WorldWideScience

Sample records for high-throughput template-based modeling

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  4. Evaluation of template-based models in CASP8 with standard measures

    KAUST Repository

    Cozzetto, Domenico; Kryshtafovych, Andriy; Fidelis, Krzysztof; Moult, John; Rost, Burkhard; Tramontano, Anna

    2009-01-01

    The strategy for evaluating template-based models submitted to CASP has continuously evolved from CASP1 to CASP5, leading to a standard procedure that has been used in all subsequent editions. The established approach includes methods

  5. Evaluation of template-based models in CASP8 with standard measures

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The strategy for evaluating template-based models submitted to CASP has continuously evolved from CASP1 to CASP5, leading to a standard procedure that has been used in all subsequent editions. The established approach includes methods for calculating the quality of each individual model, for assigning scores based on the distribution of the results for each target and for computing the statistical significance of the differences in scores between prediction methods. These data are made available to the assessor of the template-based modeling category, who uses them as a starting point for further evaluations and analyses. This article describes the detailed workflow of the procedure, provides justifications for a number of choices that are customarily made for CASP data evaluation, and reports the results of the analysis of template-based predictions at CASP8.

  6. High-throughput landslide modelling using computational grids

    Science.gov (United States)

    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

  7. Modeling Disordered Materials with a High Throughput ab-initio Approach

    Science.gov (United States)

    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

  8. High-throughput micro-scale cultivations and chromatography modeling: Powerful tools for integrated process development.

    Science.gov (United States)

    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.

  9. Refinement of protein termini in template-based modeling using conformational space annealing.

    Science.gov (United States)

    Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

    2011-09-01

    The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

  10. Estimating Margin of Exposure to Thyroid Peroxidase Inhibitors Using High-Throughput in vitro Data, High-Throughput Exposure Modeling, and Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling

    Science.gov (United States)

    Leonard, Jeremy A.; Tan, Yu-Mei; Gilbert, Mary; Isaacs, Kristin; El-Masri, Hisham

    2016-01-01

    Some pharmaceuticals and environmental chemicals bind the thyroid peroxidase (TPO) enzyme and disrupt thyroid hormone production. The potential for TPO inhibition is a function of both the binding affinity and concentration of the chemical within the thyroid gland. The former can be determined through in vitro assays, and the latter is influenced by pharmacokinetic properties, along with environmental exposure levels. In this study, a physiologically based pharmacokinetic (PBPK) model was integrated with a pharmacodynamic (PD) model to establish internal doses capable of inhibiting TPO in relation to external exposure levels predicted through exposure modeling. The PBPK/PD model was evaluated using published serum or thyroid gland chemical concentrations or circulating thyroxine (T4) and triiodothyronine (T3) hormone levels measured in rats and humans. After evaluation, the model was used to estimate human equivalent intake doses resulting in reduction of T4 and T3 levels by 10% (ED10) for 6 chemicals of varying TPO-inhibiting potencies. These chemicals were methimazole, 6-propylthiouracil, resorcinol, benzophenone-2, 2-mercaptobenzothiazole, and triclosan. Margin of exposure values were estimated for these chemicals using the ED10 and predicted population exposure levels for females of child-bearing age. The modeling approach presented here revealed that examining hazard or exposure alone when prioritizing chemicals for risk assessment may be insufficient, and that consideration of pharmacokinetic properties is warranted. This approach also provides a mechanism for integrating in vitro data, pharmacokinetic properties, and exposure levels predicted through high-throughput means when interpreting adverse outcome pathways based on biological responses. PMID:26865668

  11. Drosophila melanogaster as a High-Throughput Model for Host–Microbiota Interactions

    Directory of Open Access Journals (Sweden)

    Gregor Reid

    2017-04-01

    Full Text Available Microbiota research often assumes that differences in abundance and identity of microorganisms have unique influences on host physiology. To test this concept mechanistically, germ-free mice are colonized with microbial communities to assess causation. Due to the cost, infrastructure challenges, and time-consuming nature of germ-free mouse models, an alternative approach is needed to investigate host–microbial interactions. Drosophila melanogaster (fruit flies can be used as a high throughput in vivo screening model of host–microbiome interactions as they are affordable, convenient, and replicable. D. melanogaster were essential in discovering components of the innate immune response to pathogens. However, axenic D. melanogaster can easily be generated for microbiome studies without the need for ethical considerations. The simplified microbiota structure enables researchers to evaluate permutations of how each microbial species within the microbiota contribute to host phenotypes of interest. This enables the possibility of thorough strain-level analysis of host and microbial properties relevant to physiological outcomes. Moreover, a wide range of mutant D. melanogaster strains can be affordably obtained from public stock centers. Given this, D. melanogaster can be used to identify candidate mechanisms of host–microbe symbioses relevant to pathogen exclusion, innate immunity modulation, diet, xenobiotics, and probiotic/prebiotic properties in a high throughput manner. This perspective comments on the most promising areas of microbiota research that could immediately benefit from using the D. melanogaster model.

  12. Drosophila melanogaster as a High-Throughput Model for Host-Microbiota Interactions.

    Science.gov (United States)

    Trinder, Mark; Daisley, Brendan A; Dube, Josh S; Reid, Gregor

    2017-01-01

    Microbiota research often assumes that differences in abundance and identity of microorganisms have unique influences on host physiology. To test this concept mechanistically, germ-free mice are colonized with microbial communities to assess causation. Due to the cost, infrastructure challenges, and time-consuming nature of germ-free mouse models, an alternative approach is needed to investigate host-microbial interactions. Drosophila melanogaster (fruit flies) can be used as a high throughput in vivo screening model of host-microbiome interactions as they are affordable, convenient, and replicable. D. melanogaster were essential in discovering components of the innate immune response to pathogens. However, axenic D. melanogaster can easily be generated for microbiome studies without the need for ethical considerations. The simplified microbiota structure enables researchers to evaluate permutations of how each microbial species within the microbiota contribute to host phenotypes of interest. This enables the possibility of thorough strain-level analysis of host and microbial properties relevant to physiological outcomes. Moreover, a wide range of mutant D. melanogaster strains can be affordably obtained from public stock centers. Given this, D. melanogaster can be used to identify candidate mechanisms of host-microbe symbioses relevant to pathogen exclusion, innate immunity modulation, diet, xenobiotics, and probiotic/prebiotic properties in a high throughput manner. This perspective comments on the most promising areas of microbiota research that could immediately benefit from using the D. melanogaster model.

  13. Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis.

    Science.gov (United States)

    Li, Ben; Li, Yunxiao; Qin, Zhaohui S

    2017-06-01

    Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical 'large p , small n ' problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package "adaptiveHM", which is freely available from https://github.com/benliemory/adaptiveHM.

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

    CERN Document Server

    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...

  15. SNP calling using genotype model selection on high-throughput sequencing data

    KAUST Repository

    You, Na

    2012-01-16

    Motivation: A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base-calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for.Results: A novel method of consensus and SNP calling, Genotype Model Selection (GeMS), is given which accounts for the errors that occur during the preparation of the genomic sample. Simulations and real data analyses indicate that GeMS has the best performance balance of sensitivity and positive predictive value among the tested SNP callers. © The Author 2012. Published by Oxford University Press. All rights reserved.

  16. High-throughput screen for novel antimicrobials using a whole animal infection model.

    Science.gov (United States)

    Moy, Terence I; Conery, Annie L; Larkins-Ford, Jonah; Wu, Gang; Mazitschek, Ralph; Casadei, Gabriele; Lewis, Kim; Carpenter, Anne E; Ausubel, Frederick M

    2009-07-17

    The nematode Caenorhabditis elegans is a unique whole animal model system for identifying small molecules with in vivo anti-infective properties. C. elegans can be infected with a broad range of human pathogens, including Enterococcus faecalis, an important human nosocomial pathogen. Here, we describe an automated, high-throughput screen of 37,200 compounds and natural product extracts for those that enhance survival of C. elegans infected with E. faecalis. Using a robot to dispense live, infected animals into 384-well plates and automated microscopy and image analysis, we identified 28 compounds and extracts not previously reported to have antimicrobial properties, including six structural classes that cure infected C. elegans animals but do not affect the growth of the pathogen in vitro, thus acting by a mechanism of action distinct from antibiotics currently in clinical use.

  17. A High Throughput Model of Post-Traumatic Osteoarthritis using Engineered Cartilage Tissue Analogs

    Science.gov (United States)

    Mohanraj, Bhavana; Meloni, Gregory R.; Mauck, Robert L.; Dodge, George R.

    2014-01-01

    (1) Objective A number of in vitro models of post-traumatic osteoarthritis (PTOA) have been developed to study the effect of mechanical overload on the processes that regulate cartilage degeneration. While such frameworks are critical for the identification therapeutic targets, existing technologies are limited in their throughput capacity. Here, we validate a test platform for high-throughput mechanical injury incorporating engineered cartilage. (2) Method We utilized a high throughput mechanical testing platform to apply injurious compression to engineered cartilage and determined their strain and strain rate dependent responses to injury. Next, we validated this response by applying the same injury conditions to cartilage explants. Finally, we conducted a pilot screen of putative PTOA therapeutic compounds. (3) Results Engineered cartilage response to injury was strain dependent, with a 2-fold increase in GAG loss at 75% compared to 50% strain. Extensive cell death was observed adjacent to fissures, with membrane rupture corroborated by marked increases in LDH release. Testing of established PTOA therapeutics showed that pan-caspase inhibitor (ZVF) was effective at reducing cell death, while the amphiphilic polymer (P188) and the free-radical scavenger (NAC) reduced GAG loss as compared to injury alone. (4) Conclusions The injury response in this engineered cartilage model replicated key features of the response from cartilage explants, validating this system for application of physiologically relevant injurious compression. This study establishes a novel tool for the discovery of mechanisms governing cartilage injury, as well as a screening platform for the identification of new molecules for the treatment of PTOA. PMID:24999113

  18. Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening.

    Science.gov (United States)

    Tong, Zhi-Bin; Hogberg, Helena; Kuo, David; Sakamuru, Srilatha; Xia, Menghang; Smirnova, Lena; Hartung, Thomas; Gerhold, David

    2017-02-01

    More than 75 000 man-made chemicals contaminate the environment; many of these have not been tested for toxicities. These chemicals demand quantitative high-throughput screening assays to assess them for causative roles in neurotoxicities, including Parkinson's disease and other neurodegenerative disorders. To facilitate high throughput screening for cytotoxicity to neurons, three human neuronal cellular models were compared: SH-SY5Y neuroblastoma cells, LUHMES conditionally-immortalized dopaminergic neurons, and Neural Stem Cells (NSC) derived from human fetal brain. These three cell lines were evaluated for rapidity and degree of differentiation, and sensitivity to 32 known or candidate neurotoxicants. First, expression of neural differentiation genes was assayed during a 7-day differentiation period. Of the three cell lines, LUHMES showed the highest gene expression of neuronal markers after differentiation. Both in the undifferentiated state and after 7 days of neuronal differentiation, LUHMES cells exhibited greater cytotoxic sensitivity to most of 32 suspected or known neurotoxicants than SH-SY5Y or NSCs. LUHMES cells were also unique in being more susceptible to several compounds in the differentiating state than in the undifferentiated state; including known neurotoxicants colchicine, methyl-mercury (II), and vincristine. Gene expression results suggest that differentiating LUHMES cells may be susceptible to apoptosis because they express low levels of anti-apoptotic genes BCL2 and BIRC5/survivin, whereas SH-SY5Y cells may be resistant to apoptosis because they express high levels of BCL2, BIRC5/survivin, and BIRC3 genes. Thus, LUHMES cells exhibited favorable characteristics for neuro-cytotoxicity screening: rapid differentiation into neurons that exhibit high level expression neuronal marker genes, and marked sensitivity of LUHMES cells to known neurotoxicants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  19. High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models.

    Science.gov (United States)

    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

  20. Risk-based high-throughput chemical screening and prioritization using exposure models and in vitro bioactivity assays

    DEFF Research Database (Denmark)

    Shin, Hyeong-Moo; Ernstoff, Alexi; Arnot, Jon

    2015-01-01

    We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify....../oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models....

  1. Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

    International Nuclear Information System (INIS)

    Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R.; Jijakli, Kenan; Salehi-Ashtiani, Kourosh

    2014-01-01

    Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

  2. Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

    Energy Technology Data Exchange (ETDEWEB)

    Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R. [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Jijakli, Kenan [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Engineering Division, Biofinery, Manhattan, KS (United States); Salehi-Ashtiani, Kourosh, E-mail: ksa3@nyu.edu [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates)

    2014-12-10

    Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

  3. High Throughput Screen for Novel Antimicrobials using a Whole Animal Infection Model

    Science.gov (United States)

    Moy, Terence I.; Conery, Annie L.; Larkins-Ford, Jonah; Wu, Gang; Mazitschek, Ralph; Casadei, Gabriele; Lewis, Kim; Carpenter, Anne E.; Ausubel, Frederick M.

    2009-01-01

    The nematode Caenorhabditis elegans is a unique whole animal model system for identifying small molecules with in vivo anti-infective properties. C. elegans can be infected with a broad range of human pathogens, including Enterococcus faecalis, an important human nosocomial pathogen with a mortality rate of up to 37% that is increasingly acquiring resistance to antibiotics. Here, we describe an automated, high throughput screen of 37,200 compounds and natural product extracts for those that enhance survival of C. elegans infected with E. faecalis. The screen uses a robot to accurately dispense live, infected animals into 384-well plates, and automated microscopy and image analysis to generate quantitative, high content data. We identified 28 compounds and extracts that were not previously reported to have antimicrobial properties, including 6 structural classes that cure infected C. elegans animals but do not affect the growth of the pathogen in vitro, thus acting by a mechanism of action distinct from antibiotics currently in clinical use. Our versatile and robust screening system can be easily adapted for other whole animal assays to probe a broad range of biological processes. PMID:19572548

  4. Neural progenitor cells as models for high-throughput screens of developmental neurotoxicity: State of the science

    NARCIS (Netherlands)

    Breier, J.M.; Gassmann, K.; Kayser, R.; Stegeman, H.; Groot, D.de; Fritsche, E.; Shafer, T.J.

    2010-01-01

    In vitro, high-throughput methods have been widely recommended as an approach to screen chemicals for the potential to cause developmental neurotoxicity and prioritize them for additional testing. The choice of cellular models for such an approach will have important ramifications for the accuracy,

  5. DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

    Science.gov (United States)

    Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L

    2013-08-26

    DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

  6. Insights into Sonogashira cross-coupling by high-throughput kinetics and descriptor modeling

    NARCIS (Netherlands)

    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.

  7. Understanding the general packing rearrangements required for successful template based modeling of protein structure from a CASP experiment.

    Science.gov (United States)

    Day, Ryan; Joo, Hyun; Chavan, Archana C; Lennox, Kristin P; Chen, Y Ann; Dahl, David B; Vannucci, Marina; Tsai, Jerry W

    2013-02-01

    As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. High throughput research and evaporation rate modeling for solvent screening for ethylcellulose barrier membranes in pharmaceutical applications.

    Science.gov (United States)

    Schoener, Cody A; Curtis-Fisk, Jaime L; Rogers, True L; Tate, Michael P

    2016-10-01

    Ethylcellulose is commonly dissolved in a solvent or formed into an aqueous dispersion and sprayed onto various dosage forms to form a barrier membrane to provide controlled release in pharmaceutical formulations. Due to the variety of solvents utilized in the pharmaceutical industry and the importance solvent can play on film formation and film strength it is critical to understand how solvent can influence these parameters. To systematically study a variety of solvent blends and how these solvent blends influence ethylcellulose film formation, physical and mechanical film properties and solution properties such as clarity and viscosity. Using high throughput capabilities and evaporation rate modeling, thirty-one different solvent blends composed of ethanol, isopropanol, acetone, methanol, and/or water were formulated, analyzed for viscosity and clarity, and narrowed down to four solvent blends. Brookfield viscosity, film casting, mechanical film testing and water permeation were also completed. High throughput analysis identified isopropanol/water, ethanol, ethanol/water and methanol/acetone/water as solvent blends with unique clarity and viscosity values. Evaporation rate modeling further rank ordered these candidates from excellent to poor interaction with ethylcellulose. Isopropanol/water was identified as the most suitable solvent blend for ethylcellulose due to azeotrope formation during evaporation, which resulted in a solvent-rich phase allowing the ethylcellulose polymer chains to remain maximally extended during film formation. Consequently, the highest clarity and most ductile films were formed. Employing high throughput capabilities paired with evaporation rate modeling allowed strong predictions between solvent interaction with ethylcellulose and mechanical film properties.

  9. High-throughput screening for novel anti-infectives using a C. elegans pathogenesis model.

    Science.gov (United States)

    Conery, Annie L; Larkins-Ford, Jonah; Ausubel, Frederick M; Kirienko, Natalia V

    2014-03-14

    In recent history, the nematode Caenorhabditis elegans has provided a compelling platform for the discovery of novel antimicrobial drugs. In this protocol, we present an automated, high-throughput C. elegans pathogenesis assay, which can be used to screen for anti-infective compounds that prevent nematodes from dying due to Pseudomonas aeruginosa. New antibiotics identified from such screens would be promising candidates for treatment of human infections, and also can be used as probe compounds to identify novel targets in microbial pathogenesis or host immunity. Copyright © 2014 John Wiley & Sons, Inc.

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

    Science.gov (United States)

    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

  11. High Throughput Facility

    Data.gov (United States)

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

  12. Using high throughput experimental data and in silico models to discover alternatives to toxic chromate corrosion inhibitors

    International Nuclear Information System (INIS)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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)

  14. Risk-based high-throughput chemical screening and prioritization using exposure models and in vitro bioactivity assays

    International Nuclear Information System (INIS)

    Shin, Hyeong-Moo; Ernstoff, Alexi; Csiszar, Susan A.

    2015-01-01

    We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate daily intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models

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

    Directory of Open Access Journals (Sweden)

    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

  16. Validation of visualized transgenic zebrafish as a high throughput model to assay bradycardia related cardio toxicity risk candidates.

    Science.gov (United States)

    Wen, Dingsheng; Liu, Aiming; Chen, Feng; Yang, Julin; Dai, Renke

    2012-10-01

    Drug-induced QT prolongation usually leads to torsade de pointes (TdP), thus for drugs in the early phase of development this risk should be evaluated. In the present study, we demonstrated a visualized transgenic zebrafish as an in vivo high-throughput model to assay the risk of drug-induced QT prolongation. Zebrafish larvae 48 h post-fertilization expressing green fluorescent protein in myocardium were incubated with compounds reported to induce QT prolongation or block the human ether-a-go-go-related gene (hERG) K⁺ current. The compounds sotalol, indapaminde, erythromycin, ofoxacin, levofloxacin, sparfloxacin and roxithromycin were additionally administrated by microinjection into the larvae yolk sac. The ventricle heart rate was recorded using the automatic monitoring system after incubation or microinjection. As a result, 14 out of 16 compounds inducing dog QT prolongation caused bradycardia in zebrafish. A similar result was observed with 21 out of 26 compounds which block hERG current. Among the 30 compounds which induced human QT prolongation, 25 caused bradycardia in this model. Thus, the risk of compounds causing bradycardia in this transgenic zebrafish correlated with that causing QT prolongation and hERG K⁺ current blockage in established models. The tendency that high logP values lead to high risk of QT prolongation in this model was indicated, and non-sensitivity of this model to antibacterial agents was revealed. These data suggest application of this transgenic zebrafish as a high-throughput model to screen QT prolongation-related cardio toxicity of the drug candidates. Copyright © 2012 John Wiley & Sons, Ltd.

  17. Understanding the stable boron clusters: A bond model and first-principles calculations based on high-throughput screening

    International Nuclear Information System (INIS)

    Xu, Shao-Gang; Liao, Ji-Hai; Zhao, Yu-Jun; Yang, Xiao-Bao

    2015-01-01

    The unique electronic property induced diversified structure of boron (B) cluster has attracted much interest from experimentalists and theorists. B 30–40 were reported to be planar fragments of triangular lattice with proper concentrations of vacancies recently. Here, we have performed high-throughput screening for possible B clusters through the first-principles calculations, including various shapes and distributions of vacancies. As a result, we have determined the structures of B n clusters with n = 30–51 and found a stable planar cluster of B 49 with a double-hexagon vacancy. Considering the 8-electron rule and the electron delocalization, a concise model for the distribution of the 2c–2e and 3c–2e bonds has been proposed to explain the stability of B planar clusters, as well as the reported B cages

  18. Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

    Science.gov (United States)

    Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

    2017-07-01

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

  19. High-throughput migration modelling for estimating exposure to chemicals in food packaging in screening and prioritization tools.

    Science.gov (United States)

    Ernstoff, Alexi S; Fantke, Peter; Huang, Lei; Jolliet, Olivier

    2017-11-01

    Specialty software and simplified models are often used to estimate migration of potentially toxic chemicals from packaging into food. Current models, however, are not suitable for emerging applications in decision-support tools, e.g. in Life Cycle Assessment and risk-based screening and prioritization, which require rapid computation of accurate estimates for diverse scenarios. To fulfil this need, we develop an accurate and rapid (high-throughput) model that estimates the fraction of organic chemicals migrating from polymeric packaging materials into foods. Several hundred step-wise simulations optimised the model coefficients to cover a range of user-defined scenarios (e.g. temperature). The developed model, operationalised in a spreadsheet for future dissemination, nearly instantaneously estimates chemical migration, and has improved performance over commonly used model simplifications. When using measured diffusion coefficients the model accurately predicted (R 2  = 0.9, standard error (S e ) = 0.5) hundreds of empirical data points for various scenarios. Diffusion coefficient modelling, which determines the speed of chemical transfer from package to food, was a major contributor to uncertainty and dramatically decreased model performance (R 2  = 0.4, S e  = 1). In all, this study provides a rapid migration modelling approach to estimate exposure to chemicals in food packaging for emerging screening and prioritization approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. The landscape of existing models for high-throughput exposure assessment

    DEFF Research Database (Denmark)

    Jolliet, O.; Fantke, Peter; Huang, L.

    2017-01-01

    and ability to easily handle large datasets. For building materials a series of diffusion-based models have been developed to predict the chemicals emissions from building materials to indoor air, but existing models require complex analytical or numerical solutions, which are not suitable for LCA or HTS...... applications. Thus, existing model solutions needed to be simplified for application in LCA and HTS, and a parsimonious model has been developed by Huang et al. (2017) to address this need. For SVOCs, simplified solutions do exist, assuming constant SVOC concentrations in building materials and steadystate...... for skin permeation and volatilization as competing processes and that requires a limited number of readily available physiochemical properties would be suitable for LCA and HTS purposes. Thus, the multi-pathway exposure model for chemicals in cosmetics developed by Ernstoff et al.constitutes a suitable...

  1. Advancing Toxicology Research Using In Vivo High Throughput Toxicology with Small Fish Models

    Science.gov (United States)

    Planchart, Antonio; Mattingly, Carolyn J.; Allen, David; Ceger, Patricia; Casey, Warren; Hinton, David; Kanungo, Jyotshna; Kullman, Seth W.; Tal, Tamara; Bondesson, Maria; Burgess, Shawn M.; Sullivan, Con; Kim, Carol; Behl, Mamta; Padilla, Stephanie; Reif, David M.; Tanguay, Robert L.; Hamm, Jon

    2017-01-01

    Summary Small freshwater fish models, especially zebrafish, offer advantages over traditional rodent models, including low maintenance and husbandry costs, high fecundity, genetic diversity, physiology similar to that of traditional biomedical models, and reduced animal welfare concerns. The Collaborative Workshop on Aquatic Models and 21st Century Toxicology was held at North Carolina State University on May 5-6, 2014, in Raleigh, North Carolina, USA. Participants discussed the ways in which small fish are being used as models to screen toxicants and understand mechanisms of toxicity. Workshop participants agreed that the lack of standardized protocols is an impediment to broader acceptance of these models, whereas development of standardized protocols, validation, and subsequent regulatory acceptance would facilitate greater usage. Given the advantages and increasing application of small fish models, there was widespread interest in follow-up workshops to review and discuss developments in their use. In this article, we summarize the recommendations formulated by workshop participants to enhance the utility of small fish species in toxicology studies, as well as many of the advances in the field of toxicology that resulted from using small fish species, including advances in developmental toxicology, cardiovascular toxicology, neurotoxicology, and immunotoxicology. We also review many emerging issues that will benefit from using small fish species, especially zebrafish, and new technologies that will enable using these organisms to yield results unprecedented in their information content to better understand how toxicants affect development and health. PMID:27328013

  2. High-throughput Gene Expression Analysis In Pigs As Model For Respiratory Infections

    DEFF Research Database (Denmark)

    Skovgaard, Kerstin; Brogaard, Louise; Schou, Kirstine Klitgaard

    model for disease and inflammation. Pigs are fully susceptible to human influenza, and have been demonstrated to be involved in influenza evolution and ecology. Pigs share many similarities with humans regarding lung physiology and innate immune cell infiltration of the respiratory system and thus seem...... to be an obvious large animal model for respiratory infections. This study aimed at providing a better understanding of the involvement of circulating non-coding RNA and innate immune factors in porcine blood leukocytes during influenza virus infection. By employing the pig as a model we were able to perform...

  3. High-throughput gene expression analysis in pigs as model for respiratory infections

    DEFF Research Database (Denmark)

    Skovgaard, Kerstin; Brogaard, Louise; Schou, Kirstine Klitgaard

    for disease and inflammation. Pigs are fully susceptible to human influenza, and have been demonstrated to be involved in influenza evolution and ecology. Pigs share many similarities with humans regarding lung physiology and innate immune cell infiltration of the respiratory system and thus seem...... to be an obvious large animal model for respiratory infections. This study aimed at providing a better understanding of the involvement of circulating non-coding RNA and innate immune factors in porcine blood leukocytes during influenza virus infection. By employing the pig as a model we were able to perform...

