DNA methylation is stable during replication and cell cycle arrest

Order-of-Mutation Effects on Cancer Progression: Models for Myeloproliferative Neoplasm

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found: JAK2 V617F and one in the TET2 gene. Whether one mutation is present influences how the other subsequent mutation will affect the regulation of gene expression. In other words, when a patient carries both mutations, the order of when they first arose has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation, the Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. Combined, these observations are used to shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.

Deregulated transcription factors in the emerging cancer hallmarks

Cancer progression is a multifaceted process that entails several stages and demands the persistent expression or activation of transcription factors (TFs) to facilitate growth and survival. TFs are a cluster of proteins with DNA-binding domains that attach to promoter or enhancer DNA strands to start the transcription of genes by collaborating with RNA polymerase and other supporting proteins. They are generally acknowledged as the major regulatory molecules that coordinate biological homeostasis and the appropriate functioning of cellular components, subsequently contributing to human physiology. TFs proteins are crucial for controlling transcription during the embryonic stage and development, and the stability of different cell types depends on how they function in different cell types. The development and progression of cancer cells and tumors might be triggered by any anomaly in transcription factor function. It has long been acknowledged that cancer development is accompanied by the dysregulated activity of TF alterations which might result in faulty gene expression. Recent studies have suggested that dysregulated transcription factors play a major role in developing various human malignancies by altering and rewiring metabolic processes, modifying the immune response, and triggering oncogenic signaling cascades. This review emphasizes the interplay between TFs involved in metabolic and epigenetic reprogramming, evading immune attacks, cellular senescence, and the maintenance of cancer stemness in cancerous cells. The insights presented herein will facilitate the development of innovative therapeutic modalities to tackle the dysregulated transcription factors underlying cancer.

Assessment of aberrant DNA methylation two years after paediatric critical illness: a pre-planned secondary analysis of the international PEPaNIC trial

Critically ill children requiring intensive care suffer from impaired physical/neurocognitive development 2 y later, partially preventable by omitting early use of parenteral nutrition (early-PN) in the paediatric intensive-care-unit (PICU). Altered methylation of DNA from peripheral blood during PICU-stay provided a molecular basis hereof. Whether DNA-methylation of former PICU patients, assessed 2 y after critical illness, is different from that of healthy children remained unknown. In a pre-planned secondary analysis of the PEPaNIC-RCT (clinicaltrials.gov-NCT01536275) 2-year follow-up, we assessed buccal-mucosal DNA-methylation (Infinium-HumanMethylation-EPIC-BeadChip) of former PICU-patients (N = 406 early-PN; N = 414 late-PN) and matched healthy children (N = 392). CpG-sites differentially methylated between groups were identified with multivariable linear regression and differentially methylated DNA-regions via clustering of differentially methylated CpG-sites using kernel-estimates. Analyses were adjusted for technical variation and baseline risk factors, and corrected for multiple testing (false-discovery-rate <0.05). Differentially methylated genes were functionally annotated (KEGG-pathway database), and allocated to three classes depending on involvement in physical/neurocognitive development, critical illness and intensive medical care, or pre-PICU-admission disorders. As compared with matched healthy children, former PICU-patients showed significantly different DNA-methylation at 4047 CpG-sites (2186 genes) and 494 DNA-regions (468 genes), with most CpG-sites being hypomethylated (90.3%) and with an average absolute 2% effect-size, irrespective of timing of PN initiation. Of the differentially methylated KEGG-pathways, 41.2% were related to physical/neurocognitive development, 32.8% to critical illness and intensive medical care and 26.0% to pre-PICU-admission disorders. Two years after critical illness in children, buccal-mucosal DNA showed abnormal methylation of CpG-sites and DNA-regions located in pathways known to be important for physical/neurocognitive development.

Epigallocatechin Gallate (EGCG), an Active Phenolic Compound of Green Tea, Inhibits Tumor Growth of Head and Neck Cancer Cells by Targeting DNA Hypermethylation

