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Sample records for computational proteomics high-throughput

  1. Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

    Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

    2015-07-15

    Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. High-throughput proteomics : optical approaches.

    Davidson, George S.

    2008-09-01

    Realistic cell models could greatly accelerate our ability to engineer biochemical pathways and the production of valuable organic products, which would be of great use in the development of biofuels, pharmaceuticals, and the crops for the next green revolution. However, this level of engineering will require a great deal more knowledge about the mechanisms of life than is currently available. In particular, we need to understand the interactome (which proteins interact) as it is situated in the three dimensional geometry of the cell (i.e., a situated interactome), and the regulation/dynamics of these interactions. Methods for optical proteomics have become available that allow the monitoring and even disruption/control of interacting proteins in living cells. Here, a range of these methods is reviewed with respect to their role in elucidating the interactome and the relevant spatial localizations. Development of these technologies and their integration into the core competencies of research organizations can position whole institutions and teams of researchers to lead in both the fundamental science and the engineering applications of cellular biology. That leadership could be particularly important with respect to problems of national urgency centered around security, biofuels, and healthcare.

  3. Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

    Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

    2008-04-01

    The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

  4. Dimensioning storage and computing clusters for efficient High Throughput Computing

    CERN. Geneva

    2012-01-01

    Scientific experiments are producing huge amounts of data, and they continue increasing the size of their datasets and the total volume of data. These data are then processed by researchers belonging to large scientific collaborations, with the Large Hadron Collider being a good example. The focal point of Scientific Data Centres has shifted from coping efficiently with PetaByte scale storage to deliver quality data processing throughput. The dimensioning of the internal components in High Throughput Computing (HTC) data centers is of crucial importance to cope with all the activities demanded by the experiments, both the online (data acceptance) and the offline (data processing, simulation and user analysis). This requires a precise setup involving disk and tape storage services, a computing cluster and the internal networking to prevent bottlenecks, overloads and undesired slowness that lead to losses cpu cycles and batch jobs failures. In this paper we point out relevant features for running a successful s...

  5. Computational tools for high-throughput discovery in biology

    Jones, Neil Christopher

    2007-01-01

    High throughput data acquisition technology has inarguably transformed the landscape of the life sciences, in part by making possible---and necessary---the computational disciplines of bioinformatics and biomedical informatics. These fields focus primarily on developing tools for analyzing data and generating hypotheses about objects in nature, and it is in this context that we address three pressing problems in the fields of the computational life sciences which each require computing capaci...

  6. Intel: High Throughput Computing Collaboration: A CERN openlab / Intel collaboration

    CERN. Geneva

    2015-01-01

    The Intel/CERN High Throughput Computing Collaboration studies the application of upcoming Intel technologies to the very challenging environment of the LHC trigger and data-acquisition systems. These systems will need to transport and process many terabits of data every second, in some cases with tight latency constraints. Parallelisation and tight integration of accelerators and classical CPU via Intel's OmniPath fabric are the key elements in this project.

  7. Dimensioning storage and computing clusters for efficient high throughput computing

    Accion, E; Bria, A; Bernabeu, G; Caubet, M; Delfino, M; Espinal, X; Merino, G; Lopez, F; Martinez, F; Planas, E

    2012-01-01

    Scientific experiments are producing huge amounts of data, and the size of their datasets and total volume of data continues increasing. These data are then processed by researchers belonging to large scientific collaborations, with the Large Hadron Collider being a good example. The focal point of scientific data centers has shifted from efficiently coping with PetaByte scale storage to deliver quality data processing throughput. The dimensioning of the internal components in High Throughput Computing (HTC) data centers is of crucial importance to cope with all the activities demanded by the experiments, both the online (data acceptance) and the offline (data processing, simulation and user analysis). This requires a precise setup involving disk and tape storage services, a computing cluster and the internal networking to prevent bottlenecks, overloads and undesired slowness that lead to losses cpu cycles and batch jobs failures. In this paper we point out relevant features for running a successful data storage and processing service in an intensive HTC environment.

  8. An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

    Albert-Baskar Arul

    2013-06-01

    Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

  9. The Principals and Practice of Distributed High Throughput Computing

    CERN. Geneva

    2016-01-01

    The potential of Distributed Processing Systems to deliver computing capabilities with qualities ranging from high availability and reliability to easy expansion in functionality and capacity were recognized and formalized in the 1970’s. For more three decade these principals Distributed Computing guided the development of the HTCondor resource and job management system. The widely adopted suite of software tools offered by HTCondor are based on novel distributed computing technologies and are driven by the evolving needs of High Throughput scientific applications. We will review the principals that underpin our work, the distributed computing frameworks and technologies we developed and the lessons we learned from delivering effective and dependable software tools in an ever changing landscape computing technologies and needs that range today from a desktop computer to tens of thousands of cores offered by commercial clouds. About the speaker Miron Livny received a B.Sc. degree in Physics and Mat...

  10. A Primer on High-Throughput Computing for Genomic Selection

    Xiao-Lin eWu

    2011-02-01

    Full Text Available High-throughput computing (HTC uses computer clusters to solve advanced computational problems, with the goal of accomplishing high throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general purpose computation on a graphics processing unit (GPU provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin – Madison, which can be leveraged for genomic selection, in terms of central processing unit (CPU capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of

  11. High-Throughput Cloning and Expression Library Creation for Functional Proteomics

    Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

    2013-01-01

    The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particular important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single gene experiments, creating the need for fast, flexible and reliable cloning systems. These collections of open reading frame (ORF) clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator™ DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP12). Details can be found at http://www.proteomicstutorials.org. PMID:23457047

  12. Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

    Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

    2015-08-25

    Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

  13. COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING

    Afonnikov D.

    2012-08-01

    Full Text Available The growing need for rapid and accurate approaches for large-scale assessment of phenotypic characters in plants becomes more and more obvious in the studies looking into relationships between genotype and phenotype. This need is due to the advent of high throughput methods for analysis of genomes. Nowadays, any genetic experiment involves data on thousands and dozens of thousands of plants. Traditional ways of assessing most phenotypic characteristics (those with reliance on the eye, the touch, the ruler are little effective on samples of such sizes. Modern approaches seek to take advantage of automated phenotyping, which warrants a much more rapid data acquisition, higher accuracy of the assessment of phenotypic features, measurement of new parameters of these features and exclusion of human subjectivity from the process. Additionally, automation allows measurement data to be rapidly loaded into computer databases, which reduces data processing time.In this work, we present the WheatPGE information system designed to solve the problem of integration of genotypic and phenotypic data and parameters of the environment, as well as to analyze the relationships between the genotype and phenotype in wheat. The system is used to consolidate miscellaneous data on a plant for storing and processing various morphological traits and genotypes of wheat plants as well as data on various environmental factors. The system is available at www.wheatdb.org. Its potential in genetic experiments has been demonstrated in high-throughput phenotyping of wheat leaf pubescence.

  14. A primer on high-throughput computing for genomic selection.

    Wu, Xiao-Lin; Beissinger, Timothy M; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J M; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

    2011-01-01

    High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin-Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

  15. Machine learning in computational biology to accelerate high-throughput protein expression.

    Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

    2017-08-15

    The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  16. High-throughput computational search for strengthening precipitates in alloys

    Kirklin, S.; Saal, James E.; Hegde, Vinay I.; Wolverton, C.

    2016-01-01

    The search for high-strength alloys and precipitation hardened systems has largely been accomplished through Edisonian trial and error experimentation. Here, we present a novel strategy using high-throughput computational approaches to search for promising precipitate/alloy systems. We perform density functional theory (DFT) calculations of an extremely large space of ∼200,000 potential compounds in search of effective strengthening precipitates for a variety of different alloy matrices, e.g., Fe, Al, Mg, Ni, Co, and Ti. Our search strategy involves screening phases that are likely to produce coherent precipitates (based on small lattice mismatch) and are composed of relatively common alloying elements. When combined with the Open Quantum Materials Database (OQMD), we can computationally screen for precipitates that either have a stable two-phase equilibrium with the host matrix, or are likely to precipitate as metastable phases. Our search produces (for the structure types considered) nearly all currently known high-strength precipitates in a variety of fcc, bcc, and hcp matrices, thus giving us confidence in the strategy. In addition, we predict a number of new, currently-unknown precipitate systems that should be explored experimentally as promising high-strength alloy chemistries.

  17. Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

    Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

    2017-10-01

    The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

  18. High throughput proteomic analysis of the secretome in an explant model of articular cartilage inflammation

    Clutterbuck, Abigail L.; Smith, Julia R.; Allaway, David; Harris, Pat; Liddell, Susan; Mobasheri, Ali

    2011-01-01

    This study employed a targeted high-throughput proteomic approach to identify the major proteins present in the secretome of articular cartilage. Explants from equine metacarpophalangeal joints were incubated alone or with interleukin-1beta (IL-1β, 10 ng/ml), with or without carprofen, a non-steroidal anti-inflammatory drug, for six days. After tryptic digestion of culture medium supernatants, resulting peptides were separated by HPLC and detected in a Bruker amaZon ion trap instrument. The five most abundant peptides in each MS scan were fragmented and the fragmentation patterns compared to mammalian entries in the Swiss-Prot database, using the Mascot search engine. Tryptic peptides originating from aggrecan core protein, cartilage oligomeric matrix protein (COMP), fibronectin, fibromodulin, thrombospondin-1 (TSP-1), clusterin (CLU), cartilage intermediate layer protein-1 (CILP-1), chondroadherin (CHAD) and matrix metalloproteinases MMP-1 and MMP-3 were detected. Quantitative western blotting confirmed the presence of CILP-1, CLU, MMP-1, MMP-3 and TSP-1. Treatment with IL-1β increased MMP-1, MMP-3 and TSP-1 and decreased the CLU precursor but did not affect CILP-1 and CLU levels. Many of the proteins identified have well-established extracellular matrix functions and are involved in early repair/stress responses in cartilage. This high throughput approach may be used to study the changes that occur in the early stages of osteoarthritis. PMID:21354348

  19. High-throughput sperm differential proteomics suggests that epigenetic alterations contribute to failed assisted reproduction.

    Azpiazu, Rubén; Amaral, Alexandra; Castillo, Judit; Estanyol, Josep Maria; Guimerà, Marta; Ballescà, Josep Lluís; Balasch, Juan; Oliva, Rafael

    2014-06-01

    Are there quantitative alterations in the proteome of normozoospermic sperm samples that are able to complete IVF but whose female partner does not achieve pregnancy? Normozoospermic sperm samples with different IVF outcomes (pregnancy versus no pregnancy) differed in the levels of at least 66 proteins. The analysis of the proteome of sperm samples with distinct fertilization capacity using low-throughput proteomic techniques resulted in the detection of a few differential proteins. Current high-throughput mass spectrometry approaches allow the identification and quantification of a substantially higher number of proteins. This was a case-control study including 31 men with normozoospermic sperm and their partners who underwent IVF with successful fertilization recruited between 2007 and 2008. Normozoospermic sperm samples from 15 men whose female partners did not achieve pregnancy after IVF (no pregnancy) and 16 men from couples that did achieve pregnancy after IVF (pregnancy) were included in this study. To perform the differential proteomic experiments, 10 no pregnancy samples and 10 pregnancy samples were separately pooled and subsequently used for tandem mass tags (TMT) protein labelling, sodium dodecyl sulphate-polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry (LC-MS/MS) identification and peak intensity relative protein quantification. Bioinformatic analyses were performed using UniProt Knowledgebase, DAVID and Reactome. Individual samples (n = 5 no pregnancy samples; n = 6 pregnancy samples) and aliquots from the above TMT pools were used for western blotting. By using TMT labelling and LC-MS/MS, we have detected 31 proteins present at lower abundance (ratio no pregnancy/pregnancy 1.5) in the no pregnancy group. Bioinformatic analyses showed that the proteins with differing abundance are involved in chromatin assembly and lipoprotein metabolism (P values Economia y Competividad; FEDER BFU 2009-07118 and PI13/00699) and

  20. A high-throughput sample preparation method for cellular proteomics using 96-well filter plates.

    Switzar, Linda; van Angeren, Jordy; Pinkse, Martijn; Kool, Jeroen; Niessen, Wilfried M A

    2013-10-01

    A high-throughput sample preparation protocol based on the use of 96-well molecular weight cutoff (MWCO) filter plates was developed for shotgun proteomics of cell lysates. All sample preparation steps, including cell lysis, buffer exchange, protein denaturation, reduction, alkylation and proteolytic digestion are performed in a 96-well plate format, making the platform extremely well suited for processing large numbers of samples and directly compatible with functional assays for cellular proteomics. In addition, the usage of a single plate for all sample preparation steps following cell lysis reduces potential samples losses and allows for automation. The MWCO filter also enables sample concentration, thereby increasing the overall sensitivity, and implementation of washing steps involving organic solvents, for example, to remove cell membranes constituents. The optimized protocol allowed for higher throughput with improved sensitivity in terms of the number of identified cellular proteins when compared to an established protocol employing gel-filtration columns. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Elucidation of the compatible interaction between banana and Meloidogyne incognita via high-throughput proteome profiling.

    Aisyafaznim Al-Idrus

    Full Text Available With a diverse host range, Meloidogyne incognita (root-knot nematode is listed as one of the most economically important obligate parasites of agriculture. This nematode species establishes permanent feeding sites in plant root systems soon after infestation. A compatible host-nematode interaction triggers a cascade of morphological and physiological process disruptions of the host, leading to pathogenesis. Such disruption is reflected by altered gene expression in affected cells, detectable using molecular approaches. We employed a high-throughput proteomics approach to elucidate the events involved in a compatible banana- M. incognita interaction. This study serves as the first crucial step in developing natural banana resistance for the purpose of biological-based nematode management programme. We successfully profiled 114 Grand naine root proteins involved in the interaction with M. incognita at the 30th- and 60th- day after inoculation (dai. The abundance of proteins involved in fundamental biological processes, cellular component organisation and stress responses were significantly altered in inoculated root samples. In addition, the abundance of proteins in pathways associated with defence and giant cell maintenance in plants such as phenylpropanoid biosynthesis, glycolysis and citrate cycle were also implicated by the infestation.

  2. High-Throughput Quantitative Proteomic Analysis of Dengue Virus Type 2 Infected A549 Cells

    Chiu, Han-Chen; Hannemann, Holger; Heesom, Kate J.; Matthews, David A.; Davidson, Andrew D.

    2014-01-01

    Disease caused by dengue virus is a global health concern with up to 390 million individuals infected annually worldwide. There are no vaccines or antiviral compounds available to either prevent or treat dengue disease which may be fatal. To increase our understanding of the interaction of dengue virus with the host cell, we analyzed changes in the proteome of human A549 cells in response to dengue virus type 2 infection using stable isotope labelling in cell culture (SILAC) in combination with high-throughput mass spectrometry (MS). Mock and infected A549 cells were fractionated into nuclear and cytoplasmic extracts before analysis to identify proteins that redistribute between cellular compartments during infection and reduce the complexity of the analysis. We identified and quantified 3098 and 2115 proteins in the cytoplasmic and nuclear fractions respectively. Proteins that showed a significant alteration in amount during infection were examined using gene enrichment, pathway and network analysis tools. The analyses revealed that dengue virus infection modulated the amounts of proteins involved in the interferon and unfolded protein responses, lipid metabolism and the cell cycle. The SILAC-MS results were validated for a select number of proteins over a time course of infection by Western blotting and immunofluorescence microscopy. Our study demonstrates for the first time the power of SILAC-MS for identifying and quantifying novel changes in cellular protein amounts in response to dengue virus infection. PMID:24671231

  3. High-throughput quantitative proteomic analysis of dengue virus type 2 infected A549 cells.

    Han-Chen Chiu

    Full Text Available Disease caused by dengue virus is a global health concern with up to 390 million individuals infected annually worldwide. There are no vaccines or antiviral compounds available to either prevent or treat dengue disease which may be fatal. To increase our understanding of the interaction of dengue virus with the host cell, we analyzed changes in the proteome of human A549 cells in response to dengue virus type 2 infection using stable isotope labelling in cell culture (SILAC in combination with high-throughput mass spectrometry (MS. Mock and infected A549 cells were fractionated into nuclear and cytoplasmic extracts before analysis to identify proteins that redistribute between cellular compartments during infection and reduce the complexity of the analysis. We identified and quantified 3098 and 2115 proteins in the cytoplasmic and nuclear fractions respectively. Proteins that showed a significant alteration in amount during infection were examined using gene enrichment, pathway and network analysis tools. The analyses revealed that dengue virus infection modulated the amounts of proteins involved in the interferon and unfolded protein responses, lipid metabolism and the cell cycle. The SILAC-MS results were validated for a select number of proteins over a time course of infection by Western blotting and immunofluorescence microscopy. Our study demonstrates for the first time the power of SILAC-MS for identifying and quantifying novel changes in cellular protein amounts in response to dengue virus infection.

  4. High throughput computing: a solution for scientific analysis

    O'Donnell, M.

    2011-01-01

    Public land management agencies continually face resource management problems that are exacerbated by climate warming, land-use change, and other human activities. As the U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) works with managers in U.S. Department of the Interior (DOI) agencies and other federal, state, and private entities, researchers are finding that the science needed to address these complex ecological questions across time and space produces substantial amounts of data. The additional data and the volume of computations needed to analyze it require expanded computing resources well beyond single- or even multiple-computer workstations. To meet this need for greater computational capacity, FORT investigated how to resolve the many computational shortfalls previously encountered when analyzing data for such projects. Our objectives included finding a solution that would:

  5. Performance Measurements in a High Throughput Computing Environment

    AUTHOR|(CDS)2145966; Gribaudo, Marco

    The IT infrastructures of companies and research centres are implementing new technologies to satisfy the increasing need of computing resources for big data analysis. In this context, resource profiling plays a crucial role in identifying areas where the improvement of the utilisation efficiency is needed. In order to deal with the profiling and optimisation of computing resources, two complementary approaches can be adopted: the measurement-based approach and the model-based approach. The measurement-based approach gathers and analyses performance metrics executing benchmark applications on computing resources. Instead, the model-based approach implies the design and implementation of a model as an abstraction of the real system, selecting only those aspects relevant to the study. This Thesis originates from a project carried out by the author within the CERN IT department. CERN is an international scientific laboratory that conducts fundamental researches in the domain of elementary particle physics. The p...

  6. Streptococcus mutans Protein Synthesis during Mixed-Species Biofilm Development by High-Throughput Quantitative Proteomics

    Klein, Marlise I.; Xiao, Jin; Lu, Bingwen; Delahunty, Claire M.; Yates, John R.; Koo, Hyun

    2012-01-01

    Biofilms formed on tooth surfaces are comprised of mixed microbiota enmeshed in an extracellular matrix. Oral biofilms are constantly exposed to environmental changes, which influence the microbial composition, matrix formation and expression of virulence. Streptococcus mutans and sucrose are key modulators associated with the evolution of virulent-cariogenic biofilms. In this study, we used a high-throughput quantitative proteomics approach to examine how S. mutans produces relevant proteins that facilitate its establishment and optimal survival during mixed-species biofilms development induced by sucrose. Biofilms of S. mutans, alone or mixed with Actinomyces naeslundii and Streptococcus oralis, were initially formed onto saliva-coated hydroxyapatite surface under carbohydrate-limiting condition. Sucrose (1%, w/v) was then introduced to cause environmental changes, and to induce biofilm accumulation. Multidimensional protein identification technology (MudPIT) approach detected up to 60% of proteins encoded by S. mutans within biofilms. Specific proteins associated with exopolysaccharide matrix assembly, metabolic and stress adaptation processes were highly abundant as the biofilm transit from earlier to later developmental stages following sucrose introduction. Our results indicate that S. mutans within a mixed-species biofilm community increases the expression of specific genes associated with glucan synthesis and remodeling (gtfBC, dexA) and glucan-binding (gbpB) during this transition (Pmutans up-regulates specific adaptation mechanisms to cope with acidic environments (F1F0-ATPase system, fatty acid biosynthesis, branched chain amino acids metabolism), and molecular chaperones (GroEL). Interestingly, the protein levels and gene expression are in general augmented when S. mutans form mixed-species biofilms (vs. single-species biofilms) demonstrating fundamental differences in the matrix assembly, survival and biofilm maintenance in the presence of other

  7. High-throughput landslide modelling using computational grids

    Wallace, M.; Metson, S.; Holcombe, L.; Anderson, M.; Newbold, D.; Brook, N.

    2012-04-01

    Landslides are an increasing problem in developing countries. Multiple landslides can be triggered by heavy rainfall resulting in loss of life, homes and critical infrastructure. Through computer simulation of individual slopes it is possible to predict the causes, timing and magnitude of landslides and estimate the potential physical impact. Geographical scientists at the University of Bristol have developed software that integrates a physically-based slope hydrology and stability model (CHASM) with an econometric model (QUESTA) in order to predict landslide risk over time. These models allow multiple scenarios to be evaluated for each slope, accounting for data uncertainties, different engineering interventions, risk management approaches and rainfall patterns. Individual scenarios can be computationally intensive, however each scenario is independent and so multiple scenarios can be executed in parallel. As more simulations are carried out the overhead involved in managing input and output data becomes significant. This is a greater problem if multiple slopes are considered concurrently, as is required both for landslide research and for effective disaster planning at national levels. There are two critical factors in this context: generated data volumes can be in the order of tens of terabytes, and greater numbers of simulations result in long total runtimes. Users of such models, in both the research community and in developing countries, need to develop a means for handling the generation and submission of landside modelling experiments, and the storage and analysis of the resulting datasets. Additionally, governments in developing countries typically lack the necessary computing resources and infrastructure. Consequently, knowledge that could be gained by aggregating simulation results from many different scenarios across many different slopes remains hidden within the data. To address these data and workload management issues, University of Bristol particle

  8. High-throughput open source computational methods for genetics and genomics

    Prins, J.C.P.

    2015-01-01

    Biology is increasingly data driven by virtue of the development of high-throughput technologies, such as DNA and RNA sequencing. Computational biology and bioinformatics are scientific disciplines that cross-over between the disciplines of biology, informatics and statistics; which is clearly

  9. Definition, modeling and simulation of a grid computing system for high throughput computing

    Caron, E; Tsaregorodtsev, A Yu

    2006-01-01

    In this paper, we study and compare grid and global computing systems and outline the benefits of having an hybrid system called dirac. To evaluate the dirac scheduling for high throughput computing, a new model is presented and a simulator was developed for many clusters of heterogeneous nodes belonging to a local network. These clusters are assumed to be connected to each other through a global network and each cluster is managed via a local scheduler which is shared by many users. We validate our simulator by comparing the experimental and analytical results of a M/M/4 queuing system. Next, we do the comparison with a real batch system and we obtain an average error of 10.5% for the response time and 12% for the makespan. We conclude that the simulator is realistic and well describes the behaviour of a large-scale system. Thus we can study the scheduling of our system called dirac in a high throughput context. We justify our decentralized, adaptive and oppor! tunistic approach in comparison to a centralize...

  10. Solid-Phase Extraction Strategies to Surmount Body Fluid Sample Complexity in High-Throughput Mass Spectrometry-Based Proteomics

    Bladergroen, Marco R.; van der Burgt, Yuri E. M.

    2015-01-01

    For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations. PMID:25692071

  11. An Automated High Performance Capillary Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometer for High-Throughput Proteomics

    Belov, Mikhail E.; Anderson, Gordon A.; Wingerd, Mark A.; Udseth, Harold R.; Tang, Keqi; Prior, David C.; Swanson, Kenneth R.; Buschbach, Michael A.; Strittmatter, Eric F.; Moore, Ronald J.; Smith, Richard D.

    2004-01-01

    We report on a fully automated 9.4 tesla Fourier transform ion resonance cyclotron (FTICR) mass spectrometer coupled to reverse-phase chromatography for high-throughput proteomic studies. Modifications made to the front-end of a commercial FTICR instrument--a dual-ESI-emitter ion source; dual-channel electrodynamic ion funnel; and collisional-cooling, selection and accumulation quadrupoles--significantly improved the sensitivity, dynamic range and mass measurement accuracy of the mass spectrometer. A high-pressure capillary liquid chromatography (LC) system was incorporated with an autosampler that enabled 24 h/day operation. A novel method for accumulating ions in the ICR cell was also developed. Unattended operation of the instrument revealed the exceptional reproducibility (1-5% deviation in elution times for peptides from a bacterial proteome), repeatability (10-20% deviation in detected abundances for peptides from the same aliquot analyzed a few weeks apart) and robustness (high-throughput operation for 5 months without downtime) of the LC/FTICR system. When combined with modulated-ion-energy gated trapping, the internal calibration of FTICR mass spectra decreased dispersion of mass measurement errors for peptide identifications in conjunction with high resolution capillary LC separations to < 5 ppm over a dynamic range for each spectrum of 10 3

  12. Multiplex High-Throughput Targeted Proteomic Assay To Identify Induced Pluripotent Stem Cells.

    Baud, Anna; Wessely, Frank; Mazzacuva, Francesca; McCormick, James; Camuzeaux, Stephane; Heywood, Wendy E; Little, Daniel; Vowles, Jane; Tuefferd, Marianne; Mosaku, Olukunbi; Lako, Majlinda; Armstrong, Lyle; Webber, Caleb; Cader, M Zameel; Peeters, Pieter; Gissen, Paul; Cowley, Sally A; Mills, Kevin

    2017-02-21

    Induced pluripotent stem cells have great potential as a human model system in regenerative medicine, disease modeling, and drug screening. However, their use in medical research is hampered by laborious reprogramming procedures that yield low numbers of induced pluripotent stem cells. For further applications in research, only the best, competent clones should be used. The standard assays for pluripotency are based on genomic approaches, which take up to 1 week to perform and incur significant cost. Therefore, there is a need for a rapid and cost-effective assay able to distinguish between pluripotent and nonpluripotent cells. Here, we describe a novel multiplexed, high-throughput, and sensitive peptide-based multiple reaction monitoring mass spectrometry assay, allowing for the identification and absolute quantitation of multiple core transcription factors and pluripotency markers. This assay provides simpler and high-throughput classification into either pluripotent or nonpluripotent cells in 7 min analysis while being more cost-effective than conventional genomic tests.

  13. Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data

    Yang, Laurence; Tan, Justin; O'Brien, Edward J.

    2015-01-01

    based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma......Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood...... at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass...

  14. Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

    Schwämmle, Veit; Braga, Thiago Verano; Roepstorff, Peter

    2015-01-01

    The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines...... for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis...

  15. A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.

    Turetschek, Reinhard; Lyon, David; Desalegn, Getinet; Kaul, Hans-Peter; Wienkoop, Stefanie

    2016-01-01

    The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identification and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workflow, cultivar-specific mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confidential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specific mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.

  16. Towards high throughput and spatiotemporal proteomics : analytical workflows and quantitative label-free mass spectrometry

    Mostovenko, Ekaterina

    2013-01-01

    A large part of modern biology is dedicated to the functional annotation and interpretation of genetic information and its influence on the subject’s phenotype. Proteomics describes the state of the system from the perspective of expression, structure, localization, interaction and function of the

  17. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    Abdurachmanov, David; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

    2014-01-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

  18. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

    2015-05-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

  19. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Muzaffar, Shahzad; Knight, Robert

    2015-01-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG). (paper)

  20. High Throughput Computing Impact on Meta Genomics (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

    Gore, Brooklin

    2011-10-12

    This presentation includes a brief background on High Throughput Computing, correlating gene transcription factors, optical mapping, genotype to phenotype mapping via QTL analysis, and current work on next gen sequencing.

  1. AELAS: Automatic ELAStic property derivations via high-throughput first-principles computation

    Zhang, S. H.; Zhang, R. F.

    2017-11-01

    The elastic properties are fundamental and important for crystalline materials as they relate to other mechanical properties, various thermodynamic qualities as well as some critical physical properties. However, a complete set of experimentally determined elastic properties is only available for a small subset of known materials, and an automatic scheme for the derivations of elastic properties that is adapted to high-throughput computation is much demanding. In this paper, we present the AELAS code, an automated program for calculating second-order elastic constants of both two-dimensional and three-dimensional single crystal materials with any symmetry, which is designed mainly for high-throughput first-principles computation. Other derivations of general elastic properties such as Young's, bulk and shear moduli as well as Poisson's ratio of polycrystal materials, Pugh ratio, Cauchy pressure, elastic anisotropy and elastic stability criterion, are also implemented in this code. The implementation of the code has been critically validated by a lot of evaluations and tests on a broad class of materials including two-dimensional and three-dimensional materials, providing its efficiency and capability for high-throughput screening of specific materials with targeted mechanical properties. Program Files doi:http://dx.doi.org/10.17632/f8fwg4j9tw.1 Licensing provisions: BSD 3-Clause Programming language: Fortran Nature of problem: To automate the calculations of second-order elastic constants and the derivations of other elastic properties for two-dimensional and three-dimensional materials with any symmetry via high-throughput first-principles computation. Solution method: The space-group number is firstly determined by the SPGLIB code [1] and the structure is then redefined to unit cell with IEEE-format [2]. Secondly, based on the determined space group number, a set of distortion modes is automatically specified and the distorted structure files are generated

  2. Morphology control in polymer blend fibers—a high throughput computing approach

    Sesha Sarath Pokuri, Balaji; Ganapathysubramanian, Baskar

    2016-08-01

    Fibers made from polymer blends have conventionally enjoyed wide use, particularly in textiles. This wide applicability is primarily aided by the ease of manufacturing such fibers. More recently, the ability to tailor the internal morphology of polymer blend fibers by carefully designing processing conditions has enabled such fibers to be used in technologically relevant applications. Some examples include anisotropic insulating properties for heat and anisotropic wicking of moisture, coaxial morphologies for optical applications as well as fibers with high internal surface area for filtration and catalysis applications. However, identifying the appropriate processing conditions from the large space of possibilities using conventional trial-and-error approaches is a tedious and resource-intensive process. Here, we illustrate a high throughput computational approach to rapidly explore and characterize how processing conditions (specifically blend ratio and evaporation rates) affect the internal morphology of polymer blends during solvent based fabrication. We focus on a PS: PMMA system and identify two distinct classes of morphologies formed due to variations in the processing conditions. We subsequently map the processing conditions to the morphology class, thus constructing a ‘phase diagram’ that enables rapid identification of processing parameters for specific morphology class. We finally demonstrate the potential for time dependent processing conditions to get desired features of the morphology. This opens up the possibility of rational stage-wise design of processing pathways for tailored fiber morphology using high throughput computing.

  3. Quantitative proteomic analysis for high-throughput screening of differential glycoproteins in hepatocellular carcinoma serum

    Gao, Hua-Jun; Chen, Ya-Jing; Zuo, Duo; Xiao, Ming-Ming; Li, Ying; Guo, Hua; Zhang, Ning; Chen, Rui-Bing

    2015-01-01

    Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC

  4. High-throughput proteomics detection of novel splice isoforms in human platelets.

    Power, Karen A

    2009-01-01

    Alternative splicing (AS) is an intrinsic regulatory mechanism of all metazoans. Recent findings suggest that 100% of multiexonic human genes give rise to splice isoforms. AS can be specific to tissue type, environment or developmentally regulated. Splice variants have also been implicated in various diseases including cancer. Detection of these variants will enhance our understanding of the complexity of the human genome and provide disease-specific and prognostic biomarkers. We adopted a proteomics approach to identify exon skip events - the most common form of AS. We constructed a database harboring the peptide sequences derived from all hypothetical exon skip junctions in the human genome. Searching tandem mass spectrometry (MS\\/MS) data against the database allows the detection of exon skip events, directly at the protein level. Here we describe the application of this approach to human platelets, including the mRNA-based verification of novel splice isoforms of ITGA2, NPEPPS and FH. This methodology is applicable to all new or existing MS\\/MS datasets.

  5. A ground-up approach to High Throughput Cloud Computing in High-Energy Physics

    AUTHOR|(INSPIRE)INSPIRE-00245123; Ganis, Gerardo; Bagnasco, Stefano

    The thesis explores various practical approaches in making existing High Throughput computing applications common in High Energy Physics work on cloud-provided resources, as well as opening the possibility for running new applications. The work is divided into two parts: firstly we describe the work done at the computing facility hosted by INFN Torino to entirely convert former Grid resources into cloud ones, eventually running Grid use cases on top along with many others in a more flexible way. Integration and conversion problems are duly described. The second part covers the development of solutions for automatizing the orchestration of cloud workers based on the load of a batch queue and the development of HEP applications based on ROOT's PROOF that can adapt at runtime to a changing number of workers.

  6. ExSTA: External Standard Addition Method for Accurate High-Throughput Quantitation in Targeted Proteomics Experiments.

    Mohammed, Yassene; Pan, Jingxi; Zhang, Suping; Han, Jun; Borchers, Christoph H

    2018-03-01

    Targeted proteomics using MRM with stable-isotope-labeled internal-standard (SIS) peptides is the current method of choice for protein quantitation in complex biological matrices. Better quantitation can be achieved with the internal standard-addition method, where successive increments of synthesized natural form (NAT) of the endogenous analyte are added to each sample, a response curve is generated, and the endogenous concentration is determined at the x-intercept. Internal NAT-addition, however, requires multiple analyses of each sample, resulting in increased sample consumption and analysis time. To compare the following three methods, an MRM assay for 34 high-to-moderate abundance human plasma proteins is used: classical internal SIS-addition, internal NAT-addition, and external NAT-addition-generated in buffer using NAT and SIS peptides. Using endogenous-free chicken plasma, the accuracy is also evaluated. The internal NAT-addition outperforms the other two in precision and accuracy. However, the curves derived by internal vs. external NAT-addition differ by only ≈3.8% in slope, providing comparable accuracies and precision with good CV values. While the internal NAT-addition method may be "ideal", this new external NAT-addition can be used to determine the concentration of high-to-moderate abundance endogenous plasma proteins, providing a robust and cost-effective alternative for clinical analyses or other high-throughput applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. LC-MS/MS-based proteome profiling in Daphnia pulex and Daphnia longicephala: the Daphnia pulex genome database as a key for high throughput proteomics in Daphnia

    Mayr Tobias

    2009-04-01

    Full Text Available Abstract Background Daphniids, commonly known as waterfleas, serve as important model systems for ecology, evolution and the environmental sciences. The sequencing and annotation of the Daphnia pulex genome both open future avenues of research on this model organism. As proteomics is not only essential to our understanding of cell function, and is also a powerful validation tool for predicted genes in genome annotation projects, a first proteomic dataset is presented in this article. Results A comprehensive set of 701,274 peptide tandem-mass-spectra, derived from Daphnia pulex, was generated, which lead to the identification of 531 proteins. To measure the impact of the Daphnia pulex filtered models database for mass spectrometry based Daphnia protein identification, this result was compared with results obtained with the Swiss-Prot and the Drosophila melanogaster database. To further validate the utility of the Daphnia pulex database for research on other Daphnia species, additional 407,778 peptide tandem-mass-spectra, obtained from Daphnia longicephala, were generated and evaluated, leading to the identification of 317 proteins. Conclusion Peptides identified in our approach provide the first experimental evidence for the translation of a broad variety of predicted coding regions within the Daphnia genome. Furthermore it could be demonstrated that identification of Daphnia longicephala proteins using the Daphnia pulex protein database is feasible but shows a slightly reduced identification rate. Data provided in this article clearly demonstrates that the Daphnia genome database is the key for mass spectrometry based high throughput proteomics in Daphnia.

  8. Extraction of drainage networks from large terrain datasets using high throughput computing

    Gong, Jianya; Xie, Jibo

    2009-02-01

    Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

  9. The impact of computer science in molecular medicine: enabling high-throughput research.

    de la Iglesia, Diana; García-Remesal, Miguel; de la Calle, Guillermo; Kulikowski, Casimir; Sanz, Ferran; Maojo, Víctor

    2013-01-01

    The Human Genome Project and the explosion of high-throughput data have transformed the areas of molecular and personalized medicine, which are producing a wide range of studies and experimental results and providing new insights for developing medical applications. Research in many interdisciplinary fields is resulting in data repositories and computational tools that support a wide diversity of tasks: genome sequencing, genome-wide association studies, analysis of genotype-phenotype interactions, drug toxicity and side effects assessment, prediction of protein interactions and diseases, development of computational models, biomarker discovery, and many others. The authors of the present paper have developed several inventories covering tools, initiatives and studies in different computational fields related to molecular medicine: medical informatics, bioinformatics, clinical informatics and nanoinformatics. With these inventories, created by mining the scientific literature, we have carried out several reviews of these fields, providing researchers with a useful framework to locate, discover, search and integrate resources. In this paper we present an analysis of the state-of-the-art as it relates to computational resources for molecular medicine, based on results compiled in our inventories, as well as results extracted from a systematic review of the literature and other scientific media. The present review is based on the impact of their related publications and the available data and software resources for molecular medicine. It aims to provide information that can be useful to support ongoing research and work to improve diagnostics and therapeutics based on molecular-level insights.

  10. High-Throughput Computing on High-Performance Platforms: A Case Study

    Oleynik, D [University of Texas at Arlington; Panitkin, S [Brookhaven National Laboratory (BNL); Matteo, Turilli [Rutgers University; Angius, Alessio [Rutgers University; Oral, H Sarp [ORNL; De, K [University of Texas at Arlington; Klimentov, A [Brookhaven National Laboratory (BNL); Wells, Jack C. [ORNL; Jha, S [Rutgers University

    2017-10-01

    The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan -- a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner.

  11. Computational and statistical methods for high-throughput mass spectrometry-based PTM analysis

    Schwämmle, Veit; Vaudel, Marc

    2017-01-01

    Cell signaling and functions heavily rely on post-translational modifications (PTMs) of proteins. Their high-throughput characterization is thus of utmost interest for multiple biological and medical investigations. In combination with efficient enrichment methods, peptide mass spectrometry analy...

  12. Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations

    Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

    2017-12-01

    Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.

  13. EGI-EUDAT integration activity - Pair data and high-throughput computing resources together

    Scardaci, Diego; Viljoen, Matthew; Vitlacil, Dejan; Fiameni, Giuseppe; Chen, Yin; sipos, Gergely; Ferrari, Tiziana

    2016-04-01

    EGI (www.egi.eu) is a publicly funded e-infrastructure put together to give scientists access to more than 530,000 logical CPUs, 200 PB of disk capacity and 300 PB of tape storage to drive research and innovation in Europe. The infrastructure provides both high throughput computing and cloud compute/storage capabilities. Resources are provided by about 350 resource centres which are distributed across 56 countries in Europe, the Asia-Pacific region, Canada and Latin America. EUDAT (www.eudat.eu) is a collaborative Pan-European infrastructure providing research data services, training and consultancy for researchers, research communities, research infrastructures and data centres. EUDAT's vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, combining the richness of numerous community-specific data repositories with the permanence and persistence of some of Europe's largest scientific data centres. EGI and EUDAT, in the context of their flagship projects, EGI-Engage and EUDAT2020, started in March 2015 a collaboration to harmonise the two infrastructures, including technical interoperability, authentication, authorisation and identity management, policy and operations. The main objective of this work is to provide end-users with a seamless access to an integrated infrastructure offering both EGI and EUDAT services and, then, pairing data and high-throughput computing resources together. To define the roadmap of this collaboration, EGI and EUDAT selected a set of relevant user communities, already collaborating with both infrastructures, which could bring requirements and help to assign the right priorities to each of them. In this way, from the beginning, this activity has been really driven by the end users. The identified user communities are

  14. Machine learning in computational biology to accelerate high-throughput protein expression

    Sastry, Anand; Monk, Jonathan M.; Tegel, Hanna

    2017-01-01

    and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide...... the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. Availability and implementation: We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template...

  15. High-throughput computational methods and software for quantitative trait locus (QTL) mapping

    Arends, Danny

    2014-01-01

    De afgelopen jaren zijn vele nieuwe technologieen zoals Tiling arrays en High throughput DNA sequencing een belangrijke rol gaan spelen binnen het onderzoeksveld van de systeem genetica. Voor onderzoekers is het extreem belangrijk om te begrijpen dat deze methodes hun manier van werken zullen gaan

  16. Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics.

    Das, Abhiram; Schneider, Hannah; Burridge, James; Ascanio, Ana Karine Martinez; Wojciechowski, Tobias; Topp, Christopher N; Lynch, Jonathan P; Weitz, Joshua S; Bucksch, Alexander

    2015-01-01

    Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput. Here, we present an open-source phenomics platform "DIRT", as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute "commons" enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size. DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots

  17. High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

    Lin, Lin; Zheng, Jiaxin; Yu, Quan; Chen, Wendong; Xing, Jinchun; Chen, Chenxi; Tian, Ruijun

    2018-03-01

    Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application

  18. Cancer panomics: computational methods and infrastructure for integrative analysis of cancer high-throughput "omics" data

    Brunak, Søren; De La Vega, Francisco M.; Rätsch, Gunnar

    2014-01-01

    Targeted cancer treatment is becoming the goal of newly developed oncology medicines and has already shown promise in some spectacular cases such as the case of BRAF kinase inhibitors in BRAF-mutant (e.g. V600E) melanoma. These developments are driven by the advent of high-throughput sequencing......, which continues to drop in cost, and that has enabled the sequencing of the genome, transcriptome, and epigenome of the tumors of a large number of cancer patients in order to discover the molecular aberrations that drive the oncogenesis of several types of cancer. Applying these technologies...... in the clinic promises to transform cancer treatment by identifying therapeutic vulnerabilities of each patient's tumor. These approaches will need to address the panomics of cancer--the integration of the complex combination of patient-specific characteristics that drive the development of each person's tumor...

  19. Evaluation of Meta scheduler Architectures and Task assignment Policies for High throughput Computing

    Caron, E; Tsaregorodtsev, A Yu

    2006-01-01

    In this paper we present a model and simulator for many clusters of heterogeneous PCs belonging to a local network. These clusters are assumed to be connected to each other through a global network and each cluster is managed via a local scheduler which is shared by many users. We validate our simulator by comparing the experimental and analytical results of a M/M/4 queuing system. These studies indicate that the simulator is consistent. Next, we do the comparison with a real batch system and we obtain an average error of 10.5\\% for the response time and 12\\% for the makespan. We conclude that the simulator is realistic and well describes the behaviour of a large-scale system. Thus we can study the scheduling of our system called \\dirac in a high throughput context. We justify our decentralized, adaptive and opportunistic approach in comparison to a centralized approach in such a context.

  20. MStern Blotting–High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates*

    Berger, Sebastian T.; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

    2015-01-01

    We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used mem...

  1. High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

    Greub, Gilbert; Kebbi-Beghdadi, Carole; Bertelli, Claire; Collyn, François; Riederer, Beat M; Yersin, Camille; Croxatto, Antony; Raoult, Didier

    2009-12-23

    With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

  2. Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds

    Mounet, Nicolas; Gibertini, Marco; Schwaller, Philippe; Campi, Davide; Merkys, Andrius; Marrazzo, Antimo; Sohier, Thibault; Castelli, Ivano Eligio; Cepellotti, Andrea; Pizzi, Giovanni; Marzari, Nicola

    2018-02-01

    Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozen 2D materials have been successfully synthesized or exfoliated. Here, we search for 2D materials that can be easily exfoliated from their parent compounds. Starting from 108,423 unique, experimentally known 3D compounds, we identify a subset of 5,619 compounds that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van der Waals density functional theory, validated against experimental structural data and calculated random phase approximation binding energies, further allowed the identification of 1,825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1,036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 compounds, we explore vibrational, electronic, magnetic and topological properties, identifying 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors.

  3. High-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsules

    Ray, Aniruddha

    2017-04-25

    Design and synthesis of degradable nanoparticles are very important in drug delivery and biosensing fields. Although accurate assessment of nanoparticle degradation rate would improve the characterization and optimization of drug delivery vehicles, current methods rely on estimating the size of the particles at discrete points over time using, for example, electron microscopy or dynamic light scattering (DLS), among other techniques, all of which have drawbacks and practical limitations. There is a significant need for a high-throughput and cost-effective technology to accurately monitor nanoparticle degradation as a function of time and using small amounts of sample. To address this need, here we present two different computational imaging-based methods for monitoring and quantification of nanoparticle degradation. The first method is suitable for discrete testing, where a computational holographic microscope is designed to track the size changes of protease-sensitive protein-core nanoparticles following degradation, by periodically sampling a subset of particles mixed with proteases. In the second method, a sandwich structure was utilized to observe, in real-time, the change in the properties of liquid nanolenses that were self-assembled around degrading nanoparticles, permitting continuous monitoring and quantification of the degradation process. These cost-effective holographic imaging based techniques enable high-throughput monitoring of the degradation of any type of nanoparticle, using an extremely small amount of sample volume that is at least 3 orders of magnitude smaller than what is required by, for example, DLS-based techniques.

  4. High-throughput measurement of rice tillers using a conveyor equipped with x-ray computed tomography

    Yang, Wanneng; Xu, Xiaochun; Duan, Lingfeng; Luo, Qingming; Chen, Shangbin; Zeng, Shaoqun; Liu, Qian

    2011-02-01

    Tillering is one of the most important agronomic traits because the number of shoots per plant determines panicle number, a key component of grain yield. The conventional method of counting tillers is still manual. Under the condition of mass measurement, the accuracy and efficiency could be gradually degraded along with fatigue of experienced staff. Thus, manual measurement, including counting and recording, is not only time consuming but also lack objectivity. To automate this process, we developed a high-throughput facility, dubbed high-throughput system for measuring automatically rice tillers (H-SMART), for measuring rice tillers based on a conventional x-ray computed tomography (CT) system and industrial conveyor. Each pot-grown rice plant was delivered into the CT system for scanning via the conveyor equipment. A filtered back-projection algorithm was used to reconstruct the transverse section image of the rice culms. The number of tillers was then automatically extracted by image segmentation. To evaluate the accuracy of this system, three batches of rice at different growth stages (tillering, heading, or filling) were tested, yielding absolute mean absolute errors of 0.22, 0.36, and 0.36, respectively. Subsequently, the complete machine was used under industry conditions to estimate its efficiency, which was 4320 pots per continuous 24 h workday. Thus, the H-SMART could determine the number of tillers of pot-grown rice plants, providing three advantages over the manual tillering method: absence of human disturbance, automation, and high throughput. This facility expands the application of agricultural photonics in plant phenomics.

  5. Reducing the cost of semi-automated in-gel tryptic digestion and GeLC sample preparation for high-throughput proteomics.

    Ruelcke, Jayde E; Loo, Dorothy; Hill, Michelle M

    2016-10-21

    Peptide generation by trypsin digestion is typically the first step in mass spectrometry-based proteomics experiments, including 'bottom-up' discovery and targeted proteomics using multiple reaction monitoring. Manual tryptic digest and the subsequent clean-up steps can add variability even before the sample reaches the analytical platform. While specialized filter plates and tips have been designed for automated sample processing, the specialty reagents required may not be accessible or feasible due to their high cost. Here, we report a lower-cost semi-automated protocol for in-gel digestion and GeLC using standard 96-well microplates. Further cost savings were realized by re-using reagent tips with optimized sample ordering. To evaluate the methodology, we compared a simple mixture of 7 proteins and a complex cell-lysate sample. The results across three replicates showed that our semi-automated protocol had performance equal to or better than a manual in-gel digestion with respect to replicate variability and level of contamination. In this paper, we also provide the Agilent Bravo method file, which can be adapted to other liquid handlers. The simplicity, reproducibility, and cost-effectiveness of our semi-automated protocol make it ideal for routine in-gel and GeLC sample preparations, as well as high throughput processing of large clinical sample cohorts. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. High-throughput screening of cellulase F mutants from multiplexed plasmid sets using an automated plate assay on a functional proteomic robotic workcell

    Qureshi Nasib

    2006-05-01

    Full Text Available Abstract Background The field of plasmid-based functional proteomics requires the rapid assay of proteins expressed from plasmid libraries. Automation is essential since large sets of mutant open reading frames are being cloned for evaluation. To date no integrated automated platform is available to carry out the entire process including production of plasmid libraries, expression of cloned genes, and functional testing of expressed proteins. Results We used a functional proteomic assay in a multiplexed setting on an integrated plasmid-based robotic workcell for high-throughput screening of mutants of cellulase F, an endoglucanase from the anaerobic fungus Orpinomyces PC-2. This allowed us to identify plasmids containing optimized clones expressing mutants with improved activity at lower pH. A plasmid library of mutagenized clones of the celF gene with targeted variations in the last four codons was constructed by site-directed PCR mutagenesis and transformed into Escherichia coli. A robotic picker integrated into the workcell was used to inoculate medium in a 96-well deep well plate, combining the transformants into a multiplexed set in each well, and the plate was incubated on the workcell. Plasmids were prepared from the multiplexed culture on the liquid handler component of the workcell and used for in vitro transcription/translation. The multiplexed expressed recombinant proteins were screened for improved activity and stability in an azo-carboxymethylcellulose plate assay. The multiplexed wells containing mutants with improved activity were identified and linked back to the corresponding multiplexed cultures stored in glycerol. Spread plates were prepared from the glycerol stocks and the workcell was used to pick single colonies from the spread plates, prepare plasmid, produce recombinant protein, and assay for activity. The screening assay and subsequent deconvolution of the multiplexed wells resulted in identification of improved Cel

  7. High throughput sequencing and proteomics to identify immunogenic proteins of a new pathogen: the dirty genome approach.

