922 resultados para High-Throughput Nucleotide Sequencing


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Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

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In this study, high-throughput sequencing (HTS) metabarcoding was applied for the surveillance of plankton communities within the southeastern (SE) Baltic Sea coastal zone. These results were compared with those from routine monitoring survey and morphological analyses. Four of five nonindigenous species found in the samples were identified exclusively by metabarcoding. All of them are considered as invasive in the Baltic Sea with reported impact on the ecosystem and biodiversity. This study indicates that, despite some current limitations, HTS metabarcoding can provide information on the presence of exotic species and advantageously complement conventional approaches, only requiring the same monitoring effort as before. Even in the currently immature status of HTS, this combination of HTS metabarcoding and observational records is recommended in the early detection of marine pests and delivery of the environmental status metrics of nonindigenous species.

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Photosynthetic eukaryotes have a critical role as the main producers in most ecosystems of the biosphere. The ongoing environmental metabarcoding revolution opens the perspective for holistic ecosystems biological studies of these organisms, in particular the unicellular microalgae that often lack distinctive morphological characters and have complex life cycles. To interpret environmental sequences, metabarcoding necessarily relies on taxonomically curated databases containing reference sequences of the targeted gene (or barcode) from identified organisms. To date, no such reference framework exists for photosynthetic eukaryotes. In this study, we built the PhytoREF database that contains 6490 plastidial 16S rDNA reference sequences that originate from a large diversity of eukaryotes representing all known major photosynthetic lineages. We compiled 3333 amplicon sequences available from public databases and 879 sequences extracted from plastidial genomes, and generated 411 novel sequences from cultured marine microalgal strains belonging to different eukaryotic lineages. A total of 1867 environmental Sanger 16S rDNA sequences were also included in the database. Stringent quality filtering and a phylogeny-based taxonomic classification were applied for each 16S rDNA sequence. The database mainly focuses on marine microalgae, but sequences from land plants (representing half of the PhytoREF sequences) and freshwater taxa were also included to broaden the applicability of PhytoREF to different aquatic and terrestrial habitats. PhytoREF, accessible via a web interface (http://phytoref.fr), is a new resource in molecular ecology to foster the discovery, assessment and monitoring of the diversity of photosynthetic eukaryotes using high-throughput sequencing.

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Photosynthetic eukaryotes have a critical role as the main producers in most ecosystems of the biosphere. The ongoing environmental metabarcoding revolution opens the perspective for holistic ecosystems biological studies of these organisms, in particular the unicellular microalgae that often lack distinctive morphological characters and have complex life cycles. To interpret environmental sequences, metabarcoding necessarily relies on taxonomically curated databases containing reference sequences of the targeted gene (or barcode) from identified organisms. To date, no such reference framework exists for photosynthetic eukaryotes. In this study, we built the PhytoREF database that contains 6490 plastidial 16S rDNA reference sequences that originate from a large diversity of eukaryotes representing all known major photosynthetic lineages. We compiled 3333 amplicon sequences available from public databases and 879 sequences extracted from plastidial genomes, and generated 411 novel sequences from cultured marine microalgal strains belonging to different eukaryotic lineages. A total of 1867 environmental Sanger 16S rDNA sequences were also included in the database. Stringent quality filtering and a phylogeny-based taxonomic classification were applied for each 16S rDNA sequence. The database mainly focuses on marine microalgae, but sequences from land plants (representing half of the PhytoREF sequences) and freshwater taxa were also included to broaden the applicability of PhytoREF to different aquatic and terrestrial habitats. PhytoREF, accessible via a web interface (http://phytoref.fr), is a new resource in molecular ecology to foster the discovery, assessment and monitoring of the diversity of photosynthetic eukaryotes using high-throughput sequencing.

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Schistosomiasis is a neglected tropical disease of clinical significance that, despite years of research, still requires an effective vaccine and improved diagnostics for surveillance, control and potential elimination. Furthermore, the causes of host pathology during schistosomiasis are still not completely understood. The recent sequencing of the genomes of the three key schistosome species has enabled the discovery of many new possible vaccine and drug targets, as well as diagnostic biomarkers, using high-throughput and sensitive proteomics methods. This review focuses on the literature of the last 5 years that has reported on the use of proteomics to both better understand the biology of the schistosome parasites and the disease they cause in definitive mammalian hosts.

