Alexander Olek

Active demethylation of the paternal genome in the mouse zygote.

DNA methylation is essential for the control of a number of biological mechanisms in mammals [1]. Mammalian development is accompanied by two major waves of genome-wide demethylation and remethylation: one during germ-cell development and the other after fertilisation [2] [3] [4] [5] [6] [7]. Most previous studies have suggested that the genome-wide demethylation observed after fertilisation occurs passively, that is, by the lack of maintenance methylation following DNA replication and cell division [6] [7], although one other study has reported that replication-independent demethylation may also occur during early embryogenesis [8]. Here, we report that genes that are highly methylated in sperm are rapidly demethylated in the zygote only hours after fertilisation, before the first round of DNA replication commences. By contrast, the oocyte-derived maternal alleles are unaffected by this reprogramming. They either remain methylated after fertilisation or become further methylated de novo. These results provide the first direct evidence for active demethylation of single-copy genes in the mammalian zygote and, moreover, reveal a striking asymmetry in epigenetic methylation reprogramming. Whereas paternally (sperm)-derived sequences are exposed to putative active demethylases in the oocyte cytoplasm, maternally (oocyte)-derived sequences are protected from this reaction. These results, whose generality is supported by findings of Mayer et al. [9], have important implications for the establishment of biparental genetic totipotency after fertilisation, the establishment and maintenance of genomic imprinting, and the reprogramming of somatic cells during cloning.

DNA methylation profiling of the human major histocompatibility complex: A pilot study for the Human Epigenome Project

The Human Epigenome Project aims to identify, catalogue, and interpret genome-wide DNA methylation phenomena. Occurring naturally on cytosine bases at cytosine–guanine dinucleotides, DNA methylation is intimately involved in diverse biological processes and the aetiology of many diseases. Differentially methylated cytosines give rise to distinct profiles, thought to be specific for gene activity, tissue type, and disease state. The identification of such methylation variable positions will significantly improve our understanding of genome biology and our ability to diagnose disease. Here, we report the results of the pilot study for the Human Epigenome Project entailing the methylation analysis of the human major histocompatibility complex. This study involved the development of an integrated pipeline for high-throughput methylation analysis using bisulphite DNA sequencing, discovery of methylation variable positions, epigenotyping by matrix-assisted laser desorption/ionisation mass spectrometry, and development of an integrated public database available at http://www.epigenome.org. Our analysis of DNA methylation levels within the major histocompatibility complex, including regulatory exonic and intronic regions associated with 90 genes in multiple tissues and individuals, reveals a bimodal distribution of methylation profiles (i.e., the vast majority of the analysed regions were either hypo- or hypermethylated), tissue specificity, inter-individual variation, and correlation with independent gene expression data.

Oligonucleotide‐based microarray for DNA methylation analysis: Principles and applications

Gene silencing via promoter CpG island hypermethylation offers tumor cells growth advantages. This epigenetic event is pharmacologically reversible, and uncovering a unique set of methylation‐silenced genes in tumor cells can bring a new avenue to cancer treatment. However, high‐throughput tools capable of surveying the methylation status of multiple gene promoters are needed for this discovery process. Herein we describe an oligonucleotide‐based microarray technique that is both versatile and sensitive in revealing hypermethylation in defined regions of the genome. DNA samples are bisulfite‐treated and PCR‐amplified to distinguish CpG dinucleotides that are methylated from those that are not. Fluorescently labeled PCR products are hybridized to arrayed oligonucleotides that can discriminate between methylated and unmethylated alleles in regions of interest. Using this technique, two clinical subtypes of non‐Hodgkins lymphomas, mantle cell lymphoma, and grades I/II follicular lymphoma, were further separated based on the differential methylation profiles of several gene promoters. Work is underway in our laboratory to extend the interrogation power of this microarray system in multiple candidate genes. This novel tool, therefore, holds promise to monitor the outcome of various epigenetic therapies on cancer patients.