    Gilbert Greub

    Full Text Available BACKGROUND: With the availability of new generation sequencing technologies, bacterial genome projects have undergone a major boost. Still, chromosome completion needs a costly and time-consuming gap closure, especially when containing highly repetitive elements. However, incomplete genome data may be sufficiently informative to derive the pursued information. For emerging pathogens, i.e. newly identified pathogens, lack of release of genome data during gap closure stage is clearly medically counterproductive. METHODS/PRINCIPAL FINDINGS: We thus investigated the feasibility of a dirty genome approach, i.e. the release of unfinished genome sequences to develop serological diagnostic tools. We showed that almost the whole genome sequence of the emerging pathogen Parachlamydia acanthamoebae was retrieved even with relatively short reads from Genome Sequencer 20 and Solexa. The bacterial proteome was analyzed to select immunogenic proteins, which were then expressed and used to elaborate the first steps of an ELISA. CONCLUSIONS/SIGNIFICANCE: This work constitutes the proof of principle for a dirty genome approach, i.e. the use of unfinished genome sequences of pathogenic bacteria, coupled with proteomics to rapidly identify new immunogenic proteins useful to develop in the future specific diagnostic tests such as ELISA, immunohistochemistry and direct antigen detection. Although applied here to an emerging pathogen, this combined dirty genome sequencing/proteomic approach may be used for any pathogen for which better diagnostics are needed. These genome sequences may also be very useful to develop DNA based diagnostic tests. All these diagnostic tools will allow further evaluations of the pathogenic potential of this obligate intracellular bacterium.

  8. MStern Blotting-High Throughput Polyvinylidene Fluoride (PVDF) Membrane-Based Proteomic Sample Preparation for 96-Well Plates.

    Berger, Sebastian T; Ahmed, Saima; Muntel, Jan; Cuevas Polo, Nerea; Bachur, Richard; Kentsis, Alex; Steen, Judith; Steen, Hanno

    2015-10-01

    We describe a 96-well plate compatible membrane-based proteomic sample processing method, which enables the complete processing of 96 samples (or multiples thereof) within a single workday. This method uses a large-pore hydrophobic PVDF membrane that efficiently adsorbs proteins, resulting in fast liquid transfer through the membrane and significantly reduced sample processing times. Low liquid transfer speeds have prevented the useful 96-well plate implementation of FASP as a widely used membrane-based proteomic sample processing method. We validated our approach on whole-cell lysate and urine and cerebrospinal fluid as clinically relevant body fluids. Without compromising peptide and protein identification, our method uses a vacuum manifold and circumvents the need for digest desalting, making our processing method compatible with standard liquid handling robots. In summary, our new method maintains the strengths of FASP and simultaneously overcomes one of the major limitations of FASP without compromising protein identification and quantification. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  9. The performance of a new Geant4 Bertini intra-nuclear cascade model in high throughput computing (HTC) cluster architecture

    Aatos, Heikkinen; Andi, Hektor; Veikko, Karimaki; Tomas, Linden [Helsinki Univ., Institute of Physics (Finland)

    2003-07-01

    We study the performance of a new Bertini intra-nuclear cascade model implemented in the general detector simulation tool-kit Geant4 with a High Throughput Computing (HTC) cluster architecture. A 60 node Pentium III open-Mosix cluster is used with the Mosix kernel performing automatic process load-balancing across several CPUs. The Mosix cluster consists of several computer classes equipped with Windows NT workstations that automatically boot, daily and become nodes of the Mosix cluster. The models included in our study are a Bertini intra-nuclear cascade model with excitons, consisting of a pre-equilibrium model, a nucleus explosion model, a fission model and an evaporation model. The speed and accuracy obtained for these models is presented. (authors)

  10. Quantitative high-throughput profiling of snake venom gland transcriptomes and proteomes (Ovophis okinavensis and Protobothrops flavoviridis)

    2013-01-01

    Background Advances in DNA sequencing and proteomics have facilitated quantitative comparisons of snake venom composition. Most studies have employed one approach or the other. Here, both Illumina cDNA sequencing and LC/MS were used to compare the transcriptomes and proteomes of two pit vipers, Protobothrops flavoviridis and Ovophis okinavensis, which differ greatly in their biology. Results Sequencing of venom gland cDNA produced 104,830 transcripts. The Protobothrops transcriptome contained transcripts for 103 venom-related proteins, while the Ovophis transcriptome contained 95. In both, transcript abundances spanned six orders of magnitude. Mass spectrometry identified peptides from 100% of transcripts that occurred at higher than contaminant (e.g. human keratin) levels, including a number of proteins never before sequenced from snakes. These transcriptomes reveal fundamentally different envenomation strategies. Adult Protobothrops venom promotes hemorrhage, hypotension, incoagulable blood, and prey digestion, consistent with mammalian predation. Ovophis venom composition is less readily interpreted, owing to insufficient pharmacological data for venom serine and metalloproteases, which comprise more than 97.3% of Ovophis transcripts, but only 38.0% of Protobothrops transcripts. Ovophis venom apparently represents a hybrid strategy optimized for frogs and small mammals. Conclusions This study illustrates the power of cDNA sequencing combined with MS profiling. The former quantifies transcript composition, allowing detection of novel proteins, but cannot indicate which proteins are actually secreted, as does MS. We show, for the first time, that transcript and peptide abundances are correlated. This means that MS can be used for quantitative, non-invasive venom profiling, which will be beneficial for studies of endangered species. PMID:24224955

  11. A High-Throughput Computational Framework for Identifying Significant Copy Number Aberrations from Array Comparative Genomic Hybridisation Data

    Ian Roberts

    2012-01-01

    Full Text Available Reliable identification of copy number aberrations (CNA from comparative genomic hybridization data would be improved by the availability of a generalised method for processing large datasets. To this end, we developed swatCGH, a data analysis framework and region detection heuristic for computational grids. swatCGH analyses sequentially displaced (sliding windows of neighbouring probes and applies adaptive thresholds of varying stringency to identify the 10% of each chromosome that contains the most frequently occurring CNAs. We used the method to analyse a published dataset, comparing data preprocessed using four different DNA segmentation algorithms, and two methods for prioritising the detected CNAs. The consolidated list of the most commonly detected aberrations confirmed the value of swatCGH as a simplified high-throughput method for identifying biologically significant CNA regions of interest.

  12. High-throughput proteomic characterization of plasma rich in growth factors (PRGF-Endoret)-derived fibrin clot interactome.

    Anitua, Eduardo; Prado, Roberto; Azkargorta, Mikel; Rodriguez-Suárez, Eva; Iloro, Ibon; Casado-Vela, Juan; Elortza, Felix; Orive, Gorka

    2015-11-01

    Plasma rich in growth factors (PRGF®-Endoret®) is an autologous technology that contains a set of proteins specifically addressed to wound healing and tissue regeneration. The scaffold formed by using this technology is a clot mainly composed of fibrin protein, forming a three-dimensional (3D) macroscopic network. This biomaterial is easily obtained by biotechnological means from blood and can be used in a range of situations to help wound healing and tissue regeneration. Although the main constituent of this clot is the fibrin scaffold, little is known about other proteins interacting in this clot that may act as adjuvants in the healing process. The aim of this study was to characterize the proteins enclosed by PRGF-Endoret scaffold, using a double-proteomic approach that combines 1D-SDS-PAGE approach followed by LC-MS/MS, and 2-DE followed by MALDI-TOF/TOF. The results presented here provide a description of the catalogue of key proteins in close contact with the fibrin scaffold. The obtained lists of proteins were grouped into families and networks according to gene ontology. Taken together, an enrichment of both proteins and protein families specifically involved in tissue regeneration and wound healing has been found. Copyright © 2013 John Wiley & Sons, Ltd.

  13. FPGA Compute Acceleration for High-Throughput Data Processing in High-Energy Physics Experiments

    CERN. Geneva

    2017-01-01

    The upgrades of the four large experiments of the LHC at CERN in the coming years will result in a huge increase of data bandwidth for each experiment which needs to be processed very efficiently. For example the LHCb experiment will upgrade its detector 2019/2020 to a 'triggerless' readout scheme, where all of the readout electronics and several sub-detector parts will be replaced. The new readout electronics will be able to readout the detector at 40MHz. This increases the data bandwidth from the detector down to the event filter farm to 40TBit/s, which must be processed to select the interesting proton-proton collisions for later storage. The architecture of such a computing farm, which can process this amount of data as efficiently as possible, is a challenging task and several compute accelerator technologies are being considered.    In the high performance computing sector more and more FPGA compute accelerators are being used to improve the compute performance and reduce the...

  14. High-Throughput Computational Assessment of Previously Synthesized Semiconductors for Photovoltaic and Photoelectrochemical Devices

    Kuhar, Korina; Pandey, Mohnish; Thygesen, Kristian Sommer

    2018-01-01

    Using computational screening we identify materials with potential use as light absorbers in photovoltaic or photoelectrochemical devices. The screening focuses on compounds of up to three different chemical elements which are abundant and nontoxic. A prescreening is carried out based on informat...

  15. Secure and robust cloud computing for high-throughput forensic microsatellite sequence analysis and databasing.

    Bailey, Sarah F; Scheible, Melissa K; Williams, Christopher; Silva, Deborah S B S; Hoggan, Marina; Eichman, Christopher; Faith, Seth A

    2017-11-01

    Next-generation Sequencing (NGS) is a rapidly evolving technology with demonstrated benefits for forensic genetic applications, and the strategies to analyze and manage the massive NGS datasets are currently in development. Here, the computing, data storage, connectivity, and security resources of the Cloud were evaluated as a model for forensic laboratory systems that produce NGS data. A complete front-to-end Cloud system was developed to upload, process, and interpret raw NGS data using a web browser dashboard. The system was extensible, demonstrating analysis capabilities of autosomal and Y-STRs from a variety of NGS instrumentation (Illumina MiniSeq and MiSeq, and Oxford Nanopore MinION). NGS data for STRs were concordant with standard reference materials previously characterized with capillary electrophoresis and Sanger sequencing. The computing power of the Cloud was implemented with on-demand auto-scaling to allow multiple file analysis in tandem. The system was designed to store resulting data in a relational database, amenable to downstream sample interpretations and databasing applications following the most recent guidelines in nomenclature for sequenced alleles. Lastly, a multi-layered Cloud security architecture was tested and showed that industry standards for securing data and computing resources were readily applied to the NGS system without disadvantageous effects for bioinformatic analysis, connectivity or data storage/retrieval. The results of this study demonstrate the feasibility of using Cloud-based systems for secured NGS data analysis, storage, databasing, and multi-user distributed connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction

    Butenko Melinka A

    2009-10-01

    Full Text Available Abstract Background When generating a genetically modified organism (GMO, the primary goal is to give a target organism one or several novel traits by using biotechnology techniques. A GMO will differ from its parental strain in that its pool of transcripts will be altered. Currently, there are no methods that are reliably able to determine if an organism has been genetically altered if the nature of the modification is unknown. Results We show that the concept of computational subtraction can be used to identify transgenic cDNA sequences from genetically modified plants. Our datasets include 454-type sequences from a transgenic line of Arabidopsis thaliana and published EST datasets from commercially relevant species (rice and papaya. Conclusion We believe that computational subtraction represents a powerful new strategy for determining if an organism has been genetically modified as well as to define the nature of the modification. Fewer assumptions have to be made compared to methods currently in use and this is an advantage particularly when working with unknown GMOs.

  17. ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

    Ramos Hector

    2011-03-01

    Full Text Available Abstract Background Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology. Result We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM, which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM. ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site. This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser. Conclusions Targeted

  18. Scalable Computational Methods for the Analysis of High-Throughput Biological Data

    Langston, Michael A. [Univ. of Tennessee, Knoxville, TN (United States)

    2012-09-06

    This primary focus of this research project is elucidating genetic regulatory mechanisms that control an organism's responses to low-dose ionizing radiation. Although low doses (at most ten centigrays) are not lethal to humans, they elicit a highly complex physiological response, with the ultimate outcome in terms of risk to human health unknown. The tools of molecular biology and computational science will be harnessed to study coordinated changes in gene expression that orchestrate the mechanisms a cell uses to manage the radiation stimulus. High performance implementations of novel algorithms that exploit the principles of fixed-parameter tractability will be used to extract gene sets suggestive of co-regulation. Genomic mining will be performed to scrutinize, winnow and highlight the most promising gene sets for more detailed investigation. The overall goal is to increase our understanding of the health risks associated with exposures to low levels of radiation.

  19. High-Throughput Proteomics Using High Efficiency Multiple-Capillary Liquid Chromatography With On-Line High-Performance ESI FTICR Mass Spectrometry

    Shen, Yufeng (BATTELLE (PACIFIC NW LAB)); Tolic, Nikola (BATTELLE (PACIFIC NW LAB)); Zhao, Rui (ASSOC WESTERN UNIVERSITY); Pasa Tolic, Ljiljana (BATTELLE (PACIFIC NW LAB)); Li, Lingjun (Illinois Univ Of-Urbana/Champa); Berger, Scott J.(ASSOC WESTERN UNIVERSITY); Harkewicz, Richard (BATTELLE (PACIFIC NW LAB)); Anderson, Gordon A.(BATTELLE (PACIFIC NW LAB)); Belov, Mikhail E.(BATTELLE (PACIFIC NW LAB)); Smith, Richard D.(BATTELLE (PACIFIC NW LAB))

    2000-12-01

    We report on the design and application of a high-efficiency multiple-capillary liquid chromatography (LC) system for high-throughput proteome analysis. The multiple-capillary LC system was operated at the pressure of 10,000 psi using commercial LC pumps to deliver the mobile phase and newly developed passive feedback valves to switch the mobile phase flow and introduce samples. The multiple-capillary LC system was composed of several serially connected dual-capillary column devices. The dual-capillary column approach was designed to eliminate the time delay for regeneration (or equilibrium) of the capillary column after its use under the mobile phase gradient condition (i.e. one capillary column was used in separation and the other was washed using mobile phase A). The serially connected dual-capillary columns and ESI sources were operated independently, and could be used for either''backup'' operation or with other mass spectrometer(s). This high-efficiency multiple-capillary LC system uses switching valves for all operations and is highly amenable to automation. The separations efficiency of dual-capillary column device, optimal capillary dimensions (column length and packed particle size), suitable mobile phases for electrospray, and the capillary re-generation were investigated. A high magnetic field (11.5 tesla) Fourier transform ion cyclotron resonance (FTICR) mass spectrometer was coupled on-line with this high-efficiency multiple-capillary LC system through an electrospray ionization source. The capillary LC provided a peak capacity of {approx}600, and the 2-D capillary LC-FTICR provided a combined resolving power of > 6 x 10 7 polypeptide isotopic distributions. For yeast cellular tryptic digests, > 100,000 polypeptides were typically detected, and {approx}1,000 proteins can be characterized in a single run.

  20. High Throughput Facility

    Federal Laboratory Consortium — Argonne?s high throughput facility provides highly automated and parallel approaches to material and materials chemistry development. The facility allows scientists...

  1. Injection of fully-defined signal mixtures: a novel high-throughput tool to study neuronal encoding and computations.

    Vladimir Ilin

    discuss several open questions that this novel high-throughput paradigm may address.

  2. High-Throughput Computational Screening of the Metal Organic Framework Database for CH4/H2 Separations.

    Altintas, Cigdem; Erucar, Ilknur; Keskin, Seda

    2018-01-31

    Metal organic frameworks (MOFs) have been considered as one of the most exciting porous materials discovered in the last decade. Large surface areas, high pore volumes, and tailorable pore sizes make MOFs highly promising in a variety of applications, mainly in gas separations. The number of MOFs has been increasing very rapidly, and experimental identification of materials exhibiting high gas separation potential is simply impractical. High-throughput computational screening studies in which thousands of MOFs are evaluated to identify the best candidates for target gas separation is crucial in directing experimental efforts to the most useful materials. In this work, we used molecular simulations to screen the most complete and recent collection of MOFs from the Cambridge Structural Database to unlock their CH 4 /H 2 separation performances. This is the first study in the literature, which examines the potential of all existing MOFs for adsorption-based CH 4 /H 2 separation. MOFs (4350) were ranked based on several adsorbent evaluation metrics including selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability. A large number of MOFs were identified to have extraordinarily large CH 4 /H 2 selectivities compared to traditional adsorbents such as zeolites and activated carbons. We examined the relations between structural properties of MOFs such as pore sizes, porosities, and surface areas and their selectivities. Correlations between the heat of adsorption, adsorbility, metal type of MOFs, and selectivities were also studied. On the basis of these relations, a simple mathematical model that can predict the CH 4 /H 2 selectivity of MOFs was suggested, which will be very useful in guiding the design and development of new MOFs with extraordinarily high CH 4 /H 2 separation performances.

  3. Computing the functional proteome

    O'Brien, Edward J.; Palsson, Bernhard

    2015-01-01

    Constraint-based models enable the computation of feasible, optimal, and realized biological phenotypes from reaction network reconstructions and constraints on their operation. To date, stoichiometric reconstructions have largely focused on metabolism, resulting in genome-scale metabolic models (M...

  4. Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

    Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

    2015-01-01

    Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

  5. Computational toxicology as implemented by the U.S. EPA: providing high throughput decision support tools for screening and assessing chemical exposure, hazard and risk.

    Kavlock, Robert; Dix, David

    2010-02-01

    Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environmental Protection Agency EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in air, water, and hazardous-waste sites. The Office of Research and Development (ORD) Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the U.S. EPA Science to Achieve Results (STAR) program. Together these elements form the key components in the implementation of both the initial strategy, A Framework for a Computational Toxicology Research Program (U.S. EPA, 2003), and the newly released The U.S. Environmental Protection Agency's Strategic Plan for Evaluating the Toxicity of Chemicals (U.S. EPA, 2009a). Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast) and exposure (ExpoCast), and creating virtual liver (v-Liver) and virtual embryo (v-Embryo) systems models. U.S. EPA-funded STAR centers are also providing bioinformatics, computational toxicology data and models, and developmental toxicity data and models. The models and underlying data are being made publicly

  6. CSReport: A New Computational Tool Designed for Automatic Analysis of Class Switch Recombination Junctions Sequenced by High-Throughput Sequencing.

    Boyer, François; Boutouil, Hend; Dalloul, Iman; Dalloul, Zeinab; Cook-Moreau, Jeanne; Aldigier, Jean-Claude; Carrion, Claire; Herve, Bastien; Scaon, Erwan; Cogné, Michel; Péron, Sophie

    2017-05-15

    B cells ensure humoral immune responses due to the production of Ag-specific memory B cells and Ab-secreting plasma cells. In secondary lymphoid organs, Ag-driven B cell activation induces terminal maturation and Ig isotype class switch (class switch recombination [CSR]). CSR creates a virtually unique IgH locus in every B cell clone by intrachromosomal recombination between two switch (S) regions upstream of each C region gene. Amount and structural features of CSR junctions reveal valuable information about the CSR mechanism, and analysis of CSR junctions is useful in basic and clinical research studies of B cell functions. To provide an automated tool able to analyze large data sets of CSR junction sequences produced by high-throughput sequencing (HTS), we designed CSReport, a software program dedicated to support analysis of CSR recombination junctions sequenced with a HTS-based protocol (Ion Torrent technology). CSReport was assessed using simulated data sets of CSR junctions and then used for analysis of Sμ-Sα and Sμ-Sγ1 junctions from CH12F3 cells and primary murine B cells, respectively. CSReport identifies junction segment breakpoints on reference sequences and junction structure (blunt-ended junctions or junctions with insertions or microhomology). Besides the ability to analyze unprecedentedly large libraries of junction sequences, CSReport will provide a unified framework for CSR junction studies. Our results show that CSReport is an accurate tool for analysis of sequences from our HTS-based protocol for CSR junctions, thereby facilitating and accelerating their study. Copyright © 2017 by The American Association of Immunologists, Inc.

  7. Serial isoelectric focusing as an effective and economic way to obtain maximal resolution and high-throughput in 2D-based comparative proteomics of scarce samples: proof-of-principle.

    Farhoud, Murtada H; Wessels, Hans J C T; Wevers, Ron A; van Engelen, Baziel G; van den Heuvel, Lambert P; Smeitink, Jan A

    2005-01-01

    In 2D-based comparative proteomics of scarce samples, such as limited patient material, established methods for prefractionation and subsequent use of different narrow range IPG strips to increase overall resolution are difficult to apply. Also, a high number of samples, a prerequisite for drawing meaningful conclusions when pathological and control samples are considered, will increase the associated amount of work almost exponentially. Here, we introduce a novel, effective, and economic method designed to obtain maximum 2D resolution while maintaining the high throughput necessary to perform large-scale comparative proteomics studies. The method is based on connecting different IPG strips serially head-to-tail so that a complete line of different IPG strips with sequential pH regions can be focused in the same experiment. We show that when 3 IPG strips (covering together the pH range of 3-11) are connected head-to-tail an optimal resolution is achieved along the whole pH range. Sample consumption, time required, and associated costs are reduced by almost 70%, and the workload is reduced significantly.

  8. Computer Vision for High-Throughput Quantitative Phenotyping: A Case Study of Grapevine Downy Mildew Sporulation and Leaf Trichomes.

    Divilov, Konstantin; Wiesner-Hanks, Tyr; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

    2017-12-01

    Quantitative phenotyping of downy mildew sporulation is frequently used in plant breeding and genetic studies, as well as in studies focused on pathogen biology such as chemical efficacy trials. In these scenarios, phenotyping a large number of genotypes or treatments can be advantageous but is often limited by time and cost. We present a novel computational pipeline dedicated to estimating the percent area of downy mildew sporulation from images of inoculated grapevine leaf discs in a manner that is time and cost efficient. The pipeline was tested on images from leaf disc assay experiments involving two F 1 grapevine families, one that had glabrous leaves (Vitis rupestris B38 × 'Horizon' [RH]) and another that had leaf trichomes (Horizon × V. cinerea B9 [HC]). Correlations between computer vision and manual visual ratings reached 0.89 in the RH family and 0.43 in the HC family. Additionally, we were able to use the computer vision system prior to sporulation to measure the percent leaf trichome area. We estimate that an experienced rater scoring sporulation would spend at least 90% less time using the computer vision system compared with the manual visual method. This will allow more treatments to be phenotyped in order to better understand the genetic architecture of downy mildew resistance and of leaf trichome density. We anticipate that this computer vision system will find applications in other pathosystems or traits where responses can be imaged with sufficient contrast from the background.

  9. Many-core technologies: The move to energy-efficient, high-throughput x86 computing (TFLOPS on a chip)

    CERN. Geneva

    2012-01-01

    With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms at all levels of integration and programming to achieve higher performance and energy efficiency. Especially in the area of High-Performance Computing (HPC) users can entertain a combination of different hardware and software parallel architectures and programming environments. Those technologies range from vectorization and SIMD computation over shared memory multi-threading (e.g. OpenMP) to distributed memory message passing (e.g. MPI) on cluster systems. We will discuss HPC industry trends and Intel's approach to it from processor/system architectures and research activities to hardware and software tools technologies. This includes the recently announced new Intel(r) Many Integrated Core (MIC) architecture for highly-parallel workloads and general purpose, energy efficient TFLOPS performance, some of its architectural features and its programming environment. At the end we will have a br...

  10. SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data

    Miller, Mark P.; Knaus, Brian J.; Mullins, Thomas D.; Haig, Susan M.

    2013-01-01

    SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (SSRs; for example, microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains three analysis modules along with a fourth control module that can be used to automate analyses of large volumes of data. The modules are used to (1) identify the subset of paired-end sequences that pass quality standards, (2) align paired-end reads into a single composite DNA sequence, and (3) identify sequences that possess microsatellites conforming to user specified parameters. Each of the three separate analysis modules also can be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc). All modules are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, Windows). The program suite relies on a compiled Python extension module to perform paired-end alignments. Instructions for compiling the extension from source code are provided in the documentation. Users who do not have Python installed on their computers or who do not have the ability to compile software also may choose to download packaged executable files. These files include all Python scripts, a copy of the compiled extension module, and a minimal installation of Python in a single binary executable. See program documentation for more information.

  11. High Throughput Plasma Water Treatment

    Mujovic, Selman; Foster, John

    2016-10-01

    The troublesome emergence of new classes of micro-pollutants, such as pharmaceuticals and endocrine disruptors, poses challenges for conventional water treatment systems. In an effort to address these contaminants and to support water reuse in drought stricken regions, new technologies must be introduced. The interaction of water with plasma rapidly mineralizes organics by inducing advanced oxidation in addition to other chemical, physical and radiative processes. The primary barrier to the implementation of plasma-based water treatment is process volume scale up. In this work, we investigate a potentially scalable, high throughput plasma water reactor that utilizes a packed bed dielectric barrier-like geometry to maximize the plasma-water interface. Here, the water serves as the dielectric medium. High-speed imaging and emission spectroscopy are used to characterize the reactor discharges. Changes in methylene blue concentration and basic water parameters are mapped as a function of plasma treatment time. Experimental results are compared to electrostatic and plasma chemistry computations, which will provide insight into the reactor's operation so that efficiency can be assessed. Supported by NSF (CBET 1336375).

  12. High Throughput Transcriptomics @ USEPA (Toxicology ...

    The ideal chemical testing approach will provide complete coverage of all relevant toxicological responses. It should be sensitive and specific It should identify the mechanism/mode-of-action (with dose-dependence). It should identify responses relevant to the species of interest. Responses should ideally be translated into tissue-, organ-, and organism-level effects. It must be economical and scalable. Using a High Throughput Transcriptomics platform within US EPA provides broader coverage of biological activity space and toxicological MOAs and helps fill the toxicological data gap. Slide presentation at the 2016 ToxForum on using High Throughput Transcriptomics at US EPA for broader coverage biological activity space and toxicological MOAs.

  13. High-throughput continuous cryopump

    Foster, C.A.

    1986-01-01

    A cryopump with a unique method of regeneration which allows continuous operation at high throughput has been constructed and tested. Deuterium was pumped continuously at a throughput of 30 Torr.L/s at a speed of 2000 L/s and a compression ratio of 200. Argon was pumped at a throughput of 60 Torr.L/s at a speed of 1275 L/s. To produce continuous operation of the pump, a method of regeneration that does not thermally cycle the pump is employed. A small chamber (the ''snail'') passes over the pumping surface and removes the frost from it either by mechanical action with a scraper or by local heating. The material removed is topologically in a secondary vacuum system with low conductance into the primary vacuum; thus, the exhaust can be pumped at pressures up to an effective compression ratio determined by the ratio of the pumping speed to the leakage conductance of the snail. The pump, which is all-metal-sealed and dry and which regenerates every 60 s, would be an ideal system for pumping tritium. Potential fusion applications are for mpmp limiters, for repeating pneumatic pellet injection lines, and for the centrifuge pellet injector spin tank, all of which will require pumping tritium at high throughput. Industrial applications requiring ultraclean pumping of corrosive gases at high throughput, such as the reactive ion etch semiconductor process, may also be feasible

  14. High throughput protein production screening

    Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

    2009-09-08

    Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

  15. High throughput production of mouse monoclonal antibodies using antigen microarrays

    De Masi, Federico; Chiarella, P.; Wilhelm, H.

    2005-01-01

    Recent advances in proteomics research underscore the increasing need for high-affinity monoclonal antibodies, which are still generated with lengthy, low-throughput antibody production techniques. Here we present a semi-automated, high-throughput method of hybridoma generation and identification....... Monoclonal antibodies were raised to different targets in single batch runs of 6-10 wk using multiplexed immunisations, automated fusion and cell-culture, and a novel antigen-coated microarray-screening assay. In a large-scale experiment, where eight mice were immunized with ten antigens each, we generated...

  16. High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME

    Otis, Richard A.; Liu, Zi-Kui

    2017-05-01

    One foundational component of the integrated computational materials engineering (ICME) and Materials Genome Initiative is the computational thermodynamics based on the calculation of phase diagrams (CALPHAD) method. The CALPHAD method pioneered by Kaufman has enabled the development of thermodynamic, atomic mobility, and molar volume databases of individual phases in the full space of temperature, composition, and sometimes pressure for technologically important multicomponent engineering materials, along with sophisticated computational tools for using the databases. In this article, our recent efforts will be presented in terms of developing new computational tools for high-throughput modeling and uncertainty quantification based on high-throughput, first-principles calculations and the CALPHAD method along with their potential propagations to downstream ICME modeling and simulations.

  17. Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays (SOT)

    Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays DE DeGroot, RS Thomas, and SO SimmonsNational Center for Computational Toxicology, US EPA, Research Triangle Park, NC USAThe EPA’s ToxCast program utilizes a wide variety of high-throughput s...

  18. AOPs and Biomarkers: Bridging High Throughput Screening ...

    As high throughput screening (HTS) plays a larger role in toxicity testing, camputational toxicology has emerged as a critical component in interpreting the large volume of data produced. Computational models designed to quantify potential adverse effects based on HTS data will benefit from additional data sources that connect the magnitude of perturbation from the in vitro system to a level of concern at the organism or population level. The adverse outcome pathway (AOP) concept provides an ideal framework for combining these complementary data. Recent international efforts under the auspices of the Organization for Economic Co-operation and Development (OECD) have resulted in an AOP wiki designed to house formal descriptions of AOPs suitable for use in regulatory decision making. Recent efforts have built upon this to include an ontology describing the AOP with linkages to biological pathways, physiological terminology, and taxonomic applicability domains. Incorporation of an AOP network tool developed by the U.S. Army Corps of Engineers also allows consideration of cumulative risk from chemical and non-chemical stressors. Biomarkers are an important complement to formal AOP descriptions, particularly when dealing with susceptible subpopulations or lifestages in human health risk assessment. To address the issue of nonchemical stressors than may modify effects of criteria air pollutants, a novel method was used to integrate blood gene expression data with hema

  19. Uncertainty Quantification in High Throughput Screening ...

    Using uncertainty quantification, we aim to improve the quality of modeling data from high throughput screening assays for use in risk assessment. ToxCast is a large-scale screening program that analyzes thousands of chemicals using over 800 assays representing hundreds of biochemical and cellular processes, including endocrine disruption, cytotoxicity, and zebrafish development. Over 2.6 million concentration response curves are fit to models to extract parameters related to potency and efficacy. Models built on ToxCast results are being used to rank and prioritize the toxicological risk of tested chemicals and to predict the toxicity of tens of thousands of chemicals not yet tested in vivo. However, the data size also presents challenges. When fitting the data, the choice of models, model selection strategy, and hit call criteria must reflect the need for computational efficiency and robustness, requiring hard and somewhat arbitrary cutoffs. When coupled with unavoidable noise in the experimental concentration response data, these hard cutoffs cause uncertainty in model parameters and the hit call itself. The uncertainty will then propagate through all of the models built on the data. Left unquantified, this uncertainty makes it difficult to fully interpret the data for risk assessment. We used bootstrap resampling methods to quantify the uncertainty in fitting models to the concentration response data. Bootstrap resampling determines confidence intervals for

  20. High-throughput theoretical design of lithium battery materials

    Ling Shi-Gang; Gao Jian; Xiao Rui-Juan; Chen Li-Quan

    2016-01-01

    The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is reviewed, including high-capacity cathodes, low-strain cathodes, anodes, solid state electrolytes, and electrolyte additives. With the development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new materials. With the help of automatic simulation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve performance, and some representative criteria are: higher energy density, better safety, and faster charge/discharge speed. (topical review)

  1. High-throughput bioinformatics with the Cyrille2 pipeline system

    de Groot Joost CW

    2008-02-01

    Full Text Available Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1 a web based, graphical user interface (GUI that enables a pipeline operator to manage the system; 2 the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3 the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

  2. High throughput sample processing and automated scoring

    Gunnar eBrunborg

    2014-10-01

    Full Text Available The comet assay is a sensitive and versatile method for assessing DNA damage in cells. In the traditional version of the assay, there are many manual steps involved and few samples can be treated in one experiment. High throughput modifications have been developed during recent years, and they are reviewed and discussed. These modifications include accelerated scoring of comets; other important elements that have been studied and adapted to high throughput are cultivation and manipulation of cells or tissues before and after exposure, and freezing of treated samples until comet analysis and scoring. High throughput methods save time and money but they are useful also for other reasons: large-scale experiments may be performed which are otherwise not practicable (e.g., analysis of many organs from exposed animals, and human biomonitoring studies, and automation gives more uniform sample treatment and less dependence on operator performance. The high throughput modifications now available vary largely in their versatility, capacity, complexity and costs. The bottleneck for further increase of throughput appears to be the scoring.

  3. High Throughput Analysis of Photocatalytic Water Purification

    Sobral Romao, J.I.; Baiao Barata, David; Habibovic, Pamela; Mul, Guido; Baltrusaitis, Jonas

    2014-01-01

    We present a novel high throughput photocatalyst efficiency assessment method based on 96-well microplates and UV-Vis spectroscopy. We demonstrate the reproducibility of the method using methyl orange (MO) decomposition, and compare kinetic data obtained with those provided in the literature for

  4. High-throughput scoring of seed germination

    Ligterink, Wilco; Hilhorst, Henk W.M.

    2017-01-01

    High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very

  5. High-throughput sequence alignment using Graphics Processing Units

    Trapnell Cole

    2007-12-01

    Full Text Available Abstract Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

  6. High Throughput WAN Data Transfer with Hadoop-based Storage

    Amin, A.; Bockelman, B.; Letts, J.; Levshina, T.; Martin, T.; Pi, H.; Sfiligoi, I.; Thomas, M.; Wüerthwein, F.

    2011-12-01

    Hadoop distributed file system (HDFS) is becoming more popular in recent years as a key building block of integrated grid storage solution in the field of scientific computing. Wide Area Network (WAN) data transfer is one of the important data operations for large high energy physics experiments to manage, share and process datasets of PetaBytes scale in a highly distributed grid computing environment. In this paper, we present the experience of high throughput WAN data transfer with HDFS-based Storage Element. Two protocols, GridFTP and fast data transfer (FDT), are used to characterize the network performance of WAN data transfer.

  7. High Throughput WAN Data Transfer with Hadoop-based Storage

    Amin, A; Thomas, M; Bockelman, B; Letts, J; Martin, T; Pi, H; Sfiligoi, I; Wüerthwein, F; Levshina, T

    2011-01-01

    Hadoop distributed file system (HDFS) is becoming more popular in recent years as a key building block of integrated grid storage solution in the field of scientific computing. Wide Area Network (WAN) data transfer is one of the important data operations for large high energy physics experiments to manage, share and process datasets of PetaBytes scale in a highly distributed grid computing environment. In this paper, we present the experience of high throughput WAN data transfer with HDFS-based Storage Element. Two protocols, GridFTP and fast data transfer (FDT), are used to characterize the network performance of WAN data transfer.

  8. High Throughput Neuro-Imaging Informatics

    Michael I Miller

    2013-12-01

    Full Text Available This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high dimensional neuroinformatic representations index containing O(E3-E4 discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high throughput machine learning methods for supporting (i cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii integration of image and non-image information for diagnosis and prognosis.

  9. Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.

    Halligan, Brian D; Geiger, Joey F; Vallejos, Andrew K; Greene, Andrew S; Twigger, Simon N

    2009-06-01

    One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

  10. A high-throughput, multi-channel photon-counting detector with picosecond timing

    Lapington, J S; Miller, G M; Ashton, T J R; Jarron, P; Despeisse, M; Powolny, F; Howorth, J; Milnes, J

    2009-01-01

    High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchanne...

  11. Application of high-throughput DNA sequencing in phytopathology.

    Studholme, David J; Glover, Rachel H; Boonham, Neil

    2011-01-01

    The new sequencing technologies are already making a big impact in academic research on medically important microbes and may soon revolutionize diagnostics, epidemiology, and infection control. Plant pathology also stands to gain from exploiting these opportunities. This manuscript reviews some applications of these high-throughput sequencing methods that are relevant to phytopathology, with emphasis on the associated computational and bioinformatics challenges and their solutions. Second-generation sequencing technologies have recently been exploited in genomics of both prokaryotic and eukaryotic plant pathogens. They are also proving to be useful in diagnostics, especially with respect to viruses. Copyright © 2011 by Annual Reviews. All rights reserved.

  12. REDItools: high-throughput RNA editing detection made easy.

    Picardi, Ernesto; Pesole, Graziano

    2013-07-15

    The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data. REDItools are in python programming language and freely available at http://code.google.com/p/reditools/. ernesto.picardi@uniba.it or graziano.pesole@uniba.it Supplementary data are available at Bioinformatics online.

  13. High throughput screening method for assessing heterogeneity of microorganisms

    Ingham, C.J.; Sprenkels, A.J.; van Hylckama Vlieg, J.E.T.; Bomer, Johan G.; de Vos, W.M.; van den Berg, Albert

    2006-01-01

    The invention relates to the field of microbiology. Provided is a method which is particularly powerful for High Throughput Screening (HTS) purposes. More specific a high throughput method for determining heterogeneity or interactions of microorganisms is provided.

  14. Application of ToxCast High-Throughput Screening and ...

    Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenesis Distruptors Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenssis Distruptors

  15. High Throughput PBTK: Open-Source Data and Tools for ...

    Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy

  16. High-Throughput Scoring of Seed Germination.

    Ligterink, Wilco; Hilhorst, Henk W M

    2017-01-01

    High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very informative as it lacks information about start, rate, and uniformity of germination, which are highly indicative of such traits as dormancy, stress tolerance, and seed longevity. The calculation of cumulative germination curves requires information about germination percentage at various time points. We developed the GERMINATOR package: a simple, highly cost-efficient, and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The GERMINATOR package contains three modules: (I) design of experimental setup with various options to replicate and randomize samples; (II) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (III) curve fitting of cumulative germination data and the extraction, recap, and visualization of the various germination parameters. GERMINATOR is a freely available package that allows the monitoring and analysis of several thousands of germination tests, several times a day by a single person.

  17. High throughput nonparametric probability density estimation.

    Farmer, Jenny; Jacobs, Donald

    2018-01-01

    In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

  18. Modeling Steroidogenesis Disruption Using High-Throughput ...

    Environmental chemicals can elicit endocrine disruption by altering steroid hormone biosynthesis and metabolism (steroidogenesis) causing adverse reproductive and developmental effects. Historically, a lack of assays resulted in few chemicals having been evaluated for effects on steroidogenesis. The steroidogenic pathway is a series of hydroxylation and dehydrogenation steps carried out by CYP450 and hydroxysteroid dehydrogenase enzymes, yet the only enzyme in the pathway for which a high-throughput screening (HTS) assay has been developed is aromatase (CYP19A1), responsible for the aromatization of androgens to estrogens. Recently, the ToxCast HTS program adapted the OECD validated H295R steroidogenesis assay using human adrenocortical carcinoma cells into a high-throughput model to quantitatively assess the concentration-dependent (0.003-100 µM) effects of chemicals on 10 steroid hormones including progestagens, androgens, estrogens and glucocorticoids. These results, in combination with two CYP19A1 inhibition assays, comprise a large dataset amenable to clustering approaches supporting the identification and characterization of putative mechanisms of action (pMOA) for steroidogenesis disruption. In total, 514 chemicals were tested in all CYP19A1 and steroidogenesis assays. 216 chemicals were identified as CYP19A1 inhibitors in at least one CYP19A1 assay. 208 of these chemicals also altered hormone levels in the H295R assay, suggesting 96% sensitivity in the

  19. Preliminary High-Throughput Metagenome Assembly

    Dusheyko, Serge; Furman, Craig; Pangilinan, Jasmyn; Shapiro, Harris; Tu, Hank

    2007-03-26

    Metagenome data sets present a qualitatively different assembly problem than traditional single-organism whole-genome shotgun (WGS) assembly. The unique aspects of such projects include the presence of a potentially large number of distinct organisms and their representation in the data set at widely different fractions. In addition, multiple closely related strains could be present, which would be difficult to assemble separately. Failure to take these issues into account can result in poor assemblies that either jumble together different strains or which fail to yield useful results. The DOE Joint Genome Institute has sequenced a number of metagenomic projects and plans to considerably increase this number in the coming year. As a result, the JGI has a need for high-throughput tools and techniques for handling metagenome projects. We present the techniques developed to handle metagenome assemblies in a high-throughput environment. This includes a streamlined assembly wrapper, based on the JGI?s in-house WGS assembler, Jazz. It also includes the selection of sensible defaults targeted for metagenome data sets, as well as quality control automation for cleaning up the raw results. While analysis is ongoing, we will discuss preliminary assessments of the quality of the assembly results (http://fames.jgi-psf.org).

  20. Controlling high-throughput manufacturing at the nano-scale

    Cooper, Khershed P.

    2013-09-01

    Interest in nano-scale manufacturing research and development is growing. The reason is to accelerate the translation of discoveries and inventions of nanoscience and nanotechnology into products that would benefit industry, economy and society. Ongoing research in nanomanufacturing is focused primarily on developing novel nanofabrication techniques for a variety of applications—materials, energy, electronics, photonics, biomedical, etc. Our goal is to foster the development of high-throughput methods of fabricating nano-enabled products. Large-area parallel processing and highspeed continuous processing are high-throughput means for mass production. An example of large-area processing is step-and-repeat nanoimprinting, by which nanostructures are reproduced again and again over a large area, such as a 12 in wafer. Roll-to-roll processing is an example of continuous processing, by which it is possible to print and imprint multi-level nanostructures and nanodevices on a moving flexible substrate. The big pay-off is high-volume production and low unit cost. However, the anticipated cost benefits can only be realized if the increased production rate is accompanied by high yields of high quality products. To ensure product quality, we need to design and construct manufacturing systems such that the processes can be closely monitored and controlled. One approach is to bring cyber-physical systems (CPS) concepts to nanomanufacturing. CPS involves the control of a physical system such as manufacturing through modeling, computation, communication and control. Such a closely coupled system will involve in-situ metrology and closed-loop control of the physical processes guided by physics-based models and driven by appropriate instrumentation, sensing and actuation. This paper will discuss these ideas in the context of controlling high-throughput manufacturing at the nano-scale.

  1. High-Throughput Analysis of Enzyme Activities

    Lu, Guoxin [Iowa State Univ., Ames, IA (United States)

    2007-01-01

    High-throughput screening (HTS) techniques have been applied to many research fields nowadays. Robot microarray printing technique and automation microtiter handling technique allows HTS performing in both heterogeneous and homogeneous formats, with minimal sample required for each assay element. In this dissertation, new HTS techniques for enzyme activity analysis were developed. First, patterns of immobilized enzyme on nylon screen were detected by multiplexed capillary system. The imaging resolution is limited by the outer diameter of the capillaries. In order to get finer images, capillaries with smaller outer diameters can be used to form the imaging probe. Application of capillary electrophoresis allows separation of the product from the substrate in the reaction mixture, so that the product doesn't have to have different optical properties with the substrate. UV absorption detection allows almost universal detection for organic molecules. Thus, no modifications of either the substrate or the product molecules are necessary. This technique has the potential to be used in screening of local distribution variations of specific bio-molecules in a tissue or in screening of multiple immobilized catalysts. Another high-throughput screening technique is developed by directly monitoring the light intensity of the immobilized-catalyst surface using a scientific charge-coupled device (CCD). Briefly, the surface of enzyme microarray is focused onto a scientific CCD using an objective lens. By carefully choosing the detection wavelength, generation of product on an enzyme spot can be seen by the CCD. Analyzing the light intensity change over time on an enzyme spot can give information of reaction rate. The same microarray can be used for many times. Thus, high-throughput kinetic studies of hundreds of catalytic reactions are made possible. At last, we studied the fluorescence emission spectra of ADP and obtained the detection limits for ADP under three different

  2. High-Throughput Process Development for Biopharmaceuticals.

    Shukla, Abhinav A; Rameez, Shahid; Wolfe, Leslie S; Oien, Nathan

    2017-11-14

    The ability to conduct multiple experiments in parallel significantly reduces the time that it takes to develop a manufacturing process for a biopharmaceutical. This is particularly significant before clinical entry, because process development and manufacturing are on the "critical path" for a drug candidate to enter clinical development. High-throughput process development (HTPD) methodologies can be similarly impactful during late-stage development, both for developing the final commercial process as well as for process characterization and scale-down validation activities that form a key component of the licensure filing package. This review examines the current state of the art for HTPD methodologies as they apply to cell culture, downstream purification, and analytical techniques. In addition, we provide a vision of how HTPD activities across all of these spaces can integrate to create a rapid process development engine that can accelerate biopharmaceutical drug development. Graphical Abstract.

  3. High-throughput GPU-based LDPC decoding

    Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

    2010-08-01

    Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

  4. A Fully Automated High-Throughput Zebrafish Behavioral Ototoxicity Assay.

    Todd, Douglas W; Philip, Rohit C; Niihori, Maki; Ringle, Ryan A; Coyle, Kelsey R; Zehri, Sobia F; Zabala, Leanne; Mudery, Jordan A; Francis, Ross H; Rodriguez, Jeffrey J; Jacob, Abraham

    2017-08-01

    Zebrafish animal models lend themselves to behavioral assays that can facilitate rapid screening of ototoxic, otoprotective, and otoregenerative drugs. Structurally similar to human inner ear hair cells, the mechanosensory hair cells on their lateral line allow the zebrafish to sense water flow and orient head-to-current in a behavior called rheotaxis. This rheotaxis behavior deteriorates in a dose-dependent manner with increased exposure to the ototoxin cisplatin, thereby establishing itself as an excellent biomarker for anatomic damage to lateral line hair cells. Building on work by our group and others, we have built a new, fully automated high-throughput behavioral assay system that uses automated image analysis techniques to quantify rheotaxis behavior. This novel system consists of a custom-designed swimming apparatus and imaging system consisting of network-controlled Raspberry Pi microcomputers capturing infrared video. Automated analysis techniques detect individual zebrafish, compute their orientation, and quantify the rheotaxis behavior of a zebrafish test population, producing a powerful, high-throughput behavioral assay. Using our fully automated biological assay to test a standardized ototoxic dose of cisplatin against varying doses of compounds that protect or regenerate hair cells may facilitate rapid translation of candidate drugs into preclinical mammalian models of hearing loss.

  5. CrossCheck: an open-source web tool for high-throughput screen data analysis.

    Najafov, Jamil; Najafov, Ayaz

    2017-07-19

    Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

  6. Cardiovascular proteomics in the era of big data: experimental and computational advances.

    Lam, Maggie P Y; Lau, Edward; Ng, Dominic C M; Wang, Ding; Ping, Peipei

    2016-01-01

    Proteomics plays an increasingly important role in our quest to understand cardiovascular biology. Fueled by analytical and computational advances in the past decade, proteomics applications can now go beyond merely inventorying protein species, and address sophisticated questions on cardiac physiology. The advent of massive mass spectrometry datasets has in turn led to increasing intersection between proteomics and big data science. Here we review new frontiers in technological developments and their applications to cardiovascular medicine. The impact of big data science on cardiovascular proteomics investigations and translation to medicine is highlighted.

  7. Systems biology of bacterial nitrogen fixation: High-throughput technology and its integrative description with constraint-based modeling

    Resendis-Antonio Osbaldo

    2011-07-01

    Full Text Available Abstract Background Bacterial nitrogen fixation is the biological process by which atmospheric nitrogen is uptaken by bacteroids located in plant root nodules and converted into ammonium through the enzymatic activity of nitrogenase. In practice, this biological process serves as a natural form of fertilization and its optimization has significant implications in sustainable agricultural programs. Currently, the advent of high-throughput technology supplies with valuable data that contribute to understanding the metabolic activity during bacterial nitrogen fixation. This undertaking is not trivial, and the development of computational methods useful in accomplishing an integrative, descriptive and predictive framework is a crucial issue to decoding the principles that regulated the metabolic activity of this biological process. Results In this work we present a systems biology description of the metabolic activity in bacterial nitrogen fixation. This was accomplished by an integrative analysis involving high-throughput data and constraint-based modeling to characterize the metabolic activity in Rhizobium etli bacteroids located at the root nodules of Phaseolus vulgaris (bean plant. Proteome and transcriptome technologies led us to identify 415 proteins and 689 up-regulated genes that orchestrate this biological process. Taking into account these data, we: 1 extended the metabolic reconstruction reported for R. etli; 2 simulated the metabolic activity during symbiotic nitrogen fixation; and 3 evaluated the in silico results in terms of bacteria phenotype. Notably, constraint-based modeling simulated nitrogen fixation activity in such a way that 76.83% of the enzymes and 69.48% of the genes were experimentally justified. Finally, to further assess the predictive scope of the computational model, gene deletion analysis was carried out on nine metabolic enzymes. Our model concluded that an altered metabolic activity on these enzymes induced

  8. High-throughput determination of RNA structure by proximity ligation.

    Ramani, Vijay; Qiu, Ruolan; Shendure, Jay

    2015-09-01

    We present an unbiased method to globally resolve RNA structures through pairwise contact measurements between interacting regions. RNA proximity ligation (RPL) uses proximity ligation of native RNA followed by deep sequencing to yield chimeric reads with ligation junctions in the vicinity of structurally proximate bases. We apply RPL in both baker's yeast (Saccharomyces cerevisiae) and human cells and generate contact probability maps for ribosomal and other abundant RNAs, including yeast snoRNAs, the RNA subunit of the signal recognition particle and the yeast U2 spliceosomal RNA homolog. RPL measurements correlate with established secondary structures for these RNA molecules, including stem-loop structures and long-range pseudoknots. We anticipate that RPL will complement the current repertoire of computational and experimental approaches in enabling the high-throughput determination of secondary and tertiary RNA structures.

