917 resultados para High-throughput


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L'introduction des technologies de séquençage de nouvelle génération est en vue de révolutionner la médecine moderne. L'impact de ces nouveaux outils a déjà contribué à la découverte de nouveaux gènes et de voies cellulaires impliqués dans la pathologie de maladies génétiques rares ou communes. En revanche, l'énorme quantité de données générées par ces systèmes ainsi que la complexité des analyses bioinformatiques nécessaires, engendre un goulet d'étranglement pour résoudre les cas les plus difficiles. L'objectif de cette thèse a été d'identifier les causes génétiques de deux maladies héréditaires utilisant ces nouvelles techniques de séquençage, couplées à des technologies d'enrichissement de gènes. Dans ce cadre, nous avons développé notre propre méthode de travail (pipeline) pour l'alignement des fragments de séquence (reads). Suite à l'identification de gènes, nous avons réalisé une analyse fonctionnelle pour élucider leur rôle dans la maladie. Dans un premier temps, nous avons étudié et identifié des mutations impliquées dans une forme récessive de la rétinite pigmentaire qui est à ce jour la dégénérescence rétinienne héréditaire la plus fréquente. En particulier, nous avons constaté que des mutations faux-sens dans le gène FAM161A étaient la cause de la rétinite pigmentaire préalablement associé avec le locus RP28. De plus, nous avons démontré que ce gène avait des fonctions au niveau du cil du photorécepteur, complétant le large spectre des cilliopathies rétiniennes héréditaires. Dans un second temps, nous avons exploré la possibilité qu'un syndrome, relativement fréquent en pédiatrie de fièvre récurrente, appelé PFAPA (acronyme de fièvre périodique avec adénite stomatite, pharyngite et cervical aphteuse) puisse avoir une origine génétique. L'étiologie de cette maladie n'étant pas claire, nous avons tenté d'identifier le spectre génétique de patients PFAPA. Comme nous n'avons pas pu mettre à jour un nouveau gène unique muté et responsable de la maladie chez tous les individus dépistés, il semblerait qu'un modèle génétique plus complexe suggérant l'implication de plusieurs gènes dans la pathologie ait été identifié chez les patients touchés. Ces gènes seraient notamment impliqués dans des processus liés à l'inflammation ce qui élargirait l'impact de ces études à d'autres maladies auto-inflammatoires.

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Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.

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Viime vuosien nopea kehitys on kiihdyttänyt uusien lääkkeiden kehittämisprosessia. Kombinatorinen kemia on tehnyt mahdolliseksi syntetisoida suuria kokoelmia rakenteeltaan toisistaan poikkeavia molekyylejä, nk. kombinatorisia kirjastoja, biologista seulontaa varten. Siinä molekyylien rakenteeseen liittyvä aktiivisuus tutkitaan useilla erilaisilla biologisilla testeillä mahdollisten "osumien" löytämiseksi, joista osasta saatetaan myöhemmin kehittää uusia lääkeaineita. Jotta biologisten tutkimusten tulokset olisivat luotettavia, on syntetisoitujen komponenttien oltava mahdollisimman puhtaita. Tämän vuoksi tarvitaan HTP-puhdistusta korkealaatuisten komponenttien ja luotettavan biologisen tiedon takaamiseksi. Jatkuvasti kasvavat tuotantovaatimukset ovat johtaneet näiden puhdistustekniikoiden automatisointiin ja rinnakkaistamiseen. Preparatiivinen LC/MS soveltuu kombinatoristen kirjastojen nopeaan ja tehokkaaseen puhdistamiseen. Monet tekijät, esimerkiksi erotuskolonnin ominaisuudet sekä virtausgradientti, vaikuttavat preparatiivisen LC/MS puhdistusprosessin tehokkuuteen. Nämä parametrit on optimoitava parhaan tuloksen saamiseksi. Tässä työssä tutkittiin emäksisiä komponentteja erilaisissa virtausolosuhteissa. Menetelmä kombinatoristen kirjastojen puhtaustason määrittämiseksi LC/MS-puhdistuksen jälkeen optimoitiin ja määritettiin puhtaus joillekin komponenteille eri kirjastoista ennen puhdistusta.