  4. SNP calling using genotype model selection on high-throughput sequencing data

    KAUST Repository

    You, Na; Murillo, Gabriel; Su, Xiaoquan; Zeng, Xiaowei; Xu, Jian; Ning, Kang; Zhang, ShouDong; Zhu, Jian-Kang; Cui, Xinping

    2012-01-01

    calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for.Results: A novel method of consensus and SNP calling, Genotype Model Selection (GeMS), is given which accounts

  5. High Throughput Exposure Modeling of Semi-Volatile Chemicals in Articles of Commerce (ACS)

    Science.gov (United States)

    Risk due to chemical exposure is a function of both chemical hazard and exposure. Near-field exposures to chemicals in consumer products are identified as the main drivers of exposure and yet are not well quantified or understood. The ExpoCast project is developing a model that e...

  6. Introduction of a high-throughput double-stent animal model for the evaluation of biodegradable vascular stents.

    Science.gov (United States)

    Borinski, Mauricio; Flege, Christian; Schreiber, Fabian; Krott, Nicole; Gries, Thomas; Liehn, Elisa; Blindt, Rüdiger; Marx, Nikolaus; Vogt, Felix

    2012-11-01

    Current stent system efficacy for the treatment of coronary artery disease is hampered by in-stent restenosis (ISR) rates of up to 20% in certain high-risk settings and by the risk of stent thrombosis, which is characterized by a high mortality rate. In theory, biodegradable vascular devices exhibit crucial advantages. Most absorbable implant materials are based on poly-L-lactic acid (PLLA) owing to its mechanical properties; however, PLLA might induce an inflammatory reaction in the vessel wall. Evaluation of biodegradable implant efficacy includes a long-term examination of tissue response; therefore, a simple in vivo tool for thorough biocompatibility and biodegradation evaluation would facilitate future stent system development. Rats have been used for the study of in vivo degradation processes, and stent implantation into the abdominal aorta of rats is a proven model for stent evaluation. Here, we report the transformation of the porcine double-stent animal model into the high-throughput rat abdominal aorta model. As genetic manipulation of rats was introduced recently, this novel method presents a powerful tool for future in vivo biodegradable candidate stent biocompatibility and biodegradation characterization in a reliable simple model of coronary ISR. Copyright © 2012 Wiley Periodicals, Inc.

  7. Staphylococcus aureus virulence factors identified by using a high-throughput Caenorhabditis elegans-killing model.

    Science.gov (United States)

    Begun, Jakob; Sifri, Costi D; Goldman, Samuel; Calderwood, Stephen B; Ausubel, Frederick M

    2005-02-01

    Staphylococcus aureus is an important human pathogen that is also able to kill the model nematode Caenorhabditis elegans. We constructed a 2,950-member Tn917 transposon insertion library in S. aureus strain NCTC 8325. Twenty-one of these insertions exhibited attenuated C. elegans killing, and of these, 12 contained insertions in different genes or chromosomal locations. Ten of these 12 insertions showed attenuated killing phenotypes when transduced into two different S. aureus strains, and 5 of the 10 mutants correspond to genes that have not been previously identified in signature-tagged mutagenesis studies. These latter five mutants were tested in a murine renal abscess model, and one mutant harboring an insertion in nagD exhibited attenuated virulence. Interestingly, Tn917 was shown to have a very strong bias for insertions near the terminus of DNA replication.

  8. Performance Modeling in CUDA Streams - A Means for High-Throughput Data Processing.

    Science.gov (United States)

    Li, Hao; Yu, Di; Kumar, Anand; Tu, Yi-Cheng

    2014-10-01

    Push-based database management system (DBMS) is a new type of data processing software that streams large volume of data to concurrent query operators. The high data rate of such systems requires large computing power provided by the query engine. In our previous work, we built a push-based DBMS named G-SDMS to harness the unrivaled computational capabilities of modern GPUs. A major design goal of G-SDMS is to support concurrent processing of heterogenous query processing operations and enable resource allocation among such operations. Understanding the performance of operations as a result of resource consumption is thus a premise in the design of G-SDMS. With NVIDIA's CUDA framework as the system implementation platform, we present our recent work on performance modeling of CUDA kernels running concurrently under a runtime mechanism named CUDA stream . Specifically, we explore the connection between performance and resource occupancy of compute-bound kernels and develop a model that can predict the performance of such kernels. Furthermore, we provide an in-depth anatomy of the CUDA stream mechanism and summarize the main kernel scheduling disciplines in it. Our models and derived scheduling disciplines are verified by extensive experiments using synthetic and real-world CUDA kernels.

  9. A high throughput data acquisition and processing model for applications based on GPUs

    International Nuclear Information System (INIS)

    Nieto, J.; Arcas, G. de; Ruiz, M.; Castro, R.; Vega, J.; Guillen, P.

    2015-01-01

    Highlights: • Implementation of a direct communication path between a data acquisition NI FlexRIO device and a NVIDIA GPU device. • Customization of a Linux Kernel Open Driver (NI FlexRIO) and a C API Interface for work con NVIDIA RDMA GPUDirect. • Performance evaluation with respect to traditional model that use CPU as buffer data allocation. - Abstract: There is an increasing interest in the use of GPU technologies for real time analysis in fusion devices. The availability of high bandwidth interfaces has made them a very cost effective alternative not only for high volume data analysis or simulation, and commercial products are available for some interest areas. However from the point of view of their application in real time scenarios, there are still some issues under analysis, such as the possibility to improve the data throughput inside a discrete system consisting of data acquisition devices (DAQ) and GPUs. This paper addresses the possibility of using peer to peer data communication between DAQ devices and GPUs sharing the same PCIexpress bus to implement continuous real time acquisition and processing systems where data transfers require minimum CPU intervention. This technology eliminates unnecessary system memory copies and lowers CPU overhead, avoiding bottleneck when the system uses the main system memory.

  10. A high throughput data acquisition and processing model for applications based on GPUs

    Energy Technology Data Exchange (ETDEWEB)

    Nieto, J., E-mail: jnieto@sec.upm.es [Instrumentation and Applied Acoustic Research Group, Technical University of Madrid (UPM), Madrid (Spain); Arcas, G. de; Ruiz, M. [Instrumentation and Applied Acoustic Research Group, Technical University of Madrid (UPM), Madrid (Spain); Castro, R.; Vega, J. [Data acquisition Group EURATOM/CIEMAT Association for Fusion, Madrid (Spain); Guillen, P. [Instrumentation and Applied Acoustic Research Group, Technical University of Madrid (UPM), Madrid (Spain)

    2015-10-15

    Highlights: • Implementation of a direct communication path between a data acquisition NI FlexRIO device and a NVIDIA GPU device. • Customization of a Linux Kernel Open Driver (NI FlexRIO) and a C API Interface for work con NVIDIA RDMA GPUDirect. • Performance evaluation with respect to traditional model that use CPU as buffer data allocation. - Abstract: There is an increasing interest in the use of GPU technologies for real time analysis in fusion devices. The availability of high bandwidth interfaces has made them a very cost effective alternative not only for high volume data analysis or simulation, and commercial products are available for some interest areas. However from the point of view of their application in real time scenarios, there are still some issues under analysis, such as the possibility to improve the data throughput inside a discrete system consisting of data acquisition devices (DAQ) and GPUs. This paper addresses the possibility of using peer to peer data communication between DAQ devices and GPUs sharing the same PCIexpress bus to implement continuous real time acquisition and processing systems where data transfers require minimum CPU intervention. This technology eliminates unnecessary system memory copies and lowers CPU overhead, avoiding bottleneck when the system uses the main system memory.

  11. PetriCode: A Tool for Template-Based Code Generation from CPN Models

    DEFF Research Database (Denmark)

    Simonsen, Kent Inge

    2014-01-01

    Code generation is an important part of model driven methodologies. In this paper, we present PetriCode, a software tool for generating protocol software from a subclass of Coloured Petri Nets (CPNs). The CPN subclass is comprised of hierarchical CPN models describing a protocol system at different...

  12. Lightweight robotic mobility: template-based modeling for dynamics and controls using ADAMS/car and MATLAB

    Science.gov (United States)

    Adamczyk, Peter G.; Gorsich, David J.; Hudas, Greg R.; Overholt, James

    2003-09-01

    The U.S. Army is seeking to develop autonomous off-road mobile robots to perform tasks in the field such as supply delivery and reconnaissance in dangerous territory. A key problem to be solved with these robots is off-road mobility, to ensure that the robots can accomplish their tasks without loss or damage. We have developed a computer model of one such concept robot, the small-scale "T-1" omnidirectional vehicle (ODV), to study the effects of different control strategies on the robot's mobility in off-road settings. We built the dynamic model in ADAMS/Car and the control system in Matlab/Simulink. This paper presents the template-based method used to construct the ADAMS model of the T-1 ODV. It discusses the strengths and weaknesses of ADAMS/Car software in such an application, and describes the benefits and challenges of the approach as a whole. The paper also addresses effective linking of ADAMS/Car and Matlab for complete control system development. Finally, this paper includes a section describing the extension of the T-1 templates to other similar ODV concepts for rapid development.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  15. Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

    Science.gov (United States)

    Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

    2018-03-01

    We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

  16. Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12.

    Science.gov (United States)

    Zhang, Chengxin; Mortuza, S M; He, Baoji; Wang, Yanting; Zhang, Yang

    2018-03-01

    We develop two complementary pipelines, "Zhang-Server" and "QUARK", based on I-TASSER and QUARK pipelines for template-based modeling (TBM) and free modeling (FM), and test them in the CASP12 experiment. The combination of I-TASSER and QUARK successfully folds three medium-size FM targets that have more than 150 residues, even though the interplay between the two pipelines still awaits further optimization. Newly developed sequence-based contact prediction by NeBcon plays a critical role to enhance the quality of models, particularly for FM targets, by the new pipelines. The inclusion of NeBcon predicted contacts as restraints in the QUARK simulations results in an average TM-score of 0.41 for the best in top five predicted models, which is 37% higher than that by the QUARK simulations without contacts. In particular, there are seven targets that are converted from non-foldable to foldable (TM-score >0.5) due to the use of contact restraints in the simulations. Another additional feature in the current pipelines is the local structure quality prediction by ResQ, which provides a robust residue-level modeling error estimation. Despite the success, significant challenges still remain in ab initio modeling of multi-domain proteins and folding of β-proteins with complicated topologies bound by long-range strand-strand interactions. Improvements on domain boundary and long-range contact prediction, as well as optimal use of the predicted contacts and multiple threading alignments, are critical to address these issues seen in the CASP12 experiment. © 2017 Wiley Periodicals, Inc.

  17. Predictive models for anti-tubercular molecules using machine learning on high-throughput biological screening datasets.

    Science.gov (United States)

    Periwal, Vinita; Rajappan, Jinuraj K; Jaleel, Abdul Uc; Scaria, Vinod

    2011-11-18

    Tuberculosis is a contagious disease caused by Mycobacterium tuberculosis (Mtb), affecting more than two billion people around the globe and is one of the major causes of morbidity and mortality in the developing world. Recent reports suggest that Mtb has been developing resistance to the widely used anti-tubercular drugs resulting in the emergence and spread of multi drug-resistant (MDR) and extensively drug-resistant (XDR) strains throughout the world. In view of this global epidemic, there is an urgent need to facilitate fast and efficient lead identification methodologies. Target based screening of large compound libraries has been widely used as a fast and efficient approach for lead identification, but is restricted by the knowledge about the target structure. Whole organism screens on the other hand are target-agnostic and have been now widely employed as an alternative for lead identification but they are limited by the time and cost involved in running the screens for large compound libraries. This could be possibly be circumvented by using computational approaches to prioritize molecules for screening programmes. We utilized physicochemical properties of compounds to train four supervised classifiers (Naïve Bayes, Random Forest, J48 and SMO) on three publicly available bioassay screens of Mtb inhibitors and validated the robustness of the predictive models using various statistical measures. This study is a comprehensive analysis of high-throughput bioassay data for anti-tubercular activity and the application of machine learning approaches to create target-agnostic predictive models for anti-tubercular agents.

  18. Predictive models for anti-tubercular molecules using machine learning on high-throughput biological screening datasets

    Directory of Open Access Journals (Sweden)

    Periwal Vinita

    2011-11-01

    Full Text Available Abstract Background Tuberculosis is a contagious disease caused by Mycobacterium tuberculosis (Mtb, affecting more than two billion people around the globe and is one of the major causes of morbidity and mortality in the developing world. Recent reports suggest that Mtb has been developing resistance to the widely used anti-tubercular drugs resulting in the emergence and spread of multi drug-resistant (MDR and extensively drug-resistant (XDR strains throughout the world. In view of this global epidemic, there is an urgent need to facilitate fast and efficient lead identification methodologies. Target based screening of large compound libraries has been widely used as a fast and efficient approach for lead identification, but is restricted by the knowledge about the target structure. Whole organism screens on the other hand are target-agnostic and have been now widely employed as an alternative for lead identification but they are limited by the time and cost involved in running the screens for large compound libraries. This could be possibly be circumvented by using computational approaches to prioritize molecules for screening programmes. Results We utilized physicochemical properties of compounds to train four supervised classifiers (Naïve Bayes, Random Forest, J48 and SMO on three publicly available bioassay screens of Mtb inhibitors and validated the robustness of the predictive models using various statistical measures. Conclusions This study is a comprehensive analysis of high-throughput bioassay data for anti-tubercular activity and the application of machine learning approaches to create target-agnostic predictive models for anti-tubercular agents.

  19. Model SNP development for complex genomes based on hexaploid oat using high-throughput 454 sequencing technology

    Directory of Open Access Journals (Sweden)

    Chao Shiaoman

    2011-01-01

    Full Text Available Abstract Background Genetic markers are pivotal to modern genomics research; however, discovery and genotyping of molecular markers in oat has been hindered by the size and complexity of the genome, and by a scarcity of sequence data. The purpose of this study was to generate oat expressed sequence tag (EST information, develop a bioinformatics pipeline for SNP discovery, and establish a method for rapid, cost-effective, and straightforward genotyping of SNP markers in complex polyploid genomes such as oat. Results Based on cDNA libraries of four cultivated oat genotypes, approximately 127,000 contigs were assembled from approximately one million Roche 454 sequence reads. Contigs were filtered through a novel bioinformatics pipeline to eliminate ambiguous polymorphism caused by subgenome homology, and 96 in silico SNPs were selected from 9,448 candidate loci for validation using high-resolution melting (HRM analysis. Of these, 52 (54% were polymorphic between parents of the Ogle1040 × TAM O-301 (OT mapping population, with 48 segregating as single Mendelian loci, and 44 being placed on the existing OT linkage map. Ogle and TAM amplicons from 12 primers were sequenced for SNP validation, revealing complex polymorphism in seven amplicons but general sequence conservation within SNP loci. Whole-amplicon interrogation with HRM revealed insertions, deletions, and heterozygotes in secondary oat germplasm pools, generating multiple alleles at some primer targets. To validate marker utility, 36 SNP assays were used to evaluate the genetic diversity of 34 diverse oat genotypes. Dendrogram clusters corresponded generally to known genome composition and genetic ancestry. Conclusions The high-throughput SNP discovery pipeline presented here is a rapid and effective method for identification of polymorphic SNP alleles in the oat genome. The current-generation HRM system is a simple and highly-informative platform for SNP genotyping. These techniques provide

  20. RSCA genotyping of MHC for high-throughput evolutionary studies in the model organism three-spined stickleback Gasterosteus aculeatus

    Science.gov (United States)

    Lenz, Tobias L; Eizaguirre, Christophe; Becker, Sven; Reusch, Thorsten BH

    2009-01-01

    Background In all jawed vertebrates, highly polymorphic genes of the major histocompatibility complex (MHC) encode antigen presenting molecules that play a key role in the adaptive immune response. Their polymorphism is composed of multiple copies of recently duplicated genes, each possessing many alleles within populations, as well as high nucleotide divergence between alleles of the same species. Experimental evidence is accumulating that MHC polymorphism is a result of balancing selection by parasites and pathogens. In order to describe MHC diversity and analyse the underlying mechanisms that maintain it, a reliable genotyping technique is required that is suitable for such highly variable genes. Results We present a genotyping protocol that uses Reference Strand-mediated Conformation Analysis (RSCA), optimised for recently duplicated MHC class IIB genes that are typical for many fish and bird species, including the three-spined stickleback, Gasterosteus aculeatus. In addition we use a comprehensive plasmid library of MHC class IIB alleles to determine the nucleotide sequence of alleles represented by RSCA allele peaks. Verification of the RSCA typing by cloning and sequencing demonstrates high congruency between both methods and provides new insight into the polymorphism of classical stickleback MHC genes. Analysis of the plasmid library additionally reveals the high resolution and reproducibility of the RSCA technique. Conclusion This new RSCA genotyping protocol offers a fast, but sensitive and reliable way to determine the MHC allele repertoire of three-spined sticklebacks. It therefore provides a valuable tool to employ this highly polymorphic and adaptive marker in future high-throughput studies of host-parasite co-evolution and ecological speciation in this emerging model organism. PMID:19291291

  1. RSCA genotyping of MHC for high-throughput evolutionary studies in the model organism three-spined stickleback Gasterosteus aculeatus

    Directory of Open Access Journals (Sweden)

    Becker Sven

    2009-03-01

    Full Text Available Abstract Background In all jawed vertebrates, highly polymorphic genes of the major histocompatibility complex (MHC encode antigen presenting molecules that play a key role in the adaptive immune response. Their polymorphism is composed of multiple copies of recently duplicated genes, each possessing many alleles within populations, as well as high nucleotide divergence between alleles of the same species. Experimental evidence is accumulating that MHC polymorphism is a result of balancing selection by parasites and pathogens. In order to describe MHC diversity and analyse the underlying mechanisms that maintain it, a reliable genotyping technique is required that is suitable for such highly variable genes. Results We present a genotyping protocol that uses Reference Strand-mediated Conformation Analysis (RSCA, optimised for recently duplicated MHC class IIB genes that are typical for many fish and bird species, including the three-spined stickleback, Gasterosteus aculeatus. In addition we use a comprehensive plasmid library of MHC class IIB alleles to determine the nucleotide sequence of alleles represented by RSCA allele peaks. Verification of the RSCA typing by cloning and sequencing demonstrates high congruency between both methods and provides new insight into the polymorphism of classical stickleback MHC genes. Analysis of the plasmid library additionally reveals the high resolution and reproducibility of the RSCA technique. Conclusion This new RSCA genotyping protocol offers a fast, but sensitive and reliable way to determine the MHC allele repertoire of three-spined sticklebacks. It therefore provides a valuable tool to employ this highly polymorphic and adaptive marker in future high-throughput studies of host-parasite co-evolution and ecological speciation in this emerging model organism.

  2. Generation of SNCA Cell Models Using Zinc Finger Nuclease (ZFN) Technology for Efficient High-Throughput Drug Screening.

    Science.gov (United States)

    Dansithong, Warunee; Paul, Sharan; Scoles, Daniel R; Pulst, Stefan M; Huynh, Duong P

    2015-01-01

    Parkinson's disease (PD) is a progressive neurodegenerative disorder caused by loss of dopaminergic neurons of the substantia nigra. The hallmark of PD is the appearance of neuronal protein aggregations known as Lewy bodies and Lewy neurites, of which α-synuclein forms a major component. Familial PD is rare and is associated with missense mutations of the SNCA gene or increases in gene copy number resulting in SNCA overexpression. This suggests that lowering SNCA expression could be therapeutic for PD. Supporting this hypothesis, SNCA reduction was neuroprotective in cell line and rodent PD models. We developed novel cell lines expressing SNCA fused to the reporter genes luciferase (luc) or GFP with the objective to enable high-throughput compound screening (HTS) for small molecules that can lower SNCA expression. Because SNCA expression is likely regulated by far-upstream elements (including the NACP-REP1 located at 8852 bp upstream of the transcription site), we employed zinc finger nuclease (ZFN) genome editing to insert reporter genes in-frame downstream of the SNCA gene in order to retain native SNCA expression control. This ensured full retention of known and unknown up- and downstream genetic elements controlling SNCA expression. Treatment of cells with the histone deacetylase inhibitor valproic acid (VPA) resulted in significantly increased SNCA-luc and SNCA-GFP expression supporting the use of our cell lines for identifying small molecules altering complex modes of expression control. Cells expressing SNCA-luc treated with a luciferase inhibitor or SNCA siRNA resulted in Z'-scores ≥ 0.75, suggesting the suitability of these cell lines for use in HTS. This study presents a novel use of genome editing for the creation of cell lines expressing α-synuclein fusion constructs entirely under native expression control. These cell lines are well suited for HTS for compounds that lower SNCA expression directly or by acting at long-range sites to the SNCA

  3. Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis.

    Science.gov (United States)

    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.

  4. Insect-derived cecropins display activity against Acinetobacter baumannii in a whole-animal high-throughput Caenorhabditis elegans model.

    Science.gov (United States)

    Jayamani, Elamparithi; Rajamuthiah, Rajmohan; Larkins-Ford, Jonah; Fuchs, Beth Burgwyn; Conery, Annie L; Vilcinskas, Andreas; Ausubel, Frederick M; Mylonakis, Eleftherios

    2015-03-01

    The rise of multidrug-resistant Acinetobacter baumannii and a concomitant decrease in antibiotic treatment options warrants a search for new classes of antibacterial agents. We have found that A. baumannii is pathogenic and lethal to the model host organism Caenorhabditis elegans and have exploited this phenomenon to develop an automated, high-throughput, high-content screening assay in liquid culture that can be used to identify novel antibiotics effective against A. baumannii. The screening assay involves coincubating C. elegans with A. baumannii in 384-well plates containing potential antibacterial compounds. At the end of the incubation period, worms are stained with a dye that stains only dead animals, and images are acquired using automated microscopy and then analyzed using an automated image analysis program. This robust assay yields a Z' factor consistently greater than 0.7. In a pilot experiment to test the efficacy of the assay, we screened a small custom library of synthetic antimicrobial peptides (AMPs) that were synthesized using publicly available sequence data and/or transcriptomic data from immune-challenged insects. We identified cecropin A and 14 other cecropin or cecropin-like peptides that were able to enhance C. elegans survival in the presence of A. baumannii. Interestingly, one particular hit, BR003-cecropin A, a cationic peptide synthesized by the mosquito Aedes aegypti, showed antibiotic activity against a panel of Gram-negative bacteria and exhibited a low MIC (5 μg/ml) against A. baumannii. BR003-cecropin A causes membrane permeability in A. baumannii, which could be the underlying mechanism of its lethality. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  5. Development of a high-throughput in vitro intestinal lipolysis model for rapid screening of lipid-based drug delivery systems

    DEFF Research Database (Denmark)

    Mosgaard, Mette D; Sassene, Philip; Mu, Huiling

    2015-01-01

    : The HTP model is able to predict drug distribution during digestion of LbDDS containing poorly water soluble drugs in the same manner as the DIVL model. Thus the HTP model might prove applicable for high-throughput evaluation of LbDDS in e.g. 96 well plates or small scale dissolution equipment....... (DIVL) model with regard to the extent of lipid digestion and drug distribution of two poorly soluble model drugs (cinnarizine and danazol), during digestion of three LbDDS (LbDDS I-III). RESULT: The HTP model was able to maintain pH around 6.5 during digestion, without the addition of Na...

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

    Science.gov (United States)

    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.

  7. A mobile, high-throughput semi-automated system for testing cognition in large non-primate animal models of Huntington disease.

    Science.gov (United States)

    McBride, Sebastian D; Perentos, Nicholas; Morton, A Jennifer

    2016-05-30

    For reasons of cost and ethical concerns, models of neurodegenerative disorders such as Huntington disease (HD) are currently being developed in farm animals, as an alternative to non-human primates. Developing reliable methods of testing cognitive function is essential to determining the usefulness of such models. Nevertheless, cognitive testing of farm animal species presents a unique set of challenges. The primary aims of this study were to develop and validate a mobile operant system suitable for high throughput cognitive testing of sheep. We designed a semi-automated testing system with the capability of presenting stimuli (visual, auditory) and reward at six spatial locations. Fourteen normal sheep were used to validate the system using a two-choice visual discrimination task. Four stages of training devised to acclimatise animals to the system are also presented. All sheep progressed rapidly through the training stages, over eight sessions. All sheep learned the 2CVDT and performed at least one reversal stage. The mean number of trials the sheep took to reach criterion in the first acquisition learning was 13.9±1.5 and for the reversal learning was 19.1±1.8. This is the first mobile semi-automated operant system developed for testing cognitive function in sheep. We have designed and validated an automated operant behavioural testing system suitable for high throughput cognitive testing in sheep and other medium-sized quadrupeds, such as pigs and dogs. Sheep performance in the two-choice visual discrimination task was very similar to that reported for non-human primates and strongly supports the use of farm animals as pre-clinical models for the study of neurodegenerative diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    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...

  9. Application of high-throughput mini-bioreactor system for systematic scale-down modeling, process characterization, and control strategy development.