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Tumor genomic instability and selective treatment pressures result in clonal disease evolution; molecular stratification for molecularly targeted drug administration requires repeated access to tumor DNA. We hypothesized that circulating plasma DNA (cpDNA) in advanced cancer patients is largely derived from tumor, has prognostic utility, and can be utilized for multiplex tumor mutation sequencing when repeat biopsy is not feasible. We utilized the Sequenom MassArray System and OncoCarta panel for somatic mutation profiling. Matched samples, acquired from the same patient but at different time points were evaluated; these comprised formalin-fixed paraffin-embedded (FFPE) archival tumor tissue (primary and/or metastatic) and cpDNA. The feasibility, sensitivity, and specificity of this high-throughput, multiplex mutation detection approach was tested utilizing specimens acquired from 105 patients with solid tumors referred for participation in Phase I trials of molecularly targeted drugs. The median cpDNA concentration was 17 ng/ml (range: 0.5-1600); this was 3-fold higher than in healthy volunteers. Moreover, higher cpDNA concentrations associated with worse overall survival; there was an overall survival (OS) hazard ratio of 2.4 (95% CI 1.4, 4.2) for each 10-fold increase in cpDNA concentration and in multivariate analyses, cpDNA concentration, albumin, and performance status remained independent predictors of OS. These data suggest that plasma DNA in these cancer patients is largely derived from tumor. We also observed high detection concordance for critical 'hot-spot' mutations (KRAS, BRAF, PIK3CA) in matched cpDNA and archival tumor tissue, and important differences between archival tumor and cpDNA. This multiplex sequencing assay can be utilized to detect somatic mutations from plasma in advanced cancer patients, when safe repeat tumor biopsy is not feasible and genomic analysis of archival tumor is deemed insufficient. Overall, circulating nucleic acid biomarker studies have clinically important multi-purpose utility in advanced cancer patients and further studies to pursue their incorporation into the standard of care are warranted.

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The McMurdo Dry Valleys of Antarctica are an extreme polar desert. Mineral soils support subsurface microbial communities and translucent rocks support development of hypolithic communities on ventral surfaces in soil contact. Despite significant research attention, relatively little is known about taxonomic and functional diversity or their inter-relationships. Here we report a combined diversity and functional interrogation for soil and hypoliths of the Miers Valley in the McMurdo Dry Valleys of Antarctica. The study employed 16S rRNA fingerprinting and high throughput sequencing combined with the GeoChip functional microarray. The soil community was revealed as a highly diverse reservoir of bacterial diversity dominated by actinobacteria. Hypolithic communities were less diverse and dominated by cyanobacteria. Major differences in putative functionality were that soil communities displayed greater diversity in stress tolerance and recalcitrant substrate utilization pathways, whilst hypolithic communities supported greater diversity of nutrient limitation adaptation pathways. A relatively high level of functional redundancy in both soil and hypoliths may indicate adaptation of these communities to fluctuating environmental conditions.

