Design and evaluation of a panel os single-nucleotide polymorphisms in microRNA genomic regions for association studies in human disease

MicroRNAs (miRNA) are recognized posttranscriptional gene repressors involved in the control of almost every biological process. Allelic variants in these regions may be an important source of phenotypic diversity and contribute to disease susceptibility. We analyzed the genomic organization of 325 human miRNAs (release 7.1, miRBase) to construct a panel of 768 single-nucleotide polymorphisms (SNPs) covering approximately 1 Mb of genomic DNA, including 131 isolated miRNAs (40%) and 194 miRNAs arranged in 48 miRNA clusters, as well as their 5-kb flanking regions. Of these miRNAs, 37% were inside known protein-coding genes, which were significantly associated with biological functions regarding neurological, psychological or nutritional disorders. SNP coverage analysis revealed a lower SNP density in miRNAs compared with the average of the genome, with only 24 SNPs located in the 325 miRNAs studied. Further genotyping of 340 unrelated Spanish individuals showed that more than half of the SNPs in miRNAs were either rare or monomorphic, in agreement with the reported selective constraint on human miRNAs. A comparison of the minor allele frequencies between Spanish and HapMap population samples confirmed the applicability of this SNP panel to the study of complex disorders among the Spanish population, and revealed two miRNA regions, hsa-mir-26a-2 in the CTDSP2 gene and hsa-mir-128-1 in the R3HDM1 gene, showing geographical allelic frequency variation among the four HapMap populations, probably because of differences in natural selection. The designed miRNA SNP panel could help to identify still hidden links between miRNAs and human disease.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Error and attack tolerance of layered complex networks.

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of five examples of two-layer complex systems: three real-life data sets in the fields of communication (the Internet), transportation (the European railway system), and biology (the human brain), and two models based on random graphs. In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multi-layer systems are much more vulnerable to errors and intentional attacks than they appear from a single layer perspective.

Analysis of variables that are not directly observable: influence on decision-making during the research process

The sample dimension, types of variables, format used for measurement, and construction of instruments to collect valid and reliable data must be considered during the research process. In the social and health sciences, and more specifically in nursing, data-collection instruments are usually composed of latent variables or variables that cannot be directly observed. Such facts emphasize the importance of deciding how to measure study variables (using an ordinal scale or a Likert or Likert-type scale). Psychometric scales are examples of instruments that are affected by the type of variables that comprise them, which could cause problems with measurement and statistical analysis (parametric tests versus non-parametric tests). Hence, investigators using these variables must rely on suppositions based on simulation studies or recommendations based on scientific evidence in order to make the best decisions.

Targeting of DNA polymerase to the adenovirus origin of DNA replication by interaction with nuclear factor I.

Efficient initiation by the DNA polymerase of adenovirus type 2 requires nuclear factor I (NFI), a cellular sequence-specific transcription factor. Three functions of NFI--dimerization, DNA binding, and activation of DNA replication--are colocalized within the N-terminal portion of the protein. To define more precisely the role of NFI in viral DNA replication, a series of site-directed mutations within the N-terminal domain have been generated, thus allowing the separation of all three functions contained within this region. Impairment of the dimerization function prevents sequence-specific DNA binding and in turn abolishes the NFI-mediated activation of DNA replication. NFI DNA-binding activity, although necessary, is not sufficient to activate the initiation of adenovirus replication. A distinct class of NFI mutations that abolish the recruitment of the viral DNA polymerase to the origin also prevent the activation of replication. Thus, a direct interaction of NFI with the viral DNA polymerase complex is required to form a stable and active preinitiation complex on the origin and is responsible for the activation of replication by NFI.

Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

Analysis of antiviral immunity in primary and chronic infections

Several evidences in humans underscored the contribution of CD4 and CD8 T-cell responses in controlling viral and bacterial infections. However, CD4 and CD8 Τ cells have distinct and specific effector functions leading to a hierarchical importance in responding to different types of pathogens. In this context, the present work aimed to investigate distinct CD8 T-cell features potentially influencing T-cell efficacy against viral infection. To achieve this-objective, CD8 Τ cells derived from HIV-infected patients and healthy donors harbouring virus-specific immune responses or immunized with an HTV vaccine candidate were studied. In particular, we performed a comprehensive cross-sectional and longitudinal analysis to characterize the function, the phenotype and the functional avidity of HIV-specific CD8 Τ cells during acute (PHI) and chronic infection and, in particular, we investigated immunological parameters potentially associated with the functional avidity of HIV-specific CD8 Τ cells. In addition, we studied the expression pattern of co-inhibitory molecules and the influence of CD 160 on the functions of CD8 Τ cells in absence of chronic infections. From these analyses we observed that the functional avidity of HIV-specific CD8 T- cell responses was significantly lower in acute than in chronic infection, but was not different between chronic progressive and non-progressive patients. Functional avidity remained low after several years of antiretroviral therapy in PHI patients, but increased in patients experiencing a virus rebound following treatment interruption in association with a massive renewal of the global CD8 complementarity-determining region 3 of the TCR. The functional avidity was also directly associated to T-cell exhaustion. In individuals with no sign of HIV or Hepatitis A, Β or C virus infection, CD8 Τ cells expressed higher levels of co-inhibitory molecules than CD4 Τ cells and this was dependent on the stage of T-cell differentiation and activation. The expression of CD 160 impaired the proliferation capacity and IL-2 production of CD8 Τ cells and was reduced upon CD8 T-cell activation, entitling CD 160 as unique marker of CD8 T-cell exhaustion. The CD 160 blockade restored the proliferation capacity of virus-specific CD8 Τ cells providing a potential new target for immunotherapy. All together, these results expand our knowledge regarding the interplay between the immune system and the viruses. - De nombreuses études chez l'Homme ont mis en évidence la contribution des réponses cellulaires Τ CD4 et CD8 dans le contrôle des infections virales et bactériennes. En particulier, les lymphocytes Τ ont différentes fonctions effectrices spécifiques qui leur confèrent un rôle clé lors d'infections par différents pathogènes. Ce travail vise à étudier différentes caractéristiques des cellules Τ CD8 affectant l'efficacité des réponses cellulaires contre les virus. Pour atteindre cet objectif nous avons étudié les cellules Τ CD8 provenant de patients infectés par le VIH et de donneurs sains avec des réponses immunitaires naturelles ou vaccinales contre des virus. Nous avons effectué plusieurs analyses transversales et longitudinales des fonctions, du phénotype et de l'avidité fonctionnelle des lymphocytes Τ CD8 spécifiques au VIH au cours d'infections aiguës et chroniques; en particulier, nous avons étudié les paramètres immunologiques qui pourraient être associés à l'avidité fonctionnelle. De plus, nous avons investigué le profil d'expression des principales molécules co-inhibitrices et en particulier le rôle du CD 160 dans les fonctions des lymphocytes Τ CD8. Sur la base de ces analyses, nous avons constaté que l'avidité fonctionnelle des cellules Τ CD8 spécifiques au VIH était significativement plus faible lors infections aiguës que lors d'infections chroniques, mais n'était, par contre, pas différente entre les patients avec des infections chroniques progressives et non progressives. L'avidité fonctionnelle reste faible après plusieurs années de traitement antirétroviral, mais augmente chez les patients subissant un rebond viral, et donc exposés à des hautes virémies, suite à l'interruption du traitement. Cette augmentation d'avidité des lymphocytes Τ CD8, liée à un épuisement fonctionnel accru, était quantitativement directement associée à un renouvellement massif du TCR. Indépendamment de l'infection par le VIH, les cellules Τ CD8 expriment des niveaux plus élevés de molécules co-inhibitrices (PD-1, 2B4 et CD 160) par rapport aux cellules Τ CD4 et ceci dépend de leur stade de différenciation et d'activation. En particulier, CD 160 semble être un marqueur clé d'épuisement cellulaire des cellules Τ CD8, et donc une nouvelle cible potentielle pour l'immunothérapie, car a) son expression réduit la capacité proliférative et la production d'IL-2 b) CD 160 diminue suite à 1'activation et c) le blocage de CD 160 redonne la capacité proliférative aux cellules Τ CD8 spécifiques aux virus. - Le système immunitaire est un ensemble de cellules, tissus et organes indispensables pour limiter l'entrée des pathogènes à travers la peau et les muqueuses. Parmi les différentes cellules composant le système immunitaire, les cellules Τ CD4 et CD8 sont fondamentales pour le contrôle des infections virales et bactériennes. Les moyens pour combattre les différents pathogènes peuvent être cependant très variables. Les cellules Τ CD8, qui sont indispensables pour la lutte contre les virus, peuvent avoir différents niveaux de sensibilité; les cellules qui répondent à de faibles quantités d'antigène ont une forte sensibilité. Suite à une première infection virale, les cellules Τ CD8 ont une sensibilité plus faible que lors d'expositions répétées au même virus. En effet, la réexposition au pathogène induit une augmentation de sensibilité, grâce au recrutement et/ou à l'expansion de cellules Τ dotées d'une sensibilité plus élevée. Les cellules Τ CD8 avec une plus haute sensibilité semblent être caractérisées par une perte de fonctionnalité (épuisement fonctionnel associé à une haute expression de molécules dites inhibitrices). En absence d'infection, la fonction des molécules inhibitrices n'est pas encore clairement définie. Les cellules Τ CD8 montrent un niveau d'expression plus élevé de ces molécules par rapport aux cellules Τ CD4. Ceci dépend de l'état des cellules. Parmi ces molécules, le CD160 est associé à l'incapacité des cellules à proliférer et à produire de l'IL-2, une protéine importante pour la prolifération et la survie cellulaire. L'incapacité des cellules exprimant le CD 160 à proliférer en réponse à des virus peut être restaurée par le blocage fonctionnel du récepteur CD 160. Cette étude étoffe notre connaissance du rôle des cellules Τ CD8 ainsi que des conséquences induites par leur épuisement fonctionnel. Ces informations sont fondamentales pour le développement de nouvelles stratégies thérapeutiques et vaccinales.

