EuroPhenome: a repository for high-throughput mouse phenotyping data

PubMed Central

Morgan, Hugh; Beck, Tim; Blake, Andrew; Gates, Hilary; Adams, Niels; Debouzy, Guillaume; Leblanc, Sophie; Lengger, Christoph; Maier, Holger; Melvin, David; Meziane, Hamid; Richardson, Dave; Wells, Sara; White, Jacqui; Wood, Joe; de Angelis, Martin Hrabé; Brown, Steve D. M.; Hancock, John M.; Mallon, Ann-Marie

2010-01-01

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies. PMID:19933761

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

PubMed

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.

High-throughput two-dimensional root system phenotyping platform facilitates genetic analysis of root growth and development.

PubMed

Clark, Randy T; Famoso, Adam N; Zhao, Keyan; Shaff, Jon E; Craft, Eric J; Bustamante, Carlos D; McCouch, Susan R; Aneshansley, Daniel J; Kochian, Leon V

2013-02-01

High-throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user-guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large-scale phenotyping studies. To demonstrate the unique capabilities and high-throughput capacity of this phenotyping platform for studying root systems, genome-wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population. © 2012 Blackwell Publishing Ltd.

[Methods of high-throughput plant phenotyping for large-scale breeding and genetic experiments].

PubMed

Afonnikov, D A; Genaev, M A; Doroshkov, A V; Komyshev, E G; Pshenichnikova, T A

2016-07-01

Phenomics is a field of science at the junction of biology and informatics which solves the problems of rapid, accurate estimation of the plant phenotype; it was rapidly developed because of the need to analyze phenotypic characteristics in large scale genetic and breeding experiments in plants. It is based on using the methods of computer image analysis and integration of biological data. Owing to automation, new approaches make it possible to considerably accelerate the process of estimating the characteristics of a phenotype, to increase its accuracy, and to remove a subjectivism (inherent to humans). The main technologies of high-throughput plant phenotyping in both controlled and field conditions, their advantages and disadvantages, and also the prospects of their use for the efficient solution of problems of plant genetics and breeding are presented in the review.

Novel throughput phenotyping platforms in plant genetic studies.

PubMed

Montes, Juan M; Melchinger, Albrecht E; Reif, Jochen C

2007-10-01

Unraveling the genetic basis of complex traits in plants is limited by the lack of appropriate phenotyping platforms that enable high-throughput screening of many genotypes in multilocation field trials. Near-infrared spectroscopy on agricultural harvesters and spectral reflectance of plant canopies have recently been reported as promising components of novel phenotyping platforms. Understanding the genetic basis of complex traits is now within reach with the use of these new techniques.

High-throughput phenotyping of large wheat breeding nurseries using unmanned aerial system, remote sensing and GIS techniques

NASA Astrophysics Data System (ADS)

Haghighattalab, Atena

Wheat breeders are in a race for genetic gain to secure the future nutritional needs of a growing population. Multiple barriers exist in the acceleration of crop improvement. Emerging technologies are reducing these obstacles. Advances in genotyping technologies have significantly decreased the cost of characterizing the genetic make-up of candidate breeding lines. However, this is just part of the equation. Field-based phenotyping informs a breeder's decision as to which lines move forward in the breeding cycle. This has long been the most expensive and time-consuming, though most critical, aspect of breeding. The grand challenge remains in connecting genetic variants to observed phenotypes followed by predicting phenotypes based on the genetic composition of lines or cultivars. In this context, the current study was undertaken to investigate the utility of UAS in assessment field trials in wheat breeding programs. The major objective was to integrate remotely sensed data with geospatial analysis for high throughput phenotyping of large wheat breeding nurseries. The initial step was to develop and validate a semi-automated high-throughput phenotyping pipeline using a low-cost UAS and NIR camera, image processing, and radiometric calibration to build orthomosaic imagery and 3D models. The relationship between plot-level data (vegetation indices and height) extracted from UAS imagery and manual measurements were examined and found to have a high correlation. Data derived from UAS imagery performed as well as manual measurements while exponentially increasing the amount of data available. The high-resolution, high-temporal HTP data extracted from this pipeline offered the opportunity to develop a within season grain yield prediction model. Due to the variety in genotypes and environmental conditions, breeding trials are inherently spatial in nature and vary non-randomly across the field. This makes geographically weighted regression models a good choice as a

Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping

PubMed Central

Shafiekhani, Ali; Kadam, Suhas; Fritschi, Felix B.; DeSouza, Guilherme N.

2017-01-01

In this paper, a new robotic architecture for plant phenotyping is being introduced. The architecture consists of two robotic platforms: an autonomous ground vehicle (Vinobot) and a mobile observation tower (Vinoculer). The ground vehicle collects data from individual plants, while the observation tower oversees an entire field, identifying specific plants for further inspection by the Vinobot. The advantage of this architecture is threefold: first, it allows the system to inspect large areas of a field at any time, during the day and night, while identifying specific regions affected by biotic and/or abiotic stresses; second, it provides high-throughput plant phenotyping in the field by either comprehensive or selective acquisition of accurate and detailed data from groups or individual plants; and third, it eliminates the need for expensive and cumbersome aerial vehicles or similarly expensive and confined field platforms. As the preliminary results from our algorithms for data collection and 3D image processing, as well as the data analysis and comparison with phenotype data collected by hand demonstrate, the proposed architecture is cost effective, reliable, versatile, and extendable. PMID:28124976

High-Throughput Phenotyping of Maize Leaf Physiological and Biochemical Traits Using Hyperspectral Reflectance1[OPEN

PubMed Central

Yendrek, Craig R.; Tomaz, Tiago; Montes, Christopher M.; Cao, Youyuan; Morse, Alison M.; Brown, Patrick J.; McIntyre, Lauren M.; Leakey, Andrew D.B.

2017-01-01

High-throughput, noninvasive field phenotyping has revealed genetic variation in crop morphological, developmental, and agronomic traits, but rapid measurements of the underlying physiological and biochemical traits are needed to fully understand genetic variation in plant-environment interactions. This study tested the application of leaf hyperspectral reflectance (λ = 500–2,400 nm) as a high-throughput phenotyping approach for rapid and accurate assessment of leaf photosynthetic and biochemical traits in maize (Zea mays). Leaf traits were measured with standard wet-laboratory and gas-exchange approaches alongside measurements of leaf reflectance. Partial least-squares regression was used to develop a measure of leaf chlorophyll content, nitrogen content, sucrose content, specific leaf area, maximum rate of phosphoenolpyruvate carboxylation, [CO2]-saturated rate of photosynthesis, and leaf oxygen radical absorbance capacity from leaf reflectance spectra. Partial least-squares regression models accurately predicted five out of seven traits and were more accurate than previously used simple spectral indices for leaf chlorophyll, nitrogen content, and specific leaf area. Correlations among leaf traits and statistical inferences about differences among genotypes and treatments were similar for measured and modeled data. The hyperspectral reflectance approach to phenotyping was dramatically faster than traditional measurements, enabling over 1,000 rows to be phenotyped during midday hours over just 2 to 4 d, and offers a nondestructive method to accurately assess physiological and biochemical trait responses to environmental stress. PMID:28049858

Dissecting the Phenotypic Components of Crop Plant Growth and Drought Responses Based on High-Throughput Image Analysis[W][OPEN

PubMed Central

Chen, Dijun; Neumann, Kerstin; Friedel, Swetlana; Kilian, Benjamin; Chen, Ming; Altmann, Thomas; Klukas, Christian

2014-01-01

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. PMID:25501589

High-Throughput Genome Editing and Phenotyping Facilitated by High Resolution Melting Curve Analysis

PubMed Central

Thomas, Holly R.; Percival, Stefanie M.; Yoder, Bradley K.; Parant, John M.

2014-01-01

With the goal to generate and characterize the phenotypes of null alleles in all genes within an organism and the recent advances in custom nucleases, genome editing limitations have moved from mutation generation to mutation detection. We previously demonstrated that High Resolution Melting (HRM) analysis is a rapid and efficient means of genotyping known zebrafish mutants. Here we establish optimized conditions for HRM based detection of novel mutant alleles. Using these conditions, we demonstrate that HRM is highly efficient at mutation detection across multiple genome editing platforms (ZFNs, TALENs, and CRISPRs); we observed nuclease generated HRM positive targeting in 1 of 6 (16%) open pool derived ZFNs, 14 of 23 (60%) TALENs, and 58 of 77 (75%) CRISPR nucleases. Successful targeting, based on HRM of G0 embryos correlates well with successful germline transmission (46 of 47 nucleases); yet, surprisingly mutations in the somatic tail DNA weakly correlate with mutations in the germline F1 progeny DNA. This suggests that analysis of G0 tail DNA is a good indicator of the efficiency of the nuclease, but not necessarily a good indicator of germline alleles that will be present in the F1s. However, we demonstrate that small amplicon HRM curve profiles of F1 progeny DNA can be used to differentiate between specific mutant alleles, facilitating rare allele identification and isolation; and that HRM is a powerful technique for screening possible off-target mutations that may be generated by the nucleases. Our data suggest that micro-homology based alternative NHEJ repair is primarily utilized in the generation of CRISPR mutant alleles and allows us to predict likelihood of generating a null allele. Lastly, we demonstrate that HRM can be used to quickly distinguish genotype-phenotype correlations within F1 embryos derived from G0 intercrosses. Together these data indicate that custom nucleases, in conjunction with the ease and speed of HRM, will facilitate future high-throughput

High throughput integrated thermal characterization with non-contact optical calorimetry

NASA Astrophysics Data System (ADS)

Hou, Sichao; Huo, Ruiqing; Su, Ming

2017-10-01

Commonly used thermal analysis tools such as calorimeter and thermal conductivity meter are separated instruments and limited by low throughput, where only one sample is examined each time. This work reports an infrared based optical calorimetry with its theoretical foundation, which is able to provide an integrated solution to characterize thermal properties of materials with high throughput. By taking time domain temperature information of spatially distributed samples, this method allows a single device (infrared camera) to determine the thermal properties of both phase change systems (melting temperature and latent heat of fusion) and non-phase change systems (thermal conductivity and heat capacity). This method further allows these thermal properties of multiple samples to be determined rapidly, remotely, and simultaneously. In this proof-of-concept experiment, the thermal properties of a panel of 16 samples including melting temperatures, latent heats of fusion, heat capacities, and thermal conductivities have been determined in 2 min with high accuracy. Given the high thermal, spatial, and temporal resolutions of the advanced infrared camera, this method has the potential to revolutionize the thermal characterization of materials by providing an integrated solution with high throughput, high sensitivity, and short analysis time.