Head and neck cancers are among the deadliest cancers, ranked sixth globally in rates of high mortality and poor patient prognoses. The prevalence of head and neck squamous cell carcinoma (HNSCC) is associated with smoking and excessive alcohol consumption. Despite several advances in diagnostic and interventional methods, the morbidity of subjects with HNSCC has remained unchanged over the last 30 years. Epigenetic alterations, such as DNA hypermethylation, are commonly associated with several cancers, including HNSCC. Thus, epigenetic changes are considered promising therapeutic targets for chemoprevention. Here, we investigated the effect of EGCG on DNA hypermethylation and the growth of HNSCC. First, we assessed the expression levels of global DNA methylation in HNSCC cells (FaDu and SCC-1) and observed enhanced methylation levels compared with normal human bronchial epithelial cells (NHBE). Treatment of EGCG to HNSCC cells significantly inhibited global DNA hypermethylation by up to 70–80% after 6 days. Inhibition of DNA hypermethylation in HNSCC cells was confirmed by the conversion of 5-methylcytosine (5-mc) into 5-hydroxy methylcytosine (5hmC). DNA methyltransferases regulate DNA methylation. Next, we checked the effect of EGCG on the expression levels of DNA methyltransferases (DNMTs) and DNMT activity. Treatment of EGCG to HNSCC cells significantly reduced DNMT activity to 60% in SCC-1 and 80% in FaDu cells. The protein levels of DNMT3a and DNMT3b were downregulated in both cell lines after EGCG treatment. EGCG treatment to HNSCC cells reactivated tumor suppressors and caused decreased cell proliferation. Our in vivo study demonstrated that administration of EGCG (0.5%, w/w) as a supplement within an AIN76A diet resulted in inhibition of tumor growth in FaDu xenografts in nude mice (80%; p < 0.01) compared with non-EGCG-treated controls. The growth inhibitory effect of dietary EGCG on the HNSCC xenograft tumors was associated with the inhibition of DNMTs and reactivation of silenced tumor suppressors. Together, our study provides evidence that EGCG acts as a DNA demethylating agent and can reactivate epigenetically silenced tumor suppressors to inhibit the growth of HNSCC cells.

Epigenetic reprogramming in cancer: From diagnosis to treatment

Disruption of the epigenetic program of gene expression is a hallmark of cancer that initiates and propagates tumorigenesis. Altered DNA methylation, histone modifications and ncRNAs expression are a feature of cancer cells. The dynamic epigenetic changes during oncogenic transformation are related to tumor heterogeneity, unlimited self-renewal and multi-lineage differentiation. This stem cell-like state or the aberrant reprogramming of cancer stem cells is the major challenge in treatment and drug resistance. Given the reversible nature of epigenetic modifications, the ability to restore the cancer epigenome through the inhibition of the epigenetic modifiers is a promising therapy for cancer treatment, either as a monotherapy or in combination with other anticancer therapies, including immunotherapies. Herein, we highlighted the main epigenetic alterations, their potential as a biomarker for early diagnosis and the epigenetic therapies approved for cancer treatment.

Aclust2.0: a revamped unsupervised R tool for Infinium methylation beadchips data analyses

MOTIVATION

A wide range of computational packages has been developed for regional DNA methylation analyses of Illumina's Infinium array data. Aclust, one of the first unsupervised algorithms, was originally designed to analyze regional methylation of Infinium's 27K and 450K arrays by clustering neighboring methylation sites prior to downstream analyses. However, Aclust relied on outdated packages that rendered it largely non-operational especially with the newer Infinium EPIC and mouse arrays.

RESULTS

We have created Aclust2.0, a streamlined pipeline that involves five steps for the analyses of human (450K and EPIC) and mouse array data. Aclust2.0 provides a user-friendly pipeline and versatile for regional DNA methylation analyses for molecular epidemiological and mouse studies.

AVAILABILITY AND IMPLEMENTATION

Aclust2.0 is freely available on Github (https://github.com/OluwayioseOA/Alcust2.0.git).

Completing Single-Cell DNA Methylome Profiles via Transfer Learning Together With KL-Divergence

The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with very low coverage (below 2%). Transfer learning was used to leverage less sparse profiles that are typically available for different tissues for the same species, while KL divergence was employed to maximize the usage of information carried in the input data. A deep neural network was adopted to extract both DNA sequence and local methylation patterns for imputation. Our study of training models for completing methylome profiles of bovine oocytes and early embryos demonstrates the effectiveness of transfer learning and KL divergence, with individual increase of 29.98 and 29.43%, respectively, in prediction performance and 38.70% increase when the two were used together. The drastically increased data coverage (43.80-73.6%) after imputation powers downstream analyses involving methylomes that cannot be effectively done using the very low coverage profiles (0.06-1.47%) before imputation.

DNA methylation signatures in human neonatal blood following maternal antenatal corticosteroid treatment

Antenatal corticosteroids (ACS) are used to treat women at risk of preterm birth to improve neonatal survival. Though affected children may be at long-term risk of neurobehavioural disorders, the driving mechanisms remain unknown. Animal studies have shown that ACS exposure can lead to overlapping changes in DNA methylation between the blood and the brain, identifying gene pathways for neurodevelopment, which highlights the potential to examine peripheral blood as a surrogate for inaccessible human brain tissue. We hypothesized that differential methylation will be identified in blood of term-born neonates following ACS. Mother-infant dyads that received ACS were retrospectively identified through the Ontario Birth Study at Sinai Health Complex and matched to untreated controls for maternal age, BMI, parity and foetal sex (n = 14/group). Genome-wide methylation differences were examined at single-nucleotide resolution in DNA extracted from dried bloodspot cards using reduced representative bisulfite sequencing approaches. 505 differentially methylated CpG sites (DMCs) were identified, wherein 231 were hypermethylated and 274 were hypomethylated. These sites were annotated to 219 genes, of which USP48, SH3PXD2A, NTM, CAMK2N2, MAP6D1 were five of the top ten genes with known neurological function. Collectively, the set of hypermethylated genes were enriched for pathways of transcription regulation, while pathways of proteasome activity were enriched among the set of hypomethylated genes. This study is the first to identify DNA methylation changes in human neonatal blood following ACS. Understanding the epigenetic changes that occur in response to ACS will support future investigations to delineate the effects of prenatal glucocorticoid exposure on human development.