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Les écosystèmes dunaires remplissent plusieurs fonctions écologiques essentielles comme celle de protéger le littoral grâce à leur capacité d’amortissement face aux vents et vagues des tempêtes. Les dunes jouent aussi un rôle dans la filtration de l’eau, la recharge de la nappe phréatique, le maintien de la biodiversité, en plus de présenter un attrait culturel, récréatif et touristique. Les milieux dunaires sont très dynamiques et incluent plusieurs stades de succession végétale, passant de la plage de sable nu à la dune bordière stabilisée par l’ammophile à ligule courte, laquelle permet aussi l’établissement d’autres herbacées, d’arbustes et, éventuellement, d’arbres. Or, la survie de ces végétaux est intimement liée aux microorganismes du sol. Les champignons du sol interagissent intimement avec les racines des plantes, modifient la structure des sols, et contribuent à la décomposition de la matière organique et à la disponibilité des nutriments. Ils sont donc des acteurs clés de l’écologie des sols et contribuent à la stabilisation des dunes. Malgré cela, la diversité et la structure des communautés fongiques, ainsi que les mécanismes influençant leur dynamique écologique, demeurent relativement méconnus. Le travail présenté dans cette thèse explore la diversité des communautés fongiques à travers le gradient de succession et de conditions édaphiques d’un écosystème dunaire côtier afin d’améliorer la compréhension de la dynamique des sols en milieux dunaires. Une vaste collecte de données sur le terrain a été réalisée sur une plaine de dunes reliques se trouvant aux Îles de la Madeleine, Qc. J’ai échantillonné plus de 80 sites répartis sur l’ensemble de ce système dunaire et caractérisé les champignons du sol grâce au séquençage à haut débit. Dans un premier temps, j’ai dressé un portait d’ensemble des communautés fongiques du sol à travers les différentes zones des dunes. En plus d’une description taxonomique, les modes de vie fongiques ont été prédits afin de mieux comprendre comment les variations au niveau des communautés de champignons du sol peuvent se traduire en changements fonctionnels. J’ai observé un niveau de diversité fongique élevé (plus de 3400 unités taxonomiques opérationnelles au total) et des communautés taxonomiquement et fonctionnellement distinctes à travers un gradient de succession et de conditions édaphiques. Ces résultats ont aussi indiqué que toutes les zones des dunes, incluant la zone pionière, supportent des communautés fongiques diversifiées. Ensuite, le lien entre les communautés végétales et fongiques a été étudié à travers l’ensemble de la séquence dunaire. Ces résultats ont montré une augmentation claire de la richesse spécifique végétale, ainsi qu’une augmentation de la diversité des stratégies d’acquisition de nutriments (traits souterrains lié à la nutrition des plantes, soit mycorhizien à arbuscule, ectomycorhizien, mycorhizien éricoide, fixateur d’azote ou non spécialisé). J’ai aussi pu établir une forte corrélation entre les champignons du sol et la végétation, qui semblent tous deux réagir de façon similaire aux conditions physicochimiques du sol. Le pH du sol influençait fortement les communautés végétales et fongiques. Le lien observé entre les communautés végétales et fongiques met l’emphase sur l’importance des interactions biotiques positives au fil de la succession dans les environnements pauvres en nutriments. Finalement, j’ai comparé les communautés de champignons ectomycorhiziens associées aux principales espèces arborescentes dans les forêts dunaires. J’ai observé une richesse importante, avec un total de 200 unités taxonomiques opérationnelles ectomycorhiziennes, appartenant principalement aux Agaricomycètes. Une analyse de réseaux n’a pas permis de détecter de modules (c'est-à-dire des sous-groupes d’espèces en interaction), ce qui indique un faible niveau de spécificité des associations ectomycorhiziennes. De plus, je n’ai pas observé de différences en termes de richesse ou de structure des communautés entre les quatre espèces hôtes. En conclusion, j’ai pu observer à travers la succession dunaire des communautés diversifiées et des structures distinctes selon la zone de la dune, tant chez les champignons que chez les plantes. La succession semble toutefois moins marquée au niveau des communautés fongiques, par rapport aux patrons observés chez les plantes. Ces résultats ont alimenté une réflexion sur le potentiel et les perspectives, mais aussi sur les limitations des approches reposant sur le séquençage à haut-débit en écologie microbienne.

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Thesis (Ph.D.)--University of Washington, 2016-08

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Metagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.

