MeCP2: the chromatin connection and beyond

Of the recently discovered group of proteins that interpret DNA methylation signals by preferentially associating with methylated CpG dinucleotides, the methyl-CpG-binding protein 2 (MeCP2) has attracted considerable attention in view of its ability to repress transcription. The interest in MeCP2 dramatically increased following the discovery of mutated forms of the protein in patients with Rett syndrome, a neurodevelopmental disease. A connection with carcino-genesis has also been established. This review attempts to bring together and critically discuss recently acquired information about the molecular biology of the protein and its mechanism of action. A careful overview of the literature reveals the complexity of its activity, which goes well beyond the recognized chromatin connections. Finally, the newly established facts concerning the connection of MeCP2 to human disease are presented. Key words: methyl-CpG-binding proteins, MeCP2, transcription repression, chromatin modification, Rett syndrome, cancer.

Download Full-text

DNMT3A haploinsufficiency results in behavioral deficits and global epigenomic dysregulation shared across neurodevelopmental disorders

10.1101/2020.07.10.195859 ◽

2020 ◽

Author(s):

Diana L. Christian ◽

Dennis Y. Wu ◽

Jenna R. Martin ◽

J. Russell Moore ◽

Yiran R. Liu ◽

...

Keyword(s):

Dna Methylation ◽

Rett Syndrome ◽

Neurodevelopmental Disorders ◽

Dna Methyltransferase ◽

Behavioral Alterations ◽

Protein Activity ◽

Neurodevelopmental Disease ◽

Convergence Point ◽

Nervous System Function ◽

Syndrome Protein

SummaryMutations in DNA methyltransferase 3A (DNMT3A) have been detected in autism and related disorders, but how these mutations disrupt nervous system function is unknown. Here we define the effects of neurodevelopmental disease-associated DNMT3A mutations. We show that diverse mutations affect different aspects of protein activity yet lead to shared deficiencies in neuronal DNA methylation. Heterozygous DNMT3A knockout mice mimicking DNMT3A disruption in disease display growth and behavioral alterations consistent with human phenotypes. Strikingly, in these mice we detect global disruption of neuron-enriched non-CG DNA methylation, a binding site for the Rett syndrome protein MeCP2. Loss of this methylation leads to enhancer and gene dysregulation that overlaps with models of Rett syndrome and autism. These findings define effects of DNMT3A haploinsufficiency in the brain and uncover disruption of the non-CG methylation pathway as a convergence point across neurodevelopmental disorders.

Download Full-text

Faculty Opinions recommendation of Potential role of DNA methylation as a facilitator of target search processes for transcription factors through interplay with methyl-CpG-binding proteins.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.727592293.793537373 ◽

2017 ◽

Author(s):

Martha Bulyk ◽

Raluca Gordan

Keyword(s):

Dna Methylation ◽

Transcription Factors ◽

Binding Proteins ◽

Potential Role ◽

Target Search ◽

Search Processes

Download Full-text

DBP-PSSM: Combination of evolutionary profiles with the XGBoost algorithm to improve the identification of DNA-binding proteins

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323999201124203531 ◽

2020 ◽

Vol 23 ◽

Author(s):

Yanping Zhang ◽

Pengcheng Chen ◽

Ya Gao ◽

Jianwei Ni ◽

Xiaosheng Wang

Keyword(s):

Logistic Regression ◽

Protein Structure ◽

Dna Binding ◽

Molecular Biology ◽

Binding Proteins ◽

Protein Sequences ◽

Low Complexity ◽

Dna Binding Proteins ◽

Position Information ◽

Position Representation

Aim and Objective:: Given the rapidly increasing number of molecular biology data available, computational methods of low complexity are necessary to infer protein structure, function, and evolution. Method:: In the work, we proposed a novel mthod, FermatS, which based on the global position information and local position representation from the curve and normalized moments of inertia, respectively, to extract features information of protein sequences. Furthermore, we use the generated features by FermatS method to analyze the similarity/dissimilarity of nine ND5 proteins and establish the prediction model of DNA-binding proteins based on logistic regression with 5-fold crossvalidation. Results:: In the similarity/dissimilarity analysis of nine ND5 proteins, the results are consistent with evolutionary theory. Moreover, this method can effectively predict the DNA-binding proteins in realistic situations. Conclusion:: The findings demonstrate that the proposed method is effective for comparing, recognizing and predicting protein sequences. The main code and datasets can download from https://github.com/GaoYa1122/FermatS.

Download Full-text

Comparison of DNA Methylation Profiles of Hemostatic Genes between Liver Tissue and Peripheral Blood within Individuals

Thrombosis and Haemostasis ◽

10.1055/s-0040-1720980 ◽

2020 ◽

Author(s):

Annelie Angerfors ◽

Martina Olsson Lindvall ◽

Björn Andersson ◽

Staffan Nilsson ◽

Marcela Davila Lopez ◽

...