A pseudo-spectral method for simulating of poro-elastic seismic wave propagation in complex borehole environments

We present a novel numerical approach for the comprehensive, flexible, and accurate simulation of poro-elastic wave propagation in cylindrical coordinates. An important application of this method is the modeling of complex seismic wave phenomena in fluid-filled boreholes, which represents a major, and as of yet largely unresolved, computational problem in exploration geophysics. In view of this, we consider a numerical mesh consisting of three concentric domains representing the borehole fluid in the center, the borehole casing and the surrounding porous formation. The spatial discretization is based on a Chebyshev expansion in the radial direction, Fourier expansions in the other directions, and a Runge-Kutta integration scheme for the time evolution. A domain decomposition method based on the method of characteristics is used to match the boundary conditions at the fluid/porous-solid and porous-solid/porous-solid interfaces. The viability and accuracy of the proposed method has been tested and verified in 2D polar coordinates through comparisons with analytical solutions as well as with the results obtained with a corresponding, previously published, and independently benchmarked solution for 2D Cartesian coordinates. The proposed numerical solution also satisfies the reciprocity theorem, which indicates that the inherent singularity associated with the origin of the polar coordinate system is handled adequately.

Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Genomic roles of the HCF transcriptional regulator in "Drosophila"

Abstract : Transcriptional regulation is the result of a combination of positive and negative effectors, such as transcription factors, cofactors and chromatin modifiers. During my thesis project I studied chromatin association, and transcriptional and cell cycle regulatory functions of dHCF, the Drosophila homologue of the human protein HCF-1 (host cell factor-1). The human and Drosophila HCF proteins are synthesized as large polypeptides that are cleaved into two subunits (HCFN and HCFC), which remain associated with one another by non covalent interactions. Studies in mammalian cells over the past 20 years have been devoted to understanding the cellular functions of HCF-1 and have revealed that it is a key regulator of transcription and cell cycle regulation. In human cells, HCF-1 interacts with the histone methyltransferase Set1/Ash2 and MLL/Ash2 complexes and the histone deacetylase Sin3 complex, which are involved in transcriptional activation and repression, respectively. HCF-1 is also recruited to promoters to regulate G1 -to-S phase progression during the cell cycle by the activator transcription factors E2F1 and E2F3, and by the repressor transcription factor E2F4. HCF-1 protein structure and these interactions between HCP-1 and E2F transcriptional regulator proteins are also conserved in Drosophila. In this doctoral thesis, I use proliferating Drosophila SL2 cells to study both the genomic-binding sites of dHCF, using a combination of chromatin immunoprecipitation and ultra high throughput sequencing (ChIP-seq) analysis, and dHCF regulated genes, employing RNAi and microarray expression analysis. I show that dHCF is bound to over 7500 chromosomal sites in proliferating SL2 cells, and is located at +-200 bp relative to the transcriptional start sites of about 30% of Drosophila genes. There is also a direct relationship between dHCF promoter association and promoter- associated transcriptional activity. Thus, dHCF binding levels at promoters correlated directly with transcriptional activity. In contrast, expression studies showed that dHCF appears to be involved in both transcriptional activation and repression. Analysis of dHCF-binding sites identified nine dHCF-associated motifs, four of them linked dHCF to (i) two insulator proteins, GAGA and BEAF, (ii) the E-box motif, and (iii) a degenerated TATA-box. The dHCF-associated motifs allowed the organization of the dHCF-bound genes into five biological processes: differentiation, cell cycle and gene expression, regulation of endocytosis, and cellular localization. I further show that different mechanisms regulate dHCF association with chromatin. Despite that after dHCF cleavage the dHCFN and dHCFC subunits remain associated, the two subunits showed different affinities for chromatin and differential binding to a set of tested promoters, suggesting that dHCF could target specific promoters through each of the two subunits. Moreover, in addition to the interaction between dHCF and E2F transcription factors, the dHCF binding pattern is correlated with dE2F2 genomic 4 distribution. I show that dE2F factors are necessary for recruitment of dHCF to the promoter of a set of dHCF regulated genes. Therefore