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La fonte et l’effondrement du pergélisol riche en glace dans la région subarctique du Québec ont donné lieu à la formation de petits lacs (mares de thermokarst) qui émettent des gaz à effet de serre dans l’atmosphère tels que du dioxyde de carbone et du méthane. Pourtant, la composition de la communauté microbienne qui est à la base des processus biogéochimiques dans les mares de fonte a été très peu étudiée, particulièrement en ce qui concerne la diversité et l’activité des micro-organismes impliqués dans le cycle du méthane. L’objectif de cette thèse est donc d’étudier la diversité phylogénétique et fonctionnelle des micro-organismes dans les mares de fonte subarctiques en lien avec les caractéristiques de l’environnement et les émissions de méthane. Pour ce faire, une dizaine de mares ont été échantillonnées dans quatre vallées situées à travers un gradient de fonte du pergélisol, et disposant de différentes propriétés physico-chimiques. Selon les vallées, les mares peuvent être issues de la fonte de palses (buttes de tourbe, à dominance organique) ou de lithalses (buttes de sol à dominance minérale) ce qui influence la nature du carbone organique disponible pour la reminéralisation microbienne. Durant l’été, les mares étaient fortement stratifiées; il y avait un fort gradient physico-chimique au sein de la colonne d’eau, avec une couche d’eau supérieure oxique et une couche d’eau profonde pauvre en oxygène ou anoxique. Pour identifier les facteurs qui influencent les communautés microbiennes, des techniques de séquençage à haut débit ont été utilisées ciblant les transcrits des gènes de l’ARNr 16S et des gènes impliqués dans le cycle du méthane : mcrA pour la méthanogenèse et pmoA pour la méthanotrophie. Pour évaluer l’activité des micro-organismes, la concentration des transcrits des gènes fonctionnels a aussi été mesurée avec des PCR quantitatives (qPCR). Les résultats montrent une forte dominance de micro-organismes impliqués dans le cycle du méthane, c’est-à-dire des archées méthanogènes et des bactéries méthanotrophes. L’analyse du gène pmoA indique que les bactéries méthanotrophes n’étaient pas seulement actives à la surface, mais aussi dans le fond de la mare où les concentrations en oxygène étaient minimales; ce qui est inattendu compte tenu de leur besoin en oxygène pour consommer le méthane. En général, la composition des communautés microbiennes était principalement influencée par l’origine de la mare (palse ou lithalse), et moins par le gradient de dégradation du pergélisol. Des variables environnementales clefs comme le pH, le phosphore et le carbone organique dissous, contribuent à la distinction des communautés microbiennes entre les mares issues de palses ou de lithalses. Avec l’intensification des effets du réchauffement climatique, ces communautés microbiennes vont faire face à des changements de conditions qui risquent de modifier leur composition taxonomique, et leurs réponses aux changements seront probablement différentes selon le type de mares. De plus, dans le futur les conditions d’oxygénation au sein des mares seront soumises à des modifications majeures associées avec un changement dans la durée des périodes de fonte de glace et de stratification. Ce type de changement aura un impact sur l’équilibre entre la méthanogenèse et la méthanotrophie, et affectera ainsi les taux d’émissions de méthane. Cependant, les résultats obtenus dans cette thèse indiquent que les archées méthanogènes et les bactéries méthanotrophes peuvent développer des stratégies pour survivre et rester actives au-delà des limites de leurs conditions d’oxygène habituelles.

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Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

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Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