Keyword(s):

Dna Methylation ◽

Peripheral Blood ◽

Liver Tissue ◽

Association Studies ◽

Epidemiological Studies ◽

Methylation Pattern ◽

Cpg Dinucleotides ◽

Phenotypic Differences ◽

Targeted Bisulfite Sequencing ◽

Hemostatic Genes

AbstractDNA methylation has become increasingly recognized in the etiology of complex diseases, including thrombotic disorders. Blood is often collected in epidemiological studies for genotyping and has recently also been used to examine DNA methylation in epigenome-wide association studies. DNA methylation patterns are often tissue-specific, thus, peripheral blood may not accurately reflect the methylation pattern in the tissue of relevance. Here, we collected paired liver and blood samples concurrently from 27 individuals undergoing liver surgery. We performed targeted bisulfite sequencing for a set of 35 hemostatic genes primarily expressed in liver to analyze DNA methylation levels of >10,000 cytosine-phosphate-guanine (CpG) dinucleotides. We evaluated whether DNA methylation in blood could serve as a proxy for DNA methylation in liver at individual CpGs. Approximately 30% of CpGs were nonvariable and were predominantly hypo- (<25%) or hypermethylated (>70%) in both tissues. While blood can serve as a proxy for liver at these CpGs, the low variability renders these unlikely to explain phenotypic differences. We therefore focused on CpG sites with variable methylation levels in liver. The level of blood–liver tissue correlation varied widely across these variable CpGs; moderate correlations (0.5 ≤ r < 0.75) were detected for 6% and strong correlations (r ≥ 0.75) for a further 4%. Our findings indicate that it is essential to study the concordance of DNA methylation between blood and liver at individual CpGs. This paired blood–liver dataset is intended as a resource to aid interpretation of blood-based DNA methylation results.

Download Full-text

DNA Methylation in Solid Tumors: Functions and Methods of Detection

International Journal of Molecular Sciences ◽

10.3390/ijms22084247 ◽

2021 ◽

Vol 22 (8) ◽

pp. 4247

Author(s):

Andrea Martisova ◽

Jitka Holcakova ◽

Nasim Izadi ◽

Ravery Sebuyoya ◽

Roman Hrstka ◽

...

Keyword(s):

Dna Methylation ◽

Solid Tumors ◽

Epigenetic Modification ◽

Single Gene ◽

Restriction Enzymes ◽

Methylation Analysis ◽

Cpg Dinucleotides ◽

Sequencing Technologies ◽

Genome Level ◽

Dna Methylation Analysis

DNA methylation, i.e., addition of methyl group to 5′-carbon of cytosine residues in CpG dinucleotides, is an important epigenetic modification regulating gene expression, and thus implied in many cellular processes. Deregulation of DNA methylation is strongly associated with onset of various diseases, including cancer. Here, we review how DNA methylation affects carcinogenesis process and give examples of solid tumors where aberrant DNA methylation is often present. We explain principles of methods developed for DNA methylation analysis at both single gene and whole genome level, based on (i) sodium bisulfite conversion, (ii) methylation-sensitive restriction enzymes, and (iii) interactions of 5-methylcytosine (5mC) with methyl-binding proteins or antibodies against 5mC. In addition to standard methods, we describe recent advances in next generation sequencing technologies applied to DNA methylation analysis, as well as in development of biosensors that represent their cheaper and faster alternatives. Most importantly, we highlight not only advantages, but also disadvantages and challenges of each method.

Download Full-text

Genome-Wide DNA Methylation Pattern of Cancer Stem Cells in Esophageal Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033820983793 ◽

2020 ◽

Vol 19 ◽

pp. 153303382098379

Author(s):

Xiying Yu ◽

Ying Teng ◽

Xingran Jiang ◽

Hui Yuan ◽

Wei Jiang

Keyword(s):

Dna Methylation ◽

Stem Cells ◽

Esophageal Cancer ◽

Cancer Stem Cells ◽

Side Population ◽

Methylation Status ◽

Methylation Profile ◽

Cpg Dinucleotides ◽

Genome Wide ◽

Differentially Methylated Genes

Background: Cancer stem cells (CSCs) are considered the main cause of cancer recurrence and metastasis, and DNA methylation is involved in the maintenance of CSCs. However, the methylation profile of esophageal CSCs remains unknown. Methods: Side population (SP) cells were isolated from esophageal squamous cell carcinoma (ESCC) cell lines KYSE150 and EC109. Sphere-forming cells were collected from human primary esophageal cancer cells. SP cells and sphere-forming cells were used as substitutes for cancer stem-like cells. We investigated the genome-wide DNA methylation profile in esophageal cancer stem-like cells using reduced representation bisulfite sequencing (RRBS). Results: Methylated cytosine (mC) was found mostly in CpG dinucleotides, located mostly in the intronic, intergenic, and exonic regions. Forty intersected differentially methylated regions (DMRs) were identified in these 3 groups of samples. Thirteen differentially methylated genes with the same alteration trend were detected; these included OTX1, SPACA1, CD163L1, ST8SIA2, TECR, CADM3, GRM1, LRRK1, CHSY1, PROKR2, LINC00658, LOC100506688, and NKD2. DMRs covering ST8SIA2 and GRM1 were located in exons. These differentially methylated genes were involved in 10 categories of biological processes and 3 cell signaling pathways. Conclusions: When compared to non-CSCs, cancer stem-like cells have a differential methylation status, which provides an important biological base for understanding esophageal CSCs and developing therapeutic targets for esophageal cancer.