Cluster mean-field theory accurately predicts statistical properties of large-scale DNA methylation patterns

The accurate establishment and maintenance of DNA methylation patterns is vital for mammalian development and disruption to these processes causes human disease. Our understanding of DNA methylation mechanisms has been facilitated by mathematical modelling, particularly stochastic simulations. Megabase-scale variation in DNA methylation patterns is observed in development, cancer and ageing and the mechanisms generating these patterns are little understood. However, the computational cost of stochastic simulations prevents them from modelling such large genomic regions. Here, we test the utility of three different mean-field models to predict summary statistics associated with large-scale DNA methylation patterns. By comparison to stochastic simulations, we show that a cluster mean-field model accurately predicts the statistical properties of steady-state DNA methylation patterns, including the mean and variance of methylation levels calculated across a system of CpG sites, as well as the covariance and correlation of methylation levels between neighbouring sites. We also demonstrate that a cluster mean-field model can be used within an approximate Bayesian computation framework to accurately infer model parameters from data. As mean-field models can be solved numerically in a few seconds, our work demonstrates their utility for understanding the processes underpinning large-scale DNA methylation patterns.

Chromatin Dynamics During Entry to Quiescence and Compromised Functionality in Cancer Cells

Quiescence is a vital cellular state where cells can reversibly exit the cell cycle and cease proliferation in unfavourable conditions. Cells can undergo multiple transitions in and out of quiescence during their lifetime, and an imbalance in this highly regulated process can promote tumorigenesis and disease. The nucleus experiences vast changes during entry to quiescence, including changes in gene expression and a reduction in size due to increased chromatin compaction. Studies into these changes have highlighted the importance of a core quiescence gene expression programme, reorganisation of nuclear structures, and the action of the condensin complex in creating a stable, quiescent nucleus. However, the underpinning mechanisms behind the formation of a quiescent nucleus are still not fully understood. This chapter explores the current literature surrounding chromatin dynamics during entry to quiescence and the association between quiescence and disease and accentuates the need for further studies to understand this transition. Linking failure to maintain a stable, quiescent state with potential genome instability may help in the advancement of medical interventions for a range of diseases, including cancer.

Live-Cell Probe for In Situ Single-Cell Monitoring of Mitochondrial DNA Methylation

Mitochondria, as the center of energy production, play an important role in cell homeostasis by regulating the cellular metabolism and mediating the cellular response to stress. Epigenetic changes such as DNA and histone methylation have been increasingly recognized to play a significant role in homeostasis and stress response. The cross-talking between the metabolome and the epigenome has attracted significant attention in recent years but with a major focus on how metabolism contributes to epigenomic changes. Few studies have focused on how epigenetic modifications may alter the mitochondrial composition and activity. In this work, we designed a novel probe targeting methylated CpGs of mitochondrial DNA (mtDNA). We demonstrated the capability of our probe to reveal the spatial distribution of methylated mtDNA and capture the mtDNA methylation changes at a single-cell level. We were also able to track single-cell mtDNA and nDNA methylation simultaneously and discovered the unsynchronized dynamics of the nucleus and mitochondria. Our tool offers a unique opportunity to understand the epigenetic regulation of mtDNA and its dynamic response to the microenvironment and cellular changes.

The effects of flavonoids, green tea polyphenols and coffee on DMBA induced LINE-1 DNA hypomethylation