Label-free cell-cycle analysis by high-throughput quantitative phase time-stretch imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mok, Aaron T. Y.; Lee, Kelvin C. M.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2018-02-01

Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude of cellular states. Changes in cell size, dry mass and subcellular morphology, for instance, are relevant to cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) is among the effective biophysical phenotyping tools that can quantify cell sizes and sub-cellular dry mass density distribution of single cells at high spatial resolution. However, limited camera frame rate and thus imaging throughput makes QPM incompatible with high-throughput flow cytometry - a gold standard in multiparametric cell-based assay. Here we present a high-throughput approach for label-free analysis of cell cycle based on quantitative-phase time-stretch imaging flow cytometry at a throughput of > 10,000 cells/s. Our time-stretch QPM system enables sub-cellular resolution even at high speed, allowing us to extract a multitude (at least 24) of single-cell biophysical phenotypes (from both amplitude and phase images). Those phenotypes can be combined to track cell-cycle progression based on a t-distributed stochastic neighbor embedding (t-SNE) algorithm. Using multivariate analysis of variance (MANOVA) discriminant analysis, cell-cycle phases can also be predicted label-free with high accuracy at >90% in G1 and G2 phase, and >80% in S phase. We anticipate that high throughput label-free cell cycle characterization could open new approaches for large-scale single-cell analysis, bringing new mechanistic insights into complex biological processes including diseases pathogenesis.

Development of a phenotyping platform for high throughput screening of nodal root angle in sorghum.

PubMed

Joshi, Dinesh C; Singh, Vijaya; Hunt, Colleen; Mace, Emma; van Oosterom, Erik; Sulman, Richard; Jordan, David; Hammer, Graeme

2017-01-01

In sorghum, the growth angle of nodal roots is a major component of root system architecture. It strongly influences the spatial distribution of roots of mature plants in the soil profile, which can impact drought adaptation. However, selection for nodal root angle in sorghum breeding programs has been restricted by the absence of a suitable high throughput phenotyping platform. The aim of this study was to develop a phenotyping platform for the rapid, non-destructive and digital measurement of nodal root angle of sorghum at the seedling stage. The phenotyping platform comprises of 500 soil filled root chambers (50 × 45 × 0.3 cm in size), made of transparent perspex sheets that were placed in metal tubs and covered with polycarbonate sheets. Around 3 weeks after sowing, once the first flush of nodal roots was visible, roots were imaged in situ using an imaging box that included two digital cameras that were remotely controlled by two android tablets. Free software ( openGelPhoto.tcl ) allowed precise measurement of nodal root angle from the digital images. The reliability and efficiency of the platform was evaluated by screening a large nested association mapping population of sorghum and a set of hybrids in six independent experimental runs that included up to 500 plants each. The platform revealed extensive genetic variation and high heritability (repeatability) for nodal root angle. High genetic correlations and consistent ranking of genotypes across experimental runs confirmed the reproducibility of the platform. This low cost, high throughput root phenotyping platform requires no sophisticated equipment, is adaptable to most glasshouse environments and is well suited to dissect the genetic control of nodal root angle of sorghum. The platform is suitable for use in sorghum breeding programs aiming to improve drought adaptation through root system architecture manipulation.

A platform for high-throughput bioenergy production phenotype characterization in single cells

PubMed Central

Kelbauskas, Laimonas; Glenn, Honor; Anderson, Clifford; Messner, Jacob; Lee, Kristen B.; Song, Ganquan; Houkal, Jeff; Su, Fengyu; Zhang, Liqiang; Tian, Yanqing; Wang, Hong; Bussey, Kimberly; Johnson, Roger H.; Meldrum, Deirdre R.

2017-01-01

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers. PMID:28349963

Arabidopsis Seed Content QTL Mapping Using High-Throughput Phenotyping: The Assets of Near Infrared Spectroscopy

PubMed Central

Jasinski, Sophie; Lécureuil, Alain; Durandet, Monique; Bernard-Moulin, Patrick; Guerche, Philippe

2016-01-01

Seed storage compounds are of crucial importance for human diet, feed and industrial uses. In oleo-proteaginous species like rapeseed, seed oil and protein are the qualitative determinants that conferred economic value to the harvested seed. To date, although the biosynthesis pathways of oil and storage protein are rather well-known, the factors that determine how these types of reserves are partitioned in seeds have to be identified. With the aim of implementing a quantitative genetics approach, requiring phenotyping of 100s of plants, our first objective was to establish near-infrared reflectance spectroscopic (NIRS) predictive equations in order to estimate oil, protein, carbon, and nitrogen content in Arabidopsis seed with high-throughput level. Our results demonstrated that NIRS is a powerful non-destructive, high-throughput method to assess the content of these four major components studied in Arabidopsis seed. With this tool in hand, we analyzed Arabidopsis natural variation for these four components and illustrated that they all displayed a wide range of variation. Finally, NIRS was used in order to map QTL for these four traits using seeds from the Arabidopsis thaliana Ct-1 × Col-0 recombinant inbred line population. Some QTL co-localized with QTL previously identified, but others mapped to chromosomal regions never identified so far for such traits. This paper illustrates the usefulness of NIRS predictive equations to perform accurate high-throughput phenotyping of Arabidopsis seed content, opening new perspectives in gene identification following QTL mapping and genome wide association studies. PMID:27891138

Towards High-Throughput, Simultaneous Characterization of Thermal and Thermoelectric Properties

NASA Astrophysics Data System (ADS)

Miers, Collier Stephen

The extension of thermoelectric generators to more general markets requires that the devices be affordable and practical (low $/Watt) to implement. A key challenge in this pursuit is the quick and accurate characterization of thermoelectric materials, which will allow researchers to tune and modify the material properties quickly. The goal of this thesis is to design and fabricate a high-throughput characterization system for the simultaneous characterization of thermal, electrical, and thermoelectric properties for device scale material samples. The measurement methodology presented in this thesis combines a custom designed measurement system created specifically for high-throughput testing with a novel device structure that permits simultaneous characterization of the material properties. The measurement system is based upon the 3o method for thermal conductivity measurements, with the addition of electrodes and voltage probes to measure the electrical conductivity and Seebeck coefficient. A device designed and optimized to permit the rapid characterization of thermoelectric materials is also presented. This structure is optimized to ensure 1D heat transfer within the sample, thus permitting rapid data analysis and fitting using a MATLAB script. Verification of the thermal portion of the system is presented using fused silica and sapphire materials for benchmarking. The fused silica samples yielded a thermal conductivity of 1.21 W/(m K), while a thermal conductivity of 31.2 W/(m K) was measured for the sapphire samples. The device and measurement system designed and developed in this thesis provide insight and serve as a foundation for the development of high throughput, simultaneous measurement platforms.

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

PubMed Central

Yin, Zheng; Zhou, Xiaobo; Bakal, Chris; Li, Fuhai; Sun, Youxian; Perrimon, Norbert; Wong, Stephen TC

2008-01-01

Background The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets

Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

PubMed

Yu, Sheng; Liao, Katherine P; Shaw, Stanley Y; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Cai, Tianxi

2015-09-01

Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy. Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype. The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features. Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable. The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

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

PubMed

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

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping

PubMed Central

Thompson, Alison L.; Thorp, Kelly R.; Conley, Matthew; Andrade-Sanchez, Pedro; Heun, John T.; Dyer, John M.; White, Jeffery W.

2018-01-01

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions. PMID:29868041

Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat (Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect s...

SmartGrain: high-throughput phenotyping software for measuring seed shape through image analysis.

PubMed

Tanabata, Takanari; Shibaya, Taeko; Hori, Kiyosumi; Ebana, Kaworu; Yano, Masahiro

2012-12-01

Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.

High throughput workflow for coacervate formation and characterization in shampoo systems.

PubMed

Kalantar, T H; Tucker, C J; Zalusky, A S; Boomgaard, T A; Wilson, B E; Ladika, M; Jordan, S L; Li, W K; Zhang, X; Goh, C G

2007-01-01

Cationic cellulosic polymers find wide utility as benefit agents in shampoo. Deposition of these polymers onto hair has been shown to mend split-ends, improve appearance and wet combing, as well as provide controlled delivery of insoluble actives. The deposition is thought to be enhanced by the formation of a polymer/surfactant complex that phase-separates from the bulk solution upon dilution. A standard characterization method has been developed to characterize the coacervate formation upon dilution, but the test is time and material prohibitive. We have developed a semi-automated high throughput workflow to characterize the coacervate-forming behavior of different shampoo formulations. A procedure that allows testing of real use shampoo dilutions without first formulating a complete shampoo was identified. This procedure was adapted to a Tecan liquid handler by optimizing the parameters for liquid dispensing as well as for mixing. The high throughput workflow enabled preparation and testing of hundreds of formulations with different types and levels of cationic cellulosic polymers and surfactants, and for each formulation a haze diagram was constructed. Optimal formulations and their dilutions that give substantial coacervate formation (determined by haze measurements) were identified. Results from this high throughput workflow were shown to reproduce standard haze and bench-top turbidity measurements, and this workflow has the advantages of using less material and allowing more variables to be tested with significant time savings.

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.

PubMed

Zhang, Xuehai; Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Xiong, Lizhong; Yang, Wanneng; Yan, Jianbing

2017-03-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize ( Zea mays ) recombinant inbred line population ( n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. © 2017 American Society of Plant Biologists. All Rights Reserved.

