Veränderungen der DNA-Methylierung in Patienten mit AHCY-Defizienz

Die S-adenosyl-L-Homocysteinhydrolase (AHCY)-Defizienz ist eine seltene autosomal rezessive Erbkrankheit, bei der Mutationen im AHCY-Gen die Funktionsfähigkeit des kodierten Enzyms beeinträchtigen. Diese Krankheit führt zu Symptomen wie Entwicklungsverzögerungen, mentaler Retardierung und Myopathie. In der vorliegenden Arbeit wurde der Einfluss der AHCY-Defizienz auf die Methylierung der DNA in Blutproben und Fibroblasten von Patienten mit AHCY-Defizienz, sowie in HEK293- und HepG2-Zelllinien mit AHCY-Knockdown untersucht. Der gesamtgenomische Methylierungsstatus wurde mit Hilfe des MethylFlash ™ Methylated DNA Quantification Kit (Epigentek) bei drei Patienten-Blutproben festgestellt. In den Blutproben von sieben Patienten und Fibroblasten von einem Patienten wurde die Methylierung von DMRs sieben geprägter Gene (GTL2, H19, LIT1, MEST, NESPAS, PEG3, SNRPN) und zwei repetitiver Elemente (Alu, LINE1) mittels Bisulfit-Pyrosequenzierung quantifiziert und durch High Resolution Melting-Analyse bestätigt. Zusätzlich wurde eine genomweite Methylierungsanalyse mit dem Infinium® HumanMethylation450 BeadChip (Illumina) für vier Patientenproben durchgeführt und die Expression von AHCY in Fibroblasten mittels Expressions-qPCR und QUASEP-Analyse untersucht. Die Methylierungsanalysen ergaben eine Hypermethylierung der gesamtgenomischen DNA und stochastische Hypermethylierungen von DMRs geprägter Gene bei einigen Patienten. Die HEK293- und HepG2-Zelllinien wiesen dagegen hauptsächlich stochastische Hypomethylierungen an einigen DMRs geprägter Gene und LINE1-Elementen auf. Die genomweite Methylierungsarray-Analyse konnte die Ergebnisse der Bisulfit-Pyrosequenzierung nicht bestätigen. Die Expressionsanalysen der AHCY-defizienten Fibroblasten zeigten eine verminderte Expression von AHCY, wobei beide Allele etwa gleich stark transkribiert wurden. Die Ergebnisse deuten darauf hin, dass die AHCY-Defizienz eine gute Modellerkrankung für die Untersuchung biologischer Konsequenzen von Methylierungsstörungen im Rahmen der Epigenetik-Forschung sein könnte. Sie ist unseres Wissens die erste monogene Erkrankung mit symptomaler DNA-Hypermethylierung beim Menschen.

Distinct DNA methylation patterns in cirrhotic liver and hepatocellular carcinoma

Abberrant DNA methylation is one of the hallmarks of cancerogenesis. Our study aims to delineate differential DNA methylation in cirrhosis and hepatic cancerogenesis. Patterns of methylation of 27,578 individual CpG loci in 12 hepatocellular carcinomas (HCCs), 15 cirrhotic controls and 12 normal liver samples were investigated using an array-based technology. A supervised principal component analysis (PCA) revealed 167 hypomethylated loci and 100 hypermethylated loci in cirrhosis and HCC as compared to normal controls. Thus, these loci show a "cirrhotic" methylation pattern that is maintained in HCC. In pairwise supervised PCAs between normal liver, cirrhosis and HCC, eight loci were significantly changed in all analyses differentiating the three groups (p < 0.0001). Of these, five loci showed highest methylation levels in HCC and lowest in control tissue (LOC55908, CELSR1, CRMP1, GNRH2, ALOX12 and ANGPTL7), whereas two loci showed the opposite direction of change (SPRR3 and TNFSF15). Genes hypermethylated between normal liver to cirrhosis, which maintain this methylation pattern during the development of HCC, are depleted for CpG islands, high CpG content promoters and polycomb repressive complex 2 (PRC2) targets in embryonic stem cells. In contrast, genes selectively hypermethylated in HCC as compared to nonmalignant samples showed an enrichment of CpG islands, high CpG content promoters and PRC2 target genes (p < 0.0001). Cirrhosis and HCC show distinct patterns of differential methylation with regards to promoter structure, PRC2 targets and CpG islands.

A Faster Circular Binary Segmentation Algorithm for the Analysis of Array CGH Data

Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number (Olshen {\it et~al}, 2004). The algorithm tests for change-points using a maximal $t$-statistic with a permutation reference distribution to obtain the corresponding $p$-value. The number of computations required for the maximal test statistic is $O(N^2),$ where $N$ is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster. algorithm. Results: We present a hybrid approach to obtain the $p$-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analysis of array CGH data from a breast cancer cell line to show the impact of the new approaches on the analysis of real data. Availability: An R (R Development Core Team, 2006) version of the CBS algorithm has been implemented in the ``DNAcopy'' package of the Bioconductor project (Gentleman {\it et~al}, 2004). The proposed hybrid method for the $p$-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.