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Most fishes produce free-living embryos that are exposed to environmental stressors immediately following fertilization, including pathogenic microorganisms. Initial immune protection of embryos involves the chorion, as a protective barrier, and maternally-allocated antimicrobial compounds. At later developmental stages, host-genetic effects influence susceptibility and tolerance, suggesting a direct interaction between embryo genes and pathogens. So far, only a few host genes could be identified that correlate with embryonic survival under pathogen stress in salmonids. Here, we utilized high-throughput RNA-sequencing in order to describe the transcriptional response of a non-model fish, the Alpine whitefish Coregonus palaea, to infection, both in terms of host genes that are likely manipulated by the pathogen, and those involved in an early putative immune response. Embryos were produced in vitro, raised individually, and exposed at the late-eyed stage to a virulent strain of the opportunistic fish pathogen Pseudomonas fluorescens. The pseudomonad increased embryonic mortality and affected gene expression substantially. For example, essential, upregulated metabolic pathways in embryos under pathogen stress included ion binding pathways, aminoacyl-tRNA-biosynthesis, and the production of arginine and proline, most probably mediated by the pathogen for its proliferation. Most prominently downregulated transcripts comprised the biosynthesis of unsaturated fatty acids, the citrate cycle, and various isoforms of b-cell transcription factors. These factors have been shown to play a significant role in host blood cell differentiation and renewal. With regard to specific immune functions, differentially expressed transcripts mapped to the complement cascade, MHC class I and II, TNF-alpha, and T-cell differentiation proteins. The results of this study reveal insights into how P. fluorescens impairs the development of whitefish embryos and set a foundation for future studies investigating host pathogen interactions in fish embryos.

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Turbot (Scophthalmus maximus L.) is an important aquacultural resource both in Europe and Asia. However, there is little information on gene sequences available in public databases. Currently, one of the main problems affecting the culture of this flatfish is mortality due to several pathogens, especially viral diseases which are not treatable. In order to identify new genes involved in immune defense, we conducted 454-pyrosequencing of the turbot transcriptome after different immune stimulations.

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The Manila clam (Ruditapes philippinarum) is a worldwide cultured bivalve species with important commercial value. Diseases affecting this species can result in large economic losses. Because knowledge of the molecular mechanisms of the immune response in bivalves, especially clams, is scarce and fragmentary, we sequenced RNA from immune-stimulated R. philippinarum hemocytes by 454-pyrosequencing to identify genes involved in their immune defense against infectious diseases.

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High-throughput screening of cellular effects of RNA interference (RNAi) libraries is now being increasingly applied to explore the role of genes in specific cell biological processes and disease states. However, the technology is still limited to specialty laboratories, due to the requirements for robotic infrastructure, access to expensive reagent libraries, expertise in high-throughput screening assay development, standardization, data analysis and applications. In the future, alternative screening platforms will be required to expand functional large-scale experiments to include more RNAi constructs, allow combinatorial loss-of-function analyses (e.g. genegene or gene-drug interaction), gain-of-function screens, multi-parametric phenotypic readouts or comparative analysis of many different cell types. Such comprehensive perturbation of gene networks in cells will require a major increase in the flexibility of the screening platforms, throughput and reduction of costs. As an alternative for the conventional multi-well based high-throughput screening -platforms, here the development of a novel cell spot microarray method for production of high density siRNA reverse transfection arrays is described. The cell spot microarray platform is distinguished from the majority of other transfection cell microarray techniques by the spatially confined array layout that allow highly parallel screening of large-scale RNAi reagent libraries with assays otherwise difficult or not applicable to high-throughput screening. This study depicts the development of the cell spot microarray method along with biological application examples of high-content immunofluorescence and phenotype based cancer cell biological analyses focusing on the regulation of prostate cancer cell growth, maintenance of genomic integrity in breast cancer cells, and functional analysis of integrin protein-protein interactions in situ.