High-throughput characterization for solar fuels materials discovery

NASA Astrophysics Data System (ADS)

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.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

PubMed Central

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

2017-01-01

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

An image analysis toolbox for high-throughput C. elegans assays

PubMed Central

Wählby, Carolina; Kamentsky, Lee; Liu, Zihan H.; Riklin-Raviv, Tammy; Conery, Annie L.; O’Rourke, Eyleen J.; Sokolnicki, Katherine L.; Visvikis, Orane; Ljosa, Vebjorn; Irazoqui, Javier E.; Golland, Polina; Ruvkun, Gary; Ausubel, Frederick M.; Carpenter, Anne E.

2012-01-01

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays of C. elegans for the study of diverse biological pathways relevant to human disease. PMID:22522656

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

PubMed

Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

2018-01-01

A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

High-Throughput Screening Enhances Kidney Organoid Differentiation from Human Pluripotent Stem Cells and Enables Automated Multidimensional Phenotyping.

PubMed

Czerniecki, Stefan M; Cruz, Nelly M; Harder, Jennifer L; Menon, Rajasree; Annis, James; Otto, Edgar A; Gulieva, Ramila E; Islas, Laura V; Kim, Yong Kyun; Tran, Linh M; Martins, Timothy J; Pippin, Jeffrey W; Fu, Hongxia; Kretzler, Matthias; Shankland, Stuart J; Himmelfarb, Jonathan; Moon, Randall T; Paragas, Neal; Freedman, Benjamin S

2018-05-15

Organoids derived from human pluripotent stem cells are a potentially powerful tool for high-throughput screening (HTS), but the complexity of organoid cultures poses a significant challenge for miniaturization and automation. Here, we present a fully automated, HTS-compatible platform for enhanced differentiation and phenotyping of human kidney organoids. The entire 21-day protocol, from plating to differentiation to analysis, can be performed automatically by liquid-handling robots, or alternatively by manual pipetting. High-content imaging analysis reveals both dose-dependent and threshold effects during organoid differentiation. Immunofluorescence and single-cell RNA sequencing identify previously undetected parietal, interstitial, and partially differentiated compartments within organoids and define conditions that greatly expand the vascular endothelium. Chemical modulation of toxicity and disease phenotypes can be quantified for safety and efficacy prediction. Screening in gene-edited organoids in this system reveals an unexpected role for myosin in polycystic kidney disease. Organoids in HTS formats thus establish an attractive platform for multidimensional phenotypic screening. Copyright © 2018 Elsevier Inc. All rights reserved.

High-Throughput Microbore UPLC-MS Metabolic Phenotyping of Urine for Large-Scale Epidemiology Studies.

PubMed

Gray, Nicola; Lewis, Matthew R; Plumb, Robert S; Wilson, Ian D; Nicholson, Jeremy K

2015-06-05

A new generation of metabolic phenotyping centers are being created to meet the increasing demands of personalized healthcare, and this has resulted in a major requirement for economical, high-throughput metabonomic analysis by liquid chromatography-mass spectrometry (LC-MS). Meeting these new demands represents an emerging bioanalytical problem that must be solved if metabolic phenotyping is to be successfully applied to large clinical and epidemiological sample sets. Ultraperformance (UP)LC-MS-based metabolic phenotyping, based on 2.1 mm i.d. LC columns, enables comprehensive metabolic phenotyping but, when employed for the analysis of thousands of samples, results in high solvent usage. The use of UPLC-MS employing 1 mm i.d. columns for metabolic phenotyping rather than the conventional 2.1 mm i.d. methodology shows that the resulting optimized microbore method provided equivalent or superior performance in terms of peak capacity, sensitivity, and robustness. On average, we also observed, when using the microbore scale separation, an increase in response of 2-3 fold over that obtained with the standard 2.1 mm scale method. When applied to the analysis of human urine, the 1 mm scale method showed no decline in performance over the course of 1000 analyses, illustrating that microbore UPLC-MS represents a viable alternative to conventional 2.1 mm i.d. formats for routine large-scale metabolic profiling studies while also resulting in a 75% reduction in solvent usage. The modest increase in sensitivity provided by this methodology also offers the potential to either reduce sample consumption or increase the number of metabolite features detected with confidence due to the increased signal-to-noise ratios obtained. Implementation of this miniaturized UPLC-MS method of metabolic phenotyping results in clear analytical, economic, and environmental benefits for large-scale metabolic profiling studies with similar or improved analytical performance compared to

High-Throughput Characterization of Vapor-Deposited Organic Glasses

NASA Astrophysics Data System (ADS)

Dalal, Shakeel S.

Glasses are non-equilibrium materials which on short timescales behave like solids, and on long timescales betray their liquid-like structure. The most common way of preparing a glass is to cool the liquid faster than it can structurally rearrange. Until recently, most preparation schemes for a glass were considered to result in materials with undifferentiable structure and properties. This thesis utilizes a particular preparation method, physical vapor deposition, in order to prepare glasses of organic molecules with properties otherwise considered to be unobtainable. The glasses are characterized using spectroscopic ellipsometry, both as a dilatometric technique and as a reporter of molecular packing. The results reported here develop ellipsometry as a dilatometric technique on a pair of model glass formers, alpha,alpha,beta-trisnaphthylbenzene and indomethacin. It is found that the molecular orientation, as measured by birefringence, can be tuned by changing the substrate temperature during the deposition. In order to efficiently characterize the properties of vapor-deposited indomethacin as a function of substrate temperature, a high-throughput method is developed to capture the entire interesting range of substrate temperatures in just a few experiments. This high-throughput method is then leveraged to describe molecular mobility in vapor-deposited indomethacin. It is also used to demonstrate that the behavior of organic semiconducting molecules agrees with indomethacin quantitatively, and this agreement has implications for emerging technologies such as light-emitting diodes, photovoltaics and thin-film transistors made from organic molecules.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

PubMed Central

Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

2017-01-01

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here ‘POP6’), whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.

PubMed

Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

2017-01-01

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F 2 partially inbred population (termed here 'POP6'), whose F 1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature ( T c ) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE PAGES

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; ...

2017-02-21

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

RGB picture vegetation indexes for High-Throughput Phenotyping Platforms (HTPPs)

NASA Astrophysics Data System (ADS)

Kefauver, Shawn C.; El-Haddad, George; Vergara-Diaz, Omar; Araus, José Luis

2015-10-01

Extreme and abnormal weather events, as well as the more gradual meteorological changes associated with climate change, often coincide with not only increased abiotic risks (such as increases in temperature and decreases in precipitation), but also increased biotic risks due to environmental conditions that favor the rapid spread of crop pests and diseases. Durum wheat is by extension the most cultivated cereal in the south and east margins of the Mediterranean Basin. It is of strategic importance for Mediterranean agriculture to develop new varieties of durum wheat with greater production potential, better adaptation to increasingly adverse environmental conditions (drought) and better grain quality. Similarly, maize is the top staple crop for low-income populations in Sub-Saharan Africa and is currently suffering from the appearance of new diseases, which, together with increased abiotic stresses from climate change, are challenging the very sustainability of African societies. Current constraints in field phenotyping remain a major bottleneck for future breeding advances, but RGB-based High-Throughput Phenotyping Platforms (HTPPs) have shown promise for rapidly developing both disease-resistant and weather-resilient crops. RGB cameras have proven costeffective in studies assessing the effect of abiotic stresses, but have yet to be fully exploited to phenotype disease resistance. Recent analyses of durum wheat in Spain have shown RGB vegetation indexes to outperform multispectral indexes such as NDVI consistently in disease and yield prediction. Towards HTTP development for breeding maize disease resistance, some of the same RGB picture vegetation indexes outperformed NDVI (Normalized Difference Vegetation Index), with R2 values up to 0.65, compared to 0.56 for NDVI. . Specifically, hue, a*, u*, and Green Area (GA), as produced by FIJI and BreedPix open source software, performed similar to or better than NDVI in predicting yield and disease severity conditions

High-throughput electrical characterization for robust overlay lithography control

NASA Astrophysics Data System (ADS)

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.

High-throughput methods for characterizing the mechanical properties of coatings

NASA Astrophysics Data System (ADS)

Siripirom, Chavanin

The characterization of mechanical properties in a combinatorial and high-throughput workflow has been a bottleneck that reduced the speed of the materials development process. High-throughput characterization of the mechanical properties was applied in this research in order to reduce the amount of sample handling and to accelerate the output. A puncture tester was designed and built to evaluate the toughness of materials using an innovative template design coupled with automation. The test is in the form of a circular free-film indentation. A single template contains 12 samples which are tested in a rapid serial approach. Next, the operational principles of a novel parallel dynamic mechanical-thermal analysis instrument were analyzed in detail for potential sources of errors. The test uses a model of a circular bilayer fixed-edge plate deformation. A total of 96 samples can be analyzed simultaneously which provides a tremendous increase in efficiency compared with a conventional dynamic test. The modulus values determined by the system had considerable variation. The errors were observed and improvements to the system were made. A finite element analysis was used to analyze the accuracy given by the closed-form solution with respect to testing geometries, such as thicknesses of the samples. A good control of the thickness of the sample was proven to be crucial to the accuracy and precision of the output. Then, the attempt to correlate the high-throughput experiments and conventional coating testing methods was made. Automated nanoindentation in dynamic mode was found to provide information on the near-surface modulus and could potentially correlate with the pendulum hardness test using the loss tangent component. Lastly, surface characterization of stratified siloxane-polyurethane coatings was carried out with X-ray photoelectron spectroscopy, Rutherford backscattering spectroscopy, transmission electron microscopy, and nanoindentation. The siloxane component

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth1[OPEN

PubMed Central

Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Yang, Wanneng

2017-01-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. PMID:28153923

A cost-effective and customizable automated irrigation system for precise high-throughput phenotyping in drought stress studies

PubMed Central

2018-01-01

The development of high-yielding crops with drought tolerance is necessary to increase food, feed, fiber and fuel production. Methods that create similar environmental conditions for a large number of genotypes are essential to investigate plant responses to drought in gene discovery studies. Modern facilities that control water availability for each plant remain cost-prohibited to some sections of the research community. We present an alternative cost-effective automated irrigation system scalable for a high-throughput and controlled dry-down treatment of plants. This system was tested in sorghum using two experiments. First, four genotypes were subjected to ten days of dry-down to achieve three final Volumetric Water Content (VWC) levels: drought (0.10 and 0.20 m3 m-3) and control (0.30 m3 m-3). The final average VWC was 0.11, 0.22, and 0.31 m3 m-3, respectively, and significant differences in biomass accumulation were observed between control and drought treatments. Second, 42 diverse sorghum genotypes were subjected to a seven-day dry-down treatment for a final drought stress of 0.15 m3 m-3 VWC. The final average VWC was 0.17 m3 m-3, and plants presented significant differences in photosynthetic rate during the drought period. These results demonstrate that cost-effective automation systems can successfully control substrate water content for each plant, to accurately compare their phenotypic responses to drought, and be scaled up for high-throughput phenotyping studies. PMID:29870560

A cost-effective and customizable automated irrigation system for precise high-throughput phenotyping in drought stress studies.