The intake of carcinogenic and chemopreventive compounds are important nutritional factors related to the development of malignant tumorous diseases. Repetitive long interspersed element-1 (LINE-1) DNA methylation pattern plays a key role in both carcinogenesis and chemoprevention. In our present in vivo animal model, we examined LINE-1 DNA methylation pattern as potential biomarker in the liver, spleen and kidney of mice consuming green tea (Camellia sinensis) extract (catechins 80%), a chinese bayberry (Morella rubra) extract (myricetin 80%), a flavonoid extract (with added resveratrol) and coffee (Coffee arabica) extract. In the organs examined, carcinogen 7,12-dimethylbenz(a)anthracene (DMBA)-induced hypomethylation was prevented by all test materials except chinese bayberry extract in the kidneys. Moreover, the flavonoid extract caused significant hypermethylation in the liver compared to untreated controls and to other test materials. The tested chemopreventive substances have antioxidant, anti-inflammatory properties and regulate molecular biological signaling pathways. They increase glutathione levels, induce antioxidant enzymes, which decrease free radical damage caused by DMBA, and ultimately, they are able to increase the activity of DNA methyltransferase enzymes. Furthermore, flavonoids in the liver may inhibit the procarcinogen to carcinogen activation of DMBA through the inhibition of CYP1A1 enzyme. At the same time, paradoxically, myricetin can act as a prooxidant as a result of free radical damage, which can explain that it did not prevent hypomethylation in the kidneys. Our results demonstrated that LINE-1 DNA methylation pattern is a useful potential biomarker for detecting and monitoring carcinogenic and chemopreventive effects of dietary compounds.

Dioxin Disrupts Dynamic DNA Methylation Patterns in Genes That Govern Cardiomyocyte Maturation

Congenital heart disease (CHD), the leading birth defect worldwide, has a largely unknown etiology, likely to result from complex interactions between genetic and environmental factors during heart development, at a time when the heart adapts to diverse physiological and pathophysiological conditions. Crucial among these is the regulation of cardiomyocyte development and postnatal maturation, governed by dynamic changes in DNA methylation. Previous work from our laboratory has shown that exposure to the environmental toxicant tetrachlorodibenzo-p-dioxin (TCDD) disrupts several molecular networks responsible for heart development and function. To test the hypothesis that the disruption caused by TCDD in the heart results from changes in DNA methylation and gene expression patterns of cardiomyocytes, we established a stable mouse embryonic stem cell line expressing a puromycin resistance selectable marker under control of the cardiomyocyte-specific Nkx2-5 promoter. Differentiation of these cells in the presence of puromycin induces the expression of a large suite of cardiomyocyte-specific markers. To assess the consequences of TCDD treatment on gene expression and DNA methylation in these cardiomyocytes, we subjected them to transcriptome and methylome analyses in the presence of TCDD. Unlike control cardiomyocytes maintained in vehicle, the TCDD-treated cardiomyocytes showed extensive gene expression changes, with a significant correlation between differential RNA expression and DNA methylation in 111 genes, many of which are key elements of pathways that regulate cardiovascular development and function. Our findings provide an important clue toward the elucidation of the complex interactions between genetic and epigenetic mechanisms after developmental TCDD exposure that may contribute to CHD.

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome

We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. Differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

A Mathematical Model for Inheritance of DNA Methylation Patterns in Somatic Cells

DNA methylation is an essential epigenetic mechanism used by cells to regulate gene expression. Interestingly, DNA replication, a function necessary for cell division, disrupts the methylation pattern. Since perturbed methylation patterns are associated with aberrant gene expression and many diseases, including cancer, restoration of the correct pattern following DNA replication is crucial. However, the exact mechanisms of this restoration remain under investigation. DNA methyltransferases (Dnmts) perform methylation by adding a methyl group to cytosines at CpG sites in the DNA. These CpG sites are found in regions of high density, termed CpG islands (CGIs), and regions of low density in the genome. Nearly, every CpG site in a CGI has the same state, either methylated or unmethylated, and almost all CpG sites in regions of low CpG density are methylated. We propose a stochastic model for the dynamics of the post-replicative restoration of methylation patterns. The model considers the recruitment of Dnmts and demethylating enzymes to regions of hyper- and hypomethylation, respectively. The model also includes the interaction between Dnmt1 and PCNA, an enzyme that localizes Dnmt1 to the replication complex. Using our model, we predict that the methylation of regions of DNA can be bistable. Further, we predict that recruitment mechanisms maintain methylation in CGIs, whereas the Dnmt1-PCNA interaction maintains methylation in low-density regions.

Stochastic modeling reveals kinetic heterogeneity in post-replication DNA methylation

DNA methylation is a heritable epigenetic modification that plays an essential role in mammalian development. Genomic methylation patterns are dynamically maintained, with DNA methyltransferases mediating inheritance of methyl marks onto nascent DNA over cycles of replication. A recently developed experimental technique employing immunoprecipitation of bromodeoxyuridine labeled nascent DNA followed by bisulfite sequencing (Repli-BS) measures post-replication temporal evolution of cytosine methylation, thus enabling genome-wide monitoring of methylation maintenance. In this work, we combine statistical analysis and stochastic mathematical modeling to analyze Repli-BS data from human embryonic stem cells. We estimate site-specific kinetic rate constants for the restoration of methyl marks on >10 million uniquely mapped cytosines within the CpG (cytosine-phosphate-guanine) dinucleotide context across the genome using Maximum Likelihood Estimation. We find that post-replication remethylation rate constants span approximately two orders of magnitude, with half-lives of per-site recovery of steady-state methylation levels ranging from shorter than ten minutes to five hours and longer. Furthermore, we find that kinetic constants of maintenance methylation are correlated among neighboring CpG sites. Stochastic mathematical modeling provides insight to the biological mechanisms underlying the inference results, suggesting that enzyme processivity and/or collaboration can produce the observed kinetic correlations. Our combined statistical/mathematical modeling approach expands the utility of genomic datasets and disentangles heterogeneity in methylation patterns arising from replication-associated temporal dynamics versus stable cell-to-cell differences.

