Epigenetic regulatory elements associate with specific histone modifications to prevent silencing of telomeric genes

In eukaryotic cells, transgene expression levels may be limited by an unfavourable chromatin structure at the integration site. Epigenetic regulators are DNA sequences which may protect transgenes from such position effect. We evaluated different epigenetic regulators for their ability to protect transgene expression at telomeres, which are commonly associated to low or inconsistent expression because of their repressive chromatin environment. Although to variable extents, matrix attachment regions (MARs), ubiquitous chromatin opening element (UCOE) and the chicken cHS4 insulator acted as barrier elements, protecting a telomeric-distal transgene from silencing. MARs also increased the probability of silent gene reactivation in time-course experiments. Additionally, all MARs improved the level of expression in non-silenced cells, unlike other elements. MARs were associated to histone marks usually linked to actively expressed genes, especially acetylation of histone H3 and H4, suggesting that they may prevent the spread of silencing chromatin by imposing acetylation marks on nearby nucleosomes. Alternatively, an UCOE was found to act by preventing deposition of repressive chromatin marks. We conclude that epigenetic DNA elements used to enhance and stabilize transgene expression all have specific epigenetic signature that might be at the basis of their mode of actio

Stochastic models and numerical algorithms for a class of regulatory gene networks

Regulatory gene networks contain generic modules like those involving feedback loops, which are essential for the regulation of many biological functions. We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady state distributions of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in synthetic biology and in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loop

Proof of concept for microarray-based detection of DNA-binding oncogenes in cell extracts

The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein-DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput leve

Stochastic Models and Numerical Algorithms for a Class ofRegulatory Gene Networks

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido etal. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loop

High-level transgene expression by homologous recombination-mediated gene transfer

Gene transfer and expression in eukaryotes is often limited by a number of stably maintained gene copies and by epigenetic silencing effects. Silencing may be limited by the use of epigenetic regulatory sequences such as matrix attachment regions (MAR). Here, we show that successive transfections of MAR-containing vectors allow a synergistic increase of transgene expression. This finding is partly explained by an increased entry into the cell nuclei and genomic integration of the DNA, an effect that requires both the MAR element and iterative transfections. Fluorescence in situ hybridization analysis often showed single integration events, indicating that DNAs introduced in successive transfections could recombine. High expression was also linked to the cell division cycle, so that nuclear transport of the DNA occurs when homologous recombination is most active. Use of cells deficient in either non-homologous end-joining or homologous recombination suggested that efficient integration and expression may require homologous recombination-based genomic integration of MAR-containing plasmids and the lack of epigenetic silencing events associated with tandem gene copies. We conclude that MAR elements may promote homologous recombination, and that cells and vectors can be engineered to take advantage of this property to mediate highly efficient gene transfer and expressio

Statistical significance of quantitative PCR

BACKGROUND: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. RESULTS: Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. CONCLUSION: Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision

Proof of concept for microarray-based detection of DNA-binding oncogenes in cell extracts

The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein–DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput level

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Measurement of the top quark-pair production cross section with ATLAS in pp collisions at \sqrt{s}=7\TeV

A measurement of the production cross-section for top quark pairs(\ttbar) in $pp$ collisions at \sqrt{s}=7 \TeV is presented using data recorded with the ATLAS detector at the Large Hadron Collider. Events are selected in two different topologies: single lepton (electron $e$ or muon $\mu$) with large missing transverse energy and at least four jets, and dilepton ($ee$, $\mu\mu$ or $e\mu$) with large missing transverse energy and at least two jets. In a data sample of 2.9 pb-1, 37 candidate events are observed in the single-lepton topology and 9 events in the dilepton topology. The corresponding expected backgrounds from non-\ttbar Standard Model processes are estimated using data-driven methods and determined to be $12.2 \pm 3.9$ events and $2.5 \pm 0.6$ events, respectively. The kinematic properties of the selected events are consistent with SM \ttbar production. The inclusive top quark pair production cross-section is measured to be \sigmattbar=145 \pm 31 ^{+42}_{-27} pb where the first uncertainty is statistical and the second systematic. The measurement agrees with perturbative QCD calculations.Comment: 30 pages plus author list (50 pages total), 9 figures, 11 tables, CERN-PH number and final journal adde

Inclusive search for same-sign dilepton signatures in pp collisions at root s=7 TeV with the ATLAS detector

An inclusive search is presented for new physics in events with two isolated leptons (e or mu) having the same electric charge. The data are selected from events collected from p p collisions at root s = 7 TeV by the ATLAS detector and correspond to an integrated luminosity of 34 pb(-1). The spectra in dilepton invariant mass, missing transverse momentum and jet multiplicity are presented and compared to Standard Model predictions. In this event sample, no evidence is found for contributions beyond those of the Standard Model. Limits are set on the cross-section in a fiducial region for new sources of same-sign high-mass dilepton events in the ee, e mu and mu mu channels. Four models predicting same-sign dilepton signals are constrained: two descriptions of Majorana neutrinos, a cascade topology similar to supersymmetry or universal extra dimensions, and fourth generation d-type quarks. Assuming a new physics scale of 1 TeV, Majorana neutrinos produced by an effective operator V with masses below 460 GeV are excluded at 95% confidence level. A lower limit of 290 GeV is set at 95% confidence level on the mass of fourth generation d-type quarks