918 resultados para High throughput


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John Draper, Luis A.J. Mur, Glyn Jenkins, Gadab C. Ghosh-Biswas, Pauline Bablak, Robert Hasterok,and Andrew P.M. Routledge (2001). Brachypodium distachyon. A new model system for functional genomics in grasses. Plant Physiology, 127 (4), 1539-1555. Sponsorship: BBSRC / Gatsby Foundation RAE2008

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BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

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To screen for novel ribosomally synthesised antimicrobials, in-silico genome mining was performed on all publically available fully sequenced bacterial genomes. 49 novel type 1 lantibiotic clusters were identified from a number of species, genera and phyla not usually associated with lantibiotic production, and indicates high prevalence. A crucial step towards the commercialisation of fermented beverages is the characterisation of the microbial content. To achieve this goal, we applied next-generation sequencing techniques to analyse the bacterial and yeast populations of the organic, symbiotically-fermented beverages kefir, water kefir and kombucha. A number of minor components were revealed, many of which had not previously been associated with these beverages. The dominant microorganism in each of the water kefir grains and fermentates was Zymomonas, an ethanol-producing bacterium that had not previously been detected on such a scale. These studies represent the most accurate description of these populations to date, and should aid in future starter design and in determining which species are responsible for specific attributes of the beverages. Finally, high-throughput robotics was applied to screen for the presence of antimicrobial producers associated with these beverages. This revealed a low frequency of bacteriocin production amongst the bacterial isolates, with only lactococcins A, B and LcnN of lactococcin M being identified. However, a proteinaceous antimicrobial produced by the yeast Dekkera bruxellensis, isolated from kombucha, was found to be active against Lactobacillus bulgaricus. This peptide was patially purified.

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RNA editing is a biological phenomena that alters nascent RNA transcripts by insertion, deletion and/or substitution of one or a few nucleotides. It is ubiquitous in all kingdoms of life and in viruses. The predominant editing event in organisms with a developed central nervous system is Adenosine to Inosine deamination. Inosine is recognized as Guanosine by the translational machinery and reverse-transcriptase. In primates, RNA editing occurs frequently in transcripts from repetitive regions of the genome. In humans, more than 500,000 editing instances have been identified, by applying computational pipelines on available ESTs and high-throughput sequencing data, and by using chemical methods. However, the functions of only a small number of cases have been studied thoroughly. RNA editing instances have been found to have roles in peptide variants synthesis by non-synonymous codon substitutions, transcript variants by alterations in splicing sites and gene silencing by miRNAs sequence modifications. We established the Database of RNA EDiting (DARNED) to accommo-date the reference genomic coordinates of substitution editing in human, mouse and fly transcripts from published literatures, with additional information on edited genomic coordinates collected from various databases e.g. UCSC, NCBI. DARNED contains mostly Adenosine to Inosine editing and allows searches based on genomic region, gene ID, and user provided sequence. The Database is accessible at http://darned.ucc.ie RNA editing instances in coding region are likely to result in recoding in protein synthesis. This encouraged me to focus my research on the occurrences of RNA editing specific CDS and non-Alu exonic regions. By applying various filters on discrepancies between available ESTs and their corresponding reference genomic sequences, putative RNA editing candidates were identified. High-throughput sequencing was used to validate these candidates. All predicted coordinates appeared to be either SNPs or unedited.

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The global rise in antibiotic resistance is a significant problem facing healthcare professionals. In particular within the cystic fibrosis (CF) lung, bacteria can establish chronic infection and resistance to a wide array of antibiotic therapies. One of the principle pathogens associated with chronic infection in the CF lung is Pseudomonas aeruginosa. P. aeruginosa can establish chronic infection in the CF lung partly through the use of the biofilm mode of growth. This biofilm mode of growth offers a considerable degree of protection from a wide variety of challenges such as the host immune system or antibiotic therapy. The threat posed by the emergence of chronic pathogens is prompting the development of next generation antimicrobials. The biofilm mode of growth is often central to the establishment of chronic infection and the development of antibiotic resistance. Thus, targeting biofilm formation has emerged as one of the principle strategies for the development of next generation antimicrobials. In this thesis two separate approaches were used to identify potential anti - biofilm targets. The first strategy focused on the identification of novel genes with a role in a biofilm formation. High throughput screening identified almost 300 genes which had a role in biofilm formation. A number of these genes were characterised at a phenotypic and a molecular level. The second strategy focused on the identification of compounds capable of inhibiting biofilm formation. A collection of marine sponge isolated bacteria were screened for the ability to inhibit the central pathway regulating biofilm formation, quorum sensing. A number of distinct isolates were identified that had quorum sensing inhibition activity from which, a Pseudomonas isolate was selected for further characterisation. A specific compound capable of inhibiting quorum sensing was identified using chemical analytical technologies in the supernatant of this marine isolate.