  9. Ultraspecific probes for high throughput HLA typing

    Eggers Rick

    2009-02-01

    Full Text Available Abstract Background The variations within an individual's HLA (Human Leukocyte Antigen genes have been linked to many immunological events, e.g. susceptibility to disease, response to vaccines, and the success of blood, tissue, and organ transplants. Although the microarray format has the potential to achieve high-resolution typing, this has yet to be attained due to inefficiencies of current probe design strategies. Results We present a novel three-step approach for the design of high-throughput microarray assays for HLA typing. This approach first selects sequences containing the SNPs present in all alleles of the locus of interest and next calculates the number of base changes necessary to convert a candidate probe sequences to the closest subsequence within the set of sequences that are likely to be present in the sample including the remainder of the human genome in order to identify those candidate probes which are "ultraspecific" for the allele of interest. Due to the high specificity of these sequences, it is possible that preliminary steps such as PCR amplification are no longer necessary. Lastly, the minimum number of these ultraspecific probes is selected such that the highest resolution typing can be achieved for the minimal cost of production. As an example, an array was designed and in silico results were obtained for typing of the HLA-B locus. Conclusion The assay presented here provides a higher resolution than has previously been developed and includes more alleles than previously considered. Based upon the in silico and preliminary experimental results, we believe that the proposed approach can be readily applied to any highly polymorphic gene system.

  10. 20180311 - High Throughput Transcriptomics: From screening to pathways (SOT 2018)

    The EPA ToxCast effort has screened thousands of chemicals across hundreds of high-throughput in vitro screening assays. The project is now leveraging high-throughput transcriptomic (HTTr) technologies to substantially expand its coverage of biological pathways. The first HTTr sc...

  11. High-throughput screening (HTS) and modeling of the retinoid ...

    Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system

  12. High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

    High throughput toxicokinetics (HTTK) is an approach that allows for rapid estimations of TK for hundreds of environmental chemicals. HTTK-based reverse dosimetry (i.e, reverse toxicokinetics or RTK) is used in order to convert high throughput in vitro toxicity screening (HTS) da...

  13. Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

    High-throughput screening (HTS) generates in vitro data for characterizing potential chemical hazard. TK models are needed to allow in vitro to in vivo extrapolation (IVIVE) to real world situations. The U.S. EPA has created a public tool (R package “httk” for high throughput tox...

  14. High-throughput characterization methods for lithium batteries

    Yingchun Lyu

    2017-09-01

    Full Text Available The development of high-performance lithium ion batteries requires the discovery of new materials and the optimization of key components. By contrast with traditional one-by-one method, high-throughput method can synthesize and characterize a large number of compositionally varying samples, which is able to accelerate the pace of discovery, development and optimization process of materials. Because of rapid progress in thin film and automatic control technologies, thousands of compounds with different compositions could be synthesized rapidly right now, even in a single experiment. However, the lack of rapid or combinatorial characterization technologies to match with high-throughput synthesis methods, limit the application of high-throughput technology. Here, we review a series of representative high-throughput characterization methods used in lithium batteries, including high-throughput structural and electrochemical characterization methods and rapid measuring technologies based on synchrotron light sources.

  15. A high-throughput surface plasmon resonance biosensor based on differential interferometric imaging

    Wang, Daqian; Ding, Lili; Zhang, Wei; Zhang, Enyao; Yu, Xinglong; Luo, Zhaofeng; Ou, Huichao

    2012-01-01

    A new high-throughput surface plasmon resonance (SPR) biosensor based on differential interferometric imaging is reported. The two SPR interferograms of the sensing surface are imaged on two CCD cameras. The phase difference between the two interferograms is 180°. The refractive index related factor (RIRF) of the sensing surface is calculated from the two simultaneously acquired interferograms. The simulation results indicate that the RIRF exhibits a linear relationship with the refractive index of the sensing surface and is unaffected by the noise, drift and intensity distribution of the light source. The affinity and kinetic information can be extracted in real time from continuously acquired RIRF distributions. The results of refractometry experiments show that the dynamic detection range of SPR differential interferometric imaging system can be over 0.015 refractive index unit (RIU). High refractive index resolution is down to 0.45 RU (1 RU = 1 × 10 −6 RIU). Imaging and protein microarray experiments demonstrate the ability of high-throughput detection. The aptamer experiments demonstrate that the SPR sensor based on differential interferometric imaging has a great capability to be implemented for high-throughput aptamer kinetic evaluation. These results suggest that this biosensor has the potential to be utilized in proteomics and drug discovery after further improvement. (paper)

  16. Applications of ambient mass spectrometry in high-throughput screening.

    Li, Li-Ping; Feng, Bao-Sheng; Yang, Jian-Wang; Chang, Cui-Lan; Bai, Yu; Liu, Hu-Wei

    2013-06-07

    The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

  17. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer?s-Associated A? Oligomers

    Wilcox, Kyle C.; Marunde, Matthew R.; Das, Aditi; Velasco, Pauline T.; Kuhns, Benjamin D.; Marty, Michael T.; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G.; Klein, William L.

    2015-01-01

    Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein int...

  18. [New-generation high-throughput technologies based 'omics' research strategy in human disease].

    Yang, Xu; Jiao, Rui; Yang, Lin; Wu, Li-Ping; Li, Ying-Rui; Wang, Jun

    2011-08-01

    In recent years, new-generation high-throughput technologies, including next-generation sequencing technology and mass spectrometry method, have been widely applied in solving biological problems, especially in human diseases field. This data driven, large-scale and industrialized research model enables the omnidirectional and multi-level study of human diseases from the perspectives of genomics, transcriptomics and proteomics levels, etc. In this paper, the latest development of the high-throughput technologies that applied in DNA, RNA, epigenomics, metagenomics including proteomics and some applications in translational medicine are reviewed. At genomics level, exome sequencing has been the hot spot of the recent research. However, the predominance of whole genome resequencing in detecting large structural variants within the whole genome level is coming to stand out as the drop of sequencing cost, which also makes it possible for personalized genome based medicine application. At trancriptomics level, e.g., small RNA sequencing can be used to detect known and predict unknown miRNA. Those small RNA could not only be the biomarkers for disease diagnosis and prognosis, but also show the potential of disease treatment. At proteomics level, e.g., target proteomics can be used to detect the possible disease-related protein or peptides, which can be useful index for clinical staging and typing. Furthermore, the application and development of trans-omics study in disease research are briefly introduced. By applying bioinformatics technologies for integrating multi-omics data, the mechanism, diagnosis and therapy of the disease are likely to be systemically explained and realized, so as to provide powerful tools for disease diagnosis and therapies.

  19. A high-throughput, multi-channel photon-counting detector with picosecond timing

    Lapington, J. S.; Fraser, G. W.; Miller, G. M.; Ashton, T. J. R.; Jarron, P.; Despeisse, M.; Powolny, F.; Howorth, J.; Milnes, J.

    2009-06-01

    High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchannel plate devices with very high time resolution, and high-speed multi-channel ASIC electronics developed for the LHC at CERN, provides the necessary building blocks for a high-throughput detector system with up to 1024 parallel counting channels and 20 ps time resolution. We describe the detector and electronic design, discuss the current status of the HiContent project and present the results from a 64-channel prototype system. In the absence of an operational detector, we present measurements of the electronics performance using a pulse generator to simulate detector events. Event timing results from the NINO high-speed front-end ASIC captured using a fast digital oscilloscope are compared with data taken with the proposed electronic configuration which uses the multi-channel HPTDC timing ASIC.

  20. A high-throughput, multi-channel photon-counting detector with picosecond timing

    Lapington, J.S.; Fraser, G.W.; Miller, G.M.; Ashton, T.J.R.; Jarron, P.; Despeisse, M.; Powolny, F.; Howorth, J.; Milnes, J.

    2009-01-01

    High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchannel plate devices with very high time resolution, and high-speed multi-channel ASIC electronics developed for the LHC at CERN, provides the necessary building blocks for a high-throughput detector system with up to 1024 parallel counting channels and 20 ps time resolution. We describe the detector and electronic design, discuss the current status of the HiContent project and present the results from a 64-channel prototype system. In the absence of an operational detector, we present measurements of the electronics performance using a pulse generator to simulate detector events. Event timing results from the NINO high-speed front-end ASIC captured using a fast digital oscilloscope are compared with data taken with the proposed electronic configuration which uses the multi-channel HPTDC timing ASIC.

  1. High throughput screening of starch structures using carbohydrate microarrays

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg

    2016-01-01

    In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated...

  2. High-Throughput Analysis and Automation for Glycomics Studies

    Shubhakar, A.; Reiding, K.R.; Gardner, R.A.; Spencer, D.I.R.; Fernandes, D.L.; Wuhrer, M.

    2015-01-01

    This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing

  3. MIPHENO: Data normalization for high throughput metabolic analysis.

    High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...

  4. compomics-utilities: an open-source Java library for computational proteomics.

    Barsnes, Harald; Vaudel, Marc; Colaert, Niklaas; Helsens, Kenny; Sickmann, Albert; Berven, Frode S; Martens, Lennart

    2011-03-08

    The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. In order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. As a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.

  5. compomics-utilities: an open-source Java library for computational proteomics

    Helsens Kenny

    2011-03-01

    Full Text Available Abstract Background The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. Results In order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. Conclusions As a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.

  6. Assessing the utility and limitations of high throughput virtual screening

    Paul Daniel Phillips

    2016-05-01

    Full Text Available Due to low cost, speed, and unmatched ability to explore large numbers of compounds, high throughput virtual screening and molecular docking engines have become widely utilized by computational scientists. It is generally accepted that docking engines, such as AutoDock, produce reliable qualitative results for ligand-macromolecular receptor binding, and molecular docking results are commonly reported in literature in the absence of complementary wet lab experimental data. In this investigation, three variants of the sixteen amino acid peptide, α-conotoxin MII, were docked to a homology model of the a3β2-nicotinic acetylcholine receptor. DockoMatic version 2.0 was used to perform a virtual screen of each peptide ligand to the receptor for ten docking trials consisting of 100 AutoDock cycles per trial. The results were analyzed for both variation in the calculated binding energy obtained from AutoDock, and the orientation of bound peptide within the receptor. The results show that, while no clear correlation exists between consistent ligand binding pose and the calculated binding energy, AutoDock is able to determine a consistent positioning of bound peptide in the majority of trials when at least ten trials were evaluated.

  7. High-throughput literature mining to support read-across ...

    Building scientific confidence in the development and evaluation of read-across remains an ongoing challenge. Approaches include establishing systematic frameworks to identify sources of uncertainty and ways to address them. One source of uncertainty is related to characterizing biological similarity. Many research efforts are underway such as structuring mechanistic data in adverse outcome pathways and investigating the utility of high throughput (HT)/high content (HC) screening data. A largely untapped resource for read-across to date is the biomedical literature. This information has the potential to support read-across by facilitating the identification of valid source analogues with similar biological and toxicological profiles as well as providing the mechanistic understanding for any prediction made. A key challenge in using biomedical literature is to convert and translate its unstructured form into a computable format that can be linked to chemical structure. We developed a novel text-mining strategy to represent literature information for read across. Keywords were used to organize literature into toxicity signatures at the chemical level. These signatures were integrated with HT in vitro data and curated chemical structures. A rule-based algorithm assessed the strength of the literature relationship, providing a mechanism to rank and visualize the signature as literature ToxPIs (LitToxPIs). LitToxPIs were developed for over 6,000 chemicals for a varie

  8. Computational Omics Funding Opportunity | Office of Cancer Clinical Proteomics Research

    The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the NVIDIA Foundation are pleased to announce funding opportunities in the fight against cancer. Each organization has launched a request for proposals (RFP) that will collectively fund up to $2 million to help to develop a new generation of data-intensive scientific tools to find new ways to treat cancer.

  9. Applications of High Throughput Nucleotide Sequencing

    Waage, Johannes Eichler

    equally large demands in data handling, analysis and interpretation, perhaps defining the modern challenge of the computational biologist of the post-genomic era. The first part of this thesis consists of a general introduction to the history, common terms and challenges of next generation sequencing......-sequencing, a study of the effects on alternative RNA splicing of KO of the nonsense mediated RNA decay system in Mus, using digital gene expression and a custom-built exon-exon junction mapping pipeline is presented (article I). Evolved from this work, a Bioconductor package, spliceR, for classifying alternative...

  10. Computational Omics Pre-Awardees | Office of Cancer Clinical Proteomics Research

    The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) is pleased to announce the pre-awardees of the Computational Omics solicitation. Working with NVIDIA Foundation's Compute the Cure initiative and Leidos Biomedical Research Inc., the NCI, through this solicitation, seeks to leverage computational efforts to provide tools for the mining and interpretation of large-scale publicly available ‘omics’ datasets.

  11. Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

    2016-05-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  12. Image Harvest: an open-source platform for high-throughput plant image processing and analysis

    Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

    2016-01-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

  13. The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

    Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister

    2014-05-01

    The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

  14. High-throughput screening to identify inhibitors of lysine demethylases.

    Gale, Molly; Yan, Qin

    2015-01-01

    Lysine demethylases (KDMs) are epigenetic regulators whose dysfunction is implicated in the pathology of many human diseases including various types of cancer, inflammation and X-linked intellectual disability. Particular demethylases have been identified as promising therapeutic targets, and tremendous efforts are being devoted toward developing suitable small-molecule inhibitors for clinical and research use. Several High-throughput screening strategies have been developed to screen for small-molecule inhibitors of KDMs, each with advantages and disadvantages in terms of time, cost, effort, reliability and sensitivity. In this Special Report, we review and evaluate the High-throughput screening methods utilized for discovery of novel small-molecule KDM inhibitors.

  15. High throughput materials research and development for lithium ion batteries

    Parker Liu

    2017-09-01

    Full Text Available Development of next generation batteries requires a breakthrough in materials. Traditional one-by-one method, which is suitable for synthesizing large number of sing-composition material, is time-consuming and costly. High throughput and combinatorial experimentation, is an effective method to synthesize and characterize huge amount of materials over a broader compositional region in a short time, which enables to greatly speed up the discovery and optimization of materials with lower cost. In this work, high throughput and combinatorial materials synthesis technologies for lithium ion battery research are discussed, and our efforts on developing such instrumentations are introduced.

  16. Towards a high throughput droplet-based agglutination assay

    Kodzius, Rimantas; Castro, David; Foulds, Ian G.

    2013-01-01

    This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

  17. Towards a high throughput droplet-based agglutination assay

    Kodzius, Rimantas

    2013-10-22

    This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

  18. Leaderboard Now Open: CPTAC’s DREAM Proteogenomics Computational Challenge | Office of Cancer Clinical Proteomics Research

    The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) is pleased to announce the opening of the leaderboard to its Proteogenomics Computational DREAM Challenge. The leadership board remains open for submissions during September 25, 2017 through October 8, 2017, with the Challenge expected to run until November 17, 2017.

  19. Mining Chemical Activity Status from High-Throughput Screening Assays

    Soufan, Othman

    2015-12-14

    High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we performed a comprehensive comparison analysis with several other methods and evaluated them on data from 11 PubChem assays through 1,350 experiments that involved approximately 500,000 interactions between chemicals and their target proteins. As an example of potential use, we applied DRAMOTE to develop robust models for predicting FDA approved drugs that have high probability to interact with the thyroid stimulating hormone receptor (TSHR) in humans. Our findings are further partially and indirectly supported by 3D docking results and literature information. The results based on approximately 500,000 interactions suggest that DRAMOTE has performed the best and that it can be used for developing robust virtual screening models. The datasets and implementation of all solutions are available as a MATLAB toolbox online at www.cbrc.kaust.edu.sa/dramote and can be found on Figshare.

  20. Using In Vitro High-Throughput Screening Data for Predicting ...

    Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values and risk screening values. We aim to use computational toxicology and quantitative high throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. By coupling qHTS data with adverse outcome pathways (AOPs) we can use ontologies to make predictions about potential hazards and to identify those assays which are sufficient to infer these same hazards. Once those assays are identified, we can use bootstrap natural spline-based metaregression to integrate the evidence across multiple replicates or assays (if a combination of assays are together necessary to be sufficient). In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene (B[k]F) may induce DNA damage and steatosis using qHTS data and two separate AOPs. We also demonstrate how bootstrap natural spline-based metaregression can be used to integrate the data across multiple assay replicates to generate a concentration-response curve. We used this analysis to calculate an internal point of departure of 0.751µM and risk-specific concentrations of 0.378µM for both 1:1,000 and 1:10,000 additive risk for B[k]F induced DNA damage based on the p53 assay. Based on the available evidence, we

  1. Mining Chemical Activity Status from High-Throughput Screening Assays

    Soufan, Othman; Ba Alawi, Wail; Afeef, Moataz A.; Essack, Magbubah; Rodionov, Valentin; Kalnis, Panos; Bajic, Vladimir B.

    2015-01-01

    High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we performed a comprehensive comparison analysis with several other methods and evaluated them on data from 11 PubChem assays through 1,350 experiments that involved approximately 500,000 interactions between chemicals and their target proteins. As an example of potential use, we applied DRAMOTE to develop robust models for predicting FDA approved drugs that have high probability to interact with the thyroid stimulating hormone receptor (TSHR) in humans. Our findings are further partially and indirectly supported by 3D docking results and literature information. The results based on approximately 500,000 interactions suggest that DRAMOTE has performed the best and that it can be used for developing robust virtual screening models. The datasets and implementation of all solutions are available as a MATLAB toolbox online at www.cbrc.kaust.edu.sa/dramote and can be found on Figshare.

  2. Scanning fluorescence detector for high-throughput DNA genotyping

    Rusch, Terry L.; Petsinger, Jeremy; Christensen, Carl; Vaske, David A.; Brumley, Robert L., Jr.; Luckey, John A.; Weber, James L.

    1996-04-01

    A new scanning fluorescence detector (SCAFUD) was developed for high-throughput genotyping of short tandem repeat polymorphisms (STRPs). Fluorescent dyes are incorporated into relatively short DNA fragments via polymerase chain reaction (PCR) and are separated by electrophoresis in short, wide polyacrylamide gels (144 lanes with well to read distances of 14 cm). Excitation light from an argon laser with primary lines at 488 and 514 nm is introduced into the gel through a fiber optic cable, dichroic mirror, and 40X microscope objective. Emitted fluorescent light is collected confocally through a second fiber. The confocal head is translated across the bottom of the gel at 0.5 Hz. The detection unit utilizes dichroic mirrors and band pass filters to direct light with 10 - 20 nm bandwidths to four photomultiplier tubes (PMTs). PMT signals are independently amplified with variable gain and then sampled at a rate of 2500 points per scan using a computer based A/D board. LabView software (National Instruments) is used for instrument operation. Currently, three fluorescent dyes (Fam, Hex and Rox) are simultaneously detected with peak detection wavelengths of 543, 567, and 613 nm, respectively. The detection limit for fluorescein-labeled primers is about 100 attomoles. Planned SCAFUD upgrades include rearrangement of laser head geometry, use of additional excitation lasers for simultaneous detection of more dyes, and the use of detector arrays instead of individual PMTs. Extensive software has been written for automatic analysis of SCAFUD images. The software enables background subtraction, band identification, multiple- dye signal resolution, lane finding, band sizing and allele calling. Whole genome screens are currently underway to search for loci influencing such complex diseases as diabetes, asthma, and hypertension. Seven production SCAFUDs are currently in operation. Genotyping output for the coming year is projected to be about one million total genotypes (DNA

  3. Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

    Tanel Pärnamaa

    2017-05-01

    Full Text Available High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.

  4. Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.

    Pärnamaa, Tanel; Parts, Leopold

    2017-05-05

    High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy. Copyright © 2017 Parnamaa and Parts.

  5. A modified FASP protocol for high-throughput preparation of protein samples for mass spectrometry.

    Jeremy Potriquet

    Full Text Available To facilitate high-throughput proteomic analyses we have developed a modified FASP protocol which improves the rate at which protein samples can be processed prior to mass spectrometry. Adapting the original FASP protocol to a 96-well format necessitates extended spin times for buffer exchange due to the low centrifugation speeds tolerated by these devices. However, by using 96-well plates with a more robust polyethersulfone molecular weight cutoff membrane, instead of the cellulose membranes typically used in these devices, we could use isopropanol as a wetting agent, decreasing spin times required for buffer exchange from an hour to 30 minutes. In a typical work flow used in our laboratory this equates to a reduction of 3 hours per plate, providing processing times similar to FASP for the processing of up to 96 samples per plate. To test whether our modified protocol produced similar results to FASP and other FASP-like protocols we compared the performance of our modified protocol to the original FASP and the more recently described eFASP and MStern-blot. We show that all FASP-like methods, including our modified protocol, display similar performance in terms of proteins identified and reproducibility. Our results show that our modified FASP protocol is an efficient method for the high-throughput processing of protein samples for mass spectral analysis.

  6. High throughput techniques to reveal the molecular physiology and evolution of digestion in spiders.

    Fuzita, Felipe J; Pinkse, Martijn W H; Patane, José S L; Verhaert, Peter D E M; Lopes, Adriana R

    2016-09-07

    Spiders are known for their predatory efficiency and for their high capacity of digesting relatively large prey. They do this by combining both extracorporeal and intracellular digestion. Whereas many high throughput ("-omics") techniques focus on biomolecules in spider venom, so far this approach has not yet been applied to investigate the protein composition of spider midgut diverticula (MD) and digestive fluid (DF). We here report on our investigations of both MD and DF of the spider Nephilingis (Nephilengys) cruentata through the use of next generation sequencing and shotgun proteomics. This shows that the DF is composed of a variety of hydrolases including peptidases, carbohydrases, lipases and nuclease, as well as of toxins and regulatory proteins. We detect 25 astacins in the DF. Phylogenetic analysis of the corresponding transcript(s) in Arachnida suggests that astacins have acquired an unprecedented role for extracorporeal digestion in Araneae, with different orthologs used by each family. The results of a comparative study of spiders in distinct physiological conditions allow us to propose some digestion mechanisms in this interesting animal taxon. All the high throughput data allowed the demonstration that DF is a secretion originating from the MD. We identified enzymes involved in the extracellular and intracellular phases of digestion. Besides that, data analyses show a large gene duplication event in Araneae digestive process evolution, mainly of astacin genes. We were also able to identify proteins expressed and translated in the digestive system, which until now had been exclusively associated to venom glands.

  7. Optimization and high-throughput screening of antimicrobial peptides.

    Blondelle, Sylvie E; Lohner, Karl

    2010-01-01

    While a well-established process for lead compound discovery in for-profit companies, high-throughput screening is becoming more popular in basic and applied research settings in academia. The development of combinatorial libraries combined with easy and less expensive access to new technologies have greatly contributed to the implementation of high-throughput screening in academic laboratories. While such techniques were earlier applied to simple assays involving single targets or based on binding affinity, they have now been extended to more complex systems such as whole cell-based assays. In particular, the urgent need for new antimicrobial compounds that would overcome the rapid rise of drug-resistant microorganisms, where multiple target assays or cell-based assays are often required, has forced scientists to focus onto high-throughput technologies. Based on their existence in natural host defense systems and their different mode of action relative to commercial antibiotics, antimicrobial peptides represent a new hope in discovering novel antibiotics against multi-resistant bacteria. The ease of generating peptide libraries in different formats has allowed a rapid adaptation of high-throughput assays to the search for novel antimicrobial peptides. Similarly, the availability nowadays of high-quantity and high-quality antimicrobial peptide data has permitted the development of predictive algorithms to facilitate the optimization process. This review summarizes the various library formats that lead to de novo antimicrobial peptide sequences as well as the latest structural knowledge and optimization processes aimed at improving the peptides selectivity.

  8. HTTK: R Package for High-Throughput Toxicokinetics

    Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concent...

  9. Fun with High Throughput Toxicokinetics (CalEPA webinar)

    Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21. These chemicals are tested in part because there are limited or no data on hazard, exposure, or toxicokinetics (TK). TK models aid in predicting tissue concentrations ...

  10. High-throughput cloning and expression in recalcitrant bacteria

    Geertsma, Eric R.; Poolman, Bert

    We developed a generic method for high-throughput cloning in bacteria that are less amenable to conventional DNA manipulations. The method involves ligation-independent cloning in an intermediary Escherichia coli vector, which is rapidly converted via vector-backbone exchange (VBEx) into an

  11. Enzyme free cloning for high throughput gene cloning and expression

    de Jong, R.N.; Daniëls, M.; Kaptein, R.; Folkers, G.E.

    2006-01-01

    Structural and functional genomics initiatives significantly improved cloning methods over the past few years. Although recombinational cloning is highly efficient, its costs urged us to search for an alternative high throughput (HTP) cloning method. We implemented a modified Enzyme Free Cloning

  12. High-throughput bioinformatics with the Cyrille2 pipeline system.

    Fiers, M.W.E.J.; Burgt, van der A.; Datema, E.; Groot, de J.C.W.; Ham, van R.C.H.J.

    2008-01-01

    Background - Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses

  13. A bead-based western for high-throughput cellular signal transduction analyses

    Treindl, Fridolin; Ruprecht, Benjamin; Beiter, Yvonne; Schultz, Silke; Döttinger, Anette; Staebler, Annette; Joos, Thomas O.; Kling, Simon; Poetz, Oliver; Fehm, Tanja; Neubauer, Hans; Kuster, Bernhard; Templin, Markus F.

    2016-01-01

    Dissecting cellular signalling requires the analysis of large number of proteins. The DigiWest approach we describe here transfers the western blot to a bead-based microarray platform. By combining gel-based protein separation with immobilization on microspheres, hundreds of replicas of the initial blot are created, thus enabling the comprehensive analysis of limited material, such as cells collected by laser capture microdissection, and extending traditional western blotting to reach proteomic scales. The combination of molecular weight resolution, sensitivity and signal linearity on an automated platform enables the rapid quantification of hundreds of specific proteins and protein modifications in complex samples. This high-throughput western blot approach allowed us to identify and characterize alterations in cellular signal transduction that occur during the development of resistance to the kinase inhibitor Lapatinib, revealing major changes in the activation state of Ephrin-mediated signalling and a central role for p53-controlled processes. PMID:27659302

  14. Fractal-like Distributions over the Rational Numbers in High-throughput Biological and Clinical Data

    Trifonov, Vladimir; Pasqualucci, Laura; Dalla-Favera, Riccardo; Rabadan, Raul

    2011-12-01

    Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing (HTS), expression profiles, proteomics, and electronic health records (EHR) are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of fractal-like distributions that commonly appear in the analysis of such data. The first set of examples are drawn from a HTS experiment. Here, the distributions appear as part of the evaluation of the error rate of the sequencing and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in EHR. The distributions are also relevant to identification of subclonal populations in tumors and the study of quasi-species and intrahost diversity of viral populations.

  15. Integrative Genomics: Quantifying significance of phenotype-genotype relationships from multiple sources of high-throughput data

    Eric eGamazon

    2013-05-01

    Full Text Available Given recent advances in the generation of high-throughput data such as whole genome genetic variation and transcriptome expression, it is critical to come up with novel methods to integrate these heterogeneous datasets and to assess the significance of identified phenotype-genotype relationships. Recent studies show that genome-wide association findings are likely to fall in loci with gene regulatory effects such as expression quantitative trait loci (eQTLs, demonstrating the utility of such integrative approaches. When genotype and gene expression data are available on the same individuals, we developed methods wherein top phenotype-associated genetic variants are prioritized if they are associated, as eQTLs, with gene expression traits that are themselves associated with the phenotype. Yet there has been no method to determine an overall p-value for the findings that arise specifically from the integrative nature of the approach. We propose a computationally feasible permutation method that accounts for the assimilative nature of the method and the correlation structure among gene expression traits and among genotypes. We apply the method to data from a study of cellular sensitivity to etoposide, one of the most widely used chemotherapeutic drugs. To our knowledge, this study is the first statistically sound quantification of the significance of the genotype-phenotype relationships resulting from applying an integrative approach. This method can be easily extended to cases in which gene expression data are replaced by other molecular phenotypes of interest, e.g., microRNA or proteomic data. This study has important implications for studies seeking to expand on genetic association studies by the use of omics data. Finally, we provide an R code to compute the empirical FDR when p-values for the observed and simulated phenotypes are available.

  16. Large-scale DNA Barcode Library Generation for Biomolecule Identification in High-throughput Screens.

    Lyons, Eli; Sheridan, Paul; Tremmel, Georg; Miyano, Satoru; Sugano, Sumio

    2017-10-24

    High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.

  17. High-throughput search for caloric materials: the CaloriCool approach

    Zarkevich, N. A.; Johnson, D. D.; Pecharsky, V. K.

    2018-01-01

    The high-throughput search paradigm adopted by the newly established caloric materials consortium—CaloriCool®—with the goal to substantially accelerate discovery and design of novel caloric materials is briefly discussed. We begin with describing material selection criteria based on known properties, which are then followed by heuristic fast estimates, ab initio calculations, all of which has been implemented in a set of automated computational tools and measurements. We also demonstrate how theoretical and computational methods serve as a guide for experimental efforts by considering a representative example from the field of magnetocaloric materials.

  18. Computational biology for ageing

    Wieser, Daniela; Papatheodorou, Irene; Ziehm, Matthias; Thornton, Janet M.

    2011-01-01

    High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions. PMID:21115530

  19. Continuing Development of Alternative High-Throughput Screens to Determine Endocrine Disruption, Focusing on Androgen Receptor, Steroidogenesis, and Thyroid Pathways

    The focus of this meeting is the SAP's review and comment on the Agency's proposed high-throughput computational model of androgen receptor pathway activity as an alternative to the current Tier 1 androgen receptor assay (OCSPP 890.1150: Androgen Receptor Binding Rat Prostate Cyt...

  20. SeqAPASS to evaluate conservation of high-throughput screening targets across non-mammalian species

    Cell-based high-throughput screening (HTS) and computational technologies are being applied as tools for toxicity testing in the 21st century. The U.S. Environmental Protection Agency (EPA) embraced these technologies and created the ToxCast Program in 2007, which has served as a...

  1. High throughput 16S rRNA gene amplicon sequencing

    Nierychlo, Marta; Larsen, Poul; Jørgensen, Mads Koustrup

    S rRNA gene amplicon sequencing has been developed over the past few years and is now ready to use for more comprehensive studies related to plant operation and optimization thanks to short analysis time, low cost, high throughput, and high taxonomic resolution. In this study we show how 16S r......RNA gene amplicon sequencing can be used to reveal factors of importance for the operation of full-scale nutrient removal plants related to settling problems and floc properties. Using optimized DNA extraction protocols, indexed primers and our in-house Illumina platform, we prepared multiple samples...... be correlated to the presence of the species that are regarded as “strong” and “weak” floc formers. In conclusion, 16S rRNA gene amplicon sequencing provides a high throughput approach for a rapid and cheap community profiling of activated sludge that in combination with multivariate statistics can be used...

  2. A CRISPR CASe for High-Throughput Silencing

    Jacob eHeintze

    2013-10-01

    Full Text Available Manipulation of gene expression on a genome-wide level is one of the most important systematic tools in the post-genome era. Such manipulations have largely been enabled by expression cloning approaches using sequence-verified cDNA libraries, large-scale RNA interference libraries (shRNA or siRNA and zinc finger nuclease technologies. More recently, the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated (Cas9-mediated gene editing technology has been described that holds great promise for future use of this technology in genomic manipulation. It was suggested that the CRISPR system has the potential to be used in high-throughput, large-scale loss of function screening. Here we discuss some of the challenges in engineering of CRISPR/Cas genomic libraries and some of the aspects that need to be addressed in order to use this technology on a high-throughput scale.

  3. High throughput electrophysiology: new perspectives for ion channel drug discovery

    Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter

    2003-01-01

    Proper function of ion channels is crucial for all living cells. Ion channel dysfunction may lead to a number of diseases, so-called channelopathies, and a number of common diseases, including epilepsy, arrhythmia, and type II diabetes, are primarily treated by drugs that modulate ion channels....... A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct...... characterization of ion channel properties. However, patch clamp is a slow, labor-intensive, and thus expensive, technique. New techniques combining the reliability and high information content of patch clamping with the virtues of high throughput philosophy are emerging and predicted to make a number of ion...

  4. Reverse Phase Protein Arrays for High-throughput Toxicity Screening

    Pedersen, Marlene Lemvig; Block, Ines; List, Markus

    High-throughput screening is extensively applied for identification of drug targets and drug discovery and recently it found entry into toxicity testing. Reverse phase protein arrays (RPPAs) are used widespread for quantification of protein markers. We reasoned that RPPAs also can be utilized...... beneficially in automated high-throughput toxicity testing. An advantage of using RPPAs is that, in addition to the baseline toxicity readout, they allow testing of multiple markers of toxicity, such as inflammatory responses, which do not necessarily cumulate in cell death. We used transfection of si......RNAs with known killing effects as a model system to demonstrate that RPPA-based protein quantification can serve as substitute readout of cell viability, hereby reliably reflecting toxicity. In terms of automation, cell exposure, protein harvest, serial dilution and sample reformatting were performed using...

  5. A high-throughput multiplex method adapted for GMO detection.

    Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

    2008-12-24

    A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

  6. High-throughput epitope identification for snakebite antivenom

    Engmark, Mikael; De Masi, Federico; Laustsen, Andreas Hougaard

    Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individua...... toxins from pit vipers (Crotalidae) using the ICP Crotalidae antivenom. Due to an abundance of snake venom metalloproteinases and phospholipase A2s in the venoms used for production of the investigated antivenom, this study focuses on these toxin families.......Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individual...

  7. High-throughput optical system for HDES hyperspectral imager

    Václavík, Jan; Melich, Radek; Pintr, Pavel; Pleštil, Jan

    2015-01-01

    Affordable, long-wave infrared hyperspectral imaging calls for use of an uncooled FPA with high-throughput optics. This paper describes the design of the optical part of a stationary hyperspectral imager in a spectral range of 7-14 um with a field of view of 20°×10°. The imager employs a push-broom method made by a scanning mirror. High throughput and a demand for simplicity and rigidity led to a fully refractive design with highly aspheric surfaces and off-axis positioning of the detector array. The design was optimized to exploit the machinability of infrared materials by the SPDT method and a simple assemblage.

  8. Development of rapid high throughput biodosimetry tools for radiological triage

    Balajee, Adayabalam S.; Escalona, Maria; Smith, Tammy; Ryan, Terri; Dainiak, Nicholas

    2018-01-01

    Accidental or intentional radiological or nuclear (R/N) disasters constitute a major threat around the globe that can affect several tens, hundreds and thousands of humans. Currently available cytogenetic biodosimeters are time consuming and laborious to perform making them impractical for triage scenarios. Therefore, it is imperative to develop high throughput techniques which will enable timely assessment of personalized dose for making an appropriate 'life-saving' clinical decision

  9. A Functional High-Throughput Assay of Myelination in Vitro

    2014-07-01

    Human induced pluripotent stem cells, hydrogels, 3D culture, electrophysiology, high-throughput assay 16. SECURITY CLASSIFICATION OF: 17...image the 3D rat dorsal root ganglion ( DRG ) cultures with sufficiently low background as to detect electrically-evoked depolarization events, as...of voltage-sensitive dyes. 8    We have made substantial progress in Task 4.1. We have fabricated neural fiber tracts from DRG explants and

  10. High throughput electrophysiology: new perspectives for ion channel drug discovery

    Willumsen, Niels J; Bech, Morten; Olesen, Søren-Peter

    2003-01-01

    . A cornerstone in current drug discovery is high throughput screening assays which allow examination of the activity of specific ion channels though only to a limited extent. Conventional patch clamp remains the sole technique with sufficiently high time resolution and sensitivity required for precise and direct....... The introduction of new powerful HTS electrophysiological techniques is predicted to cause a revolution in ion channel drug discovery....

  11. High-Throughput Block Optical DNA Sequence Identification.

    Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

    2018-01-01

    Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Cloud CPFP: a shotgun proteomics data analysis pipeline using cloud and high performance computing.

    Trudgian, David C; Mirzaei, Hamid

    2012-12-07

    We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

  13. High-throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

    Sloane, A.J.; Duff, J.L.; Hopwood, F.G.; Wilson, N.L.; Smith, P.E.; Hill, C.J.; Packer, N.H.; Williams, K.L.; Gooley, A.A.; Cole, R.A.; Cooley, P.W.; Wallace, D.B.

    2001-01-01

    We describe a 'chemical printer' that uses piezoelectric pulsing for rapid and accurate microdispensing of picolitre volumes of fluid for proteomic analysis of 'protein macroarrays'. Unlike positive transfer and pin transfer systems, our printer dispenses fluid in a non-contact process that ensures that the fluid source cannot be contaminated by substrate during a printing event. We demonstrate automated delivery of enzyme and matrix solutions for on-membrane protein digestion and subsequent peptide mass fingerprinting (pmf) analysis directly from the membrane surface using matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). This approach bypasses the more commonly used multi-step procedures, thereby permitting a more rapid procedure for protein identification. We also highlight the advantage of printing different chemistries onto an individual protein spot for multiple microscale analyses. This ability is particularly useful when detailed characterisation of rare and valuable sample is required. Using a combination of PNGase F and trypsin we have mapped sites of N-glycosylation using on-membrane digestion strategies. We also demonstrate the ability to print multiple serum samples in a micro-ELISA format and rapidly screen a protein macroarray of human blood plasma for pathogen-derived antigens. We anticipate that the 'chemical printer' will be a major component of proteomic platforms for high-throughput protein identification and characterisation with widespread applications in biomedical and diagnostic discovery

  14. High-throughput molecular analysis in lung cancer: insights into biology and potential clinical applications.

    Ocak, S; Sos, M L; Thomas, R K; Massion, P P

    2009-08-01

    During the last decade, high-throughput technologies including genomic, epigenomic, transcriptomic and proteomic have been applied to further our understanding of the molecular pathogenesis of this heterogeneous disease, and to develop strategies that aim to improve the management of patients with lung cancer. Ultimately, these approaches should lead to sensitive, specific and noninvasive methods for early diagnosis, and facilitate the prediction of response to therapy and outcome, as well as the identification of potential novel therapeutic targets. Genomic studies were the first to move this field forward by providing novel insights into the molecular biology of lung cancer and by generating candidate biomarkers of disease progression. Lung carcinogenesis is driven by genetic and epigenetic alterations that cause aberrant gene function; however, the challenge remains to pinpoint the key regulatory control mechanisms and to distinguish driver from passenger alterations that may have a small but additive effect on cancer development. Epigenetic regulation by DNA methylation and histone modifications modulate chromatin structure and, in turn, either activate or silence gene expression. Proteomic approaches critically complement these molecular studies, as the phenotype of a cancer cell is determined by proteins and cannot be predicted by genomics or transcriptomics alone. The present article focuses on the technological platforms available and some proposed clinical applications. We illustrate herein how the "-omics" have revolutionised our approach to lung cancer biology and hold promise for personalised management of lung cancer.

  15. Lessons we learned from high-throughput and top-down systems biology analyses about glioma stem cells.

    Mock, Andreas; Chiblak, Sara; Herold-Mende, Christel

    2014-01-01

    A growing body of evidence suggests that glioma stem cells (GSCs) account for tumor initiation, therapy resistance, and the subsequent regrowth of gliomas. Thus, continuous efforts have been undertaken to further characterize this subpopulation of less differentiated tumor cells. Although we are able to enrich GSCs, we still lack a comprehensive understanding of GSC phenotypes and behavior. The advent of high-throughput technologies raised hope that incorporation of these newly developed platforms would help to tackle such questions. Since then a couple of comparative genome-, transcriptome- and proteome-wide studies on GSCs have been conducted giving new insights in GSC biology. However, lessons had to be learned in designing high-throughput experiments and some of the resulting conclusions fell short of expectations because they were performed on only a few GSC lines or at one molecular level instead of an integrative poly-omics approach. Despite these shortcomings, our knowledge of GSC biology has markedly expanded due to a number of survival-associated biomarkers as well as glioma-relevant signaling pathways and therapeutic targets being identified. In this article we review recent findings obtained by comparative high-throughput analyses of GSCs. We further summarize fundamental concepts of systems biology as well as its applications for glioma stem cell research.

  16. A high-throughput pipeline for the design of real-time PCR signatures

    Reifman Jaques

    2010-06-01

    Full Text Available Abstract Background Pathogen diagnostic assays based on polymerase chain reaction (PCR technology provide high sensitivity and specificity. However, the design of these diagnostic assays is computationally intensive, requiring high-throughput methods to identify unique PCR signatures in the presence of an ever increasing availability of sequenced genomes. Results We present the Tool for PCR Signature Identification (TOPSI, a high-performance computing pipeline for the design of PCR-based pathogen diagnostic assays. The TOPSI pipeline efficiently designs PCR signatures common to multiple bacterial genomes by obtaining the shared regions through pairwise alignments between the input genomes. TOPSI successfully designed PCR signatures common to 18 Staphylococcus aureus genomes in less than 14 hours using 98 cores on a high-performance computing system. Conclusions TOPSI is a computationally efficient, fully integrated tool for high-throughput design of PCR signatures common to multiple bacterial genomes. TOPSI is freely available for download at http://www.bhsai.org/downloads/topsi.tar.gz.

  17. High-throughput gated photon counter with two detection windows programmable down to 70 ps width

    Boso, Gianluca; Tosi, Alberto, E-mail: alberto.tosi@polimi.it; Zappa, Franco [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Piazza Leonardo Da Vinci 32, 20133 Milano (Italy); Mora, Alberto Dalla [Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo Da Vinci 32, 20133 Milano (Italy)

    2014-01-15

    We present the design and characterization of a high-throughput gated photon counter able to count electrical pulses occurring within two well-defined and programmable detection windows. We extensively characterized and validated this instrument up to 100 Mcounts/s and with detection window width down to 70 ps. This instrument is suitable for many applications and proves to be a cost-effective and compact alternative to time-correlated single-photon counting equipment, thanks to its easy configurability, user-friendly interface, and fully adjustable settings via a Universal Serial Bus (USB) link to a remote computer.

  18. High throughput diffractive multi-beam femtosecond laser processing using a spatial light modulator

    Kuang Zheng [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom)], E-mail: z.kuang@liv.ac.uk; Perrie, Walter [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom); Leach, Jonathan [Department of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Sharp, Martin; Edwardson, Stuart P. [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom); Padgett, Miles [Department of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Dearden, Geoff; Watkins, Ken G. [Laser Group, Department of Engineering, University of Liverpool Brownlow Street, Liverpool L69 3GQ (United Kingdom)

    2008-12-30

    High throughput femtosecond laser processing is demonstrated by creating multiple beams using a spatial light modulator (SLM). The diffractive multi-beam patterns are modulated in real time by computer generated holograms (CGHs), which can be calculated by appropriate algorithms. An interactive LabVIEW program is adopted to generate the relevant CGHs. Optical efficiency at this stage is shown to be {approx}50% into first order beams and real time processing has been carried out at 50 Hz refresh rate. Results obtained demonstrate high precision surface micro-structuring on silicon and Ti6Al4V with throughput gain >1 order of magnitude.

  19. High-throughput gated photon counter with two detection windows programmable down to 70 ps width

    Boso, Gianluca; Tosi, Alberto; Zappa, Franco; Mora, Alberto Dalla

    2014-01-01

    We present the design and characterization of a high-throughput gated photon counter able to count electrical pulses occurring within two well-defined and programmable detection windows. We extensively characterized and validated this instrument up to 100 Mcounts/s and with detection window width down to 70 ps. This instrument is suitable for many applications and proves to be a cost-effective and compact alternative to time-correlated single-photon counting equipment, thanks to its easy configurability, user-friendly interface, and fully adjustable settings via a Universal Serial Bus (USB) link to a remote computer

  20. Development of a high-throughput method for the systematic identification of human proteins nuclear translocation potential

    Kawai Jun

    2009-09-01

    Full Text Available Abstract Background Important clues to the function of novel and uncharacterized proteins can be obtained by identifying their ability to translocate in the nucleus. In addition, a comprehensive definition of the nuclear proteome undoubtedly represents a key step toward a better understanding of the biology of this organelle. Although several high-throughput experimental methods have been developed to explore the sub-cellular localization of proteins, these methods tend to focus on the predominant localizations of gene products and may fail to provide a complete catalog of proteins that are able to transiently locate into the nucleus. Results We have developed a method for examining the nuclear localization potential of human gene products at the proteome scale by adapting a mammalian two-hybrid system we have previously developed. Our system is composed of three constructs co-transfected into a mammalian cell line. First, it contains a PCR construct encoding a fusion protein composed of a tested protein, the PDZ-protein TIP-1, and the transactivation domain of TNNC2 (referred to as ACT construct. Second, our system contains a PCR construct encoding a fusion protein composed of the DNA binding domain of GAL4 and the PDZ binding domain of rhotekin (referred to as the BIND construct. Third, a GAL4-responsive luciferase reporter is used to detect the reconstitution of a transcriptionally active BIND-ACT complex through the interaction of TIP-1 and rhotekin, which indicates the ability of the tested protein to translocate into the nucleus. We validated our method in a small-scale feasibility study by comparing it to green fluorescent protein (GFP fusion-based sub-cellular localization assays, sequence-based computational prediction of protein sub-cellular localization, and current sub-cellular localization data available from the literature for 22 gene products. Conclusion Our reporter-based system can rapidly screen gene products for their ability

  1. High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

    Boger, Dale L

    2005-01-01

    .... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

  2. High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

    Boger, Dale

    2004-01-01

    .... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

  3. High throughput experimentation for the discovery of new catalysts

    Thomson, S.; Hoffmann, C.; Johann, T.; Wolf, A.; Schmidt, H.-W.; Farrusseng, D.; Schueth, F.

    2002-01-01

    Full text: The use of combinatorial chemistry to obtain new materials has been developed extensively by the pharmaceutical and biochemical industries, but such approaches have been slow to impact on the field of heterogeneous catalysis. The reasons for this lie in with difficulties associated in the synthesis, characterisation and determination of catalytic properties of such materials. In many synthetic and catalytic reactions, the conditions used are difficult to emulate using High Throughput Experimentation (HTE). Furthermore, the ability to screen these catalysts simultaneously in real time, requires the development and/or modification of characterisation methods. Clearly, there is a need for both high throughput synthesis and screening of new and novel reactions, and we describe several new concepts that help to achieve these goals. Although such problems have impeded the development of combinatorial catalysis, the fact remains that many highly attractive processes still exist for which no suitable catalysts have been developed. The ability to decrease the tiFme needed to evaluate catalyst is therefore essential and this makes the use of high throughput techniques highly desirable. In this presentation we will describe the synthesis, catalytic testing, and novel screening methods developed at the Max Planck Institute. Automated synthesis procedures, performed by the use of a modified Gilson pipette robot, will be described, as will the development of two 16 and 49 sample fixed bed reactors and two 25 and 29 sample three phase reactors for catalytic testing. We will also present new techniques for the characterisation of catalysts and catalytic products using standard IR microscopy and infrared focal plane array detection, respectively

  4. High-throughput screening to enhance oncolytic virus immunotherapy

    Allan KJ

    2016-04-01

    Full Text Available KJ Allan,1,2 David F Stojdl,1–3 SL Swift1 1Children’s Hospital of Eastern Ontario (CHEO Research Institute, 2Department of Biology, Microbiology and Immunology, 3Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada Abstract: High-throughput screens can rapidly scan and capture large amounts of information across multiple biological parameters. Although many screens have been designed to uncover potential new therapeutic targets capable of crippling viruses that cause disease, there have been relatively few directed at improving the efficacy of viruses that are used to treat disease. Oncolytic viruses (OVs are biotherapeutic agents with an inherent specificity for treating malignant disease. Certain OV platforms – including those based on herpes simplex virus, reovirus, and vaccinia virus – have shown success against solid tumors in advanced clinical trials. Yet, many of these OVs have only undergone minimal engineering to solidify tumor specificity, with few extra modifications to manipulate additional factors. Several aspects of the interaction between an OV and a tumor-bearing host have clear value as targets to improve therapeutic outcomes. At the virus level, these include delivery to the tumor, infectivity, productivity, oncolysis, bystander killing, spread, and persistence. At the host level, these include engaging the immune system and manipulating the tumor microenvironment. Here, we review the chemical- and genome-based high-throughput screens that have been performed to manipulate such parameters during OV infection and analyze their impact on therapeutic efficacy. We further explore emerging themes that represent key areas of focus for future research. Keywords: oncolytic, virus, screen, high-throughput, cancer, chemical, genomic, immunotherapy

  5. High-throughput fractionation of human plasma for fast enrichment of low- and high-abundance proteins.

    Breen, Lucas; Cao, Lulu; Eom, Kirsten; Srajer Gajdosik, Martina; Camara, Lila; Giacometti, Jasminka; Dupuy, Damian E; Josic, Djuro

    2012-05-01

    Fast, cost-effective and reproducible isolation of IgM from plasma is invaluable to the study of IgM and subsequent understanding of the human immune system. Additionally, vast amounts of information regarding human physiology and disease can be derived from analysis of the low abundance proteome of the plasma. In this study, methods were optimized for both the high-throughput isolation of IgM from human plasma, and the high-throughput isolation and fractionation of low abundance plasma proteins. To optimize the chromatographic isolation of IgM from human plasma, many variables were examined including chromatography resin, mobile phases, and order of chromatographic separations. Purification of IgM was achieved most successfully through isolation of immunoglobulin from human plasma using Protein A chromatography with a specific resin followed by subsequent fractionation using QA strong anion exchange chromatography. Through these optimization experiments, an additional method was established to prepare plasma for analysis of low abundance proteins. This method involved chromatographic depletion of high-abundance plasma proteins and reduction of plasma proteome complexity through further chromatographic fractionation. Purification of IgM was achieved with high purity as confirmed by SDS-PAGE and IgM-specific immunoblot. Isolation and fractionation of low abundance protein was also performed successfully, as confirmed by SDS-PAGE and mass spectrometry analysis followed by label-free quantitative spectral analysis. The level of purity of the isolated IgM allows for further IgM-specific analysis of plasma samples. The developed fractionation scheme can be used for high throughput screening of human plasma in order to identify low and high abundance proteins as potential prognostic and diagnostic disease biomarkers.