    Science.gov (United States)

    Janakiraman, Vijay; Kwiatkowski, Chris; Kshirsagar, Rashmi; Ryll, Thomas; Huang, Yao-Ming

    2015-01-01

    High-throughput systems and processes have typically been targeted for process development and optimization in the bioprocessing industry. For process characterization, bench scale bioreactors have been the system of choice. Due to the need for performing different process conditions for multiple process parameters, the process characterization studies typically span several months and are considered time and resource intensive. In this study, we have shown the application of a high-throughput mini-bioreactor system viz. the Advanced Microscale Bioreactor (ambr15(TM) ), to perform process characterization in less than a month and develop an input control strategy. As a pre-requisite to process characterization, a scale-down model was first developed in the ambr system (15 mL) using statistical multivariate analysis techniques that showed comparability with both manufacturing scale (15,000 L) and bench scale (5 L). Volumetric sparge rates were matched between ambr and manufacturing scale, and the ambr process matched the pCO2 profiles as well as several other process and product quality parameters. The scale-down model was used to perform the process characterization DoE study and product quality results were generated. Upon comparison with DoE data from the bench scale bioreactors, similar effects of process parameters on process yield and product quality were identified between the two systems. We used the ambr data for setting action limits for the critical controlled parameters (CCPs), which were comparable to those from bench scale bioreactor data. In other words, the current work shows that the ambr15(TM) system is capable of replacing the bench scale bioreactor system for routine process development and process characterization. © 2015 American Institute of Chemical Engineers.

  10. High-throughput migration modelling for estimating exposure to chemicals in food packaging in screening and prioritization tools

    DEFF Research Database (Denmark)

    Ernstoff, Alexi S; Fantke, Peter; Huang, Lei

    2017-01-01

    Specialty software and simplified models are often used to estimate migration of potentially toxic chemicals from packaging into food. Current models, however, are not suitable for emerging applications in decision-support tools, e.g. in Life Cycle Assessment and risk-based screening and prioriti...... to uncertainty and dramatically decreased model performance (R2 = 0.4, Se = 1). In all, this study provides a rapid migration modelling approach to estimate exposure to chemicals in food packaging for emerging screening and prioritization approaches....

  11. 20180311 - Differential Gene Expression and Concentration-Response Modeling Workflow for High-Throughput Transcriptomic (HTTr) Data: Results From MCF7 Cells (SOT)

    Science.gov (United States)

    Increasing efficiency and declining cost of generating whole transcriptome profiles has made high-throughput transcriptomics a practical option for chemical bioactivity screening. The resulting data output provides information on the expression of thousands of genes and is amenab...

  12. Differential Gene Expression and Concentration-Response Modeling Workflow for High-Throughput Transcriptomic (HTTr) Data: Results From MCF7 Cells

    Science.gov (United States)

    Increasing efficiency and declining cost of generating whole transcriptome profiles has made high-throughput transcriptomics a practical option for chemical bioactivity screening. The resulting data output provides information on the expression of thousands of genes and is amenab...

  13. Critical analysis of 3-D organoid in vitro cell culture models for high-throughput drug candidate toxicity assessments.

    Science.gov (United States)

    Astashkina, Anna; Grainger, David W

    2014-04-01

    Drug failure due to toxicity indicators remains among the primary reasons for staggering drug attrition rates during clinical studies and post-marketing surveillance. Broader validation and use of next-generation 3-D improved cell culture models are expected to improve predictive power and effectiveness of drug toxicological predictions. However, after decades of promising research significant gaps remain in our collective ability to extract quality human toxicity information from in vitro data using 3-D cell and tissue models. Issues, challenges and future directions for the field to improve drug assay predictive power and reliability of 3-D models are reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Assessing Interval Estimation Methods for Hill Model Parameters in a High-Throughput Screening Context (IVIVE meeting)

    Science.gov (United States)

    The Hill model of concentration-response is ubiquitous in toxicology, perhaps because its parameters directly relate to biologically significant metrics of toxicity such as efficacy and potency. Point estimates of these parameters obtained through least squares regression or maxi...

  15. High-throughput continuous cryopump

    International Nuclear Information System (INIS)

    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

  16. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

    International Nuclear Information System (INIS)

    Valerio, Luis G.; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.

    2007-01-01

    Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest is MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals

  17. [Ideas and methods of two-dimensional zebrafish model combined with chromatographic techniques in high-throughput screening of active anti-osteoporosis components of traditional Chinese medicines].

    Science.gov (United States)

    Wei, Ying-Jie; Jing, Li-Jun; Zhan, Yang; Sun, E; Jia, Xiao-Bin

    2014-05-01

    To break through the restrictions of the evaluation model and the quantity of compounds by using the two-dimensional zebrafish model combined with chromatographic techniques, and establish a new method for the high-throughput screening of active anti-osteoporosis components. According to the research group-related studies and relevant foreign literatures, on the basis of the fact that the zebrafish osteoporosis model could efficiently evaluate the activity, the zebrafish metabolism model could efficiently enrich metabolites and the chromatographic techniques could efficiently separate and analyze components of traditional Chinese medicines, we proposed that the inherent combination of the three methods is expected to efficiently decode in vivo and in vitro efficacious anti-osteoporosis materials of traditional Chinese medicines. The method makes it simple and efficient in the enrichment, separation and analysis on components of traditional Chinese medicines, particularly micro-components and metabolites and the screening anti-osteoporosis activity, fully reflects that efficacious materials of traditional Chinese medicines contain original components and metabolites, with characteristic of "multi-components, multi-targets and integral effect", which provides new ideas and methods for the early and rapid discovery of active anti-osteoporosis components of traditional Chinese medicines.

  18. High throughput ADME screening: practical considerations, impact on the portfolio and enabler of in silico ADME models.

    Science.gov (United States)

    Hop, Cornelis E C A; Cole, Mark J; Davidson, Ralph E; Duignan, David B; Federico, James; Janiszewski, John S; Jenkins, Kelly; Krueger, Suzanne; Lebowitz, Rebecca; Liston, Theodore E; Mitchell, Walter; Snyder, Mark; Steyn, Stefan J; Soglia, John R; Taylor, Christine; Troutman, Matt D; Umland, John; West, Michael; Whalen, Kevin M; Zelesky, Veronica; Zhao, Sabrina X

    2008-11-01

    Evaluation and optimization of drug metabolism and pharmacokinetic data plays an important role in drug discovery and development and several reliable in vitro ADME models are available. Recently higher throughput in vitro ADME screening facilities have been established in order to be able to evaluate an appreciable fraction of synthesized compounds. The ADME screening process can be dissected in five distinct steps: (1) plate management of compounds in need of in vitro ADME data, (2) optimization of the MS/MS method for the compounds, (3) in vitro ADME experiments and sample clean up, (4) collection and reduction of the raw LC-MS/MS data and (5) archival of the processed ADME data. All steps will be described in detail and the value of the data on drug discovery projects will be discussed as well. Finally, in vitro ADME screening can generate large quantities of data obtained under identical conditions to allow building of reliable in silico models.

  19. Fostering efficacy and toxicity evaluation of traditional Chinese medicine and natural products: Chick embryo as a high throughput model bridging in vitro and in vivo studies.

    Science.gov (United States)

    Wu, Tong; Yu, Gui-Yuan; Xiao, Jia; Yan, Chang; Kurihara, Hiroshi; Li, Yi-Fang; So, Kwok-Fai; He, Rong-Rong

    2018-04-19

    Efficacy and safety assessments are essential thresholds for drug candidates from preclinical to clinical research. Conventional mammalian in vivo models cannot offer rapid pharmacological and toxicological screening, whereas cell-based or cell-free in vitro systems often lead to inaccurate results because of the lack of physiological environment. Within the avian species, gallus gallus is the first bird to have its genome sequencing. Meantime, chick embryo is an easily operating, relatively transparent and extensively accessible model, whose physiological and pathological alterations can be visualized by egg candler, staining and image technologies. These features facilitate chick embryo as a high-throughput screening platform bridging in vivo and in vitro gaps in the pharmaceutical research. Due to the complicated ingredients and multiple-targets natures of traditional Chinese medicine (TCM), testing the efficacy and safety of TCM by in vitro methods are laborious and inaccurate, while testing in mammalian models consume massive cost and time. As such, the productive living organism chick embryo serves as an ideal biological system for pharmacodynamics studies of TCM. Herein, we comprehensively update recent progresses on the specialty of chick embryo in evaluation of efficacy and toxicity of drugs, with special concerns of TCM. Copyright © 2018 Elsevier Ltd. All rights reserved.

  20. HIV-1 entry inhibition by small-molecule CCR5 antagonists: A combined molecular modeling and mutant study using a high-throughput assay

    International Nuclear Information System (INIS)

    Labrecque, Jean; Metz, Markus; Lau, Gloria; Darkes, Marilyn C.; Wong, Rebecca S.Y.; Bogucki, David; Carpenter, Bryon; Chen Gang; Li Tongshuang; Nan, Susan; Schols, Dominique; Bridger, Gary J.; Fricker, Simon P.; Skerlj, Renato T.

    2011-01-01

    Based on the attrition rate of CCR5 small molecule antagonists in the clinic the discovery and development of next generation antagonists with an improved pharmacology and safety profile is necessary. Herein, we describe a combined molecular modeling, CCR5-mediated cell fusion, and receptor site-directed mutagenesis approach to study the molecular interactions of six structurally diverse compounds (aplaviroc, maraviroc, vicriviroc, TAK-779, SCH-C and a benzyloxycarbonyl-aminopiperidin-1-yl-butane derivative) with CCR5, a coreceptor for CCR5-tropic HIV-1 strains. This is the first study using an antifusogenic assay, a model of the interaction of the gp120 envelope protein with CCR5. This assay avoids the use of radioactivity and HIV infection assays, and can be used in a high throughput mode. The assay was validated by comparison with other established CCR5 assays. Given the hydrophobic nature of the binding pocket several binding models are suggested which could prove useful in the rational drug design of new lead compounds.

  1. Validation of the high-throughput marker technology DArT using the model plant Arabidopsis thaliana.

    Science.gov (United States)

    Wittenberg, Alexander H J; van der Lee, Theo; Cayla, Cyril; Kilian, Andrzej; Visser, Richard G F; Schouten, Henk J

    2005-08-01

    Diversity Arrays Technology (DArT) is a microarray-based DNA marker technique for genome-wide discovery and genotyping of genetic variation. DArT allows simultaneous scoring of hundreds of restriction site based polymorphisms between genotypes and does not require DNA sequence information or site-specific oligonucleotides. This paper demonstrates the potential of DArT for genetic mapping by validating the quality and molecular basis of the markers, using the model plant Arabidopsis thaliana. Restriction fragments from a genomic representation of the ecotype Landsberg erecta (Ler) were amplified by PCR, individualized by cloning and spotted onto glass slides. The arrays were then hybridized with labeled genomic representations of the ecotypes Columbia (Col) and Ler and of individuals from an F(2) population obtained from a Col x Ler cross. The scoring of markers with specialized software was highly reproducible and 107 markers could unambiguously be ordered on a genetic linkage map. The marker order on the genetic linkage map coincided with the order on the DNA sequence map. Sequencing of the Ler markers and alignment with the available Col genome sequence confirmed that the polymorphism in DArT markers is largely a result of restriction site polymorphisms.

  2. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

    KAUST Repository

    Lensink, Marc F.

    2016-04-28

    We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

  3. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

    KAUST Repository

    Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen-You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan-Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie-Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaë l A.G.; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Franç oise; Guerois, Raphaë l; Vangone, Anna; Rodrigues, Joã o P.G.L.M.; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung-Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jimé nez-Garcí a, Brian; Moal, Iain H.; Fé rnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

    2016-01-01

    We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

  4. Common Duckweed (Lemna minor) Is a Versatile High-Throughput Infection Model For the Burkholderia cepacia Complex and Other Pathogenic Bacteria

    Science.gov (United States)

    Thomson, Euan L. S.; Dennis, Jonathan J.

    2013-01-01

    Members of the Burkholderia cepacia complex (Bcc) have emerged in recent decades as problematic pulmonary pathogens of cystic fibrosis (CF) patients, with severe infections progressing to acute necrotizing pneumonia and sepsis. This study presents evidence that Lemna minor (Common duckweed) is useful as a plant model for the Bcc infectious process, and has potential as a model system for bacterial pathogenesis in general. To investigate the relationship between Bcc virulence in duckweed and Galleria mellonella (Greater wax moth) larvae, a previously established Bcc infection model, a duckweed survival assay was developed and used to determine LD50 values. A strong correlation (R2 = 0.81) was found between the strains’ virulence ranks in the two infection models, suggesting conserved pathways in these vastly different hosts. To broaden the application of the duckweed model, enteropathogenic Escherichia coli (EPEC) and five isogenic mutants with previously established LD50 values in the larval model were tested against duckweed, and a strong correlation (R2 = 0.93) was found between their raw LD50 values. Potential virulence factors in B. cenocepacia K56-2 were identified using a high-throughput screen against single duckweed plants. In addition to the previously characterized antifungal compound (AFC) cluster genes, several uncharacterized genes were discovered including a novel lysR regulator, a histidine biosynthesis gene hisG, and a gene located near the gene encoding the recently characterized virulence factor SuhBBc. Finally, to demonstrate the utility of this model in therapeutic applications, duckweed was rescued from Bcc infection by treating with bacteriophage at 6-h intervals. It was observed that phage application became ineffective at a timepoint that coincided with a sharp increase in bacterial invasion of plant tissue. These results indicate that common duckweed can serve as an effective infection model for the investigation of bacterial virulence

  5. Common duckweed (Lemna minor is a versatile high-throughput infection model for the Burkholderia cepacia complex and other pathogenic bacteria.

    Directory of Open Access Journals (Sweden)

    Euan L S Thomson

    Full Text Available Members of the Burkholderia cepacia complex (Bcc have emerged in recent decades as problematic pulmonary pathogens of cystic fibrosis (CF patients, with severe infections progressing to acute necrotizing pneumonia and sepsis. This study presents evidence that Lemna minor (Common duckweed is useful as a plant model for the Bcc infectious process, and has potential as a model system for bacterial pathogenesis in general. To investigate the relationship between Bcc virulence in duckweed and Galleria mellonella (Greater wax moth larvae, a previously established Bcc infection model, a duckweed survival assay was developed and used to determine LD50 values. A strong correlation (R(2 = 0.81 was found between the strains' virulence ranks in the two infection models, suggesting conserved pathways in these vastly different hosts. To broaden the application of the duckweed model, enteropathogenic Escherichia coli (EPEC and five isogenic mutants with previously established LD50 values in the larval model were tested against duckweed, and a strong correlation (R(2 = 0.93 was found between their raw LD50 values. Potential virulence factors in B. cenocepacia K56-2 were identified using a high-throughput screen against single duckweed plants. In addition to the previously characterized antifungal compound (AFC cluster genes, several uncharacterized genes were discovered including a novel lysR regulator, a histidine biosynthesis gene hisG, and a gene located near the gene encoding the recently characterized virulence factor SuhB(Bc. Finally, to demonstrate the utility of this model in therapeutic applications, duckweed was rescued from Bcc infection by treating with bacteriophage at 6-h intervals. It was observed that phage application became ineffective at a timepoint that coincided with a sharp increase in bacterial invasion of plant tissue. These results indicate that common duckweed can serve as an effective infection model for the investigation of bacterial

  6. Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals.

    Science.gov (United States)

    Csiszar, Susan A; Meyer, David E; Dionisio, Kathie L; Egeghy, Peter; Isaacs, Kristin K; Price, Paul S; Scanlon, Kelly A; Tan, Yu-Mei; Thomas, Kent; Vallero, Daniel; Bare, Jane C

    2016-11-01

    Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

  7. High throughput protein production screening

    Science.gov (United States)

    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.

  8. High-throughput, signature-tagged mutagenic approach to identify novel virulence factors of Yersinia pestis CO92 in a mouse model of infection.

    Science.gov (United States)

    Ponnusamy, Duraisamy; Fitts, Eric C; Sha, Jian; Erova, Tatiana E; Kozlova, Elena V; Kirtley, Michelle L; Tiner, Bethany L; Andersson, Jourdan A; Chopra, Ashok K

    2015-05-01

    The identification of new virulence factors in Yersinia pestis and understanding their molecular mechanisms during an infection process are necessary in designing a better vaccine or to formulate an appropriate therapeutic intervention. By using a high-throughput, signature-tagged mutagenic approach, we created 5,088 mutants of Y. pestis strain CO92 and screened them in a mouse model of pneumonic plague at a dose equivalent to 5 50% lethal doses (LD50) of wild-type (WT) CO92. From this screen, we obtained 118 clones showing impairment in disseminating to the spleen, based on hybridization of input versus output DNA from mutant pools with 53 unique signature tags. In the subsequent screen, 20/118 mutants exhibited attenuation at 8 LD50 when tested in a mouse model of bubonic plague, with infection by 10/20 of the aforementioned mutants resulting in 40% or higher survival rates at an infectious dose of 40 LD50. Upon sequencing, six of the attenuated mutants were found to carry interruptions in genes encoding hypothetical proteins or proteins with putative functions. Mutants with in-frame deletion mutations of two of the genes identified from the screen, namely, rbsA, which codes for a putative sugar transport system ATP-binding protein, and vasK, a component of the type VI secretion system, were also found to exhibit some attenuation at 11 or 12 LD50 in a mouse model of pneumonic plague. Likewise, among the remaining 18 signature-tagged mutants, 9 were also attenuated (40 to 100%) at 12 LD50 in a pneumonic plague mouse model. Previously, we found that deleting genes encoding Braun lipoprotein (Lpp) and acyltransferase (MsbB), the latter of which modifies lipopolysaccharide function, reduced the virulence of Y. pestis CO92 in mouse models of bubonic and pneumonic plague. Deletion of rbsA and vasK genes from either the Δlpp single or the Δlpp ΔmsbB double mutant augmented the attenuation to provide 90 to 100% survivability to mice in a pneumonic plague model at 20

  9. Toward a Molecular Understanding of the Interaction of Dual Specificity Phosphatases with Substrates: Insights from Structure-Based Modeling and High Throughput Screening

    OpenAIRE

    Bakan, Ahmet; Lazo, John S; Wipf, Peter; Brummond, Kay M; Bahar, Ivet

    2008-01-01

    Dual-specificity phosphatases (DSPs) are important, but poorly understood, cell signaling enzymes that remove phosphate groups from tyrosine and serine/threonine residues on their substrate. Deregulation of DSPs has been implicated in cancer, obesity, diabetes, inflammation, and Alzheimer’s disease. Due to their biological and biomedical significance, DSPs have increasingly become the subject of drug discovery high-throughput screening (HTS) and focused compound library development efforts. P...

  10. High Throughput Plasma Water Treatment

    Science.gov (United States)

    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).

  11. Combining thermodynamic modeling and 3D printing of elemental powder blends for high-throughput investigation of high-entropy alloys – Towards rapid alloy screening and design

    International Nuclear Information System (INIS)

    Haase, Christian; Tang, Florian; Wilms, Markus B.; Weisheit, Andreas; Hallstedt, Bengt

    2017-01-01

    High-entropy alloys have gained high interest of both academia and industry in recent years due to their excellent properties and large variety of possible alloy systems. However, so far prediction of phase constitution and stability is based on empirical rules that can only be applied to selected alloy systems. In the current study, we introduce a methodology that enables high-throughput theoretical and experimental alloy screening and design. As a basis for thorough thermodynamic calculations, a new database was compiled for the Co–Cr–Fe–Mn–Ni system and used for Calphad and Scheil simulations. For bulk sample production, laser metal deposition (LMD) of an elemental powder blend was applied to build up the equiatomic CoCrFeMnNi Cantor alloy as a first demonstrator. This production approach allows high flexibility in varying the chemical composition and, thus, renders itself suitable for high-throughput alloy production. The microstructure, texture, and mechanical properties of the material processed were characterized using optical microscopy, EBSD, EDX, XRD, hardness and compression testing. The LMD-produced alloy revealed full density, strongly reduced segregation compared to conventionally cast material, pronounced texture, and excellent mechanical properties. Phase constitution and elemental distribution were correctly predicted by simulations. The applicability of the introduced methodology to high-entropy alloys and extension to compositionally complex alloys is discussed.

  12. Combining thermodynamic modeling and 3D printing of elemental powder blends for high-throughput investigation of high-entropy alloys – Towards rapid alloy screening and design

    Energy Technology Data Exchange (ETDEWEB)

    Haase, Christian, E-mail: christian.haase@iehk.rwth-aachen.de [Department of Ferrous Metallurgy, RWTH Aachen University, 52072 Aachen (Germany); Tang, Florian [Institute for Materials Applications in Mechanical Engineering, RWTH Aachen University, 52062 Aachen (Germany); Wilms, Markus B.; Weisheit, Andreas [Fraunhofer Institute for Laser Technology ILT, 52074 Aachen (Germany); Hallstedt, Bengt [Institute for Materials Applications in Mechanical Engineering, RWTH Aachen University, 52062 Aachen (Germany)

    2017-03-14

    High-entropy alloys have gained high interest of both academia and industry in recent years due to their excellent properties and large variety of possible alloy systems. However, so far prediction of phase constitution and stability is based on empirical rules that can only be applied to selected alloy systems. In the current study, we introduce a methodology that enables high-throughput theoretical and experimental alloy screening and design. As a basis for thorough thermodynamic calculations, a new database was compiled for the Co–Cr–Fe–Mn–Ni system and used for Calphad and Scheil simulations. For bulk sample production, laser metal deposition (LMD) of an elemental powder blend was applied to build up the equiatomic CoCrFeMnNi Cantor alloy as a first demonstrator. This production approach allows high flexibility in varying the chemical composition and, thus, renders itself suitable for high-throughput alloy production. The microstructure, texture, and mechanical properties of the material processed were characterized using optical microscopy, EBSD, EDX, XRD, hardness and compression testing. The LMD-produced alloy revealed full density, strongly reduced segregation compared to conventionally cast material, pronounced texture, and excellent mechanical properties. Phase constitution and elemental distribution were correctly predicted by simulations. The applicability of the introduced methodology to high-entropy alloys and extension to compositionally complex alloys is discussed.

  13. Uncertainty Quantification in High Throughput Screening ...

    Science.gov (United States)

    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

  14. HTTK: R Package for High-Throughput Toxicokinetics

    Science.gov (United States)

    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...

  15. Fun with High Throughput Toxicokinetics (CalEPA webinar)

    Science.gov (United States)

    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 ...

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

    NARCIS (Netherlands)

    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

  17. ZNStress: a high-throughput drug screening protocol for identification of compounds modulating neuronal stress in the transgenic mutant sod1G93R zebrafish model of amyotrophic lateral sclerosis.

    Science.gov (United States)

    McGown, Alexander; Shaw, Dame Pamela J; Ramesh, Tennore

    2016-07-26

    Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease with death on average within 2-3 years of symptom onset. Mutations in superoxide dismutase 1 (SOD1) have been identified to cause ALS. Riluzole, the only neuroprotective drug for ALS provides life extension of only 3 months on average. Thishighlights the need for compound screening in disease models to identify new neuroprotective therapies for this disease. Zebrafish is an emerging model system that is well suited for the study of diseasepathophysiology and also for high throughput (HT) drug screening. The mutant sod1 zebrafish model of ALS mimics the hallmark features of ALS. Using a fluorescence based readout of neuronal stress, we developed a high throughput (HT) screen to identify neuroprotective compounds. Here we show that the zebrafish screen is a robust system that can be used to rapidly screen thousands ofcompounds and also demonstrate that riluzole is capable of reducing neuronal stress in this model system. The screen shows optimal quality control, maintaining a high sensitivity and specificity withoutcompromising throughput. Most importantly, we demonstrate that many compounds previously failed in human clinical trials, showed no stress reducing activity in the zebrafish assay. We conclude that HT drug screening using a mutant sod1 zebrafish is a reliable model system which supplemented with secondary assays would be useful in identifying drugs with potential for neuroprotective efficacy in ALS.

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

    Science.gov (United States)

    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. High throughput sample processing and automated scoring

    Directory of Open Access Journals (Sweden)

    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.

  20. High Throughput Analysis of Photocatalytic Water Purification

    NARCIS (Netherlands)

    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

  1. High-throughput scoring of seed germination

    NARCIS (Netherlands)

    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

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

    DEFF Research Database (Denmark)

    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...

  3. High Throughput Neuro-Imaging Informatics

    Directory of Open Access Journals (Sweden)

    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.

  4. High-throughput bioinformatics with the Cyrille2 pipeline system

    Directory of Open Access Journals (Sweden)

    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.

  5. High throughput screening method for assessing heterogeneity of microorganisms

    NARCIS (Netherlands)

    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.

  6. An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

    Science.gov (United States)

    Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

    2016-01-01

    The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

  7. High-Throughput Scoring of Seed Germination.

    Science.gov (United States)

    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.

  8. High throughput nonparametric probability density estimation.

    Science.gov (United States)

    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.

  9. Preliminary High-Throughput Metagenome Assembly

    Energy Technology Data Exchange (ETDEWEB)

    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).

  10. Optimization of de novo transcriptome assembly from high-throughput short read sequencing data improves functional annotation for non-model organisms

    Directory of Open Access Journals (Sweden)

    Haznedaroglu Berat Z

    2012-07-01

    Full Text Available Abstract Background The k-mer hash length is a key factor affecting the output of de novo transcriptome assembly packages using de Bruijn graph algorithms. Assemblies constructed with varying single k-mer choices might result in the loss of unique contiguous sequences (contigs and relevant biological information. A common solution to this problem is the clustering of single k-mer assemblies. Even though annotation is one of the primary goals of a transcriptome assembly, the success of assembly strategies does not consider the impact of k-mer selection on the annotation output. This study provides an in-depth k-mer selection analysis that is focused on the degree of functional annotation achieved for a non-model organism where no reference genome information is available. Individual k-mers and clustered assemblies (CA were considered using three representative software packages. Pair-wise comparison analyses (between individual k-mers and CAs were produced to reveal missing Kyoto Encyclopedia of Genes and Genomes (KEGG ortholog identifiers (KOIs, and to determine a strategy that maximizes the recovery of biological information in a de novo transcriptome assembly. Results Analyses of single k-mer assemblies resulted in the generation of various quantities of contigs and functional annotations within the selection window of k-mers (k-19 to k-63. For each k-mer in this window, generated assemblies contained certain unique contigs and KOIs that were not present in the other k-mer assemblies. Producing a non-redundant CA of k-mers 19 to 63 resulted in a more complete functional annotation than any single k-mer assembly. However, a fraction of unique annotations remained (~0.19 to 0.27% of total KOIs in the assemblies of individual k-mers (k-19 to k-63 that were not present in the non-redundant CA. A workflow to recover these unique annotations is presented. Conclusions This study demonstrated that different k-mer choices result in various quantities

  11. A high throughput platform for understanding the influence of excipients on physical and chemical stability

    DEFF Research Database (Denmark)

    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....