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Real time monitoring of oxygenation and respiration is on the cutting edge of bioanalysis, including studies of cell metabolism, bioenergetics, mitochondrial function and drug toxicity. This thesis presents the development and evaluation of new luminescent probes and techniques for intracellular O2 sensing and imaging. A new oxygen consumption rate (OCR) platform based on the commercial microfluidic perfusion channel μ-slides compatible with extra- and intracellular O2 sensitive probes, different cell lines and measurement conditions was developed. The design of semi-closed channels allowed cell treatments, multiplexing with other assays and two-fold higher sensitivity to compare with microtiter plate. We compared three common OCR platforms: hermetically sealed quartz cuvettes for absolute OCRs, partially sealed with mineral oil 96-WPs for relative OCRs, and open 96-WPs for local cell oxygenation. Both 96-WP platforms were calibrated against absolute OCR platform with MEF cell line, phosphorescent O2 probe MitoXpress-Intra and time-resolved fluorescence reader. Found correlations allow tracing of cell respiration over time in a high throughput format with the possibility of cell stimulation and of changing measurement conditions. A new multimodal intracellular O2 probe, based on the phosphorescent reporter dye PtTFPP, fluorescent FRET donor and two-photon antennae PFO and cationic nanoparticles RL-100 was described. This probe, called MM2, possesses high brightness, photo- and chemical stability, low toxicity, efficient cell staining and high-resolution intracellular O2 imaging with 2D and 3D cell cultures in intensity, ratiometric and lifetime-based modalities with luminescence readers and FLIM microscopes. Extended range of O2 sensitive probes was designed and studied in order to optimize their spectral characteristics and intracellular targeting, using different NPs materials, delivery vectors, ratiometric pairs and IR dyes. The presented improvements provide useful tool for high sensitive monitoring and imaging of intracellular O2 in different measurement formats with wide range of physiological applications.

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The generation of recombinant antibodies (Abs) using phage display is a proven method to obtain a large variety of Abs that bind with high affinity to a given antigen. Traditionally, the generation of single-chain Abs depends on the use of recombinant proteins in several stages of the procedure. This can be a problem, especially in the case of cell-surface receptors, because Abs generated and selected against recombinant proteins may not bind the same protein expressed on a cell surface in its native form and because the expression of some receptors as recombinant proteins is problematic. To overcome these difficulties, we developed a strategy to generate single-chain Abs that does not require the use of recombinant protein at any stage of the procedure. In this strategy, stably transfected cells are used for the immunization of mice, measuring Ab responses to immunization, panning the phage library, high-throughput screening of arrayed phage clones, and characterization of recombinant single-chain variable regions. This strategy was used to generate a panel of single-chain Abs specific for the innate immunity receptor Toll-like receptor 2. Once generated, individual single-chain variable regions were subcloned into an expression vector allowing the production of recombinant Abs in insect cells, thus avoiding the contamination of recombinant Abs with microbial products. This cell-based system efficiently generates Abs that bind to native molecules on the cell surface, bypasses the requirement of recombinant protein production, and avoids risks of microbial component contamination.

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The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make predictions based on clustering of simple physical parameters. Their usefulness depends on the availability of reliable data over the entire parameter space. Recent development of high-throughput methods opens the possibility to enhance these empirical structure maps by ab initio calculations in regions of the parameter space where the experimental evidence is lacking or not well characterized. In this paper we construct enhanced maps for the binary alloys of hcp metals, where the experimental data leaves large regions of poorly characterized systems believed to be phase separating. In these enhanced maps, the clusters of noncompound-forming systems are much smaller than indicated by the empirical results alone. © 2010 The American Physical Society.

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The dynamic interaction between laser-generated tandem bubble and individual polystyrene particles of 2 and 10 μm in diameter is studied in a microfluidic channel (25 μm height) by high-speed imaging and particle image velocimetry. The asymmetric collapse of the tandem bubble produces a pair of microjets and associated long-lasting vortices that can propel a single particle to a maximum velocity of 1.4 m∕s in 30 μs after the bubble collapse with a resultant directional displacement up to 60 μm in 150 μs. This method may be useful for high-throughput cell sorting in microfluidic devices.