Transgenerational Inheritance of Environmentally Induced Epigenetic Alterations during Mammalian Development

Genetic studies traditionally focus on DNA as the molecule that passes information on from parents to their offspring. Changes in the DNA code alter heritable information and can more or less severely affect the progeny's phenotype. While the idea that information can be inherited between generations independently of the DNA's nucleotide sequence is not new, the outcome of recent studies provides a mechanistic foundation for the concept. In this review, we attempt to summarize our current knowledge about the transgenerational inheritance of environmentally induced epigenetic changes. We focus primarily on studies using mice but refer to other species to illustrate salient points. Some studies support the notion that there is a somatic component within the phenomenon of epigenetic inheritance. However, here, we will mostly focus on gamete-based processes and the primary molecular mechanisms that are thought to contribute to epigenetic inheritance: DNA methylation, histone modifications, and non-coding RNAs. Most of the rodent studies published in the literature suggest that transgenerational epigenetic inheritance through gametes can be modulated by environmental factors. Modification and redistribution of chromatin proteins in gametes is one of the major routes for transmitting epigenetic information from parents to the offspring. Our recent studies provide additional specific cues for this concept and help better understand environmental exposure influences fitness and fidelity in the germline. In summary, environmental cues can induce parental alterations and affect the phenotypes of offspring through gametic epigenetic inheritance. Consequently, epigenetic factors and their heritability should be considered during disease risk assessment.

The Bright and Dark Side of DNA Methylation: A Matter of Balance

DNA methylation controls several cellular processes, from early development to old age, including biological responses to endogenous or exogenous stimuli contributing to disease transition. As a result, minimal DNA methylation changes during developmental stages drive severe phenotypes, as observed in germ-line imprinting disorders, while genome-wide alterations occurring in somatic cells are linked to cancer onset and progression. By summarizing the molecular events governing DNA methylation, we focus on the methods that have facilitated mapping and understanding of this epigenetic mark in healthy conditions and diseases. Overall, we review the bright (health-related) and dark (disease-related) side of DNA methylation changes, outlining how bulk and single-cell genomic analyses are moving toward the identification of new molecular targets and driving the development of more specific and less toxic demethylating agents.

A Free Radical Scavenger Ameliorates Teratogenic Activity of a DNA Hypomethylating Hematological Therapeutic

The spin-trap free radical scavenger N-tert-butyl-α-phenylnitron (PBN) ameliorated effects of several teratogens involving reactive oxygen species (ROS). We investigated for the first time whether PBN could ameliorate teratogenesis induced by a DNA hypomethylating hematological therapeutic 5-azacytidine (5azaC). At days 12 and 13 of gestation, Fisher rat dams were pretreated by an i.v. injection of PBN (40 mg/kg) and 1 h later by an i.p. injection of 5azaC (5mg/kg). Development was analyzed at gestation day 15 in embryos and day 20 in fetuses. PBN alone did not significantly affect development. PBN pretreatment restored survival of 5azaC-treated dams' embryos to the control level, restored weight of embryos and partially of fetuses, and partially restored crown-rump lengths. PBN pretreatment converted limb adactyly to less severe oligodactyly. PBN pretreatment restored global DNA methylation level in the limb buds to the control level. Cell proliferation in limb buds of all 5azaC-treated dams remained significantly lower than in controls. In the embryonic liver, PBN pretreatment normalized proliferation diminished significantly by 5azaC; whereas in embryonic vertebral cartilage, proliferation of all 5azaC-treated dams was significantly higher than in PBN-treated dams or controls. Apoptotic indices significantly enhanced by 5azaC in liver and cartilage were not influenced by PBN pretreatment. However, PBN significantly diminished ROS or reactive nitrogen species markers nitrotyrosine and 8-hydroxy-2'deoxyguanosine elevated by 5azaC in embryonic tissues, and, therefore, activity of this DNA hypomethylating agent was associated to the activation of free radicals. That pretreatment with PBN enhanced proliferation in the liver and not in immature tissue is interesting for the treatment of 5azaC-induced hepatotoxicity and liver regeneration.