  6. High-throughput anisotropic plasma etching of polyimide for MEMS

    Bliznetsov, Vladimir; Manickam, Anbumalar; Ranganathan, Nagarajan; Chen, Junwei

    2011-01-01

    This note describes a new high-throughput process of polyimide etching for the fabrication of MEMS devices with an organic sacrificial layer approach. Using dual frequency superimposed capacitively coupled plasma we achieved a vertical profile of polyimide with an etching rate as high as 3.5 µm min −1 . After the fabrication of vertical structures in a polyimide material, additional steps were performed to fabricate structural elements of MEMS by deposition of a SiO 2 layer and performing release etching of polyimide. (technical note)

  7. High Throughput System for Plant Height and Hyperspectral Measurement

    Zhao, H.; Xu, L.; Jiang, H.; Shi, S.; Chen, D.

    2018-04-01

    Hyperspectral and three-dimensional measurement can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. And narrow field of view (FOV) extends the working hours in farms. Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information.

  8. Quack: A quality assurance tool for high throughput sequence data.

    Thrash, Adam; Arick, Mark; Peterson, Daniel G

    2018-05-01

    The quality of data generated by high-throughput DNA sequencing tools must be rapidly assessed in order to determine how useful the data may be in making biological discoveries; higher quality data leads to more confident results and conclusions. Due to the ever-increasing size of data sets and the importance of rapid quality assessment, tools that analyze sequencing data should quickly produce easily interpretable graphics. Quack addresses these issues by generating information-dense visualizations from FASTQ files at a speed far surpassing other publicly available quality assurance tools in a manner independent of sequencing technology. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Creation of a small high-throughput screening facility.

    Flak, Tod

    2009-01-01

    The creation of a high-throughput screening facility within an organization is a difficult task, requiring a substantial investment of time, money, and organizational effort. Major issues to consider include the selection of equipment, the establishment of data analysis methodologies, and the formation of a group having the necessary competencies. If done properly, it is possible to build a screening system in incremental steps, adding new pieces of equipment and data analysis modules as the need grows. Based upon our experience with the creation of a small screening service, we present some guidelines to consider in planning a screening facility.

  10. High throughput platforms for structural genomics of integral membrane proteins.

    Mancia, Filippo; Love, James

    2011-08-01

    Structural genomics approaches on integral membrane proteins have been postulated for over a decade, yet specific efforts are lagging years behind their soluble counterparts. Indeed, high throughput methodologies for production and characterization of prokaryotic integral membrane proteins are only now emerging, while large-scale efforts for eukaryotic ones are still in their infancy. Presented here is a review of recent literature on actively ongoing structural genomics of membrane protein initiatives, with a focus on those aimed at implementing interesting techniques aimed at increasing our rate of success for this class of macromolecules. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. Spectrophotometric Enzyme Assays for High-Throughput Screening

    Jean-Louis Reymond

    2004-01-01

    Full Text Available This paper reviews high-throughput screening enzyme assays developed in our laboratory over the last ten years. These enzyme assays were initially developed for the purpose of discovering catalytic antibodies by screening cell culture supernatants, but have proved generally useful for testing enzyme activities. Examples include TLC-based screening using acridone-labeled substrates, fluorogenic assays based on the β-elimination of umbelliferone or nitrophenol, and indirect assays such as the back-titration method with adrenaline and the copper-calcein fluorescence assay for aminoacids.

  12. Correction of Microplate Data from High-Throughput Screening.

    Wang, Yuhong; Huang, Ruili

    2016-01-01

    High-throughput screening (HTS) makes it possible to collect cellular response data from a large number of cell lines and small molecules in a timely and cost-effective manner. The errors and noises in the microplate-formatted data from HTS have unique characteristics, and they can be generally grouped into three categories: run-wise (temporal, multiple plates), plate-wise (background pattern, single plate), and well-wise (single well). In this chapter, we describe a systematic solution for identifying and correcting such errors and noises, mainly basing on pattern recognition and digital signal processing technologies.

  13. HIGH THROUGHPUT SYSTEM FOR PLANT HEIGHT AND HYPERSPECTRAL MEASUREMENT

    H. Zhao

    2018-04-01

    Full Text Available Hyperspectral and three-dimensional measurement can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. And narrow field of view (FOV extends the working hours in farms. Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information.

  14. High-throughput fragment screening by affinity LC-MS.

    Duong-Thi, Minh-Dao; Bergström, Maria; Fex, Tomas; Isaksson, Roland; Ohlson, Sten

    2013-02-01

    Fragment screening, an emerging approach for hit finding in drug discovery, has recently been proven effective by its first approved drug, vemurafenib, for cancer treatment. Techniques such as nuclear magnetic resonance, surface plasmon resonance, and isothemal titration calorimetry, with their own pros and cons, have been employed for screening fragment libraries. As an alternative approach, screening based on high-performance liquid chromatography separation has been developed. In this work, we present weak affinity LC/MS as a method to screen fragments under high-throughput conditions. Affinity-based capillary columns with immobilized thrombin were used to screen a collection of 590 compounds from a fragment library. The collection was divided into 11 mixtures (each containing 35 to 65 fragments) and screened by MS detection. The primary screening was performed in 3500 fragments per day). Thirty hits were defined, which subsequently entered a secondary screening using an active site-blocked thrombin column for confirmation of specificity. One hit showed selective binding to thrombin with an estimated dissociation constant (K (D)) in the 0.1 mM range. This study shows that affinity LC/MS is characterized by high throughput, ease of operation, and low consumption of target and fragments, and therefore it promises to be a valuable method for fragment screening.

  15. High-throughput screening of ionic conductivity in polymer membranes

    Zapata, Pedro; Basak, Pratyay; Carson Meredith, J.

    2009-01-01

    Combinatorial and high-throughput techniques have been successfully used for efficient and rapid property screening in multiple fields. The use of these techniques can be an advantageous new approach to assay ionic conductivity and accelerate the development of novel materials in research areas such as fuel cells. A high-throughput ionic conductivity (HTC) apparatus is described and applied to screening candidate polymer electrolyte membranes for fuel cell applications. The device uses a miniature four-point probe for rapid, automated point-to-point AC electrochemical impedance measurements in both liquid and humid air environments. The conductivity of Nafion 112 HTC validation standards was within 1.8% of the manufacturer's specification. HTC screening of 40 novel Kynar poly(vinylidene fluoride) (PVDF)/acrylic polyelectrolyte (PE) membranes focused on varying the Kynar type (5x) and PE composition (8x) using reduced sample sizes. Two factors were found to be significant in determining the proton conducting capacity: (1) Kynar PVDF series: membranes containing a particular Kynar PVDF type exhibited statistically identical mean conductivity as other membranes containing different Kynar PVDF types that belong to the same series or family. (2) Maximum effective amount of polyelectrolyte: increments in polyelectrolyte content from 55 wt% to 60 wt% showed no statistically significant effect in increasing conductivity. In fact, some membranes experienced a reduction in conductivity.

  16. High-throughput technology for novel SO2 oxidation catalysts

    Loskyll, Jonas; Stoewe, Klaus; Maier, Wilhelm F

    2011-01-01

    We review the state of the art and explain the need for better SO 2 oxidation catalysts for the production of sulfuric acid. A high-throughput technology has been developed for the study of potential catalysts in the oxidation of SO 2 to SO 3 . High-throughput methods are reviewed and the problems encountered with their adaptation to the corrosive conditions of SO 2 oxidation are described. We show that while emissivity-corrected infrared thermography (ecIRT) can be used for primary screening, it is prone to errors because of the large variations in the emissivity of the catalyst surface. UV-visible (UV-Vis) spectrometry was selected instead as a reliable analysis method of monitoring the SO 2 conversion. Installing plain sugar absorbents at reactor outlets proved valuable for the detection and quantitative removal of SO 3 from the product gas before the UV-Vis analysis. We also overview some elements used for prescreening and those remaining after the screening of the first catalyst generations. (topical review)

  17. High-throughput electrical characterization for robust overlay lithography control

    Devender, Devender; Shen, Xumin; Duggan, Mark; Singh, Sunil; Rullan, Jonathan; Choo, Jae; Mehta, Sohan; Tang, Teck Jung; Reidy, Sean; Holt, Jonathan; Kim, Hyung Woo; Fox, Robert; Sohn, D. K.

    2017-03-01

    Realizing sensitive, high throughput and robust overlay measurement is a challenge in current 14nm and advanced upcoming nodes with transition to 300mm and upcoming 450mm semiconductor manufacturing, where slight deviation in overlay has significant impact on reliability and yield1). Exponentially increasing number of critical masks in multi-patterning lithoetch, litho-etch (LELE) and subsequent LELELE semiconductor processes require even tighter overlay specification2). Here, we discuss limitations of current image- and diffraction- based overlay measurement techniques to meet these stringent processing requirements due to sensitivity, throughput and low contrast3). We demonstrate a new electrical measurement based technique where resistance is measured for a macro with intentional misalignment between two layers. Overlay is quantified by a parabolic fitting model to resistance where minima and inflection points are extracted to characterize overlay control and process window, respectively. Analyses using transmission electron microscopy show good correlation between actual overlay performance and overlay obtained from fitting. Additionally, excellent correlation of overlay from electrical measurements to existing image- and diffraction- based techniques is found. We also discuss challenges of integrating electrical measurement based approach in semiconductor manufacturing from Back End of Line (BEOL) perspective. Our findings open up a new pathway for accessing simultaneous overlay as well as process window and margins from a robust, high throughput and electrical measurement approach.

  18. Fluorescent foci quantitation for high-throughput analysis

    Elena Ledesma-Fernández

    2015-06-01

    Full Text Available A number of cellular proteins localize to discrete foci within cells, for example DNA repair proteins, microtubule organizing centers, P bodies or kinetochores. It is often possible to measure the fluorescence emission from tagged proteins within these foci as a surrogate for the concentration of that specific protein. We wished to develop tools that would allow quantitation of fluorescence foci intensities in high-throughput studies. As proof of principle we have examined the kinetochore, a large multi-subunit complex that is critical for the accurate segregation of chromosomes during cell division. Kinetochore perturbations lead to aneuploidy, which is a hallmark of cancer cells. Hence, understanding kinetochore homeostasis and regulation are important for a global understanding of cell division and genome integrity. The 16 budding yeast kinetochores colocalize within the nucleus to form a single focus. Here we have created a set of freely-available tools to allow high-throughput quantitation of kinetochore foci fluorescence. We use this ‘FociQuant’ tool to compare methods of kinetochore quantitation and we show proof of principle that FociQuant can be used to identify changes in kinetochore protein levels in a mutant that affects kinetochore function. This analysis can be applied to any protein that forms discrete foci in cells.

  19. A gas trapping method for high-throughput metabolic experiments.

    Krycer, James R; Diskin, Ciana; Nelson, Marin E; Zeng, Xiao-Yi; Fazakerley, Daniel J; James, David E

    2018-01-01

    Research into cellular metabolism has become more high-throughput, with typical cell-culture experiments being performed in multiwell plates (microplates). This format presents a challenge when trying to collect gaseous products, such as carbon dioxide (CO2), which requires a sealed environment and a vessel separate from the biological sample. To address this limitation, we developed a gas trapping protocol using perforated plastic lids in sealed cell-culture multiwell plates. We used this trap design to measure CO2 production from glucose and fatty acid metabolism, as well as hydrogen sulfide production from cysteine-treated cells. Our data clearly show that this gas trap can be applied to liquid and solid gas-collection media and can be used to study gaseous product generation by both adherent cells and cells in suspension. Since our gas traps can be adapted to multiwell plates of various sizes, they present a convenient, cost-effective solution that can accommodate the trend toward high-throughput measurements in metabolic research.

  20. The JCSG high-throughput structural biology pipeline

    Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wooley, John; Wüthrich, Kurt; Wilson, Ian A.

    2010-01-01

    The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years and has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe. The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications

  1. High-throughput characterization for solar fuels materials discovery

    Mitrovic, Slobodan; Becerra, Natalie; Cornell, Earl; Guevarra, Dan; Haber, Joel; Jin, Jian; Jones, Ryan; Kan, Kevin; Marcin, Martin; Newhouse, Paul; Soedarmadji, Edwin; Suram, Santosh; Xiang, Chengxiang; Gregoire, John; High-Throughput Experimentation Team

    2014-03-01

    In this talk I will present the status of the High-Throughput Experimentation (HTE) project of the Joint Center for Artificial Photosynthesis (JCAP). JCAP is an Energy Innovation Hub of the U.S. Department of Energy with a mandate to deliver a solar fuel generator based on an integrated photoelectrochemical cell (PEC). However, efficient and commercially viable catalysts or light absorbers for the PEC do not exist. The mission of HTE is to provide the accelerated discovery through combinatorial synthesis and rapid screening of material properties. The HTE pipeline also features high-throughput material characterization using x-ray diffraction and x-ray photoemission spectroscopy (XPS). In this talk I present the currently operating pipeline and focus on our combinatorial XPS efforts to build the largest free database of spectra from mixed-metal oxides, nitrides, sulfides and alloys. This work was performed at Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993.

  2. Combinatorial chemoenzymatic synthesis and high-throughput screening of sialosides.

    Chokhawala, Harshal A; Huang, Shengshu; Lau, Kam; Yu, Hai; Cheng, Jiansong; Thon, Vireak; Hurtado-Ziola, Nancy; Guerrero, Juan A; Varki, Ajit; Chen, Xi

    2008-09-19

    Although the vital roles of structures containing sialic acid in biomolecular recognition are well documented, limited information is available on how sialic acid structural modifications, sialyl linkages, and the underlying glycan structures affect the binding or the activity of sialic acid-recognizing proteins and related downstream biological processes. A novel combinatorial chemoenzymatic method has been developed for the highly efficient synthesis of biotinylated sialosides containing different sialic acid structures and different underlying glycans in 96-well plates from biotinylated sialyltransferase acceptors and sialic acid precursors. By transferring the reaction mixtures to NeutrAvidin-coated plates and assaying for the yields of enzymatic reactions using lectins recognizing sialyltransferase acceptors but not the sialylated products, the biotinylated sialoside products can be directly used, without purification, for high-throughput screening to quickly identify the ligand specificity of sialic acid-binding proteins. For a proof-of-principle experiment, 72 biotinylated alpha2,6-linked sialosides were synthesized in 96-well plates from 4 biotinylated sialyltransferase acceptors and 18 sialic acid precursors using a one-pot three-enzyme system. High-throughput screening assays performed in NeutrAvidin-coated microtiter plates show that whereas Sambucus nigra Lectin binds to alpha2,6-linked sialosides with high promiscuity, human Siglec-2 (CD22) is highly selective for a number of sialic acid structures and the underlying glycans in its sialoside ligands.

  3. High-throughput screening with micro-x-ray fluorescence

    Havrilla, George J.; Miller, Thomasin C.

    2005-01-01

    Micro-x-ray fluorescence (MXRF) is a useful characterization tool for high-throughput screening of combinatorial libraries. Due to the increasing threat of use of chemical warfare (CW) agents both in military actions and against civilians by terrorist extremists, there is a strong push to improve existing methods and develop means for the detection of a broad spectrum of CW agents in a minimal amount of time to increase national security. This paper describes a combinatorial high-throughput screening technique for CW receptor discovery to aid in sensor development. MXRF can screen materials for elemental composition at the mesoscale level (tens to hundreds of micrometers). The key aspect of this work is the use of commercial MXRF instrumentation coupled with the inherent heteroatom elements within the target molecules of the combinatorial reaction to provide rapid and specific identification of lead species. The method is demonstrated by screening an 11-mer oligopeptide library for selective binding of the degradation products of the nerve agent VX. The identified oligopeptides can be used as selective molecular receptors for sensor development. The MXRF screening method is nondestructive, requires minimal sample preparation or special tags for analysis, and the screening time depends on the desired sensitivity

  4. A high throughput architecture for a low complexity soft-output demapping algorithm

    Ali, I.; Wasenmüller, U.; Wehn, N.

    2015-11-01

    Iterative channel decoders such as Turbo-Code and LDPC decoders show exceptional performance and therefore they are a part of many wireless communication receivers nowadays. These decoders require a soft input, i.e., the logarithmic likelihood ratio (LLR) of the received bits with a typical quantization of 4 to 6 bits. For computing the LLR values from a received complex symbol, a soft demapper is employed in the receiver. The implementation cost of traditional soft-output demapping methods is relatively large in high order modulation systems, and therefore low complexity demapping algorithms are indispensable in low power receivers. In the presence of multiple wireless communication standards where each standard defines multiple modulation schemes, there is a need to have an efficient demapper architecture covering all the flexibility requirements of these standards. Another challenge associated with hardware implementation of the demapper is to achieve a very high throughput in double iterative systems, for instance, MIMO and Code-Aided Synchronization. In this paper, we present a comprehensive communication and hardware performance evaluation of low complexity soft-output demapping algorithms to select the best algorithm for implementation. The main goal of this work is to design a high throughput, flexible, and area efficient architecture. We describe architectures to execute the investigated algorithms. We implement these architectures on a FPGA device to evaluate their hardware performance. The work has resulted in a hardware architecture based on the figured out best low complexity algorithm delivering a high throughput of 166 Msymbols/second for Gray mapped 16-QAM modulation on Virtex-5. This efficient architecture occupies only 127 slice registers, 248 slice LUTs and 2 DSP48Es.

  5. Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data.

    Gallant, Andrew; Leiserson, Mark D M; Kachalov, Maxim; Cowen, Lenore J; Hescott, Benjamin J

    2013-01-18

    New technology has resulted in high-throughput screens for pairwise genetic interactions in yeast and other model organisms. For each pair in a collection of non-essential genes, an epistasis score is obtained, representing how much sicker (or healthier) the double-knockout organism will be compared to what would be expected from the sickness of the component single knockouts. Recent algorithmic work has identified graph-theoretic patterns in this data that can indicate functional modules, and even sets of genes that may occur in compensatory pathways, such as a BPM-type schema first introduced by Kelley and Ideker. However, to date, any algorithms for finding such patterns in the data were implemented internally, with no software being made publically available. Genecentric is a new package that implements a parallelized version of the Leiserson et al. algorithm (J Comput Biol 18:1399-1409, 2011) for generating generalized BPMs from high-throughput genetic interaction data. Given a matrix of weighted epistasis values for a set of double knock-outs, Genecentric returns a list of generalized BPMs that may represent compensatory pathways. Genecentric also has an extension, GenecentricGO, to query FuncAssociate (Bioinformatics 25:3043-3044, 2009) to retrieve GO enrichment statistics on generated BPMs. Python is the only dependency, and our web site provides working examples and documentation. We find that Genecentric can be used to find coherent functional and perhaps compensatory gene sets from high throughput genetic interaction data. Genecentric is made freely available for download under the GPLv2 from http://bcb.cs.tufts.edu/genecentric.

  6. High-Throughput Screening Using Fourier-Transform Infrared Imaging

    Erdem Sasmaz

    2015-06-01

    Full Text Available Efficient parallel screening of combinatorial libraries is one of the most challenging aspects of the high-throughput (HT heterogeneous catalysis workflow. Today, a number of methods have been used in HT catalyst studies, including various optical, mass-spectrometry, and gas-chromatography techniques. Of these, rapid-scanning Fourier-transform infrared (FTIR imaging is one of the fastest and most versatile screening techniques. Here, the new design of the 16-channel HT reactor is presented and test results for its accuracy and reproducibility are shown. The performance of the system was evaluated through the oxidation of CO over commercial Pd/Al2O3 and cobalt oxide nanoparticles synthesized with different reducer-reductant molar ratios, surfactant types, metal and surfactant concentrations, synthesis temperatures, and ramp rates.

  7. High-Throughput Nanoindentation for Statistical and Spatial Property Determination

    Hintsala, Eric D.; Hangen, Ude; Stauffer, Douglas D.

    2018-04-01

    Standard nanoindentation tests are "high throughput" compared to nearly all other mechanical tests, such as tension or compression. However, the typical rates of tens of tests per hour can be significantly improved. These higher testing rates enable otherwise impractical studies requiring several thousands of indents, such as high-resolution property mapping and detailed statistical studies. However, care must be taken to avoid systematic errors in the measurement, including choosing of the indentation depth/spacing to avoid overlap of plastic zones, pileup, and influence of neighboring microstructural features in the material being tested. Furthermore, since fast loading rates are required, the strain rate sensitivity must also be considered. A review of these effects is given, with the emphasis placed on making complimentary standard nanoindentation measurements to address these issues. Experimental applications of the technique, including mapping of welds, microstructures, and composites with varying length scales, along with studying the effect of surface roughness on nominally homogeneous specimens, will be presented.

  8. Proposed high throughput electrorefining treatment for spent N- Reactor fuel

    Gay, E.C.; Miller, W.E.; Laidler, J.J.

    1996-01-01

    A high-throughput electrorefining process is being adapted to treat spent N-Reactor fuel for ultimate disposal in a geologic repository. Anodic dissolution tests were made with unirradiated N-Reactor fuel to determine the type of fragmentation necessary to provide fuel segments suitable for this process. Based on these tests, a conceptual design was produced of a plant-scale electrorefiner. In this design, the diameter of an electrode assembly is about 1.07 m (42 in.). Three of these assemblies in an electrorefiner would accommodate a 3-metric-ton batch of N-Reactor fuel that would be processed at a rate of 42 kg of uranium per hour

  9. Printing Proteins as Microarrays for High-Throughput Function Determination

    MacBeath, Gavin; Schreiber, Stuart L.

    2000-09-01

    Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

  10. Noise and non-linearities in high-throughput data

    Nguyen, Viet-Anh; Lió, Pietro; Koukolíková-Nicola, Zdena; Bagnoli, Franco

    2009-01-01

    High-throughput data analyses are becoming common in biology, communications, economics and sociology. The vast amounts of data are usually represented in the form of matrices and can be considered as knowledge networks. Spectra-based approaches have proved useful in extracting hidden information within such networks and for estimating missing data, but these methods are based essentially on linear assumptions. The physical models of matching, when applicable, often suggest non-linear mechanisms, that may sometimes be identified as noise. The use of non-linear models in data analysis, however, may require the introduction of many parameters, which lowers the statistical weight of the model. According to the quality of data, a simpler linear analysis may be more convenient than more complex approaches. In this paper, we show how a simple non-parametric Bayesian model may be used to explore the role of non-linearities and noise in synthetic and experimental data sets

  11. High-throughput ab-initio dilute solute diffusion database.

    Wu, Henry; Mayeshiba, Tam; Morgan, Dane

    2016-07-19

    We demonstrate automated generation of diffusion databases from high-throughput density functional theory (DFT) calculations. A total of more than 230 dilute solute diffusion systems in Mg, Al, Cu, Ni, Pd, and Pt host lattices have been determined using multi-frequency diffusion models. We apply a correction method for solute diffusion in alloys using experimental and simulated values of host self-diffusivity. We find good agreement with experimental solute diffusion data, obtaining a weighted activation barrier RMS error of 0.176 eV when excluding magnetic solutes in non-magnetic alloys. The compiled database is the largest collection of consistently calculated ab-initio solute diffusion data in the world.

  12. High Throughput In Situ XAFS Screening of Catalysts

    Tsapatsaris, Nikolaos; Beesley, Angela M.; Weiher, Norbert; Tatton, Helen; Schroeder, Sven L. M.; Dent, Andy J.; Mosselmans, Frederick J. W.; Tromp, Moniek; Russu, Sergio; Evans, John; Harvey, Ian; Hayama, Shu

    2007-01-01

    We outline and demonstrate the feasibility of high-throughput (HT) in situ XAFS for synchrotron radiation studies. An XAS data acquisition and control system for the analysis of dynamic materials libraries under control of temperature and gaseous environments has been developed. The system is compatible with the 96-well industry standard and coupled to multi-stream quadrupole mass spectrometry (QMS) analysis of reactor effluents. An automated analytical workflow generates data quickly compared to traditional individual spectrum acquisition and analyses them in quasi-real time using an HT data analysis tool based on IFFEFIT. The system was used for the automated characterization of a library of 91 catalyst precursors containing ternary combinations of Cu, Pt, and Au on γ-Al2O3, and for the in situ characterization of Au catalysts supported on Al2O3 and TiO2

  13. Machine Learning for High-Throughput Stress Phenotyping in Plants.

    Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh Kumar; Sarkar, Soumik

    2016-02-01

    Advances in automated and high-throughput imaging technologies have resulted in a deluge of high-resolution images and sensor data of plants. However, extracting patterns and features from this large corpus of data requires the use of machine learning (ML) tools to enable data assimilation and feature identification for stress phenotyping. Four stages of the decision cycle in plant stress phenotyping and plant breeding activities where different ML approaches can be deployed are (i) identification, (ii) classification, (iii) quantification, and (iv) prediction (ICQP). We provide here a comprehensive overview and user-friendly taxonomy of ML tools to enable the plant community to correctly and easily apply the appropriate ML tools and best-practice guidelines for various biotic and abiotic stress traits. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. High-throughput mouse genotyping using robotics automation.

    Linask, Kaari L; Lo, Cecilia W

    2005-02-01

    The use of mouse models is rapidly expanding in biomedical research. This has dictated the need for the rapid genotyping of mutant mouse colonies for more efficient utilization of animal holding space. We have established a high-throughput protocol for mouse genotyping using two robotics workstations: a liquid-handling robot to assemble PCR and a microfluidics electrophoresis robot for PCR product analysis. This dual-robotics setup incurs lower start-up costs than a fully automated system while still minimizing human intervention. Essential to this automation scheme is the construction of a database containing customized scripts for programming the robotics workstations. Using these scripts and the robotics systems, multiple combinations of genotyping reactions can be assembled simultaneously, allowing even complex genotyping data to be generated rapidly with consistency and accuracy. A detailed protocol, database, scripts, and additional background information are available at http://dir.nhlbi.nih.gov/labs/ldb-chd/autogene/.

  15. Advances in analytical tools for high throughput strain engineering

    Marcellin, Esteban; Nielsen, Lars Keld

    2018-01-01

    The emergence of inexpensive, base-perfect genome editing is revolutionising biology. Modern industrial biotechnology exploits the advances in genome editing in combination with automation, analytics and data integration to build high-throughput automated strain engineering pipelines also known...... as biofoundries. Biofoundries replace the slow and inconsistent artisanal processes used to build microbial cell factories with an automated design–build–test cycle, considerably reducing the time needed to deliver commercially viable strains. Testing and hence learning remains relatively shallow, but recent...... advances in analytical chemistry promise to increase the depth of characterization possible. Analytics combined with models of cellular physiology in automated systems biology pipelines should enable deeper learning and hence a steeper pitch of the learning cycle. This review explores the progress...

  16. Ethoscopes: An open platform for high-throughput ethomics.

    Quentin Geissmann

    2017-10-01

    Full Text Available Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

  17. Radiation metabolomics : a window to high throughput radiation biodosimetry

    Rana, Poonam

    2016-01-01

    In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for radiation exposure is critical. In particular, a significant number of victims may sustain radiation injury, which increases mortality and worsens the overall prognosis of victims from radiation trauma. Availability of a high-throughput noninvasive in vivo biodosimetry tool for assessing the radiation exposure is of particular importance for timely diagnosis of radiation injury. In this study, we describe the potential NMR techniques in evaluating the radiation injury. NMR is the most versatile technique that has been extensively used in the diverse fields of science since its discovery. NMR and biomedical sciences have been going hand in hand since its application in clinical imaging as MRI and metabolic profiling of biofluids was identified. We have established an NMR based metabonomic and in vivo spectroscopy approach to analyse and identify metabolic profile to measure metabolic fingerprint for radiation exposure. NMR spectroscopy experiments were conducted on urine and serum samples collected from mice irradiated with different doses of radiation. Additionally, in vivo NMR spectroscopy was also performed in different region of brains post irradiation in animal model. A number of metabolites associated with energy metabolism, gut flora metabolites, osmolytes, amino acids and membrane metabolism were identified in serum and urine metabolome. Our results illustrated a metabolic fingerprint for radiation exposure that elucidates perturbed physiological functions. Quantitative as well as multivariate analysis/assessment of these metabolites demonstrated dose and time dependent toxicological effect. In vivo spectroscopy from brain showed radiation induced changes in hippocampus region indicating whole body radiation had striking effect on brain metabolism as well. The results of the present work lay a

  18. A robust robotic high-throughput antibody purification platform.

    Schmidt, Peter M; Abdo, Michael; Butcher, Rebecca E; Yap, Min-Yin; Scotney, Pierre D; Ramunno, Melanie L; Martin-Roussety, Genevieve; Owczarek, Catherine; Hardy, Matthew P; Chen, Chao-Guang; Fabri, Louis J

    2016-07-15

    Monoclonal antibodies (mAbs) have become the fastest growing segment in the drug market with annual sales of more than 40 billion US$ in 2013. The selection of lead candidate molecules involves the generation of large repertoires of antibodies from which to choose a final therapeutic candidate. Improvements in the ability to rapidly produce and purify many antibodies in sufficient quantities reduces the lead time for selection which ultimately impacts on the speed with which an antibody may transition through the research stage and into product development. Miniaturization and automation of chromatography using micro columns (RoboColumns(®) from Atoll GmbH) coupled to an automated liquid handling instrument (ALH; Freedom EVO(®) from Tecan) has been a successful approach to establish high throughput process development platforms. Recent advances in transient gene expression (TGE) using the high-titre Expi293F™ system have enabled recombinant mAb titres of greater than 500mg/L. These relatively high protein titres reduce the volume required to generate several milligrams of individual antibodies for initial biochemical and biological downstream assays, making TGE in the Expi293F™ system ideally suited to high throughput chromatography on an ALH. The present publication describes a novel platform for purifying Expi293F™-expressed recombinant mAbs directly from cell-free culture supernatant on a Perkin Elmer JANUS-VariSpan ALH equipped with a plate shuttle device. The purification platform allows automated 2-step purification (Protein A-desalting/size exclusion chromatography) of several hundred mAbs per week. The new robotic method can purify mAbs with high recovery (>90%) at sub-milligram level with yields of up to 2mg from 4mL of cell-free culture supernatant. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. A pocket device for high-throughput optofluidic holographic microscopy

    Mandracchia, B.; Bianco, V.; Wang, Z.; Paturzo, M.; Bramanti, A.; Pioggia, G.; Ferraro, P.

    2017-06-01

    Here we introduce a compact holographic microscope embedded onboard a Lab-on-a-Chip (LoC) platform. A wavefront division interferometer is realized by writing a polymer grating onto the channel to extract a reference wave from the object wave impinging the LoC. A portion of the beam reaches the samples flowing along the channel path, carrying their information content to the recording device, while one of the diffraction orders from the grating acts as an off-axis reference wave. Polymeric micro-lenses are delivered forward the chip by Pyro-ElectroHydroDynamic (Pyro-EHD) inkjet printing techniques. Thus, all the required optical components are embedded onboard a pocket device, and fast, non-iterative, reconstruction algorithms can be used. We use our device in combination with a novel high-throughput technique, named Space-Time Digital Holography (STDH). STDH exploits the samples motion inside microfluidic channels to obtain a synthetic hologram, mapped in a hybrid space-time domain, and with intrinsic useful features. Indeed, a single Linear Sensor Array (LSA) is sufficient to build up a synthetic representation of the entire experiment (i.e. the STDH) with unlimited Field of View (FoV) along the scanning direction, independently from the magnification factor. The throughput of the imaging system is dramatically increased as STDH provides unlimited FoV, refocusable imaging of samples inside the liquid volume with no need for hologram stitching. To test our embedded STDH microscopy module, we counted, imaged and tracked in 3D with high-throughput red blood cells moving inside the channel volume under non ideal flow conditions.

  20. A high throughput mechanical screening device for cartilage tissue engineering.

    Mohanraj, Bhavana; Hou, Chieh; Meloni, Gregory R; Cosgrove, Brian D; Dodge, George R; Mauck, Robert L

    2014-06-27

    Articular cartilage enables efficient and near-frictionless load transmission, but suffers from poor inherent healing capacity. As such, cartilage tissue engineering strategies have focused on mimicking both compositional and mechanical properties of native tissue in order to provide effective repair materials for the treatment of damaged or degenerated joint surfaces. However, given the large number design parameters available (e.g. cell sources, scaffold designs, and growth factors), it is difficult to conduct combinatorial experiments of engineered cartilage. This is particularly exacerbated when mechanical properties are a primary outcome, given the long time required for testing of individual samples. High throughput screening is utilized widely in the pharmaceutical industry to rapidly and cost-effectively assess the effects of thousands of compounds for therapeutic discovery. Here we adapted this approach to develop a high throughput mechanical screening (HTMS) system capable of measuring the mechanical properties of up to 48 materials simultaneously. The HTMS device was validated by testing various biomaterials and engineered cartilage constructs and by comparing the HTMS results to those derived from conventional single sample compression tests. Further evaluation showed that the HTMS system was capable of distinguishing and identifying 'hits', or factors that influence the degree of tissue maturation. Future iterations of this device will focus on reducing data variability, increasing force sensitivity and range, as well as scaling-up to even larger (96-well) formats. This HTMS device provides a novel tool for cartilage tissue engineering, freeing experimental design from the limitations of mechanical testing throughput. © 2013 Published by Elsevier Ltd.

  1. A High-Throughput Antibody-Based Microarray Typing Platform

    Ashan Perera

    2013-05-01

    Full Text Available Many rapid methods have been developed for screening foods for the presence of pathogenic microorganisms. Rapid methods that have the additional ability to identify microorganisms via multiplexed immunological recognition have the potential for classification or typing of microbial contaminants thus facilitating epidemiological investigations that aim to identify outbreaks and trace back the contamination to its source. This manuscript introduces a novel, high throughput typing platform that employs microarrayed multiwell plate substrates and laser-induced fluorescence of the nucleic acid intercalating dye/stain SYBR Gold for detection of antibody-captured bacteria. The aim of this study was to use this platform for comparison of different sets of antibodies raised against the same pathogens as well as demonstrate its potential effectiveness for serotyping. To that end, two sets of antibodies raised against each of the “Big Six” non-O157 Shiga toxin-producing E. coli (STEC as well as E. coli O157:H7 were array-printed into microtiter plates, and serial dilutions of the bacteria were added and subsequently detected. Though antibody specificity was not sufficient for the development of an STEC serotyping method, the STEC antibody sets performed reasonably well exhibiting that specificity increased at lower capture antibody concentrations or, conversely, at lower bacterial target concentrations. The favorable results indicated that with sufficiently selective and ideally concentrated sets of biorecognition elements (e.g., antibodies or aptamers, this high-throughput platform can be used to rapidly type microbial isolates derived from food samples within ca. 80 min of total assay time. It can also potentially be used to detect the pathogens from food enrichments and at least serve as a platform for testing antibodies.

  2. Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

    Ching, Travers; Zhu, Xun; Garmire, Lana X

    2018-04-01

    Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

  3. High-throughput sample adaptive offset hardware architecture for high-efficiency video coding

    Zhou, Wei; Yan, Chang; Zhang, Jingzhi; Zhou, Xin

    2018-03-01

    A high-throughput hardware architecture for a sample adaptive offset (SAO) filter in the high-efficiency video coding video coding standard is presented. First, an implementation-friendly and simplified bitrate estimation method of rate-distortion cost calculation is proposed to reduce the computational complexity in the mode decision of SAO. Then, a high-throughput VLSI architecture for SAO is presented based on the proposed bitrate estimation method. Furthermore, multiparallel VLSI architecture for in-loop filters, which integrates both deblocking filter and SAO filter, is proposed. Six parallel strategies are applied in the proposed in-loop filters architecture to improve the system throughput and filtering speed. Experimental results show that the proposed in-loop filters architecture can achieve up to 48% higher throughput in comparison with prior work. The proposed architecture can reach a high-operating clock frequency of 297 MHz with TSMC 65-nm library and meet the real-time requirement of the in-loop filters for 8 K × 4 K video format at 132 fps.

  4. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

    Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

    2012-07-15

    In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

  5. A high-throughput two channel discrete wavelet transform architecture for the JPEG2000 standard

    Badakhshannoory, Hossein; Hashemi, Mahmoud R.; Aminlou, Alireza; Fatemi, Omid

    2005-07-01

    The Discrete Wavelet Transform (DWT) is increasingly recognized in image and video compression standards, as indicated by its use in JPEG2000. The lifting scheme algorithm is an alternative DWT implementation that has a lower computational complexity and reduced resource requirement. In the JPEG2000 standard two lifting scheme based filter banks are introduced: the 5/3 and 9/7. In this paper a high throughput, two channel DWT architecture for both of the JPEG2000 DWT filters is presented. The proposed pipelined architecture has two separate input channels that process the incoming samples simultaneously with minimum memory requirement for each channel. The architecture had been implemented in VHDL and synthesized on a Xilinx Virtex2 XCV1000. The proposed architecture applies DWT on a 2K by 1K image at 33 fps with a 75 MHZ clock frequency. This performance is achieved with 70% less resources than two independent single channel modules. The high throughput and reduced resource requirement has made this architecture the proper choice for real time applications such as Digital Cinema.

  6. High-Throughput Molecular Simulations of Metal Organic Frameworks for CO2 Separation: Opportunities and Challenges

    Ilknur Erucar

    2018-02-01

    Full Text Available Metal organic frameworks (MOFs have emerged as great alternatives to traditional nanoporous materials for CO2 separation applications. MOFs are porous materials that are formed by self-assembly of transition metals and organic ligands. The most important advantage of MOFs over well-known porous materials is the possibility to generate multiple materials with varying structural properties and chemical functionalities by changing the combination of metal centers and organic linkers during the synthesis. This leads to a large diversity of materials with various pore sizes and shapes that can be efficiently used for CO2 separations. Since the number of synthesized MOFs has already reached to several thousand, experimental investigation of each MOF at the lab-scale is not practical. High-throughput computational screening of MOFs is a great opportunity to identify the best materials for CO2 separation and to gain molecular-level insights into the structure–performance relationships. This type of knowledge can be used to design new materials with the desired structural features that can lead to extraordinarily high CO2 selectivities. In this mini-review, we focused on developments in high-throughput molecular simulations of MOFs for CO2 separations. After reviewing the current studies on this topic, we discussed the opportunities and challenges in the field and addressed the potential future developments.

  7. High-throughput Molecular Simulations of MOFs for CO2 Separation: Opportunities and Challenges

    Erucar, Ilknur; Keskin, Seda

    2018-02-01

    Metal organic frameworks (MOFs) have emerged as great alternatives to traditional nanoporous materials for CO2 separation applications. MOFs are porous materials that are formed by self-assembly of transition metals and organic ligands. The most important advantage of MOFs over well-known porous materials is the possibility to generate multiple materials with varying structural properties and chemical functionalities by changing the combination of metal centers and organic linkers during the synthesis. This leads to a large diversity of materials with various pore sizes and shapes that can be efficiently used for CO2 separations. Since the number of synthesized MOFs has already reached to several thousand, experimental investigation of each MOF at the lab-scale is not practical. High-throughput computational screening of MOFs is a great opportunity to identify the best materials for CO2 separation and to gain molecular-level insights into the structure-performance relationships. This type of knowledge can be used to design new materials with the desired structural features that can lead to extraordinarily high CO2 selectivities. In this mini-review, we focused on developments in high-throughput molecular simulations of MOFs for CO2 separations. After reviewing the current studies on this topic, we discussed the opportunities and challenges in the field and addressed the potential future developments.

  8. XMRF: an R package to fit Markov Networks to high-throughput genetics data.

    Wan, Ying-Wooi; Allen, Genevera I; Baker, Yulia; Yang, Eunho; Ravikumar, Pradeep; Anderson, Matthew; Liu, Zhandong

    2016-08-26

    Technological advances in medicine have led to a rapid proliferation of high-throughput "omics" data. Tools to mine this data and discover disrupted disease networks are needed as they hold the key to understanding complicated interactions between genes, mutations and aberrations, and epi-genetic markers. We developed an R software package, XMRF, that can be used to fit Markov Networks to various types of high-throughput genomics data. Encoding the models and estimation techniques of the recently proposed exponential family Markov Random Fields (Yang et al., 2012), our software can be used to learn genetic networks from RNA-sequencing data (counts via Poisson graphical models), mutation and copy number variation data (categorical via Ising models), and methylation data (continuous via Gaussian graphical models). XMRF is the only tool that allows network structure learning using the native distribution of the data instead of the standard Gaussian. Moreover, the parallelization feature of the implemented algorithms computes the large-scale biological networks efficiently. XMRF is available from CRAN and Github ( https://github.com/zhandong/XMRF ).

  9. Subnuclear foci quantification using high-throughput 3D image cytometry

    Wadduwage, Dushan N.; Parrish, Marcus; Choi, Heejin; Engelward, Bevin P.; Matsudaira, Paul; So, Peter T. C.

    2015-07-01

    Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

  10. DESIGN OF LOW EPI AND HIGH THROUGHPUT CORDIC CELL TO IMPROVE THE PERFORMANCE OF MOBILE ROBOT

    P. VELRAJKUMAR

    2014-04-01

    Full Text Available This paper mainly focuses on pass logic based design, which gives an low Energy Per Instruction (EPI and high throughput COrdinate Rotation Digital Computer (CORDIC cell for application of robotic exploration. The basic components of CORDIC cell namely register, multiplexer and proposed adder is designed using pass transistor logic (PTL design. The proposed adder is implemented in bit-parallel iterative CORDIC circuit whereas designed using DSCH2 VLSI CAD tool and their layouts are generated by Microwind 3 VLSI CAD tool. The propagation delay, area and power dissipation are calculated from the simulated results for proposed adder based CORDIC cell. The EPI, throughput and effect of temperature are calculated from generated layout. The output parameter of generated layout is analysed using BSIM4 advanced analyzer. The simulated result of the proposed adder based CORDIC circuit is compared with other adder based CORDIC circuits. From the analysis of these simulated results, it was found that the proposed adder based CORDIC circuit dissipates low power, gives faster response, low EPI and high throughput.

  11. Characterizing ncRNAs in human pathogenic protists using high-throughput sequencing technology

    Lesley Joan Collins

    2011-12-01

    Full Text Available ncRNAs are key genes in many human diseases including cancer and viral infection, as well as providing critical functions in pathogenic organisms such as fungi, bacteria, viruses and protists. Until now the identification and characterization of ncRNAs associated with disease has been slow or inaccurate requiring many years of testing to understand complicated RNA and protein gene relationships. High-throughput sequencing now offers the opportunity to characterize miRNAs, siRNAs, snoRNAs and long ncRNAs on a genomic scale making it faster and easier to clarify how these ncRNAs contribute to the disease state. However, this technology is still relatively new, and ncRNA discovery is not an application of high priority for streamlined bioinformatics. Here we summarize background concepts and practical approaches for ncRNA analysis using high-throughput sequencing, and how it relates to understanding human disease. As a case study, we focus on the parasitic protists Giardia lamblia and Trichomonas vaginalis, where large evolutionary distance has meant difficulties in comparing ncRNAs with those from model eukaryotes. A combination of biological, computational and sequencing approaches has enabled easier classification of ncRNA classes such as snoRNAs, but has also aided the identification of novel classes. It is hoped that a higher level of understanding of ncRNA expression and interaction may aid in the development of less harsh treatment for protist-based diseases.

  12. Characterizing ncRNAs in Human Pathogenic Protists Using High-Throughput Sequencing Technology

    Collins, Lesley Joan

    2011-01-01

    ncRNAs are key genes in many human diseases including cancer and viral infection, as well as providing critical functions in pathogenic organisms such as fungi, bacteria, viruses, and protists. Until now the identification and characterization of ncRNAs associated with disease has been slow or inaccurate requiring many years of testing to understand complicated RNA and protein gene relationships. High-throughput sequencing now offers the opportunity to characterize miRNAs, siRNAs, small nucleolar RNAs (snoRNAs), and long ncRNAs on a genomic scale, making it faster and easier to clarify how these ncRNAs contribute to the disease state. However, this technology is still relatively new, and ncRNA discovery is not an application of high priority for streamlined bioinformatics. Here we summarize background concepts and practical approaches for ncRNA analysis using high-throughput sequencing, and how it relates to understanding human disease. As a case study, we focus on the parasitic protists Giardia lamblia and Trichomonas vaginalis, where large evolutionary distance has meant difficulties in comparing ncRNAs with those from model eukaryotes. A combination of biological, computational, and sequencing approaches has enabled easier classification of ncRNA classes such as snoRNAs, but has also aided the identification of novel classes. It is hoped that a higher level of understanding of ncRNA expression and interaction may aid in the development of less harsh treatment for protist-based diseases. PMID:22303390

  13. High-throughput volumetric reconstruction for 3D wheat plant architecture studies

    Wei Fang

    2016-09-01

    Full Text Available For many tiller crops, the plant architecture (PA, including the plant fresh weight, plant height, number of tillers, tiller angle and stem diameter, significantly affects the grain yield. In this study, we propose a method based on volumetric reconstruction for high-throughput three-dimensional (3D wheat PA studies. The proposed methodology involves plant volumetric reconstruction from multiple images, plant model processing and phenotypic parameter estimation and analysis. This study was performed on 80 Triticum aestivum plants, and the results were analyzed. Comparing the automated measurements with manual measurements, the mean absolute percentage error (MAPE in the plant height and the plant fresh weight was 2.71% (1.08cm with an average plant height of 40.07cm and 10.06% (1.41g with an average plant fresh weight of 14.06g, respectively. The root mean square error (RMSE was 1.37cm and 1.79g for the plant height and plant fresh weight, respectively. The correlation coefficients were 0.95 and 0.96 for the plant height and plant fresh weight, respectively. Additionally, the proposed methodology, including plant reconstruction, model processing and trait extraction, required only approximately 20s on average per plant using parallel computing on a graphics processing unit (GPU, demonstrating that the methodology would be valuable for a high-throughput phenotyping platform.

  14. SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets.

    Gosline, Sara J C; Spencer, Sarah J; Ursu, Oana; Fraenkel, Ernest

    2012-11-01

    The rapid development of high throughput biotechnologies has led to an onslaught of data describing genetic perturbations and changes in mRNA and protein levels in the cell. Because each assay provides a one-dimensional snapshot of active signaling pathways, it has become desirable to perform multiple assays (e.g. mRNA expression and phospho-proteomics) to measure a single condition. However, as experiments expand to accommodate various cellular conditions, proper analysis and interpretation of these data have become more challenging. Here we introduce a novel approach called SAMNet, for Simultaneous Analysis of Multiple Networks, that is able to interpret diverse assays over multiple perturbations. The algorithm uses a constrained optimization approach to integrate mRNA expression data with upstream genes, selecting edges in the protein-protein interaction network that best explain the changes across all perturbations. The result is a putative set of protein interactions that succinctly summarizes the results from all experiments, highlighting the network elements unique to each perturbation. We evaluated SAMNet in both yeast and human datasets. The yeast dataset measured the cellular response to seven different transition metals, and the human dataset measured cellular changes in four different lung cancer models of Epithelial-Mesenchymal Transition (EMT), a crucial process in tumor metastasis. SAMNet was able to identify canonical yeast metal-processing genes unique to each commodity in the yeast dataset, as well as human genes such as β-catenin and TCF7L2/TCF4 that are required for EMT signaling but escaped detection in the mRNA and phospho-proteomic data. Moreover, SAMNet also highlighted drugs likely to modulate EMT, identifying a series of less canonical genes known to be affected by the BCR-ABL inhibitor imatinib (Gleevec), suggesting a possible influence of this drug on EMT.

  15. msBiodat analysis tool, big data analysis for high-throughput experiments.

    Muñoz-Torres, Pau M; Rokć, Filip; Belužic, Robert; Grbeša, Ivana; Vugrek, Oliver

    2016-01-01

    Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of proteins. Filtering those data efficiently is the first step for extracting biologically relevant information. The filtering may increase interest by merging previous data with the data obtained from public databases, resulting in an accurate list of proteins which meet the predetermined conditions. In this article we present msBiodat Analysis Tool, a web-based application thought to approach proteomics to the big data analysis. With this tool, researchers can easily select the most relevant information from their MS experiments using an easy-to-use web interface. An interesting feature of msBiodat analysis tool is the possibility of selecting proteins by its annotation on Gene Ontology using its Gene Id, ensembl or UniProt codes. The msBiodat analysis tool is a web-based application that allows researchers with any programming experience to deal with efficient database querying advantages. Its versatility and user-friendly interface makes easy to perform fast and accurate data screening by using complex queries. Once the analysis is finished, the result is delivered by e-mail. msBiodat analysis tool is freely available at http://msbiodata.irb.hr.

  16. The main challenges that remain in applying high-throughput sequencing to clinical diagnostics.

    Loeffelholz, Michael; Fofanov, Yuriy

    2015-01-01

    Over the last 10 years, the quality, price and availability of high-throughput sequencing instruments have improved to the point that this technology may be close to becoming a routine tool in the diagnostic microbiology laboratory. Two groups of challenges, however, have to be resolved in order to move this powerful research technology into routine use in the clinical microbiology laboratory. The computational/bioinformatics challenges include data storage cost and privacy concerns, requiring analysis to be performed without access to cloud storage or expensive computational infrastructure. The logistical challenges include interpretation of complex results and acceptance and understanding of the advantages and limitations of this technology by the medical community. This article focuses on the approaches to address these challenges, such as file formats, algorithms, data collection, reporting and good laboratory practices.