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Prostate cancers form a heterogeneous group of diseases and there is a need for novel biomarkers, and for more efficient and targeted methods of treatment. In this thesis, the potential of microarray data, RNA interference (RNAi) and compound screens were utilized in order to identify novel biomarkers, drug targets and drugs for future personalized prostate cancer therapeutics. First, a bioinformatic mRNA expression analysis covering 9873 human tissue and cell samples, including 349 prostate cancer and 147 normal prostate samples, was used to distinguish in silico prevalidated putative prostate cancer biomarkers and drug targets. Second, RNAi based high-throughput (HT) functional profiling of 295 prostate and prostate cancer tissue specific genes was performed in cultured prostate cancer cells. Third, a HT compound screen approach using a library of 4910 drugs and drug-like molecules was exploited to identify potential drugs inhibiting prostate cancer cell growth. Nine candidate drug targets, with biomarker potential, and one cancer selective compound were validated in vitro and in vivo. In addition to androgen receptor (AR) signaling, endoplasmic reticulum (ER) function, arachidonic acid (AA) pathway, redox homeostasis and mitosis were identified as vital processes in prostate cancer cells. ERG oncogene positive cancer cells exhibited sensitivity to induction of oxidative and ER stress, whereas advanced and castrate-resistant prostate cancer (CRPC) could be potentially targeted through AR signaling and mitosis. In conclusion, this thesis illustrates the power of systems biological data analysis in the discovery of potential vulnerabilities present in prostate cancer cells, as well as novel options for personalized cancer management.

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The recent rapid development of biotechnological approaches has enabled the production of large whole genome level biological data sets. In order to handle thesedata sets, reliable and efficient automated tools and methods for data processingand result interpretation are required. Bioinformatics, as the field of studying andprocessing biological data, tries to answer this need by combining methods and approaches across computer science, statistics, mathematics and engineering to studyand process biological data. The need is also increasing for tools that can be used by the biological researchers themselves who may not have a strong statistical or computational background, which requires creating tools and pipelines with intuitive user interfaces, robust analysis workflows and strong emphasis on result reportingand visualization. Within this thesis, several data analysis tools and methods have been developed for analyzing high-throughput biological data sets. These approaches, coveringseveral aspects of high-throughput data analysis, are specifically aimed for gene expression and genotyping data although in principle they are suitable for analyzing other data types as well. Coherent handling of the data across the various data analysis steps is highly important in order to ensure robust and reliable results. Thus,robust data analysis workflows are also described, putting the developed tools andmethods into a wider context. The choice of the correct analysis method may also depend on the properties of the specific data setandthereforeguidelinesforchoosing an optimal method are given. The data analysis tools, methods and workflows developed within this thesis have been applied to several research studies, of which two representative examplesare included in the thesis. The first study focuses on spermatogenesis in murinetestis and the second one examines cell lineage specification in mouse embryonicstem cells.

