Modelling of complex biological systems in the context of genomics: an account of a multidisciplinary thematic seminar held in Montpellier (France) in April 2005

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Optimizing the Design of Oligonucleotides for Homology Directed Gene Targeting

BACKGROUND: Gene targeting depends on the ability of cells to use homologous recombination to integrate exogenous DNA into their own genome. A robust mechanistic model of homologous recombination is necessary to fully exploit gene targeting for therapeutic benefit. METHODOLOGY/PRINCIPAL FINDINGS: In this work, our recently developed numerical simulation model for homology search is employed to develop rules for the design of oligonucleotides used in gene targeting. A Metropolis Monte-Carlo algorithm is used to predict the pairing dynamics of an oligonucleotide with the target double-stranded DNA. The model calculates the base-alignment between a long, target double-stranded DNA and a probe nucleoprotein filament comprised of homologous recombination proteins (Rad51 or RecA) polymerized on a single strand DNA. In this study, we considered different sizes of oligonucleotides containing 1 or 3 base heterologies with the target; different positions on the probe were tested to investigate the effect of the mismatch position on the pairing dynamics and stability. We show that the optimal design is a compromise between the mean time to reach a perfect alignment between the two molecules and the stability of the complex. CONCLUSION AND SIGNIFICANCE: A single heterology can be placed anywhere without significantly affecting the stability of the triplex. In the case of three consecutive heterologies, our modeling recommends using long oligonucleotides (at least 35 bases) in which the heterologous sequences are positioned at an intermediate position. Oligonucleotides should not contain more than 10% consecutive heterologies to guarantee a stable pairing with the target dsDNA. Theoretical modeling cannot replace experiments, but we believe that our model can considerably accelerate optimization of oligonucleotides for gene therapy by predicting their pairing dynamics with the target dsDNA

Classification of microarray data using gene networks

BACKGROUND: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation. RESULTS: We propose a method to integrate a priori the knowledge of a gene network in the analysis of gene expression data. The approach is based on the spectral decomposition of gene expression profiles with respect to the eigenfunctions of the graph, resulting in an attenuation of the high-frequency components of the expression profiles with respect to the topology of the graph. We show how to derive unsupervised and supervised classification algorithms of expression profiles, resulting in classifiers with biological relevance. We illustrate the method with the analysis of a set of expression profiles from irradiated and non-irradiated yeast strains. CONCLUSION: Including a priori knowledge of a gene network for the analysis of gene expression data leads to good classification performance and improved interpretability of the results

French Roadmap for complex Systems 2008-2009

This second issue of the French Complex Systems Roadmap is the outcome of the Entretiens de Cargese 2008, an interdisciplinary brainstorming session organized over one week in 2008, jointly by RNSC, ISC-PIF and IXXI. It capitalizes on the first roadmap and gathers contributions of more than 70 scientists from major French institutions. The aim of this roadmap is to foster the coordination of the complex systems community on focused topics and questions, as well as to present contributions and challenges in the complex systems sciences and complexity science to the public, political and industrial spheres

DNA double-strand break mimicking molecules (Dbait) (a tool to disorganize damage signaling and inhibit DNA repair)

LE KREMLIN-B.- PARIS 11-BU Méd (940432101) / SudocSudocFranceF

Etude des variations du transcriptome après exposition aux rayons gamma chez Saccharomyces cerevisiae

L'exposition de la cellule à des rayonnements entraîne une réponse cellulaire dite radio- induite. D'une manière générale, celle-ci se traduit immédiatement par un arrêt (transitoire ou non) de la division cellulaire et par la réparation des lésions. Mon travail de thèse a consisté à étudier la réponse transcriptionnelle radio-induite à l'échelle génomique chez la levure S. cerevisiae. En utilisant la technologie des puces à ADN, nous avons comparé le transcriptome de cellules irradiées aux rayons gamma et non irradiées. Une première analyse a porté sur l'état transcriptionnel de 126 gènes, après exposition d'une souche diploïde à deux doses résultant en une survie cellulaire très différente. Cette étude, réalisée à différents temps après irradiation, pendant la période d'arrêt du cycle cellulaire, a mis en évidence un groupe de gènes potentiellement co-régulés. L'analyse globale du transcriptome après exposition aux rayons gamma a été réalisée en comparant la réponse transcriptionnelle radio-induite dans les trois types cellulaires de S. cerevisiae: la souche diploïde Mata/Mata et les souches haploïdes Mata et Mata. La dose à laquelle ont été exposées les cellules conduit à une différence de radiosensibilité selon la ploïdie des cellules. Un des résultats clé de cette analyse est la mise en évidence de l'induction spécifique de l'expression des gènes sub-télomériques dans les souches haploïdes. Une approche différente, rentrant dans la thématique de la réponse biologique aux faibles doses d'irradiation, a consisté à irradier les cellules durant 12 générations à des doses où aucune létalité ni retard de croissance ou modifications du matériel génétique n'étaient observés. Cette étude, assistée de plusieurs méthodes statistiques, montre l'existence d'un groupe de gènes, dont l'expression varie après une telle exposition et dont les produits sont localisés préférentiellement aux mitochondries.Exposure of cells to ionising radiation leads to the so-called radio-induced cellular response. In general, this response consisted in a cell cycle arrest and in the repair of the induced lesions. My PhD work consisted of a study of genome-wide radio-induced transcriptional response in the budding yeast Saccharomyces cerevisiae. Using DNA microarray technology, we compared genome-wide transcription levels in gamma-irradiated and unirradiated cells. The first sub-genomic analysis was carried out on 126 genes, after irradiation of diploid cells at two different doses that led to very different survival rates. The transcription level of the 126 genes was studied at different time points following irradiation and throughout the entire period of cell cycle arrest. It revealed that a group of genes are potentially co-regulated during the radio-induced cellular response. The transcriptional genome-wide analysis following gamma irradiation was carried out on three different S. cerevisiae cell types: the Mata/Mata diploid strain and the two Mata and Mata haploid strains. Exposure of these strains to the same level of ionising radiation led to very different rates of survival level. A major result of the analysis of these experiments was the demonstration that a specific set of sub-telomeric genes is specifically radio-induced in haploid strains. Using a different approach, we measured biological response to low levels of irradiation. Cells were irradiated during 12 generations at doses that neither led to any detectable lethality nor modifications of the genetic material. This study, which employed several statistical method, showed irradiation-induced changes at the transcription level for a group of genes whose products are preferentially located in the mitochondrion.ORSAY-PARIS 11-BU Sciences (914712101) / SudocSudocFranceF