Association of DNA Methylation of Phosphoserine Aminotransferase with Response to Endocrine Therapy in Patients with Recurrent Breast Cancer

To understand the biological basis of resistance to endocrine therapy is of utmost importance in patients with steroid hormone receptor-positive breast cancer. Not only will this allow us prediction of therapy success, it may also lead to novel therapies for patients resistant to current endocrine therapy. DNA methylation in the promoter regions of genes is a prominent epigenetic gene silencing mechanism that contributes to breast cancer biology. In the current study, we investigated whether promoter DNA methylation could be associated with resistance to endocrine therapy in patients with recurrent breast cancer. Using a microarray-based technology, the promoter DNA methylation status of 117 candidate genes was studied in a cohort of 200 steroid hormone receptor-positive tumors of patients who received the antiestrogen tamoxifen as first-line treatment for recurrent breast cancer. Of the genes analyzed, the promoter DNA methylation status of 10 genes was significantly associated with clinical outcome of tamoxifen therapy. The association of the promoter hypermethylation of the strongest marker, phosphoserine aminotransferase (PSAT1) with favorable clinical outcome was confirmed by an independent quantitative DNA methylation detection method. Furthermore, the extent of DNA methylation of PSAT1 was inversely associated with its expression at the mRNA level. Finally, also at the mRNA level, PSAT1 was a predictor of tamoxifen therapy response. Concluding, our work indicates that promoter hypermethylation and mRNA expression of PSAT1 are indicators of response to tamoxifen-based endocrine therapy in steroid hormone receptor-positive patients with recurrent breast cancer.

Differences in DNA methylation patterns between humans and chimpanzees

Methylation at CpG dinucleotides is important for gene regulation in mammals [1]. However, it is unknown how methylation patterns change during evolution. Here, we compare methylation patterns between humans and chimpanzees at 36 genes in the brain, the liver and in lymphocytes. We find that the extent of the change in methylation pattern is much more extensive in the brain than in the other tissues. Furthermore, of the 15 CpGs that have significantly changed methylation in the brain, 14 are more methylated in humans than in chimpanzees. This indicates that CpGs might generally be more methylated in human brains than in chimpanzee brains. Despite considerable phenotypic differences, humans and their closest living relatives, the chimpanzees, are on average 98.8% identical in their alignable genomic DNA sequences [2,3]. It is currently unknown which genotypic differences are responsible for the phenotypic differences. One possibility to tackle this question is to compare gene expression patterns between humans and chimpanzees using functional genomic approaches [4–6]. In this respect, it may also be useful to compare methylation patterns in regulatory DNA sequences, as the methylation status can be viewed as a “footprint” of the chromatin structures that are crucial for gene regulation [7,8]. In order to take a first step toward understanding the evolution of methylation patterns, we compared the methylation status of 145 CpGs in the presumed regulatory regions of 36 different genes between humans and chimpanzees in brain, liver and lymphocytes using a recently developed array technique [9–11]. Thereby, genomic DNA is treated with sodium bisulphite such that unmethylated CpGs are amplified as TpGs in the following PCR. For each CpG examined, the arrays contain two oligonucleotides: one complementary to a TpG, resembling a formerly unmethylated CpG and one complementary to a CpG, resembling a formerly methylated CpG. We identified 22 CpGs in which the ratio of the intensities of these two oligonucleotides differed significantly between human and chimpanzee in at least one tissue. By contrast, zero to three differences would be expected due to random experimental and biological variation, as is shown by permutating the species labels for each tissue (see supplemental data for all methodological details). Therefore, the differences between the two species are highly significant, whereas the differences between the individuals of the same species are within the range of the experimental error (data not shown). We also do not observe a strong correlation of methylation levels with age or time post mortem (see supplemental data), Thus, we conclude that most of the observed methylation differences between humans and chimpanzees are neither due to random measurement errors nor due to random or systematic differences in their environment. To exclude trivial genetic causes, we sequenced the region of the 22 CpG sites in the chimpanzee and excluded 4 CpGs that carried a sequence difference between the chimpanzee sequence and the human-based oligonucleotide sequence. The remaining 18 CpGs from 12 genes are shown in Figure 1. Three observations from these experiments are especially noteworthy: First, despite the limited number of CpGs studied, several significant differences in their methylation status can be found between humans and chimpanzees. Second, out of 18 differences, 15 are found between chimpanzee and human brain, whereas only six are found between the other two tissues. Third, 14 of the 15 sites differing in methylation in the brain show a higher degree of methylation in humans. The first observation indicates that — at least in humans and chimpanzees — the methylation status of many CpG sites changes during the course of evolution. The second observation indicates that more CpG sites have changed their methylation status in the brain than in liver or lymphocytes. Notably, DNA methylation seems to be especially important for the brain, as defects in methylation lead to mental retardation in humans [8] and a mouse model for one of these diseases — Rett syndrome — indicates that the symptoms can be caused solely by a defect in postmitotic neurons [12,13]. Our third observation, namely that 14 of 15 CpG sites differently methylated in the brain show a higher degree of methylation in humans, might reflect a general up-methylation of genes in the human brain, rather than several independent, gene-specific methylation changes. Although it is unclear at this point whether this up-methylation directly translates into observable changes in gene expression (supplemental data), it is tempting to speculate that such an upmethylation was important for the evolution of the human brain. However, we cannot exclude that a general tendency towards a lower degree of methylation occurred on the chimpanzee lineage. It is furthermore unclear if the change in methylation patterns is especially pronounced in the human brain or if a rapid change in methylation patterns is typical of brain evolution in many mammals. Further work has to clarify these issues.