PubMed

Ortiz, Diego; Litvin, Alexander G; Salas Fernandez, Maria G

2018-01-01

The development of high-yielding crops with drought tolerance is necessary to increase food, feed, fiber and fuel production. Methods that create similar environmental conditions for a large number of genotypes are essential to investigate plant responses to drought in gene discovery studies. Modern facilities that control water availability for each plant remain cost-prohibited to some sections of the research community. We present an alternative cost-effective automated irrigation system scalable for a high-throughput and controlled dry-down treatment of plants. This system was tested in sorghum using two experiments. First, four genotypes were subjected to ten days of dry-down to achieve three final Volumetric Water Content (VWC) levels: drought (0.10 and 0.20 m3 m-3) and control (0.30 m3 m-3). The final average VWC was 0.11, 0.22, and 0.31 m3 m-3, respectively, and significant differences in biomass accumulation were observed between control and drought treatments. Second, 42 diverse sorghum genotypes were subjected to a seven-day dry-down treatment for a final drought stress of 0.15 m3 m-3 VWC. The final average VWC was 0.17 m3 m-3, and plants presented significant differences in photosynthetic rate during the drought period. These results demonstrate that cost-effective automation systems can successfully control substrate water content for each plant, to accurately compare their phenotypic responses to drought, and be scaled up for high-throughput phenotyping studies.

A High-Throughput (HTS) Assay for Enzyme Reaction Phenotyping in Human Recombinant P450 Enzymes Using LC-MS/MS.

PubMed

Li, Xiaofeng; Suhar, Tom; Glass, Lateca; Rajaraman, Ganesh

2014-03-03

Enzyme reaction phenotyping is employed extensively during the early stages of drug discovery to identify the enzymes responsible for the metabolism of new chemical entities (NCEs). Early identification of metabolic pathways facilitates prediction of potential drug-drug interactions associated with enzyme polymorphism, induction, or inhibition, and aids in the design of clinical trials. Incubation of NCEs with human recombinant enzymes is a popular method for such work because of the specificity, simplicity, and high-throughput nature of this approach for phenotyping studies. The availability of a relative abundance factor and calculated intersystem extrapolation factor for the expressed recombinant enzymes facilitates easy scaling of in vitro data, enabling in vitro-in vivo extrapolation. Described in this unit is a high-throughput screen for identifying enzymes involved in the metabolism of NCEs. Emphasis is placed on the analysis of the human recombinant enzymes CYP1A2, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2B6, and CYP3A4, including the calculation of the intrinsic clearance for each. Copyright © 2014 John Wiley & Sons, Inc. All rights reserved.

A high throughput array microscope for the mechanical characterization of biomaterials

NASA Astrophysics Data System (ADS)

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.

High-Throughput Phenotyping to Detect Drought Tolerance QTL in Wild Barley Introgression Lines

PubMed Central

Honsdorf, Nora; March, Timothy John; Berger, Bettina; Tester, Mark; Pillen, Klaus

2014-01-01

Drought is one of the most severe stresses, endangering crop yields worldwide. In order to select drought tolerant genotypes, access to exotic germplasm and efficient phenotyping protocols are needed. In this study the high-throughput phenotyping platform “The Plant Accelerator”, Adelaide, Australia, was used to screen a set of 47 juvenile (six week old) wild barley introgression lines (S42ILs) for drought stress responses. The kinetics of growth development was evaluated under early drought stress and well watered treatments. High correlation (r = 0.98) between image based biomass estimates and actual biomass was demonstrated, and the suitability of the system to accurately and non-destructively estimate biomass was validated. Subsequently, quantitative trait loci (QTL) were located, which contributed to the genetic control of growth under drought stress. In total, 44 QTL for eleven out of 14 investigated traits were mapped, which for example controlled growth rate and water use efficiency. The correspondence of those QTL with QTL previously identified in field trials is shown. For instance, six out of eight QTL controlling plant height were also found in previous field and glasshouse studies with the same introgression lines. This indicates that phenotyping juvenile plants may assist in predicting adult plant performance. In addition, favorable wild barley alleles for growth and biomass parameters were detected, for instance, a QTL that increased biomass by approximately 36%. In particular, introgression line S42IL-121 revealed improved growth under drought stress compared to the control Scarlett. The introgression line showed a similar behavior in previous field experiments, indicating that S42IL-121 may be an attractive donor for breeding of drought tolerant barley cultivars. PMID:24823485

High-Throughput and Cost-Effective Characterization of Induced Pluripotent Stem Cells.

PubMed

D'Antonio, Matteo; Woodruff, Grace; Nathanson, Jason L; D'Antonio-Chronowska, Agnieszka; Arias, Angelo; Matsui, Hiroko; Williams, Roy; Herrera, Cheryl; Reyna, Sol M; Yeo, Gene W; Goldstein, Lawrence S B; Panopoulos, Athanasia D; Frazer, Kelly A

2017-04-11

Reprogramming somatic cells to induced pluripotent stem cells (iPSCs) offers the possibility of studying the molecular mechanisms underlying human diseases in cell types difficult to extract from living patients, such as neurons and cardiomyocytes. To date, studies have been published that use small panels of iPSC-derived cell lines to study monogenic diseases. However, to study complex diseases, where the genetic variation underlying the disorder is unknown, a sizable number of patient-specific iPSC lines and controls need to be generated. Currently the methods for deriving and characterizing iPSCs are time consuming, expensive, and, in some cases, descriptive but not quantitative. Here we set out to develop a set of simple methods that reduce cost and increase throughput in the characterization of iPSC lines. Specifically, we outline methods for high-throughput quantification of surface markers, gene expression analysis of in vitro differentiation potential, and evaluation of karyotype with markedly reduced cost. Published by Elsevier Inc.

Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium

PubMed Central

Pathak, Jyotishman; Bailey, Kent R; Beebe, Calvin E; Bethard, Steven; Carrell, David S; Chen, Pei J; Dligach, Dmitriy; Endle, Cory M; Hart, Lacey A; Haug, Peter J; Huff, Stanley M; Kaggal, Vinod C; Li, Dingcheng; Liu, Hongfang; Marchant, Kyle; Masanz, James; Miller, Timothy; Oniki, Thomas A; Palmer, Martha; Peterson, Kevin J; Rea, Susan; Savova, Guergana K; Stancl, Craig R; Sohn, Sunghwan; Solbrig, Harold R; Suesse, Dale B; Tao, Cui; Taylor, David P; Westberg, Les; Wu, Stephen; Zhuo, Ning; Chute, Christopher G

2013-01-01

Research objective To develop scalable informatics infrastructure for normalization of both structured and unstructured electronic health record (EHR) data into a unified, concept-based model for high-throughput phenotype extraction. Materials and methods Software tools and applications were developed to extract information from EHRs. Representative and convenience samples of both structured and unstructured data from two EHR systems—Mayo Clinic and Intermountain Healthcare—were used for development and validation. Extracted information was standardized and normalized to meaningful use (MU) conformant terminology and value set standards using Clinical Element Models (CEMs). These resources were used to demonstrate semi-automatic execution of MU clinical-quality measures modeled using the Quality Data Model (QDM) and an open-source rules engine. Results Using CEMs and open-source natural language processing and terminology services engines—namely, Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) and Common Terminology Services (CTS2)—we developed a data-normalization platform that ensures data security, end-to-end connectivity, and reliable data flow within and across institutions. We demonstrated the applicability of this platform by executing a QDM-based MU quality measure that determines the percentage of patients between 18 and 75 years with diabetes whose most recent low-density lipoprotein cholesterol test result during the measurement year was <100 mg/dL on a randomly selected cohort of 273 Mayo Clinic patients. The platform identified 21 and 18 patients for the denominator and numerator of the quality measure, respectively. Validation results indicate that all identified patients meet the QDM-based criteria. Conclusions End-to-end automated systems for extracting clinical information from diverse EHR systems require extensive use of standardized vocabularies and terminologies, as well as robust information models for storing

High throughput field plant phenotyping facility at University of Nebraska-Lincoln and the first year experience

NASA Astrophysics Data System (ADS)

Ge, Y.; Bai, G.; Irmak, S.; Awada, T.; Stoerger, V.; Graef, G.; Scoby, D.; Schnable, J.

2017-12-01

University of Nebraska - Lincoln's high throughput field plant phenotyping facility is a cable robot based system built on a 1-ac field. The sensor platform is tethered with eight cables via four poles at the corners of the field for its precise control and positioning. The sensor modules on the platform include a 4-band RGB-NIR camera, a thermal infrared camera, a 3D LiDAR, VNIR spectrometers, and environmental sensors. These sensors are used to collect multifaceted physiological, structural and chemical properties of plants from the field plots. A subsurface drip irrigation system is established in this field which allows a controlled amount of water and fertilizers to be delivered to individual plots. An extensive soil moisture sensor network is also established to monitor soil water status, and serve as a feedback loop for irrigation scheduling. In the first year of operation, the field is planted maize and soybean. Weekly ground truth data were collected from the plots to validate image and sensor data from the phenotyping system. This presentation will provide an overview of this state-of-the-art field plant phenotyping facility, and present preliminary data from the first year operation of the system.