A Pseudolikelihood Approach for Simultaneous Analysis of Array Comparative Genomic Hybridizations (aCGH)

DNA sequence copy number has been shown to be associated with cancer development and progression. Array-based Comparative Genomic Hybridization (aCGH) is a recent development that seeks to identify the copy number ratio at large numbers of markers across the genome. Due to experimental and biological variations across chromosomes and across hybridizations, current methods are limited to analyses of single chromosomes. We propose a more powerful approach that borrows strength across chromosomes and across hybridizations. We assume a Gaussian mixture model, with a hidden Markov dependence structure, and with random effects to allow for intertumoral variation, as well as intratumoral clonal variation. For ease of computation, we base estimation on a pseudolikelihood function. The method produces quantitative assessments of the likelihood of genetic alterations at each clone, along with a graphical display for simple visual interpretation. We assess the characteristics of the method through simulation studies and through analysis of a brain tumor aCGH data set. We show that the pseudolikelihood approach is superior to existing methods both in detecting small regions of copy number alteration and in accurately classifying regions of change when intratumoral clonal variation is present.

EXPLORATION, NORMALIZATION, AND GENOTYPE CALLS OF HIGH DENSITY OLIGONUCLEOTIDE SNP ARRAY DATA

In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.

A modular LHC built on the DNA three-way junction

A light-harvesting complex composed of a p-stacked multichromophoric array in a DNA three-way junction is described. The modular design allows for a ready exchange of non-covalently attached energy acceptors

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

Nano-mechanical transduction of polymer micro-cantilevers to detect bio-molecular interactions

Using variothermal polymer micro-injection molding, disposable arrays of eight polymer micro-cantilevers each 500 μm long, 100 μm wide and 25 μm thick were fabricated. The present study took advantage of an easy flow grade polypropylene. After gold coating for optical read-out and asymmetrical sensitization, the arrays were introduced into the Cantisens(®) Research system to perform mechanical and functional testing. We demonstrate that polypropylene cantilevers can be used as biosensors for medical purposes in the same manner as the established silicon ones to detect single-stranded DNA sequences and metal ions in real-time. A differential signal of 7 nm was detected for the hybridization of 1 μM complementary DNA sequences. For 100 nM copper ions the differential signal was found to be (36 ± 5) nm. Nano-mechanical sensing of medically relevant, nanometer-size species is essential for fast and efficient diagnosis.

A lung-on-chip array with an integrated bio-inspired respiration mechanism

We report about a lung-on-chip array that mimics the pulmonary parenchymal environment, including the thin, alveolar barrier and the three-dimensional cyclic strain induced by the breathing movements. A micro-diaphragm used to stretch the alveolar barrier is inspired by the in-vivo diaphragm, the main muscle responsible for inspiration. The design of this device aims not only at best reproducing the in-vivo conditions found in the lung parenchyma, but also at making its handling easy and robust. An innovative concept, based on the reversible bonding of the device, is presented that enables to accurately control the concentration of cells cultured on the membrane by easily accessing both sides of the membranes. The functionality of the alveolar barrier could be restored by co-culturing epithelial and endothelial cells that formed tight monolayers on each side of a thin, porous and stretchable membrane. We showed that cyclic stretch significantly affects the permeability properties of epithelial cell layers. Furthermore, we could also demonstrate that the strain influences the metabolic activity and the cytokine secretion of primary human pulmonary alveolar epithelial cells obtained from patients. These results demonstrate the potential of this device and confirm the importance of the mechanical strain induced by the breathing in pulmonary research.

Mechanical Loading Promoted Discogenic Differentiation of Human Mesenchymal Stem Cells Incorporated in 3D-PEG Scaffolds with RhGDF5 and RGD