dHCF, as in mammals, is involved in regulation of G1 to S phase progression in collaboration with the dE2Fs transcription factors. In addition, gene expression arrays reveal that dHCF could indirectly regulate cell cycle progression by promoting expression of genes involved in gene expression and protein synthesis, and inhibiting expression of genes involved in cell-cell adhesion. Therefore, dHCF is an evolutionary conserved protein, which binds to many specific sites of the Drosophila genome via interaction with DNA of chromatin-binding proteins to regulate the expression of genes involved in many different cellular functions. Résumé : La regulation de la transcription est le résultat des effets positifs et négatifs des facteurs de transcription, cofacteurs et protéines effectrices qui modifient la chromatine. Pendant mon projet de thèse, j'ai étudié l'association a la chromatine, ainsi que la régulation de la transcription et du cycle cellulaire par dHCF, l'homologue chez la drosophile de la protéine humaine HCF-1 (host cell factor-1). Chez 1'humain et la V drosophile, les deux protéines HCF sont synthétisées sous la forme d'un long polypeptide, qui est ensuite coupé en deux sous-unités au centre de la protéine. Les deux sous-unités restent associées ensemble grâce a des interactions non-covalentes. Des études réalisées pendant les 20 dernières années ont permit d'établir que HCF-l et un facteur clé dans la régulation de la transcription et du cycle cellulaire. Dans les cellules humaines, HCF-1 active et réprime la transcription en interagissant avec des complexes de protéines qui activent la transcription en méthylant les histones (HMT), comme par Set1/Ash2 et MLL/Ash2, et d'autres complexes qui répriment la transcription et sont responsables de la déacétylation des histones (HDAC) comme la protéine Sin3. HCF-l est aussi recruté aux promoteurs par les activateurs de la transcription E2F l et E2F3a, et par le répresseur de la transcription E2F4 pour réguler la transition entre les phases G1 et S du cycle cellulaire. La structure de HCF-1 et les interactions entre HCF-l et les régulateurs de la transcription sont conservées chez la drosophile. Pendant ma these j'ai utilisé les cellules de la drosophile, SL2 en culture, pour étudier les endroits de liaisons de HCF-l à la chromatine, grâce a immunoprecipitation de la chromatine et du séquençage de l'ADN massif ainsi que les gènes régulés par dHCF 3 grâce a la technique de RNAi et des microarrays. Mes résultats on montré que dHCF se lie à environ 7565 endroits, et estimé a 1200 paire de bases autour des sites d'initiation de la transcription de 30% des gènes de la drosophile. J 'ai observe une relation entre dHCF et le niveau de la transcription. En effet, le niveau de liaison dHCF au promoteur corrèle avec l'activité de la transcription. Cependant, mes études d'expression ont montré que dHCF est implique dans le processus d'activation et mais aussi de répression de la transcription. L'analyse des séquences d'ADN liées par dHCF a révèle neuf motifs, quatre de ces motifs ont permis d'associer dl-ICF a deux protéines isolatrices GAGA et BEAF, au motif pour les E-boxes et a une TATA-box dégénérée. Les neuf motifs associes à dHCF ont permis d'associer les gènes lies par dHCF au promoteur a cinq processus biologiques: différentiation, cycle cellulaire, expression de gènes, régulation de l'endocytosis et la localisation cellulaire, J 'ai aussi montré qu'il y a plusieurs mécanismes qui régulent l'association de dHCF a la chromatine, malgré qu'après clivage, les deux sous-unites dHCFN and dHCFC, restent associées, elles montrent différentes affinités pour la chromatine et lient différemment un group de promoteurs, les résultats suggèrent que dHCF peut se lier aux promoteurs en utilisant chacune de ses sous-unitées. En plus de l'association de dHCF avec les facteurs de transcription dE2F s, la distribution de dHCF sur le génome corrèle avec celle du facteur de transcription dE2F2. J'ai aussi montré que les dE2Fs sont nécessaires pour le recrutement de dHCF aux promoteurs d'un sous-groupe de gènes régules par dHCF. Mes résultats ont aussi montré que chez la drosophile comme chez les humains, dl-ICF est implique dans la régulation de la progression de la phase G1 a la phase S du cycle cellulaire en collaboration avec dE2Fs. D'ailleurs, les arrays d'expression ont suggéré que dHCF pourrait réguler le cycle cellulaire de façon indirecte en activant l'expression de gènes impliqués dans l'expression génique et la synthèse de protéines, et en inhibant l'expression de gènes impliqués dans l'adhésion cellulaire. En conclusion, dHCF est une protéine, conservée dans l'évolution, qui se lie spécifiquement a beaucoup d'endroits du génome de Drosophile, grâce à l'interaction avec d'autres protéines, pour réguler l'expression des gènes impliqués dans plusieurs fonctions cellulaires.