Biophysics of cancer progression and high-throughput mechanical characterization of biomaterials

NASA Astrophysics Data System (ADS)

Osborne, Lukas Dylan

Cancer metastasis involves a series of events known as the metastatic cascade. In this complex progression, cancer cells detach from the primary tumor, invade the surrounding stromal space, transmigrate the vascular system, and establish secondary tumors at distal sites. Specific mechanical phenotypes are likely adopted to enable cells to successfully navigate the mechanical environments encountered during metastasis. To examine the role of cell mechanics in cancer progression, I employed force-consistent biophysical and biochemical assays to characterize the mechanistic links between stiffness, stiffness response and cell invasion during the epithelial to mesenchymal transition (EMT). EMT is an essential physiological process, whose abnormal reactivation has been implicated in the detachment of cancer cells from epithelial tissue and their subsequent invasion into stromal tissue. I demonstrate that epithelial-state cells respond to force by evoking a stiffening response, and that after EMT, mesenchymal-state cells have reduced stiffness but also lose the ability to increase their stiffness in response to force. Using loss and gain of function studies, two proteins are established as functional connections between attenuated stiffness and stiffness response and the increased invasion capacity acquired after EMT. To enable larger scale assays to more fully explore the connection between biomechanics and cancer, I discuss the development of an automated array high throughput (AHT) microscope. The AHT system is shown to implement passive microbead rheology to accurately characterize the mechanical properties of biomaterials. Compared to manually performed mechanical characterizations, the AHT system executes experiments in two orders of magnitude less time. Finally, I use the AHT microscope to study the effect of gain of function oncogenic molecules on cell stiffness. I find evidence that our assay can identify alterations in cell stiffness due to constitutive

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

Comparative aerial- and ground-based high-throughput phenotyping for the genetic dissection of NDVI as a proxy for drought-adaptive traits in durum wheat

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares the results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used to mea...

Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

PubMed

Rozman, Jan; Rathkolb, Birgit; Oestereicher, Manuela A; Schütt, Christine; Ravindranath, Aakash Chavan; Leuchtenberger, Stefanie; Sharma, Sapna; Kistler, Martin; Willershäuser, Monja; Brommage, Robert; Meehan, Terrence F; Mason, Jeremy; Haselimashhadi, Hamed; Hough, Tertius; Mallon, Ann-Marie; Wells, Sara; Santos, Luis; Lelliott, Christopher J; White, Jacqueline K; Sorg, Tania; Champy, Marie-France; Bower, Lynette R; Reynolds, Corey L; Flenniken, Ann M; Murray, Stephen A; Nutter, Lauryl M J; Svenson, Karen L; West, David; Tocchini-Valentini, Glauco P; Beaudet, Arthur L; Bosch, Fatima; Braun, Robert B; Dobbie, Michael S; Gao, Xiang; Herault, Yann; Moshiri, Ala; Moore, Bret A; Kent Lloyd, K C; McKerlie, Colin; Masuya, Hiroshi; Tanaka, Nobuhiko; Flicek, Paul; Parkinson, Helen E; Sedlacek, Radislav; Seong, Je Kyung; Wang, Chi-Kuang Leo; Moore, Mark; Brown, Steve D; Tschöp, Matthias H; Wurst, Wolfgang; Klingenspor, Martin; Wolf, Eckhard; Beckers, Johannes; Machicao, Fausto; Peter, Andreas; Staiger, Harald; Häring, Hans-Ulrich; Grallert, Harald; Campillos, Monica; Maier, Holger; Fuchs, Helmut; Gailus-Durner, Valerie; Werner, Thomas; Hrabe de Angelis, Martin

2018-01-18

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

High-throughput, image-based screening of pooled genetic variant libraries

PubMed Central

Emanuel, George; Moffitt, Jeffrey R.; Zhuang, Xiaowei

2018-01-01

Image-based, high-throughput screening of genetic perturbations will advance both biology and biotechnology. We report a high-throughput screening method that allows diverse genotypes and corresponding phenotypes to be imaged in numerous individual cells. We achieve genotyping by introducing barcoded genetic variants into cells and using massively multiplexed FISH to measure the barcodes. We demonstrated this method by screening mutants of the fluorescent protein YFAST, yielding brighter and more photostable YFAST variants. PMID:29083401

Microfluidic Impedance Flow Cytometry Enabling High-Throughput Single-Cell Electrical Property Characterization

PubMed Central

Chen, Jian; Xue, Chengcheng; Zhao, Yang; Chen, Deyong; Wu, Min-Hsien; Wang, Junbo

2015-01-01

This article reviews recent developments in microfluidic impedance flow cytometry for high-throughput electrical property characterization of single cells. Four major perspectives of microfluidic impedance flow cytometry for single-cell characterization are included in this review: (1) early developments of microfluidic impedance flow cytometry for single-cell electrical property characterization; (2) microfluidic impedance flow cytometry with enhanced sensitivity; (3) microfluidic impedance and optical flow cytometry for single-cell analysis and (4) integrated point of care system based on microfluidic impedance flow cytometry. We examine the advantages and limitations of each technique and discuss future research opportunities from the perspectives of both technical innovation and clinical applications. PMID:25938973

Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems

PubMed Central

Junker, Astrid; Muraya, Moses M.; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Klukas, Christian; Melchinger, Albrecht E.; Meyer, Rhonda C.; Riewe, David; Altmann, Thomas

2015-01-01

Detailed and standardized protocols for plant cultivation in environmentally controlled conditions are an essential prerequisite to conduct reproducible experiments with precisely defined treatments. Setting up appropriate and well defined experimental procedures is thus crucial for the generation of solid evidence and indispensable for successful plant research. Non-invasive and high throughput (HT) phenotyping technologies offer the opportunity to monitor and quantify performance dynamics of several hundreds of plants at a time. Compared to small scale plant cultivations, HT systems have much higher demands, from a conceptual and a logistic point of view, on experimental design, as well as the actual plant cultivation conditions, and the image analysis and statistical methods for data evaluation. Furthermore, cultivation conditions need to be designed that elicit plant performance characteristics corresponding to those under natural conditions. This manuscript describes critical steps in the optimization of procedures for HT plant phenotyping systems. Starting with the model plant Arabidopsis, HT-compatible methods were tested, and optimized with regard to growth substrate, soil coverage, watering regime, experimental design (considering environmental inhomogeneities) in automated plant cultivation and imaging systems. As revealed by metabolite profiling, plant movement did not affect the plants' physiological status. Based on these results, procedures for maize HT cultivation and monitoring were established. Variation of maize vegetative growth in the HT phenotyping system did match well with that observed in the field. The presented results outline important issues to be considered in the design of HT phenotyping experiments for model and crop plants. It thereby provides guidelines for the setup of HT experimental procedures, which are required for the generation of reliable and reproducible data of phenotypic variation for a broad range of applications. PMID

High-throughput full-length single-cell mRNA-seq of rare cells.

PubMed

Ooi, Chin Chun; Mantalas, Gary L; Koh, Winston; Neff, Norma F; Fuchigami, Teruaki; Wong, Dawson J; Wilson, Robert J; Park, Seung-Min; Gambhir, Sanjiv S; Quake, Stephen R; Wang, Shan X

2017-01-01

Single-cell characterization techniques, such as mRNA-seq, have been applied to a diverse range of applications in cancer biology, yielding great insight into mechanisms leading to therapy resistance and tumor clonality. While single-cell techniques can yield a wealth of information, a common bottleneck is the lack of throughput, with many current processing methods being limited to the analysis of small volumes of single cell suspensions with cell densities on the order of 107 per mL. In this work, we present a high-throughput full-length mRNA-seq protocol incorporating a magnetic sifter and magnetic nanoparticle-antibody conjugates for rare cell enrichment, and Smart-seq2 chemistry for sequencing. We evaluate the efficiency and quality of this protocol with a simulated circulating tumor cell system, whereby non-small-cell lung cancer cell lines (NCI-H1650 and NCI-H1975) are spiked into whole blood, before being enriched for single-cell mRNA-seq by EpCAM-functionalized magnetic nanoparticles and the magnetic sifter. We obtain high efficiency (> 90%) capture and release of these simulated rare cells via the magnetic sifter, with reproducible transcriptome data. In addition, while mRNA-seq data is typically only used for gene expression analysis of transcriptomic data, we demonstrate the use of full-length mRNA-seq chemistries like Smart-seq2 to facilitate variant analysis of expressed genes. This enables the use of mRNA-seq data for differentiating cells in a heterogeneous population by both their phenotypic and variant profile. In a simulated heterogeneous mixture of circulating tumor cells in whole blood, we utilize this high-throughput protocol to differentiate these heterogeneous cells by both their phenotype (lung cancer versus white blood cells), and mutational profile (H1650 versus H1975 cells), in a single sequencing run. This high-throughput method can help facilitate single-cell analysis of rare cell populations, such as circulating tumor or endothelial

Establishment of integrated protocols for automated high throughput kinetic chlorophyll fluorescence analyses.

PubMed

Tschiersch, Henning; Junker, Astrid; Meyer, Rhonda C; Altmann, Thomas

2017-01-01

Automated plant phenotyping has been established as a powerful new tool in studying plant growth, development and response to various types of biotic or abiotic stressors. Respective facilities mainly apply non-invasive imaging based methods, which enable the continuous quantification of the dynamics of plant growth and physiology during developmental progression. However, especially for plants of larger size, integrative, automated and high throughput measurements of complex physiological parameters such as photosystem II efficiency determined through kinetic chlorophyll fluorescence analysis remain a challenge. We present the technical installations and the establishment of experimental procedures that allow the integrated high throughput imaging of all commonly determined PSII parameters for small and large plants using kinetic chlorophyll fluorescence imaging systems (FluorCam, PSI) integrated into automated phenotyping facilities (Scanalyzer, LemnaTec). Besides determination of the maximum PSII efficiency, we focused on implementation of high throughput amenable protocols recording PSII operating efficiency (Φ PSII ). Using the presented setup, this parameter is shown to be reproducibly measured in differently sized plants despite the corresponding variation in distance between plants and light source that caused small differences in incident light intensity. Values of Φ PSII obtained with the automated chlorophyll fluorescence imaging setup correlated very well with conventionally determined data using a spot-measuring chlorophyll fluorometer. The established high throughput operating protocols enable the screening of up to 1080 small and 184 large plants per hour, respectively. The application of the implemented high throughput protocols is demonstrated in screening experiments performed with large Arabidopsis and maize populations assessing natural variation in PSII efficiency. The incorporation of imaging systems suitable for kinetic chlorophyll

High-Throughput Phenotyping of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes and Neurons Using Electric Field Stimulation and High-Speed Fluorescence Imaging

PubMed Central

Daily, Neil J.; Du, Zhong-Wei

2017-01-01

Abstract Electrophysiology of excitable cells, including muscle cells and neurons, has been measured by making direct contact with a single cell using a micropipette electrode. To increase the assay throughput, optical devices such as microscopes and microplate readers have been used to analyze electrophysiology of multiple cells. We have established a high-throughput (HTP) analysis of action potentials (APs) in highly enriched motor neurons and cardiomyocytes (CMs) that are differentiated from human induced pluripotent stem cells (iPSCs). A multichannel electric field stimulation (EFS) device enabled the ability to electrically stimulate cells and measure dynamic changes in APs of excitable cells ultra-rapidly (>100 data points per second) by imaging entire 96-well plates. We found that the activities of both neurons and CMs and their response to EFS and chemicals are readily discerned by our fluorescence imaging-based HTP phenotyping assay. The latest generation of calcium (Ca2+) indicator dyes, FLIPR Calcium 6 and Cal-520, with the HTP device enables physiological analysis of human iPSC-derived samples highlighting its potential application for understanding disease mechanisms and discovering new therapeutic treatments. PMID:28525289

A high-throughput label-free nanoparticle analyser.