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We developed a high-throughput yeast-based assay to screen for chemical inhibitors of Ca(2+)/calmodulin-dependent kinase pathways. After screening two small libraries, we identified the novel antagonist 125-C9, a substituted ethyleneamine. In vitro kinase assays confirmed that 125-C9 inhibited several calmodulin-dependent kinases (CaMKs) competitively with Ca(2+)/calmodulin (Ca(2+)/CaM). This suggested that 125-C9 acted as an antagonist for Ca(2+)/CaM rather than for CaMKs. We confirmed this hypothesis by showing that 125-C9 binds directly to Ca(2+)/CaM using isothermal titration calorimetry. We further characterized binding of 125-C9 to Ca(2+)/CaM and compared its properties with those of two well-studied CaM antagonists: trifluoperazine (TFP) and W-13. Isothermal titration calorimetry revealed that binding of 125-C9 to CaM is absolutely Ca(2+)-dependent, likely occurs with a stoichiometry of five 125-C9 molecules to one CaM molecule, and involves an exchange of two protons at pH 7.0. Binding of 125-C9 is driven overall by entropy and appears to be competitive with TFP and W-13, which is consistent with occupation of similar binding sites. To test the effects of 125-C9 in living cells, we evaluated mitogen-stimulated re-entry of quiescent cells into proliferation and found similar, although slightly better, levels of inhibition by 125-C9 than by TFP and W-13. Our results not only define a novel Ca(2+)/CaM inhibitor but also reveal that chemically unique CaM antagonists can bind CaM by distinct mechanisms but similarly inhibit cellular actions of CaM.

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The binary A(8)B phase (prototype Pt(8)Ti) has been experimentally observed in 11 systems. A high-throughput search over all the binary transition intermetallics, however, reveals 59 occurrences of the A(8)B phase: Au(8)Zn(dagger), Cd(8)Sc(dagger), Cu(8)Ni(dagger), Cu(8)Zn(dagger), Hg(8)La, Ir(8)Os(dagger), Ir(8)Re, Ir(8)Ru(dagger), Ir(8)Tc, Ir(8)W(dagger), Nb(8)Os(dagger), Nb(8)Rh(dagger), Nb(8)Ru(dagger), Nb(8)Ta(dagger), Ni(8)Fe, Ni(8)Mo(dagger)*, Ni(8)Nb(dagger)*, Ni(8)Ta*, Ni(8)V*, Ni(8)W, Pd(8)Al(dagger), Pd(8)Fe, Pd(8)Hf, Pd(8)Mn, Pd(8)Mo*, Pd(8)Nb, Pd(8)Sc, Pd(8)Ta, Pd(8)Ti, Pd(8)V*, Pd(8)W*, Pd(8)Zn, Pd(8)Zr, Pt(8)Al(dagger), Pt(8)Cr*, Pt(8)Hf, Pt(8)Mn, Pt(8)Mo, Pt(8)Nb, Pt(8)Rh(dagger), Pt(8)Sc, Pt(8)Ta, Pt(8)Ti*, Pt(8)V*, Pt(8)W, Pt(8)Zr*, Rh(8)Mo, Rh(8)W, Ta(8)Pd, Ta(8)Pt, Ta(8)Rh, V(8)Cr(dagger), V(8)Fe(dagger), V(8)Ir(dagger), V(8)Ni(dagger), V(8)Pd, V(8)Pt, V(8)Rh, and V(8)Ru(dagger) ((dagger) = metastable, * = experimentally observed). This is surprising for the wealth of new occurrences that are predicted, especially in well-characterized systems (e.g., Cu-Zn). By verifying all experimental results while offering additional predictions, our study serves as a striking demonstration of the power of the high-throughput approach. The practicality of the method is demonstrated in the Rh-W system. A cluster-expansion-based Monte Carlo model reveals a relatively high order-disorder transition temperature.