Download Full-text

Gene expression profiling of epigenetic chromatin modification enzymes and histone marks by cigarette smoke: implications for COPD and lung cancer

AJP Lung Cellular and Molecular Physiology ◽

10.1152/ajplung.00253.2016 ◽

2016 ◽

Vol 311 (6) ◽

pp. L1245-L1258 ◽

Cited By ~ 19

Author(s):

Isaac K. Sundar ◽

Irfan Rahman

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Dna Methylation ◽

Cigarette Smoke ◽

Histone Modifications ◽

Expression Patterns ◽

Chromatin Modification ◽

Gene Expression Patterns ◽

Validation Data ◽

Histone Marks

Chromatin-modifying enzymes mediate DNA methylation and histone modifications on recruitment to specific target gene loci in response to various stimuli. The key enzymes that regulate chromatin accessibility for maintenance of modifications in DNA and histones, and for modulation of gene expression patterns in response to cigarette smoke (CS), are not known. We hypothesize that CS exposure alters the gene expression patterns of chromatin-modifying enzymes, which then affects multiple downstream pathways involved in the response to CS. We have, therefore, analyzed chromatin-modifying enzyme profiles and validated by quantitative real-time PCR (qPCR). We also performed immunoblot analysis of targeted histone marks in C57BL/6J mice exposed to acute and subchronic CS, and of lungs from nonsmokers, smokers, and patients with chronic obstructive pulmonary disease (COPD). We found a significant increase in expression of several chromatin modification enzymes, including DNA methyltransferases, histone acetyltransferases, histone methyltransferases, and SET domain proteins, histone kinases, and ubiquitinases. Our qPCR validation data revealed a significant downregulation of Dnmt1, Dnmt3a, Dnmt3b, Hdac2, Hdac4, Hat1, Prmt1, and Aurkb. We identified targeted chromatin histone marks (H3K56ac and H4K12ac), which are induced by CS. Thus CS-induced genotoxic stress differentially affects the expression of epigenetic modulators that regulate transcription of target genes via DNA methylation and site-specific histone modifications. This may have implications in devising epigenetic-based therapies for COPD and lung cancer.

Download Full-text

DNA methylation marks inter-nucleosome linker regions throughout the human genome

10.7287/peerj.preprints.27 ◽

2013 ◽

Author(s):

Benjamin P. Berman ◽

Yaping Liu ◽

Theresa K. Kelly

Keyword(s):

Dna Methylation ◽

Human Genome ◽

Ctcf Binding ◽

Gene Promoters ◽

Cpg Dinucleotides ◽

Sequencing Technologies ◽

Nucleosome Organization ◽

Genome Wide ◽

A Genome ◽

Sequencing Studies

Background: Nucleosome organization and DNA methylation are two mechanisms that are important for proper control of mammalian transcription, as well as epigenetic dysregulation associated with cancer. Whole-genome DNA methylation sequencing studies have found that methylation levels in the human genome show periodicities of approximately 190 bp, suggesting a genome-wide relationship between the two marks. A recent report (Chodavarapu et al., 2010) attributed this to higher methylation levels of DNA within nucleosomes. Here, we analyzed a number of published datasets and found a more compelling alternative explanation, namely that methylation levels are highest in linker regions between nucleosomes. Results: Reanalyzing the data from (Chodavarapu et al., 2010), we found that nucleosome-associated methylation could be strongly confounded by known sequence-related biases of the next-generation sequencing technologies. By accounting for these biases and using an unrelated nucleosome profiling technology, NOMe-seq, we found that genome-wide methylation was actually highest within linker regions occurring between nucleosomes in multi-nucleosome arrays. This effect was consistent among several methylation datasets generated independently using two unrelated methylation assays. Linker-associated methylation was most prominent within long Partially Methylated Domains (PMDs) and the positioned nucleosomes that flank CTCF binding sites. CTCF adjacent nucleosomes retained the correct positioning in regions completely devoid of CpG dinucleotides, suggesting that DNA methylation is not required for proper nucleosomes positioning. Conclusions: The biological mechanisms responsible for DNA methylation patterns outside of gene promoters remain poorly understood. We identified a significant genome-wide relationship between nucleosome organization and DNA methylation, which can be used to more accurately analyze and understand the epigenetic changes that accompany cancer and other diseases.

Download Full-text