Hydrogels have been described as ideal scaffolds for cells of 3D tissue constructs and hold strong promises with respect to in vitro 3D-cell-culture, where cells are isolated from native extracellular matrix (ECM). Synthesized polyethyleneglycol (PEG) hydrogels are appealing with regard to potential for cell therapy or as vehicles for drug delivery or even to regenerate tissue with similar hydrogel-like properties such as the nucleus pulposus of the intervertebral disc (IVD). Here, we tested whether incorporation of RGD motive would hinder discogenic differentiation of primary bone marrow-derived human mesenchymal stem cells (hMSCs) but favor proliferation of undifferentiated hMSCs. HMSCs were embedded in +RGD containing or without RGD PEG hydrogel and pre-conditioned with or without growth and differentiation factor-5 (rhGDF-5) for 13 days. Afterwards, all hMSCs-PEG gels were subsequently cyclically loaded (15% strain, 1Hz) for 5 consecutive days in a bioreactor to generate an IVD-like phenotype. Higher metabolic activity (resazurin assay) was found in groups with rhGDF5 in both gel types with and without RGD. Cell viability and morphology measured by confocal laser microscopy and DNA content showed decreased values (~60%) after 18 days of culture. Real-time RT-PCR of an array of 15 key genes suspected to be distinctive for IVD cells revealed moderate response to rhGDF5 and mechanical loading as also shown by histology staining. Preconditioning and mechanical loading showed relatively moderate responses revealed from both RT-PCR and histology although hMSCs were demonstrated to be potent to differentiate into chondrocyte-progenitor cells in micro- mass and 3D alginate bead culture.

From Ribbons to Networks: Hierarchical Organization of DNA-Grafted Supramolecular Polymers

DNA-grafted supramolecular polymers (SPs) allow the programmed organization of DNA in a highly regular, one-dimensional array. Oligonucleotides are arranged along the edges of pyrene-based helical polymers. Addition of complementary oligonucleotides triggers the assembly of individual nanoribbons resulting in the development of extended supramolecular networks. Network formation is enabled by cooperative coaxial stacking interactions of terminal GC base pairs. The process is accompanied by structural changes in the pyrene polymer core that can be followed spectroscopically. Network formation is reversible, and disassembly into individual ribbons is realized either via thermal denaturation or by addition of a DNA separator strand.

Supramolecular Polymers in DNA Nanotechnology

Creation of biocompatible functional materials is an important task in supramolecular chemistry. In this contribution, we report on noncovalent synthesis of DNA-grafted supramolecular polymers (SPs). DNA-grafted SPs enable programmed arrangement of oligonucleotides in a regular, tightly packed one-dimensional array. Further interactions of DNA-grafted SPs with complementary DNA strands leads to the formation of networks through highly cooperative G-C blunt-end stacking interactions. The structural changes in the polymeric core enable to monitor spectroscopically the stepwise formation of networks. Such stimuli-responsive supramolecular networks may lead to the development of DNA-based smart materials.

Clinical relevance of polymorphic DNA copy number variation (CNV) in African American women with stage I-II breast cancer

Objectives. The chief goal of this study was to analyze copy number variation (CNV) in breast cancer tumors from 25 African American women with early stage breast cancer (BC) using molecular inversion probes (MIP) in order to: (1) compare the degree of CNV in tumors compared to normal lymph nodes, and (2) determine whether gains and/or losses of genes in specific chromosomes differ between pathologic subtypes of breast cancer defined by known prognostic markers, (3) determine whether gains/losses in CN are associated with known oncogenes or tumor suppressor genes, and (4) determine whether increased gains/losses in CN for specific chromosomes were associated with differences in breast cancer recurrence. ^ Methods. Twenty to 37 nanograms of DNA extracted from 25 formalin-fixed paraffin embedded (FFPE) tumor samples and matched normal lymph nodes were added to individual tubes. Oligonucleotide probes with recognition sequences at each terminus were hybridized with a genomic target sequence to form a circular structure. Probes are released from genomic DNA obtained from FFPE samples, and those which have been correctly "circularized" in the proper allele/nucleotide reaction combination are amplified using polymerase chain reaction (PCR) primers. Amplicons were fluorescently labeled and the tag sequences released from the genome homology regions by treatment with uracil-N-glycosylase to cleave the probe at the site where uracils are present, and detected using a complementary tag array developed by Affymetrix. ^ Results. Analysis of CN gains and losses from tumors and normal tissues showed marked differences in tumors with numerous chromosomes affected. Similar changes were not observed in normal lymph nodes. When tumors were stratified into four groups based on expression or lack of expression of the estrogen receptor and HER2/neu, distinct patterns of CNV for different chromosomes were observed. Gains or losses in CN for specific chromosomes correlated with amplifications/deletions of particular oncogenes or tumor suppressor genes (i.e. such as found on chromosome 17) known to be associated with aggressive tumor phenotype and poor prognosis. There was a trend for increases in CN observed for chromosome 17 to correlate inversely with time to recurrence of BC (p=0.14 for trend). CNV was also observed for chromosomes 5, 8, 10, 11, and 16, which are known sites for several breast cancer susceptibility alleles. ^ Conclusions. This study is the first to validate the MIP technique, to correlate differences in gene expression with known prognostic tumor markers, and to correlate significant increases/decreases in CN with known tumor markers associated with prognosis. The results of this study may have far reaching public health implications towards identifying new high-risk groups based on genomic differences in CNP, both with respect to prognosis and response to therapy, and to eventually identify new therapeutic targets for prevention and treatment of this disease. ^