Epigenetic and metabolic alterations in human amniotic fluid stem cells induced to cardiomyogenic differentiation by DNA methyltransferases and p53 inhibitors

Human amniotic fluid-derived mesenchymal stem cells (AF-MSCs) may be a valuable source for cell therapy and regenerative medicine. In this study, the potential of DNA methyltransferases (DNMT) inhibitors Decitabine, Zebularine, RG108 alone or combined with Zebularine and p53 inhibitor Pifithrin-α to induce cardiomyogenic differentiation of AF-MSCs was investigated. Differentiation into cardiomyocyte-like cells initiation was indicated with all agents by changes in the cell phenotype, upregulation of the relative expression of the main cardiac genes (NKX2-5, TNNT2, MYH6, and DES) as well as of cardiac ion channels genes (sodium, calcium, and potassium) as determined by reverse-transcription quantitative polymerase chain reaction and the increase in Connexin43 levels as detected from Western blot and immunofluorescence data. Cellular energetics and mitochondrial function in induced cells were assessed using Seahorse analyzer and revealed the initiation of AF-MSCs metabolic transformation into cardiomyocyte-like cells. All used inducers were nontoxic to AF-MSCs, arrested cell cycle at the G0/G1 phase, and upregulated p53 and p21 expression. The relative expression of miR-34a and miR-145 that are related to cell cycle regulation was also observed. Furthermore, the evaluated levels of chromatin remodeling proteins enhancer of zeste homolog 2, suppressor of zeste 12 protein homolog, DNMT1, histone deacetylase 1 (HDAC1), HDAC2, and heterochromatin protein 1α, as well as the rate of activating histone modifications, exhibited rearrangements of chromatin after the induction of cardiomyogenic differentiation. In conclusion, we demonstrated that all explored DNMT and p53 inhibitors initiated cardiomyogenesis-related alterations in AF-MSCs through rather similar mechanisms but to a different extent providing useful insights for the future research and potential applications of AF-MSCs.

Mechanisms of establishment and functional significance of DNA demethylation during erythroid differentiation

Erythroid differentiation is associated with global DNA demethylation, but a complete methylome was lacking in the erythroid lineage. We have generated allele-specific base resolution methylomes of primary basophilic erythroblasts (BasoEs) and compared these with 8 other cell types. We found that DNA demethylation during differentiation from hematopoietic stem/progenitor cells (HSPCs) to BasoEs occurred predominantly in intergenic sequences and in inactive gene bodies causing the formation of partially methylated domains (PMDs) in 74% of the BasoE methylome. Moreover, differentially methylated regions (DMRs) between HSPCs and BasoEs occurred mostly in putative enhancer regions and were most often associated with GATA, EKLF, and AP1 binding motifs. Surprisingly, promoters silent in both HSPCs and BasoEs exhibited much more dramatic chromatin changes during differentiation than activated promoters. Unmethylated silent promoters were often associated with active chromatin states in highly methylated domains (HMDs) but with polycomb-repression in PMDs, indicating that silent promoters are generally regulated differently in HMDs and PMDs. We show that long PMDs replicate late, but that short PMDs replicate early and therefore that the partial methylation of DNA after replication during erythroid expansion occurs throughout S phase of the cell cycle. We propose that baseline maintenance methylation following replication decreases during erythroid differentiation resulting in PMD formation and that the presence of HMDs in the BasoE methylome results from transcription-associated DNA methylation of gene bodies. We detected ∼700 large allele-specific DMRs that were enriched in single-nucleotide polymorphisms, suggesting that primary DNA sequence might be a determinant of DNA methylation levels within PMDs.

Prostate Cancer Epigenetics: From Basic Mechanisms to Clinical Implications

A level of epigenetic programming, encoded by complex sets of chemical marks on DNA and histones, and by context-specific DNA, RNA, protein interactions, that all regulate the structure, organization, and function of the genome, is critical to establish both normal and neoplastic cell identities and functions. This structure-function relationship of the genome encoded by the epigenetic programming can be thought of as an epigenetic cityscape that is built on the underlying genetic landscape. Alterations in the epigenetic cityscape of prostate cancer cells compared with normal prostate tissues have a complex interplay with genetic alterations to drive prostate cancer initiation and progression. Indeed, mutations in genes encoding epigenetic enzymes are often observed in human cancers including prostate cancer. Interestingly, alterations in the prostate cancer epigenetic cityscape can be highly recurrent, a facet that can be exploited for development of biomarkers and potentially as therapeutic targets.