  12. High-Throughput Analysis of Enzyme Activities

    Energy Technology Data Exchange (ETDEWEB)

    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

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

    Science.gov (United States)

    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.

  14. High-Throughput Process Development for Biopharmaceuticals.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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

  18. Ultraspecific probes for high throughput HLA typing

    Directory of Open Access Journals (Sweden)

    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.

  19. 20180311 - High Throughput Transcriptomics: From screening to pathways (SOT 2018)

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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...

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

    Directory of Open Access Journals (Sweden)

    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

  2. High-throughput characterization methods for lithium batteries

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  4. High-throughput mouse genotyping using robotics automation.

    Science.gov (United States)

    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/.

  5. Advances in analytical tools for high throughput strain engineering

    DEFF Research Database (Denmark)

    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...

  6. Template-based protein-protein docking exploiting pairwise interfacial residue restraints

    NARCIS (Netherlands)

    Xue, Li C; Garcia Lopes Maia Rodrigues, João; Dobbs, Drena; Honavar, Vasant; Bonvin, Alexandre M J J

    2016-01-01

    Although many advanced and sophisticatedab initioapproaches for modeling protein-protein complexes have been proposed in past decades, template-based modeling (TBM) remains the most accurate and widely used approach, given a reliable template is available. However, there are many different ways to

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

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    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).

  9. High throughput screening of starch structures using carbohydrate microarrays

    DEFF Research Database (Denmark)

    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...

  10. High-Throughput Analysis and Automation for Glycomics Studies

    NARCIS (Netherlands)

    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

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  14. Development of scalable high throughput fermentation approaches for physiological characterisation of yeast and filamentous fungi

    DEFF Research Database (Denmark)

    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...

  15. High-Throughput Dietary Exposure Predictions for Chemical Migrants from Food Packaging Materials

    Science.gov (United States)

    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)

    Science.gov (United States)

    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. Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format

    OpenAIRE

    Salvo-Chirnside, Eliane; Kane, Steven; Kerr, Lorraine E

    2011-01-01

    Abstract The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP) methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated p...

  18. High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  3. Template based rodent brain extraction and atlas mapping.

    Science.gov (United States)

    Weimin Huang; Jiaqi Zhang; Zhiping Lin; Su Huang; Yuping Duan; Zhongkang Lu

    2016-08-01

    Accurate rodent brain extraction is the basic step for many translational studies using MR imaging. This paper presents a template based approach with multi-expert refinement to automatic rodent brain extraction. We first build the brain appearance model based on the learning exemplars. Together with the template matching, we encode the rodent brain position into the search space to reliably locate the rodent brain and estimate the rough segmentation. With the initial mask, a level-set segmentation and a mask-based template learning are implemented further to the brain region. The multi-expert fusion is used to generate a new mask. We finally combine the region growing based on the histogram distribution learning to delineate the final brain mask. A high-resolution rodent atlas is used to illustrate that the segmented low resolution anatomic image can be well mapped to the atlas. Tested on a public data set, all brains are located reliably and we achieve the mean Jaccard similarity score at 94.99% for brain segmentation, which is a statistically significant improvement compared to two other rodent brain extraction methods.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Towards a high throughput droplet-based agglutination assay

    KAUST Repository

    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.

  8. Towards a high throughput droplet-based agglutination assay

    KAUST Repository

    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.

  9. High-throughput proteomics : optical approaches.

    Energy Technology Data Exchange (ETDEWEB)

    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.

  10. High-throughput heterogeneous catalyst research

    Science.gov (United States)

    Turner, Howard W.; Volpe, Anthony F., Jr.; Weinberg, W. H.

    2009-06-01

    With the discovery of abundant and low cost crude oil in the early 1900's came the need to create efficient conversion processes to produce low cost fuels and basic chemicals. Enormous investment over the last century has led to the development of a set of highly efficient catalytic processes which define the modern oil refinery and which produce most of the raw materials and fuels used in modern society. Process evolution and development has led to a refining infrastructure that is both dominated and enabled by modern heterogeneous catalyst technologies. Refineries and chemical manufacturers are currently under intense pressure to improve efficiency, adapt to increasingly disadvantaged feedstocks including biomass, lower their environmental footprint, and continue to deliver their products at low cost. This pressure creates a demand for new and more robust catalyst systems and processes that can accommodate them. Traditional methods of catalyst synthesis and testing are slow and inefficient, particularly in heterogeneous systems where the structure of the active sites is typically complex and the reaction mechanism is at best ill-defined. While theoretical modeling and a growing understanding of fundamental surface science help guide the chemist in designing and synthesizing targets, even in the most well understood areas of catalysis, the parameter space that one needs to explore experimentally is vast. The result is that the chemist using traditional methods must navigate a complex and unpredictable diversity space with a limited data set to make discoveries or to optimize known systems. We describe here a mature set of synthesis and screening technologies that together form a workflow that breaks this traditional paradigm and allows for rapid and efficient heterogeneous catalyst discovery and optimization. We exemplify the power of these new technologies by describing their use in the development and commercialization of a novel catalyst for the

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

    KAUST Repository

    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.

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

    KAUST Repository

    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.

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

    Science.gov (United States)

    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.

  14. High-throughput cloning and expression in recalcitrant bacteria

    NARCIS (Netherlands)

    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

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

    NARCIS (Netherlands)

    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

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

    Science.gov (United States)

    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.

  17. Template-based automatic breast segmentation on MRI by excluding the chest region

    OpenAIRE

    Lin, M; Chen, JH; Wang, X; Chan, S; Chen, S; Su, MY

    2013-01-01

    Purpose: Methods for quantification of breast density on MRI using semiautomatic approaches are commonly used. In this study, the authors report on a fully automatic chest template-based method. Methods: Nonfat-suppressed breast MR images from 31 healthy women were analyzed. Among them, one case was randomly selected and used as th e template, and the remaining 30 cases were used for testing. Unlike most model-based breast segmentation methods that use the breast region as the template, the c...

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

    Science.gov (United States)

    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.

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

    OpenAIRE

    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 ...

  20. The French press: a repeatable and high-throughput approach to exercising zebrafish (Danio rerio).

    Science.gov (United States)

    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.

  1. Selection and optimization of hits from a high-throughput phenotypic screen against Trypanosoma cruzi.

    Science.gov (United States)

    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.

  2. Determining the optimal size of small molecule mixtures for high throughput NMR screening

    International Nuclear Information System (INIS)

    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

  3. Multiple and high-throughput droplet reactions via combination of microsampling technique and microfluidic chip

    KAUST Repository

    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.

  4. High throughput 16S rRNA gene amplicon sequencing

    DEFF Research Database (Denmark)

    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...

  5. High-throughput theoretical design of lithium battery materials

    International Nuclear Information System (INIS)

    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)

  6. A CRISPR CASe for High-Throughput Silencing

    Directory of Open Access Journals (Sweden)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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.

  9. High-throughput epitope identification for snakebite antivenom

    DEFF Research Database (Denmark)

    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...

  10. High-throughput optical system for HDES hyperspectral imager

    Science.gov (United States)

    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.

  11. Computational tools for high-throughput discovery in biology

    OpenAIRE

    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...

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

    International Nuclear Information System (INIS)

    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

  13. High-throughput sequence alignment using Graphics Processing Units

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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

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

    DEFF Research Database (Denmark)

    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....

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

    CERN Multimedia

    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.

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

    Science.gov (United States)

    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/.

  18. High-Throughput Block Optical DNA Sequence Identification.

    Science.gov (United States)

    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.

  19. High throughput comet assay to study genotoxicity of nanomaterials

    Directory of Open Access Journals (Sweden)

    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

  20. High-throughput purification of recombinant proteins using self-cleaving intein tags.

    Science.gov (United States)

    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.

  1. Assessing Morphological and Physiological Properties of Forest Species Using High Throughput Plant Phenotyping and Imaging Techniques

    Science.gov (United States)

    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

  2. Julius – a template based supplementary electronic health record system

    Directory of Open Access Journals (Sweden)

    Klein Gunnar O

    2007-05-01

    Full Text Available Abstract Background EHR systems are widely used in hospitals and primary care centres but it is usually difficult to share information and to collect patient data for clinical research. This is partly due to the different proprietary information models and inconsistent data quality. Our objective was to provide a more flexible solution enabling the clinicians to define which data to be recorded and shared for both routine documentation and clinical studies. The data should be possible to reuse through a common set of variable definitions providing a consistent nomenclature and validation of data. Another objective was that the templates used for the data entry and presentation should be possible to use in combination with the existing EHR systems. Methods We have designed and developed a template based system (called Julius that was integrated with existing EHR systems. The system is driven by the medical domain knowledge defined by clinicians in the form of templates and variable definitions stored in a common data repository. The system architecture consists of three layers. The presentation layer is purely web-based, which facilitates integration with existing EHR products. The domain layer consists of the template design system, a variable/clinical concept definition system, the transformation and validation logic all implemented in Java. The data source layer utilizes an object relational mapping tool and a relational database. Results The Julius system has been implemented, tested and deployed to three health care units in Stockholm, Sweden. The initial responses from the pilot users were positive. The template system facilitates patient data collection in many ways. The experience of using the template system suggests that enabling the clinicians to be in control of the system, is a good way to add supplementary functionality to the present EHR systems. Conclusion The approach of the template system in combination with various local EHR

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

    National Research Council Canada - National Science Library

    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...

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

    National Research Council Canada - National Science Library

    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...

  5. High throughput experimentation for the discovery of new catalysts

    International Nuclear Information System (INIS)

    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

  6. High-throughput screening to enhance oncolytic virus immunotherapy

    Directory of Open Access Journals (Sweden)

    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

  7. Optimizing transformations for automated, high throughput analysis of flow cytometry data.

    Science.gov (United States)

    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

  8. Optimizing transformations for automated, high throughput analysis of flow cytometry data

    Directory of Open Access Journals (Sweden)

    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

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

    International Nuclear Information System (INIS)

    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)

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

    Science.gov (United States)

    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.

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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 System for Plant Height and Hyperspectral Measurement

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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.

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

    Science.gov (United States)

    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.

  19. Spectrophotometric Enzyme Assays for High-Throughput Screening

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  1. HIGH THROUGHPUT SYSTEM FOR PLANT HEIGHT AND HYPERSPECTRAL MEASUREMENT

    Directory of Open Access Journals (Sweden)

    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.

  2. Zebrafish: A marvel of high-throughput biology for 21st century toxicology.

    Science.gov (United States)

    Bugel, Sean M; Tanguay, Robert L; Planchart, Antonio

    2014-09-07

    The evolutionary conservation of genomic, biochemical and developmental features between zebrafish and humans is gradually coming into focus with the end result that the zebrafish embryo model has emerged as a powerful tool for uncovering the effects of environmental exposures on a multitude of biological processes with direct relevance to human health. In this review, we highlight advances in automation, high-throughput (HT) screening, and analysis that leverage the power of the zebrafish embryo model for unparalleled advances in our understanding of how chemicals in our environment affect our health and wellbeing.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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.

  5. High-throughput technology for novel SO2 oxidation catalysts

    International Nuclear Information System (INIS)

    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)

  6. Fluorescent foci quantitation for high-throughput analysis

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  8. High-throughput GPU-based LDPC decoding

    Science.gov (United States)

    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.

  9. The JCSG high-throughput structural biology pipeline

    International Nuclear Information System (INIS)

    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

  10. High-throughput characterization for solar fuels materials discovery

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  12. COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING

    Directory of Open Access Journals (Sweden)

    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.

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

    International Nuclear Information System (INIS)

    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

  14. “httk”: EPA’s Tool for High Throughput Toxicokinetics (CompTox CoP)

    Science.gov (United States)

    Thousands of chemicals have been pro?led 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 concentr...

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

    Science.gov (United States)

    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...

  16. High-Throughput Lipolysis in 96-Well Plates for Rapid Screening of Lipid-Based Drug Delivery Systems

    DEFF Research Database (Denmark)

    Mosgaard, Mette D; Sassene, Philip J; Mu, Huiling

    2017-01-01

    The high-throughput in vitro intestinal lipolysis model (HTP) applicable for rapid and low-scale screening of lipid-based drug delivery systems (LbDDSs) was optimized and adjusted as to be conducted in 96-well plates (HTP-96). Three different LbDDSs (I-III) loaded with danazol or cinnarizine were...

  17. Testing candidate genes for attention-deficit/hyperactivity disorder in fruit flies using a high throughput assay for complex behavior

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Madsen, Lisbeth Strøm; Arvidson, Sandra Marie Neumann

    2016-01-01

    Fruit flies are important model organisms for functional testing of candidate genes in multiple disciplines, including the study of human diseases. Here we use a high-throughput locomotor activity assay to test the response on activity behavior of gene disruption in Drosophila melanogaster. The aim...

  18. ZNStress: a high-throughput drug screening protocol for identification of compounds modulating neuronal stress in the transgenic mutant sod1G93R zebrafish model of amyotrophic lateral sclerosis

    OpenAIRE

    McGown, Alexander; Shaw, Dame Pamela J.; Ramesh, Tennore

    2016-01-01

    Background Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease with death on average within 2?3 years of symptom onset. Mutations in superoxide dismutase 1 (SOD1) have been identified to cause ALS. Riluzole, the only neuroprotective drug for ALS provides life extension of only 3 months on average. Thishighlights the need for compound screening in disease models to identify new neuroprotective therapies for this disease. Zebrafish is an emerging model system that is well ...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  4. The Principals and Practice of Distributed High Throughput Computing

    CERN Multimedia

    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...

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

    CERN Multimedia

    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...

  6. High Throughput In Situ XAFS Screening of Catalysts

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  13. A high-throughput method for assessing chemical toxicity using a Caenorhabditis elegans reproduction assay

    International Nuclear Information System (INIS)

    Boyd, Windy A.; McBride, Sandra J.; Rice, Julie R.; Snyder, Daniel W.; Freedman, Jonathan H.

    2010-01-01

    The National Research Council has outlined the need for non-mammalian toxicological models to test the potential health effects of a large number of chemicals while also reducing the use of traditional animal models. The nematode Caenorhabditis elegans is an attractive alternative model because of its well-characterized and evolutionarily conserved biology, low cost, and ability to be used in high-throughput screening. A high-throughput method is described for quantifying the reproductive capacity of C. elegans exposed to chemicals for 48 h from the last larval stage (L4) to adulthood using a COPAS Biosort. Initially, the effects of exposure conditions that could influence reproduction were defined. Concentrations of DMSO vehicle ≤ 1% did not affect reproduction. Previous studies indicated that C. elegans may be influenced by exposure to low pH conditions. At pHs greater than 4.5, C. elegans reproduction was not affected; however below this pH there was a significant decrease in the number of offspring. Cadmium chloride was chosen as a model toxicant to verify that automated measurements were comparable to those of traditional observational studies. EC 50 values for cadmium for automated measurements (176-192 μM) were comparable to those previously reported for a 72-h exposure using manual counting (151 μM). The toxicity of seven test toxicants on C. elegans reproduction was highly correlative with rodent lethality suggesting that this assay may be useful in predicting the potential toxicity of chemicals in other organisms.

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

    Science.gov (United States)

    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 ).

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

    Science.gov (United States)

    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.

  16. High-throughput combinatorial chemical bath deposition: The case of doping Cu (In, Ga) Se film with antimony

    Science.gov (United States)

    Yan, Zongkai; Zhang, Xiaokun; Li, Guang; Cui, Yuxing; Jiang, Zhaolian; Liu, Wen; Peng, Zhi; Xiang, Yong

    2018-01-01

    The conventional methods for designing and preparing thin film based on wet process remain a challenge due to disadvantages such as time-consuming and ineffective, which hinders the development of novel materials. Herein, we present a high-throughput combinatorial technique for continuous thin film preparation relied on chemical bath deposition (CBD). The method is ideally used to prepare high-throughput combinatorial material library with low decomposition temperatures and high water- or oxygen-sensitivity at relatively high-temperature. To check this system, a Cu(In, Ga)Se (CIGS) thin films library doped with 0-19.04 at.% of antimony (Sb) was taken as an example to evaluate the regulation of varying Sb doping concentration on the grain growth, structure, morphology and electrical properties of CIGS thin film systemically. Combined with the Energy Dispersive Spectrometer (EDS), X-ray Photoelectron Spectroscopy (XPS), automated X-ray Diffraction (XRD) for rapid screening and Localized Electrochemical Impedance Spectroscopy (LEIS), it was confirmed that this combinatorial high-throughput system could be used to identify the composition with the optimal grain orientation growth, microstructure and electrical properties systematically, through accurately monitoring the doping content and material composition. According to the characterization results, a Sb2Se3 quasi-liquid phase promoted CIGS film-growth model has been put forward. In addition to CIGS thin film reported here, the combinatorial CBD also could be applied to the high-throughput screening of other sulfide thin film material systems.

  17. Template based parallel checkpointing in a massively parallel computer system

    Science.gov (United States)

    Archer, Charles Jens [Rochester, MN; Inglett, Todd Alan [Rochester, MN

    2009-01-13

    A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.

  18. Automated high-throughput measurement of body movements and cardiac activity of Xenopus tropicalis tadpoles

    Directory of Open Access Journals (Sweden)

    Kay Eckelt

    2014-07-01

    Full Text Available Xenopus tadpoles are an emerging model for developmental, genetic and behavioral studies. A small size, optical accessibility of most of their organs, together with a close genetic and structural relationship to humans make them a convenient experimental model. However, there is only a limited toolset available to measure behavior and organ function of these animals at medium or high-throughput. Herein, we describe an imaging-based platform to quantify body and autonomic movements of Xenopus tropicalis tadpoles of advanced developmental stages. Animals alternate periods of quiescence and locomotor movements and display buccal pumping for oxygen uptake from water and rhythmic cardiac movements. We imaged up to 24 animals in parallel and automatically tracked and quantified their movements by using image analysis software. Animal trajectories, moved distances, activity time, buccal pumping rates and heart beat rates were calculated and used to characterize the effects of test compounds. We evaluated the effects of propranolol and atropine, observing a dose-dependent bradycardia and tachycardia, respectively. This imaging and analysis platform is a simple, cost-effective high-throughput in vivo assay system for genetic, toxicological or pharmacological characterizations.

  19. Sources of PCR-induced distortions in high-throughput sequencing data sets

    Science.gov (United States)

    Kebschull, Justus M.; Zador, Anthony M.

    2015-01-01

    PCR permits the exponential and sequence-specific amplification of DNA, even from minute starting quantities. PCR is a fundamental step in preparing DNA samples for high-throughput sequencing. However, there are errors associated with PCR-mediated amplification. Here we examine the effects of four important sources of error—bias, stochasticity, template switches and polymerase errors—on sequence representation in low-input next-generation sequencing libraries. We designed a pool of diverse PCR amplicons with a defined structure, and then used Illumina sequencing to search for signatures of each process. We further developed quantitative models for each process, and compared predictions of these models to our experimental data. We find that PCR stochasticity is the major force skewing sequence representation after amplification of a pool of unique DNA amplicons. Polymerase errors become very common in later cycles of PCR but have little impact on the overall sequence distribution as they are confined to small copy numbers. PCR template switches are rare and confined to low copy numbers. Our results provide a theoretical basis for removing distortions from high-throughput sequencing data. In addition, our findings on PCR stochasticity will have particular relevance to quantification of results from single cell sequencing, in which sequences are represented by only one or a few molecules. PMID:26187991

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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

  2. SNP-PHAGE – High throughput SNP discovery pipeline

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

    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

  4. An Improved Methodology for Multidimensional High-Throughput Preformulation Characterization of Protein Conformational Stability

    Science.gov (United States)

    Maddux, Nathaniel R.; Rosen, Ilan T.; Hu, Lei; Olsen, Christopher M.; Volkin, David B.; Middaugh, C. Russell

    2013-01-01

    The Empirical Phase Diagram (EPD) technique is a vector-based multidimensional analysis method for summarizing large data sets from a variety of biophysical techniques. It can be used to provide comprehensive preformulation characterization of a macromolecule’s higher-order structural integrity and conformational stability. In its most common mode, it represents a type of stimulus-response diagram using environmental variables such as temperature, pH, and ionic strength as the stimulus, with alterations in macromolecular structure being the response. Until now EPD analysis has not been available in a high throughput mode because of the large number of experimental techniques and environmental stressor/stabilizer variables typically employed. A new instrument has been developed that combines circular dichroism, UV-absorbance, fluorescence spectroscopy and light scattering in a single unit with a 6-position temperature controlled cuvette turret. Using this multifunctional instrument and a new software system we have generated EPDs for four model proteins. Results confirm the reproducibility of the apparent phase boundaries and protein behavior within the boundaries. This new approach permits two EPDs to be generated per day using only 0.5 mg of protein per EPD. Thus, the new methodology generates reproducible EPDs in high-throughput mode, and represents the next step in making such determinations more routine. PMID:22447621

  5. A high throughput biochemical fluorometric method for measuring lipid peroxidation in HDL.

    Directory of Open Access Journals (Sweden)

    Theodoros Kelesidis

    Full Text Available Current cell-based assays for determining the functional properties of high-density lipoproteins (HDL have limitations. We report here the development of a new, robust fluorometric cell-free biochemical assay that measures HDL lipid peroxidation (HDLox based on the oxidation of the fluorochrome Amplex Red. HDLox correlated with previously validated cell-based (r = 0.47, p<0.001 and cell-free assays (r = 0.46, p<0.001. HDLox distinguished dysfunctional HDL in established animal models of atherosclerosis and Human Immunodeficiency Virus (HIV patients. Using an immunoaffinity method for capturing HDL, we demonstrate the utility of this novel assay for measuring HDLox in a high throughput format. Furthermore, HDLox correlated significantly with measures of cardiovascular diseases including carotid intima media thickness (r = 0.35, p<0.01 and subendocardial viability ratio (r = -0.21, p = 0.05 and physiological parameters such as metabolic and anthropometric parameters (p<0.05. In conclusion, we report the development of a new fluorometric method that offers a reproducible and rapid means for determining HDL function/quality that is suitable for high throughput implementation.

  6. A multi-endpoint, high-throughput study of nanomaterial toxicity in Caenorhabditis elegans

    Science.gov (United States)

    Jung, Sang-Kyu; Qu, Xiaolei; Aleman-Meza, Boanerges; Wang, Tianxiao; Riepe, Celeste; Liu, Zheng; Li, Qilin; Zhong, Weiwei

    2015-01-01

    The booming nanotech industry has raised public concerns about the environmental health and safety impact of engineered nanomaterials (ENMs). High-throughput assays are needed to obtain toxicity data for the rapidly increasing number of ENMs. Here we present a suite of high-throughput methods to study nanotoxicity in intact animals using Caenorhabditis elegans as a model. At the population level, our system measures food consumption of thousands of animals to evaluate population fitness. At the organism level, our automated system analyzes hundreds of individual animals for body length, locomotion speed, and lifespan. To demonstrate the utility of our system, we applied this technology to test the toxicity of 20 nanomaterials under four concentrations. Only fullerene nanoparticles (nC60), fullerol, TiO2, and CeO2 showed little or no toxicity. Various degrees of toxicity were detected from different forms of carbon nanotubes, graphene, carbon black, Ag, and fumed SiO2 nanoparticles. Aminofullerene and UV irradiated nC60 also showed small but significant toxicity. We further investigated the effects of nanomaterial size, shape, surface chemistry, and exposure conditions on toxicity. Our data are publicly available at the open-access nanotoxicity database www.QuantWorm.org/nano. PMID:25611253

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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/.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  2. High-Throughput Network Communication with NetIO

    CERN Document Server

    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...

  3. High Throughput Sequencing for Detection of Foodborne Pathogens

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  7. High-Throughput Printing Process for Flexible Electronics

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  9. Towards Prebiotic Catalytic Amyloids Using High Throughput Screening.

    Directory of Open Access Journals (Sweden)

    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.

  10. Probabilistic Methods for Processing High-Throughput Sequencing Signals

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  14. High Throughput T Epitope Mapping and Vaccine Development

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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

  16. High-Throughput DNA sequencing of ancient wood.

    Science.gov (United States)

    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.

  17. Iron oxide nanotubes synthesized via template-based electrodeposition

    Science.gov (United States)

    Lim, Jin-Hee; Min, Seong-Gi; Malkinski, Leszek; Wiley, John B.