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La compréhension de processus biologiques complexes requiert des approches expérimentales et informatiques sophistiquées. Les récents progrès dans le domaine des stratégies génomiques fonctionnelles mettent dorénavant à notre disposition de puissants outils de collecte de données sur l’interconnectivité des gènes, des protéines et des petites molécules, dans le but d’étudier les principes organisationnels de leurs réseaux cellulaires. L’intégration de ces connaissances au sein d’un cadre de référence en biologie systémique permettrait la prédiction de nouvelles fonctions de gènes qui demeurent non caractérisées à ce jour. Afin de réaliser de telles prédictions à l’échelle génomique chez la levure Saccharomyces cerevisiae, nous avons développé une stratégie innovatrice qui combine le criblage interactomique à haut débit des interactions protéines-protéines, la prédiction de la fonction des gènes in silico ainsi que la validation de ces prédictions avec la lipidomique à haut débit. D’abord, nous avons exécuté un dépistage à grande échelle des interactions protéines-protéines à l’aide de la complémentation de fragments protéiques. Cette méthode a permis de déceler des interactions in vivo entre les protéines exprimées par leurs promoteurs naturels. De plus, aucun biais lié aux interactions des membranes n’a pu être mis en évidence avec cette méthode, comparativement aux autres techniques existantes qui décèlent les interactions protéines-protéines. Conséquemment, nous avons découvert plusieurs nouvelles interactions et nous avons augmenté la couverture d’un interactome d’homéostasie lipidique dont la compréhension demeure encore incomplète à ce jour. Par la suite, nous avons appliqué un algorithme d’apprentissage afin d’identifier huit gènes non caractérisés ayant un rôle potentiel dans le métabolisme des lipides. Finalement, nous avons étudié si ces gènes et un groupe de régulateurs transcriptionnels distincts, non préalablement impliqués avec les lipides, avaient un rôle dans l’homéostasie des lipides. Dans ce but, nous avons analysé les lipidomes des délétions mutantes de gènes sélectionnés. Afin d’examiner une grande quantité de souches, nous avons développé une plateforme à haut débit pour le criblage lipidomique à contenu élevé des bibliothèques de levures mutantes. Cette plateforme consiste en la spectrométrie de masse à haute resolution Orbitrap et en un cadre de traitement des données dédié et supportant le phénotypage des lipides de centaines de mutations de Saccharomyces cerevisiae. Les méthodes expérimentales en lipidomiques ont confirmé les prédictions fonctionnelles en démontrant certaines différences au sein des phénotypes métaboliques lipidiques des délétions mutantes ayant une absence des gènes YBR141C et YJR015W, connus pour leur implication dans le métabolisme des lipides. Une altération du phénotype lipidique a également été observé pour une délétion mutante du facteur de transcription KAR4 qui n’avait pas été auparavant lié au métabolisme lipidique. Tous ces résultats démontrent qu’un processus qui intègre l’acquisition de nouvelles interactions moléculaires, la prédiction informatique des fonctions des gènes et une plateforme lipidomique innovatrice à haut débit , constitue un ajout important aux méthodologies existantes en biologie systémique. Les développements en méthodologies génomiques fonctionnelles et en technologies lipidomiques fournissent donc de nouveaux moyens pour étudier les réseaux biologiques des eucaryotes supérieurs, incluant les mammifères. Par conséquent, le stratégie présenté ici détient un potentiel d’application au sein d’organismes plus complexes.

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Pan-viral DNA array (PVDA) and high-throughput sequencing (HTS) are useful tools to identify novel viruses of emerging diseases. However, both techniques have difficulties to identify viruses in clinical samples because of the host genomic nucleic acid content (hg/cont). Both propidium monoazide (PMA) and ethidium bromide monoazide (EMA) have the capacity to bind free DNA/RNA, but are cell membrane-impermeable. Thus, both are unable to bind protected nucleic acid such as viral genomes within intact virions. However, EMA/PMA modified genetic material cannot be amplified by enzymes. In order to assess the potential of EMA/PMA to lower the presence of amplifiable hg/cont in samples and improve virus detection, serum and lung tissue homogenates were spiked with porcine reproductive and respiratory virus (PRRSV) and were processed with EMA/PMA. In addition, PRRSV RT-qPCR positive clinical samples were also tested. EMA/PMA treatments significantly decreased amplifiable hg/cont and significantly increased the number of PVDA positive probes and their signal intensity compared to untreated spiked lung samples. EMA/PMA treatments also increased the sensitivity of HTS by increasing the number of specific PRRSV reads and the PRRSV percentage of coverage. Interestingly, EMA/PMA treatments significantly increased the sensitivity of PVDA and HTS in two out of three clinical tissue samples. Thus, EMA/PMA treatments offer a new approach to lower the amplifiable hg/cont in clinical samples and increase the success of PVDA and HTS to identify viruses.

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We have designed and implemented a low-cost digital system using closed-circuit television cameras coupled to a digital acquisition system for the recording of in vivo behavioral data in rodents and for allowing observation and recording of more than 10 animals simultaneously at a reduced cost, as compared with commercially available solutions. This system has been validated using two experimental rodent models: one involving chemically induced seizures and one assessing appetite and feeding. We present observational results showing comparable or improved levels of accuracy and observer consistency between this new system and traditional methods in these experimental models, discuss advantages of the presented system over conventional analog systems and commercially available digital systems, and propose possible extensions to the system and applications to nonrodent studies.