PubMed

Fraikin, Jean-Luc; Teesalu, Tambet; McKenney, Christopher M; Ruoslahti, Erkki; Cleland, Andrew N

2011-05-01

Synthetic nanoparticles and genetically modified viruses are used in a range of applications, but high-throughput analytical tools for the physical characterization of these objects are needed. Here we present a microfluidic analyser that detects individual nanoparticles and characterizes complex, unlabelled nanoparticle suspensions. We demonstrate the detection, concentration analysis and sizing of individual synthetic nanoparticles in a multicomponent mixture with sufficient throughput to analyse 500,000 particles per second. We also report the rapid size and titre analysis of unlabelled bacteriophage T7 in both salt solution and mouse blood plasma, using just ~1 × 10⁻⁶ l of analyte. Unexpectedly, in the native blood plasma we discover a large background of naturally occurring nanoparticles with a power-law size distribution. The high-throughput detection capability, scalable fabrication and simple electronics of this instrument make it well suited for diverse applications.

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

PubMed Central

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

High-Throughput Phenotypic Screening of Human Astrocytes to Identify Compounds That Protect Against Oxidative Stress.

PubMed

Thorne, Natasha; Malik, Nasir; Shah, Sonia; Zhao, Jean; Class, Bradley; Aguisanda, Francis; Southall, Noel; Xia, Menghang; McKew, John C; Rao, Mahendra; Zheng, Wei

2016-05-01

Astrocytes are the predominant cell type in the nervous system and play a significant role in maintaining neuronal health and homeostasis. Recently, astrocyte dysfunction has been implicated in the pathogenesis of many neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. Astrocytes are thus an attractive new target for drug discovery for neurological disorders. Using astrocytes differentiated from human embryonic stem cells, we have developed an assay to identify compounds that protect against oxidative stress, a condition associated with many neurodegenerative diseases. This phenotypic oxidative stress assay has been optimized for high-throughput screening in a 1,536-well plate format. From a screen of approximately 4,100 bioactive tool compounds and approved drugs, we identified a set of 22 that acutely protect human astrocytes from the consequences of hydrogen peroxide-induced oxidative stress. Nine of these compounds were also found to be protective of induced pluripotent stem cell-differentiated astrocytes in a related assay. These compounds are thought to confer protection through hormesis, activating stress-response pathways and preconditioning astrocytes to handle subsequent exposure to hydrogen peroxide. In fact, four of these compounds were found to activate the antioxidant response element/nuclear factor-E2-related factor 2 pathway, a protective pathway induced by toxic insults. Our results demonstrate the relevancy and utility of using astrocytes differentiated from human stem cells as a disease model for drug discovery and development. Astrocytes play a key role in neurological diseases. Drug discovery efforts that target astrocytes can identify novel therapeutics. Human astrocytes are difficult to obtain and thus are challenging to use for high-throughput screening, which requires large numbers of cells. Using human embryonic stem cell-derived astrocytes and an

High-throughput RAD-SNP genotyping for characterization of sugar beet genotypes

USDA-ARS?s Scientific Manuscript database

High-throughput SNP genotyping provides a rapid way of developing resourceful set of markers for delineating the genetic architecture and for effective species discrimination. In the presented research, we demonstrate a set of 192 SNPs for effective genotyping in sugar beet using high-throughput mar...

High-throughput single-molecule telomere characterization.

PubMed

McCaffrey, Jennifer; Young, Eleanor; Lassahn, Katy; Sibert, Justin; Pastor, Steven; Riethman, Harold; Xiao, Ming

2017-11-01

We have developed a novel method that enables global subtelomere and haplotype-resolved analysis of telomere lengths at the single-molecule level. An in vitro CRISPR/Cas9 RNA-directed nickase system directs the specific labeling of human (TTAGGG)n DNA tracts in genomes that have also been barcoded using a separate nickase enzyme that recognizes a 7-bp motif genome-wide. High-throughput imaging and analysis of large DNA single molecules from genomes labeled in this fashion using a nanochannel array system permits mapping through subtelomere repeat element (SRE) regions to unique chromosomal DNA while simultaneously measuring the (TTAGGG)n tract length at the end of each large telomere-terminal DNA segment. The methodology also permits subtelomere and haplotype-resolved analyses of SRE organization and variation, providing a window into the population dynamics and potential functions of these complex and structurally variant telomere-adjacent DNA regions. At its current stage of development, the assay can be used to identify and characterize telomere length distributions of 30-35 discrete telomeres simultaneously and accurately. The assay's utility is demonstrated using early versus late passage and senescent human diploid fibroblasts, documenting the anticipated telomere attrition on a global telomere-by-telomere basis as well as identifying subtelomere-specific biases for critically short telomeres. Similarly, we present the first global single-telomere-resolved analyses of two cancer cell lines. © 2017 McCaffrey et al.; Published by Cold Spring Harbor Laboratory Press.

Lateral Temperature-Gradient Method for High-Throughput Characterization of Material Processing by Millisecond Laser Annealing.

PubMed

Bell, Robert T; Jacobs, Alan G; Sorg, Victoria C; Jung, Byungki; Hill, Megan O; Treml, Benjamin E; Thompson, Michael O

2016-09-12

A high-throughput method for characterizing the temperature dependence of material properties following microsecond to millisecond thermal annealing, exploiting the temperature gradients created by a lateral gradient laser spike anneal (lgLSA), is presented. Laser scans generate spatial thermal gradients of up to 5 °C/μm with peak temperatures ranging from ambient to in excess of 1400 °C, limited only by laser power and materials thermal limits. Discrete spatial property measurements across the temperature gradient are then equivalent to independent measurements after varying temperature anneals. Accurate temperature calibrations, essential to quantitative analysis, are critical and methods for both peak temperature and spatial/temporal temperature profile characterization are presented. These include absolute temperature calibrations based on melting and thermal decomposition, and time-resolved profiles measured using platinum thermistors. A variety of spatially resolved measurement probes, ranging from point-like continuous profiling to large area sampling, are discussed. Examples from annealing of III-V semiconductors, CdSe quantum dots, low-κ dielectrics, and block copolymers are included to demonstrate the flexibility, high throughput, and precision of this technique.

Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time

PubMed Central

Neilson, E. H.; Edwards, A. M.; Blomstedt, C. K.; Berger, B.; Møller, B. Lindberg; Gleadow, R. M.

2015-01-01

The use of high-throughput phenotyping systems and non-destructive imaging is widely regarded as a key technology allowing scientists and breeders to develop crops with the ability to perform well under diverse environmental conditions. However, many of these phenotyping studies have been optimized using the model plant Arabidopsis thaliana. In this study, The Plant Accelerator® at The University of Adelaide, Australia, was used to investigate the growth and phenotypic response of the important cereal crop, Sorghum bicolor L. Moench and related hybrids to water-limited conditions and different levels of fertilizer. Imaging in different spectral ranges was used to monitor plant composition, chlorophyll, and moisture content. Phenotypic image analysis accurately measured plant biomass. The data set obtained enabled the responses of the different sorghum varieties to the experimental treatments to be differentiated and modelled. Plant architectural instead of architecture elements were determined using imaging and found to correlate with an improved tolerance to stress, for example diurnal leaf curling and leaf area index. Analysis of colour images revealed that leaf ‘greenness’ correlated with foliar nitrogen and chlorophyll, while near infrared reflectance (NIR) analysis was a good predictor of water content and leaf thickness, and correlated with plant moisture content. It is shown that imaging sorghum using a high-throughput system can accurately identify and differentiate between growth and specific phenotypic traits. R scripts for robust, parsimonious models are provided to allow other users of phenomic imaging systems to extract useful data readily, and thus relieve a bottleneck in phenotypic screening of multiple genotypes of key crop plants. PMID:25697789

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

PubMed Central

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

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

PubMed

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

2015-01-01

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

Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

EPA Science Inventory

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...

A high-throughput phenotypic screen identifies clofazimine as a potential treatment for cryptosporidiosis

PubMed Central

Jumani, Rajiv S.; Wright, Timothy M.; Chatterjee, Arnab K.; Huston, Christopher D.; Schultz, Peter G.; McNamara, Case W.