  17. Automated degenerate PCR primer design for high-throughput sequencing improves efficiency of viral sequencing

    Li Kelvin

    2012-11-01

    Full Text Available Abstract Background In a high-throughput environment, to PCR amplify and sequence a large set of viral isolates from populations that are potentially heterogeneous and continuously evolving, the use of degenerate PCR primers is an important strategy. Degenerate primers allow for the PCR amplification of a wider range of viral isolates with only one set of pre-mixed primers, thus increasing amplification success rates and minimizing the necessity for genome finishing activities. To successfully select a large set of degenerate PCR primers necessary to tile across an entire viral genome and maximize their success, this process is best performed computationally. Results We have developed a fully automated degenerate PCR primer design system that plays a key role in the J. Craig Venter Institute’s (JCVI high-throughput viral sequencing pipeline. A consensus viral genome, or a set of consensus segment sequences in the case of a segmented virus, is specified using IUPAC ambiguity codes in the consensus template sequence to represent the allelic diversity of the target population. PCR primer pairs are then selected computationally to produce a minimal amplicon set capable of tiling across the full length of the specified target region. As part of the tiling process, primer pairs are computationally screened to meet the criteria for successful PCR with one of two described amplification protocols. The actual sequencing success rates for designed primers for measles virus, mumps virus, human parainfluenza virus 1 and 3, human respiratory syncytial virus A and B and human metapneumovirus are described, where >90% of designed primer pairs were able to consistently successfully amplify >75% of the isolates. Conclusions Augmenting our previously developed and published JCVI Primer Design Pipeline, we achieved similarly high sequencing success rates with only minor software modifications. The recommended methodology for the construction of the consensus

  18. A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

    Nicolas Pinto

    2009-11-01

    Full Text Available While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor. In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

  19. A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

    Pinto, Nicolas; Doukhan, David; DiCarlo, James J; Cox, David D

    2009-11-01

    While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

  20. Quantitative high throughput analytics to support polysaccharide production process development.

    Noyes, Aaron; Godavarti, Ranga; Titchener-Hooker, Nigel; Coffman, Jonathan; Mukhopadhyay, Tarit

    2014-05-19

    The rapid development of purification processes for polysaccharide vaccines is constrained by a lack of analytical tools current technologies for the measurement of polysaccharide recovery and process-related impurity clearance are complex, time-consuming, and generally not amenable to high throughput process development (HTPD). HTPD is envisioned to be central to the improvement of existing polysaccharide manufacturing processes through the identification of critical process parameters that potentially impact the quality attributes of the vaccine and to the development of de novo processes for clinical candidates, across the spectrum of downstream processing. The availability of a fast and automated analytics platform will expand the scope, robustness, and evolution of Design of Experiment (DOE) studies. This paper details recent advances in improving the speed, throughput, and success of in-process analytics at the micro-scale. Two methods, based on modifications of existing procedures, are described for the rapid measurement of polysaccharide titre in microplates without the need for heating steps. A simplification of a commercial endotoxin assay is also described that features a single measurement at room temperature. These assays, along with existing assays for protein and nucleic acids are qualified for deployment in the high throughput screening of polysaccharide feedstreams. Assay accuracy, precision, robustness, interference, and ease of use are assessed and described. In combination, these assays are capable of measuring the product concentration and impurity profile of a microplate of 96 samples in less than one day. This body of work relies on the evaluation of a combination of commercially available and clinically relevant polysaccharides to ensure maximum versatility and reactivity of the final assay suite. Together, these advancements reduce overall process time by up to 30-fold and significantly reduce sample volume over current practices. The

  1. SNP-PHAGE – High throughput SNP discovery pipeline

    Cregan Perry B

    2006-10-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs, amplified fragment length polymorphisms (AFLPs and simple sequence repeats (SSRs or microsatellite markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable. Results We developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis and GenBank (-dbSNP submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at http://bfgl.anri.barc.usda.gov/ML/snp-phage/. Conclusion SNP-PHAGE provides a bioinformatics

  2. Alignment of time-resolved data from high throughput experiments.

    Abidi, Nada; Franke, Raimo; Findeisen, Peter; Klawonn, Frank

    2016-12-01

    To better understand the dynamics of the underlying processes in cells, it is necessary to take measurements over a time course. Modern high-throughput technologies are often used for this purpose to measure the behavior of cell products like metabolites, peptides, proteins, [Formula: see text]RNA or mRNA at different points in time. Compared to classical time series, the number of time points is usually very limited and the measurements are taken at irregular time intervals. The main reasons for this are the costs of the experiments and the fact that the dynamic behavior usually shows a strong reaction and fast changes shortly after a stimulus and then slowly converges to a certain stable state. Another reason might simply be missing values. It is common to repeat the experiments and to have replicates in order to carry out a more reliable analysis. The ideal assumptions that the initial stimulus really started exactly at the same time for all replicates and that the replicates are perfectly synchronized are seldom satisfied. Therefore, there is a need to first adjust or align the time-resolved data before further analysis is carried out. Dynamic time warping (DTW) is considered as one of the common alignment techniques for time series data with equidistant time points. In this paper, we modified the DTW algorithm so that it can align sequences with measurements at different, non-equidistant time points with large gaps in between. This type of data is usually known as time-resolved data characterized by irregular time intervals between measurements as well as non-identical time points for different replicates. This new algorithm can be easily used to align time-resolved data from high-throughput experiments and to come across existing problems such as time scarcity and existing noise in the measurements. We propose a modified method of DTW to adapt requirements imposed by time-resolved data by use of monotone cubic interpolation splines. Our presented approach

  3. Spatial Mapping of Protein Abundances in the Mouse Brain by Voxelation Integrated with High-Throughput Liquid Chromatography ? Mass Spectrometry

    Petyuk, Vladislav A.; Qian, Weijun; Chin, Mark H.; Wang, Haixing H.; Livesay, Eric A.; Monroe, Matthew E.; Adkins, Joshua N.; Jaitly, Navdeep; Anderson, David J.; Camp, David G.; Smith, Desmond J.; Smith, Richard D.

    2007-01-01

    Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput LC system coupled with high resolution Fourier transform ion cyclotron mass spectrometer and a ''universal'' stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1,028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion

  4. Adaptation to high throughput batch chromatography enhances multivariate screening.

    Barker, Gregory A; Calzada, Joseph; Herzer, Sibylle; Rieble, Siegfried

    2015-09-01

    High throughput process development offers unique approaches to explore complex process design spaces with relatively low material consumption. Batch chromatography is one technique that can be used to screen chromatographic conditions in a 96-well plate. Typical batch chromatography workflows examine variations in buffer conditions or comparison of multiple resins in a given process, as opposed to the assessment of protein loading conditions in combination with other factors. A modification to the batch chromatography paradigm is described here where experimental planning, programming, and a staggered loading approach increase the multivariate space that can be explored with a liquid handling system. The iterative batch chromatography (IBC) approach is described, which treats every well in a 96-well plate as an individual experiment, wherein protein loading conditions can be varied alongside other factors such as wash and elution buffer conditions. As all of these factors are explored in the same experiment, the interactions between them are characterized and the number of follow-up confirmatory experiments is reduced. This in turn improves statistical power and throughput. Two examples of the IBC method are shown and the impact of the load conditions are assessed in combination with the other factors explored. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. High Throughput Multispectral Image Processing with Applications in Food Science.

    Panagiotis Tsakanikas

    Full Text Available Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

  6. BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data.

    Giollo, Manuel; Minervini, Giovanni; Scalzotto, Marta; Leonardi, Emanuela; Ferrari, Carlo; Tosatto, Silvio C E

    2015-01-01

    Over the last decade, we have witnessed an incredible growth in the amount of available genotype data due to high throughput sequencing (HTS) techniques. This information may be used to predict phenotypes of medical relevance, and pave the way towards personalized medicine. Blood phenotypes (e.g. ABO and Rh) are a purely genetic trait that has been extensively studied for decades, with currently over thirty known blood groups. Given the public availability of blood group data, it is of interest to predict these phenotypes from HTS data which may translate into more accurate blood typing in clinical practice. Here we propose BOOGIE, a fast predictor for the inference of blood groups from single nucleotide variant (SNV) databases. We focus on the prediction of thirty blood groups ranging from the well known ABO and Rh, to the less studied Junior or Diego. BOOGIE correctly predicted the blood group with 94% accuracy for the Personal Genome Project whole genome profiles where good quality SNV annotation was available. Additionally, our tool produces a high quality haplotype phase, which is of interest in the context of ethnicity-specific polymorphisms or traits. The versatility and simplicity of the analysis make it easily interpretable and allow easy extension of the protocol towards other phenotypes. BOOGIE can be downloaded from URL http://protein.bio.unipd.it/download/.

  7. Multiplexing a high-throughput liability assay to leverage efficiencies.

    Herbst, John; Anthony, Monique; Stewart, Jeremy; Connors, David; Chen, Taosheng; Banks, Martyn; Petrillo, Edward W; Agler, Michele

    2009-06-01

    In order to identify potential cytochrome P-450 3A4 (drug-metabolizing enzyme) inducers at an early stage of the drug discovery process, a cell-based transactivation high-throughput luciferase reporter assay for the human pregnane X receptor (PXR) in HepG2 cells has been implemented and multiplexed with a viability end point for data interpretation, as part of a Lead Profiling portfolio of assays. As a routine part of Lead Profiling operations, assays are periodically evaluated for utility as well as for potential improvements in technology or process. We used a recent evaluation of our PXR-transactivation assay as a model for the application of Lean Thinking-based process analysis to lab-bench assay optimization and automation. This resulted in the development of a 384-well multiplexed homogeneous assay simultaneously detecting PXR transactivation and HepG2 cell cytotoxicity. In order to multiplex fluorescent and luminescent read-outs, modifications to each assay were necessary, which included optimization of multiple assay parameters such as cell density, plate type, and reagent concentrations. Subsequently, a set of compounds including known cytotoxic compounds and PXR inducers were used to validate the multiplexed assay. Results from the multiplexed assay correlate well with those from the singleplexed assay formats measuring PXR transactivation and viability separately. Implementation of the multiplexed assay for routine compound profiling provides improved data quality, sample conservation, cost savings, and resource efficiencies.

  8. High throughput reaction screening using desorption electrospray ionization mass spectrometry.

    Wleklinski, Michael; Loren, Bradley P; Ferreira, Christina R; Jaman, Zinia; Avramova, Larisa; Sobreira, Tiago J P; Thompson, David H; Cooks, R Graham

    2018-02-14

    We report the high throughput analysis of reaction mixture arrays using methods and data handling routines that were originally developed for biological tissue imaging. Desorption electrospray ionization (DESI) mass spectrometry (MS) is applied in a continuous on-line process at rates that approach 10 4 reactions per h at area densities of up to 1 spot per mm 2 (6144 spots per standard microtiter plate) with the sprayer moving at ca. 10 4 microns per s. Data are analyzed automatically by MS using in-house software to create ion images of selected reagents and products as intensity plots in standard array format. Amine alkylation reactions were used to optimize the system performance on PTFE membrane substrates using methanol as the DESI spray/analysis solvent. Reaction times can be screening of processes like N -alkylation and Suzuki coupling reactions as reported herein. Products and by-products were confirmed by on-line MS/MS upon rescanning of the array.

  9. Tiered High-Throughput Screening Approach to Identify ...

    High-throughput screening (HTS) for potential thyroid–disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the US EPA ToxCast screening assay portfolio. To fill one critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast Phase I and II chemical libraries, comprised of 1,074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single concentration screen were retested in concentration-response. Due to high false positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed two additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using

  10. High-Throughput Screening Using Mass Spectrometry within Drug Discovery.

    Rohman, Mattias; Wingfield, Jonathan

    2016-01-01

    In order to detect a biochemical analyte with a mass spectrometer (MS) it is necessary to ionize the analyte of interest. The analyte can be ionized by a number of different mechanisms, however, one common method is electrospray ionization (ESI). Droplets of analyte are sprayed through a highly charged field, the droplets pick up charge, and this is transferred to the analyte. High levels of salt in the assay buffer will potentially steal charge from the analyte and suppress the MS signal. In order to avoid this suppression of signal, salt is often removed from the sample prior to injection into the MS. Traditional ESI MS relies on liquid chromatography (LC) to remove the salt and reduce matrix effects, however, this is a lengthy process. Here we describe the use of RapidFire™ coupled to a triple-quadrupole MS for high-throughput screening. This system uses solid-phase extraction to de-salt samples prior to injection, reducing processing time such that a sample is injected into the MS ~every 10 s.

  11. High-throughput screening of chemical effects on ...

    Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2,060 chemical samples on steroidogenesis via HPLC-MS/MS quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a three stage screening strategy. The first stage established the maximum tolerated concentration (MTC; >70% viability) per sample. The second stage quantified changes in hormone levels at the MTC while the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were pre-stimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2,060 chemical samples evaluated, 524 samples were selected for six-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into five distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A d

  12. High Throughput Heuristics for Prioritizing Human Exposure to ...

    The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the potential hazard presented by the chemical, and the possibility of being exposed. Without the capacity to make quantitative, albeit uncertain, forecasts of exposure, the putative risk of adverse health effect from a chemical cannot be evaluated. We used Bayesian methodology to infer ranges of exposure intakes that are consistent with biomarkers of chemical exposures identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We perform linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using high throughput chemical descriptors gleaned from databases and chemical structure-based calculators. We find that five of these descriptors are capable of explaining roughly 50% of the variability across chemicals for all the demographic groups examined, including children aged 6-11. For the thousands of chemicals with no other source of information, this approach allows rapid and efficient prediction of average exposure intake of environmental chemicals. The methods described by this manuscript provide a highly improved methodology for HTS of human exposure to environmental chemicals. The manuscript includes a ranking of 7785 environmental chemicals with respect to potential human exposure, including most of the Tox21 in vit

  13. High-Throughput Identification of Antimicrobial Peptides from Amphibious Mudskippers

    Yunhai Yi

    2017-11-01

    Full Text Available Widespread existence of antimicrobial peptides (AMPs has been reported in various animals with comprehensive biological activities, which is consistent with the important roles of AMPs as the first line of host defense system. However, no big-data-based analysis on AMPs from any fish species is available. In this study, we identified 507 AMP transcripts on the basis of our previously reported genomes and transcriptomes of two representative amphibious mudskippers, Boleophthalmus pectinirostris (BP and Periophthalmus magnuspinnatus (PM. The former is predominantly aquatic with less time out of water, while the latter is primarily terrestrial with extended periods of time on land. Within these identified AMPs, 449 sequences are novel; 15 were reported in BP previously; 48 are identically overlapped between BP and PM; 94 were validated by mass spectrometry. Moreover, most AMPs presented differential tissue transcription patterns in the two mudskippers. Interestingly, we discovered two AMPs, hemoglobin β1 and amylin, with high inhibitions on Micrococcus luteus. In conclusion, our high-throughput screening strategy based on genomic and transcriptomic data opens an efficient pathway to discover new antimicrobial peptides for ongoing development of marine drugs.

  14. High-Throughput Identification of Antimicrobial Peptides from Amphibious Mudskippers.

    Yi, Yunhai; You, Xinxin; Bian, Chao; Chen, Shixi; Lv, Zhao; Qiu, Limei; Shi, Qiong

    2017-11-22

    Widespread existence of antimicrobial peptides (AMPs) has been reported in various animals with comprehensive biological activities, which is consistent with the important roles of AMPs as the first line of host defense system. However, no big-data-based analysis on AMPs from any fish species is available. In this study, we identified 507 AMP transcripts on the basis of our previously reported genomes and transcriptomes of two representative amphibious mudskippers, Boleophthalmus pectinirostris (BP) and Periophthalmus magnuspinnatus (PM). The former is predominantly aquatic with less time out of water, while the latter is primarily terrestrial with extended periods of time on land. Within these identified AMPs, 449 sequences are novel; 15 were reported in BP previously; 48 are identically overlapped between BP and PM; 94 were validated by mass spectrometry. Moreover, most AMPs presented differential tissue transcription patterns in the two mudskippers. Interestingly, we discovered two AMPs, hemoglobin β1 and amylin, with high inhibitions on Micrococcus luteus . In conclusion, our high-throughput screening strategy based on genomic and transcriptomic data opens an efficient pathway to discover new antimicrobial peptides for ongoing development of marine drugs.

  15. [Morphometry of pulmonary tissue: From manual to high throughput automation].

    Sallon, C; Soulet, D; Tremblay, Y

    2017-12-01

    Weibel's research has shown that any alteration of the pulmonary structure has effects on function. This demonstration required a quantitative analysis of lung structures called morphometry. This is possible thanks to stereology, a set of methods based on principles of geometry and statistics. His work has helped to better understand the morphological harmony of the lung, which is essential for its proper functioning. An imbalance leads to pathophysiology such as chronic obstructive pulmonary disease in adults and bronchopulmonary dysplasia in neonates. It is by studying this imbalance that new therapeutic approaches can be developed. These advances are achievable only through morphometric analytical methods, which are increasingly precise and focused, in particular thanks to the high-throughput automation of these methods. This review makes a comparison between an automated method that we developed in the laboratory and semi-manual methods of morphometric analyzes. The automation of morphometric measurements is a fundamental asset in the study of pulmonary pathophysiology because it is an assurance of robustness, reproducibility and speed. This tool will thus contribute significantly to the acceleration of the race for the development of new drugs. Copyright © 2017 SPLF. Published by Elsevier Masson SAS. All rights reserved.

  16. Use of High Throughput Screening Data in IARC Monograph ...

    Purpose: Evaluation of carcinogenic mechanisms serves a critical role in IARC monograph evaluations, and can lead to “upgrade” or “downgrade” of the carcinogenicity conclusions based on human and animal evidence alone. Three recent IARC monograph Working Groups (110, 112, and 113) pioneered analysis of high throughput in vitro screening data from the U.S. Environmental Protection Agency’s ToxCast program in evaluations of carcinogenic mechanisms. Methods: For monograph 110, ToxCast assay data across multiple nuclear receptors were used to test the hypothesis that PFOA acts exclusively through the PPAR family of receptors, with activity profiles compared to several prototypical nuclear receptor-activating compounds. For monographs 112 and 113, ToxCast assays were systematically evaluated and used as an additional data stream in the overall evaluation of the mechanistic evidence. Specifically, ToxCast assays were mapped to 10 “key characteristics of carcinogens” recently identified by an IARC expert group, and chemicals’ bioactivity profiles were evaluated both in absolute terms (number of relevant assays positive for bioactivity) and relative terms (ranking with respect to other compounds evaluated by IARC, using the ToxPi methodology). Results: PFOA activates multiple nuclear receptors in addition to the PPAR family in the ToxCast assays. ToxCast assays offered substantial coverage for 5 of the 10 “key characteristics,” with the greates

  17. Management of High-Throughput DNA Sequencing Projects: Alpheus.

    Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F

    2008-12-26

    High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.

  18. High-Throughput Network Communication with NetIO

    Schumacher, J\\"orn; The ATLAS collaboration; Vandelli, Wainer

    2016-01-01

    HPC network technologies like Infiniband, TrueScale or OmniPath provide low-latency and high-throughput communication between hosts, which makes them attractive options for data-acquisition systems in large-scale high-energy physics experiments. Like HPC networks, DAQ networks are local and include a well specified number of systems. Unfortunately traditional network communication APIs for HPC clusters like MPI or PGAS target exclusively the HPC community and are not suited well for DAQ applications. It is possible to build distributed DAQ applications using low-level system APIs like Infiniband Verbs (and this has been done), but it requires a non negligible effort and expert knowledge. On the other hand, message services like 0MQ have gained popularity in the HEP community. Such APIs allow to build distributed applications with a high-level approach and provide good performance. Unfortunately their usage usually limits developers to TCP/IP-based networks. While it is possible to operate a TCP/IP stack on to...

  19. High Throughput Sequencing for Detection of Foodborne Pathogens

    Camilla Sekse

    2017-10-01

    Full Text Available High-throughput sequencing (HTS is becoming the state-of-the-art technology for typing of microbial isolates, especially in clinical samples. Yet, its application is still in its infancy for monitoring and outbreak investigations of foods. Here we review the published literature, covering not only bacterial but also viral and Eukaryote food pathogens, to assess the status and potential of HTS implementation to inform stakeholders, improve food safety and reduce outbreak impacts. The developments in sequencing technology and bioinformatics have outpaced the capacity to analyze and interpret the sequence data. The influence of sample processing, nucleic acid extraction and purification, harmonized protocols for generation and interpretation of data, and properly annotated and curated reference databases including non-pathogenic “natural” strains are other major obstacles to the realization of the full potential of HTS in analytical food surveillance, epidemiological and outbreak investigations, and in complementing preventive approaches for the control and management of foodborne pathogens. Despite significant obstacles, the achieved progress in capacity and broadening of the application range over the last decade is impressive and unprecedented, as illustrated with the chosen examples from the literature. Large consortia, often with broad international participation, are making coordinated efforts to cope with many of the mentioned obstacles. Further rapid progress can therefore be prospected for the next decade.

  20. Using high-throughput barcode sequencing to efficiently map connectomes.

    Peikon, Ian D; Kebschull, Justus M; Vagin, Vasily V; Ravens, Diana I; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R; Bressan, Dario; Zador, Anthony M

    2017-07-07

    The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. High Throughput Multispectral Image Processing with Applications in Food Science.

    Tsakanikas, Panagiotis; Pavlidis, Dimitris; Nychas, George-John

    2015-01-01

    Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

  2. Advances in High Throughput Screening of Biomass Recalcitrance (Poster)

    Turner, G. B.; Decker, S. R.; Tucker, M. P.; Law, C.; Doeppke, C.; Sykes, R. W.; Davis, M. F.; Ziebell, A.

    2012-06-01

    This was a poster displayed at the Symposium. Advances on previous high throughput screening of biomass recalcitrance methods have resulted in improved conversion and replicate precision. Changes in plate reactor metallurgy, improved preparation of control biomass, species-specific pretreatment conditions, and enzymatic hydrolysis parameters have reduced overall coefficients of variation to an average of 6% for sample replicates. These method changes have improved plate-to-plate variation of control biomass recalcitrance and improved confidence in sugar release differences between samples. With smaller errors plant researchers can have a higher degree of assurance more low recalcitrance candidates can be identified. Significant changes in plate reactor, control biomass preparation, pretreatment conditions and enzyme have significantly reduced sample and control replicate variability. Reactor plate metallurgy significantly impacts sugar release aluminum leaching into reaction during pretreatment degrades sugars and inhibits enzyme activity. Removal of starch and extractives significantly decreases control biomass variability. New enzyme formulations give more consistent and higher conversion levels, however required re-optimization for switchgrass. Pretreatment time and temperature (severity) should be adjusted to specific biomass types i.e. woody vs. herbaceous. Desalting of enzyme preps to remove low molecular weight stabilizers and improved conversion levels likely due to water activity impacts on enzyme structure and substrate interactions not attempted here due to need to continually desalt and validate precise enzyme concentration and activity.

  3. High-Throughput Printing Process for Flexible Electronics

    Hyun, Woo Jin

    Printed electronics is an emerging field for manufacturing electronic devices with low cost and minimal material waste for a variety of applications including displays, distributed sensing, smart packaging, and energy management. Moreover, its compatibility with roll-to-roll production formats and flexible substrates is desirable for continuous, high-throughput production of flexible electronics. Despite the promise, however, the roll-to-roll production of printed electronics is quite challenging due to web movement hindering accurate ink registration and high-fidelity printing. In this talk, I will present a promising strategy for roll-to-roll production using a novel printing process that we term SCALE (Self-aligned Capillarity-Assisted Lithography for Electronics). By utilizing capillarity of liquid inks on nano/micro-structured substrates, the SCALE process facilitates high-resolution and self-aligned patterning of electrically functional inks with greatly improved printing tolerance. I will show the fabrication of key building blocks (e.g. transistor, resistor, capacitor) for electronic circuits using the SCALE process on plastics.

  4. High-throughput selection for cellulase catalysts using chemical complementation.

    Peralta-Yahya, Pamela; Carter, Brian T; Lin, Hening; Tao, Haiyan; Cornish, Virginia W

    2008-12-24

    Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases, however, is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Because of the large number of enzyme variants that selections can now test as compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity.

  5. Towards Prebiotic Catalytic Amyloids Using High Throughput Screening.

    Michael P Friedmann

    Full Text Available Enzymes are capable of directing complex stereospecific transformations and of accelerating reaction rates many orders of magnitude. As even the simplest known enzymes comprise thousands of atoms, the question arises as to how such exquisite catalysts evolved. A logical predecessor would be shorter peptides, but they lack the defined structure and size that are apparently necessary for enzyme functions. However, some very short peptides are able to assemble into amyloids, thereby forming a well-defined tertiary structure called the cross-β-sheet, which bestows unique properties upon the peptides. We have hypothesized that amyloids could have been the catalytically active precursor to modern enzymes. To test this hypothesis, we designed an amyloid peptide library that could be screened for catalytic activity. Our approach, amenable to high-throughput methodologies, allowed us to find several peptides and peptide mixtures that form amyloids with esterase activity. These results indicate that amyloids, with their stability in a wide range of conditions and their potential as catalysts with low sequence specificity, would indeed be fitting precursors to modern enzymes. Furthermore, our approach can be efficiently expanded upon in library size, screening conditions, and target activity to yield novel amyloid catalysts with potential applications in aqueous-organic mixtures, at high temperature and in other extreme conditions that could be advantageous for industrial applications.

  6. Probabilistic Methods for Processing High-Throughput Sequencing Signals

    Sørensen, Lasse Maretty

    High-throughput sequencing has the potential to answer many of the big questions in biology and medicine. It can be used to determine the ancestry of species, to chart complex ecosystems and to understand and diagnose disease. However, going from raw sequencing data to biological or medical insig....... By estimating the genotypes on a set of candidate variants obtained from both a standard mapping-based approach as well as de novo assemblies, we are able to find considerably more structural variation than previous studies...... for reconstructing transcript sequences from RNA sequencing data. The method is based on a novel sparse prior distribution over transcript abundances and is markedly more accurate than existing approaches. The second chapter describes a new method for calling genotypes from a fixed set of candidate variants....... The method queries the reads using a graph representation of the variants and hereby mitigates the reference-bias that characterise standard genotyping methods. In the last chapter, we apply this method to call the genotypes of 50 deeply sequencing parent-offspring trios from the GenomeDenmark project...

  7. Quantifying Nanoparticle Internalization Using a High Throughput Internalization Assay.

    Mann, Sarah K; Czuba, Ewa; Selby, Laura I; Such, Georgina K; Johnston, Angus P R

    2016-10-01

    The internalization of nanoparticles into cells is critical for effective nanoparticle mediated drug delivery. To investigate the kinetics and mechanism of internalization of nanoparticles into cells we have developed a DNA molecular sensor, termed the Specific Hybridization Internalization Probe - SHIP. Self-assembling polymeric 'pHlexi' nanoparticles were functionalized with a Fluorescent Internalization Probe (FIP) and the interactions with two different cell lines (3T3 and CEM cells) were studied. The kinetics of internalization were quantified and chemical inhibitors that inhibited energy dependent endocytosis (sodium azide), dynamin dependent endocytosis (Dyngo-4a) and macropinocytosis (5-(N-ethyl-N-isopropyl) amiloride (EIPA)) were used to study the mechanism of internalization. Nanoparticle internalization kinetics were significantly faster in 3T3 cells than CEM cells. We have shown that ~90% of the nanoparticles associated with 3T3 cells were internalized, compared to only 20% of the nanoparticles associated with CEM cells. Nanoparticle uptake was via a dynamin-dependent pathway, and the nanoparticles were trafficked to lysosomal compartments once internalized. SHIP is able to distinguish between nanoparticles that are associated on the outer cell membrane from nanoparticles that are internalized. This study demonstrates the assay can be used to probe the kinetics of nanoparticle internalization and the mechanisms by which the nanoparticles are taken up by cells. This information is fundamental for engineering more effective nanoparticle delivery systems. The SHIP assay is a simple and a high-throughput technique that could have wide application in therapeutic delivery research.

  8. High-Throughput Analysis and Automation for Glycomics Studies.

    Shubhakar, Archana; Reiding, Karli R; Gardner, Richard A; Spencer, Daniel I R; Fernandes, Daryl L; Wuhrer, Manfred

    This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics-for example in Genome Wide Association Studies-to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

  9. High Throughput T Epitope Mapping and Vaccine Development

    Giuseppina Li Pira

    2010-01-01

    Full Text Available Mapping of antigenic peptide sequences from proteins of relevant pathogens recognized by T helper (Th and by cytolytic T lymphocytes (CTL is crucial for vaccine development. In fact, mapping of T-cell epitopes provides useful information for the design of peptide-based vaccines and of peptide libraries to monitor specific cellular immunity in protected individuals, patients and vaccinees. Nevertheless, epitope mapping is a challenging task. In fact, large panels of overlapping peptides need to be tested with lymphocytes to identify the sequences that induce a T-cell response. Since numerous peptide panels from antigenic proteins are to be screened, lymphocytes available from human subjects are a limiting factor. To overcome this limitation, high throughput (HTP approaches based on miniaturization and automation of T-cell assays are needed. Here we consider the most recent applications of the HTP approach to T epitope mapping. The alternative or complementary use of in silico prediction and experimental epitope definition is discussed in the context of the recent literature. The currently used methods are described with special reference to the possibility of applying the HTP concept to make epitope mapping an easier procedure in terms of time, workload, reagents, cells and overall cost.

  10. High-throughput screening of chemicals as functional ...

    Identifying chemicals that provide a specific function within a product, yet have minimal impact on the human body or environment, is the goal of most formulation chemists and engineers practicing green chemistry. We present a methodology to identify potential chemical functional substitutes from large libraries of chemicals using machine learning based models. We collect and analyze publicly available information on the function of chemicals in consumer products or industrial processes to identify a suite of harmonized function categories suitable for modeling. We use structural and physicochemical descriptors for these chemicals to build 41 quantitative structure–use relationship (QSUR) models for harmonized function categories using random forest classification. We apply these models to screen a library of nearly 6400 chemicals with available structure information for potential functional substitutes. Using our Functional Use database (FUse), we could identify uses for 3121 chemicals; 4412 predicted functional uses had a probability of 80% or greater. We demonstrate the potential application of the models to high-throughput (HT) screening for “candidate alternatives” by merging the valid functional substitute classifications with hazard metrics developed from HT screening assays for bioactivity. A descriptor set could be obtained for 6356 Tox21 chemicals that have undergone a battery of HT in vitro bioactivity screening assays. By applying QSURs, we wer

  11. High-Throughput DNA sequencing of ancient wood.

    Wagner, Stefanie; Lagane, Frédéric; Seguin-Orlando, Andaine; Schubert, Mikkel; Leroy, Thibault; Guichoux, Erwan; Chancerel, Emilie; Bech-Hebelstrup, Inger; Bernard, Vincent; Billard, Cyrille; Billaud, Yves; Bolliger, Matthias; Croutsch, Christophe; Čufar, Katarina; Eynaud, Frédérique; Heussner, Karl Uwe; Köninger, Joachim; Langenegger, Fabien; Leroy, Frédéric; Lima, Christine; Martinelli, Nicoletta; Momber, Garry; Billamboz, André; Nelle, Oliver; Palomo, Antoni; Piqué, Raquel; Ramstein, Marianne; Schweichel, Roswitha; Stäuble, Harald; Tegel, Willy; Terradas, Xavier; Verdin, Florence; Plomion, Christophe; Kremer, Antoine; Orlando, Ludovic

    2018-03-01

    Reconstructing the colonization and demographic dynamics that gave rise to extant forests is essential to forecasts of forest responses to environmental changes. Classical approaches to map how population of trees changed through space and time largely rely on pollen distribution patterns, with only a limited number of studies exploiting DNA molecules preserved in wooden tree archaeological and subfossil remains. Here, we advance such analyses by applying high-throughput (HTS) DNA sequencing to wood archaeological and subfossil material for the first time, using a comprehensive sample of 167 European white oak waterlogged remains spanning a large temporal (from 550 to 9,800 years) and geographical range across Europe. The successful characterization of the endogenous DNA and exogenous microbial DNA of 140 (~83%) samples helped the identification of environmental conditions favouring long-term DNA preservation in wood remains, and started to unveil the first trends in the DNA decay process in wood material. Additionally, the maternally inherited chloroplast haplotypes of 21 samples from three periods of forest human-induced use (Neolithic, Bronze Age and Middle Ages) were found to be consistent with those of modern populations growing in the same geographic areas. Our work paves the way for further studies aiming at using ancient DNA preserved in wood to reconstruct the micro-evolutionary response of trees to climate change and human forest management. © 2018 John Wiley & Sons Ltd.

  12. On-chip polarimetry for high-throughput screening of nanoliter and smaller sample volumes

    Bachmann, Brian O. (Inventor); Bornhop, Darryl J. (Inventor); Dotson, Stephen (Inventor)

    2012-01-01

    A polarimetry technique for measuring optical activity that is particularly suited for high throughput screening employs a chip or substrate (22) having one or more microfluidic channels (26) formed therein. A polarized laser beam (14) is directed onto optically active samples that are disposed in the channels. The incident laser beam interacts with the optically active molecules in the sample, which slightly alter the polarization of the laser beam as it passes multiple times through the sample. Interference fringe patterns (28) are generated by the interaction of the laser beam with the sample and the channel walls. A photodetector (34) is positioned to receive the interference fringe patterns and generate an output signal that is input to a computer or other analyzer (38) for analyzing the signal and determining the rotation of plane polarized light by optically active material in the channel from polarization rotation calculations.

  13. High-Throughput Fabrication of Nanocomplexes Using 3D-Printed Micromixers

    Bohr, Adam; Boetker, Johan; Wang, Yingya

    2017-01-01

    3D printing allows a rapid and inexpensive manufacturing of custom made and prototype devices. Micromixers are used for rapid and controlled production of nanoparticles intended for therapeutic delivery. In this study, we demonstrate the fabrication of micromixers using computational design and 3D...... via bulk mixing. Moreover, each micromixer could process more than 2 liters per hour with unaffected performance and the setup could easily be scaled-up by aligning several micromixers in parallel. This demonstrates that 3D printing can be used to prepare disposable high-throughput micromixers...... printing, which enable a continuous and industrial scale production of nanocomplexes formed by electrostatic complexation, using the polymers poly(diallyldimethylammonium chloride) and poly(sodium 4-styrenesulfonate). Several parameters including polymer concentration, flow rate, and flow ratio were...

  14. Development and operation of a high-throughput accurate-wavelength lens-based spectrometer

    Bell, Ronald E., E-mail: rbell@pppl.gov [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States)

    2014-11-15

    A high-throughput spectrometer for the 400–820 nm wavelength range has been developed for charge exchange recombination spectroscopy or general spectroscopy. A large 2160 mm{sup −1} grating is matched with fast f/1.8 200 mm lenses, which provide stigmatic imaging. A precision optical encoder measures the grating angle with an accuracy ≤0.075 arc sec. A high quantum efficiency low-etaloning CCD detector allows operation at longer wavelengths. A patch panel allows input fibers to interface with interchangeable fiber holders that attach to a kinematic mount at the entrance slit. Computer-controlled hardware allows automated control of wavelength, timing, f-number, automated data collection, and wavelength calibration.

  15. Intersection of toxicogenomics and high throughput screening in the Tox21 program: an NIEHS perspective.

    Merrick, B Alex; Paules, Richard S; Tice, Raymond R

    Humans are exposed to thousands of chemicals with inadequate toxicological data. Advances in computational toxicology, robotic high throughput screening (HTS), and genome-wide expression have been integrated into the Tox21 program to better predict the toxicological effects of chemicals. Tox21 is a collaboration among US government agencies initiated in 2008 that aims to shift chemical hazard assessment from traditional animal toxicology to target-specific, mechanism-based, biological observations using in vitro assays and lower organism models. HTS uses biocomputational methods for probing thousands of chemicals in in vitro assays for gene-pathway response patterns predictive of adverse human health outcomes. In 1999, NIEHS began exploring the application of toxicogenomics to toxicology and recent advances in NextGen sequencing should greatly enhance the biological content obtained from HTS platforms. We foresee an intersection of new technologies in toxicogenomics and HTS as an innovative development in Tox21. Tox21 goals, priorities, progress, and challenges will be reviewed.

  16. Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping

    Al-Tamimi, Nadia Ali; Brien, Chris; Oakey, Helena; Berger, Bettina; Saade, Stephanie; Ho, Yung Shwen; Schmö ckel, Sandra M.; Tester, Mark A.; Negrã o, Só nia

    2016-01-01

    High-throughput phenotyping produces multiple measurements over time, which require new methods of analyses that are flexible in their quantification of plant growth and transpiration, yet are computationally economic. Here we develop such analyses and apply this to a rice population genotyped with a 700k SNP high-density array. Two rice diversity panels, indica and aus, containing a total of 553 genotypes, are phenotyped in waterlogged conditions. Using cubic smoothing splines to estimate plant growth and transpiration, we identify four time intervals that characterize the early responses of rice to salinity. Relative growth rate, transpiration rate and transpiration use efficiency (TUE) are analysed using a new association model that takes into account the interaction between treatment (control and salt) and genetic marker. This model allows the identification of previously undetected loci affecting TUE on chromosome 11, providing insights into the early responses of rice to salinity, in particular into the effects of salinity on plant growth and transpiration.

  17. Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping

    Al-Tamimi, Nadia Ali

    2016-11-17

    High-throughput phenotyping produces multiple measurements over time, which require new methods of analyses that are flexible in their quantification of plant growth and transpiration, yet are computationally economic. Here we develop such analyses and apply this to a rice population genotyped with a 700k SNP high-density array. Two rice diversity panels, indica and aus, containing a total of 553 genotypes, are phenotyped in waterlogged conditions. Using cubic smoothing splines to estimate plant growth and transpiration, we identify four time intervals that characterize the early responses of rice to salinity. Relative growth rate, transpiration rate and transpiration use efficiency (TUE) are analysed using a new association model that takes into account the interaction between treatment (control and salt) and genetic marker. This model allows the identification of previously undetected loci affecting TUE on chromosome 11, providing insights into the early responses of rice to salinity, in particular into the effects of salinity on plant growth and transpiration.

  18. Data reduction for a high-throughput neutron activation analysis system

    Bowman, W.W.

    1979-01-01

    To analyze samples collected as part of a geochemical survey for the National Uranium Resource Evaluation program, Savannah River Laboratory has installed a high-throughput neutron activation analysis system. As part of that system, computer programs have been developed to reduce raw data to elemental concentrations in two steps. Program RAGS reduces gamma-ray spectra to lists of photopeak energies, peak areas, and statistical errors. Program RICHES determines the elemental concentrations from photopeak and delayed-neutron data, detector efficiencies, analysis parameters (neutron flux and activation, decay, and counting times), and spectrometric and cross-section data from libraries. Both programs have been streamlined for on-line operation with a minicomputer, each requiring approx. 64 kbytes of core. 3 tables

  19. Use of a Fluorometric Imaging Plate Reader in high-throughput screening

    Groebe, Duncan R.; Gopalakrishnan, Sujatha; Hahn, Holly; Warrior, Usha; Traphagen, Linda; Burns, David J.

    1999-04-01

    High-throughput screening (HTS) efforts at Abbott Laboratories have been greatly facilitated by the use of a Fluorometric Imaging Plate Reader. The FLIPR consists of an incubated cabinet with integrated 96-channel pipettor and fluorometer. An argon laser is used to excite fluorophores in a 96-well microtiter plate and the emitted fluorometer. An argon laser is used to excite fluorophores in a 96-well microtiter plate and the emitted fluorescence is imaged by a cooled CCD camera. The image data is downloaded from the camera and processed to average the signal form each well of the microtiter pate for each time point. The data is presented in real time on the computer screen, facilitating interpretation and trouble-shooting. In addition to fluorescence, the camera can also detect luminescence form firefly luciferase.

  20. Insight into dynamic genome imaging: Canonical framework identification and high-throughput analysis.

    Ronquist, Scott; Meixner, Walter; Rajapakse, Indika; Snyder, John

    2017-07-01

    The human genome is dynamic in structure, complicating researcher's attempts at fully understanding it. Time series "Fluorescent in situ Hybridization" (FISH) imaging has increased our ability to observe genome structure, but due to cell type and experimental variability this data is often noisy and difficult to analyze. Furthermore, computational analysis techniques are needed for homolog discrimination and canonical framework detection, in the case of time-series images. In this paper we introduce novel ideas for nucleus imaging analysis, present findings extracted using dynamic genome imaging, and propose an objective algorithm for high-throughput, time-series FISH imaging. While a canonical framework could not be detected beyond statistical significance in the analyzed dataset, a mathematical framework for detection has been outlined with extension to 3D image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. HDAT: web-based high-throughput screening data analysis tools

    Liu, Rong; Hassan, Taimur; Rallo, Robert; Cohen, Yoram

    2013-01-01

    The increasing utilization of high-throughput screening (HTS) in toxicity studies of engineered nano-materials (ENMs) requires tools for rapid and reliable processing and analyses of large HTS datasets. In order to meet this need, a web-based platform for HTS data analyses tools (HDAT) was developed that provides statistical methods suitable for ENM toxicity data. As a publicly available computational nanoinformatics infrastructure, HDAT provides different plate normalization methods, various HTS summarization statistics, self-organizing map (SOM)-based clustering analysis, and visualization of raw and processed data using both heat map and SOM. HDAT has been successfully used in a number of HTS studies of ENM toxicity, thereby enabling analysis of toxicity mechanisms and development of structure–activity relationships for ENM toxicity. The online approach afforded by HDAT should encourage standardization of and future advances in HTS as well as facilitate convenient inter-laboratory comparisons of HTS datasets. (paper)

  2. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer's-Associated Aβ Oligomers.

    Kyle C Wilcox

    Full Text Available Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs. AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs. This method gives a soluble membrane protein library (SMPL--a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer's model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can

  3. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer’s-Associated Aβ Oligomers

    Wilcox, Kyle C.; Marunde, Matthew R.; Das, Aditi; Velasco, Pauline T.; Kuhns, Benjamin D.; Marty, Michael T.; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G.; Klein, William L.

    2015-01-01

    Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer’s dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs). This method gives a soluble membrane protein library (SMPL)—a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer’s model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can facilitate drug

  4. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer's-Associated Aβ Oligomers.

    Wilcox, Kyle C; Marunde, Matthew R; Das, Aditi; Velasco, Pauline T; Kuhns, Benjamin D; Marty, Michael T; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G; Klein, William L

    2015-01-01

    Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs). This method gives a soluble membrane protein library (SMPL)--a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer's model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can facilitate drug discovery

  5. Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

    Kristiansen, Troels Zakarias; Harsha, H C; Grønborg, Mads

    2008-01-01

    Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based...

  6. In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.

    Sun, Shangpeng; Li, Changying; Paterson, Andrew H; Jiang, Yu; Xu, Rui; Robertson, Jon S; Snider, John L; Chee, Peng W

    2018-01-01

    Plant breeding programs and a wide range of plant science applications would greatly benefit from the development of in-field high throughput phenotyping technologies. In this study, a terrestrial LiDAR-based high throughput phenotyping system was developed. A 2D LiDAR was applied to scan plants from overhead in the field, and an RTK-GPS was used to provide spatial coordinates. Precise 3D models of scanned plants were reconstructed based on the LiDAR and RTK-GPS data. The ground plane of the 3D model was separated by RANSAC algorithm and a Euclidean clustering algorithm was applied to remove noise generated by weeds. After that, clean 3D surface models of cotton plants were obtained, from which three plot-level morphologic traits including canopy height, projected canopy area, and plant volume were derived. Canopy height ranging from 85th percentile to the maximum height were computed based on the histogram of the z coordinate for all measured points; projected canopy area was derived by projecting all points on a ground plane; and a Trapezoidal rule based algorithm was proposed to estimate plant volume. Results of validation experiments showed good agreement between LiDAR measurements and manual measurements for maximum canopy height, projected canopy area, and plant volume, with R 2 -values of 0.97, 0.97, and 0.98, respectively. The developed system was used to scan the whole field repeatedly over the period from 43 to 109 days after planting. Growth trends and growth rate curves for all three derived morphologic traits were established over the monitoring period for each cultivar. Overall, four different cultivars showed similar growth trends and growth rate patterns. Each cultivar continued to grow until ~88 days after planting, and from then on varied little. However, the actual values were cultivar specific. Correlation analysis between morphologic traits and final yield was conducted over the monitoring period. When considering each cultivar individually

  7. Assessment of network perturbation amplitudes by applying high-throughput data to causal biological networks

    Martin Florian

    2012-05-01

    Full Text Available Abstract Background High-throughput measurement technologies produce data sets that have the potential to elucidate the biological impact of disease, drug treatment, and environmental agents on humans. The scientific community faces an ongoing challenge in the analysis of these rich data sources to more accurately characterize biological processes that have been perturbed at the mechanistic level. Here, a new approach is built on previous methodologies in which high-throughput data was interpreted using prior biological knowledge of cause and effect relationships. These relationships are structured into network models that describe specific biological processes, such as inflammatory signaling or cell cycle progression. This enables quantitative assessment of network perturbation in response to a given stimulus. Results Four complementary methods were devised to quantify treatment-induced activity changes in processes described by network models. In addition, companion statistics were developed to qualify significance and specificity of the results. This approach is called Network Perturbation Amplitude (NPA scoring because the amplitudes of treatment-induced perturbations are computed for biological network models. The NPA methods were tested on two transcriptomic data sets: normal human bronchial epithelial (NHBE cells treated with the pro-inflammatory signaling mediator TNFα, and HCT116 colon cancer cells treated with the CDK cell cycle inhibitor R547. Each data set was scored against network models representing different aspects of inflammatory signaling and cell cycle progression, and these scores were compared with independent measures of pathway activity in NHBE cells to verify the approach. The NPA scoring method successfully quantified the amplitude of TNFα-induced perturbation for each network model when compared against NF-κB nuclear localization and cell number. In addition, the degree and specificity to which CDK

  8. Semen proteomics and male infertility.

    Jodar, Meritxell; Soler-Ventura, Ada; Oliva, Rafael

    2017-06-06

    Semen is a complex body fluid containing an admixture of spermatozoa suspended in secretions from the testes and epididymis which are mixed at the time of ejaculation with secretions from other accessory sex glands such as the prostate and seminal vesicles. High-throughput technologies have revealed that, contrary to the idea that sperm cells are simply a silent delivery vehicle of the male genome to the oocyte, the sperm cells in fact provide both a specific epigenetically marked DNA together with a complex population of proteins and RNAs crucial for embryogenesis. Similarly, -omic technologies have also enlightened that seminal fluid seems to play a much greater role than simply being a medium to carry the spermatozoa through the female reproductive tract. In the present review, we briefly overview the sperm cell biology, consider the key issues in sperm and seminal fluid sample preparation for high-throughput proteomic studies, describe the current state of the sperm and seminal fluid proteomes generated by high-throughput proteomic technologies and provide new insights into the potential communication between sperm and seminal fluid. In addition, comparative proteomic studies open a window to explore the potential pathogenic mechanisms of infertility and the discovery of potential biomarkers with clinical significance. The review updates the numerous proteomics studies performed on semen, including spermatozoa and seminal fluid. In addition, an integrative analysis of the testes, sperm and seminal fluid proteomes is also included providing insights into the molecular mechanisms that regulate the generation, maturation and transit of spermatozoa. Furthermore, the compilation of several differential proteomic studies focused on male infertility reveals potential pathways disturbed in specific subtypes of male infertility and points out towards future research directions in the field. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Standardized Method for High-throughput Sterilization of Arabidopsis Seeds.