    2014-04-01

    Considerable effort has been invested in the development of synthetic methods for the preparation iron oxide nanostructures for applications in nanotechnology. While a variety of structures have been reported, only a few studies have focused on iron oxide nanotubes. Here, we present details on the synthesis and characterization of iron oxide nanotubes along with a proposed mechanism for FeOOH tube formation. The FeOOH nanotubes, fabricated via a template-based electrodeposition method, are found to exhibit a unique inner-surface. Heat treatment of these tubes under oxidizing or reducing atmospheres can produce either hematite (α-Fe2O3) or magnetite (Fe3O4) structures, respectively. Hematite nanotubes are composed of small nanoparticles less than 20 nm in diameter and the magnetization curves and FC-ZFC curves show superparamagnetic properties without the Morin transition. In the case of magnetite nanotubes, which consist of slightly larger nanoparticles, magnetization curves show ferromagnetism with weak coercivity at room temperature, while FC-ZFC curves exhibit the Verwey transition at 125 K.Considerable effort has been invested in the development of synthetic methods for the preparation iron oxide nanostructures for applications in nanotechnology. While a variety of structures have been reported, only a few studies have focused on iron oxide nanotubes. Here, we present details on the synthesis and characterization of iron oxide nanotubes along with a proposed mechanism for FeOOH tube formation. The FeOOH nanotubes, fabricated via a template-based electrodeposition method, are found to exhibit a unique inner-surface. Heat treatment of these tubes under oxidizing or reducing atmospheres can produce either hematite (α-Fe2O3) or magnetite (Fe3O4) structures, respectively. Hematite nanotubes are composed of small nanoparticles less than 20 nm in diameter and the magnetization curves and FC-ZFC curves show superparamagnetic properties without the Morin transition

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

    Directory of Open Access Journals (Sweden)

    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

  19. Template-based electrophoretic deposition of perovskite PZT nanotubes

    Energy Technology Data Exchange (ETDEWEB)

    Nourmohammadi, A. [Solid Surfaces Analysis and Electron Microscopy Group, Institute of Physics, Chemnitz University of Technology, D-09126 Chemnitz (Germany); Semiconductors Department, Materials and Energy Research Center (MERC), 31779-83634 Karaj (Iran, Islamic Republic of); Bahrevar, M.A. [Semiconductors Department, Materials and Energy Research Center (MERC), 31779-83634 Karaj (Iran, Islamic Republic of)], E-mail: ma.bahrevar@yahoo.com; Hietschold, M. [Solid Surfaces Analysis and Electron Microscopy Group, Institute of Physics, Chemnitz University of Technology, D-09126 Chemnitz (Germany)

    2009-04-03

    Template-based electrophoretic deposition of perovskite lead zirconate titanate (PZT) nanotubes was achieved using anodic alumina (AA) membranes and sols, containing lead, zirconium and titanium precursors. The effect of various anodizing voltages on the size of the channels in the anodic alumina template was investigated. The prepared sol was driven into the channels under the influence of various electric fields and subsequently sintered at about 700 deg. C. The effects of the initial heating rates and the burn-out temperature on the phase evolution of the samples were studied and a modified firing process was employed. The effects of the electrophoretic voltage and the deposition time on the average wall thickness of the tubes were investigated. Scanning and transmission electron microscopy (SEM and TEM) revealed the efficiency of electrophoresis in the growth of lead zirconate titanate nanotubes in a close-packed array. The X-ray diffraction analyses indicated the presence of perovskite as the principal phase after a modified firing schedule.

  20. Template-based education toolkit for mobile platforms

    Science.gov (United States)

    Golagani, Santosh Chandana; Esfahanian, Moosa; Akopian, David

    2012-02-01

    Nowadays mobile phones are the most widely used portable devices which evolve very fast adding new features and improving user experiences. The latest generation of hand-held devices called smartphones is equipped with superior memory, cameras and rich multimedia features, empowering people to use their mobile phones not only as a communication tool but also for entertainment purposes. With many young students showing interest in learning mobile application development one should introduce novel learning methods which may adapt to fast technology changes and introduce students to application development. Mobile phones become a common device, and engineering community incorporates phones in various solutions. Overcoming the limitations of conventional undergraduate electrical engineering (EE) education this paper explores the concept of template-based based education in mobile phone programming. The concept is based on developing small exercise templates which students can manipulate and revise for quick hands-on introduction to the application development and integration. Android platform is used as a popular open source environment for application development. The exercises relate to image processing topics typically studied by many students. The goal is to enable conventional course enhancements by incorporating in them short hands-on learning modules.

  1. High Throughput and Mechano-Active Platforms to Promote Cartilage Regeneration and Repair

    Science.gov (United States)

    Mohanraj, Bhavana

    Traumatic joint injuries initiate acute degenerative changes in articular cartilage that can lead to progressive loss of load-bearing function. As a result, patients often develop post-traumatic osteoarthritis (PTOA), a condition for which there currently exists no biologic interventions. To address this need, tissue engineering aims to mimic the structure and function of healthy, native counterparts. These constructs can be used to not only replace degenerated tissue, but also build in vitro, pre-clinical models of disease. Towards this latter goal, this thesis focuses on the design of a high throughput system to screen new therapeutics in a micro-engineered model of PTOA, and the development of a mechanically-responsive drug delivery system to augment tissue-engineered approaches for cartilage repair. High throughput screening is a powerful tool for drug discovery that can be adapted to include 3D tissue constructs. To facilitate this process for cartilage repair, we built a high throughput mechanical injury platform to create an engineered cartilage model of PTOA. Compressive injury of functionally mature constructs increased cell death and proteoglycan loss, two hallmarks of injury observed in vivo. Comparison of this response to that of native cartilage explants, and evaluation of putative therapeutics, validated this model for subsequent use in small molecule screens. A primary screen of 118 compounds identified a number of 'hits' and relevant pathways that may modulate pathologic signaling post-injury. To complement this process of therapeutic discovery, a stimuli-responsive delivery system was designed that used mechanical inputs as the 'trigger' mechanism for controlled release. The failure thresholds of these mechanically-activated microcapsules (MAMCs) were influenced by physical properties and composition, as well as matrix mechanical properties in 3D environments. TGF-beta released from the system upon mechano-activation stimulated stem cell

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    International Nuclear Information System (INIS)

    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)

  5. Towards Chip Scale Liquid Chromatography and High Throughput Immunosensing

    Energy Technology Data Exchange (ETDEWEB)

    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

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

    Science.gov (United States)

    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.

  7. High-Throughput Next-Generation Sequencing of Polioviruses

    Science.gov (United States)

    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

  8. Scanning fluorescence detector for high-throughput DNA genotyping

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

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

    KAUST Repository

    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.

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

    KAUST Repository

    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.

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

    NARCIS (Netherlands)

    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

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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...

  17. A hybrid MAC protocol design for energy-efficient very-high-throughput millimeter wave, wireless sensor communication networks

    Science.gov (United States)

    Jian, Wei; Estevez, Claudio; Chowdhury, Arshad; Jia, Zhensheng; Wang, Jianxin; Yu, Jianguo; Chang, Gee-Kung

    2010-12-01

    This paper presents an energy-efficient Medium Access Control (MAC) protocol for very-high-throughput millimeter-wave (mm-wave) wireless sensor communication networks (VHT-MSCNs) based on hybrid multiple access techniques of frequency division multiplexing access (FDMA) and time division multiplexing access (TDMA). An energy-efficient Superframe for wireless sensor communication network employing directional mm-wave wireless access technologies is proposed for systems that require very high throughput, such as high definition video signals, for sensing, processing, transmitting, and actuating functions. Energy consumption modeling for each network element and comparisons among various multi-access technologies in term of power and MAC layer operations are investigated for evaluating the energy-efficient improvement of proposed MAC protocol.

  18. A novel hanging spherical drop system for the generation of cellular spheroids and high throughput combinatorial drug screening.

    Science.gov (United States)

    Neto, A I; Correia, C R; Oliveira, M B; Rial-Hermida, M I; Alvarez-Lorenzo, C; Reis, R L; Mano, J F

    2015-04-01

    We propose a novel hanging spherical drop system for anchoring arrays of droplets of cell suspension based on the use of biomimetic superhydrophobic flat substrates, with controlled positional adhesion and minimum contact with a solid substrate. By facing down the platform, it was possible to generate independent spheroid bodies in a high throughput manner, in order to mimic in vivo tumour models on the lab-on-chip scale. To validate this system for drug screening purposes, the toxicity of the anti-cancer drug doxorubicin in cell spheroids was tested and compared to cells in 2D culture. The advantages presented by this platform, such as feasibility of the system and the ability to control the size uniformity of the spheroid, emphasize its potential to be used as a new low cost toolbox for high-throughput drug screening and in cell or tissue engineering.

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

    International Nuclear Information System (INIS)

    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

  20. Statistical methods for the analysis of high-throughput metabolomics data

    Directory of Open Access Journals (Sweden)

    Fabian J. Theis

    2013-01-01

    Full Text Available Metabolomics is a relatively new high-throughput technology that aims at measuring all endogenous metabolites within a biological sample in an unbiased fashion. The resulting metabolic profiles may be regarded as functional signatures of the physiological state, and have been shown to comprise effects of genetic regulation as well as environmental factors. This potential to connect genotypic to phenotypic information promises new insights and biomarkers for different research fields, including biomedical and pharmaceutical research. In the statistical analysis of metabolomics data, many techniques from other omics fields can be reused. However recently, a number of tools specific for metabolomics data have been developed as well. The focus of this mini review will be on recent advancements in the analysis of metabolomics data especially by utilizing Gaussian graphical models and independent component analysis.

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

    Science.gov (United States)

    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.

  2. Hadoop and friends - first experience at CERN with a new platform for high throughput analysis steps

    Science.gov (United States)

    Duellmann, D.; Surdy, K.; Menichetti, L.; Toebbicke, R.

    2017-10-01

    The statistical analysis of infrastructure metrics comes with several specific challenges, including the fairly large volume of unstructured metrics from a large set of independent data sources. Hadoop and Spark provide an ideal environment in particular for the first steps of skimming rapidly through hundreds of TB of low relevance data to find and extract the much smaller data volume that is relevant for statistical analysis and modelling. This presentation will describe the new Hadoop service at CERN and the use of several of its components for high throughput data aggregation and ad-hoc pattern searches. We will describe the hardware setup used, the service structure with a small set of decoupled clusters and the first experience with co-hosting different applications and performing software upgrades. We will further detail the common infrastructure used for data extraction and preparation from continuous monitoring and database input sources.

  3. Efficient high-throughput biological process characterization: Definitive screening design with the ambr250 bioreactor system.

    Science.gov (United States)

    Tai, Mitchell; Ly, Amanda; Leung, Inne; Nayar, Gautam

    2015-01-01

    The burgeoning pipeline for new biologic drugs has increased the need for high-throughput process characterization to efficiently use process development resources. Breakthroughs in highly automated and parallelized upstream process development have led to technologies such as the 250-mL automated mini bioreactor (ambr250™) system. Furthermore, developments in modern design of experiments (DoE) have promoted the use of definitive screening design (DSD) as an efficient method to combine factor screening and characterization. Here we utilize the 24-bioreactor ambr250™ system with 10-factor DSD to demonstrate a systematic experimental workflow to efficiently characterize an Escherichia coli (E. coli) fermentation process for recombinant protein production. The generated process model is further validated by laboratory-scale experiments and shows how the strategy is useful for quality by design (QbD) approaches to control strategies for late-stage characterization. © 2015 American Institute of Chemical Engineers.

  4. A high-throughput in vitro ring assay for vasoactivity using magnetic 3D bioprinting

    Science.gov (United States)

    Tseng, Hubert; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Shen, Tsaiwei; Hebel, Chris; Barthlow, Herbert G.; Wagoner, Matthew; Souza, Glauco R.

    2016-01-01

    Vasoactive liabilities are typically assayed using wire myography, which is limited by its high cost and low throughput. To meet the demand for higher throughput in vitro alternatives, this study introduces a magnetic 3D bioprinting-based vasoactivity assay. The principle behind this assay is the magnetic printing of vascular smooth muscle cells into 3D rings that functionally represent blood vessel segments, whose contraction can be altered by vasodilators and vasoconstrictors. A cost-effective imaging modality employing a mobile device is used to capture contraction with high throughput. The goal of this study was to validate ring contraction as a measure of vasoactivity, using a small panel of known vasoactive drugs. In vitro responses of the rings matched outcomes predicted by in vivo pharmacology, and were supported by immunohistochemistry. Altogether, this ring assay robustly models vasoactivity, which could meet the need for higher throughput in vitro alternatives. PMID:27477945

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

    CERN Document Server

    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.

  6. Label-free detection of cellular drug responses by high-throughput bright-field imaging and machine learning.

    Science.gov (United States)

    Kobayashi, Hirofumi; Lei, Cheng; Wu, Yi; Mao, Ailin; Jiang, Yiyue; Guo, Baoshan; Ozeki, Yasuyuki; Goda, Keisuke

    2017-09-29

    In the last decade, high-content screening based on multivariate single-cell imaging has been proven effective in drug discovery to evaluate drug-induced phenotypic variations. Unfortunately, this method inherently requires fluorescent labeling which has several drawbacks. Here we present a label-free method for evaluating cellular drug responses only by high-throughput bright-field imaging with the aid of machine learning algorithms. Specifically, we performed high-throughput bright-field imaging of numerous drug-treated and -untreated cells (N = ~240,000) by optofluidic time-stretch microscopy with high throughput up to 10,000 cells/s and applied machine learning to the cell images to identify their morphological variations which are too subtle for human eyes to detect. Consequently, we achieved a high accuracy of 92% in distinguishing drug-treated and -untreated cells without the need for labeling. Furthermore, we also demonstrated that dose-dependent, drug-induced morphological change from different experiments can be inferred from the classification accuracy of a single classification model. Our work lays the groundwork for label-free drug screening in pharmaceutical science and industry.

  7. Development of a high-throughput microscale cell disruption platform for Pichia pastoris in rapid bioprocess design.

    Science.gov (United States)

    Bláha, Benjamin A F; Morris, Stephen A; Ogonah, Olotu W; Maucourant, Sophie; Crescente, Vincenzo; Rosenberg, William; Mukhopadhyay, Tarit K

    2018-01-01

    The time and cost benefits of miniaturized fermentation platforms can only be gained by employing complementary techniques facilitating high-throughput at small sample volumes. Microbial cell disruption is a major bottleneck in experimental throughput and is often restricted to large processing volumes. Moreover, for rigid yeast species, such as Pichia pastoris, no effective high-throughput disruption methods exist. The development of an automated, miniaturized, high-throughput, noncontact, scalable platform based on adaptive focused acoustics (AFA) to disrupt P. pastoris and recover intracellular heterologous protein is described. Augmented modes of AFA were established by investigating vessel designs and a novel enzymatic pretreatment step. Three different modes of AFA were studied and compared to the performance high-pressure homogenization. For each of these modes of cell disruption, response models were developed to account for five different performance criteria. Using multiple responses not only demonstrated that different operating parameters are required for different response optima, with highest product purity requiring suboptimal values for other criteria, but also allowed for AFA-based methods to mimic large-scale homogenization processes. These results demonstrate that AFA-mediated cell disruption can be used for a wide range of applications including buffer development, strain selection, fermentation process development, and whole bioprocess integration. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:130-140, 2018. © 2017 American Institute of Chemical Engineers.

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

    Science.gov (United States)

    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.

  9. Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

    Science.gov (United States)

    Lee, Jia-Ying Joey; Miller, James Alastair; Basu, Sreetama; Kee, Ting-Zhen Vanessa; Loo, Lit-Hsin

    2018-06-01

    Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity. This approach is called "High-throughput In vitro Phenotypic Profiling for Toxicity Prediction" (HIPPTox). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks and/or activation of the DNA-damage response (DDR) pathway. Therefore, HIPPTox helps us to uncover these common modes-of-action of pulmonotoxic chemicals. HIPPTox may also be applied to other cell types or models, and accelerate the development of predictive in vitro assays for other cell-type- or organ-specific toxicities.

  10. Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy.

    Science.gov (United States)

    Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

    2017-08-01

    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 analyzing size and number of intracellular bacterial colonies in infected tissue culture cells. Cells are seeded in 48-well plates and infected with a GFP-expressing bacterial pathogen. Following gentamicin treatment to remove extracellular pathogens, cells are fixed and cell nuclei stained. This is followed by automated microscopy and subsequent semi-automated spot detection to determine the number of intracellular bacterial colonies, their size distribution, and the average number per host cell. Multiple 48-well plates can be processed sequentially and the procedure can be completed in one working day. As a model we quantified intracellular bacterial colonies formed by uropathogenic Escherichia coli (UPEC) during infection of human kidney cells (HKC-8). Urinary tract infections caused by UPEC are among the most common bacterial infectious diseases in humans. UPEC can colonize tissues of the urinary tract and is responsible for acute, chronic, and recurrent infections. In the bladder, UPEC can form intracellular quiescent reservoirs, thought to be responsible for recurrent infections. In the kidney, UPEC can colonize renal epithelial cells and pass to the blood stream, either via epithelial cell disruption or transcellular passage, to cause sepsis. Intracellular colonies are known to be clonal, originating from single invading UPEC. In our experimental setup, we found UPEC CFT073 intracellular bacterial colonies to be heterogeneous in size and present in nearly one third of the HKC-8 cells. This high-throughput experimental format substantially reduces experimental time and enables fast screening of the intracellular bacterial load and cellular distribution of multiple

  11. High-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays

    Directory of Open Access Journals (Sweden)

    Crenshaw Andrew

    2009-01-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs have emerged as the genetic marker of choice for mapping disease loci and candidate gene association studies, because of their high density and relatively even distribution in the human genomes. There is a need for systems allowing medium multiplexing (ten to hundreds of SNPs with high throughput, which can efficiently and cost-effectively generate genotypes for a very large sample set (thousands of individuals. Methods that are flexible, fast, accurate and cost-effective are urgently needed. This is also important for those who work on high throughput genotyping in non-model systems where off-the-shelf assays are not available and a flexible platform is needed. Results We demonstrate the use of a nanofluidic Integrated Fluidic Circuit (IFC - based genotyping system for medium-throughput multiplexing known as the Dynamic Array, by genotyping 994 individual human DNA samples on 47 different SNP assays, using nanoliter volumes of reagents. Call rates of greater than 99.5% and call accuracies of greater than 99.8% were achieved from our study, which demonstrates that this is a formidable genotyping platform. The experimental set up is very simple, with a time-to-result for each sample of about 3 hours. Conclusion Our results demonstrate that the Dynamic Array is an excellent genotyping system for medium-throughput multiplexing (30-300 SNPs, which is simple to use and combines rapid throughput with excellent call rates, high concordance and low cost. The exceptional call rates and call accuracy obtained may be of particular interest to those working on validation and replication of genome- wide- association (GWA studies.

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

    Science.gov (United States)

    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.

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

    KAUST Repository

    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

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

    KAUST Repository

    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

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

    DEFF Research Database (Denmark)

    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...

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

    Science.gov (United States)

    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...

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

    OpenAIRE

    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.

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

    DEFF Research Database (Denmark)

    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...

  19. Application of high-throughput sequencing in understanding human oral microbiome related with health and disease

    OpenAIRE

    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...

  20. A template-based approach for responsibility management in executable business processes

    Science.gov (United States)

    Cabanillas, Cristina; Resinas, Manuel; Ruiz-Cortés, Antonio

    2018-05-01

    Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

  1. Use of Threshold of Toxicological Concern (TTC) with High Throughput Exposure Predictions as a Risk-Based Screening Approach to Prioritize More Than Seven Thousand Chemicals (ASCCT)

    Science.gov (United States)

    Here, we present results of an approach for risk-based prioritization using the Threshold of Toxicological Concern (TTC) combined with high-throughput exposure (HTE) modelling. We started with 7968 chemicals with calculated population median oral daily intakes characterized by an...

  2. Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization

    Science.gov (United States)

    Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Shia, BenChang; Ma, Shuangge

    2015-01-01

    In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms “classic” meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance. PMID:24395534

  3. Template-based automatic breast segmentation on MRI by excluding the chest region

    International Nuclear Information System (INIS)

    Lin, Muqing; Chen, Jeon-Hor; Wang, Xiaoyong; Su, Min-Ying; Chan, Siwa; Chen, Siping

    2013-01-01

    Purpose: Methods for quantification of breast density on MRI using semiautomatic approaches are commonly used. In this study, the authors report on a fully automatic chest template-based method. Methods: Nonfat-suppressed breast MR images from 31 healthy women were analyzed. Among them, one case was randomly selected and used as the template, and the remaining 30 cases were used for testing. Unlike most model-based breast segmentation methods that use the breast region as the template, the chest body region on a middle slice was used as the template. Within the chest template, three body landmarks (thoracic spine and bilateral boundary of the pectoral muscle) were identified for performing the initial V-shape cut to determine the posterior lateral boundary of the breast. The chest template was mapped to each subject's image space to obtain a subject-specific chest model for exclusion. On the remaining image, the chest wall muscle was identified and excluded to obtain clean breast segmentation. The chest and muscle boundaries determined on the middle slice were used as the reference for the segmentation of adjacent slices, and the process continued superiorly and inferiorly until all 3D slices were segmented. The segmentation results were evaluated by an experienced radiologist to mark voxels that were wrongly included or excluded for error analysis. Results: The breast volumes measured by the proposed algorithm were very close to the radiologist's corrected volumes, showing a % difference ranging from 0.01% to 3.04% in 30 tested subjects with a mean of 0.86% ± 0.72%. The total error was calculated by adding the inclusion and the exclusion errors (so they did not cancel each other out), which ranged from 0.05% to 6.75% with a mean of 3.05% ± 1.93%. The fibroglandular tissue segmented within the breast region determined by the algorithm and the radiologist were also very close, showing a % difference ranging from 0.02% to 2.52% with a mean of 1.03% ± 1.03%. The

  4. High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts

    Directory of Open Access Journals (Sweden)

    Stefanie Hoffmann

    2018-02-01

    Full Text Available The quantification of bacteria in cell culture infection models is of paramount importance for the characterization of host-pathogen interactions and pathogenicity factors involved. The standard to enumerate bacteria in these assays is plating of a dilution series on solid agar and counting of the resulting colony forming units (CFU. In contrast, the virtual colony count (VCC method is a high-throughput compatible alternative with minimized manual input. Based on the recording of quantitative growth kinetics, VCC relates the time to reach a given absorbance threshold to the initial cell count using a series of calibration curves. Here, we adapted the VCC method using the model organism Salmonella enterica sv. Typhimurium (S. Typhimurium in combination with established cell culture-based infection models. For HeLa infections, a direct side-by-side comparison showed a good correlation of VCC with CFU counting after plating. For MDCK cells and RAW macrophages we found that VCC reproduced the expected phenotypes of different S. Typhimurium mutants. Furthermore, we demonstrated the use of VCC to test the inhibition of Salmonella invasion by the probiotic E. coli strain Nissle 1917. Taken together, VCC provides a flexible, label-free, automation-compatible methodology to quantify bacteria in in vitro infection assays.

  5. Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

    Science.gov (United States)

    Rahaman, Md Matiur; Ahsan, Md Asif; Gillani, Zeeshan; Chen, Ming

    2017-09-01

    Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately.

  6. Efficient production of a gene mutant cell line through integrating TALENs and high-throughput cell cloning.

    Science.gov (United States)

    Sun, Changhong; Fan, Yu; Li, Juan; Wang, Gancheng; Zhang, Hanshuo; Xi, Jianzhong Jeff

    2015-02-01

    Transcription activator-like effectors (TALEs) are becoming powerful DNA-targeting tools in a variety of mammalian cells and model organisms. However, generating a stable cell line with specific gene mutations in a simple and rapid manner remains a challenging task. Here, we report a new method to efficiently produce monoclonal cells using integrated TALE nuclease technology and a series of high-throughput cell cloning approaches. Following this method, we obtained three mTOR mutant 293T cell lines within 2 months, which included one homozygous mutant line. © 2014 Society for Laboratory Automation and Screening.

  7. High-throughput on-chip in vivo neural regeneration studies using femtosecond laser nano-surgery and microfluidics

    Science.gov (United States)

    Rohde, Christopher B.; Zeng, Fei; Gilleland, Cody; Samara, Chrysanthi; Yanik, Mehmet F.

    2009-02-01

    In recent years, the advantages of using small invertebrate animals as model systems for human disease have become increasingly apparent and have resulted in three Nobel Prizes in medicine or chemistry during the last six years for studies conducted on the nematode Caenorhabditis elegans (C. elegans). The availability of a wide array of species-specific genetic techniques, along with the transparency of the worm and its ability to grow in minute volumes make C. elegans an extremely powerful model organism. We present a suite of technologies for complex high-throughput whole-animal genetic and drug screens. We demonstrate a high-speed microfluidic sorter that can isolate and immobilize C. elegans in a well-defined geometry, an integrated chip containing individually addressable screening chambers for incubation and exposure of individual animals to biochemical compounds, and a device for delivery of compound libraries in standard multiwell plates to microfluidic devices. The immobilization stability obtained by these devices is comparable to that of chemical anesthesia and the immobilization process does not affect lifespan, progeny production, or other aspects of animal health. The high-stability enables the use of a variety of key optical techniques. We use this to demonstrate femtosecond-laser nanosurgery and three-dimensional multiphoton microscopy. Used alone or in various combinations these devices facilitate a variety of high-throughput assays using whole animals, including mutagenesis and RNAi and drug screens at subcellular resolution, as well as high-throughput high-precision manipulations such as femtosecond-laser nanosurgery for large-scale in vivo neural degeneration and regeneration studies.

  8. Perchlorate reduction by hydrogen autotrophic bacteria and microbial community analysis using high-throughput sequencing.