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BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression in a variety of organisms, including insects, vertebrates, and plants. miRNAs play important roles in cell development and differentiation as well as in the cellular response to stress and infection. To date, there are limited reports of miRNA identification in mosquitoes, insects that act as essential vectors for the transmission of many human pathogens, including flaviviruses. West Nile virus (WNV) and dengue virus, members of the Flaviviridae family, are primarily transmitted by Aedes and Culex mosquitoes. Using high-throughput deep sequencing, we examined the miRNA repertoire in Ae. albopictus cells and Cx. quinquefasciatus mosquitoes. RESULTS: We identified a total of 65 miRNAs in the Ae. albopictus C7/10 cell line and 77 miRNAs in Cx. quinquefasciatus mosquitoes, the majority of which are conserved in other insects such as Drosophila melanogaster and Anopheles gambiae. The most highly expressed miRNA in both mosquito species was miR-184, a miRNA conserved from insects to vertebrates. Several previously reported Anopheles miRNAs, including miR-1890 and miR-1891, were also found in Culex and Aedes, and appear to be restricted to mosquitoes. We identified seven novel miRNAs, arising from nine different precursors, in C7/10 cells and Cx. quinquefasciatus mosquitoes, two of which have predicted orthologs in An. gambiae. Several of these novel miRNAs reside within a ~350 nt long cluster present in both Aedes and Culex. miRNA expression was confirmed by primer extension analysis. To determine whether flavivirus infection affects miRNA expression, we infected female Culex mosquitoes with WNV. Two miRNAs, miR-92 and miR-989, showed significant changes in expression levels following WNV infection. CONCLUSIONS: Aedes and Culex mosquitoes are important flavivirus vectors. Recent advances in both mosquito genomics and high-throughput sequencing technologies enabled us to interrogate the miRNA profile in these two species. Here, we provide evidence for over 60 conserved and seven novel mosquito miRNAs, expanding upon our current understanding of insect miRNAs. Undoubtedly, some of the miRNAs identified will have roles not only in mosquito development, but also in mediating viral infection in the mosquito host.

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This article describes advances in statistical computation for large-scale data analysis in structured Bayesian mixture models via graphics processing unit (GPU) programming. The developments are partly motivated by computational challenges arising in fitting models of increasing heterogeneity to increasingly large datasets. An example context concerns common biological studies using high-throughput technologies generating many, very large datasets and requiring increasingly high-dimensional mixture models with large numbers of mixture components.We outline important strategies and processes for GPU computation in Bayesian simulation and optimization approaches, give examples of the benefits of GPU implementations in terms of processing speed and scale-up in ability to analyze large datasets, and provide a detailed, tutorial-style exposition that will benefit readers interested in developing GPU-based approaches in other statistical models. Novel, GPU-oriented approaches to modifying existing algorithms software design can lead to vast speed-up and, critically, enable statistical analyses that presently will not be performed due to compute time limitations in traditional computational environments. Supplementalmaterials are provided with all source code, example data, and details that will enable readers to implement and explore the GPU approach in this mixture modeling context. © 2010 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

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Neurodegenerative diseases such as Huntington disease are devastating disorders with no therapeutic approaches to ameliorate the underlying protein misfolding defect inherent to poly-glutamine (polyQ) proteins. Given the mounting evidence that elevated levels of protein chaperones suppress polyQ protein misfolding, the master regulator of protein chaperone gene transcription, HSF1, is an attractive target for small molecule intervention. We describe a humanized yeast-based high-throughput screen to identify small molecule activators of human HSF1. This screen is insensitive to previously characterized activators of the heat shock response that have undesirable proteotoxic activity or that inhibit Hsp90, the central chaperone for cellular signaling and proliferation. A molecule identified in this screen, HSF1A, is structurally distinct from other characterized small molecule human HSF1 activators, activates HSF1 in mammalian and fly cells, elevates protein chaperone expression, ameliorates protein misfolding and cell death in polyQ-expressing neuronal precursor cells and protects against cytotoxicity in a fly model of polyQ-mediated neurodegeneration. In addition, we show that HSF1A interacts with components of the TRiC/CCT complex, suggesting a potentially novel regulatory role for this complex in modulating HSF1 activity. These studies describe a novel approach for the identification of new classes of pharmacological interventions for protein misfolding that underlies devastating neurodegenerative disease.

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The advent of digital microfluidic lab-on-a-chip (LoC) technology offers a platform for developing diagnostic applications with the advantages of portability, reduction of the volumes of the sample and reagents, faster analysis times, increased automation, low power consumption, compatibility with mass manufacturing, and high throughput. Moreover, digital microfluidics is being applied in other areas such as airborne chemical detection, DNA sequencing by synthesis, and tissue engineering. In most diagnostic and chemical-detection applications, a key challenge is the preparation of the analyte for presentation to the on-chip detection system. Thus, in diagnostics, raw physiological samples must be introduced onto the chip and then further processed by lysing blood cells and extracting DNA. For massively parallel DNA sequencing, sample preparation can be performed off chip, but the synthesis steps must be performed in a sequential on-chip format by automated control of buffers and nucleotides to extend the read lengths of DNA fragments. In airborne particulate-sampling applications, the sample collection from an air stream must be integrated into the LoC analytical component, which requires a collection droplet to scan an exposed impacted surface after its introduction into a closed analytical section. Finally, in tissue-engineering applications, the challenge for LoC technology is to build high-resolution (less than 10 microns) 3D tissue constructs with embedded cells and growth factors by manipulating and maintaining live cells in the chip platform. This article discusses these applications and their implementation in digital-microfluidic LoC platforms. © 2007 IEEE.