Tissue-specific DNA methylation loss during ageing and carcinogenesis is linked to chromosome structure, replication timing and cell division rates

DNA methylation is an epigenetic mechanism known to affect gene expression and aberrant DNA methylation patterns have been described in cancer. However, only a small fraction of differential methylation events target genes with a defined role in cancer, raising the question of how aberrant DNA methylation contributes to carcinogenesis. As recently a link has been suggested between methylation patterns arising in ageing and those arising in cancer, we asked which aberrations are unique to cancer and which are the product of normal ageing processes. We therefore compared the methylation patterns between ageing and cancer in multiple tissues. We observed that hypermethylation preferentially occurs in regulatory elements, while hypomethylation is associated with structural features of the chromatin. Specifically, we observed consistent hypomethylation of late-replicating, lamina-associated domains. The extent of hypomethylation was stronger in cancer, but in both ageing and cancer it was proportional to the replication timing of the region and the cell division rate of the tissue. Moreover, cancer patients who displayed more hypomethylation in late-replicating, lamina-associated domains had higher expression of cell division genes. These findings suggest that different cell division rates contribute to tissue- and cancer type-specific DNA methylation profiles.

Epigenetic control of macrophage polarization: implications for targeting tumor-associated macrophages

The progression of cancer is a result of not only the growth of the malignant cells but also the behavior of other components of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are key components of the TME that influence tumor growth and disease progression. TAMs can either inhibit or support tumor growth depending on their polarization to classically-activated macrophages (M1s) or alternatively-activated macrophages (M2s), respectively. Epigenetic regulation plays a significant role in determining this polarization and manipulating the epigenetic regulation in macrophages would provide a means for selectively targeting M2s thereby eliminating tumor-supporting TAMs while sparing tumor-inhibiting M1 TAMs. Many pharmacologic modulators of epigenetic enzymes are currently used clinically and could be repurposed for treating tumors with high TAM infiltrate. While much research involving epigenetic enzymes and their modulators has been performed in M1s, significantly less is known about the epigenetic regulation of M2s. This review highlights the field’s current knowledge of key epigenetic enzymes and their pharmacologic modulators known to influence macrophage polarization.

Integration of multi-omics techniques and physiological phenotyping within a holistic phenomics approach to study senescence in model and crop plants

The study of senescence in plants is complicated by diverse levels of temporal and spatial dynamics as well as the impact of external biotic and abiotic factors and crop plant management. Whereas the molecular mechanisms involved in developmentally regulated leaf senescence are very well understood, in particular in the annual model plant species Arabidopsis, senescence of other organs such as the flower, fruit, and root is much less studied as well as senescence in perennials such as trees. This review addresses the need for the integration of multi-omics techniques and physiological phenotyping into holistic phenomics approaches to dissect the complex phenomenon of senescence. That became feasible through major advances in the establishment of various, complementary 'omics' technologies. Such an interdisciplinary approach will also need to consider knowledge from the animal field, in particular in relation to novel regulators such as small, non-coding RNAs, epigenetic control and telomere length. Such a characterization of phenotypes via the acquisition of high-dimensional datasets within a systems biology approach will allow us to systematically characterize the various programmes governing senescence beyond leaf senescence in Arabidopsis and to elucidate the underlying molecular processes. Such a multi-omics approach is expected to also spur the application of results from model plants to agriculture and their verification for sustainable and environmentally friendly improvement of crop plant stress resilience and productivity and contribute to improvements based on postharvest physiology for the food industry and the benefit of its customers.

Hypermethylation of the CHRDL1 promoter induces proliferation and metastasis by activating Akt and Erk in gastric cancer

CHRDL1 (Chordin-like 1) is a secreted protein that acts as an antagonist of bone morphogenetic protein (BMP). BMP plays a role as an activator of BMP receptor II (BMPR II), which mediates extracellular to intracellular signal transmission and is involved in carcinogenesis and metastasis. Herein, we report that CHRDL1 expression was significantly down-regulated in gastric cancer tissues and associated with poor survival. Clinic-pathological parameters demonstrated a close relationship between low CHRDL1 expression and metastasis. In vitro, CHRDL1 knockdown promoted tumor cell proliferation and migration through BMPR II by activating Akt, Erk and β-catenin. Furthermore, we observed the hypermethylation of the CHRDL1 promoter in gastric cancer, which induced low expression of CHRDL1 and decreased its secretion to the supernatant. Finally, in vivo experiments confirmed that CHRDL1 acted as a tumor suppressor gene in suppressing tumor growth and metastasis.