2017-01-01

Cryptosporidiosis has emerged as a leading cause of non-viral diarrhea in children under five years of age in the developing world, yet the current standard of care to treat Cryptosporidium infections, nitazoxanide, demonstrates limited and immune-dependent efficacy. Given the lack of treatments with universal efficacy, drug discovery efforts against cryptosporidiosis are necessary to find therapeutics more efficacious than the standard of care. To date, cryptosporidiosis drug discovery efforts have been limited to a few targeted mechanisms in the parasite and whole cell phenotypic screens against small, focused collections of compounds. Using a previous screen as a basis, we initiated the largest known drug discovery effort to identify novel anticryptosporidial agents. A high-content imaging assay for inhibitors of Cryptosporidium parvum proliferation within a human intestinal epithelial cell line was miniaturized and automated to enable high-throughput phenotypic screening against a large, diverse library of small molecules. A screen of 78,942 compounds identified 12 anticryptosporidial hits with sub-micromolar activity, including clofazimine, an FDA-approved drug for the treatment of leprosy, which demonstrated potent and selective in vitro activity (EC50 = 15 nM) against C. parvum. Clofazimine also displayed activity against C. hominis–the other most clinically-relevant species of Cryptosporidium. Importantly, clofazimine is known to accumulate within epithelial cells of the small intestine, the primary site of Cryptosporidium infection. In a mouse model of acute cryptosporidiosis, a once daily dosage regimen for three consecutive days or a single high dose resulted in reduction of oocyst shedding below the limit detectable by flow cytometry. Recently, a target product profile (TPP) for an anticryptosporidial compound was proposed by Huston et al. and highlights the need for a short dosing regimen (< 7 days) and formulations for children < 2 years

Near infrared spectroscopy for high-throughput characterization of Shea tree (Vitellaria paradoxa) nut fat profiles.

PubMed

Davrieux, Fabrice; Allal, François; Piombo, Georges; Kelly, Bokary; Okulo, John B; Thiam, Massamba; Diallo, Ousmane B; Bouvet, Jean-Marc

2010-07-14

The Shea tree (Vitellaria paradoxa) is a major tree species in African agroforestry systems. Butter extracted from its nuts offers an opportunity for sustainable development in Sudanian countries and an attractive potential for the food and cosmetics industries. The purpose of this study was to develop near-infrared spectroscopy (NIRS) calibrations to characterize Shea nut fat profiles. Powders prepared from nuts collected from 624 trees in five African countries (Senegal, Mali, Burkina Faso, Ghana and Uganda) were analyzed for moisture content, fat content using solvent extraction, and fatty acid profiles using gas chromatography. Results confirmed the differences between East and West African Shea nut fat composition: eastern nuts had significantly higher fat and oleic acid contents. Near infrared reflectance spectra were recorded for each sample. Ten percent of the samples were randomly selected for validation and the remaining samples used for calibration. For each constituent, calibration equations were developed using modified partial least squares (MPLS) regression. The equation performances were evaluated using the ratio performance to deviation (RPD(p)) and R(p)(2) parameters, obtained by comparison of the validation set NIR predictions and corresponding laboratory values. Moisture (RPD(p) = 4.45; R(p)(2) = 0.95) and fat (RPD(p) = 5.6; R(p)(2) = 0.97) calibrations enabled accurate determination of these traits. NIR models for stearic (RPD(p) = 6.26; R(p)(2) = 0.98) and oleic (RPD(p) = 7.91; R(p)(2) = 0.99) acids were highly efficient and enabled sharp characterization of these two major Shea butter fatty acids. This study demonstrated the ability of near-infrared spectroscopy for high-throughput phenotyping of Shea nuts.

Ultra-high frequency ultrasound biomicroscopy and high throughput cardiovascular phenotyping in a large scale mouse mutagenesis screen

NASA Astrophysics Data System (ADS)

Liu, Xiaoqin; Francis, Richard; Tobita, Kimimasa; Kim, Andy; Leatherbury, Linda; Lo, Cecilia W.

2013-02-01

Ultrasound biomicroscopy (UBM) is ideally suited for phenotyping fetal mice for congenital heart disease (CHD), as imaging can be carried out noninvasively to provide both hemodynamic and structural information essential for CHD diagnosis. Using the UBM (Vevo 2100; 40Hz) in conjunction with the clinical ultrasound system (Acuson Sequioa C512; 15Hz), we developed a two-step screening protocol to scan thousands fetuses derived from ENU mutagenized pedigrees. A wide spectrum of CHD was detected by the UBM, which were subsequently confirmed with follow-up necropsy and histopathology examination with episcopic fluorescence image capture. CHD observed included outflow anomalies, left/right heart obstructive lesions, septal/valvular defects and cardiac situs anomalies. Meanwhile, various extracardiac defects were found, such as polydactyly, craniofacial defects, exencephaly, omphalocele-cleft palate, most of which were associated with cardiac defects. Our analyses showed the UBM was better at assessing cardiac structure and blood flow profiles, while conventional ultrasound allowed higher throughput low-resolution screening. Our study showed the integration of conventional clinical ultrasound imaging with the UBM for fetal mouse cardiovascular phenotyping can maximize the detection and recovery of CHD mutants.

High-Throughput Characterization of Porous Materials Using Graphics Processing Units

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jihan; Martin, Richard L.; Rübel, Oliver

We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CHmore » $$_{4}$$ and CO$$_{2}$$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.« less

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains.

PubMed

Zych, Konrad; Li, Yang; van der Velde, Joeri K; Joosen, Ronny V L; Ligterink, Wilco; Jansen, Ritsert C; Arends, Danny

2015-02-19

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers. The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping. We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population. The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R

High-throughput analysis of yeast replicative aging using a microfluidic system

PubMed Central

Jo, Myeong Chan; Liu, Wei; Gu, Liang; Dang, Weiwei; Qin, Lidong

2015-01-01

Saccharomyces cerevisiae has been an important model for studying the molecular mechanisms of aging in eukaryotic cells. However, the laborious and low-throughput methods of current yeast replicative lifespan assays limit their usefulness as a broad genetic screening platform for research on aging. We address this limitation by developing an efficient, high-throughput microfluidic single-cell analysis chip in combination with high-resolution time-lapse microscopy. This innovative design enables, to our knowledge for the first time, the determination of the yeast replicative lifespan in a high-throughput manner. Morphological and phenotypical changes during aging can also be monitored automatically with a much higher throughput than previous microfluidic designs. We demonstrate highly efficient trapping and retention of mother cells, determination of the replicative lifespan, and tracking of yeast cells throughout their entire lifespan. Using the high-resolution and large-scale data generated from the high-throughput yeast aging analysis (HYAA) chips, we investigated particular longevity-related changes in cell morphology and characteristics, including critical cell size, terminal morphology, and protein subcellular localization. In addition, because of the significantly improved retention rate of yeast mother cell, the HYAA-Chip was capable of demonstrating replicative lifespan extension by calorie restriction. PMID:26170317

High-Throughput Intracellular Antimicrobial Susceptibility Testing of Legionella pneumophila

PubMed Central

Chiaraviglio, Lucius

2015-01-01

Legionella pneumophila is a Gram-negative opportunistic human pathogen that causes a severe pneumonia known as Legionnaires' disease. Notably, in the human host, the organism is believed to replicate solely within an intracellular compartment, predominantly within pulmonary macrophages. Consequently, successful therapy is predicated on antimicrobials penetrating into this intracellular growth niche. However, standard antimicrobial susceptibility testing methods test solely for extracellular growth inhibition. Here, we make use of a high-throughput assay to characterize intracellular growth inhibition activity of known antimicrobials. For select antimicrobials, high-resolution dose-response analysis was then performed to characterize and compare activity levels in both macrophage infection and axenic growth assays. Results support the superiority of several classes of nonpolar antimicrobials in abrogating intracellular growth. Importantly, our assay results show excellent correlations with prior clinical observations of antimicrobial efficacy. Furthermore, we also show the applicability of high-throughput automation to two- and three-dimensional synergy testing. High-resolution isocontour isobolograms provide in vitro support for specific combination antimicrobial therapy. Taken together, findings suggest that high-throughput screening technology may be successfully applied to identify and characterize antimicrobials that target bacterial pathogens that make use of an intracellular growth niche. PMID:26392509

Optimization of high-throughput nanomaterial developmental toxicity testing in zebrafish embryos

EPA Science Inventory

Nanomaterial (NM) developmental toxicities are largely unknown. With an extensive variety of NMs available, high-throughput screening methods may be of value for initial characterization of potential hazard. We optimized a zebrafish embryo test as an in vivo high-throughput assay...

Characterization of DNA-protein interactions using high-throughput sequencing data from pulldown experiments

NASA Astrophysics Data System (ADS)

Moreland, Blythe; Oman, Kenji; Curfman, John; Yan, Pearlly; Bundschuh, Ralf

Methyl-binding domain (MBD) protein pulldown experiments have been a valuable tool in measuring the levels of methylated CpG dinucleotides. Due to the frequent use of this technique, high-throughput sequencing data sets are available that allow a detailed quantitative characterization of the underlying interaction between methylated DNA and MBD proteins. Analyzing such data sets, we first found that two such proteins cannot bind closer to each other than 2 bp, consistent with structural models of the DNA-protein interaction. Second, the large amount of sequencing data allowed us to find rather weak but nevertheless clearly statistically significant sequence preferences for several bases around the required CpG. These results demonstrate that pulldown sequencing is a high-precision tool in characterizing DNA-protein interactions. This material is based upon work supported by the National Science Foundation under Grant No. DMR-1410172.

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

PubMed

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.

High-throughput profiling and analysis of plant responses over time to abiotic stress

USDA-ARS?s Scientific Manuscript database

Energy sorghum (Sorghum bicolor (L.) Moench) is a rapidly growing, high-biomass, annual crop prized for abiotic stress tolerance. Measuring genotype-by-environment (G x E) interactions remains a progress bottleneck. High throughput phenotyping within controlled environments has been proposed as a po...

High-Throughput Intracellular Antimicrobial Susceptibility Testing of Legionella pneumophila.

