post-Translational; Substrate Specificity
PubMed: 32491837
DOI: 10.1021/acschembio.0c00237 -
FEBS Open Bio Dec 2020Hashimoto's thyroiditis (HT) during pregnancy is usually accompanied by an elevation of thyroid-stimulating hormone and a reduction of serum-free thyroxine during...
Hashimoto's thyroiditis (HT) during pregnancy is usually accompanied by an elevation of thyroid-stimulating hormone and a reduction of serum-free thyroxine during gestation, which may lead to abortion, preterm delivery, and reduced intellectual function of the offspring. Epigenetic alterations may provide important insights into genetic-environmental interactions in HT. Here, we examined global DNA methylation patterns in patients with HT during pregnancy. DNA was extracted from 13 women with HT during pregnancy (HTDP) and eight healthy pregnant women as a control group. Genome-wide methylation was detected with the use of an Illumina Human Methylation 850K Beadchip. A total of 652 differentially methylated positions (DMPs) and 27 differentially methylated regions (DMRs) were identified between the HTDP and control groups. GO analysis revealed that DMPs were significantly enriched in 540 GO terms, which included regulation of the differentiation of keratinocytes, T helper cell differentiation, and alpha-beta T-cell differentiation. Moreover, significant enrichment of KEGG pathways of the DMPs included mucin-type O-glycan biosynthesis, focal adhesion, and the insulin signaling pathway. The GO items associated with DMRs included muscle cell proliferation, response to biotic stimulus, anatomical structure formation involved in morphogenesis, and genes primarily involved in the FoxO signaling pathway. Finally, the DTNA gene was identified as the seed gene of functional epigenetic modules. In summary, the DNA methylation pattern of the HTDP group was distinct from that of the control group, and thus, changes in DNA methylation may influence the development of HT by regulation of the autoimmunity process.
Topics: DNA Methylation; Female; Hashimoto Disease; Humans; Oligonucleotide Array Sequence Analysis; Pregnancy
PubMed: 33113271
DOI: 10.1002/2211-5463.13018 -
Frontiers in Endocrinology 2022Gestational diabetes mellitus (GDM) "program" an elevated risk of metabolic syndrome in the offspring. Epigenetic alterations are a suspected mechanism. GDM has been...
Gestational diabetes mellitus (GDM) "program" an elevated risk of metabolic syndrome in the offspring. Epigenetic alterations are a suspected mechanism. GDM has been associated with placental DNA methylation changes in some epigenome-wide association studies. It remains unclear which genes or pathways are affected, and whether any placental differential gene methylations are correlated to fetal growth or circulating metabolic health biomarkers. In an epigenome-wide association study using the Infinium MethylationEPIC Beadchip, we sought to identify genome-wide placental differentially methylated genes and enriched pathways in GDM, and to assess the correlations with fetal growth and metabolic health biomarkers in cord blood. The study samples were 30 pairs of term placentas in GDM vs. euglycemic pregnancies (controls) matched by infant sex and gestational age at delivery in the Shanghai Birth Cohort. Cord blood metabolic health biomarkers included insulin, C-peptide, proinsulin, IGF-I, IGF-II, leptin and adiponectin. Adjusting for maternal age, pre-pregnancy BMI, parity, mode of delivery and placental cell type heterogeneity, 256 differentially methylated positions (DMPs,130 hypermethylated and 126 hypomethylated) were detected between GDM and control groups accounting for multiple tests with false discovery rate <0.05 and beta-value difference >0.05. WSCD2 was identified as a differentially methylated gene in both site- and region-level analyses. We validated 7 hypermethylated (CYP1A2, GFRA1, HDAC4, LIMS2, NAV3, PAX6, UPK1B) and 10 hypomethylated (DPP10, CPLX1, CSMD2, GPR133, NRXN1, PCSK9, PENK, PRDM16, PTPRN2, TNXB) genes reported in previous epigenome-wide association studies. We did not find any enriched pathway accounting for multiple tests. DMPs in 11 genes (CYP2D7P1, PCDHB15, ERG, SIRPB1, DKK2, RAPGEF5, CACNA2D4, PCSK9, TSNARE1, CADM2, KCNAB2) were correlated with birth weight (z score) accounting for multiple tests. There were no significant correlations between placental gene methylations and cord blood biomarkers. In conclusions, GDM was associated with DNA methylation changes in a number of placental genes, but these placental gene methylations were uncorrelated to the observed metabolic health biomarkers (fetal growth factors, leptin and adiponectin) in cord blood. We validated 17 differentially methylated placental genes in GDM, and identified 11 differentially methylated genes relevant to fetal growth.
Topics: Adiponectin; Biomarkers; China; DNA Methylation; Diabetes, Gestational; Female; Fetal Blood; Fetal Development; Humans; Infant; Leptin; Parity; Placenta; Pregnancy; Proprotein Convertase 9
PubMed: 35721735
DOI: 10.3389/fendo.2022.875180 -
Clinical Epigenetics Oct 2021
Topics: DNA Methylation; Disease Susceptibility; Ethnicity; Humans
PubMed: 34635160
DOI: 10.1186/s13148-021-01180-9