Passive DNA demethylation preferentially up-regulates pluripotency-related genes and facilitates the generation of induced pluripotent stem cells

A high proliferation rate has been observed to facilitate somatic cell reprogramming, but the pathways that connect proliferation and reprogramming have not been reported. DNA methyltransferase 1 (DNMT1) methylates hemimethylated CpG sites produced during S phase and maintains stable inheritance of DNA methylation. Impairing this process results in passive DNA demethylation. In this study, we show that the cell proliferation rate positively correlated with the expression of Dnmt1 in G₁ phase. In addition, as determined by whole-genome bisulfate sequencing and high-performance liquid chromatography, global DNA methylation of mouse embryonic fibroblasts was significantly higher in G₁ phase than in G₂/M phase. Thus, we suspected that high cellular proliferation requires more Dnmt1 expression in G₁ phase to prevent passive DNA demethylation. The methylation differences of individual CpG sites between G₁ and G₂/M phase were related to the methylation status and the positions of their surrounding CpG sites. In addition, larger methylation differences were observed on the promoters of pluripotency-related genes; for example, Oct4, Nanog, Sox2, Esrrb, Cdh1, and Epcam When such methylation differences or passive DNA demethylation accumulated with Dnmt1 suppression and proliferation acceleration, DNA methylation on pluripotency-related genes was decreased, and their expression was up-regulated, which subsequently promoted pluripotency and mesenchymal-epithelial transition, a necessary step for reprogramming. We infer that high cellular proliferation rates promote generation of induced pluripotent stem cells at least partially by inducing passive DNA demethylation and up-regulating pluripotency-related genes. Therefore, these results uncover a connection between cell reprogramming and DNA methylation.

Reconstructing cell cycle pseudo time-series via single-cell transcriptome data

Single-cell mRNA sequencing, which permits whole transcriptional profiling of individual cells, has been widely applied to study growth and development of tissues and tumors. Resolving cell cycle for such groups of cells is significant, but may not be adequately achieved by commonly used approaches. Here we develop a traveling salesman problem and hidden Markov model-based computational method named reCAT, to recover cell cycle along time for unsynchronized single-cell transcriptome data. We independently test reCAT for accuracy and reliability using several data sets. We find that cell cycle genes cluster into two major waves of expression, which correspond to the two well-known checkpoints, G1 and G2. Moreover, we leverage reCAT to exhibit methylation variation along the recovered cell cycle. Thus, reCAT shows the potential to elucidate diverse profiles of cell cycle, as well as other cyclic or circadian processes (e.g., in liver), on single-cell resolution.In single-cell RNA sequencing data of heterogeneous cell populations, cell cycle stage of individual cells would often be informative. Here, the authors introduce a computational model to reconstruct a pseudo-time series from single cell transcriptome data, identify the cell cycle stages, identify candidate cell cycle-regulated genes and recover the methylome changes during the cell cycle.

Reconstructing cell cycle pseudo time-series via single-cell transcriptome data

Single-cell mRNA sequencing, which permits whole transcriptional profiling of individual cells, has been widely applied to study growth and development of tissues and tumors. Resolving cell cycle for such groups of cells is significant, but may not be adequately achieved by commonly used approaches. Here we develop a traveling salesman problem and hidden Markov model-based computational method named reCAT, to recover cell cycle along time for unsynchronized single-cell transcriptome data. We independently test reCAT for accuracy and reliability using several data sets. We find that cell cycle genes cluster into two major waves of expression, which correspond to the two well-known checkpoints, G1 and G2. Moreover, we leverage reCAT to exhibit methylation variation along the recovered cell cycle. Thus, reCAT shows the potential to elucidate diverse profiles of cell cycle, as well as other cyclic or circadian processes (e.g., in liver), on single-cell resolution.

In single-cell RNA sequencing data of heterogeneous cell populations, cell cycle stage of individual cells would often be informative. Here, the authors introduce a computational model to reconstruct a pseudo-time series from single cell transcriptome data, identify the cell cycle stages, identify candidate cell cycle-regulated genes and recover the methylome changes during the cell cycle.

Prostate cancer epigenetics and its clinical implications

Normal cells have a level of epigenetic programming that is superimposed on the genetic code to establish and maintain their cell identity and phenotypes. This epigenetic programming can be thought as the architecture, a sort of cityscape, that is built upon the underlying genetic landscape. The epigenetic programming is encoded by a complex set of chemical marks on DNA, on histone proteins in nucleosomes, and by numerous context-specific DNA, RNA, protein interactions that all regulate the structure, organization, and function of the genome in a given cell. It is becoming increasingly evident that abnormalities in both the genetic landscape and epigenetic cityscape can cooperate to drive carcinogenesis and disease progression. Large-scale cancer genome sequencing studies have revealed that mutations in genes encoding the enzymatic machinery for shaping the epigenetic cityscape are among the most common mutations observed in human cancers, including prostate cancer. Interestingly, although the constellation of genetic mutations in a given cancer can be quite heterogeneous from person to person, there are numerous epigenetic alterations that appear to be highly recurrent, and nearly universal in a given cancer type, including in prostate cancer. The highly recurrent nature of these alterations can be exploited for development of biomarkers for cancer detection and risk stratification and as targets for therapeutic intervention. Here, we explore the basic principles of epigenetic processes in normal cells and prostate cancer cells and discuss the potential clinical implications with regards to prostate cancer biomarker development and therapy.