Methylation levels at selected CpG sites in the factor VIII and FGFR3 genes, in mature female and male germ cells: implications for male-driven evolution.

Transitional mutations at CpG dinucleotides account for approximately a third of all point mutations. These mutations probably arise through spontaneous deamination of 5-methylcytosine. Studies of CpG mutation rates in disease-linked genes, such as factor VIII and FGFR3, have indicated that they more frequently originate in male than in female germ cells. It has been speculated that these sex-biased mutation rates might be a consequence of sex-specific methylation differences between the female and the male germ lines. Using the bisulfite-based genomic-sequencing method, we investigated the methylation status of the human factor VIII and FGFR3 genes in mature male and female germ cells. With the exception of a single CpG, both genes were found to be equally and highly methylated in oocytes and spermatocytes. Whereas these observations strongly support the notion that DNA methylation is the major determining factor for recurrent CpG germ-line mutations in patients with hemophilia and achondroplasia, the higher mutation rate in the male germ line is apparently not a simple reflection of sex-specific methylation differences.

The epigenome : molecular hide and seek

1 Five Not Four: History and Significance of the Fifth Base (Douglas S Millar, Robin Holliday, and Geoffrey W Grigg).Summary.1.1 Historical Introduction.1.2 Sequencing 5-methylcytosine (5-mC) Residues in Genomic DNA.The Bisulfite Method.1.3 Gene Silencing.1.4 Development.1.5 Abnormal DNA Methylation in Cancer Cells.1.6 Nuclear Transfer.1.7 Aging.1.8 The Future.References.2 (Epi)genetic Signals: Towards a Human Genome Sequence of All Five Nucleotides (Walter Doerfler).Summary.2.1 A Linguistic Prologue.2.2 Towards the Complete Sequence of the Human Genome with Five Nucleotides.2.3 Patterns of DNA Methylation - the Scaffold for Building a Functional Genome.2.4 DNA Methylation Patterns in Segments of the Human Genome and in Viral Genomes.2.4.1 On Viral Genomes and Foreign DNA Integrates.2.4.2 DNA Methylation Patterns in the Human Genome.02.5 Ins ertions of Foreign DNA into Established Mammalian Genomes.2.6 De Novo Methylation of Integrated Foreign DNA.2.6.1 Ad12 Genomes in Hamster Tumor Cells.2.6.2 De Novo Methylation of Foreign DNA Integrated into the Mouse Genome by Homologous or Heterologous Recombination [23].2.7 Genome-wide Perturbations in the Mammalian Genome upon Foreign DNA Insertion.2.8 Outlook and Recommendations.References.3 Epi Meets Genomics: Technologies for Finding and Reading the 5th Base (Tim Hui-Ming Huang, Christoph Plass, Gangning Liang, and Peter W. Laird).Summary.13.1 The Development of 5th-Base Technologies.3.1.1 Unusual DNA-cutting Enzymes.3.1.2 A Unique Chemical Reaction that Modifies Methylated DNA.3.1.3 The Advance of 5th Base Technologies in Epigenomic Research.3.2 Restriction Landmark Genomic Scanning (RLGS): Finding the 5th-base Signposts in the Genomic Atlas.3.2.1 Principle.3.2.2 How Does RLGS Work?3.2.3 Applications.3.3 Methylation-sensitive Arbitrarily Primed (AP) PCR: Fishing for the 5th Bases in Genomic Ponds.3.3.1 Principle.3.3.2 How Does MS AP-PCR Work?3.3.3 Applications.3.4 Differential Methylation Hybridization (DMH): Identifying the 5th Bases in the Genomic Crossword Puzzle.3.4.1 Principle.3.4.2 How Does DMH Work?3.4.3 Applications.3.5 MethyLight: Finding 5th-base Patterns in Genomic Shadows.3.5.1 Principle.3.5.2 How Does MethyLight Work?3.5.3 Applications.3.6 Exploring the Epigenome.References.4 Mammalian Epigenomics: Reprogramming the Genome for Development and Therapy (Wolf Reik and Wendy Dean).Summary.4.1 Introduction.4.2 DNA Methylation.4.3 Histone Modifications.4.4 Imprinting.4.5 Reprogramming and Cloning.4.6 Epimutations and Epigenetic Inheritance.4.7 Epigenomics: The Future.4.7 Conclusions.References.5 At the Controls: Genomic Imprinting and the Epigenetic Regulation of Gene Expression (Anne Ferguson-Smith).Summary.5.1 Introduction.5.2 Genomic Imprinting.5.2.1 The Role of DNA Methylation in Imprinted Gene Expression.5.2.3 Organization of Imprinted Genes.5.2.4 The Mechanism of Imprinting at the Mouse Igf2r Imprinted Domain Requires a Cis-acting Noncoding Antisense Transcript Regulated by DNA Methylation (Fig. 5.2a).5.2.5 Imprinting at the Mouse Distal Chromosome 7 Domain Is Regulated by at Least Two Imprinting Control Regions (ICRs) Acting on Different Sets of Genes (Fig. 5.2b & c).5.2.6 The Mechanisms of Imprinting at the PWS/AS Imprinted Domain (Fig. 5.2d).5.3 DNA Methylation and Chromatin.5.4 X Inactivation.5.5 Prospects and Patterns.References.6 Epigenetic Trouble: Human Diseases Caused by Epimutations (Jorn Walter and Martina Paulsen).Summary.6.1 Introduction.6.2 Mechanisms of DNA Methylation.6.3 Molecular Recognition of Methylation Patterns.6.4 Rett Syndrome.6.5 ICF Syndrome.6.6 ATR-X Syndrome.6.7 Fragile-X Syndrome.6.8 Imprinting Syndromes.References.7 Liver or Broccoli? Foods Lasting Effect on Genome Methylation (Michael Fenech).Summary.7.1 Introduction.7.2 Important Dietary Sources of Folate, Vitamin B12, Choline, and Methionine.7.3 Evidence from in Vitro Cultures for the Role of Folic Acid in Genomic Stability of Human Cells.7.4 Evidence from in Vivo Studies for the Role of Folate and Vitamin B12 in Genomic Stability of Human Cells.7.5 Environmental and Genetic Factors that Determine the Bioavailability of Folate and Vitamin B12.7.6 Recommended Dietary Allowances (RDAs) for Folate and Vitamin B12 Based on Genomic Stability.7.7 Conclusion.References.8 Living Longer: The Aging Epigenome (Jean-Pierre Issa).Summary.8.1 Introduction.8.2 Methylation as a Mark of Epigenetic Silencing.8.3 The Dogma: Formation of Methylation Patterns.8.4 The Reality: Age-related Methylation and Epigenetic Mosaicism in Normal Epithelium.8.5 The Consequences: Methylation and Age-related Diseases.8.6 The Bottom Line: Clinical Implications.References.9 Digitizing Molecular Diagnostics: Current and Future Applications of Epigenome Technology (Sven Olek, Sabine Maier, Klaus Olek, and Alexander Olek).Summary.9.1 Introduction.9.2 Molecular Diagnostics.9.2.1 Advantages of Methylation as a Diagnostic Parameter.9.2.2 Cancer Management.9.2.3 Methylation, the Environment, and Lifestyle Diseases.9.2.4 Disease Gene Discovery.9.3 Tissue Engineering.9.3.1 The Development of Tissue Engineering.9.3.2 Complex Result Assessment in Tissue Engineering: an Unmet Need...9.3.3 ...That May Be Met by DNA-methylation Technologies.9.4 Methylation Therapy.9.4.1 Methylation Therapy.9.5 Agriculture.9.6 Outlook.References.