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Les écosystèmes dunaires remplissent plusieurs fonctions écologiques essentielles comme celle de protéger le littoral grâce à leur capacité d’amortissement face aux vents et vagues des tempêtes. Les dunes jouent aussi un rôle dans la filtration de l’eau, la recharge de la nappe phréatique, le maintien de la biodiversité, en plus de présenter un attrait culturel, récréatif et touristique. Les milieux dunaires sont très dynamiques et incluent plusieurs stades de succession végétale, passant de la plage de sable nu à la dune bordière stabilisée par l’ammophile à ligule courte, laquelle permet aussi l’établissement d’autres herbacées, d’arbustes et, éventuellement, d’arbres. Or, la survie de ces végétaux est intimement liée aux microorganismes du sol. Les champignons du sol interagissent intimement avec les racines des plantes, modifient la structure des sols, et contribuent à la décomposition de la matière organique et à la disponibilité des nutriments. Ils sont donc des acteurs clés de l’écologie des sols et contribuent à la stabilisation des dunes. Malgré cela, la diversité et la structure des communautés fongiques, ainsi que les mécanismes influençant leur dynamique écologique, demeurent relativement méconnus. Le travail présenté dans cette thèse explore la diversité des communautés fongiques à travers le gradient de succession et de conditions édaphiques d’un écosystème dunaire côtier afin d’améliorer la compréhension de la dynamique des sols en milieux dunaires. Une vaste collecte de données sur le terrain a été réalisée sur une plaine de dunes reliques se trouvant aux Îles de la Madeleine, Qc. J’ai échantillonné plus de 80 sites répartis sur l’ensemble de ce système dunaire et caractérisé les champignons du sol grâce au séquençage à haut débit. Dans un premier temps, j’ai dressé un portait d’ensemble des communautés fongiques du sol à travers les différentes zones des dunes. En plus d’une description taxonomique, les modes de vie fongiques ont été prédits afin de mieux comprendre comment les variations au niveau des communautés de champignons du sol peuvent se traduire en changements fonctionnels. J’ai observé un niveau de diversité fongique élevé (plus de 3400 unités taxonomiques opérationnelles au total) et des communautés taxonomiquement et fonctionnellement distinctes à travers un gradient de succession et de conditions édaphiques. Ces résultats ont aussi indiqué que toutes les zones des dunes, incluant la zone pionière, supportent des communautés fongiques diversifiées. Ensuite, le lien entre les communautés végétales et fongiques a été étudié à travers l’ensemble de la séquence dunaire. Ces résultats ont montré une augmentation claire de la richesse spécifique végétale, ainsi qu’une augmentation de la diversité des stratégies d’acquisition de nutriments (traits souterrains lié à la nutrition des plantes, soit mycorhizien à arbuscule, ectomycorhizien, mycorhizien éricoide, fixateur d’azote ou non spécialisé). J’ai aussi pu établir une forte corrélation entre les champignons du sol et la végétation, qui semblent tous deux réagir de façon similaire aux conditions physicochimiques du sol. Le pH du sol influençait fortement les communautés végétales et fongiques. Le lien observé entre les communautés végétales et fongiques met l’emphase sur l’importance des interactions biotiques positives au fil de la succession dans les environnements pauvres en nutriments. Finalement, j’ai comparé les communautés de champignons ectomycorhiziens associées aux principales espèces arborescentes dans les forêts dunaires. J’ai observé une richesse importante, avec un total de 200 unités taxonomiques opérationnelles ectomycorhiziennes, appartenant principalement aux Agaricomycètes. Une analyse de réseaux n’a pas permis de détecter de modules (c'est-à-dire des sous-groupes d’espèces en interaction), ce qui indique un faible niveau de spécificité des associations ectomycorhiziennes. De plus, je n’ai pas observé de différences en termes de richesse ou de structure des communautés entre les quatre espèces hôtes. En conclusion, j’ai pu observer à travers la succession dunaire des communautés diversifiées et des structures distinctes selon la zone de la dune, tant chez les champignons que chez les plantes. La succession semble toutefois moins marquée au niveau des communautés fongiques, par rapport aux patrons observés chez les plantes. Ces résultats ont alimenté une réflexion sur le potentiel et les perspectives, mais aussi sur les limitations des approches reposant sur le séquençage à haut-débit en écologie microbienne.

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Shiga toxin-producing Escherichia coli (STEC) and enteropathogenic E. coli (EPEC) strains may be responsible for food-borne infections in humans. Twenty-eight STEC and 75 EPEC strains previously isolated from French shellfish-harvesting areas and their watersheds and belonging to 68 distinguishable serotypes were characterized in this study. High-throughput real-time PCR was used to search for the presence of 75 E. coli virulence-associated gene targets, and genes encoding Shiga toxin (stx) and intimin (eae) were subtyped using PCR tests and DNA sequencing, respectively. The results showed a high level of diversity between strains, with 17 unique virulence gene profiles for STEC and 56 for EPEC. Seven STEC and 15 EPEC strains were found to display a large number or a particular combination of genetic markers of virulence and the presence of stx and/or eae variants, suggesting their potential pathogenicity for humans. Among these, an O26:H11 stx1a eae-β1 strain was associated with a large number of virulence-associated genes (n = 47), including genes carried on the locus of enterocyte effacement (LEE) or other pathogenicity islands, such as OI-122, OI-71, OI-43/48, OI-50, OI-57, and the high-pathogenicity island (HPI). One O91:H21 STEC strain containing 4 stx variants (stx1a, stx2a, stx2c, and stx2d) was found to possess genes associated with pathogenicity islands OI-122, OI-43/48, and OI-15. Among EPEC strains harboring a large number of virulence genes (n, 34 to 50), eight belonged to serotype O26:H11, O103:H2, O103:H25, O145:H28, O157:H7, or O153:H2.