    Science.gov (United States)

    Wan, Dongjin; Liu, Yongde; Niu, Zhenhua; Xiao, Shuhu; Li, Daorong

    2016-02-01

    Hydrogen autotrophic reduction of perchlorate have advantages of high removal efficiency and harmless to drinking water. But so far the reported information about the microbial community structure was comparatively limited, changes in the biodiversity and the dominant bacteria during acclimation process required detailed study. In this study, perchlorate-reducing hydrogen autotrophic bacteria were acclimated by hydrogen aeration from activated sludge. For the first time, high-throughput sequencing was applied to analyze changes in biodiversity and the dominant bacteria during acclimation process. The Michaelis-Menten model described the perchlorate reduction kinetics well. Model parameters q(max) and K(s) were 2.521-3.245 (mg ClO4(-)/gVSS h) and 5.44-8.23 (mg/l), respectively. Microbial perchlorate reduction occurred across at pH range 5.0-11.0; removal was highest at pH 9.0. The enriched mixed bacteria could use perchlorate, nitrate and sulfate as electron accepter, and the sequence of preference was: NO3(-) > ClO4(-) > SO4(2-). Compared to the feed culture, biodiversity decreased greatly during acclimation process, the microbial community structure gradually stabilized after 9 acclimation cycles. The Thauera genus related to Rhodocyclales was the dominated perchlorate reducing bacteria (PRB) in the mixed culture.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  10. Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

    International Nuclear Information System (INIS)

    Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan; Durmus, Naside Gozde

    2011-01-01

    Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

  11. Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

    Energy Technology Data Exchange (ETDEWEB)

    Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan [Department of Medicine, Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Center for Biomedical Engineering, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Durmus, Naside Gozde, E-mail: udemirci@rics.bwh.harvard.edu [School of Engineering and Division of Biology and Medicine, Brown University, Providence, RI (United States)

    2011-09-15

    Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

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

    Science.gov (United States)

    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. Two-Phase Microfluidic Systems for High Throughput Quantification of Agglutination Assays

    KAUST Repository

    Castro, David

    2018-04-01

    Lab-on-Chip, the miniaturization of the chemical and analytical lab, is an endeavor that seems to come out of science fiction yet is slowly becoming a reality. It is a multidisciplinary field that combines different areas of science and engineering. Within these areas, microfluidics is a specialized field that deals with the behavior, control and manipulation of small volumes of fluids. Agglutination assays are rapid, single-step, low-cost immunoassays that use microspheres to detect a wide variety molecules and pathogens by using a specific antigen-antibody interaction. Agglutination assays are particularly suitable for the miniaturization and automation that two-phase microfluidics can offer, a combination that can help tackle the ever pressing need of high-throughput screening for blood banks, epidemiology, food banks diagnosis of infectious diseases. In this thesis, we present a two-phase microfluidic system capable of incubating and quantifying agglutination assays. The microfluidic channel is a simple fabrication solution, using laboratory tubing. These assays are incubated by highly efficient passive mixing with a sample-to-answer time of 2.5 min, a 5-10 fold improvement over traditional agglutination assays. It has a user-friendly interface that that does not require droplet generators, in which a pipette is used to continuously insert assays on-demand, with no down-time in between experiments at 360 assays/h. System parameters are explored, using the streptavidin-biotin interaction as a model assay, with a minimum detection limit of 50 ng/mL using optical image analysis. We compare optical image analysis and light scattering as quantification methods, and demonstrate the first light scattering quantification of agglutination assays in a two-phase ow format. The application can be potentially applied to other biomarkers, which we demonstrate using C-reactive protein (CRP) assays. Using our system, we can take a commercially available CRP qualitative slide

  14. High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging

    Directory of Open Access Journals (Sweden)

    Piyush Pandey

    2017-08-01

    Full Text Available Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo. These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N, phosphorus (P, potassium (K, magnesium (Mg, calcium (Ca, and sulfur (S, and micronutrients sodium (Na, iron (Fe, manganese (Mn, boron (B, copper (Cu, and zinc (Zn. Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [R2 = 0.93 and RPD (Ratio of Performance to Deviation = 3.8]. All macronutrients were also quantified satisfactorily (R2 from 0.69 to 0.92, RPD from 1.62 to 3.62, with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy (R2 from 0.19 to 0.86, RPD from 1.09 to 2.69 than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily (R2 < 0.3 and RPD < 1.2. This study suggested

  15. Comparison of Points of Departure for Health Risk Assessment Based on High-Throughput Screening Data

    Science.gov (United States)

    Sand, Salomon; Parham, Fred; Portier, Christopher J.; Tice, Raymond R.; Krewski, Daniel

    2016-01-01

    Background: The National Research Council’s vision for toxicity testing in the 21st century anticipates that points of departure (PODs) for establishing human exposure guidelines in future risk assessments will increasingly be based on in vitro high-throughput screening (HTS) data. Objectives: The aim of this study was to compare different PODs for HTS data. Specifically, benchmark doses (BMDs) were compared to the signal-to-noise crossover dose (SNCD), which has been suggested as the lowest dose applicable as a POD. Methods: Hill models were fit to > 10,000 in vitro concentration–response curves, obtained for > 1,400 chemicals tested as part of the U.S. Tox21 Phase I effort. BMDs and lower confidence limits on the BMDs (BMDLs) corresponding to extra effects (i.e., changes in response relative to the maximum response) of 5%, 10%, 20%, 30%, and 40% were estimated for > 8,000 curves, along with BMDs and BMDLs corresponding to additional effects (i.e., absolute changes in response) of 5%, 10%, 15%, 20%, and 25%. The SNCD, defined as the dose where the ratio between the additional effect and the difference between the upper and lower bounds of the two-sided 90% confidence interval on absolute effect was 1, 0.67, and 0.5, respectively, was also calculated and compared with the BMDLs. Results: The BMDL40, BMDL25, and BMDL18, defined in terms of extra effect, corresponded to the SNCD1.0, SNCD0.67, and SNCD0.5, respectively, at the median. Similarly, the BMDL25, BMDL17, and BMDL13, defined in terms of additional effect, corresponded to the SNCD1.0, SNCD0.67, and SNCD0.5, respectively, at the median. Conclusions: The SNCD may serve as a reference level that guides the determination of standardized BMDs for risk assessment based on HTS concentration–response data. The SNCD may also have application as a POD for low-dose extrapolation. Citation: Sand S, Parham F, Portier CJ, Tice RR, Krewski D. 2017. Comparison of points of departure for health risk assessment based on

  16. Searching for resistance genes to Bursaphelenchus xylophilus using high throughput screening

    Directory of Open Access Journals (Sweden)

    Santos Carla S

    2012-11-01

    Full Text Available Abstract Background Pine wilt disease (PWD, caused by the pinewood nematode (PWN; Bursaphelenchus xylophilus, damages and kills pine trees and is causing serious economic damage worldwide. Although the ecological mechanism of infestation is well described, the plant’s molecular response to the pathogen is not well known. This is due mainly to the lack of genomic information and the complexity of the disease. High throughput sequencing is now an efficient approach for detecting the expression of genes in non-model organisms, thus providing valuable information in spite of the lack of the genome sequence. In an attempt to unravel genes potentially involved in the pine defense against the pathogen, we hereby report the high throughput comparative sequence analysis of infested and non-infested stems of Pinus pinaster (very susceptible to PWN and Pinus pinea (less susceptible to PWN. Results Four cDNA libraries from infested and non-infested stems of P. pinaster and P. pinea were sequenced in a full 454 GS FLX run, producing a total of 2,083,698 reads. The putative amino acid sequences encoded by the assembled transcripts were annotated according to Gene Ontology, to assign Pinus contigs into Biological Processes, Cellular Components and Molecular Functions categories. Most of the annotated transcripts corresponded to Picea genes-25.4-39.7%, whereas a smaller percentage, matched Pinus genes, 1.8-12.8%, probably a consequence of more public genomic information available for Picea than for Pinus. The comparative transcriptome analysis showed that when P. pinaster was infested with PWN, the genes malate dehydrogenase, ABA, water deficit stress related genes and PAR1 were highly expressed, while in PWN-infested P. pinea, the highly expressed genes were ricin B-related lectin, and genes belonging to the SNARE and high mobility group families. Quantitative PCR experiments confirmed the differential gene expression between the two pine species

  17. Searching for resistance genes to Bursaphelenchus xylophilus using high throughput screening

    Science.gov (United States)

    2012-01-01

    Background Pine wilt disease (PWD), caused by the pinewood nematode (PWN; Bursaphelenchus xylophilus), damages and kills pine trees and is causing serious economic damage worldwide. Although the ecological mechanism of infestation is well described, the plant’s molecular response to the pathogen is not well known. This is due mainly to the lack of genomic information and the complexity of the disease. High throughput sequencing is now an efficient approach for detecting the expression of genes in non-model organisms, thus providing valuable information in spite of the lack of the genome sequence. In an attempt to unravel genes potentially involved in the pine defense against the pathogen, we hereby report the high throughput comparative sequence analysis of infested and non-infested stems of Pinus pinaster (very susceptible to PWN) and Pinus pinea (less susceptible to PWN). Results Four cDNA libraries from infested and non-infested stems of P. pinaster and P. pinea were sequenced in a full 454 GS FLX run, producing a total of 2,083,698 reads. The putative amino acid sequences encoded by the assembled transcripts were annotated according to Gene Ontology, to assign Pinus contigs into Biological Processes, Cellular Components and Molecular Functions categories. Most of the annotated transcripts corresponded to Picea genes-25.4-39.7%, whereas a smaller percentage, matched Pinus genes, 1.8-12.8%, probably a consequence of more public genomic information available for Picea than for Pinus. The comparative transcriptome analysis showed that when P. pinaster was infested with PWN, the genes malate dehydrogenase, ABA, water deficit stress related genes and PAR1 were highly expressed, while in PWN-infested P. pinea, the highly expressed genes were ricin B-related lectin, and genes belonging to the SNARE and high mobility group families. Quantitative PCR experiments confirmed the differential gene expression between the two pine species. Conclusions Defense-related genes

  18. Novel strategy for protein exploration: high-throughput screening assisted with fuzzy neural network.

    Science.gov (United States)

    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

  19. High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

    Science.gov (United States)

    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.

  20. Operational evaluation of high-throughput community-based mass prophylaxis using Just-in-time training.

    Science.gov (United States)

    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.

  1. Template-based self-assembly for silicon chips and 01005 surface-mount components

    International Nuclear Information System (INIS)

    Hoo, J H; Park, Kwang Soon; Baskaran, Rajashree; Böhringer, Karl F

    2014-01-01

    We present template-based microscale self-assembly as a technique that promotes the electronics industry's initiative towards functional diversification and function densification, demonstrating that our process can improve existing assembly and packaging techniques, and also enable possibilities restricted by current industry methodologies. We first present foundational work that performs part (370 × 370 × 150 µm 3 ) delivery to receptor sites (20 × 10 array) with a stochastic batch delivery process that completes within tens of seconds. The delivery mechanism is statistically characterized and a chemical kinetics inspired model is developed. Based on this understanding, repeatable and programmable 100% yield assembly is achieved in open-loop and feedback-based configurations. The established methodology is adapted to deliver and assemble standard 01 005 format (0.016″ × 0.008″, 0.4 mm × 0.2 mm) monolithic ceramic capacitors and thin-film resistors onto silicon substrates. This process is CMOS compatible and is competitive with capacitors and resistors fabricated through standard foundry processes. (paper)

  2. Performance Measurements in a High Throughput Computing Environment

    CERN Document Server

    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...

  3. A high throughput mass spectrometry screening analysis based on two-dimensional carbon microfiber fractionation system.

    Science.gov (United States)

    Ma, Biao; Zou, Yilin; Xie, Xuan; Zhao, Jinhua; Piao, Xiangfan; Piao, Jingyi; Yao, Zhongping; Quinto, Maurizio; Wang, Gang; Li, Donghao

    2017-06-09

    A novel high-throughput, solvent saving and versatile integrated two-dimensional microscale carbon fiber/active carbon fiber system (2DμCFs) that allows a simply and rapid separation of compounds in low-polar, medium-polar and high-polar fractions, has been coupled with ambient ionization-mass spectrometry (ESI-Q-TOF-MS and ESI-QqQ-MS) for screening and quantitative analyses of real samples. 2DμCFs led to a substantial interference reduction and minimization of ionization suppression effects, thus increasing the sensitivity and the screening capabilities of the subsequent MS analysis. The method has been applied to the analysis of Schisandra Chinensis extracts, obtaining with a single injection a simultaneous determination of 33 compounds presenting different polarities, such as organic acids, lignans, and flavonoids in less than 7min, at low pressures and using small solvent amounts. The method was also validated using 10 model compounds, giving limit of detections (LODs) ranging from 0.3 to 30ngmL -1 , satisfactory recoveries (from 75.8 to 93.2%) and reproducibilities (relative standard deviations, RSDs, from 1.40 to 8.06%). Copyright © 2017 Elsevier B.V. All rights reserved.

  4. High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array.

    Science.gov (United States)

    Tung, Yi-Chung; Hsiao, Amy Y; Allen, Steven G; Torisawa, Yu-suke; Ho, Mitchell; Takayama, Shuichi

    2011-02-07

    Culture of cells as three-dimensional (3D) aggregates can enhance in vitro tests for basic biological research as well as for therapeutics development. Such 3D culture models, however, are often more complicated, cumbersome, and expensive than two-dimensional (2D) cultures. This paper describes a 384-well format hanging drop culture plate that makes spheroid formation, culture, and subsequent drug testing on the obtained 3D cellular constructs as straightforward to perform and adapt to existing high-throughput screening (HTS) instruments as conventional 2D cultures. Using this platform, we show that drugs with different modes of action produce distinct responses in the physiological 3D cell spheroids compared to conventional 2D cell monolayers. Specifically, the anticancer drug 5-fluorouracil (5-FU) has higher anti-proliferative effects on 2D cultures whereas the hypoxia activated drug commonly referred to as tirapazamine (TPZ) are more effective against 3D cultures. The multiplexed 3D hanging drop culture and testing plate provides an efficient way to obtain biological insights that are often lost in 2D platforms.

  5. Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

    Directory of Open Access Journals (Sweden)

    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.

  6. HTSeq--a Python framework to work with high-throughput sequencing data.

    Science.gov (United States)

    Anders, Simon; Pyl, Paul Theodor; Huber, Wolfgang

    2015-01-15

    A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. © The Author 2014. Published by Oxford University Press.

  7. High-Throughput Screening to Identify Regulators of Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

    Science.gov (United States)

    Kassir, Yona

    2017-01-01

    Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.

  8. High-throughput mapping of brain-wide activity in awake and drug-responsive vertebrates.

    Science.gov (United States)

    Lin, Xudong; Wang, Shiqi; Yu, Xudong; Liu, Zhuguo; Wang, Fei; Li, Wai Tsun; Cheng, Shuk Han; Dai, Qiuyun; Shi, Peng

    2015-02-07

    The reconstruction of neural activity across complete neural circuits, or brain activity mapping, has great potential in both fundamental and translational neuroscience research. Larval zebrafish, a vertebrate model, has recently been demonstrated to be amenable to whole brain activity mapping in behaving animals. Here we demonstrate a microfluidic array system ("Fish-Trap") that enables high-throughput mapping of brain-wide activity in awake larval zebrafish. Unlike the commonly practiced larva-processing methods using a rigid gel or a capillary tube, which are laborious and time-consuming, the hydrodynamic design of our microfluidic chip allows automatic, gel-free, and anesthetic-free processing of tens of larvae for microscopic imaging with single-cell resolution. Notably, this system provides the capability to directly couple pharmaceutical stimuli with real-time recording of neural activity in a large number of animals, and the local and global effects of pharmacoactive drugs on the nervous system can be directly visualized and evaluated by analyzing drug-induced functional perturbation within or across different brain regions. Using this technology, we tested a set of neurotoxin peptides and obtained new insights into how to exploit neurotoxin derivatives as therapeutic agents. The novel and versatile "Fish-Trap" technology can be readily unitized to study other stimulus (optical, acoustic, or physical) associated functional brain circuits using similar experimental strategies.

  9. Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

    Science.gov (United States)

    Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

    2018-05-17

    In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Intuitive web-based experimental design for high-throughput biomedical data.

    Science.gov (United States)

    Friedrich, Andreas; Kenar, Erhan; Kohlbacher, Oliver; Nahnsen, Sven

    2015-01-01

    Big data bioinformatics aims at drawing biological conclusions from huge and complex biological datasets. Added value from the analysis of big data, however, is only possible if the data is accompanied by accurate metadata annotation. Particularly in high-throughput experiments intelligent approaches are needed to keep track of the experimental design, including the conditions that are studied as well as information that might be interesting for failure analysis or further experiments in the future. In addition to the management of this information, means for an integrated design and interfaces for structured data annotation are urgently needed by researchers. Here, we propose a factor-based experimental design approach that enables scientists to easily create large-scale experiments with the help of a web-based system. We present a novel implementation of a web-based interface allowing the collection of arbitrary metadata. To exchange and edit information we provide a spreadsheet-based, humanly readable format. Subsequently, sample sheets with identifiers and metainformation for data generation facilities can be created. Data files created after measurement of the samples can be uploaded to a datastore, where they are automatically linked to the previously created experimental design model.

  11. High-throughput sequencing, characterization and detection of new and conserved cucumber miRNAs.

    Directory of Open Access Journals (Sweden)

    Germán Martínez

    Full Text Available Micro RNAS (miRNAs are a class of endogenous small non coding RNAs involved in the post-transcriptional regulation of gene expression. In plants, a great number of conserved and specific miRNAs, mainly arising from model species, have been identified to date. However less is known about the diversity of these regulatory RNAs in vegetal species with agricultural and/or horticultural importance. Here we report a combined approach of bioinformatics prediction, high-throughput sequencing data and molecular methods to analyze miRNAs populations in cucumber (Cucumis sativus plants. A set of 19 conserved and 6 known but non-conserved miRNA families were found in our cucumber small RNA dataset. We also identified 7 (3 with their miRNA* strand not previously described miRNAs, candidates to be cucumber-specific. To validate their description these new C. sativus miRNAs were detected by northern blot hybridization. Additionally, potential targets for most conserved and new miRNAs were identified in cucumber genome.In summary, in this study we have identified, by first time, conserved, known non-conserved and new miRNAs arising from an agronomically important species such as C. sativus. The detection of this complex population of regulatory small RNAs suggests that similarly to that observe in other plant species, cucumber miRNAs may possibly play an important role in diverse biological and metabolic processes.

  12. Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data.

    Science.gov (United States)

    Althammer, Sonja; González-Vallinas, Juan; Ballaré, Cecilia; Beato, Miguel; Eyras, Eduardo

    2011-12-15

    High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein-DNA and protein-RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing. We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxy eduardo.eyras@upf.edu Supplementary data are available at Bioinformatics online.

  13. High-Throughput Light Sheet Microscopy for the Automated Live Imaging of Larval Zebrafish

    Science.gov (United States)

    Baker, Ryan; Logan, Savannah; Dudley, Christopher; Parthasarathy, Raghuveer

    The zebrafish is a model organism with a variety of useful properties; it is small and optically transparent, it reproduces quickly, it is a vertebrate, and there are a large variety of transgenic animals available. Because of these properties, the zebrafish is well suited to study using a variety of optical technologies including light sheet fluorescence microscopy (LSFM), which provides high-resolution three-dimensional imaging over large fields of view. Research progress, however, is often not limited by optical techniques but instead by the number of samples one can examine over the course of an experiment, which in the case of light sheet imaging has so far been severely limited. Here we present an integrated fluidic circuit and microscope which provides rapid, automated imaging of zebrafish using several imaging modes, including LSFM, Hyperspectral Imaging, and Differential Interference Contrast Microscopy. Using this system, we show that we can increase our imaging throughput by a factor of 10 compared to previous techniques. We also show preliminary results visualizing zebrafish immune response, which is sensitive to gut microbiota composition, and which shows a strong variability between individuals that highlights the utility of high throughput imaging. National Science Foundation, Award No. DBI-1427957.

  14. Use of high-throughput mass spectrometry to elucidate host-pathogen interactions in Salmonella

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles; Chowdhury, Saiful M.; Manes, Nathan P.; Shi, Liang; Yoon, Hyunjin; Smith, Richard D.; Heffron, Fred

    2008-12-01

    New improvements to mass spectrometry include increased sensitivity, improvements in analyzing the collected data, and most important, from the standpoint of this review, a much higher throughput allowing analysis of many samples in a single day. This short review describes how host-pathogen interactions can be dissected by mass spectrometry using Salmonella as a model system. The approach allowed direct identification of the majority of annotate Salmonella proteins, how expression changed under various in vitro growth conditions, and how this relates to virulence and expression within host cell cells. One of the most significant findings is that a very high percentage of the all annotated genes (>20%) are regulated post-transcriptionally. In addition, new and unexpected interactions have been identified for several Salmonella virulence regulators that involve protein-protein interactions suggesting additional functions of the regulator in coordinating virulence expression. Overall high throughput mass spectrometer provides a new view of pathogen-host interaction emphasizing the protein products and defining how protein interactions determine the outcome of infection.

  15. Use of high-throughput mass spectrometry to elucidate host pathogen interactions in Salmonella

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles; Chowdhury, Saiful M.; Manes, Nathan P.; Shi, Liang; Yoon, Hyunjin; Smith, Richard D.; Heffron, Fred

    2008-12-01

    Capabilities in mass spectrometry are evolving rapidly, with recent improvements in sensitivity, data analysis, and most important, from the standpoint of this review, much higher throughput allowing analysis of many samples in a single day. This short review describes how these improvements in mass spectrometry can be used to dissect host-pathogen interactions using Salmonella as a model system. This approach enabled direct identification of the majority of annotated Salmonella proteins, quantitation of expression changes under various in vitro growth conditions, and new insights into virulence and expression of Salmonella proteins within host cell cells. One of the most significant findings is that a very high percentage of the all annotated genes (>20%) in Salmonella are regulated post-transcriptionally. In addition, new and unexpected interactions have been identified for several Salmonella virulence regulators that involve protein-protein interactions, suggesting additional functions of these regulators in coordinating virulence expression. Overall high throughput mass spectrometry provides a new view of pathogen-host interactions emphasizing the protein products and defining how protein interactions determine the outcome of infection.

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

    Science.gov (United States)

    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.

  17. High-Throughput Screening of Ototoxic and Otoprotective Pharmacological Drugs

    Science.gov (United States)

    Kalinec, Federico

    2005-01-01

    Drug ototoxicity research has relied traditionally on animal models for the discovery and development of therapeutic interventions. More than 50 years of research, however, has delivered few--if any--successful clinical strategies for preventing or ameliorating the ototoxic effects of common pharmacological drugs such as aminoglycoside…

  18. A Self-Reporting Photocatalyst for Online Fluorescence Monitoring of High Throughput RAFT Polymerization.

    Science.gov (United States)

    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.

  19. Informatics and High Throughput Screening of Thermophysical Properties

    Science.gov (United States)

    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.

  20. Filtering high-throughput protein-protein interaction data using a combination of genomic features

    Directory of Open Access Journals (Sweden)

    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.

  1. High-throughput screening of carbohydrate-degrading enzymes using novel insoluble chromogenic substrate assay kits

    DEFF Research Database (Denmark)

    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....

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

    DEFF Research Database (Denmark)

    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...

  3. Recent advances in high-throughput molecular marker identification for superficial and invasive bladder cancers

    DEFF Research Database (Denmark)

    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....

  4. Integrated Automation of High-Throughput Screening and Reverse Phase Protein Array Sample Preparation

    DEFF Research Database (Denmark)

    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...

  5. NanoTopoChip: High-throughput nanotopographical cell instruction.

    Science.gov (United States)

    Hulshof, Frits F B; Zhao, Yiping; Vasilevich, Aliaksei; Beijer, Nick R M; de Boer, Meint; Papenburg, Bernke J; van Blitterswijk, Clemens; Stamatialis, Dimitrios; de Boer, Jan

    2017-10-15

    Surface topography is able to influence cell phenotype in numerous ways and offers opportunities to manipulate cells and tissues. In this work, we develop the Nano-TopoChip and study the cell instructive effects of nanoscale topographies. A combination of deep UV projection lithography and conventional lithography was used to fabricate a library of more than 1200 different defined nanotopographies. To illustrate the cell instructive effects of nanotopography, actin-RFP labeled U2OS osteosarcoma cells were cultured and imaged on the Nano-TopoChip. Automated image analysis shows that of many cell morphological parameters, cell spreading, cell orientation and actin morphology are mostly affected by the nanotopographies. Additionally, by using modeling, the changes of cell morphological parameters could by predicted by several feature shape parameters such as lateral size and spacing. This work overcomes the technological challenges of fabricating high quality defined nanoscale features on unprecedented large surface areas of a material relevant for tissue culture such as PS and the screening system is able to infer nanotopography - cell morphological parameter relationships. Our screening platform provides opportunities to identify and study the effect of nanotopography with beneficial properties for the culture of various cell types. The nanotopography of biomaterial surfaces can be modified to influence adhering cells with the aim to improve the performance of medical implants and tissue culture substrates. However, the necessary knowledge of the underlying mechanisms remains incomplete. One reason for this is the limited availability of high-resolution nanotopographies on relevant biomaterials, suitable to conduct systematic biological studies. The present study shows the fabrication of a library of nano-sized surface topographies with high fidelity. The potential of this library, called the 'NanoTopoChip' is shown in a proof of principle HTS study which

  6. High throughput miniature drug-screening platform using bioprinting technology

    International Nuclear Information System (INIS)

    Rodríguez-Dévora, Jorge I; Reyna, Daniel; Xu Tao; Zhang Bimeng; Shi Zhidong

    2012-01-01

    In the pharmaceutical industry, new drugs are tested to find appropriate compounds for therapeutic purposes for contemporary diseases. Unfortunately, novel compounds emerge at expensive prices and current target evaluation processes have limited throughput, thus leading to an increase of cost and time for drug development. This work shows the development of the novel inkjet-based deposition method for assembling a miniature drug-screening platform, which can realistically and inexpensively evaluate biochemical reactions in a picoliter-scale volume at a high speed rate. As proof of concept, applying a modified Hewlett Packard model 5360 compact disc printer, green fluorescent protein expressing Escherichia coli cells along with alginate gel solution have been arrayed on a coverslip chip under a repeatable volume of 180% ± 26% picoliters per droplet; subsequently, different antibiotic droplets were patterned on the spots of cells to evaluate the inhibition of bacteria for antibiotic screening. The proposed platform was compared to the current screening process, validating its effectiveness. The viability and basic function of the printed cells were evaluated, resulting in cell viability above 98% and insignificant or no DNA damage to human kidney cells transfected. Based on the reduction of investment and compound volume used by this platform, this technique has the potential to improve the actual drug discovery process at its target evaluation stage. (paper)

  7. High-throughput Agrobacterium-mediated barley transformation

    Directory of Open Access Journals (Sweden)

    Snape John W

    2008-09-01

    Full Text Available Abstract Background Plant transformation is an invaluable tool for basic plant research, as well as a useful technique for the direct improvement of commercial crops. Barley (Hordeum vulgare is the fourth most abundant cereal crop in the world. It also provides a useful model for the study of wheat, which has a larger and more complex genome. Most existing barley transformation methodologies are either complex or have low ( Results A robust, simple and reproducible barley transformation protocol has been developed that yields average transformation efficiencies of 25%. This protocol is based on the infection of immature barley embryos with Agrobacterium strain AGL1, carrying vectors from the pBract series that contain the hpt gene (conferring hygromycin resistance as a selectable marker. Results of large scale experiments utilising the luc (firefly luciferase gene as a reporter are described. The method presented here has been used to produce hundreds of independent, transgenic plant lines and we show that a large proportion of these lines contain single copies of the luc gene. Conclusion This protocol demonstrates significant improvements in both efficiency and ease of use over existing barley transformation methods. This opens up opportunities for the development of functional genomics resources in barley.