    Lindsey, Benson E; Rivero, Luz; Calhoun, Chistopher S; Grotewold, Erich; Brkljacic, Jelena

    2017-10-17

    Arabidopsis thaliana (Arabidopsis) seedlings often need to be grown on sterile media. This requires prior seed sterilization to prevent the growth of microbial contaminants present on the seed surface. Currently, Arabidopsis seeds are sterilized using two distinct sterilization techniques in conditions that differ slightly between labs and have not been standardized, often resulting in only partially effective sterilization or in excessive seed mortality. Most of these methods are also not easily scalable to a large number of seed lines of diverse genotypes. As technologies for high-throughput analysis of Arabidopsis continue to proliferate, standardized techniques for sterilizing large numbers of seeds of different genotypes are becoming essential for conducting these types of experiments. The response of a number of Arabidopsis lines to two different sterilization techniques was evaluated based on seed germination rate and the level of seed contamination with microbes and other pathogens. The treatments included different concentrations of sterilizing agents and times of exposure, combined to determine optimal conditions for Arabidopsis seed sterilization. Optimized protocols have been developed for two different sterilization methods: bleach (liquid-phase) and chlorine (Cl2) gas (vapor-phase), both resulting in high seed germination rates and minimal microbial contamination. The utility of these protocols was illustrated through the testing of both wild type and mutant seeds with a range of germination potentials. Our results show that seeds can be effectively sterilized using either method without excessive seed mortality, although detrimental effects of sterilization were observed for seeds with lower than optimal germination potential. In addition, an equation was developed to enable researchers to apply the standardized chlorine gas sterilization conditions to airtight containers of different sizes. The protocols described here allow easy, efficient, and

  10. Towards high throughput screening of electrochemical stability of battery electrolytes

    Borodin, Oleg; Olguin, Marco; Spear, Carrie E; Leiter, Kenneth W; Knap, Jaroslaw

    2015-01-01

    High throughput screening of solvents and additives with potential applications in lithium batteries is reported. The initial test set is limited to carbonate and phosphate-based compounds and focused on their electrochemical properties. Solvent stability towards first and second reduction and oxidation is reported from density functional theory (DFT) calculations performed on isolated solvents surrounded by implicit solvent. The reorganization energy is estimated from the difference between vertical and adiabatic redox energies and found to be especially important for the accurate prediction of reduction stability. A majority of tested compounds had the second reduction potential higher than the first reduction potential indicating that the second reduction reaction might play an important role in the passivation layer formation. Similarly, the second oxidation potential was smaller for a significant subset of tested molecules than the first oxidation potential. A number of potential sources of errors introduced during screening of the electrolyte electrochemical properties were examined. The formation of lithium fluoride during reduction of semifluorinated solvents such as fluoroethylene carbonate and the H-transfer during oxidation of solvents were found to shift the electrochemical potential by 1.5–2 V and could shrink the electrochemical stability window by as much as 3.5 V when such reactions are included in the screening procedure. The initial oxidation reaction of ethylene carbonate and dimethyl carbonate at the surface of the completely de-lithiated LiNi 0.5 Mn 1.5 O 4 high voltage spinel cathode was examined using DFT. Depending on the molecular orientation at the cathode surface, a carbonate molecule either exhibited deprotonation or was found bound to the transition metal via its carbonyl oxygen. (paper)

  11. Towards Chip Scale Liquid Chromatography and High Throughput Immunosensing

    Ni, Jing [Iowa State Univ., Ames, IA (United States)

    2000-09-21

    This work describes several research projects aimed towards developing new instruments and novel methods for high throughput chemical and biological analysis. Approaches are taken in two directions. The first direction takes advantage of well-established semiconductor fabrication techniques and applies them to miniaturize instruments that are workhorses in analytical laboratories. Specifically, the first part of this work focused on the development of micropumps and microvalves for controlled fluid delivery. The mechanism of these micropumps and microvalves relies on the electrochemically-induced surface tension change at a mercury/electrolyte interface. A miniaturized flow injection analysis device was integrated and flow injection analyses were demonstrated. In the second part of this work, microfluidic chips were also designed, fabricated, and tested. Separations of two fluorescent dyes were demonstrated in microfabricated channels, based on an open-tubular liquid chromatography (OT LC) or an electrochemically-modulated liquid chromatography (EMLC) format. A reduction in instrument size can potentially increase analysis speed, and allow exceedingly small amounts of sample to be analyzed under diverse separation conditions. The second direction explores the surface enhanced Raman spectroscopy (SERS) as a signal transduction method for immunoassay analysis. It takes advantage of the improved detection sensitivity as a result of surface enhancement on colloidal gold, the narrow width of Raman band, and the stability of Raman scattering signals to distinguish several different species simultaneously without exploiting spatially-separated addresses on a biochip. By labeling gold nanoparticles with different Raman reporters in conjunction with different detection antibodies, a simultaneous detection of a dual-analyte immunoassay was demonstrated. Using this scheme for quantitative analysis was also studied and preliminary dose-response curves from an immunoassay of a

  12. A bioimage informatics platform for high-throughput embryo phenotyping.

    Brown, James M; Horner, Neil R; Lawson, Thomas N; Fiegel, Tanja; Greenaway, Simon; Morgan, Hugh; Ring, Natalie; Santos, Luis; Sneddon, Duncan; Teboul, Lydia; Vibert, Jennifer; Yaikhom, Gagarine; Westerberg, Henrik; Mallon, Ann-Marie

    2018-01-01

    High-throughput phenotyping is a cornerstone of numerous functional genomics projects. In recent years, imaging screens have become increasingly important in understanding gene-phenotype relationships in studies of cells, tissues and whole organisms. Three-dimensional (3D) imaging has risen to prominence in the field of developmental biology for its ability to capture whole embryo morphology and gene expression, as exemplified by the International Mouse Phenotyping Consortium (IMPC). Large volumes of image data are being acquired by multiple institutions around the world that encompass a range of modalities, proprietary software and metadata. To facilitate robust downstream analysis, images and metadata must be standardized to account for these differences. As an open scientific enterprise, making the data readily accessible is essential so that members of biomedical and clinical research communities can study the images for themselves without the need for highly specialized software or technical expertise. In this article, we present a platform of software tools that facilitate the upload, analysis and dissemination of 3D images for the IMPC. Over 750 reconstructions from 80 embryonic lethal and subviable lines have been captured to date, all of which are openly accessible at mousephenotype.org. Although designed for the IMPC, all software is available under an open-source licence for others to use and develop further. Ongoing developments aim to increase throughput and improve the analysis and dissemination of image data. Furthermore, we aim to ensure that images are searchable so that users can locate relevant images associated with genes, phenotypes or human diseases of interest. © The Author 2016. Published by Oxford University Press.

  13. High-Throughput Next-Generation Sequencing of Polioviruses

    Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

    2016-01-01

    ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929

  14. Maximizing gain in high-throughput screening using conformal prediction.

    Svensson, Fredrik; Afzal, Avid M; Norinder, Ulf; Bender, Andreas

    2018-02-21

    Iterative screening has emerged as a promising approach to increase the efficiency of screening campaigns compared to traditional high throughput approaches. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models, resulting in more efficient screening. One way to evaluate screening is to consider the cost of screening compared to the gain associated with finding an active compound. In this work, we introduce a conformal predictor coupled with a gain-cost function with the aim to maximise gain in iterative screening. Using this setup we were able to show that by evaluating the predictions on the training data, very accurate predictions on what settings will produce the highest gain on the test data can be made. We evaluate the approach on 12 bioactivity datasets from PubChem training the models using 20% of the data. Depending on the settings of the gain-cost function, the settings generating the maximum gain were accurately identified in 8-10 out of the 12 datasets. Broadly, our approach can predict what strategy generates the highest gain based on the results of the cost-gain evaluation: to screen the compounds predicted to be active, to screen all the remaining data, or not to screen any additional compounds. When the algorithm indicates that the predicted active compounds should be screened, our approach also indicates what confidence level to apply in order to maximize gain. Hence, our approach facilitates decision-making and allocation of the resources where they deliver the most value by indicating in advance the likely outcome of a screening campaign.

  15. Best Performers Announced for the NCI-CPTAC DREAM Proteogenomics Computational Challenge | Office of Cancer Clinical Proteomics Research

    The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) is pleased to announce that teams led by Jaewoo Kang (Korea University), and Yuanfang Guan with Hongyang Li (University of Michigan) as the best performers of the NCI-CPTAC DREAM Proteogenomics Computational Challenge. Over 500 participants from 20 countries registered for the Challenge, which offered $25,000 in cash awards contributed by the NVIDIA Foundation through its Compute the Cure initiative.

  16. High-throughput sequencing of black pepper root transcriptome

    2012-01-01

    Background Black pepper (Piper nigrum L.) is one of the most popular spices in the world. It is used in cooking and the preservation of food and even has medicinal properties. Losses in production from disease are a major limitation in the culture of this crop. The major diseases are root rot and foot rot, which are results of root infection by Fusarium solani and Phytophtora capsici, respectively. Understanding the molecular interaction between the pathogens and the host’s root region is important for obtaining resistant cultivars by biotechnological breeding. Genetic and molecular data for this species, though, are limited. In this paper, RNA-Seq technology has been employed, for the first time, to describe the root transcriptome of black pepper. Results The root transcriptome of black pepper was sequenced by the NGS SOLiD platform and assembled using the multiple-k method. Blast2Go and orthoMCL methods were used to annotate 10338 unigenes. The 4472 predicted proteins showed about 52% homology with the Arabidopsis proteome. Two root proteomes identified 615 proteins, which seem to define the plant’s root pattern. Simple-sequence repeats were identified that may be useful in studies of genetic diversity and may have applications in biotechnology and ecology. Conclusions This dataset of 10338 unigenes is crucially important for the biotechnological breeding of black pepper and the ecogenomics of the Magnoliids, a major group of basal angiosperms. PMID:22984782

  17. High-throughput sequencing of black pepper root transcriptome

    Gordo Sheila MC

    2012-09-01

    Full Text Available Abstract Background Black pepper (Piper nigrum L. is one of the most popular spices in the world. It is used in cooking and the preservation of food and even has medicinal properties. Losses in production from disease are a major limitation in the culture of this crop. The major diseases are root rot and foot rot, which are results of root infection by Fusarium solani and Phytophtora capsici, respectively. Understanding the molecular interaction between the pathogens and the host’s root region is important for obtaining resistant cultivars by biotechnological breeding. Genetic and molecular data for this species, though, are limited. In this paper, RNA-Seq technology has been employed, for the first time, to describe the root transcriptome of black pepper. Results The root transcriptome of black pepper was sequenced by the NGS SOLiD platform and assembled using the multiple-k method. Blast2Go and orthoMCL methods were used to annotate 10338 unigenes. The 4472 predicted proteins showed about 52% homology with the Arabidopsis proteome. Two root proteomes identified 615 proteins, which seem to define the plant’s root pattern. Simple-sequence repeats were identified that may be useful in studies of genetic diversity and may have applications in biotechnology and ecology. Conclusions This dataset of 10338 unigenes is crucially important for the biotechnological breeding of black pepper and the ecogenomics of the Magnoliids, a major group of basal angiosperms.

  18. High throughput, low set-up time reconfigurable linear feedback shift registers

    Nas, R.J.M.; Berkel, van C.H.

    2010-01-01

    This paper presents a hardware design for a scalable, high throughput, configurable LFSR. High throughput is achieved by producing L consecutive outputs per clock cycle with a clock cycle period that, for practical cases, increases only logarithmically with the block size L and the length of the

  19. High throughput label-free platform for statistical bio-molecular sensing

    Bosco, Filippo; Hwu, En-Te; Chen, Ching-Hsiu

    2011-01-01

    Sensors are crucial in many daily operations including security, environmental control, human diagnostics and patient monitoring. Screening and online monitoring require reliable and high-throughput sensing. We report on the demonstration of a high-throughput label-free sensor platform utilizing...

  20. DockoMatic: automated peptide analog creation for high throughput virtual screening.

    Jacob, Reed B; Bullock, Casey W; Andersen, Tim; McDougal, Owen M

    2011-10-01

    The purpose of this manuscript is threefold: (1) to describe an update to DockoMatic that allows the user to generate cyclic peptide analog structure files based on protein database (pdb) files, (2) to test the accuracy of the peptide analog structure generation utility, and (3) to evaluate the high throughput capacity of DockoMatic. The DockoMatic graphical user interface interfaces with the software program Treepack to create user defined peptide analogs. To validate this approach, DockoMatic produced cyclic peptide analogs were tested for three-dimensional structure consistency and binding affinity against four experimentally determined peptide structure files available in the Research Collaboratory for Structural Bioinformatics database. The peptides used to evaluate this new functionality were alpha-conotoxins ImI, PnIA, and their published analogs. Peptide analogs were generated by DockoMatic and tested for their ability to bind to X-ray crystal structure models of the acetylcholine binding protein originating from Aplysia californica. The results, consisting of more than 300 simulations, demonstrate that DockoMatic predicts the binding energy of peptide structures to within 3.5 kcal mol(-1), and the orientation of bound ligand compares to within 1.8 Å root mean square deviation for ligand structures as compared to experimental data. Evaluation of high throughput virtual screening capacity demonstrated that Dockomatic can collect, evaluate, and summarize the output of 10,000 AutoDock jobs in less than 2 hours of computational time, while 100,000 jobs requires approximately 15 hours and 1,000,000 jobs is estimated to take up to a week. Copyright © 2011 Wiley Periodicals, Inc.

  1. Moving Toward Integrating Gene Expression Profiling into High-throughput Testing:A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

    Microarray profiling of chemical-induced effects is being increasingly used in medium and high-throughput formats. In this study, we describe computational methods to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), ...

  2. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

    Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

    2017-12-21

    In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

  3. Advanced high throughput MOX fuel fabrication technology and sustainable development

    Krellmann, Juergen

    2005-01-01

    The MELOX plant in the south of France together with the La Hague reprocessing plant, are part of the two industrial facilities in charge of closing the nuclear fuel cycle in France. Started up in 1995, MELOX has since accumulated a solid know-how in recycling plutonium recovered from spent uranium fuel into MOX: a fuel blend comprised of both uranium and plutonium oxides. Converting recovered Pu into a proliferation-resistant material that can readily be used to power a civil nuclear reactor, MOX fabrication offers a sustainable solution to safely take advantage of the plutonium's high energy content. Being the first large-capacity industrial facility dedicated to MOX fuel fabrication, MELOX distinguishes itself from the first generation MOX plants with high capacity (around 200 tHM versus around 40 tHM) and several unique operational features designed to improve productivity, reliability and flexibility while maintaining high safety standards. Providing an exemplary reference for high throughput MOX fabrication with 1,000 tHM produced since start-up, the unique process and technologies implemented at MELOX are currently inspiring other MOX plant construction projects (in Japan with the J-MOX plant, in the US and in Russia as part of the weapon-grade plutonium inventory reduction). Spurred by the growing international demand, MELOX has embarked upon an ambitious production development and diversification plan. Starting from an annual level of 100 tons of heavy metal (tHM), MELOX demonstrated production capacity is continuously increasing: MELOX is now aiming for a minimum of 140 tHM by the end of 2005, with the ultimate ambition of reaching the full capacity of the plant (around 200 tHM) in the near future. With regards to its activity, MELOX also remains deeply committed to sustainable development in a consolidated involvement within AREVA group. The French minister of Industry, on August 26th 2005, acknowledged the benefits of MOX fuel production at MELOX: 'In

  4. High throughput comet assay to study genotoxicity of nanomaterials

    Naouale El Yamani

    2015-06-01

    Full Text Available The unique physicochemical properties of engineered nanomaterials (NMs have accelerated their use in diverse industrial and domestic products. Although their presence in consumer products represents a major concern for public health safety, their potential impact on human health is poorly understood. There is therefore an urgent need to clarify the toxic effects of NMs and to elucidate the mechanisms involved. In view of the large number of NMs currently being used, high throughput (HTP screening technologies are clearly needed for efficient assessment of toxicity. The comet assay is the most used method in nanogenotoxicity studies and has great potential for increasing throughput as it is fast, versatile and robust; simple technical modifications of the assay make it possible to test many compounds (NMs in a single experiment. The standard gel of 70-100 μL contains thousands of cells, of which only a tiny fraction are actually scored. Reducing the gel to a volume of 5 μL, with just a few hundred cells, allows twelve gels to be set on a standard slide, or 96 as a standard 8x12 array. For the 12 gel format, standard slides precoated with agarose are placed on a metal template and gels are set on the positions marked on the template. The HTP comet assay, incorporating digestion of DNA with formamidopyrimidine DNA glycosylase (FPG to detect oxidised purines, has recently been applied to study the potential induction of genotoxicity by NMs via reactive oxygen. In the NanoTEST project we investigated the genotoxic potential of several well-characterized metal and polymeric nanoparticles with the comet assay. All in vitro studies were harmonized; i.e. NMs were from the same batch, and identical dispersion protocols, exposure time, concentration range, culture conditions, and time-courses were used. As a kidney model, Cos-1 fibroblast-like kidney cells were treated with different concentrations of iron oxide NMs, and cells embedded in minigels (12

  5. Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

    Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

    2012-12-05

    For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

  6. The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

    Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

    2013-01-01

    We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

  7. High-throughput protein crystallization on the World Community Grid and the GPU

    Kotseruba, Yulia; Cumbaa, Christian A; Jurisica, Igor

    2012-01-01

    We have developed CPU and GPU versions of an automated image analysis and classification system for protein crystallization trial images from the Hauptman Woodward Institute's High-Throughput Screening lab. The analysis step computes 12,375 numerical features per image. Using these features, we have trained a classifier that distinguishes 11 different crystallization outcomes, recognizing 80% of all crystals, 94% of clear drops, 94% of precipitates. The computing requirements for this analysis system are large. The complete HWI archive of 120 million images is being processed by the donated CPU cycles on World Community Grid, with a GPU phase launching in early 2012. The main computational burden of the analysis is the measure of textural (GLCM) features within the image at multiple neighbourhoods, distances, and at multiple greyscale intensity resolutions. CPU runtime averages 4,092 seconds (single threaded) on an Intel Xeon, but only 65 seconds on an NVIDIA Tesla C2050. We report on the process of adapting the C++ code to OpenCL, optimized for multiple platforms.

  8. The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

    Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

    2013-01-01

    We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

  9. Analysis of high-throughput biological data using their rank values.

    Dembélé, Doulaye

    2018-01-01

    High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .

  10. GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

    Pronk, Sander [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Pall, Szilard [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Schulz, Roland [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Larsson, Per [Univ. of Virginia, Charlottesville, VA (United States); Bjelkmar, Par [Science for Life Lab., Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden); Apostolov, Rossen [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Shirts, Michael R. [Univ. of Virginia, Charlottesville, VA (United States); Smith, Jeremy C. [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kasson, Peter M. [Univ. of Virginia, Charlottesville, VA (United States); van der Spoel, David [Science for Life Lab., Stockholm (Sweden); Uppsala Univ., Uppsala (Sweden); Hess, Berk [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Lindahl, Erik [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden)

    2013-02-13

    In this study, molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. As a result, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

  11. Scaling up high throughput field phenotyping of corn and soy research plots using ground rovers

    Peshlov, Boyan; Nakarmi, Akash; Baldwin, Steven; Essner, Scott; French, Jasenka

    2017-05-01

    Crop improvement programs require large and meticulous selection processes that effectively and accurately collect and analyze data to generate quality plant products as efficiently as possible, develop superior cropping and/or crop improvement methods. Typically, data collection for such testing is performed by field teams using hand-held instruments or manually-controlled devices. Although steps are taken to reduce error, the data collected in such manner can be unreliable due to human error and fatigue, which reduces the ability to make accurate selection decisions. Monsanto engineering teams have developed a high-clearance mobile platform (Rover) as a step towards high throughput and high accuracy phenotyping at an industrial scale. The rovers are equipped with GPS navigation, multiple cameras and sensors and on-board computers to acquire data and compute plant vigor metrics per plot. The supporting IT systems enable automatic path planning, plot identification, image and point cloud data QA/QC and near real-time analysis where results are streamed to enterprise databases for additional statistical analysis and product advancement decisions. Since the rover program was launched in North America in 2013, the number of research plots we can analyze in a growing season has expanded dramatically. This work describes some of the successes and challenges in scaling up of the rover platform for automated phenotyping to enable science at scale.

  12. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit.

    Pronk, Sander; Páll, Szilárd; Schulz, Roland; Larsson, Per; Bjelkmar, Pär; Apostolov, Rossen; Shirts, Michael R; Smith, Jeremy C; Kasson, Peter M; van der Spoel, David; Hess, Berk; Lindahl, Erik

    2013-04-01

    Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. GROMACS is an open source and free software available from http://www.gromacs.org. Supplementary data are available at Bioinformatics online.

  13. Centroid based clustering of high throughput sequencing reads based on n-mer counts.

    Solovyov, Alexander; Lipkin, W Ian

    2013-09-08

    Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read.

  14. The Perseus computational platform for comprehensive analysis of (prote)omics data.

    Tyanova, Stefka; Temu, Tikira; Sinitcyn, Pavel; Carlson, Arthur; Hein, Marco Y; Geiger, Tamar; Mann, Matthias; Cox, Jürgen

    2016-09-01

    A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

  15. Manual evaluation of tissue microarrays in a high-throughput research project: The contribution of Indian surgical pathology to the Human Protein Atlas (HPA) project.

    Navani, Sanjay

    2016-04-01

    The Human Protein Atlas (HPA) program (www.proteinatlas.org) is an international program that has been set up to allow for a systematic exploration of the human proteome using antibody-based proteomics. This is accomplished by combining high-throughput generation of affinity-purified (mono-specific) antibodies with protein profiling in a multitude of tissues/cell types assembled in tissue microarrays. Twenty-six surgical pathologists over a seven-and-half year period have annotated and curated approximately sixteen million tissue images derived from immunostaining of normal and cancer tissues by approximately 23 000 antibodies. Web-based annotation software that allows for a basic and rapid evaluation of immunoreactivity in tissues has been utilized. Intensity, fraction of immunoreactive cells and subcellular localization were recorded for each given cell population. A text comment summarizing the characteristics for each antibody was added. The methods used and the challenges encountered for this exercise, the largest effort ever by a single group of surgical pathologists, are discussed. Manual annotation of digital images is an important tool that may be successfully utilized in high-throughput research projects. This is the first time an Indian private pathology laboratory has been associated with cutting-edge research internationally providing a classic example of developed and emerging nation collaboration. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. A method for high throughput bioelectrochemical research based on small scale microbial electrolysis cells

    Call, Douglas F.; Logan, Bruce E.

    2011-01-01

    There is great interest in studying exoelectrogenic microorganisms, but existing methods can require expensive electrochemical equipment and specialized reactors. We developed a simple system for conducting high throughput bioelectrochemical

  17. DRABAL: novel method to mine large high-throughput screening assays using Bayesian active learning

    Soufan, Othman; Ba Alawi, Wail; Afeef, Moataz A.; Essack, Magbubah; Kalnis, Panos; Bajic, Vladimir B.

    2016-01-01

    Mining high-throughput screening (HTS) assays is key for enhancing decisions in the area of drug repositioning and drug discovery. However, many challenges are encountered in the process of developing suitable and accurate methods

  18. EMBRYONIC VASCULAR DISRUPTION ADVERSE OUTCOMES: LINKING HIGH THROUGHPUT SIGNALING SIGNATURES WITH FUNCTIONAL CONSEQUENCES

    Embryonic vascular disruption is an important adverse outcome pathway (AOP) given the knowledge that chemical disruption of early cardiovascular system development leads to broad prenatal defects. High throughput screening (HTS) assays provide potential building blocks for AOP d...

  19. Applications of high-throughput sequencing to chromatin structure and function in mammals

    Dunham, Ian

    2009-01-01

    High-throughput DNA sequencing approaches have enabled direct interrogation of chromatin samples from mammalian cells. We are beginning to develop a genome-wide description of nuclear function during development, but further data collection, refinement, and integration are needed.

  20. Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection

    Ernstsen, Christina Lundgaard; Login, Frédéric H.; Jensen, Helene Halkjær

    2017-01-01

    Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacteria...

  1. Design and initial characterization of the SC-200 proteomics standard mixture.

    Bauman, Andrew; Higdon, Roger; Rapson, Sean; Loiue, Brenton; Hogan, Jason; Stacy, Robin; Napuli, Alberto; Guo, Wenjin; van Voorhis, Wesley; Roach, Jared; Lu, Vincent; Landorf, Elizabeth; Stewart, Elizabeth; Kolker, Natali; Collart, Frank; Myler, Peter; van Belle, Gerald; Kolker, Eugene

    2011-01-01

    High-throughput (HTP) proteomics studies generate large amounts of data. Interpretation of these data requires effective approaches to distinguish noise from biological signal, particularly as instrument and computational capacity increase and studies become more complex. Resolving this issue requires validated and reproducible methods and models, which in turn requires complex experimental and computational standards. The absence of appropriate standards and data sets for validating experimental and computational workflows hinders the development of HTP proteomics methods. Most protein standards are simple mixtures of proteins or peptides, or undercharacterized reference standards in which the identity and concentration of the constituent proteins is unknown. The Seattle Children's 200 (SC-200) proposed proteomics standard mixture is the next step toward developing realistic, fully characterized HTP proteomics standards. The SC-200 exhibits a unique modular design to extend its functionality, and consists of 200 proteins of known identities and molar concentrations from 6 microbial genomes, distributed into 10 molar concentration tiers spanning a 1,000-fold range. We describe the SC-200's design, potential uses, and initial characterization. We identified 84% of SC-200 proteins with an LTQ-Orbitrap and 65% with an LTQ-Velos (false discovery rate = 1% for both). There were obvious trends in success rate, sequence coverage, and spectral counts with protein concentration; however, protein identification, sequence coverage, and spectral counts vary greatly within concentration levels.

  2. A high throughput platform for understanding the influence of excipients on physical and chemical stability

    Raijada, Dhara; Cornett, Claus; Rantanen, Jukka

    2013-01-01

    The present study puts forward a miniaturized high-throughput platform to understand influence of excipient selection and processing on the stability of a given drug compound. Four model drugs (sodium naproxen, theophylline, amlodipine besylate and nitrofurantoin) and ten different excipients were...... for chemical degradation. The proposed high-throughput platform can be used during early drug development to simulate typical processing induced stress in a small scale and to understand possible phase transformation behaviour and influence of excipients on this....

  3. Application of high-throughput sequencing in understanding human oral microbiome related with health and disease

    Chen, Hui; Jiang, Wen

    2014-01-01

    The oral microbiome is one of most diversity habitat in the human body and they are closely related with oral health and disease. As the technique developing,, high throughput sequencing has become a popular approach applied for oral microbial analysis. Oral bacterial profiles have been studied to explore the relationship between microbial diversity and oral diseases such as caries and periodontal disease. This review describes the application of high-throughput sequencing for characterizati...

  4. High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models.

    Monaco, James P; Tomaszewski, John E; Feldman, Michael D; Hagemann, Ian; Moradi, Mehdi; Mousavi, Parvin; Boag, Alexander; Davidson, Chris; Abolmaesumi, Purang; Madabhushi, Anant

    2010-08-01

    In this paper we present a high-throughput system for detecting regions of carcinoma of the prostate (CaP) in HSs from radical prostatectomies (RPs) using probabilistic pairwise Markov models (PPMMs), a novel type of Markov random field (MRF). At diagnostic resolution a digitized HS can contain 80Kx70K pixels - far too many for current automated Gleason grading algorithms to process. However, grading can be separated into two distinct steps: (1) detecting cancerous regions and (2) then grading these regions. The detection step does not require diagnostic resolution and can be performed much more quickly. Thus, we introduce a CaP detection system capable of analyzing an entire digitized whole-mount HS (2x1.75cm(2)) in under three minutes (on a desktop computer) while achieving a CaP detection sensitivity and specificity of 0.87 and 0.90, respectively. We obtain this high-throughput by tailoring the system to analyze the HSs at low resolution (8microm per pixel). This motivates the following algorithm: (Step 1) glands are segmented, (Step 2) the segmented glands are classified as malignant or benign, and (Step 3) the malignant glands are consolidated into continuous regions. The classification of individual glands leverages two features: gland size and the tendency for proximate glands to share the same class. The latter feature describes a spatial dependency which we model using a Markov prior. Typically, Markov priors are expressed as the product of potential functions. Unfortunately, potential functions are mathematical abstractions, and constructing priors through their selection becomes an ad hoc procedure, resulting in simplistic models such as the Potts. Addressing this problem, we introduce PPMMs which formulate priors in terms of probability density functions, allowing the creation of more sophisticated models. To demonstrate the efficacy of our CaP detection system and assess the advantages of using a PPMM prior instead of the Potts, we alternately

  5. Novel strategy for protein exploration: high-throughput screening assisted with fuzzy neural network.

    Kato, Ryuji; Nakano, Hideo; Konishi, Hiroyuki; Kato, Katsuya; Koga, Yuchi; Yamane, Tsuneo; Kobayashi, Takeshi; Honda, Hiroyuki

    2005-08-19

    To engineer proteins with desirable characteristics from a naturally occurring protein, high-throughput screening (HTS) combined with directed evolutional approach is the essential technology. However, most HTS techniques are simple positive screenings. The information obtained from the positive candidates is used only as results but rarely as clues for understanding the structural rules, which may explain the protein activity. In here, we have attempted to establish a novel strategy for exploring functional proteins associated with computational analysis. As a model case, we explored lipases with inverted enantioselectivity for a substrate p-nitrophenyl 3-phenylbutyrate from the wild-type lipase of Burkhorderia cepacia KWI-56, which is originally selective for (S)-configuration of the substrate. Data from our previous work on (R)-enantioselective lipase screening were applied to fuzzy neural network (FNN), bioinformatic algorithm, to extract guidelines for screening and engineering processes to be followed. FNN has an advantageous feature of extracting hidden rules that lie between sequences of variants and their enzyme activity to gain high prediction accuracy. Without any prior knowledge, FNN predicted a rule indicating that "size at position L167," among four positions (L17, F119, L167, and L266) in the substrate binding core region, is the most influential factor for obtaining lipase with inverted (R)-enantioselectivity. Based on the guidelines obtained, newly engineered novel variants, which were not found in the actual screening, were experimentally proven to gain high (R)-enantioselectivity by engineering the size at position L167. We also designed and assayed two novel variants, namely FIGV (L17F, F119I, L167G, and L266V) and FFGI (L17F, L167G, and L266I), which were compatible with the guideline obtained from FNN analysis, and confirmed that these designed lipases could acquire high inverted enantioselectivity. The results have shown that with the aid of

  6. Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

    Mariusz Butkiewicz

    2013-01-01

    Full Text Available With the rapidly increasing availability of High-Throughput Screening (HTS data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR models are built using Artificial Neural Networks (ANNs, Support Vector Machines (SVMs, Decision Trees (DTs, and Kohonen networks (KNs. Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.

  7. High-Throughput Characterization of Porous Materials Using Graphics Processing Units

    Kim, Jihan; Martin, Richard L.; Rübel, Oliver; Haranczyk, Maciej; Smit, Berend

    2012-05-08

    We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CH$_{4}$ and CO$_{2}$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.

  8. PChopper: high throughput peptide prediction for MRM/SRM transition design

    Huang Jeffrey T-J

    2011-08-01

    Full Text Available Abstract Background The use of selective reaction monitoring (SRM based LC-MS/MS analysis for the quantification of phosphorylation stoichiometry has been rapidly increasing. At the same time, the number of sites that can be monitored in a single LC-MS/MS experiment is also increasing. The manual processes associated with running these experiments have highlighted the need for computational assistance to quickly design MRM/SRM candidates. Results PChopper has been developed to predict peptides that can be produced via enzymatic protein digest; this includes single enzyme digests, and combinations of enzymes. It also allows digests to be simulated in 'batch' mode and can combine information from these simulated digests to suggest the most appropriate enzyme(s to use. PChopper also allows users to define the characteristic of their target peptides, and can automatically identify phosphorylation sites that may be of interest. Two application end points are available for interacting with the system; the first is a web based graphical tool, and the second is an API endpoint based on HTTP REST. Conclusions Service oriented architecture was used to rapidly develop a system that can consume and expose several services. A graphical tool was built to provide an easy to follow workflow that allows scientists to quickly and easily identify the enzymes required to produce multiple peptides in parallel via enzymatic digests in a high throughput manner.

  9. High-throughput, Highly Sensitive Analyses of Bacterial Morphogenesis Using Ultra Performance Liquid Chromatography*

    Desmarais, Samantha M.; Tropini, Carolina; Miguel, Amanda; Cava, Felipe; Monds, Russell D.; de Pedro, Miguel A.; Huang, Kerwyn Casey

    2015-01-01

    The bacterial cell wall is a network of glycan strands cross-linked by short peptides (peptidoglycan); it is responsible for the mechanical integrity of the cell and shape determination. Liquid chromatography can be used to measure the abundance of the muropeptide subunits composing the cell wall. Characteristics such as the degree of cross-linking and average glycan strand length are known to vary across species. However, a systematic comparison among strains of a given species has yet to be undertaken, making it difficult to assess the origins of variability in peptidoglycan composition. We present a protocol for muropeptide analysis using ultra performance liquid chromatography (UPLC) and demonstrate that UPLC achieves resolution comparable with that of HPLC while requiring orders of magnitude less injection volume and a fraction of the elution time. We also developed a software platform to automate the identification and quantification of chromatographic peaks, which we demonstrate has improved accuracy relative to other software. This combined experimental and computational methodology revealed that peptidoglycan composition was approximately maintained across strains from three Gram-negative species despite taxonomical and morphological differences. Peptidoglycan composition and density were maintained after we systematically altered cell size in Escherichia coli using the antibiotic A22, indicating that cell shape is largely decoupled from the biochemistry of peptidoglycan synthesis. High-throughput, sensitive UPLC combined with our automated software for chromatographic analysis will accelerate the discovery of peptidoglycan composition and the molecular mechanisms of cell wall structure determination. PMID:26468288

  10. iCanPlot: visual exploration of high-throughput omics data using interactive Canvas plotting.

    Amit U Sinha

    Full Text Available Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis--which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression.

  11. High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

    Luo, Wei; Shabbir, Faizan; Gong, Chao; Gulec, Cagatay; Pigeon, Jeremy; Shaw, Jessica; Greenbaum, Alon; Tochitsky, Sergei; Joshi, Chandrashekhar [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Ozcan, Aydogan, E-mail: ozcan@ucla.edu [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Bioengineering Department, University of California, Los Angeles, California 90095 (United States); California NanoSystems Institute (CNSI), University of California, Los Angeles, California 90095 (United States)

    2015-04-13

    We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processing units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.

  12. Alignment of high-throughput sequencing data inside in-memory databases.

    Firnkorn, Daniel; Knaup-Gregori, Petra; Lorenzo Bermejo, Justo; Ganzinger, Matthias

    2014-01-01

    In times of high-throughput DNA sequencing techniques, performance-capable analysis of DNA sequences is of high importance. Computer supported DNA analysis is still an intensive time-consuming task. In this paper we explore the potential of a new In-Memory database technology by using SAP's High Performance Analytic Appliance (HANA). We focus on read alignment as one of the first steps in DNA sequence analysis. In particular, we examined the widely used Burrows-Wheeler Aligner (BWA) and implemented stored procedures in both, HANA and the free database system MySQL, to compare execution time and memory management. To ensure that the results are comparable, MySQL has been running in memory as well, utilizing its integrated memory engine for database table creation. We implemented stored procedures, containing exact and inexact searching of DNA reads within the reference genome GRCh37. Due to technical restrictions in SAP HANA concerning recursion, the inexact matching problem could not be implemented on this platform. Hence, performance analysis between HANA and MySQL was made by comparing the execution time of the exact search procedures. Here, HANA was approximately 27 times faster than MySQL which means, that there is a high potential within the new In-Memory concepts, leading to further developments of DNA analysis procedures in the future.

  13. Informatics and High Throughput Screening of Thermophysical Properties

    Hyers, Robert W.; Rogers, Jan R.

    2008-01-01

    The combination of computer-aided experiments with computational modeling enables a new class of powerful tools for materials research. A non-contact method for measuring density, thermal expansion, and creep of undercooled and high-temperature materials has been developed, using electrostatic levitation and optical diagnostics, including digital video. These experiments were designed to take advantage of the large volume of data (many gigabytes/experiment, terabytes/campaign) to gain additional information about the samples. For example, using sub-pixel interpolation to measure about 1000 vectors per image of the sample's surface allows the density of an axisymmetric sample to be determined to an accuracy of about 200 ppm (0.02%). A similar analysis applied to the surface shape of a rapidly rotating sample is combined with finite element modeling to determine the stress-dependence of creep in the sample in a single test. Details of the methods for both the computer-aided experiments and computational models will be discussed.

  14. Operational evaluation of high-throughput community-based mass prophylaxis using Just-in-time training.

    Spitzer, James D; Hupert, Nathaniel; Duckart, Jonathan; Xiong, Wei

    2007-01-01

    Community-based mass prophylaxis is a core public health operational competency, but staffing needs may overwhelm the local trained health workforce. Just-in-time (JIT) training of emergency staff and computer modeling of workforce requirements represent two complementary approaches to address this logistical problem. Multnomah County, Oregon, conducted a high-throughput point of dispensing (POD) exercise to test JIT training and computer modeling to validate POD staffing estimates. The POD had 84% non-health-care worker staff and processed 500 patients per hour. Post-exercise modeling replicated observed staff utilization levels and queue formation, including development and amelioration of a large medical evaluation queue caused by lengthy processing times and understaffing in the first half-hour of the exercise. The exercise confirmed the feasibility of using JIT training for high-throughput antibiotic dispensing clinics staffed largely by nonmedical professionals. Patient processing times varied over the course of the exercise, with important implications for both staff reallocation and future POD modeling efforts. Overall underutilization of staff revealed the opportunity for greater efficiencies and even higher future throughputs.

  15. Proteomics Core

    Federal Laboratory Consortium — Proteomics Core is the central resource for mass spectrometry based proteomics within the NHLBI. The Core staff help collaborators design proteomics experiments in a...

  16. MUSCLE: multiple sequence alignment with high accuracy and high throughput.

    Edgar, Robert C

    2004-01-01

    We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

  17. High Throughput Analysis of Breast Cancer Specimens on the Grid

    Yang, Lin; Chen, Wenjin; Meer, Peter; Salaru, Gratian; Feldman, Michael D.; Foran, David J.

    2007-01-01

    Breast cancer accounts for about 30% of all cancers and 15% of all cancer deaths in women in the United States. Advances in computer assisted diagnosis (CAD) holds promise for early detecting and staging disease progression. In this paper we introduce a Grid-enabled CAD to perform automatic analysis of imaged histopathology breast tissue specimens. More than 100,000 digitized samples (1200 × 1200 pixels) have already been processed on the Grid. We have analyzed results for 3744 breast tissue ...

  18. Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

    Antonio M Rezende

    Full Text Available The Trypanosomatids parasites Leishmania braziliensis, Leishmania major and Leishmania infantum are important human pathogens. Despite of years of study and genome availability, effective vaccine has not been developed yet, and the chemotherapy is highly toxic. Therefore, it is clear just interdisciplinary integrated studies will have success in trying to search new targets for developing of vaccines and drugs. An essential part of this rationale is related to protein-protein interaction network (PPI study which can provide a better understanding of complex protein interactions in biological system. Thus, we modeled PPIs for Trypanosomatids through computational methods using sequence comparison against public database of protein or domain interaction for interaction prediction (Interolog Mapping and developed a dedicated combined system score to address the predictions robustness. The confidence evaluation of network prediction approach was addressed using gold standard positive and negative datasets and the AUC value obtained was 0.94. As result, 39,420, 43,531 and 45,235 interactions were predicted for L. braziliensis, L. major and L. infantum respectively. For each predicted network the top 20 proteins were ranked by MCC topological index. In addition, information related with immunological potential, degree of protein sequence conservation among orthologs and degree of identity compared to proteins of potential parasite hosts was integrated. This information integration provides a better understanding and usefulness of the predicted networks that can be valuable to select new potential biological targets for drug and vaccine development. Network modularity which is a key when one is interested in destabilizing the PPIs for drug or vaccine purposes along with multiple alignments of the predicted PPIs were performed revealing patterns associated with protein turnover. In addition, around 50% of hypothetical protein present in the networks

  19. Discovery and annotation of small proteins using genomics, proteomics and computational approaches

    Yang, Xiaohan; Tschaplinski, Timothy J.; Hurst, Gregory B.; Jawdy, Sara; Abraham, Paul E.; Lankford, Patricia K.; Adams, Rachel M.; Shah, Manesh B.; Hettich, Robert L.; Lindquist, Erika; Kalluri, Udaya C.; Gunter, Lee E.; Pennacchio, Christa; Tuskan, Gerald A.

    2011-03-02

    Small proteins (10 200 amino acids aa in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained 2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts from the EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10 200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) codingpotential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene family clustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were new to the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.

  20. The amino acid's backup bone - storage solutions for proteomics facilities.

    Meckel, Hagen; Stephan, Christian; Bunse, Christian; Krafzik, Michael; Reher, Christopher; Kohl, Michael; Meyer, Helmut Erich; Eisenacher, Martin

    2014-01-01

    Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013. Published by Elsevier B.V.

  1. Applications of High-Throughput Nucleotide Sequencing (PhD)

    Waage, Johannes

    equally large demands in data handling, analysis and interpretation, perhaps defining the modern challenge of the computational biologist of the post-genomic era. The first part of this thesis consists of a general introduction to the history, common terms and challenges of next generation sequencing......-sequencing, a study of the effects on alternative RNA splicing of KO of the nonsense mediated RNA decay system in Mus, using digital gene expression and a custom-built exon-exon junction mapping pipeline is presented (article I). Evolved from this work, a Bioconductor package, spliceR, for classifying alternative...

  2. High-Throughput Sequencing Based Methods of RNA Structure Investigation

    Kielpinski, Lukasz Jan

    In this thesis we describe the development of four related methods for RNA structure probing that utilize massive parallel sequencing. Using them, we were able to gather structural data for multiple, long molecules simultaneously. First, we have established an easy to follow experimental...... and computational protocol for detecting the reverse transcription termination sites (RTTS-Seq). This protocol was subsequently applied to hydroxyl radical footprinting of three dimensional RNA structures to give a probing signal that correlates well with the RNA backbone solvent accessibility. Moreover, we applied...

  3. Freud: a software suite for high-throughput simulation analysis

    Harper, Eric; Spellings, Matthew; Anderson, Joshua; Glotzer, Sharon

    Computer simulation is an indispensable tool for the study of a wide variety of systems. As simulations scale to fill petascale and exascale supercomputing clusters, so too does the size of the data produced, as well as the difficulty in analyzing these data. We present Freud, an analysis software suite for efficient analysis of simulation data. Freud makes no assumptions about the system being analyzed, allowing for general analysis methods to be applied to nearly any type of simulation. Freud includes standard analysis methods such as the radial distribution function, as well as new methods including the potential of mean force and torque and local crystal environment analysis. Freud combines a Python interface with fast, parallel C + + analysis routines to run efficiently on laptops, workstations, and supercomputing clusters. Data analysis on clusters reduces data transfer requirements, a prohibitive cost for petascale computing. Used in conjunction with simulation software, Freud allows for smart simulations that adapt to the current state of the system, enabling the study of phenomena such as nucleation and growth, intelligent investigation of phases and phase transitions, and determination of effective pair potentials.

  4. High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

    Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

    2012-05-01

    Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

  5. High-throughput materials discovery and development: breakthroughs and challenges in the mapping of the materials genome

    Buongiorno Nardelli, Marco

    High-Throughput Quantum-Mechanics computation of materials properties by ab initio methods has become the foundation of an effective approach to materials design, discovery and characterization. This data driven approach to materials science currently presents the most promising path to the development of advanced technological materials that could solve or mitigate important social and economic challenges of the 21st century. In particular, the rapid proliferation of computational data on materials properties presents the possibility to complement and extend materials property databases where the experimental data is lacking and difficult to obtain. Enhanced repositories such as AFLOWLIB open novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds, metastable structures and correlations between various properties. The practical realization of these opportunities depends almost exclusively on the the design of efficient algorithms for electronic structure simulations of realistic material systems beyond the limitations of the current standard theories. In this talk, I will review recent progress in theoretical and computational tools, and in particular, discuss the development and validation of novel functionals within Density Functional Theory and of local basis representations for effective ab-initio tight-binding schemes. Marco Buongiorno Nardelli is a pioneer in the development of computational platforms for theory/data/applications integration rooted in his profound and extensive expertise in the design of electronic structure codes and in his vision for sustainable and innovative software development for high-performance materials simulations. His research activities range from the design and discovery of novel materials for 21st century applications in renewable energy, environment, nano-electronics and devices, the development of advanced electronic structure theories and high-throughput techniques in

  6. Automated high-throughput quantification of mitotic spindle positioning from DIC movies of Caenorhabditis embryos.

    David Cluet

    Full Text Available The mitotic spindle is a microtubule-based structure that elongates to accurately segregate chromosomes during anaphase. Its position within the cell also dictates the future cell cleavage plan, thereby determining daughter cell orientation within a tissue or cell fate adoption for polarized cells. Therefore, the mitotic spindle ensures at the same time proper cell division and developmental precision. Consequently, spindle dynamics is the matter of intensive research. Among the different cellular models that have been explored, the one-cell stage C. elegans embryo has been an essential and powerful system to dissect the molecular and biophysical basis of spindle elongation and positioning. Indeed, in this large and transparent cell, spindle poles (or centrosomes can be easily detected from simple DIC microscopy by human eyes. To perform quantitative and high-throughput analysis of spindle motion, we developed a computer program ACT for Automated-Centrosome-Tracking from DIC movies of C. elegans embryos. We therefore offer an alternative to the image acquisition and processing of transgenic lines expressing fluorescent spindle markers. Consequently, experiments on large sets of cells can be performed with a simple setup using inexpensive microscopes. Moreover, analysis of any mutant or wild-type backgrounds is accessible because laborious rounds of crosses with transgenic lines become unnecessary. Last, our program allows spindle detection in other nematode species, offering the same quality of DIC images but for which techniques of transgenesis are not accessible. Thus, our program also opens the way towards a quantitative evolutionary approach of spindle dynamics. Overall, our computer program is a unique macro for the image- and movie-processing platform ImageJ. It is user-friendly and freely available under an open-source licence. ACT allows batch-wise analysis of large sets of mitosis events. Within 2 minutes, a single movie is processed

  7. Using high throughput experimental data and in silico models to discover alternatives to toxic chromate corrosion inhibitors

    Winkler, D.A.; Breedon, M.; White, P.; Hughes, A.E.; Sapper, E.D.; Cole, I.

    2016-01-01

    Highlights: • We screened a large library of organic compounds as replacements for toxic chromates. • High throughput automated corrosion testing was used to assess inhibitor performance. • Robust, predictive machine learning models of corrosion inhibition were developed. • Models indicated molecular features contributing to performance of organic inhibitors. • We also showed that quantum chemistry descriptors do not correlate with performance. - Abstract: Restrictions on the use of toxic chromate-based corrosion inhibitors have created important issues for the aerospace and other industries. Benign alternatives that offer similar or superior performance are needed. We used high throughput experiments to assess 100 small organic molecules as potential inhibitors of corrosion in aerospace aluminium alloys AA2024 and AA7075. We generated robust, predictive, quantitative computational models of inhibitor efficiency at two pH values using these data. The models identified molecular features of inhibitor molecules that had the greatest impact on corrosion inhibition. Models can be used to discover better corrosion inhibitors by screening libraries of organic compounds for candidates with high corrosion inhibition.

  8. High-throughput screening of effective siRNAs using luciferase-linked chimeric mRNA.

    Shen Pang

    Full Text Available The use of siRNAs to knock down gene expression can potentially be an approach to treat various diseases. To avoid siRNA toxicity the less transcriptionally active H1 pol III promoter, rather than the U6 promoter, was proposed for siRNA expression. To identify highly efficacious siRNA sequences, extensive screening is required, since current computer programs may not render ideal results. Here, we used CCR5 gene silencing as a model to investigate a rapid and efficient screening approach. We constructed a chimeric luciferase-CCR5 gene for high-throughput screening of siRNA libraries. After screening approximately 900 shRNA clones, 12 siRNA sequences were identified. Sequence analysis demonstrated that most (11 of the 12 sequences of these siRNAs did not match those identified by available siRNA prediction algorithms. Significant inhibition of CCR5 in a T-lymphocyte cell line and primary T cells by these identified siRNAs was confirmed using the siRNA lentiviral vectors to infect these cells. The inhibition of CCR5 expression significantly protected cells from R5 HIV-1JRCSF infection. These results indicated that the high-throughput screening method allows efficient identification of siRNA sequences to inhibit the target genes at low levels of expression.

  9. Adaptive sampling strategies with high-throughput molecular dynamics

    Clementi, Cecilia

    Despite recent significant hardware and software developments, the complete thermodynamic and kinetic characterization of large macromolecular complexes by molecular simulations still presents significant challenges. The high dimensionality of these systems and the complexity of the associated potential energy surfaces (creating multiple metastable regions connected by high free energy barriers) does not usually allow to adequately sample the relevant regions of their configurational space by means of a single, long Molecular Dynamics (MD) trajectory. Several different approaches have been proposed to tackle this sampling problem. We focus on the development of ensemble simulation strategies, where data from a large number of weakly coupled simulations are integrated to explore the configurational landscape of a complex system more efficiently. Ensemble methods are of increasing interest as the hardware roadmap is now mostly based on increasing core counts, rather than clock speeds. The main challenge in the development of an ensemble approach for efficient sampling is in the design of strategies to adaptively distribute the trajectories over the relevant regions of the systems' configurational space, without using any a priori information on the system global properties. We will discuss the definition of smart adaptive sampling approaches that can redirect computational resources towards unexplored yet relevant regions. Our approaches are based on new developments in dimensionality reduction for high dimensional dynamical systems, and optimal redistribution of resources. NSF CHE-1152344, NSF CHE-1265929, Welch Foundation C-1570.

  10. A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements.

    Orton, Daniel J; Tfaily, Malak M; Moore, Ronald J; LaMarche, Brian L; Zheng, Xueyun; Fillmore, Thomas L; Chu, Rosalie K; Weitz, Karl K; Monroe, Matthew E; Kelly, Ryan T; Smith, Richard D; Baker, Erin S

    2018-01-02

    To better understand disease conditions and environmental perturbations, multiomic studies combining proteomic, lipidomic, and metabolomic analyses are vastly increasing in popularity. In a multiomic study, a single sample is typically extracted in multiple ways, and various analyses are performed using different instruments, most often based upon mass spectrometry (MS). Thus, one sample becomes many measurements, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injections. While some FIA systems have been created to address these challenges, many have limitations such as costly consumables, low pressure capabilities, limited pressure monitoring, and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at a range of flow rates (∼50 nL/min to 500 μL/min) to accommodate both low- and high-flow MS ionization sources. This system also functions at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system, and results showed a highly robust and reproducible platform capable of providing consistent performance over many days without carryover, as long as washing buffers specific to each molecular analysis were utilized.