The cellular ratio of immune tolerance (immunoCRIT) is a definite marker for aggressiveness of solid tumors and may explain tumor dissemination patterns

The adaptive immune system is involved in tumor establishment and aggressiveness. Tumors of the ovaries, an immune-privileged organ, spread via transceolomic routes and rarely to distant organs. This is contrary to tumors of non-immune privileged organs, which often disseminate hematogenously to distant organs. Epigenetics-based immune cell quantification allows direct comparison of the immune status in benign and malignant tissues and in blood. Here, we introduce the “cellular ratio of immune tolerance” (immunoCRIT) as defined by the ratio of regulatory T cells to total T lymphocytes. The immunoCRIT was analyzed on 273 benign tissue samples of colorectal, bronchial, renal and ovarian origin as well as in 808 samples from primary colorectal, bronchial, mammary and ovarian cancers. ImmunoCRIT is strongly increased in all cancerous tissues and gradually augmented strictly dependent on tumor aggressiveness. In peripheral blood of ovarian cancer patients, immunoCRIT incrementally increases from primary diagnosis to disease recurrence, at which distant metastases frequently occur. We postulate that non-pathological immunoCRIT values observed in peripheral blood of immune privileged ovarian tumor patients are sufficient to prevent hematogenous spread at primary diagnosis. Contrarily, non-immune privileged tumors establish high immunoCRIT in an immunological environment equivalent to the bloodstream and thus spread hematogenously to distant organs. In summary, our data suggest that the immunoCRIT is a powerful marker for tumor aggressiveness and disease dissemination.

Methylation Analysis in Cancer

Aberrant DNA methylation is an early and common event in human cancers. Methylation acts as an epigenetic regulator of gene expression and is involved in cancer development as well as resistance to drug treatments. Specific methylation patterns have been shown for different cancer types and there is evidence that methylation can be used as a diagnostic tool. Several methods have been developed to study methylation on a genome wide basis. However they are labor intensive and can assess only a limited number of tissues at a time preventing the assessment of these genes in larger populations. Methylation microarrays now offer the possibility to validate these candidate genes statistically filling the gap between genome wide discovery methods and single gene assays which could be adjusted to routine clinical use. Here we show how all these methods can be combined to broaden our knowledge regarding DNA methylation and transform some of this information into powerful diagnostic tests.