  8. Development of a high-throughput Candida albicans biofilm chip.

    Directory of Open Access Journals (Sweden)

    Anand Srinivasan

    2011-04-01

    Full Text Available We have developed a high-density microarray platform consisting of nano-biofilms of Candida albicans. A robotic microarrayer was used to print yeast cells of C. albicans encapsulated in a collagen matrix at a volume as low as 50 nL onto surface-modified microscope slides. Upon incubation, the cells grow into fully formed "nano-biofilms". The morphological and architectural complexity of these biofilms were evaluated by scanning electron and confocal scanning laser microscopy. The extent of biofilm formation was determined using a microarray scanner from changes in fluorescence intensities due to FUN 1 metabolic processing. This staining technique was also adapted for antifungal susceptibility testing, which demonstrated that, similar to regular biofilms, cells within the on-chip biofilms displayed elevated levels of resistance against antifungal agents (fluconazole and amphotericin B. Thus, results from structural analyses and antifungal susceptibility testing indicated that despite miniaturization, these biofilms display the typical phenotypic properties associated with the biofilm mode of growth. In its final format, the C. albicans biofilm chip (CaBChip is composed of 768 equivalent and spatially distinct nano-biofilms on a single slide; multiple chips can be printed and processed simultaneously. Compared to current methods for the formation of microbial biofilms, namely the 96-well microtiter plate model, this fungal biofilm chip has advantages in terms of miniaturization and automation, which combine to cut reagent use and analysis time, minimize labor intensive steps, and dramatically reduce assay costs. Such a chip should accelerate the antifungal drug discovery process by enabling rapid, convenient and inexpensive screening of hundreds-to-thousands of compounds simultaneously.

  9. High throughput assay for evaluation of reactive carbonyl scavenging capacity.

    Science.gov (United States)

    Vidal, N; Cavaille, J P; Graziani, F; Robin, M; Ouari, O; Pietri, S; Stocker, P

    2014-01-01

    Many carbonyl species from either lipid peroxidation or glycoxidation are extremely reactive and can disrupt the function of proteins and enzymes. 4-hydroxynonenal and methylglyoxal are the most abundant and toxic lipid-derived reactive carbonyl species. The presence of these toxics leads to carbonyl stress and cause a significant amount of macromolecular damages in several diseases. Much evidence indicates trapping of reactive carbonyl intermediates may be a useful strategy for inhibiting or decreasing carbonyl stress-associated pathologies. There is no rapid and convenient analytical method available for the assessment of direct carbonyl scavenging capacity, and a very limited number of carbonyl scavengers have been identified to date, their therapeutic potential being highlighted only recently. In this context, we have developed a new and rapid sensitive fluorimetric method for the assessment of reactive carbonyl scavengers without involvement glycoxidation systems. Efficacy of various thiol- and non-thiol-carbonyl scavenger pharmacophores was tested both using this screening assay adapted to 96-well microplates and in cultured cells. The scavenging effects on the formation of Advanced Glycation End-product of Bovine Serum Albumin formed with methylglyoxal, 4-hydroxynonenal and glucose-glycated as molecular models were also examined. Low molecular mass thiols with an α-amino-β-mercaptoethane structure showed the highest degree of inhibitory activity toward both α,β-unsaturated aldehydes and dicarbonyls. Cysteine and cysteamine have the best scavenging ability toward methylglyoxal. WR-1065 which is currently approved for clinical use as a protective agent against radiation and renal toxicity was identified as the best inhibitor of 4-hydroxynonenal.

  10. High throughput assay for evaluation of reactive carbonyl scavenging capacity

    Directory of Open Access Journals (Sweden)

    N. Vidal

    2014-01-01

    Full Text Available Many carbonyl species from either lipid peroxidation or glycoxidation are extremely reactive and can disrupt the function of proteins and enzymes. 4-hydroxynonenal and methylglyoxal are the most abundant and toxic lipid-derived reactive carbonyl species. The presence of these toxics leads to carbonyl stress and cause a significant amount of macromolecular damages in several diseases. Much evidence indicates trapping of reactive carbonyl intermediates may be a useful strategy for inhibiting or decreasing carbonyl stress-associated pathologies. There is no rapid and convenient analytical method available for the assessment of direct carbonyl scavenging capacity, and a very limited number of carbonyl scavengers have been identified to date, their therapeutic potential being highlighted only recently. In this context, we have developed a new and rapid sensitive fluorimetric method for the assessment of reactive carbonyl scavengers without involvement glycoxidation systems. Efficacy of various thiol- and non-thiol-carbonyl scavenger pharmacophores was tested both using this screening assay adapted to 96-well microplates and in cultured cells. The scavenging effects on the formation of Advanced Glycation End-product of Bovine Serum Albumin formed with methylglyoxal, 4-hydroxynonenal and glucose-glycated as molecular models were also examined. Low molecular mass thiols with an α-amino-β-mercaptoethane structure showed the highest degree of inhibitory activity toward both α,β-unsaturated aldehydes and dicarbonyls. Cysteine and cysteamine have the best scavenging ability toward methylglyoxal. WR-1065 which is currently approved for clinical use as a protective agent against radiation and renal toxicity was identified as the best inhibitor of 4-hydroxynonenal.

  11. A fluorescence high throughput screening method for the detection of reactive electrophiles as potential skin sensitizers

    Energy Technology Data Exchange (ETDEWEB)

    Avonto, Cristina; Chittiboyina, Amar G. [National Center for Natural Products Research, Research Institute of Pharmaceutical Sciences, School of Pharmacy, The University of Mississippi, University, MS 38677 (United States); Rua, Diego [The Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD 20740 (United States); Khan, Ikhlas A., E-mail: ikhan@olemiss.edu [National Center for Natural Products Research, Research Institute of Pharmaceutical Sciences, School of Pharmacy, The University of Mississippi, University, MS 38677 (United States); Division of Pharmacognosy, Department of BioMolecular Sciences, School of Pharmacy, The University of Mississippi, University, MS 38677 (United States)

    2015-12-01

    Skin sensitization is an important toxicological end-point in the risk assessment of chemical allergens. Because of the complexity of the biological mechanisms associated with skin sensitization, integrated approaches combining different chemical, biological and in silico methods are recommended to replace conventional animal tests. Chemical methods are intended to characterize the potential of a sensitizer to induce earlier molecular initiating events. The presence of an electrophilic mechanistic domain is considered one of the essential chemical features to covalently bind to the biological target and induce further haptenation processes. Current in chemico assays rely on the quantification of unreacted model nucleophiles after incubation with the candidate sensitizer. In the current study, a new fluorescence-based method, ‘HTS-DCYA assay’, is proposed. The assay aims at the identification of reactive electrophiles based on their chemical reactivity toward a model fluorescent thiol. The reaction workflow enabled the development of a High Throughput Screening (HTS) method to directly quantify the reaction adducts. The reaction conditions have been optimized to minimize solubility issues, oxidative side reactions and increase the throughput of the assay while minimizing the reaction time, which are common issues with existing methods. Thirty-six chemicals previously classified with LLNA, DPRA or KeratinoSens™ were tested as a proof of concept. Preliminary results gave an estimated 82% accuracy, 78% sensitivity, 90% specificity, comparable to other in chemico methods such as Cys-DPRA. In addition to validated chemicals, six natural products were analyzed and a prediction of their sensitization potential is presented for the first time. - Highlights: • A novel fluorescence-based method to detect electrophilic sensitizers is proposed. • A model fluorescent thiol was used to directly quantify the reaction products. • A discussion of the reaction workflow

  12. A fluorescence high throughput screening method for the detection of reactive electrophiles as potential skin sensitizers

    International Nuclear Information System (INIS)

    Avonto, Cristina; Chittiboyina, Amar G.; Rua, Diego; Khan, Ikhlas A.

    2015-01-01

    Skin sensitization is an important toxicological end-point in the risk assessment of chemical allergens. Because of the complexity of the biological mechanisms associated with skin sensitization, integrated approaches combining different chemical, biological and in silico methods are recommended to replace conventional animal tests. Chemical methods are intended to characterize the potential of a sensitizer to induce earlier molecular initiating events. The presence of an electrophilic mechanistic domain is considered one of the essential chemical features to covalently bind to the biological target and induce further haptenation processes. Current in chemico assays rely on the quantification of unreacted model nucleophiles after incubation with the candidate sensitizer. In the current study, a new fluorescence-based method, ‘HTS-DCYA assay’, is proposed. The assay aims at the identification of reactive electrophiles based on their chemical reactivity toward a model fluorescent thiol. The reaction workflow enabled the development of a High Throughput Screening (HTS) method to directly quantify the reaction adducts. The reaction conditions have been optimized to minimize solubility issues, oxidative side reactions and increase the throughput of the assay while minimizing the reaction time, which are common issues with existing methods. Thirty-six chemicals previously classified with LLNA, DPRA or KeratinoSens™ were tested as a proof of concept. Preliminary results gave an estimated 82% accuracy, 78% sensitivity, 90% specificity, comparable to other in chemico methods such as Cys-DPRA. In addition to validated chemicals, six natural products were analyzed and a prediction of their sensitization potential is presented for the first time. - Highlights: • A novel fluorescence-based method to detect electrophilic sensitizers is proposed. • A model fluorescent thiol was used to directly quantify the reaction products. • A discussion of the reaction workflow

  13. ZebraZoom: an automated program for high-throughput behavioral analysis and categorization

    Science.gov (United States)

    Mirat, Olivier; Sternberg, Jenna R.; Severi, Kristen E.; Wyart, Claire

    2013-01-01

    The zebrafish larva stands out as an emergent model organism for translational studies involving gene or drug screening thanks to its size, genetics, and permeability. At the larval stage, locomotion occurs in short episodes punctuated by periods of rest. Although phenotyping behavior is a key component of large-scale screens, it has not yet been automated in this model system. We developed ZebraZoom, a program to automatically track larvae and identify maneuvers for many animals performing discrete movements. Our program detects each episodic movement and extracts large-scale statistics on motor patterns to produce a quantification of the locomotor repertoire. We used ZebraZoom to identify motor defects induced by a glycinergic receptor antagonist. The analysis of the blind mutant atoh7 revealed small locomotor defects associated with the mutation. Using multiclass supervised machine learning, ZebraZoom categorized all episodes of movement for each larva into one of three possible maneuvers: slow forward swim, routine turn, and escape. ZebraZoom reached 91% accuracy for categorization of stereotypical maneuvers that four independent experimenters unanimously identified. For all maneuvers in the data set, ZebraZoom agreed with four experimenters in 73.2–82.5% of cases. We modeled the series of maneuvers performed by larvae as Markov chains and observed that larvae often repeated the same maneuvers within a group. When analyzing subsequent maneuvers performed by different larvae, we found that larva–larva interactions occurred as series of escapes. Overall, ZebraZoom reached the level of precision found in manual analysis but accomplished tasks in a high-throughput format necessary for large screens. PMID:23781175

  14. Automated Threshold Selection for Template-Based Sonar Target Detection

    Science.gov (United States)

    2017-08-01

    features,” OCEANS 2014 - TAIPEI. 4. Groen, J.; Coiras, E .; Del Rio, J.; Evans, Vera B., “Model-based sea mine classification with synthetic aperture...2) 3$*(6 D1$0(2)5(63216,%/(3(5621 D5(3257 E $%675$&7 F7+,63$*( /,0,7$7,212) $%675$&7 6WDQGDUG)RUP 5HY...3UHVFULEHG E \\$16,6WG= 7KHSXEOLFUHSRUWLQJEXUGHQIRUWKLVFROOHFWLRQRI LQIRUPDWLRQLVHVWLPDWHGWRDYHUDJHKRXUSHUUHVSRQVH

  15. The Evolution of MALDI-TOF Mass Spectrometry toward Ultra-High-Throughput Screening: 1536-Well Format and Beyond.

    Science.gov (United States)

    Haslam, Carl; Hellicar, John; Dunn, Adrian; Fuetterer, Arne; Hardy, Neil; Marshall, Peter; Paape, Rainer; Pemberton, Michelle; Resemannand, Anja; Leveridge, Melanie

    2016-02-01

    Mass spectrometry (MS) offers a label-free, direct-detection method, in contrast to fluorescent or colorimetric methodologies. Over recent years, solid-phase extraction-based techniques, such as the Agilent RapidFire system, have emerged that are capable of analyzing samples in high-throughput screening (HTS). Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) offers an alternative for high-throughput MS detection. However, sample preparation and deposition onto the MALDI target, as well as interference from matrix ions, have been considered limitations for the use of MALDI for screening assays. Here we describe the development and validation of assays for both small-molecule and peptide analytes using MALDI-TOF coupled with nanoliter liquid handling. Using the JMJD2c histone demethylase and acetylcholinesterase as model systems, we have generated robust data in a 1536 format and also increased sample deposition to 6144 samples per target. Using these methods, we demonstrate that this technology can deliver fast sample analysis time with low sample volume, and data comparable to that of current RapidFire assays. © 2015 Society for Laboratory Automation and Screening.

  16. Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format.

    Science.gov (United States)

    Salvo-Chirnside, Eliane; Kane, Steven; Kerr, Lorraine E

    2011-12-02

    The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP) methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue). The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates) can easily be fully processed (samples homogenised, RNA purified and quantified) in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C) for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments.

  17. High-throughput screening of effective siRNAs using luciferase-linked chimeric mRNA.

    Directory of Open Access Journals (Sweden)

    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.

  18. High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

    Science.gov (United States)

    Laurens, L M L; Wolfrum, E J

    2013-12-18

    One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

  19. Laterally orienting C. elegans using geometry at microscale for high-throughput visual screens in neurodegeneration and neuronal development studies.

    Directory of Open Access Journals (Sweden)

    Ivan de Carlos Cáceres

    Full Text Available C. elegans is an excellent model system for studying neuroscience using genetics because of its relatively simple nervous system, sequenced genome, and the availability of a large number of transgenic and mutant strains. Recently, microfluidic devices have been used for high-throughput genetic screens, replacing traditional methods of manually handling C. elegans. However, the orientation of nematodes within microfluidic devices is random and often not conducive to inspection, hindering visual analysis and overall throughput. In addition, while previous studies have utilized methods to bias head and tail orientation, none of the existing techniques allow for orientation along the dorso-ventral body axis. Here, we present the design of a simple and robust method for passively orienting worms into lateral body positions in microfluidic devices to facilitate inspection of morphological features with specific dorso-ventral alignments. Using this technique, we can position animals into lateral orientations with up to 84% efficiency, compared to 21% using existing methods. We isolated six mutants with neuronal development or neurodegenerative defects, showing that our technology can be used for on-chip analysis and high-throughput visual screens.

  20. Identification of antifungal compounds active against Candida albicans using an improved high-throughput Caenorhabditis elegans assay.

    Directory of Open Access Journals (Sweden)

    Ikechukwu Okoli

    2009-09-01

    Full Text Available Candida albicans, the most common human pathogenic fungus, can establish a persistent lethal infection in the intestine of the microscopic nematode Caenorhabditis elegans. The C. elegans-C. albicans infection model was previously adapted to screen for antifungal compounds. Modifications to this screen have been made to facilitate a high-throughput assay including co-inoculation of nematodes with C. albicans and instrumentation allowing precise dispensing of worms into assay wells, eliminating two labor-intensive steps. This high-throughput method was utilized to screen a library of 3,228 compounds represented by 1,948 bioactive compounds and 1,280 small molecules derived via diversity-oriented synthesis. Nineteen compounds were identified that conferred an increase in C. elegans survival, including most known antifungal compounds within the chemical library. In addition to seven clinically used antifungal compounds, twelve compounds were identified which are not primarily used as antifungal agents, including three immunosuppressive drugs. This assay also allowed the assessment of the relative minimal inhibitory concentration, the effective concentration in vivo, and the toxicity of the compound in a single assay.

  1. Real versus template-based Natural Language Generation: a false opposition?

    NARCIS (Netherlands)

    van Deemter, Kees; Krahmer, Emiel; Theune, Mariet

    2005-01-01

    This paper challenges the received wisdom that template-based approaches to the generation of language are necessarily inferior to other approaches as regards their maintainability, linguistic well-foundedness and quality of output. Some recent NLG systems that call themselves `templatebased' will

  2. Solid-phase cloning for high-throughput assembly of single and multiple DNA parts

    DEFF Research Database (Denmark)

    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 ...

  3. Quantitative in vitro-to-in vivo extrapolation in a high-throughput environment

    International Nuclear Information System (INIS)

    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

  4. Discovery of viruses and virus-like pathogens in pistachio using high-throughput sequencing

    Science.gov (United States)

    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...

  5. High throughput deposition of hydrogenated amorphous carbon coatings on rubber with expanding thermal plasma

    NARCIS (Netherlands)

    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

  6. High-throughput investigation of polymerization kinetics by online monitoring of GPC and GC

    NARCIS (Netherlands)

    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

  7. High-throughput assessment of context-dependent effects of chromatin proteins

    NARCIS (Netherlands)

    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

  8. High-throughput, temperature-controlled microchannel acoustophoresis device made with rapid prototyping

    DEFF Research Database (Denmark)

    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...

  9. A high-throughput method for GMO multi-detection using a microfluidic dynamic array

    NARCIS (Netherlands)

    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

  10. Retrofit Strategies for Incorporating Xenobiotic Metabolism into High Throughput Screening Assays (EMGS)

    Science.gov (United States)

    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...

  11. Development of automatic image analysis methods for high-throughput and high-content screening

    NARCIS (Netherlands)

    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

  12. High-throughput verification of transcriptional starting sites by Deep-RACE

    DEFF Research Database (Denmark)

    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...

  13. New approach for high-throughput screening of drug activity on Plasmodium liver stages.

    NARCIS (Netherlands)

    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

  14. High-throughput experimentation in synthetic polymer chemistry: From RAFT and anionic polymerizations to process development

    NARCIS (Netherlands)

    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

  15. Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy

    DEFF Research Database (Denmark)

    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...

  16. A high throughput DNA extraction method with high yield and quality

    Directory of Open Access Journals (Sweden)

    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.

  17. High throughput "omics" approaches to assess the effects of phytochemicals in human health studies

    Czech Academy of Sciences Publication Activity Database

    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

  18. High-throughput sequencing of forensic genetic samples using punches of FTA cards with buccal swabs

    DEFF Research Database (Denmark)

    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...

  19. Defining the taxonomic domain of applicability for mammalian-based high-throughput screening assays

    Science.gov (United States)

    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...

  20. 40 CFR Table 3 to Subpart Eeee of... - Operating Limits-High Throughput Transfer Racks

    Science.gov (United States)

    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...

  1. High-throughput testing of terpenoid biosynthesis candidate genes using transient expression in Nicotiana benthamiana

    DEFF Research Database (Denmark)

    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...

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

    NARCIS (Netherlands)

    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

  3. Evaluation of Simple and Inexpensive High-Throughput Methods for Phytic Acid Determination

    DEFF Research Database (Denmark)

    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....

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

    NARCIS (Netherlands)

    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

  5. The protein crystallography beamline BW6 at DORIS - automatic operation and high-throughput data collection

    CERN Document Server

    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.

  6. tcpl: The ToxCast Pipeline for High-Throughput Screening Data

    Science.gov (United States)

    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...

  7. Reverse Phase Protein Arrays for High-Throughput Protein Measurements in Mammospheres

    DEFF Research Database (Denmark)

    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...

  8. High throughput generated micro-aggregates of chondrocytes stimulate cartilage formation in vitro and in vivo

    NARCIS (Netherlands)

    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

  9. An Automated, High-Throughput Method for Interpreting the Tandem Mass Spectra of Glycosaminoglycans

    Science.gov (United States)

    Duan, Jiana; Jonathan Amster, I.

    2018-05-01

    The biological interactions between glycosaminoglycans (GAGs) and other biomolecules are heavily influenced by structural features of the glycan. The structure of GAGs can be assigned using tandem mass spectrometry (MS2), but analysis of these data, to date, requires manually interpretation, a slow process that presents a bottleneck to the broader deployment of this approach to solving biologically relevant problems. Automated interpretation remains a challenge, as GAG biosynthesis is not template-driven, and therefore, one cannot predict structures from genomic data, as is done with proteins. The lack of a structure database, a consequence of the non-template biosynthesis, requires a de novo approach to interpretation of the mass spectral data. We propose a model for rapid, high-throughput GAG analysis by using an approach in which candidate structures are scored for the likelihood that they would produce the features observed in the mass spectrum. To make this approach tractable, a genetic algorithm is used to greatly reduce the search-space of isomeric structures that are considered. The time required for analysis is significantly reduced compared to an approach in which every possible isomer is considered and scored. The model is coded in a software package using the MATLAB environment. This approach was tested on tandem mass spectrometry data for long-chain, moderately sulfated chondroitin sulfate oligomers that were derived from the proteoglycan bikunin. The bikunin data was previously interpreted manually. Our approach examines glycosidic fragments to localize SO3 modifications to specific residues and yields the same structures reported in literature, only much more quickly.

  10. High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

    Science.gov (United States)

    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).

  11. Template-based automatic breast segmentation on MRI by excluding the chest region

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Muqing [Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697-5020 and National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical Engineering, School of Medicine, Shenzhen University, 518060 China (China); Chen, Jeon-Hor [Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697-5020 and Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung 82445, Taiwan (China); Wang, Xiaoyong; Su, Min-Ying, E-mail: msu@uci.edu [Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, California 92697-5020 (United States); Chan, Siwa [Department of Radiology, Taichung Veterans General Hospital, Taichung 40407, Taiwan (China); Chen, Siping [National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical Engineering, School of Medicine, Shenzhen University, 518060 China (China)

    2013-12-15

    Purpose: Methods for quantification of breast density on MRI using semiautomatic approaches are commonly used. In this study, the authors report on a fully automatic chest template-based method. Methods: Nonfat-suppressed breast MR images from 31 healthy women were analyzed. Among them, one case was randomly selected and used as the template, and the remaining 30 cases were used for testing. Unlike most model-based breast segmentation methods that use the breast region as the template, the chest body region on a middle slice was used as the template. Within the chest template, three body landmarks (thoracic spine and bilateral boundary of the pectoral muscle) were identified for performing the initial V-shape cut to determine the posterior lateral boundary of the breast. The chest template was mapped to each subject's image space to obtain a subject-specific chest model for exclusion. On the remaining image, the chest wall muscle was identified and excluded to obtain clean breast segmentation. The chest and muscle boundaries determined on the middle slice were used as the reference for the segmentation of adjacent slices, and the process continued superiorly and inferiorly until all 3D slices were segmented. The segmentation results were evaluated by an experienced radiologist to mark voxels that were wrongly included or excluded for error analysis. Results: The breast volumes measured by the proposed algorithm were very close to the radiologist's corrected volumes, showing a % difference ranging from 0.01% to 3.04% in 30 tested subjects with a mean of 0.86% ± 0.72%. The total error was calculated by adding the inclusion and the exclusion errors (so they did not cancel each other out), which ranged from 0.05% to 6.75% with a mean of 3.05% ± 1.93%. The fibroglandular tissue segmented within the breast region determined by the algorithm and the radiologist were also very close, showing a % difference ranging from 0.02% to 2.52% with a mean of 1.03% ± 1

  12. WormSizer: high-throughput analysis of nematode size and shape.

    Directory of Open Access Journals (Sweden)

    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.

  13. Cyber-T web server: differential analysis of high-throughput data.

    Science.gov (United States)

    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/.

  14. High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    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.

  15. Automated high-throughput quantification of mitotic spindle positioning from DIC movies of Caenorhabditis embryos.

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

    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.

  17. High-throughput sequencing of RNA silencing-associated small RNAs in olive (Olea europaea L..

    Directory of Open Access Journals (Sweden)

    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.