  11. A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements

    Orton, Daniel J. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Tfaily, Malak M. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Moore, Ronald J. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; LaMarche, Brian L. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Zheng, Xueyun [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Fillmore, Thomas L. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Chu, Rosalie K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Weitz, Karl K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Monroe, Matthew E. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Kelly, Ryan T. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Smith, Richard D. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Baker, Erin S. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States

    2017-12-13

    To better understand disease conditions and environmental perturbations, multi-omic studies (i.e. proteomic, lipidomic, metabolomic, etc. analyses) are vastly increasing in popularity. In a multi-omic study, a single sample is typically extracted in multiple ways and numerous analyses are performed using different instruments. Thus, one sample becomes many analyses, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injection. While some FIA systems have been created to address these challenges, many have limitations such as high consumable costs, low pressure capabilities, limited pressure monitoring and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at diverse flow rates (~50 nL/min to 500 µL/min) to accommodate low- and high-flow instrument sources. This system can also operate at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system. The results from these studies showed a highly robust platform, providing consistent performance over many days without carryover as long as washing buffers specific to each molecular analysis were utilized.

  12. An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

    Alex Xijie Lu

    Full Text Available Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

  13. An Unsupervised kNN Method to Systematically Detect Changes in Protein Localization in High-Throughput Microscopy Images.

    Lu, Alex Xijie; Moses, Alan M

    2016-01-01

    Despite the importance of characterizing genes that exhibit subcellular localization changes between conditions in proteome-wide imaging experiments, many recent studies still rely upon manual evaluation to assess the results of high-throughput imaging experiments. We describe and demonstrate an unsupervised k-nearest neighbours method for the detection of localization changes. Compared to previous classification-based supervised change detection methods, our method is much simpler and faster, and operates directly on the feature space to overcome limitations in needing to manually curate training sets that may not generalize well between screens. In addition, the output of our method is flexible in its utility, generating both a quantitatively ranked list of localization changes that permit user-defined cut-offs, and a vector for each gene describing feature-wise direction and magnitude of localization changes. We demonstrate that our method is effective at the detection of localization changes using the Δrpd3 perturbation in Saccharomyces cerevisiae, where we capture 71.4% of previously known changes within the top 10% of ranked genes, and find at least four new localization changes within the top 1% of ranked genes. The results of our analysis indicate that simple unsupervised methods may be able to identify localization changes in images without laborious manual image labelling steps.

  14. A Self-Reporting Photocatalyst for Online Fluorescence Monitoring of High Throughput RAFT Polymerization.

    Yeow, Jonathan; Joshi, Sanket; Chapman, Robert; Boyer, Cyrille Andre Jean Marie

    2018-04-25

    Translating controlled/living radical polymerization (CLRP) from batch to the high throughput production of polymer libraries presents several challenges in terms of both polymer synthesis and characterization. Although recently there have been significant advances in the field of low volume, high throughput CLRP, techniques able to simultaneously monitor multiple polymerizations in an "online" manner have not yet been developed. Here, we report our discovery that 5,10,15,20-tetraphenyl-21H,23H-porphine zinc (ZnTPP) is a self-reporting photocatalyst that can mediate PET-RAFT polymerization as well as report on monomer conversion via changes in its fluorescence properties. This enables the use of a microplate reader to conduct high throughput "online" monitoring of PET-RAFT polymerizations performed directly in 384-well, low volume microtiter plates. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Filtering high-throughput protein-protein interaction data using a combination of genomic features

    Patil Ashwini

    2005-04-01

    Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.

  16. High-throughput screening of carbohydrate-degrading enzymes using novel insoluble chromogenic substrate assay kits

    Schückel, Julia; Kracun, Stjepan Kresimir; Willats, William George Tycho

    2016-01-01

    for this is that advances in genome and transcriptome sequencing, together with associated bioinformatics tools allow for rapid identification of candidate CAZymes, but technology for determining an enzyme's biochemical characteristics has advanced more slowly. To address this technology gap, a novel high-throughput assay...... CPH and ICB substrates are provided in a 96-well high-throughput assay system. The CPH substrates can be made in four different colors, enabling them to be mixed together and thus increasing assay throughput. The protocol describes a 96-well plate assay and illustrates how this assay can be used...... for screening the activities of enzymes, enzyme cocktails, and broths....

  17. Recent advances in high-throughput molecular marker identification for superficial and invasive bladder cancers

    Andersen, Lars Dyrskjøt; Zieger, Karsten; Ørntoft, Torben Falck

    2007-01-01

    individually contributed to the management of the disease. However, the development of high-throughput techniques for simultaneous assessment of a large number of markers has allowed classification of tumors into clinically relevant molecular subgroups beyond those possible by pathological classification. Here......Bladder cancer is the fifth most common neoplasm in industrialized countries. Due to frequent recurrences of the superficial form of this disease, bladder cancer ranks as one of the most common cancers. Despite the description of a large number of tumor markers for bladder cancers, none have......, we review the recent advances in high-throughput molecular marker identification for superficial and invasive bladder cancers....

  18. Integrated Automation of High-Throughput Screening and Reverse Phase Protein Array Sample Preparation

    Pedersen, Marlene Lemvig; Block, Ines; List, Markus

    into automated robotic high-throughput screens, which allows subsequent protein quantification. In this integrated solution, samples are directly forwarded to automated cell lysate preparation and preparation of dilution series, including reformatting to a protein spotter-compatible format after the high......-throughput screening. Tracking of huge sample numbers and data analysis from a high-content screen to RPPAs is accomplished via MIRACLE, a custom made software suite developed by us. To this end, we demonstrate that the RPPAs generated in this manner deliver reliable protein readouts and that GAPDH and TFR levels can...

  19. High throughput static and dynamic small animal imaging using clinical PET/CT: potential preclinical applications

    Aide, Nicolas; Desmonts, Cedric; Agostini, Denis; Bardet, Stephane; Bouvard, Gerard; Beauregard, Jean-Mathieu; Roselt, Peter; Neels, Oliver; Beyer, Thomas; Kinross, Kathryn; Hicks, Rodney J.

    2010-01-01

    The objective of the study was to evaluate state-of-the-art clinical PET/CT technology in performing static and dynamic imaging of several mice simultaneously. A mouse-sized phantom was imaged mimicking simultaneous imaging of three mice with computation of recovery coefficients (RCs) and spillover ratios (SORs). Fifteen mice harbouring abdominal or subcutaneous tumours were imaged on clinical PET/CT with point spread function (PSF) reconstruction after injection of [18F]fluorodeoxyglucose or [18F]fluorothymidine. Three of these mice were imaged alone and simultaneously at radial positions -5, 0 and 5 cm. The remaining 12 tumour-bearing mice were imaged in groups of 3 to establish the quantitative accuracy of PET data using ex vivo gamma counting as the reference. Finally, a dynamic scan was performed in three mice simultaneously after the injection of 68 Ga-ethylenediaminetetraacetic acid (EDTA). For typical lesion sizes of 7-8 mm phantom experiments indicated RCs of 0.42 and 0.76 for ordered subsets expectation maximization (OSEM) and PSF reconstruction, respectively. For PSF reconstruction, SOR air and SOR water were 5.3 and 7.5%, respectively. A strong correlation (r 2 = 0.97, p 2 = 0.98; slope = 0.89, p 2 = 0.96; slope = 0.62, p 68 Ga-EDTA dynamic acquisition. New generation clinical PET/CT can be used for simultaneous imaging of multiple small animals in experiments requiring high throughput and where a dedicated small animal PET system is not available. (orig.)

  20. WormSizer: high-throughput analysis of nematode size and shape.

    Brad T Moore

    Full Text Available The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy mutant is short and fat and that a Long (Lon mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc and Roller (Rol mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.

  1. Cyber-T web server: differential analysis of high-throughput data.

    Kayala, Matthew A; Baldi, Pierre

    2012-07-01

    The Bayesian regularization method for high-throughput differential analysis, described in Baldi and Long (A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics 2001: 17: 509-519) and implemented in the Cyber-T web server, is one of the most widely validated. Cyber-T implements a t-test using a Bayesian framework to compute a regularized variance of the measurements associated with each probe under each condition. This regularized estimate is derived by flexibly combining the empirical measurements with a prior, or background, derived from pooling measurements associated with probes in the same neighborhood. This approach flexibly addresses problems associated with low replication levels and technology biases, not only for DNA microarrays, but also for other technologies, such as protein arrays, quantitative mass spectrometry and next-generation sequencing (RNA-seq). Here we present an update to the Cyber-T web server, incorporating several useful new additions and improvements. Several preprocessing data normalization options including logarithmic and (Variance Stabilizing Normalization) VSN transforms are included. To augment two-sample t-tests, a one-way analysis of variance is implemented. Several methods for multiple tests correction, including standard frequentist methods and a probabilistic mixture model treatment, are available. Diagnostic plots allow visual assessment of the results. The web server provides comprehensive documentation and example data sets. The Cyber-T web server, with R source code and data sets, is publicly available at http://cybert.ics.uci.edu/.

  2. High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

    Rajkomar, Alvin; Lingam, Sneha; Taylor, Andrew G; Blum, Michael; Mongan, John

    2017-02-01

    The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on 909 patients obtained between January 2013 and July 2015 at our institution were retrieved and anonymized. The source images were manually annotated as frontal or lateral and randomly divided into training, validation, and test sets. Training and validation sets were augmented to over 150,000 images using standard image manipulations. We then pre-trained a series of deep convolutional networks based on the open-source GoogLeNet with various transformations of the open-source ImageNet (non-radiology) images. These trained networks were then fine-tuned using the original and augmented radiology images. The model with highest validation accuracy was applied to our institutional test set and a publicly available set. Accuracy was assessed by using the Youden Index to set a binary cutoff for frontal or lateral classification. This retrospective study was IRB approved prior to initiation. A network pre-trained on 1.2 million greyscale ImageNet images and fine-tuned on augmented radiographs was chosen. The binary classification method correctly classified 100 % (95 % CI 99.73-100 %) of both our test set and the publicly available images. Classification was rapid, at 38 images per second. A deep convolutional neural network created using non-radiological images, and an augmented set of radiographs is effective in highly accurate classification of chest radiograph view type and is a feasible, rapid method for high-throughput annotation.

  3. High-throughput sequencing of three Lemnoideae (duckweeds chloroplast genomes from total DNA.

    Wenqin Wang

    Full Text Available BACKGROUND: Chloroplast genomes provide a wealth of information for evolutionary and population genetic studies. Chloroplasts play a particularly important role in the adaption for aquatic plants because they float on water and their major surface is exposed continuously to sunlight. The subfamily of Lemnoideae represents such a collection of aquatic species that because of photosynthesis represents one of the fastest growing plant species on earth. METHODS: We sequenced the chloroplast genomes from three different genera of Lemnoideae, Spirodela polyrhiza, Wolffiella lingulata and Wolffia australiana by high-throughput DNA sequencing of genomic DNA using the SOLiD platform. Unfractionated total DNA contains high copies of plastid DNA so that sequences from the nucleus and mitochondria can easily be filtered computationally. Remaining sequence reads were assembled into contiguous sequences (contigs using SOLiD software tools. Contigs were mapped to a reference genome of Lemna minor and gaps, selected by PCR, were sequenced on the ABI3730xl platform. CONCLUSIONS: This combinatorial approach yielded whole genomic contiguous sequences in a cost-effective manner. Over 1,000-time coverage of chloroplast from total DNA were reached by the SOLiD platform in a single spot on a quadrant slide without purification. Comparative analysis indicated that the chloroplast genome was conserved in gene number and organization with respect to the reference genome of L. minor. However, higher nucleotide substitution, abundant deletions and insertions occurred in non-coding regions of these genomes, indicating a greater genomic dynamics than expected from the comparison of other related species in the Pooideae. Noticeably, there was no transition bias over transversion in Lemnoideae. The data should have immediate applications in evolutionary biology and plant taxonomy with increased resolution and statistical power.

  4. High-throughput sequencing of RNA silencing-associated small RNAs in olive (Olea europaea L..

    Livia Donaire

    Full Text Available Small RNAs (sRNAs of 20 to 25 nucleotides (nt in length maintain genome integrity and control gene expression in a multitude of developmental and physiological processes. Despite RNA silencing has been primarily studied in model plants, the advent of high-throughput sequencing technologies has enabled profiling of the sRNA component of more than 40 plant species. Here, we used deep sequencing and molecular methods to report the first inventory of sRNAs in olive (Olea europaea L.. sRNA libraries prepared from juvenile and adult shoots revealed that the 24-nt class dominates the sRNA transcriptome and atypically accumulates to levels never seen in other plant species, suggesting an active role of heterochromatin silencing in the maintenance and integrity of its large genome. A total of 18 known miRNA families were identified in the libraries. Also, 5 other sRNAs derived from potential hairpin-like precursors remain as plausible miRNA candidates. RNA blots confirmed miRNA expression and suggested tissue- and/or developmental-specific expression patterns. Target mRNAs of conserved miRNAs were computationally predicted among the olive cDNA collection and experimentally validated through endonucleolytic cleavage assays. Finally, we use expression data to uncover genetic components of the miR156, miR172 and miR390/TAS3-derived trans-acting small interfering RNA (tasiRNA regulatory nodes, suggesting that these interactive networks controlling developmental transitions are fully operational in olive.

  5. SEED 2: a user-friendly platform for amplicon high-throughput sequencing data analyses.

    Vetrovský, Tomáš; Baldrian, Petr; Morais, Daniel; Berger, Bonnie

    2018-02-14

    Modern molecular methods have increased our ability to describe microbial communities. Along with the advances brought by new sequencing technologies, we now require intensive computational resources to make sense of the large numbers of sequences continuously produced. The software developed by the scientific community to address this demand, although very useful, require experience of the command-line environment, extensive training and have steep learning curves, limiting their use. We created SEED 2, a graphical user interface for handling high-throughput amplicon-sequencing data under Windows operating systems. SEED 2 is the only sequence visualizer that empowers users with tools to handle amplicon-sequencing data of microbial community markers. It is suitable for any marker genes sequences obtained through Illumina, IonTorrent or Sanger sequencing. SEED 2 allows the user to process raw sequencing data, identify specific taxa, produce of OTU-tables, create sequence alignments and construct phylogenetic trees. Standard dual core laptops with 8 GB of RAM can handle ca. 8 million of Illumina PE 300 bp sequences, ca. 4GB of data. SEED 2 was implemented in Object Pascal and uses internal functions and external software for amplicon data processing. SEED 2 is a freeware software, available at http://www.biomed.cas.cz/mbu/lbwrf/seed/ as a self-contained file, including all the dependencies, and does not require installation. Supplementary data contain a comprehensive list of supported functions. daniel.morais@biomed.cas.cz. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

  6. Open source libraries and frameworks for mass spectrometry based proteomics: A developer's perspective☆

    Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

    2014-01-01

    Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23467006

  7. Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.

    Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

    2014-01-01

    Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study

    Haußmann Ute

    2011-06-01

    Full Text Available Abstract Background Mass spectrometry-based proteomics has reached a stage where it is possible to comprehensively analyze the whole proteome of a cell in one experiment. Here, the employment of stable isotopes has become a standard technique to yield relative abundance values of proteins. In recent times, more and more experiments are conducted that depict not only a static image of the up- or down-regulated proteins at a distinct time point but instead compare developmental stages of an organism or varying experimental conditions. Results Although the scientific questions behind these experiments are of course manifold, there are, nevertheless, two questions that commonly arise: 1 which proteins are differentially regulated regarding the selected experimental conditions, and 2 are there groups of proteins that show similar abundance ratios, indicating that they have a similar turnover? We give advice on how these two questions can be answered and comprehensively compare a variety of commonly applied computational methods and their outcomes. Conclusions This work provides guidance through the jungle of computational methods to analyze mass spectrometry-based isotope-labeled datasets and recommends an effective and easy-to-use evaluation strategy. We demonstrate our approach with three recently published datasets on Bacillus subtilis 12 and Corynebacterium glutamicum 3. Special focus is placed on the application and validation of cluster analysis methods. All applied methods were implemented within the rich internet application QuPE 4. Results can be found at http://qupe.cebitec.uni-bielefeld.de.

  9. Fusarium graminearum and Its Interactions with Cereal Heads: Studies in the Proteomics Era

    Yang, Fen; Jacobsen, Susanne; Jørgensen, Hans J L

    2013-01-01

    of humans and animals. In recent years, high-throughput proteomics, aiming at identifying a broad spectrum of proteins with a potential role in the pathogenicity and host resistance, has become a very useful tool in plant-fungus interaction research. In this review, we describe the progress in proteomics...... applications toward a better understanding of pathogenesis, virulence, and host defense mechanisms. The contribution of proteomics to the development of crop protection strategies against this pathogen is also discussed briefly....

  10. Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins.

    Reddy, Jithender G; Kumar, Dinesh; Hosur, Ramakrishna V

    2015-02-01

    Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.

  11. Proteomics - new analytical approaches

    Hancock, W.S.

    2001-01-01

    Full text: Recent developments in the sequencing of the human genome have indicated that the number of coding gene sequences may be as few as 30,000. It is clear, however, that the complexity of the human species is dependent on the much greater diversity of the corresponding protein complement. Estimates of the diversity (discrete protein species) of the human proteome range from 200,000 to 300,000 at the lower end to 2,000,000 to 3,000,000 at the high end. In addition, proteomics (the study of the protein complement to the genome) has been subdivided into two main approaches. Global proteomics refers to a high throughput examination of the full protein set present in a cell under a given environmental condition. Focused proteomics refers to a more detailed study of a restricted set of proteins that are related to a specified biochemical pathway or subcellular structure. While many of the advances in proteomics will be based on the sequencing of the human genome, de novo characterization of protein microheterogeneity (glycosylation, phosphorylation and sulfation as well as the incorporation of lipid components) will be required in disease studies. To characterize these modifications it is necessary to digest the protein mixture with an enzyme to produce the corresponding mixture of peptides. In a process analogous to sequencing of the genome, shot-gun sequencing of the proteome is based on the characterization of the key fragments produced by such a digest. Thus, a glycopeptide and hence a specific glycosylation motif will be identified by a unique mass and then a diagnostic MS/MS spectrum. Mass spectrometry will be the preferred detector in these applications because of the unparalleled information content provided by one or more dimensions of mass measurement. In addition, highly efficient separation processes are an absolute requirement for advanced proteomic studies. For example, a combination of the orthogonal approaches, HPLC and HPCE, can be very powerful

  12. CGPD: Cancer Genetics and Proteomics Database - A Dataset for Computational Analysis and Online Cancer Diagnostic Centre

    Muhammad Rizwan Riaz

    2014-06-01

    Full Text Available Cancer Genetics and Proteomics Database (CGPD is a repository for genetics and proteomics data of those Homo sapiens genes which are involved in Cancer. These genes are categorized in the database on the basis of cancer type. 72 genes of 13 types of cancers are considered in this database yet. Primers, promoters and peptides of these genes are also made available. Primers provided for each gene, with their features and conditions given to facilitate the researchers, are useful in PCR amplification, especially in cloning experiments. CGPD also contains Online Cancer Diagnostic Center (OCDC. It also contains transcription and translation tools to assist research work in progressive manner. The database is publicly available at http://www.cgpd.comyr.com.

  13. Using ALFA for high throughput, distributed data transmission in the ALICE O2 system

    Wegrzynek, A.; ALICE Collaboration

    2017-10-01

    ALICE (A Large Ion Collider Experiment) is a heavy-ion detector designed to study the physics of strongly interacting matter (the Quark-Gluon Plasma at the CERN LHC (Large Hadron Collider). ALICE has been successfully collecting physics data in Run 2 since spring 2015. In parallel, preparations for a major upgrade of the computing system, called O2 (Online-Offline), scheduled for the Long Shutdown 2 in 2019-2020, are being made. One of the major requirements of the system is the capacity to transport data between so-called FLPs (First Level Processors), equipped with readout cards, and the EPNs (Event Processing Node), performing data aggregation, frame building and partial reconstruction. It is foreseen to have 268 FLPs dispatching data to 1500 EPNs with an average output of 20 Gb/s each. In overall, the O2 processing system will operate at terabits per second of throughput while handling millions of concurrent connections. The ALFA framework will standardize and handle software related tasks such as readout, data transport, frame building, calibration, online reconstruction and more in the upgraded computing system. ALFA supports two data transport libraries: ZeroMQ and nanomsg. This paper discusses the efficiency of ALFA in terms of high throughput data transport. The tests were performed with multiple FLPs pushing data to multiple EPNs. The transfer was done using push-pull communication patterns and two socket configurations: bind, connect. The set of benchmarks was prepared to get the most performant results on each hardware setup. The paper presents the measurement process and final results - data throughput combined with computing resources usage as a function of block size. The high number of nodes and connections in the final set up may cause race conditions that can lead to uneven load balancing and poor scalability. The performed tests allow us to validate whether the traffic is distributed evenly over all receivers. It also measures the behaviour of

  14. Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale.

    Daniel L Parton

    2016-06-01

    Full Text Available The rapidly expanding body of available genomic and protein structural data provides a rich resource for understanding protein dynamics with biomolecular simulation. While computational infrastructure has grown rapidly, simulations on an omics scale are not yet widespread, primarily because software infrastructure to enable simulations at this scale has not kept pace. It should now be possible to study protein dynamics across entire (superfamilies, exploiting both available structural biology data and conformational similarities across homologous proteins. Here, we present a new tool for enabling high-throughput simulation in the genomics era. Ensembler takes any set of sequences-from a single sequence to an entire superfamily-and shepherds them through various stages of modeling and refinement to produce simulation-ready structures. This includes comparative modeling to all relevant PDB structures (which may span multiple conformational states of interest, reconstruction of missing loops, addition of missing atoms, culling of nearly identical structures, assignment of appropriate protonation states, solvation in explicit solvent, and refinement and filtering with molecular simulation to ensure stable simulation. The output of this pipeline is an ensemble of structures ready for subsequent molecular simulations using computer clusters, supercomputers, or distributed computing projects like Folding@home. Ensembler thus automates much of the time-consuming process of preparing protein models suitable for simulation, while allowing scalability up to entire superfamilies. A particular advantage of this approach can be found in the construction of kinetic models of conformational dynamics-such as Markov state models (MSMs-which benefit from a diverse array of initial configurations that span the accessible conformational states to aid sampling. We demonstrate the power of this approach by constructing models for all catalytic domains in the human

  15. Solid-phase cloning for high-throughput assembly of single and multiple DNA parts

    Lundqvist, Magnus; Edfors, Fredrik; Sivertsson, Åsa

    2015-01-01

    We describe solid-phase cloning (SPC) for high-throughput assembly of expression plasmids. Our method allows PCR products to be put directly into a liquid handler for capture and purification using paramagnetic streptavidin beads and conversion into constructs by subsequent cloning reactions. We ...

  16. Quantitative in vitro-to-in vivo extrapolation in a high-throughput environment

    Wetmore, Barbara A.

    2015-01-01

    High-throughput in vitro toxicity screening provides an efficient way to identify potential biological targets for environmental and industrial chemicals while conserving limited testing resources. However, reliance on the nominal chemical concentrations in these in vitro assays as an indicator of bioactivity may misrepresent potential in vivo effects of these chemicals due to differences in clearance, protein binding, bioavailability, and other pharmacokinetic factors. Development of high-throughput in vitro hepatic clearance and protein binding assays and refinement of quantitative in vitro-to-in vivo extrapolation (QIVIVE) methods have provided key tools to predict xenobiotic steady state pharmacokinetics. Using a process known as reverse dosimetry, knowledge of the chemical steady state behavior can be incorporated with HTS data to determine the external in vivo oral exposure needed to achieve internal blood concentrations equivalent to those eliciting bioactivity in the assays. These daily oral doses, known as oral equivalents, can be compared to chronic human exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. This review will describe the use of QIVIVE methods in a high-throughput environment and the promise they hold in shaping chemical testing priorities and, potentially, high-throughput risk assessment strategies

  17. Discovery of viruses and virus-like pathogens in pistachio using high-throughput sequencing

    Pistachio (Pistacia vera L.) trees from the National Clonal Germplasm Repository (NCGR) and orchards in California were surveyed for viruses and virus-like agents by high-throughput sequencing (HTS). Analyses of 60 trees including clonal UCB-1 hybrid rootstock (P. atlantica × P. integerrima) identif...

  18. Development of scalable high throughput fermentation approaches for physiological characterisation of yeast and filamentous fungi

    Knudsen, Peter Boldsen

    producing the heterologous model polyketide, 6-methylsalicylic acid (6-MSA). An automated methodology for high throughput screening focusing on growth rates, together with a fully automated method for quantitative physiological characterisation in microtiter plates, was established for yeast. Full...

  19. High throughput deposition of hydrogenated amorphous carbon coatings on rubber with expanding thermal plasma

    Pei, Y.T.; Eivani, A.R.; Zaharia, T.; Kazantis, A.V.; Sanden, van de M.C.M.; De Hosson, J.T.M.

    2014-01-01

    Flexible hydrogenated amorphous carbon (a-C:H) thin film coated on rubbers has shown outstanding protection of rubber seals from friction and wear. This work concentrates on the potential advances of expanding thermal plasma (ETP) process for a high throughput deposition of a-C:H thin films in

  20. High-throughput investigation of polymerization kinetics by online monitoring of GPC and GC

    Hoogenboom, R.; Fijten, M.W.M.; Abeln, C.H.; Schubert, U.S.

    2004-01-01

    Gel permeation chromatography (GPC) and gas chromatography (GC) were successfully introduced into a high-throughput workflow. The feasibility and limitations of online GPC with a high-speed column was evaluated by measuring polystyrene standards and comparison of the results with regular offline GPC

  1. Insights into Sonogashira cross-coupling by high-throughput kinetics and descriptor modeling

    an der Heiden, M.R.; Plenio, H.; Immel, S.; Burello, E.; Rothenberg, G.; Hoefsloot, H.C.J.

    2008-01-01

    A method is presented for the high-throughput monitoring of reaction kinetics in homogeneous catalysis, running up to 25 coupling reactions in a single reaction vessel. This method is demonstrated and validated on the Sonogashira reaction, analyzing the kinetics for almost 500 coupling reactions.

  2. Modeling Disordered Materials with a High Throughput ab-initio Approach

    2015-11-13

    Modeling Disordered Materials with a High Throughput ab - initio Approach Kesong Yang,1 Corey Oses,2 and Stefano Curtarolo3, 4 1Department of...J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set, Phys. Rev. B 54, 11169–11186 (1996

  3. High-throughput assessment of context-dependent effects of chromatin proteins

    Brueckner, L. (Laura); Van Arensbergen, J. (Joris); Akhtar, W. (Waseem); L. Pagie (Ludo); B. van Steensel (Bas)

    2016-01-01

    textabstractBackground: Chromatin proteins control gene activity in a concerted manner. We developed a high-throughput assay to study the effects of the local chromatin environment on the regulatory activity of a protein of interest. The assay combines a previously reported multiplexing strategy

  4. High-throughput, temperature-controlled microchannel acoustophoresis device made with rapid prototyping

    Adams, Jonathan D; Ebbesen, Christian L.; Barnkob, Rune

    2012-01-01

    -slide format using low-cost, rapid-prototyping techniques. This high-throughput acoustophoresis chip (HTAC) utilizes a temperature-stabilized, standing ultrasonic wave, which imposes differential acoustic radiation forces that can separate particles according to size, density and compressibility. The device...

  5. A high-throughput method for GMO multi-detection using a microfluidic dynamic array

    Brod, F.C.A.; Dijk, van J.P.; Voorhuijzen, M.M.; Dinon, A.Z.; Guimarães, L.H.S.; Scholtens, I.M.J.; Arisi, A.C.M.; Kok, E.J.

    2014-01-01

    The ever-increasing production of genetically modified crops generates a demand for high-throughput DNAbased methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the

  6. Retrofit Strategies for Incorporating Xenobiotic Metabolism into High Throughput Screening Assays (EMGS)

    The US EPA’s ToxCast program is designed to assess chemical perturbations of molecular and cellular endpoints using a variety of high-throughput screening (HTS) assays. However, existing HTS assays have limited or no xenobiotic metabolism which could lead to a mischaracterization...

  7. Development of automatic image analysis methods for high-throughput and high-content screening

    Di, Zi

    2013-01-01

    This thesis focuses on the development of image analysis methods for ultra-high content analysis of high-throughput screens where cellular phenotype responses to various genetic or chemical perturbations that are under investigation. Our primary goal is to deliver efficient and robust image analysis

  8. High-throughput verification of transcriptional starting sites by Deep-RACE

    Olivarius, Signe; Plessy, Charles; Carninci, Piero

    2009-01-01

    We present a high-throughput method for investigating the transcriptional starting sites of genes of interest, which we named Deep-RACE (Deep–rapid amplification of cDNA ends). Taking advantage of the latest sequencing technology, it allows the parallel analysis of multiple genes and is free...

  9. New approach for high-throughput screening of drug activity on Plasmodium liver stages.

    Gego, A.; Silvie, O.; Franetich, J.F.; Farhati, K.; Hannoun, L.; Luty, A.J.F.; Sauerwein, R.W.; Boucheix, C.; Rubinstein, E.; Mazier, D.

    2006-01-01

    Plasmodium liver stages represent potential targets for antimalarial prophylactic drugs. Nevertheless, there is a lack of molecules active on these stages. We have now developed a new approach for the high-throughput screening of drug activity on Plasmodium liver stages in vitro, based on an

  10. High-throughput experimentation in synthetic polymer chemistry: From RAFT and anionic polymerizations to process development

    Guerrero-Sanchez, C.A.; Paulus, R.M.; Fijten, M.W.M.; Mar, de la M.J.; Hoogenboom, R.; Schubert, U.S.

    2006-01-01

    The application of combinatorial and high-throughput approaches in polymer research is described. An overview of the utilized synthesis robots is given, including different parallel synthesizers and a process development robot. In addition, the application of the parallel synthesis robots to

  11. Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy

    Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H

    2017-01-01

    To target bacterial pathogens that invade and proliferate inside host cells, it is necessary to design intervention strategies directed against bacterial attachment, cellular invasion and intracellular proliferation. We present an automated microscopy-based, fast, high-throughput method for analy...

  12. A high throughput DNA extraction method with high yield and quality

    Xin Zhanguo

    2012-07-01

    Full Text Available Abstract Background Preparation of large quantity and high quality genomic DNA from a large number of plant samples is a major bottleneck for most genetic and genomic analyses, such as, genetic mapping, TILLING (Targeting Induced Local Lesion IN Genome, and next-generation sequencing directly from sheared genomic DNA. A variety of DNA preparation methods and commercial kits are available. However, they are either low throughput, low yield, or costly. Here, we describe a method for high throughput genomic DNA isolation from sorghum [Sorghum bicolor (L. Moench] leaves and dry seeds with high yield, high quality, and affordable cost. Results We developed a high throughput DNA isolation method by combining a high yield CTAB extraction method with an improved cleanup procedure based on MagAttract kit. The method yielded large quantity and high quality DNA from both lyophilized sorghum leaves and dry seeds. The DNA yield was improved by nearly 30 fold with 4 times less consumption of MagAttract beads. The method can also be used in other plant species, including cotton leaves and pine needles. Conclusion A high throughput system for DNA extraction from sorghum leaves and seeds was developed and validated. The main advantages of the method are low cost, high yield, high quality, and high throughput. One person can process two 96-well plates in a working day at a cost of $0.10 per sample of magnetic beads plus other consumables that other methods will also need.

  13. High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

    Guangbo Liu

    Full Text Available Saccharomyces cerevisiae (budding yeast is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids or genome mutation (e.g., gene mutation, deletion, epitope tagging is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

  14. High throughput "omics" approaches to assess the effects of phytochemicals in human health studies

    Ovesná, J.; Slabý, O.; Toussaint, O.; Kodíček, M.; Maršík, Petr; Pouchová, V.; Vaněk, Tomáš

    2008-01-01

    Roč. 99, E-S1 (2008), ES127-ES134 ISSN 0007-1145 R&D Projects: GA MŠk(CZ) 1P05OC054 Institutional research plan: CEZ:AV0Z50380511 Keywords : Nutrigenomics * Phytochemicals * High throughput platforms Subject RIV: GM - Food Processing Impact factor: 2.764, year: 2008

  15. High-Throughput Dietary Exposure Predictions for Chemical Migrants from Food Packaging Materials

    United States Environmental Protection Agency researchers have developed a Stochastic Human Exposure and Dose Simulation High -Throughput (SHEDS-HT) model for use in prioritization of chemicals under the ExpoCast program. In this research, new methods were implemented in SHEDS-HT...

  16. ToxCast Workflow: High-throughput screening assay data processing, analysis and management (SOT)

    US EPA’s ToxCast program is generating data in high-throughput screening (HTS) and high-content screening (HCS) assays for thousands of environmental chemicals, for use in developing predictive toxicity models. Currently the ToxCast screening program includes over 1800 unique c...

  17. High-throughput sequencing of forensic genetic samples using punches of FTA cards with buccal swabs

    Kampmann, Marie-Louise; Buchard, Anders; Børsting, Claus

    2016-01-01

    Here, we demonstrate that punches from buccal swab samples preserved on FTA cards can be used for high-throughput DNA sequencing, also known as massively parallel sequencing (MPS). We typed 44 reference samples with the HID-Ion AmpliSeq Identity Panel using washed 1.2 mm punches from FTA cards...

  18. Defining the taxonomic domain of applicability for mammalian-based high-throughput screening assays

    Cell-based high throughput screening (HTS) technologies are becoming mainstream in chemical safety evaluations. The US Environmental Protection Agency (EPA) Toxicity Forecaster (ToxCastTM) and the multi-agency Tox21 Programs have been at the forefront in advancing this science, m...

  19. 40 CFR Table 3 to Subpart Eeee of... - Operating Limits-High Throughput Transfer Racks

    2010-07-01

    ... 40 Protection of Environment 12 2010-07-01 2010-07-01 true Operating Limits-High Throughput Transfer Racks 3 Table 3 to Subpart EEEE of Part 63 Protection of Environment ENVIRONMENTAL PROTECTION... Throughput Transfer Racks As stated in § 63.2346(e), you must comply with the operating limits for existing...

  20. High-throughput testing of terpenoid biosynthesis candidate genes using transient expression in Nicotiana benthamiana

    Bach, Søren Spanner; Bassard, Jean-Étienne André; Andersen-Ranberg, Johan

    2014-01-01

    To respond to the rapidly growing number of genes putatively involved in terpenoid metabolism, a robust high-throughput platform for functional testing is needed. An in planta expression system offers several advantages such as the capacity to produce correctly folded and active enzymes localized...

  1. Evaluation of Simple and Inexpensive High-Throughput Methods for Phytic Acid Determination

    Raboy, Victor; Johnson, Amy; Bilyeu, Kristin

    2017-01-01

    High-throughput/low-cost/low-tech methods for phytic acid determination that are sufficiently accurate and reproducible would be of value in plant genetics, crop breeding and in the food and feed industries. Variants of two candidate methods, those described by Vaintraub and Lapteva (Anal Biochem...... and legume flours regardless of endogenous phytic acid levels or matrix constituents....

  2. The protein crystallography beamline BW6 at DORIS - automatic operation and high-throughput data collection

    Blume, H; Bourenkov, G P; Kosciesza, D; Bartunik, H D

    2001-01-01

    The wiggler beamline BW6 at DORIS has been optimized for de-novo solution of protein structures on the basis of MAD phasing. Facilities for automatic data collection, rapid data transfer and storage, and online processing have been developed which provide adequate conditions for high-throughput applications, e.g., in structural genomics.

  3. tcpl: The ToxCast Pipeline for High-Throughput Screening Data

    Motivation: The large and diverse high-throughput chemical screening efforts carried out by the US EPAToxCast program requires an efficient, transparent, and reproducible data pipeline.Summary: The tcpl R package and its associated MySQL database provide a generalized platform fo...

  4. Reverse Phase Protein Arrays for High-Throughput Protein Measurements in Mammospheres

    Pedersen, Marlene Lemvig; Block, Ines; List, Markus

    Protein Array (RPPA)-based readout format integrated into robotic siRNA screening. This technique would allow post-screening high-throughput quantification of protein changes. Recently, breast cancer stem cells (BCSCs) have attracted much attention, as a tumor- and metastasis-driving subpopulation...

  5. High throughput generated micro-aggregates of chondrocytes stimulate cartilage formation in vitro and in vivo

    Moreira Teixeira, Liliana; Leijten, Jeroen Christianus Hermanus; Sobral, J.; Jin, R.; van Apeldoorn, Aart A.; Feijen, Jan; van Blitterswijk, Clemens; Dijkstra, Pieter J.; Karperien, Hermanus Bernardus Johannes

    2012-01-01

    Cell-based cartilage repair strategies such as matrix-induced autologous chondrocyte implantation (MACI) could be improved by enhancing cell performance. We hypothesised that micro-aggregates of chondrocytes generated in high-throughput prior to implantation in a defect could stimulate cartilaginous

  6. Human Leukocyte Antigen Typing Using a Knowledge Base Coupled with a High-Throughput Oligonucleotide Probe Array Analysis

    Zhang, Guang Lan; Keskin, Derin B.; Lin, Hsin-Nan; Lin, Hong Huang; DeLuca, David S.; Leppanen, Scott; Milford, Edgar L.; Reinherz, Ellis L.; Brusic, Vladimir

    2014-01-01

    Human leukocyte antigens (HLA) are important biomarkers because multiple diseases, drug toxicity, and vaccine responses reveal strong HLA associations. Current clinical HLA typing is an elimination process requiring serial testing. We present an alternative in situ synthesized DNA-based microarray method that contains hundreds of thousands of probes representing a complete overlapping set covering 1,610 clinically relevant HLA class I alleles accompanied by computational tools for assigning HLA type to 4-digit resolution. Our proof-of-concept experiment included 21 blood samples, 18 cell lines, and multiple controls. The method is accurate, robust, and amenable to automation. Typing errors were restricted to homozygous samples or those with very closely related alleles from the same locus, but readily resolved by targeted DNA sequencing validation of flagged samples. High-throughput HLA typing technologies that are effective, yet inexpensive, can be used to analyze the world’s populations, benefiting both global public health and personalized health care. PMID:25505899

  7. elegantRingAnalysis An Interface for High-Throughput Analysis of Storage Ring Lattices Using elegant

    Borland, Michael

    2005-01-01

    The code {\\tt elegant} is widely used for simulation of linacs for drivers for free-electron lasers. Less well known is that elegant is also a very capable code for simulation of storage rings. In this paper, we show a newly-developed graphical user interface that allows the user to easily take advantage of these capabilities. The interface is designed for use on a Linux cluster, providing very high throughput. It can also be used on a single computer. Among the features it gives access to are basic calculations (Twiss parameters, radiation integrals), phase-space tracking, nonlinear dispersion, dynamic aperture (on- and off-momentum), frequency map analysis, and collective effects (IBS, bunch-lengthening). Using a cluster, it is easy to get highly detailed dynamic aperture and frequency map results in a surprisingly short time.

  8. PRIDE and "Database on Demand" as valuable tools for computational proteomics.

    Vizcaíno, Juan Antonio; Reisinger, Florian; Côté, Richard; Martens, Lennart

    2011-01-01

    The Proteomics Identifications Database (PRIDE, http://www.ebi.ac.uk/pride ) provides users with the ability to explore and compare mass spectrometry-based proteomics experiments that reveal details of the protein expression found in a broad range of taxonomic groups, tissues, and disease states. A PRIDE experiment typically includes identifications of proteins, peptides, and protein modifications. Additionally, many of the submitted experiments also include the mass spectra that provide the evidence for these identifications. Finally, one of the strongest advantages of PRIDE in comparison with other proteomics repositories is the amount of metadata it contains, a key point to put the above-mentioned data in biological and/or technical context. Several informatics tools have been developed in support of the PRIDE database. The most recent one is called "Database on Demand" (DoD), which allows custom sequence databases to be built in order to optimize the results from search engines. We describe the use of DoD in this chapter. Additionally, in order to show the potential of PRIDE as a source for data mining, we also explore complex queries using federated BioMart queries to integrate PRIDE data with other resources, such as Ensembl, Reactome, or UniProt.

  9. High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

    Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz

    2018-01-01

    High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

  10. High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

    Pan, Jian-Bo [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Nan; Pan, Wen; Hong, Ru [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Wang, Hao [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Zhi-Liang, E-mail: appo@xmu.edu.cn [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China)

    2014-01-01

    Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified.

  11. High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

    Pan, Jian-Bo; Ji, Nan; Pan, Wen; Hong, Ru; Wang, Hao; Ji, Zhi-Liang

    2014-01-01

    Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified

  12. eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

    Yuan, Tiezheng; Huang, Xiaoyi; Dittmar, Rachel L; Du, Meijun; Kohli, Manish; Boardman, Lisa; Thibodeau, Stephen N; Wang, Liang

    2014-03-05

    RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

  13. Automation, parallelism, and robotics for proteomics.

    Alterovitz, Gil; Liu, Jonathan; Chow, Jijun; Ramoni, Marco F

    2006-07-01

    The speed of the human genome project (Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C. et al., Nature 2001, 409, 860-921) was made possible, in part, by developments in automation of sequencing technologies. Before these technologies, sequencing was a laborious, expensive, and personnel-intensive task. Similarly, automation and robotics are changing the field of proteomics today. Proteomics is defined as the effort to understand and characterize proteins in the categories of structure, function and interaction (Englbrecht, C. C., Facius, A., Comb. Chem. High Throughput Screen. 2005, 8, 705-715). As such, this field nicely lends itself to automation technologies since these methods often require large economies of scale in order to achieve cost and time-saving benefits. This article describes some of the technologies and methods being applied in proteomics in order to facilitate automation within the field as well as in linking proteomics-based information with other related research areas.

  14. 40 CFR Table 9 to Subpart Eeee of... - Continuous Compliance With Operating Limits-High Throughput Transfer Racks

    2010-07-01

    ... 40 Protection of Environment 12 2010-07-01 2010-07-01 true Continuous Compliance With Operating Limits-High Throughput Transfer Racks 9 Table 9 to Subpart EEEE of Part 63 Protection of Environment...—Continuous Compliance With Operating Limits—High Throughput Transfer Racks As stated in §§ 63.2378(a) and (b...

  15. A target-based high throughput screen yields Trypanosoma brucei hexokinase small molecule inhibitors with antiparasitic activity.

    Elizabeth R Sharlow

    2010-04-01

    Full Text Available The parasitic protozoan Trypanosoma brucei utilizes glycolysis exclusively for ATP production during infection of the mammalian host. The first step in this metabolic pathway is mediated by hexokinase (TbHK, an enzyme essential to the parasite that transfers the gamma-phospho of ATP to a hexose. Here we describe the identification and confirmation of novel small molecule inhibitors of bacterially expressed TbHK1, one of two TbHKs expressed by T. brucei, using a high throughput screening assay.Exploiting optimized high throughput screening assay procedures, we interrogated 220,233 unique compounds and identified 239 active compounds from which ten small molecules were further characterized. Computation chemical cluster analyses indicated that six compounds were structurally related while the remaining four compounds were classified as unrelated or singletons. All ten compounds were approximately 20-17,000-fold more potent than lonidamine, a previously identified TbHK1 inhibitor. Seven compounds inhibited T. brucei blood stage form parasite growth (0.03

  16. InSourcerer: a high-throughput method to search for unknown metabolite modifications by mass spectrometry.

    Mrzic, Aida; Lermyte, Frederik; Vu, Trung Nghia; Valkenborg, Dirk; Laukens, Kris

    2017-09-15

    Using mass spectrometry, the analysis of known metabolite structures has become feasible in a systematic high-throughput fashion. Nevertheless, the identification of previously unknown structures remains challenging, partially because many unidentified variants originate from known molecules that underwent unexpected modifications. Here, we present a method for the discovery of unknown metabolite modifications and conjugate metabolite isoforms in a high-throughput fashion. The method is based on user-controlled in-source fragmentation which is used to induce loss of weakly bound modifications. This is followed by the comparison of product ions from in-source fragmentation and collision-induced dissociation (CID). Diagonal MS 2 -MS 3 matching allows the detection of unknown metabolite modifications, as well as substructure similarities. As the method relies heavily on the advantages of in-source fragmentation and its ability to 'magically' elucidate unknown modification, we have named it inSourcerer as a portmanteau of in-source and sorcerer. The method was evaluated using a set of 15 different cytokinin standards. Product ions from in-source fragmentation and CID were compared. Hierarchical clustering revealed that good matches are due to the presence of common substructures. Plant leaf extract, spiked with a mix of all 15 standards, was used to demonstrate the method's ability to detect these standards in a complex mixture, as well as confidently identify compounds already present in the plant material. Here we present a method that incorporates a classic liquid chromatography/mass spectrometry (LC/MS) workflow with fragmentation models and computational algorithms. The assumptions upon which the concept of the method was built were shown to be valid and the method showed that in-source fragmentation can be used to pinpoint structural similarities and indicate the occurrence of a modification. Copyright © 2017 John Wiley & Sons, Ltd.

  17. Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

    Canard Bruno

    2011-10-01

    Full Text Available Abstract Background The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4. Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. Results We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. Conclusions We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.

  18. Clinical validation of an ultra high-throughput spiral microfluidics for the detection and enrichment of viable circulating tumor cells.

    Bee Luan Khoo

    Full Text Available Circulating tumor cells (CTCs are cancer cells that can be isolated via liquid biopsy from blood and can be phenotypically and genetically characterized to provide critical information for guiding cancer treatment. Current analysis of CTCs is hindered by the throughput, selectivity and specificity of devices or assays used in CTC detection and isolation.Here, we enriched and characterized putative CTCs from blood samples of patients with both advanced stage metastatic breast and lung cancers using a novel multiplexed spiral microfluidic chip. This system detected putative CTCs under high sensitivity (100%, n = 56 (Breast cancer samples: 12-1275 CTCs/ml; Lung cancer samples: 10-1535 CTCs/ml rapidly from clinically relevant blood volumes (7.5 ml under 5 min. Blood samples were completely separated into plasma, CTCs and PBMCs components and each fraction were characterized with immunophenotyping (Pan-cytokeratin/CD45, CD44/CD24, EpCAM, fluorescence in-situ hybridization (FISH (EML4-ALK or targeted somatic mutation analysis. We used an ultra-sensitive mass spectrometry based system to highlight the presence of an EGFR-activating mutation in both isolated CTCs and plasma cell-free DNA (cf-DNA, and demonstrate concordance with the original tumor-biopsy samples.We have clinically validated our multiplexed microfluidic chip for the ultra high-throughput, low-cost and label-free enrichment of CTCs. Retrieved cells were unlabeled and viable, enabling potential propagation and real-time downstream analysis using next generation sequencing (NGS or proteomic analysis.

  19. Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis.

    Ding, Kuan-Fu; Petricoin, Emanuel F; Finlay, Darren; Yin, Hongwei; Hendricks, William P D; Sereduk, Chris; Kiefer, Jeffrey; Sekulic, Aleksandar; LoRusso, Patricia M; Vuori, Kristiina; Trent, Jeffrey M; Schork, Nicholas J

    2018-01-12

    Cancer cell lines are often used in high throughput drug screens (HTS) to explore the relationship between cell line characteristics and responsiveness to different therapies. Many current analysis methods infer relationships by focusing on one aspect of cell line drug-specific dose-response curves (DRCs), the concentration causing 50% inhibition of a phenotypic endpoint (IC 50 ). Such methods may overlook DRC features and do not simultaneously leverage information about drug response patterns across cell lines, potentially increasing false positive and negative rates in drug response associations. We consider the application of two methods, each rooted in nonlinear mixed effects (NLME) models, that test the relationship relationships between estimated cell line DRCs and factors that might mitigate response. Both methods leverage estimation and testing techniques that consider the simultaneous analysis of different cell lines to draw inferences about any one cell line. One of the methods is designed to provide an omnibus test of the differences between cell line DRCs that is not focused on any one aspect of the DRC (such as the IC 50 value). We simulated different settings and compared the different methods on the simulated data. We also compared the proposed methods against traditional IC 50 -based methods using 40 melanoma cell lines whose transcriptomes, proteomes, and, importantly, BRAF and related mutation profiles were available. Ultimately, we find that the NLME-based methods are more robust, powerful and, for the omnibus test, more flexible, than traditional methods. Their application to the melanoma cell lines reveals insights into factors that may be clinically useful.

  20. Turbocharged molecular discovery of OLED emitters: from high-throughput quantum simulation to highly efficient TADF devices

    Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Ha, Dong-Gwang; Einzinger, Markus; Wu, Tony; Baldo, Marc A.; Aspuru-Guzik, Alán.

    2016-09-01

    Discovering new OLED emitters requires many experiments to synthesize candidates and test performance in devices. Large scale computer simulation can greatly speed this search process but the problem remains challenging enough that brute force application of massive computing power is not enough to successfully identify novel structures. We report a successful High Throughput Virtual Screening study that leveraged a range of methods to optimize the search process. The generation of candidate structures was constrained to contain combinatorial explosion. Simulations were tuned to the specific problem and calibrated with experimental results. Experimentalists and theorists actively collaborated such that experimental feedback was regularly utilized to update and shape the computational search. Supervised machine learning methods prioritized candidate structures prior to quantum chemistry simulation to prevent wasting compute on likely poor performers. With this combination of techniques, each multiplying the strength of the search, this effort managed to navigate an area of molecular space and identify hundreds of promising OLED candidate structures. An experimentally validated selection of this set shows emitters with external quantum efficiencies as high as 22%.

  1. High-throughput characterization of film thickness in thin film materials libraries by digital holographic microscopy

    Lai Yiuwai; Hofmann, Martin R; Ludwig, Alfred; Krause, Michael; Savan, Alan; Thienhaus, Sigurd; Koukourakis, Nektarios

    2011-01-01

    A high-throughput characterization technique based on digital holography for mapping film thickness in thin-film materials libraries was developed. Digital holographic microscopy is used for fully automatic measurements of the thickness of patterned films with nanometer resolution. The method has several significant advantages over conventional stylus profilometry: it is contactless and fast, substrate bending is compensated, and the experimental setup is simple. Patterned films prepared by different combinatorial thin-film approaches were characterized to investigate and demonstrate this method. The results show that this technique is valuable for the quick, reliable and high-throughput determination of the film thickness distribution in combinatorial materials research. Importantly, it can also be applied to thin films that have been structured by shadow masking.