Protein-binding microarrays: probing disease markers at the interface of proteomics and genomics.

DNA-binding proteins mediate a variety of crucial molecular functions, such as transcriptional regulation and chromosome maintenance, replication and repair, which in turn control cell division and differentiation. The roles of these proteins in disease are currently being investigated using microarray-based approaches. However, these assays can be difficult to adapt to routine diagnosis of complex diseases such as cancer. Here, we review promising alternative approaches involving protein-binding microarrays (PBMs) that probe the interaction of proteins from crude cell or tissue extracts with large collections of synthetic or natural DNA sequences. Recent studies have demonstrated the use of these novel PBM approaches to provide rapid and unbiased characterization of DNA-binding proteins as molecular markers of disease, for example cancer progression or infectious diseases.

Potentiation of polarized intestinal Caco-2 cell responsiveness to probiotics complexed with secretory IgA.

The precise mechanisms underlying the interaction between intestinal bacteria and the host epithelium lead to multiple consequences that remain poorly understood at the molecular level. Deciphering such events can provide valuable information as to the mode of action of commensal and probiotic microorganisms in the gastrointestinal environment. Potential roles of such microorganisms along the privileged target represented by the mucosal immune system include maturation prior, during and after weaning, and the reduction of inflammatory reactions in pathogenic conditions. Using human intestinal epithelial Caco-2 cell grown as polarized monolayers, we found that association of a Lactobacillus or a Bifidobacterium with nonspecific secretory IgA (SIgA) enhanced probiotic adhesion by a factor of 3.4-fold or more. Bacteria alone or in complex with SIgA reinforced transepithelial electrical resistance, a phenomenon coupled with increased phosphorylation of tight junction proteins zonula occludens-1 and occludin. In contrast, association with SIgA resulted in both enhanced level of nuclear translocation of NF-κB and production of epithelial polymeric Ig receptor as compared with bacteria alone. Moreover, thymic stromal lymphopoietin production was increased upon exposure to bacteria and further enhanced with SIgA-based complexes, whereas the level of pro-inflammatory epithelial cell mediators remained unaffected. Interestingly, SIgA-mediated potentiation of the Caco-2 cell responsiveness to the two probiotics tested involved Fab-independent interaction with the bacteria. These findings add to the multiple functions of SIgA and underscore a novel role of the antibody in interaction with intestinal bacteria.

Radiochemotherapy in locally advanced squamous cell carcinomas of the head and neck.

Squamous cell carcinoma of the head and neck (SCCHN) is a common disease that develops in the upper aerodigestive epithelium. The most important risk factors are tobacco and alcohol consumption. There is also increasing evidence that human papillomavirus plays an important role in the cause of SCCHN. The complex anatomy, the vital functions of the upper aerodigestive tract and the close proximity to vital structures, explain that the goal of treatment is not only to improve survival outcomes, but also to preserve organ function. Radiotherapy and surgery are the standard modalities of treatment, reflecting the locoregional predominance of SCCHN. Chemotherapy plays an important role in the treatment of patients with locoregionally advanced disease, in conjunction with radiotherapy and surgery. Indeed, standard therapy for resectable locoregionally advanced (stage III or IV) SCCHN cancers consists either of surgery and adjuvant chemoradiotherapy or definitive concomitant chemoradiotherapy, depending upon disease site, stage and resectability of the tumour, or institutional experience. Concomitant chemoradiotherapy has been shown in several randomised trials to improve disease-free and overall survival in the postoperative setting for resected disease with poor prognostic factors. Furthermore, multiple randomised studies and meta-analyses have shown that definitive chemoradiotherapy, as well anti-epidermal growth factor receptor treatment in one randomised study, improved disease-free and overall survival when compared with radiotherapy alone. This overview reviews the most relevant published studies on the multidisciplinary management of SCCHN and discusses future strategies to reduce locoregional failures.

Class of correlated random networks with hidden variables

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.