  18. Analysis of high-throughput sequencing and annotation strategies for phage genomes.

    Directory of Open Access Journals (Sweden)

    Matthew R Henn

    Full Text Available BACKGROUND: Bacterial viruses (phages play a critical role in shaping microbial populations as they influence both host mortality and horizontal gene transfer. As such, they have a significant impact on local and global ecosystem function and human health. Despite their importance, little is known about the genomic diversity harbored in phages, as methods to capture complete phage genomes have been hampered by the lack of knowledge about the target genomes, and difficulties in generating sufficient quantities of genomic DNA for sequencing. Of the approximately 550 phage genomes currently available in the public domain, fewer than 5% are marine phage. METHODOLOGY/PRINCIPAL FINDINGS: To advance the study of phage biology through comparative genomic approaches we used marine cyanophage as a model system. We compared DNA preparation methodologies (DNA extraction directly from either phage lysates or CsCl purified phage particles, and sequencing strategies that utilize either Sanger sequencing of a linker amplification shotgun library (LASL or of a whole genome shotgun library (WGSL, or 454 pyrosequencing methods. We demonstrate that genomic DNA sample preparation directly from a phage lysate, combined with 454 pyrosequencing, is best suited for phage genome sequencing at scale, as this method is capable of capturing complete continuous genomes with high accuracy. In addition, we describe an automated annotation informatics pipeline that delivers high-quality annotation and yields few false positives and negatives in ORF calling. CONCLUSIONS/SIGNIFICANCE: These DNA preparation, sequencing and annotation strategies enable a high-throughput approach to the burgeoning field of phage genomics.

  19. High-throughput differentiation of heparin from other glycosaminoglycans by pyrolysis mass spectrometry.

    Science.gov (United States)

    Nemes, Peter; Hoover, William J; Keire, David A

    2013-08-06

    Sensors with high chemical specificity and enhanced sample throughput are vital to screening food products and medical devices for chemical or biochemical contaminants that may pose a threat to public health. For example, the rapid detection of oversulfated chondroitin sulfate (OSCS) in heparin could prevent reoccurrence of heparin adulteration that caused hundreds of severe adverse events including deaths worldwide in 2007-2008. Here, rapid pyrolysis is integrated with direct analysis in real time (DART) mass spectrometry to rapidly screen major glycosaminoglycans, including heparin, chondroitin sulfate A, dermatan sulfate, and OSCS. The results demonstrate that, compared to traditional liquid chromatography-based analyses, pyrolysis mass spectrometry achieved at least 250-fold higher sample throughput and was compatible with samples volume-limited to about 300 nL. Pyrolysis yielded an abundance of fragment ions (e.g., 150 different m/z species), many of which were specific to the parent compound. Using multivariate and statistical data analysis models, these data enabled facile differentiation of the glycosaminoglycans with high throughput. After method development was completed, authentically contaminated samples obtained during the heparin crisis by the FDA were analyzed in a blinded manner for OSCS contamination. The lower limit of differentiation and detection were 0.1% (w/w) OSCS in heparin and 100 ng/μL (20 ng) OSCS in water, respectively. For quantitative purposes the linear dynamic range spanned approximately 3 orders of magnitude. Moreover, this chemical readout was successfully employed to find clues in the manufacturing history of the heparin samples that can be used for surveillance purposes. The presented technology and data analysis protocols are anticipated to be readily adaptable to other chemical and biochemical agents and volume-limited samples.

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

    Science.gov (United States)

    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

  1. Accurate inference of shoot biomass from high-throughput images of cereal plants

    Directory of Open Access Journals (Sweden)

    Tester Mark

    2011-02-01

    Full Text Available Abstract With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in literature is to estimate the biomass of a plant as a linear function of the projected shoot area of plants in the images. However, the estimation error from this model, which is solely a function of projected shoot area, is large, prohibiting accurate estimation of the biomass of plants, particularly for the salt-stressed plants. In this paper, we propose a method based on plant specific weight for improving the accuracy of the linear model and reducing the estimation bias (the difference between actual shoot dry weight and the value of the shoot dry weight estimated with a predictive model. For the proposed method in this study, we modeled the plant shoot dry weight as a function of plant area and plant age. The data used for developing our model and comparing the results with the linear model were collected from a completely randomized block design experiment. A total of 320 plants from two bread wheat varieties were grown in a supported hydroponics system in a greenhouse. The plants were exposed to two levels of hydroponic salt treatments (NaCl at 0 and 100 mM for 6 weeks. Five harvests were carried out. Each time 64 randomly selected plants were imaged and then harvested to measure the shoot fresh weight and shoot dry weight. The results of statistical analysis showed that with our proposed method, most of the observed variance can be explained, and moreover only a small difference between actual and estimated shoot dry weight was obtained. The low estimation bias indicates that our proposed method can be used to estimate biomass of individual plants regardless of what variety the plant is and what salt treatment has been applied. We validated this model on an independent

  2. Ensembler: Enabling High-Throughput Molecular Simulations at the Superfamily Scale.

    Directory of Open Access Journals (Sweden)

    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

  3. Macrocell Builder: IP-Block-Based Design Environment for High-Throughput VLSI Dedicated Digital Signal Processing Systems

    Directory of Open Access Journals (Sweden)

    Urard Pascal

    2006-01-01

    Full Text Available We propose an efficient IP-block-based design environment for high-throughput VLSI systems. The flow generates SystemC register-transfer-level (RTL architecture, starting from a Matlab functional model described as a netlist of functional IP. The refinement model inserts automatically control structures to manage delays induced by the use of RTL IPs. It also inserts a control structure to coordinate the execution of parallel clocked IP. The delays may be managed by registers or by counters included in the control structure. The flow has been used successfully in three real-world DSP systems. The experimentations show that the approach can produce efficient RTL architecture and allows to save huge amount of time.

  4. 40 CFR Table 9 to Subpart Eeee of... - Continuous Compliance With Operating Limits-High Throughput Transfer Racks

    Science.gov (United States)

    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...

  5. Using information from historical high-throughput screens to predict active compounds.

    Science.gov (United States)

    Riniker, Sereina; Wang, Yuan; Jenkins, Jeremy L; Landrum, Gregory A

    2014-07-28

    Modern high-throughput screening (HTS) is a well-established approach for hit finding in drug discovery that is routinely employed in the pharmaceutical industry to screen more than a million compounds within a few weeks. However, as the industry shifts to more disease-relevant but more complex phenotypic screens, the focus has moved to piloting smaller but smarter chemically/biologically diverse subsets followed by an expansion around hit compounds. One standard method for doing this is to train a machine-learning (ML) model with the chemical fingerprints of the tested subset of molecules and then select the next compounds based on the predictions of this model. An alternative approach would be to take advantage of the wealth of bioactivity information contained in older (full-deck) screens using so-called HTS fingerprints, where each element of the fingerprint corresponds to the outcome of a particular assay, as input to machine-learning algorithms. We constructed HTS fingerprints using two collections of data: 93 in-house assays and 95 publicly available assays from PubChem. For each source, an additional set of 51 and 46 assays, respectively, was collected for testing. Three different ML methods, random forest (RF), logistic regression (LR), and naïve Bayes (NB), were investigated for both the HTS fingerprint and a chemical fingerprint, Morgan2. RF was found to be best suited for learning from HTS fingerprints yielding area under the receiver operating characteristic curve (AUC) values >0.8 for 78% of the internal assays and enrichment factors at 5% (EF(5%)) >10 for 55% of the assays. The RF(HTS-fp) generally outperformed the LR trained with Morgan2, which was the best ML method for the chemical fingerprint, for the majority of assays. In addition, HTS fingerprints were found to retrieve more diverse chemotypes. Combining the two models through heterogeneous classifier fusion led to a similar or better performance than the best individual model for all assays

  6. High-throughput characterization of film thickness in thin film materials libraries by digital holographic microscopy

    International Nuclear Information System (INIS)

    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.

  7. High-throughput characterization of film thickness in thin film materials libraries by digital holographic microscopy.

    Science.gov (United States)

    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.

  8. High-throughput screening of small molecule libraries using SAMDI mass spectrometry.

    Science.gov (United States)

    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.

  9. High-throughput screening assay of hepatitis C virus helicase inhibitors using fluorescence-quenching phenomenon

    International Nuclear Information System (INIS)

    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.

  10. High throughput octal alpha/gamma spectrometer for low level bioassay estimations

    International Nuclear Information System (INIS)

    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

  11. High-throughput shotgun lipidomics by quadrupole time-of-flight mass spectrometry

    DEFF Research Database (Denmark)

    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...

  12. Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis.

    Science.gov (United States)

    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.

  13. Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS)

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    CERN Document Server

    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...

  15. Fabrication of combinatorial nm-planar electrode array for high throughput evaluation of organic semiconductors

    International Nuclear Information System (INIS)

    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

  16. High-throughput Sequencing Based Immune Repertoire Study during Infectious Disease

    Directory of Open Access Journals (Sweden)

    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.

  17. Life in the fast lane: high-throughput chemistry for lead generation and optimisation.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats.

    Science.gov (United States)

    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.

  1. High-Throughput Screening of a Luciferase Reporter of Gene Silencing on the Inactive X Chromosome.

    Science.gov (United States)

    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.

  2. High-throughput tri-colour flow cytometry technique to assess Plasmodium falciparum parasitaemia in bioassays

    DEFF Research Database (Denmark)

    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...

  3. Fluorescence-based high-throughput screening of dicer cleavage activity.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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. High throughput route selection in multi-rate wireless mesh networks

    Institute of Scientific and Technical Information of China (English)

    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.

  6. From Classical to High Throughput Screening Methods for Feruloyl Esterases: A Review.

    Science.gov (United States)

    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.

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

    KAUST Repository

    Soufan, Othman

    2016-11-10

    Background 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 for extracting useful information from these assays. Virtual screening and a wide variety of databases, methods and solutions proposed to-date, did not completely overcome these challenges. This study is based on a multi-label classification (MLC) technique for modeling correlations between several HTS assays, meaning that a single prediction represents a subset of assigned correlated labels instead of one label. Thus, the devised method provides an increased probability for more accurate predictions of compounds that were not tested in particular assays. Results Here we present DRABAL, a novel MLC solution that incorporates structure learning of a Bayesian network as a step to model dependency between the HTS assays. In this study, DRABAL was used to process more than 1.4 million interactions of over 400,000 compounds and analyze the existing relationships between five large HTS assays from the PubChem BioAssay Database. Compared to different MLC methods, DRABAL significantly improves the F1Score by about 22%, on average. We further illustrated usefulness and utility of DRABAL through screening FDA approved drugs and reported ones that have a high probability to interact with several targets, thus enabling drug-multi-target repositioning. Specifically DRABAL suggests the Thiabendazole drug as a common activator of the NCP1 and Rab-9A proteins, both of which are designed to identify treatment modalities for the Niemann–Pick type C disease. Conclusion We developed a novel MLC solution based on a Bayesian active learning framework to overcome the challenge of lacking fully labeled training data and exploit actual dependencies between the HTS assays. The solution is motivated by the need to model dependencies between existing

  8. Association Study of Gut Flora in Coronary Heart Disease through High-Throughput Sequencing

    OpenAIRE

    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...

  9. Rapid 2,2'-bicinchoninic-based xylanase assay compatible with high throughput screening

    Science.gov (United States)

    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...

  10. Combinatorial Strategies and High Throughput Screening in Drug Discovery Targeted to the Channel of Botulinum Neurotoxin

    National Research Council Canada - National Science Library

    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.

  11. Patterning cell using Si-stencil for high-throughput assay

    KAUST Repository

    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.

  12. Upscaling and automation of electrophysiology: toward high throughput screening in ion channel drug discovery

    DEFF Research Database (Denmark)

    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....

  13. A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

    OpenAIRE

    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...

  14. High-throughput evaluation of interactions between biomaterials, proteins and cells using patterned superhydrophobic substrates

    OpenAIRE

    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.

  15. Geochip: A high throughput genomic tool for linking community structure to functions

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    DEFF Research Database (Denmark)

    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...

  17. Development of Microfluidic Systems Enabling High-Throughput Single-Cell Protein Characterization

    OpenAIRE

    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...

  18. Fluorescence-based high-throughput screening of dicer cleavage activity

    Czech Academy of Sciences Publication Activity Database

    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

  19. High-throughput screening of tick-borne pathogens in Europe

    DEFF Research Database (Denmark)

    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...

  20. Targeted DNA Methylation Analysis by High Throughput Sequencing in Porcine Peri-attachment Embryos

    OpenAIRE

    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...

  1. High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide

    OpenAIRE

    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...

  2. High Throughput Single-cell and Multiple-cell Micro-encapsulation

    OpenAIRE

    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 ...

  3. PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results.

    Science.gov (United States)

    He, Ji; Dai, Xinbin; Zhao, Xuechun

    2007-02-09

    BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform

  4. PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

    Directory of Open Access Journals (Sweden)

    Zhao Xuechun

    2007-02-01

    Full Text Available Abstract Background BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Results Personal BLAST Navigator (PLAN is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1 query and target sequence database management, (2 automated high-throughput BLAST searching, (3 indexing and searching of results, (4 filtering results online, (5 managing results of personal interest in favorite categories, (6 automated sequence annotation (such as NCBI NR and ontology-based annotation. PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. Conclusion PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results

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

    Science.gov (United States)

    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.

  6. Predictive Power of Machine Learning for Optimizing Solar Water Heater Performance: The Potential Application of High-Throughput Screening

    Directory of Open Access Journals (Sweden)

    Hao Li

    2017-01-01

    Full Text Available Predicting the performance of solar water heater (SWH is challenging due to the complexity of the system. Fortunately, knowledge-based machine learning can provide a fast and precise prediction method for SWH performance. With the predictive power of machine learning models, we can further solve a more challenging question: how to cost-effectively design a high-performance SWH? Here, we summarize our recent studies and propose a general framework of SWH design using a machine learning-based high-throughput screening (HTS method. Design of water-in-glass evacuated tube solar water heater (WGET-SWH is selected as a case study to show the potential application of machine learning-based HTS to the design and optimization of solar energy systems.

  7. Assessment of local variability by high-throughput e-beam metrology for prediction of patterning defect probabilities

    Science.gov (United States)

    Wang, Fuming; Hunsche, Stefan; Anunciado, Roy; Corradi, Antonio; Tien, Hung Yu; Tang, Peng; Wei, Junwei; Wang, Yongjun; Fang, Wei; Wong, Patrick; van Oosten, Anton; van Ingen Schenau, Koen; Slachter, Bram

    2018-03-01

    We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from an HMI high-throughput e-beam tool. The test case is a 10nm node SRAM via array patterned with a DUV immersion LELE process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to a seemingly qualitative differences in defectivity. The large available data volume enables further analysis to reliably distinguish global and local CDU variations, including a breakdown into local systematics and stochastics. A closer inspection of the tail end of the distributions and estimation of defect probabilities concludes that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. We expect that the analysis methodology can be applied for defect probability modeling as well as general process qualification in the future.

  8. Modular high-throughput test stand for versatile screening of thin-film materials libraries

    International Nuclear Information System (INIS)

    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.

  9. High throughput electrospinning of high-quality nanofibers via an aluminum disk spinneret

    Science.gov (United States)

    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.

  10. The application of the high throughput sequencing technology in the transposable elements.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    International Nuclear Information System (INIS)

    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)

  14. Evaluation of Capacity on a High Throughput Vol-oxidizer for Operability

    International Nuclear Information System (INIS)

    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

  15. A rapid enzymatic assay for high-throughput screening of adenosine-producing strains

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  17. A priori Considerations When Conducting High-Throughput Amplicon-Based Sequence Analysis

    Directory of Open Access Journals (Sweden)

    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.

  18. Infra-red thermography for high throughput field phenotyping in Solanum tuberosum.

    Directory of Open Access Journals (Sweden)

    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.

  19. Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  1. Optical tools for high-throughput screening of abrasion resistance of combinatorial libraries of organic coatings

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  3. A High-Throughput Biological Calorimetry Core: Steps to Startup, Run, and Maintain a Multiuser Facility.

    Science.gov (United States)

    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.

  4. PCR cycles above routine numbers do not compromise high-throughput DNA barcoding results.

    Science.gov (United States)

    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.

  5. A high throughput array microscope for the mechanical characterization of biomaterials

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  7. High-throughput gene expression profiling of memory differentiation in primary human T cells

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  9. Sensitivity of neuroprogenitor cells to chemical-induced apoptosis using a multiplexed assay suitable for high-throughput screening

    International Nuclear Information System (INIS)

    Druwe, Ingrid; Freudenrich, Theresa M.; Wallace, Kathleen; Shafer, Timothy J.; Mundy, William R.

    2015-01-01

    High-throughput methods are useful for rapidly screening large numbers of chemicals for biological activity, including the perturbation of pathways that may lead to adverse cellular effects. In vitro assays for the key events of neurodevelopment, including apoptosis, may be used in a battery of tests for detecting chemicals that could result in developmental neurotoxicity. Apoptosis contributes to nervous system development by regulating the size of the neuroprogenitor cell pool, and the balance between cellular proliferation and apoptosis during neuroprogenitor cell proliferation helps to determine the size and shape of the nervous system. Therefore, chemicals that affect apoptosis during neuronal development can have deleterious effects on the developing brain. The present study examined the utility of a high-throughput assay to detect chemical-induced apoptosis in mouse or human neuroprogenitor cells, as well as differentiated human neurons derived from induced pluripotent stem cells. Apoptosis was assessed using an assay that measures enzymatic activity of caspase-3/7 in a rapid and cost efficient manner. The results show that all three commercially available models generated a robust source of proliferating neuroprogenitor cells, and that the assay was sensitive and reproducible when used in a multi-well plate format. There were differences in the response of rodent and human neuroprogenitor cells to a set of chemicals previously shown to induce apoptosis in vitro. Neuroprogenitor cells were more sensitive to chemical-induced apoptosis than differentiated neurons, suggesting that neuroprogenitor cells are one of the cell models that should be considered for use in a developmental neurotoxicity screening battery

  10. A cell-based high-throughput screening assay for radiation susceptibility using automated cell counting

    International Nuclear Information System (INIS)

    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

  11. A high-throughput microfluidic dental plaque biofilm system to visualize and quantify the effect of antimicrobials

    Science.gov (United States)

    Nance, William C.; Dowd, Scot E.; Samarian, Derek; Chludzinski, Jeffrey; Delli, Joseph; Battista, John; Rickard, Alexander H.

    2013-01-01

    Objectives Few model systems are amenable to developing multi-species biofilms in parallel under environmentally germane conditions. This is a problem when evaluating the potential real-world effectiveness of antimicrobials in the laboratory. One such antimicrobial is cetylpyridinium chloride (CPC), which is used in numerous over-the-counter oral healthcare products. The aim of this work was to develop a high-throughput microfluidic system that is combined with a confocal laser scanning microscope (CLSM) to quantitatively evaluate the effectiveness of CPC against oral multi-species biofilms grown in human saliva. Methods Twenty-four-channel BioFlux microfluidic plates were inoculated with pooled human saliva and fed filter-sterilized saliva for 20 h at 37°C. The bacterial diversity of the biofilms was evaluated by bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). The antimicrobial/anti-biofilm effect of CPC (0.5%–0.001% w/v) was examined using Live/Dead stain, CLSM and 3D imaging software. Results The analysis of biofilms by bTEFAP demonstrated that they contained genera typically found in human dental plaque. These included Aggregatibacter, Fusobacterium, Neisseria, Porphyromonas, Streptococcus and Veillonella. Using Live/Dead stain, clear gradations in killing were observed when the biofilms were treated with CPC between 0.5% and 0.001% w/v. At 0.5% (w/v) CPC, 90% of the total signal was from dead/damaged cells. Below this concentration range, less killing was observed. In the 0.5%–0.05% (w/v) range CPC penetration/killing was greatest and biofilm thickness was significantly reduced. Conclusions This work demonstrates the utility of a high-throughput microfluidic–CLSM system to grow multi-species oral biofilms, which are compositionally similar to naturally occurring biofilms, to assess the effectiveness of antimicrobials. PMID:23800904

  12. High-Throughput Screening of Chemical Effects on Steroidogenesis Using H295R Human Adrenocortical Carcinoma Cells.

    Science.gov (United States)

    Karmaus, Agnes L; Toole, Colleen M; Filer, Dayne L; Lewis, Kenneth C; Martin, Matthew T

    2016-04-01

    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 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 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 whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-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 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

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

    Directory of Open Access Journals (Sweden)

    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

  14. Fluorescence-based high-throughput functional profiling of ligand-gated ion channels at the level of single cells.

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    Sahil Talwar

    Full Text Available Ion channels are involved in many physiological processes and are attractive targets for therapeutic intervention. Their functional properties vary according to their subunit composition, which in turn varies in a developmental and tissue-specific manner and as a consequence of pathophysiological events. Understanding this diversity requires functional analysis of ion channel properties in large numbers of individual cells. Functional characterisation of ligand-gated channels involves quantitating agonist and drug dose-response relationships using electrophysiological or fluorescence-based techniques. Electrophysiology is limited by low throughput and high-throughput fluorescence-based functional evaluation generally does not enable the characterization of the functional properties of each individual cell. Here we describe a fluorescence-based assay that characterizes functional channel properties at single cell resolution in high throughput mode. It is based on progressive receptor activation and iterative fluorescence imaging and delivers >100 dose-responses in a single well of a 384-well plate, using α1-3 homomeric and αβ heteromeric glycine receptor (GlyR chloride channels as a model system. We applied this assay with transiently transfected HEK293 cells co-expressing halide-sensitive yellow fluorescent protein and different GlyR subunit combinations. Glycine EC50 values of different GlyR isoforms were highly correlated with published electrophysiological data and confirm previously reported pharmacological profiles for the GlyR inhibitors, picrotoxin, strychnine and lindane. We show that inter and intra well variability is low and that clustering of functional phenotypes permits identification of drugs with subunit-specific pharmacological profiles. As this method dramatically improves the efficiency with which ion channel populations can be characterized in the context of cellular heterogeneity, it should facilitate systems

  15. Protocol: high throughput silica-based purification of RNA from Arabidopsis seedlings in a 96-well format

    Directory of Open Access Journals (Sweden)

    Salvo-Chirnside Eliane

    2011-12-01

    Full Text Available Abstract The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue. The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates can easily be fully processed (samples homogenised, RNA purified and quantified in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments.

  16. InSourcerer: a high-throughput method to search for unknown metabolite modifications by mass spectrometry.

    Science.gov (United States)

    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. Ultra-high-throughput screening of an in vitro-synthesized horseradish peroxidase displayed on microbeads using cell sorter.

    Directory of Open Access Journals (Sweden)

    Bo Zhu

    Full Text Available The C1a isoenzyme of horseradish peroxidase (HRP is an industrially important heme-containing enzyme that utilizes hydrogen peroxide to oxidize a wide variety of inorganic and organic compounds for practical applications, including synthesis of fine chemicals, medical diagnostics, and bioremediation. To develop a ultra-high-throughput screening system for HRP, we successfully produced active HRP in an Escherichia coli cell-free protein synthesis system, by adding disulfide bond isomerase DsbC and optimizing the concentrations of hemin and calcium ions and the temperature. The biosynthesized HRP was fused with a single-chain Cro (scCro DNA-binding tag at its N-terminal and C-terminal sites. The addition of the scCro-tag at both ends increased the solubility of the protein. Next, HRP and its fusion proteins were successfully synthesized in a water droplet emulsion by using hexadecane as the oil phase and SunSoft No. 818SK as the surfactant. HRP fusion proteins were displayed on microbeads attached with double-stranded DNA (containing the scCro binding sequence via scCro-DNA interactions. The activities of the immobilized HRP fusion proteins were detected with a tyramide-based fluorogenic assay using flow cytometry. Moreover, a model microbead library containing wild type hrp (WT and inactive mutant (MUT genes was screened using fluorescence-activated cell-sorting, thus efficiently enriching the WT gene from the 1:100 (WT:MUT library. The technique described here could serve as a novel platform for the ultra-high-throughput discovery of more useful HRP mutants and other heme-containing peroxidases.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  20. DIVERSITY in binding, regulation, and evolution revealed from high-throughput ChIP.

    Science.gov (United States)

    Mitra, Sneha; Biswas, Anushua; Narlikar, Leelavati

    2018-04-23

    Genome-wide in vivo protein-DNA interactions are routinely mapped using high-throughput chromatin immunoprecipitation (ChIP). ChIP-reported regions are typically investigated for enriched sequence-motifs, which are likely to model the DNA-binding specificity of the profiled protein and/or of co-occurring proteins. However, simple enrichment analyses can miss insights into the binding-activity of the protein. Note that ChIP reports regions making direct contact with the protein as well as those binding through intermediaries. For example, consider a ChIP experiment targeting protein X, which binds DNA at its cognate sites, but simultaneously interacts with four other proteins. Each of these proteins also binds to its own specific cognate sites along distant parts of the genome, a scenario consistent with the current view of transcriptional hubs and chromatin loops. Since ChIP will pull down all X-associated regions, the final reported data will be a union of five distinct sets of regions, each containing binding sites of one of the five proteins, respectively. Characterizing all five different motifs and the corresponding sets is important to interpret the ChIP experiment and ultimately, the role of X in regulation. We present diversity which attempts exactly this: it partitions the data so that each partition can be characterized with its own de novo motif. Diversity uses a Bayesian approach to identify the optimal number of motifs and the associated partitions, which together explain the entire dataset. This is in contrast to standard motif finders, which report motifs individually enriched in the data, but do not necessarily explain all reported regions. We show that the different motifs and associated regions identified by diversity give insights into the various complexes that may be forming along the chromatin, something that has so far not been attempted from ChIP data. Webserver at http://diversity.ncl.res.in/; standalone (Mac OS X/Linux) from https