  2. High-throughput characterization of film thickness in thin film materials libraries by digital holographic microscopy.

    Lai, Yiu Wai; Krause, Michael; Savan, Alan; Thienhaus, Sigurd; Koukourakis, Nektarios; Hofmann, Martin R; Ludwig, Alfred

    2011-10-01

    A high-throughput characterization technique based on digital holography for mapping film thickness in thin-film materials libraries was developed. Digital holographic microscopy is used for fully automatic measurements of the thickness of patterned films with nanometer resolution. The method has several significant advantages over conventional stylus profilometry: it is contactless and fast, substrate bending is compensated, and the experimental setup is simple. Patterned films prepared by different combinatorial thin-film approaches were characterized to investigate and demonstrate this method. The results show that this technique is valuable for the quick, reliable and high-throughput determination of the film thickness distribution in combinatorial materials research. Importantly, it can also be applied to thin films that have been structured by shadow masking.

  3. The French press: a repeatable and high-throughput approach to exercising zebrafish (Danio rerio).

    Usui, Takuji; Noble, Daniel W A; O'Dea, Rose E; Fangmeier, Melissa L; Lagisz, Malgorzata; Hesselson, Daniel; Nakagawa, Shinichi

    2018-01-01

    Zebrafish are increasingly used as a vertebrate model organism for various traits including swimming performance, obesity and metabolism, necessitating high-throughput protocols to generate standardized phenotypic information. Here, we propose a novel and cost-effective method for exercising zebrafish, using a coffee plunger and magnetic stirrer. To demonstrate the use of this method, we conducted a pilot experiment to show that this simple system provides repeatable estimates of maximal swim performance (intra-class correlation [ICC] = 0.34-0.41) and observe that exercise training of zebrafish on this system significantly increases their maximum swimming speed. We propose this high-throughput and reproducible system as an alternative to traditional linear chamber systems for exercising zebrafish and similarly sized fishes.

  4. Selection and optimization of hits from a high-throughput phenotypic screen against Trypanosoma cruzi.

    Keenan, Martine; Alexander, Paul W; Chaplin, Jason H; Abbott, Michael J; Diao, Hugo; Wang, Zhisen; Best, Wayne M; Perez, Catherine J; Cornwall, Scott M J; Keatley, Sarah K; Thompson, R C Andrew; Charman, Susan A; White, Karen L; Ryan, Eileen; Chen, Gong; Ioset, Jean-Robert; von Geldern, Thomas W; Chatelain, Eric

    2013-10-01

    Inhibitors of Trypanosoma cruzi with novel mechanisms of action are urgently required to diversify the current clinical and preclinical pipelines. Increasing the number and diversity of hits available for assessment at the beginning of the discovery process will help to achieve this aim. We report the evaluation of multiple hits generated from a high-throughput screen to identify inhibitors of T. cruzi and from these studies the discovery of two novel series currently in lead optimization. Lead compounds from these series potently and selectively inhibit growth of T. cruzi in vitro and the most advanced compound is orally active in a subchronic mouse model of T. cruzi infection. High-throughput screening of novel compound collections has an important role to play in diversifying the trypanosomatid drug discovery portfolio. A new T. cruzi inhibitor series with good drug-like properties and promising in vivo efficacy has been identified through this process.

  5. Determining the optimal size of small molecule mixtures for high throughput NMR screening

    Mercier, Kelly A.; Powers, Robert

    2005-01-01

    High-throughput screening (HTS) using NMR spectroscopy has become a common component of the drug discovery effort and is widely used throughout the pharmaceutical industry. NMR provides additional information about the nature of small molecule-protein interactions compared to traditional HTS methods. In order to achieve comparable efficiency, small molecules are often screened as mixtures in NMR-based assays. Nevertheless, an analysis of the efficiency of mixtures and a corresponding determination of the optimum mixture size (OMS) that minimizes the amount of material and instrumentation time required for an NMR screen has been lacking. A model for calculating OMS based on the application of the hypergeometric distribution function to determine the probability of a 'hit' for various mixture sizes and hit rates is presented. An alternative method for the deconvolution of large screening mixtures is also discussed. These methods have been applied in a high-throughput NMR screening assay using a small, directed library

  6. High-throughput screening of small molecule libraries using SAMDI mass spectrometry.

    Gurard-Levin, Zachary A; Scholle, Michael D; Eisenberg, Adam H; Mrksich, Milan

    2011-07-11

    High-throughput screening is a common strategy used to identify compounds that modulate biochemical activities, but many approaches depend on cumbersome fluorescent reporters or antibodies and often produce false-positive hits. The development of "label-free" assays addresses many of these limitations, but current approaches still lack the throughput needed for applications in drug discovery. This paper describes a high-throughput, label-free assay that combines self-assembled monolayers with mass spectrometry, in a technique called SAMDI, as a tool for screening libraries of 100,000 compounds in one day. This method is fast, has high discrimination, and is amenable to a broad range of chemical and biological applications.

  7. High-throughput screening assay of hepatitis C virus helicase inhibitors using fluorescence-quenching phenomenon

    Tani, Hidenori; Akimitsu, Nobuyoshi; Fujita, Osamu; Matsuda, Yasuyoshi; Miyata, Ryo; Tsuneda, Satoshi; Igarashi, Masayuki; Sekiguchi, Yuji; Noda, Naohiro

    2009-01-01

    We have developed a novel high-throughput screening assay of hepatitis C virus (HCV) nonstructural protein 3 (NS3) helicase inhibitors using the fluorescence-quenching phenomenon via photoinduced electron transfer between fluorescent dyes and guanine bases. We prepared double-stranded DNA (dsDNA) with a 5'-fluorescent-dye (BODIPY FL)-labeled strand hybridized with a complementary strand, the 3'-end of which has guanine bases. When dsDNA is unwound by helicase, the dye emits fluorescence owing to its release from the guanine bases. Our results demonstrate that this assay is suitable for quantitative assay of HCV NS3 helicase activity and useful for high-throughput screening for inhibitors. Furthermore, we applied this assay to the screening for NS3 helicase inhibitors from cell extracts of microorganisms, and found several cell extracts containing potential inhibitors.

  8. High throughput octal alpha/gamma spectrometer for low level bioassay estimations

    Bhasin, B.D.; Shirke, S.H.; Suri, M.M.; Vaidya, P.P.; Ghodgaonkar, M.D.

    1995-01-01

    The present paper describes the development of a high throughput octal alpha spectrometry system specially developed for the estimation of low levels of actinides in bioassay and environmental samples. The system processes simultaneously the outputs coming from eight independent detectors. It can be configured to simultaneously record low level alpha and gamma spectra. The high throughput is achieved by using a prioritised multiplexer router. The prioritised multiplexing and routing coupled with fast 8K ADC (conversion time 20 μsec) allow simultaneous acquisition of multiple spectra without any significant loss in counts. The dual (8K, 24bit) port memory facilitates easy online viewing of spectrum buildup. A menu driven user friendly software makes the operating system convenient to use. A specially developed software provides built-in routines for processing the spectra and estimating the isotopic activity. The interactive mode of software provides easy identification of isotopes compatible with the separation chemistry of different actinides. (author). 6 refs., 2 figs

  9. High-throughput shotgun lipidomics by quadrupole time-of-flight mass spectrometry

    Ståhlman, Marcus; Ejsing, Christer S.; Tarasov, Kirill

    2009-01-01

    Technological advances in mass spectrometry and meticulous method development have produced several shotgun lipidomic approaches capable of characterizing lipid species by direct analysis of total lipid extracts. Shotgun lipidomics by hybrid quadrupole time-of-flight mass spectrometry allows...... the absolute quantification of hundreds of molecular glycerophospholipid species, glycerolipid species, sphingolipid species and sterol lipids. Future applications in clinical cohort studies demand detailed lipid molecule information and the application of high-throughput lipidomics platforms. In this review...... we describe a novel high-throughput shotgun lipidomic platform based on 96-well robot-assisted lipid extraction, automated sample infusion by mircofluidic-based nanoelectrospray ionization, and quantitative multiple precursor ion scanning analysis on a quadrupole time-of-flight mass spectrometer...

  10. Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis.

    Mei, Feng; Fancy, Stephen P J; Shen, Yun-An A; Niu, Jianqin; Zhao, Chao; Presley, Bryan; Miao, Edna; Lee, Seonok; Mayoral, Sonia R; Redmond, Stephanie A; Etxeberria, Ainhoa; Xiao, Lan; Franklin, Robin J M; Green, Ari; Hauser, Stephen L; Chan, Jonah R

    2014-08-01

    Functional screening for compounds that promote remyelination represents a major hurdle in the development of rational therapeutics for multiple sclerosis. Screening for remyelination is problematic, as myelination requires the presence of axons. Standard methods do not resolve cell-autonomous effects and are not suited for high-throughput formats. Here we describe a binary indicant for myelination using micropillar arrays (BIMA). Engineered with conical dimensions, micropillars permit resolution of the extent and length of membrane wrapping from a single two-dimensional image. Confocal imaging acquired from the base to the tip of the pillars allows for detection of concentric wrapping observed as 'rings' of myelin. The platform is formatted in 96-well plates, amenable to semiautomated random acquisition and automated detection and quantification. Upon screening 1,000 bioactive molecules, we identified a cluster of antimuscarinic compounds that enhance oligodendrocyte differentiation and remyelination. Our findings demonstrate a new high-throughput screening platform for potential regenerative therapeutics in multiple sclerosis.

  11. Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS)

    Hura, Greg L.; Menon, Angeli L.; Hammel, Michal; Rambo, Robert P.; Poole II, Farris L.; Tsutakawa, Susan E.; Jenney Jr, Francis E.; Classen, Scott; Frankel, Kenneth A.; Hopkins, Robert C.; Yang, Sungjae; Scott, Joseph W.; Dillard, Bret D.; Adams, Michael W. W.; Tainer, John A.

    2009-07-20

    We present an efficient pipeline enabling high-throughput analysis of protein structure in solution with small angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling of microliter volumes, temperature and anaerobic control, rapid data collection and data analysis, and couples structural analysis with automated archiving. We subjected 50 representative proteins, mostly from Pyrococcus furiosus, to this pipeline and found that 30 were multimeric structures in solution. SAXS analysis allowed us to distinguish aggregated and unfolded proteins, define global structural parameters and oligomeric states for most samples, identify shapes and similar structures for 25 unknown structures, and determine envelopes for 41 proteins. We believe that high-throughput SAXS is an enabling technology that may change the way that structural genomics research is done.

  12. Fabrication of combinatorial nm-planar electrode array for high throughput evaluation of organic semiconductors

    Haemori, M.; Edura, T.; Tsutsui, K.; Itaka, K.; Wada, Y.; Koinuma, H.

    2006-01-01

    We have fabricated a combinatorial nm-planar electrode array by using photolithography and chemical mechanical polishing processes for high throughput electrical evaluation of organic devices. Sub-nm precision was achieved with respect to the average level difference between each pair of electrodes and a dielectric layer. The insulating property between the electrodes is high enough to measure I-V characteristics of organic semiconductors. Bottom-contact field-effect-transistors (FETs) of pentacene were fabricated on this electrode array by use of molecular beam epitaxy. It was demonstrated that the array could be used as a pre-patterned device substrate for high throughput screening of the electrical properties of organic semiconductors

  13. High-throughput Sequencing Based Immune Repertoire Study during Infectious Disease

    Dongni Hou

    2016-08-01

    Full Text Available The selectivity of the adaptive immune response is based on the enormous diversity of T and B cell antigen-specific receptors. The immune repertoire, the collection of T and B cells with functional diversity in the circulatory system at any given time, is dynamic and reflects the essence of immune selectivity. In this article, we review the recent advances in immune repertoire study of infectious diseases that achieved by traditional techniques and high-throughput sequencing techniques. High-throughput sequencing techniques enable the determination of complementary regions of lymphocyte receptors with unprecedented efficiency and scale. This progress in methodology enhances the understanding of immunologic changes during pathogen challenge, and also provides a basis for further development of novel diagnostic markers, immunotherapies and vaccines.

  14. Life in the fast lane: high-throughput chemistry for lead generation and optimisation.

    Hunter, D

    2001-01-01

    The pharmaceutical industry has come under increasing pressure due to regulatory restrictions on the marketing and pricing of drugs, competition, and the escalating costs of developing new drugs. These forces can be addressed by the identification of novel targets, reductions in the development time of new drugs, and increased productivity. Emphasis has been placed on identifying and validating new targets and on lead generation: the response from industry has been very evident in genomics and high throughput screening, where new technologies have been applied, usually coupled with a high degree of automation. The combination of numerous new potential biological targets and the ability to screen large numbers of compounds against many of these targets has generated the need for large diverse compound collections. To address this requirement, high-throughput chemistry has become an integral part of the drug discovery process. Copyright 2002 Wiley-Liss, Inc.

  15. Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

    Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

    2017-10-01

    Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

  16. High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats.

    Zhou, Jizhong; He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G; Alvarez-Cohen, Lisa

    2015-01-27

    Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied "open-format" and "closed-format" detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. Copyright © 2015 Zhou et al.

  17. High-Throughput Screening of a Luciferase Reporter of Gene Silencing on the Inactive X Chromosome.

    Keegan, Alissa; Plath, Kathrin; Damoiseaux, Robert

    2018-01-01

    Assays of luciferase gene activity are a sensitive and quantitative reporter system suited to high-throughput screening. We adapted a luciferase assay to a screening strategy for identifying factors that reactivate epigenetically silenced genes. This epigenetic luciferase reporter is subject to endogenous gene silencing mechanisms on the inactive X chromosome (Xi) in primary mouse cells and thus captures the multilayered nature of chromatin silencing in development. Here, we describe the optimization of an Xi-linked luciferase reactivation assay in 384-well format and adaptation of the assay for high-throughput siRNA and chemical screening. Xi-luciferase reactivation screening has applications in stem cell biology and cancer therapy. We have used the approach described here to identify chromatin-modifying proteins and to identify drug combinations that enhance the gene reactivation activity of the DNA demethylating drug 5-aza-2'-deoxycytidine.

  18. High-throughput tri-colour flow cytometry technique to assess Plasmodium falciparum parasitaemia in bioassays

    Tiendrebeogo, Regis W; Adu, Bright; Singh, Susheel K

    2014-01-01

    BACKGROUND: Unbiased flow cytometry-based methods have become the technique of choice in many laboratories for high-throughput, accurate assessments of malaria parasites in bioassays. A method to quantify live parasites based on mitotracker red CMXRos was recently described but consistent...... distinction of early ring stages of Plasmodium falciparum from uninfected red blood cells (uRBC) remains a challenge. METHODS: Here, a high-throughput, three-parameter (tri-colour) flow cytometry technique based on mitotracker red dye, the nucleic acid dye coriphosphine O (CPO) and the leucocyte marker CD45...... for enumerating live parasites in bioassays was developed. The technique was applied to estimate the specific growth inhibition index (SGI) in the antibody-dependent cellular inhibition (ADCI) assay and compared to parasite quantification by microscopy and mitotracker red staining. The Bland-Altman analysis...

  19. Fluorescence-based high-throughput screening of dicer cleavage activity.

    Podolska, Katerina; Sedlak, David; Bartunek, Petr; Svoboda, Petr

    2014-03-01

    Production of small RNAs by ribonuclease III Dicer is a key step in microRNA and RNA interference pathways, which employ Dicer-produced small RNAs as sequence-specific silencing guides. Further studies and manipulations of microRNA and RNA interference pathways would benefit from identification of small-molecule modulators. Here, we report a study of a fluorescence-based in vitro Dicer cleavage assay, which was adapted for high-throughput screening. The kinetic assay can be performed under single-turnover conditions (35 nM substrate and 70 nM Dicer) in a small volume (5 µL), which makes it suitable for high-throughput screening in a 1536-well format. As a proof of principle, a small library of bioactive compounds was analyzed, demonstrating potential of the assay.

  20. Multiple and high-throughput droplet reactions via combination of microsampling technique and microfluidic chip

    Wu, Jinbo

    2012-11-20

    Microdroplets offer unique compartments for accommodating a large number of chemical and biological reactions in tiny volume with precise control. A major concern in droplet-based microfluidics is the difficulty to address droplets individually and achieve high throughput at the same time. Here, we have combined an improved cartridge sampling technique with a microfluidic chip to perform droplet screenings and aggressive reaction with minimal (nanoliter-scale) reagent consumption. The droplet composition, distance, volume (nanoliter to subnanoliter scale), number, and sequence could be precisely and digitally programmed through the improved sampling technique, while sample evaporation and cross-contamination are effectively eliminated. Our combined device provides a simple model to utilize multiple droplets for various reactions with low reagent consumption and high throughput. © 2012 American Chemical Society.

  1. High throughput route selection in multi-rate wireless mesh networks

    WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

    2008-01-01

    Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

  2. From Classical to High Throughput Screening Methods for Feruloyl Esterases: A Review.

    Ramírez-Velasco, Lorena; Armendáriz-Ruiz, Mariana; Rodríguez-González, Jorge Alberto; Müller-Santos, Marcelo; Asaff-Torres, Ali; Mateos-Díaz, Juan Carlos

    2016-01-01

    Feruloyl esterases (FAEs) are a diverse group of hydrolases widely distributed in plants and microorganisms which catalyzes the cleavage and formation of ester bonds between plant cell wall polysaccharides and phenolic acids. FAEs have gained importance in biofuel, medicine and food industries due to their capability of acting on a large range of substrates for cleaving ester bonds and synthesizing highadded value molecules through esterification and transesterification reactions. During the past two decades extensive studies have been carried out on the production, characterization and classification of FAEs, however only a few reports of suitable High Throughput Screening assays for this kind of enzymes have been reported. This review is focused on a concise but complete revision of classical to High Throughput Screening methods for FAEs, highlighting its advantages and disadvantages, and finally suggesting future perspectives for this important research field.

  3. Association Study of Gut Flora in Coronary Heart Disease through High-Throughput Sequencing

    Cui, Li; Zhao, Tingting; Hu, Haibing; Zhang, Wen; Hua, Xiuguo

    2017-01-01

    Objectives. We aimed to explore the impact of gut microbiota in coronary heart disease (CHD) patients through high-throughput sequencing. Methods. A total of 29 CHD in-hospital patients and 35 healthy volunteers as controls were included. Nucleic acids were extracted from fecal samples, followed by ? diversity and principal coordinate analysis (PCoA). Based on unweighted UniFrac distance matrices, unweighted-pair group method with arithmetic mean (UPGMA) trees were created. Results. After dat...

  4. Rapid 2,2'-bicinchoninic-based xylanase assay compatible with high throughput screening

    William R. Kenealy; Thomas W. Jeffries

    2003-01-01

    High-throughput screening requires simple assays that give reliable quantitative results. A microplate assay was developed for reducing sugar analysis that uses a 2,2'-bicinchoninic-based protein reagent. Endo-1,4-â-D-xylanase activity against oat spelt xylan was detected at activities of 0.002 to 0.011 IU ml−1. The assay is linear for sugar...

  5. Combinatorial Strategies and High Throughput Screening in Drug Discovery Targeted to the Channel of Botulinum Neurotoxin

    Montal, Mauricio

    2006-01-01

    .... The major focus thus far has been the implementation of a reliable and robust high-throughput screen for blockers specific for BoNT using Neuro 2A cells in which BoNTA forms channels with similar properties to those previously characterized in lipid bilayers. The immediate task during the present reporting period involved the detailed characterization of the channel and chaperone activity of BoNTA on Neuro2A cells.

  6. Patterning cell using Si-stencil for high-throughput assay

    Wu, Jinbo

    2011-01-01

    In this communication, we report a newly developed cell pattering methodology by a silicon-based stencil, which exhibited advantages such as easy handling, reusability, hydrophilic surface and mature fabrication technologies. Cell arrays obtained by this method were used to investigate cell growth under a temperature gradient, which demonstrated the possibility of studying cell behavior in a high-throughput assay. This journal is © The Royal Society of Chemistry 2011.

  7. Upscaling and automation of electrophysiology: toward high throughput screening in ion channel drug discovery

    Asmild, Margit; Oswald, Nicholas; Krzywkowski, Karen M

    2003-01-01

    by developing two lines of automated patch clamp products, a traditional pipette-based system called Apatchi-1, and a silicon chip-based system QPatch. The degree of automation spans from semi-automation (Apatchi-1) where a trained technician interacts with the system in a limited way, to a complete automation...... (QPatch 96) where the system works continuously and unattended until screening of a full compound library is completed. The performance of the systems range from medium to high throughputs....

  8. A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

    Musah, Rabi A.; Espinoza, Edgard O.; Cody, Robert B.; Lesiak, Ashton D.; Christensen, Earl D.; Moore, Hannah E.; Maleknia, Simin; Drijfhout, Falko P.

    2015-01-01

    A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. A range of both polar and non-polar chemotypes a...

  9. Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data

    Gallant, Andrew; Leiserson, Mark DM; Kachalov, Maxim; Cowen, Lenore J; Hescott, Benjamin J

    2013-01-01

    Background New technology has resulted in high-throughput screens for pairwise genetic interactions in yeast and other model organisms. For each pair in a collection of non-essential genes, an epistasis score is obtained, representing how much sicker (or healthier) the double-knockout organism will be compared to what would be expected from the sickness of the component single knockouts. Recent algorithmic work has identified graph-theoretic patterns in this data that can indicate functional ...

  10. High-throughput evaluation of interactions between biomaterials, proteins and cells using patterned superhydrophobic substrates

    Neto, Ana I.; Custódio, Catarina A.; Wenlong Song; Mano, J. F.

    2011-01-01

    We propose a new low cost platform for high-throughput analysis that permits screening the biological performance of independent combinations of biomaterials, cells and culture media. Patterned superhydrophobic flat substrates with controlled wettable spots are used to produce microarray chips for accelerated multiplexing evaluation. This work was partially supported by Fundação para a Ciência e Tecnologia (FCT) under project PTDC/FIS/68517/2006.

  11. Geochip: A high throughput genomic tool for linking community structure to functions

    Van Nostrand, Joy D.; Liang, Yuting; He, Zhili; Li, Guanghe; Zhou, Jizhong

    2009-01-30

    GeoChip is a comprehensive functional gene array that targets key functional genes involved in the geochemical cycling of N, C, and P, sulfate reduction, metal resistance and reduction, and contaminant degradation. Studies have shown the GeoChip to be a sensitive, specific, and high-throughput tool for microbial community analysis that has the power to link geochemical processes with microbial community structure. However, several challenges remain regarding the development and applications of microarrays for microbial community analysis.

  12. Development of Microfluidic Systems Enabling High-Throughput Single-Cell Protein Characterization

    Fan, Beiyuan; Li, Xiufeng; Chen, Deyong; Peng, Hongshang; Wang, Junbo; Chen, Jian

    2016-01-01

    This article reviews recent developments in microfluidic systems enabling high-throughput characterization of single-cell proteins. Four key perspectives of microfluidic platforms are included in this review: (1) microfluidic fluorescent flow cytometry; (2) droplet based microfluidic flow cytometry; (3) large-array micro wells (microengraving); and (4) large-array micro chambers (barcode microchips). We examine the advantages and limitations of each technique and discuss future research oppor...

  13. Fluorescence-based high-throughput screening of dicer cleavage activity

    Podolská, Kateřina; Sedlák, David; Bartůněk, Petr; Svoboda, Petr

    2014-01-01

    Roč. 19, č. 3 (2014), s. 417-426 ISSN 1087-0571 R&D Projects: GA ČR GA13-29531S; GA MŠk(CZ) LC06077; GA MŠk LM2011022 Grant - others:EMBO(DE) 1483 Institutional support: RVO:68378050 Keywords : Dicer * siRNA * high-throughput screening Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.423, year: 2014

  14. High-throughput screening of tick-borne pathogens in Europe

    Michelet, Lorraine; Delannoy, Sabine; Devillers, Elodie

    2014-01-01

    was conducted on 7050 Ixodes ricinus nymphs collected from France, Denmark, and the Netherlands using a powerful new high-throughput approach. This advanced methodology permitted the simultaneous detection of 25 bacterial, and 12 parasitic species (including; Borrelia, Anaplasma, Ehrlichia, Rickettsia......, Bartonella, Candidatus Neoehrlichia, Coxiella, Francisella, Babesia, and Theileria genus) across 94 samples. We successfully determined the prevalence of expected (Borrelia burgdorferi sensu lato, Anaplasma phagocytophilum, Rickettsia helvetica, Candidatus Neoehrlichia mikurensis, Babesia divergens, Babesia...

  15. Targeted DNA Methylation Analysis by High Throughput Sequencing in Porcine Peri-attachment Embryos

    MORRILL, Benson H.; COX, Lindsay; WARD, Anika; HEYWOOD, Sierra; PRATHER, Randall S.; ISOM, S. Clay

    2013-01-01

    Abstract The purpose of this experiment was to implement and evaluate the effectiveness of a next-generation sequencing-based method for DNA methylation analysis in porcine embryonic samples. Fourteen discrete genomic regions were amplified by PCR using bisulfite-converted genomic DNA derived from day 14 in vivo-derived (IVV) and parthenogenetic (PA) porcine embryos as template DNA. Resulting PCR products were subjected to high-throughput sequencing using the Illumina Genome Analyzer IIx plat...

  16. High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide

    Hyeonhu Bae; Minwoo Park; Byungryul Jang; Yura Kang; Jinwoo Park; Hosik Lee; Haegeun Chung; ChiHye Chung; Suklyun Hong; Yongkyung Kwon; Boris I. Yakobson; Hoonkyung Lee

    2016-01-01

    Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures...

  17. High Throughput Single-cell and Multiple-cell Micro-encapsulation

    Lagus, Todd P.; Edd, Jon F.

    2012-01-01

    Microfluidic encapsulation methods have been previously utilized to capture cells in picoliter-scale aqueous, monodisperse drops, providing confinement from a bulk fluid environment with applications in high throughput screening, cytometry, and mass spectrometry. We describe a method to not only encapsulate single cells, but to repeatedly capture a set number of cells (here we demonstrate one- and two-cell encapsulation) to study both isolation and the interactions between cells in groups of ...

  18. High-throughput micro-scale cultivations and chromatography modeling: Powerful tools for integrated process development.

    Baumann, Pascal; Hahn, Tobias; Hubbuch, Jürgen

    2015-10-01

    Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance. © 2015 Wiley Periodicals, Inc.

  19. Modular high-throughput test stand for versatile screening of thin-film materials libraries

    Thienhaus, Sigurd; Hamann, Sven; Ludwig, Alfred

    2011-01-01

    Versatile high-throughput characterization tools are required for the development of new materials using combinatorial techniques. Here, we describe a modular, high-throughput test stand for the screening of thin-film materials libraries, which can carry out automated electrical, magnetic and magnetoresistance measurements in the temperature range of −40 to 300 °C. As a proof of concept, we measured the temperature-dependent resistance of Fe–Pd–Mn ferromagnetic shape-memory alloy materials libraries, revealing reversible martensitic transformations and the associated transformation temperatures. Magneto-optical screening measurements of a materials library identify ferromagnetic samples, whereas resistivity maps support the discovery of new phases. A distance sensor in the same setup allows stress measurements in materials libraries deposited on cantilever arrays. A combination of these methods offers a fast and reliable high-throughput characterization technology for searching for new materials. Using this approach, a composition region has been identified in the Fe–Pd–Mn system that combines ferromagnetism and martensitic transformation.

  20. High throughput electrospinning of high-quality nanofibers via an aluminum disk spinneret

    Zheng, Guokuo

    In this work, a simple and efficient needleless high throughput electrospinning process using an aluminum disk spinneret with 24 holes is described. Electrospun mats produced by this setup consisted of fine fibers (nano-sized) of the highest quality while the productivity (yield) was many times that obtained from conventional single-needle electrospinning. The goal was to produce scaled-up amounts of the same or better quality nanofibers under variable concentration, voltage, and the working distance than those produced with the single needle lab setting. The fiber mats produced were either polymer or ceramic (such as molybdenum trioxide nanofibers). Through experimentation the optimum process conditions were defined to be: 24 kilovolt, a distance to collector of 15cm. More diluted solutions resulted in smaller diameter fibers. Comparing the morphologies of the nanofibers of MoO3 produced by both the traditional and the high throughput set up it was found that they were very similar. Moreover, the nanofibers production rate is nearly 10 times than that of traditional needle electrospinning. Thus, the high throughput process has the potential to become an industrial nanomanufacturing process and the materials processed by it may be used as filtration devices, in tissue engineering, and as sensors.

  1. The application of the high throughput sequencing technology in the transposable elements.

    Liu, Zhen; Xu, Jian-hong

    2015-09-01

    High throughput sequencing technology has dramatically improved the efficiency of DNA sequencing, and decreased the costs to a great extent. Meanwhile, this technology usually has advantages of better specificity, higher sensitivity and accuracy. Therefore, it has been applied to the research on genetic variations, transcriptomics and epigenomics. Recently, this technology has been widely employed in the studies of transposable elements and has achieved fruitful results. In this review, we summarize the application of high throughput sequencing technology in the fields of transposable elements, including the estimation of transposon content, preference of target sites and distribution, insertion polymorphism and population frequency, identification of rare copies, transposon horizontal transfers as well as transposon tagging. We also briefly introduce the major common sequencing strategies and algorithms, their advantages and disadvantages, and the corresponding solutions. Finally, we envision the developing trends of high throughput sequencing technology, especially the third generation sequencing technology, and its application in transposon studies in the future, hopefully providing a comprehensive understanding and reference for related scientific researchers.

  2. Evaluation of Capacity on a High Throughput Vol-oxidizer for Operability

    Kim, Young Hwan; Park, Geun Il; Lee, Jung Won; Jung, Jae Hoo; Kim, Ki Ho; Lee, Yong Soon; Lee, Do Youn; Kim, Su Sung

    2010-01-01

    KAERI is developing a pyro-process. As a piece of process equipment, a high throughput vol-oxidizer which can handle a several tens kg HM/batch was developed to supply U 3 O 8 powders to an electrolytic reduction(ER) reactor. To increase the reduction yield, UO 2 pellets should be converted into uniform powders. In this paper, we aim at the evaluation of a high throughput vol-oxidizer for operability. The evaluation consisted of 3 targets, a mechanical motion test, a heating test and hull separation test. In order to test a high throughput vol-oxidizer, By using a control system, mechanical motion tests of the vol-oxidizer were conducted, and heating rates were analyzed. Also the separation tests of hulls for recovery rate were conducted. The test results of the vol-oxidizer are going to be applied for operability. A study on the characteristics of the volatile gas produced during a vol-oxidation process is not included in this study

  3. A rapid enzymatic assay for high-throughput screening of adenosine-producing strains

    Dong, Huina; Zu, Xin; Zheng, Ping; Zhang, Dawei

    2015-01-01

    Adenosine is a major local regulator of tissue function and industrially useful as precursor for the production of medicinal nucleoside substances. High-throughput screening of adenosine overproducers is important for industrial microorganism breeding. An enzymatic assay of adenosine was developed by combined adenosine deaminase (ADA) with indophenol method. The ADA catalyzes the cleavage of adenosine to inosine and NH3, the latter can be accurately determined by indophenol method. The assay system was optimized to deliver a good performance and could tolerate the addition of inorganic salts and many nutrition components to the assay mixtures. Adenosine could be accurately determined by this assay using 96-well microplates. Spike and recovery tests showed that this assay can accurately and reproducibly determine increases in adenosine in fermentation broth without any pretreatment to remove proteins and potentially interfering low-molecular-weight molecules. This assay was also applied to high-throughput screening for high adenosine-producing strains. The high selectivity and accuracy of the ADA assay provides rapid and high-throughput analysis of adenosine in large numbers of samples. PMID:25580842

  4. A priori Considerations When Conducting High-Throughput Amplicon-Based Sequence Analysis

    Aditi Sengupta

    2016-03-01

    Full Text Available Amplicon-based sequencing strategies that include 16S rRNA and functional genes, alongside “meta-omics” analyses of communities of microorganisms, have allowed researchers to pose questions and find answers to “who” is present in the environment and “what” they are doing. Next-generation sequencing approaches that aid microbial ecology studies of agricultural systems are fast gaining popularity among agronomy, crop, soil, and environmental science researchers. Given the rapid development of these high-throughput sequencing techniques, researchers with no prior experience will desire information about the best practices that can be used before actually starting high-throughput amplicon-based sequence analyses. We have outlined items that need to be carefully considered in experimental design, sampling, basic bioinformatics, sequencing of mock communities and negative controls, acquisition of metadata, and in standardization of reaction conditions as per experimental requirements. Not all considerations mentioned here may pertain to a particular study. The overall goal is to inform researchers about considerations that must be taken into account when conducting high-throughput microbial DNA sequencing and sequences analysis.

  5. High-throughput purification of recombinant proteins using self-cleaving intein tags.

    Coolbaugh, M J; Shakalli Tang, M J; Wood, D W

    2017-01-01

    High throughput methods for recombinant protein production using E. coli typically involve the use of affinity tags for simple purification of the protein of interest. One drawback of these techniques is the occasional need for tag removal before study, which can be hard to predict. In this work, we demonstrate two high throughput purification methods for untagged protein targets based on simple and cost-effective self-cleaving intein tags. Two model proteins, E. coli beta-galactosidase (βGal) and superfolder green fluorescent protein (sfGFP), were purified using self-cleaving versions of the conventional chitin-binding domain (CBD) affinity tag and the nonchromatographic elastin-like-polypeptide (ELP) precipitation tag in a 96-well filter plate format. Initial tests with shake flask cultures confirmed that the intein purification scheme could be scaled down, with >90% pure product generated in a single step using both methods. The scheme was then validated in a high throughput expression platform using 24-well plate cultures followed by purification in 96-well plates. For both tags and with both target proteins, the purified product was consistently obtained in a single-step, with low well-to-well and plate-to-plate variability. This simple method thus allows the reproducible production of highly pure untagged recombinant proteins in a convenient microtiter plate format. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Infra-red thermography for high throughput field phenotyping in Solanum tuberosum.

    Ankush Prashar

    Full Text Available The rapid development of genomic technology has made high throughput genotyping widely accessible but the associated high throughput phenotyping is now the major limiting factor in genetic analysis of traits. This paper evaluates the use of thermal imaging for the high throughput field phenotyping of Solanum tuberosum for differences in stomatal behaviour. A large multi-replicated trial of a potato mapping population was used to investigate the consistency in genotypic rankings across different trials and across measurements made at different times of day and on different days. The results confirmed a high degree of consistency between the genotypic rankings based on relative canopy temperature on different occasions. Genotype discrimination was enhanced both through normalising data by expressing genotype temperatures as differences from image means and through the enhanced replication obtained by using overlapping images. A Monte Carlo simulation approach was used to confirm the magnitude of genotypic differences that it is possible to discriminate. The results showed a clear negative association between canopy temperature and final tuber yield for this population, when grown under ample moisture supply. We have therefore established infrared thermography as an easy, rapid and non-destructive screening method for evaluating large population trials for genetic analysis. We also envisage this approach as having great potential for evaluating plant response to stress under field conditions.

  7. Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

    Gavin C. Bowick

    2011-05-01

    Full Text Available The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

  8. Optical tools for high-throughput screening of abrasion resistance of combinatorial libraries of organic coatings

    Potyrailo, Radislav A.; Chisholm, Bret J.; Olson, Daniel R.; Brennan, Michael J.; Molaison, Chris A.

    2002-02-01

    Design, validation, and implementation of an optical spectroscopic system for high-throughput analysis of combinatorially developed protective organic coatings are reported. Our approach replaces labor-intensive coating evaluation steps with an automated system that rapidly analyzes 8x6 arrays of coating elements that are deposited on a plastic substrate. Each coating element of the library is 10 mm in diameter and 2 to 5 micrometers thick. Performance of coatings is evaluated with respect to their resistance to wear abrasion because this parameter is one of the primary considerations in end-use applications. Upon testing, the organic coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Coatings are abraded using industry-accepted abrasion test methods at single-or multiple-abrasion conditions, followed by high- throughput analysis of abrasion-induced light scatter. The developed automated system is optimized for the analysis of diffusively scattered light that corresponds to 0 to 30% haze. System precision of 0.1 to 2.5% relative standard deviation provides capability for the reliable ranking of coatings performance. While the system was implemented for high-throughput screening of combinatorially developed organic protective coatings for automotive applications, it can be applied to a variety of other applications where materials ranking can be achieved using optical spectroscopic tools.

  9. Assessing Morphological and Physiological Properties of Forest Species Using High Throughput Plant Phenotyping and Imaging Techniques

    Mazis, A.; Hiller, J.; Morgan, P.; Awada, T.; Stoerger, V.

    2017-12-01

    High throughput plant phenotyping is increasingly being used to assess morphological and biophysical traits of economically important crops in agriculture. In this study, the potential application of this technique in natural resources management, through the characterization of woody plants regeneration, establishment, growth, and responses to water and nutrient manipulations was assessed. Two woody species were selected for this study, Quercus prinoides and Quercus bicolor. Seeds were collected from trees growing at the edge of their natural distribution in Nebraska and Missouri, USA. Seeds were germinated in the greenhouse and transferred to the Nebraska Innovation Campus Lemnatec3D High Throughput facility at the University of Nebraska-Lincoln. Seedlings subjected to water and N manipulations, were imaged twice or three times a week using four cameras (Visible, Fluorescence, Infrared and Hyperspectral), throughout the growing season. Traditional leaf to plant levels ecophysiological measurements were concurrently acquired to assess the relationship between these two techniques. These include gas exchange (LI 6400 and LI 6800, LICOR Inc., Lincoln NE), chlorophyll content, optical characteristics (Ocean Optics USB200), water and osmotic potentials, leaf area and weight and carbon isotope ratio. In the presentation, we highlight results on the potential use of high throughput plant phenotyping techniques to assess the morphology and physiology of woody species including responses to water availability and nutrient manipulation, and its broader application under field conditions and natural resources management. Also, we explore the different capabilities imaging provides us for modeling the plant physiological and morphological growth and how it can complement the current techniques

  10. A High-Throughput Biological Calorimetry Core: Steps to Startup, Run, and Maintain a Multiuser Facility.

    Yennawar, Neela H; Fecko, Julia A; Showalter, Scott A; Bevilacqua, Philip C

    2016-01-01

    Many labs have conventional calorimeters where denaturation and binding experiments are setup and run one at a time. While these systems are highly informative to biopolymer folding and ligand interaction, they require considerable manual intervention for cleaning and setup. As such, the throughput for such setups is limited typically to a few runs a day. With a large number of experimental parameters to explore including different buffers, macromolecule concentrations, temperatures, ligands, mutants, controls, replicates, and instrument tests, the need for high-throughput automated calorimeters is on the rise. Lower sample volume requirements and reduced user intervention time compared to the manual instruments have improved turnover of calorimetry experiments in a high-throughput format where 25 or more runs can be conducted per day. The cost and efforts to maintain high-throughput equipment typically demands that these instruments be housed in a multiuser core facility. We describe here the steps taken to successfully start and run an automated biological calorimetry facility at Pennsylvania State University. Scientists from various departments at Penn State including Chemistry, Biochemistry and Molecular Biology, Bioengineering, Biology, Food Science, and Chemical Engineering are benefiting from this core facility. Samples studied include proteins, nucleic acids, sugars, lipids, synthetic polymers, small molecules, natural products, and virus capsids. This facility has led to higher throughput of data, which has been leveraged into grant support, attracting new faculty hire and has led to some exciting publications. © 2016 Elsevier Inc. All rights reserved.

  11. PCR cycles above routine numbers do not compromise high-throughput DNA barcoding results.

    Vierna, J; Doña, J; Vizcaíno, A; Serrano, D; Jovani, R

    2017-10-01

    High-throughput DNA barcoding has become essential in ecology and evolution, but some technical questions still remain. Increasing the number of PCR cycles above the routine 20-30 cycles is a common practice when working with old-type specimens, which provide little amounts of DNA, or when facing annealing issues with the primers. However, increasing the number of cycles can raise the number of artificial mutations due to polymerase errors. In this work, we sequenced 20 COI libraries in the Illumina MiSeq platform. Libraries were prepared with 40, 45, 50, 55, and 60 PCR cycles from four individuals belonging to four species of four genera of cephalopods. We found no relationship between the number of PCR cycles and the number of mutations despite using a nonproofreading polymerase. Moreover, even when using a high number of PCR cycles, the resulting number of mutations was low enough not to be an issue in the context of high-throughput DNA barcoding (but may still remain an issue in DNA metabarcoding due to chimera formation). We conclude that the common practice of increasing the number of PCR cycles should not negatively impact the outcome of a high-throughput DNA barcoding study in terms of the occurrence of point mutations.

  12. A high throughput array microscope for the mechanical characterization of biomaterials

    Cribb, Jeremy; Osborne, Lukas D.; Hsiao, Joe Ping-Lin; Vicci, Leandra; Meshram, Alok; O'Brien, E. Tim; Spero, Richard Chasen; Taylor, Russell; Superfine, Richard

    2015-02-01

    In the last decade, the emergence of high throughput screening has enabled the development of novel drug therapies and elucidated many complex cellular processes. Concurrently, the mechanobiology community has developed tools and methods to show that the dysregulation of biophysical properties and the biochemical mechanisms controlling those properties contribute significantly to many human diseases. Despite these advances, a complete understanding of the connection between biomechanics and disease will require advances in instrumentation that enable parallelized, high throughput assays capable of probing complex signaling pathways, studying biology in physiologically relevant conditions, and capturing specimen and mechanical heterogeneity. Traditional biophysical instruments are unable to meet this need. To address the challenge of large-scale, parallelized biophysical measurements, we have developed an automated array high-throughput microscope system that utilizes passive microbead diffusion to characterize mechanical properties of biomaterials. The instrument is capable of acquiring data on twelve-channels simultaneously, where each channel in the system can independently drive two-channel fluorescence imaging at up to 50 frames per second. We employ this system to measure the concentration-dependent apparent viscosity of hyaluronan, an essential polymer found in connective tissue and whose expression has been implicated in cancer progression.

  13. High-throughput gene expression profiling of memory differentiation in primary human T cells

    Russell Kate

    2008-08-01

    Full Text Available Abstract Background The differentiation of naive T and B cells into memory lymphocytes is essential for immunity to pathogens. Therapeutic manipulation of this cellular differentiation program could improve vaccine efficacy and the in vitro expansion of memory cells. However, chemical screens to identify compounds that induce memory differentiation have been limited by 1 the lack of reporter-gene or functional assays that can distinguish naive and memory-phenotype T cells at high throughput and 2 a suitable cell-line representative of naive T cells. Results Here, we describe a method for gene-expression based screening that allows primary naive and memory-phenotype lymphocytes to be discriminated based on complex genes signatures corresponding to these differentiation states. We used ligation-mediated amplification and a fluorescent, bead-based detection system to quantify simultaneously 55 transcripts representing naive and memory-phenotype signatures in purified populations of human T cells. The use of a multi-gene panel allowed better resolution than any constituent single gene. The method was precise, correlated well with Affymetrix microarray data, and could be easily scaled up for high-throughput. Conclusion This method provides a generic solution for high-throughput differentiation screens in primary human T cells where no single-gene or functional assay is available. This screening platform will allow the identification of small molecules, genes or soluble factors that direct memory differentiation in naive human lymphocytes.

  14. A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information.

    Benjamin, Ashlee M; Thompson, J Will; Soderblom, Erik J; Geromanos, Scott J; Henao, Ricardo; Kraus, Virginia B; Moseley, M Arthur; Lucas, Joseph E

    2013-12-16

    The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples. We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

  15. Optimizing transformations for automated, high throughput analysis of flow cytometry data.

    Finak, Greg; Perez, Juan-Manuel; Weng, Andrew; Gottardo, Raphael

    2010-11-04

    In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce

  16. Optimizing transformations for automated, high throughput analysis of flow cytometry data

    Weng Andrew

    2010-11-01

    Full Text Available Abstract Background In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. Results We compare the performance of parameter-optimized and default-parameter (in flowCore data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter

  17. A cell-based high-throughput screening assay for radiation susceptibility using automated cell counting

    Hodzic, Jasmina; Dingjan, Ilse; Maas, Mariëlle JP; Meulen-Muileman, Ida H van der; Menezes, Renee X de; Heukelom, Stan; Verheij, Marcel; Gerritsen, Winald R; Geldof, Albert A; Triest, Baukelien van; Beusechem, Victor W van

    2015-01-01

    Radiotherapy is one of the mainstays in the treatment for cancer, but its success can be limited due to inherent or acquired resistance. Mechanisms underlying radioresistance in various cancers are poorly understood and available radiosensitizers have shown only modest clinical benefit. There is thus a need to identify new targets and drugs for more effective sensitization of cancer cells to irradiation. Compound and RNA interference high-throughput screening technologies allow comprehensive enterprises to identify new agents and targets for radiosensitization. However, the gold standard assay to investigate radiosensitivity of cancer cells in vitro, the colony formation assay (CFA), is unsuitable for high-throughput screening. We developed a new high-throughput screening method for determining radiation susceptibility. Fast and uniform irradiation of batches up to 30 microplates was achieved using a Perspex container and a clinically employed linear accelerator. The readout was done by automated counting of fluorescently stained nuclei using the Acumen eX3 laser scanning cytometer. Assay performance was compared to that of the CFA and the CellTiter-Blue homogeneous uniform-well cell viability assay. The assay was validated in a whole-genome siRNA library screening setting using PC-3 prostate cancer cells. On 4 different cancer cell lines, the automated cell counting assay produced radiation dose response curves that followed a linear-quadratic equation and that exhibited a better correlation to the results of the CFA than did the cell viability assay. Moreover, the cell counting assay could be used to detect radiosensitization by silencing DNA-PKcs or by adding caffeine. In a high-throughput screening setting, using 4 Gy irradiated and control PC-3 cells, the effects of DNA-PKcs siRNA and non-targeting control siRNA could be clearly discriminated. We developed a simple assay for radiation susceptibility that can be used for high-throughput screening. This will aid

  18. A high-throughput readout architecture based on PCI-Express Gen3 and DirectGMA technology

    Rota, L.; Vogelgesang, M.; Perez, L.E. Ardila; Caselle, M.; Chilingaryan, S.; Dritschler, T.; Zilio, N.; Kopmann, A.; Balzer, M.; Weber, M.

    2016-01-01

    Modern physics experiments produce multi-GB/s data rates. Fast data links and high performance computing stages are required for continuous data acquisition and processing. Because of their intrinsic parallelism and computational power, GPUs emerged as an ideal solution to process this data in high performance computing applications. In this paper we present a high-throughput platform based on direct FPGA-GPU communication. The architecture consists of a Direct Memory Access (DMA) engine compatible with the Xilinx PCI-Express core, a Linux driver for register access, and high- level software to manage direct memory transfers using AMD's DirectGMA technology. Measurements with a Gen3 x8 link show a throughput of 6.4 GB/s for transfers to GPU memory and 6.6 GB/s to system memory. We also assess the possibility of using the architecture in low latency systems: preliminary measurements show a round-trip latency as low as 1 μs for data transfers to system memory, while the additional latency introduced by OpenCL scheduling is the current limitation for GPU based systems. Our implementation is suitable for real-time DAQ system applications ranging from photon science and medical imaging to High Energy Physics (HEP) systems

  19. beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix types.

    Aaron T L Lun

    2018-05-01

    Full Text Available Biological experiments involving genomics or other high-throughput assays typically yield a data matrix that can be explored and analyzed using the R programming language with packages from the Bioconductor project. Improvements in the throughput of these assays have resulted in an explosion of data even from routine experiments, which poses a challenge to the existing computational infrastructure for statistical data analysis. For example, single-cell RNA sequencing (scRNA-seq experiments frequently generate large matrices containing expression values for each gene in each cell, requiring sparse or file-backed representations for memory-efficient manipulation in R. These alternative representations are not easily compatible with high-performance C++ code used for computationally intensive tasks in existing R/Bioconductor packages. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with dense, sparse and file-backed matrices, amongst others. We evaluated the performance of beachmat for accessing data from each matrix representation using both simulated and real scRNA-seq data, and defined a clear memory/speed trade-off to motivate the choice of an appropriate representation. We also demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large scRNA-seq data set.

  20. beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix types.

    Lun, Aaron T L; Pagès, Hervé; Smith, Mike L

    2018-05-01

    Biological experiments involving genomics or other high-throughput assays typically yield a data matrix that can be explored and analyzed using the R programming language with packages from the Bioconductor project. Improvements in the throughput of these assays have resulted in an explosion of data even from routine experiments, which poses a challenge to the existing computational infrastructure for statistical data analysis. For example, single-cell RNA sequencing (scRNA-seq) experiments frequently generate large matrices containing expression values for each gene in each cell, requiring sparse or file-backed representations for memory-efficient manipulation in R. These alternative representations are not easily compatible with high-performance C++ code used for computationally intensive tasks in existing R/Bioconductor packages. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with dense, sparse and file-backed matrices, amongst others. We evaluated the performance of beachmat for accessing data from each matrix representation using both simulated and real scRNA-seq data, and defined a clear memory/speed trade-off to motivate the choice of an appropriate representation. We also demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large scRNA-seq data set.