PubMed

Chiaraviglio, Lucius; Kirby, James E

2015-12-01

Legionella pneumophila is a Gram-negative opportunistic human pathogen that causes a severe pneumonia known as Legionnaires' disease. Notably, in the human host, the organism is believed to replicate solely within an intracellular compartment, predominantly within pulmonary macrophages. Consequently, successful therapy is predicated on antimicrobials penetrating into this intracellular growth niche. However, standard antimicrobial susceptibility testing methods test solely for extracellular growth inhibition. Here, we make use of a high-throughput assay to characterize intracellular growth inhibition activity of known antimicrobials. For select antimicrobials, high-resolution dose-response analysis was then performed to characterize and compare activity levels in both macrophage infection and axenic growth assays. Results support the superiority of several classes of nonpolar antimicrobials in abrogating intracellular growth. Importantly, our assay results show excellent correlations with prior clinical observations of antimicrobial efficacy. Furthermore, we also show the applicability of high-throughput automation to two- and three-dimensional synergy testing. High-resolution isocontour isobolograms provide in vitro support for specific combination antimicrobial therapy. Taken together, findings suggest that high-throughput screening technology may be successfully applied to identify and characterize antimicrobials that target bacterial pathogens that make use of an intracellular growth niche. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Quantifying the Onset and Progression of Plant Senescence by Color Image Analysis for High Throughput Applications

PubMed Central

Cai, Jinhai; Okamoto, Mamoru; Atieno, Judith; Sutton, Tim; Li, Yongle; Miklavcic, Stanley J.

2016-01-01

Leaf senescence, an indicator of plant age and ill health, is an important phenotypic trait for the assessment of a plant’s response to stress. Manual inspection of senescence, however, is time consuming, inaccurate and subjective. In this paper we propose an objective evaluation of plant senescence by color image analysis for use in a high throughput plant phenotyping pipeline. As high throughput phenotyping platforms are designed to capture whole-of-plant features, camera lenses and camera settings are inappropriate for the capture of fine detail. Specifically, plant colors in images may not represent true plant colors, leading to errors in senescence estimation. Our algorithm features a color distortion correction and image restoration step prior to a senescence analysis. We apply our algorithm to two time series of images of wheat and chickpea plants to quantify the onset and progression of senescence. We compare our results with senescence scores resulting from manual inspection. We demonstrate that our procedure is able to process images in an automated way for an accurate estimation of plant senescence even from color distorted and blurred images obtained under high throughput conditions. PMID:27348807

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

PubMed

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.

Adapting capillary gel electrophoresis as a sensitive, high-throughput method to accelerate characterization of nucleic acid metabolic enzymes

PubMed Central

Greenough, Lucia; Schermerhorn, Kelly M.; Mazzola, Laurie; Bybee, Joanna; Rivizzigno, Danielle; Cantin, Elizabeth; Slatko, Barton E.; Gardner, Andrew F.

2016-01-01

Detailed biochemical characterization of nucleic acid enzymes is fundamental to understanding nucleic acid metabolism, genome replication and repair. We report the development of a rapid, high-throughput fluorescence capillary gel electrophoresis method as an alternative to traditional polyacrylamide gel electrophoresis to characterize nucleic acid metabolic enzymes. The principles of assay design described here can be applied to nearly any enzyme system that acts on a fluorescently labeled oligonucleotide substrate. Herein, we describe several assays using this core capillary gel electrophoresis methodology to accelerate study of nucleic acid enzymes. First, assays were designed to examine DNA polymerase activities including nucleotide incorporation kinetics, strand displacement synthesis and 3′-5′ exonuclease activity. Next, DNA repair activities of DNA ligase, flap endonuclease and RNase H2 were monitored. In addition, a multicolor assay that uses four different fluorescently labeled substrates in a single reaction was implemented to characterize GAN nuclease specificity. Finally, a dual-color fluorescence assay to monitor coupled enzyme reactions during Okazaki fragment maturation is described. These assays serve as a template to guide further technical development for enzyme characterization or nucleoside and non-nucleoside inhibitor screening in a high-throughput manner. PMID:26365239

Image-Based High-Throughput Field Phenotyping of Crop Roots1[W][OPEN

PubMed Central

Bucksch, Alexander; Burridge, James; York, Larry M.; Das, Abhiram; Nord, Eric; Weitz, Joshua S.; Lynch, Jonathan P.

2014-01-01

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions. PMID:25187526

High Throughput Phenotypic Analysis of Mycobacterium tuberculosis and Mycobacterium bovis Strains' Metabolism Using Biolog Phenotype Microarrays

PubMed Central

Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R.

2013-01-01

Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the method. By looking for ≥5-fold differences in dye reduction, 12 substrates differentiated M. tuberculosis H37Rv and Mycobacterium bovis AF2122/97. H37Rv and a Beijing strain of M. tuberculosis could also be distinguished in this way, as could field strains of M. bovis; even pairs of strains within one spoligotype could be distinguished by 2 to 3 substrates. Cluster analysis gave three clear groups: H37Rv, Beijing, and all the M. bovis strains. The substrates used agreed well with prior knowledge, though an unexpected finding that AF2122/97 gave greater dye reduction than H37Rv with hexoses was investigated further, in culture flasks, revealing that hexoses and Tween 80 were synergistic for growth and used simultaneously rather than in a diauxic fashion. Potential new substrates for growth media were revealed, too, most promisingly N-acetyl glucosamine. Osmotic and pH arrays divided the mycobacteria into two groups with different salt tolerance, though in contrast to the substrate arrays the groups did not entirely correlate with taxonomic differences. More interestingly, these arrays suggested differences between the amines used by the M. tuberculosis complex and enteric bacteria in acid tolerance, with some hydrophobic amino acids being highly effective. In contrast, γ-aminobutyrate, used in the enteric bacteria, had no effect in the mycobacteria. This study proved principle that Phenotype MicroArrays can be used with slow-growing pathogenic mycobacteria and already has

Computational Approaches to Phenotyping

PubMed Central

Lussier, Yves A.; Liu, Yang

2007-01-01

The recent completion of the Human Genome Project has made possible a high-throughput “systems approach” for accelerating the elucidation of molecular underpinnings of human diseases, and subsequent derivation of molecular-based strategies to more effectively prevent, diagnose, and treat these diseases. Although altered phenotypes are among the most reliable manifestations of altered gene functions, research using systematic analysis of phenotype relationships to study human biology is still in its infancy. This article focuses on the emerging field of high-throughput phenotyping (HTP) phenomics research, which aims to capitalize on novel high-throughput computation and informatics technology developments to derive genomewide molecular networks of genotype–phenotype associations, or “phenomic associations.” The HTP phenomics research field faces the challenge of technological research and development to generate novel tools in computation and informatics that will allow researchers to amass, access, integrate, organize, and manage phenotypic databases across species and enable genomewide analysis to associate phenotypic information with genomic data at different scales of biology. Key state-of-the-art technological advancements critical for HTP phenomics research are covered in this review. In particular, we highlight the power of computational approaches to conduct large-scale phenomics studies. PMID:17202287

High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling

PubMed Central

Till, Bradley J.; Zerr, Troy; Bowers, Elisabeth; Greene, Elizabeth A.; Comai, Luca; Henikoff, Steven

2006-01-01

Human individuals differ from one another at only ∼0.1% of nucleotide positions, but these single nucleotide differences account for most heritable phenotypic variation. Large-scale efforts to discover and genotype human variation have been limited to common polymorphisms. However, these efforts overlook rare nucleotide changes that may contribute to phenotypic diversity and genetic disorders, including cancer. Thus, there is an increasing need for high-throughput methods to robustly detect rare nucleotide differences. Toward this end, we have adapted the mismatch discovery method known as Ecotilling for the discovery of human single nucleotide polymorphisms. To increase throughput and reduce costs, we developed a universal primer strategy and implemented algorithms for automated band detection. Ecotilling was validated by screening 90 human DNA samples for nucleotide changes in 5 gene targets and by comparing results to public resequencing data. To increase throughput for discovery of rare alleles, we pooled samples 8-fold and found Ecotilling to be efficient relative to resequencing, with a false negative rate of 5% and a false discovery rate of 4%. We identified 28 new rare alleles, including some that are predicted to damage protein function. The detection of rare damaging mutations has implications for models of human disease. PMID:16893952

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

PubMed

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

2014-01-01

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

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

PubMed

Moore, Brad T; Jordan, James M; Baugh, L Ryan

2013-01-01

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.

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

PubMed Central

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C.

2017-01-01

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 the

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

PubMed

Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C

2017-01-01

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 [ R 2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily ( R 2 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 ( R 2 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 ( R 2 < 0.3 and RPD < 1.2). This study

High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction

NASA Astrophysics Data System (ADS)

Hong, Hyundae; Benac, Jasenka; Riggsbee, Daniel; Koutsky, Keith

2014-03-01

High throughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants' responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for high throughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.

Adapting capillary gel electrophoresis as a sensitive, high-throughput method to accelerate characterization of nucleic acid metabolic enzymes.

PubMed

Greenough, Lucia; Schermerhorn, Kelly M; Mazzola, Laurie; Bybee, Joanna; Rivizzigno, Danielle; Cantin, Elizabeth; Slatko, Barton E; Gardner, Andrew F

2016-01-29

Detailed biochemical characterization of nucleic acid enzymes is fundamental to understanding nucleic acid metabolism, genome replication and repair. We report the development of a rapid, high-throughput fluorescence capillary gel electrophoresis method as an alternative to traditional polyacrylamide gel electrophoresis to characterize nucleic acid metabolic enzymes. The principles of assay design described here can be applied to nearly any enzyme system that acts on a fluorescently labeled oligonucleotide substrate. Herein, we describe several assays using this core capillary gel electrophoresis methodology to accelerate study of nucleic acid enzymes. First, assays were designed to examine DNA polymerase activities including nucleotide incorporation kinetics, strand displacement synthesis and 3'-5' exonuclease activity. Next, DNA repair activities of DNA ligase, flap endonuclease and RNase H2 were monitored. In addition, a multicolor assay that uses four different fluorescently labeled substrates in a single reaction was implemented to characterize GAN nuclease specificity. Finally, a dual-color fluorescence assay to monitor coupled enzyme reactions during Okazaki fragment maturation is described. These assays serve as a template to guide further technical development for enzyme characterization or nucleoside and non-nucleoside inhibitor screening in a high-throughput manner. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

High throughput single cell counting in droplet-based microfluidics.

PubMed

Lu, Heng; Caen, Ouriel; Vrignon, Jeremy; Zonta, Eleonora; El Harrak, Zakaria; Nizard, Philippe; Baret, Jean-Christophe; Taly, Valérie

2017-05-02

Droplet-based microfluidics is extensively and increasingly used for high-throughput single-cell studies. However, the accuracy of the cell counting method directly impacts the robustness of such studies. We describe here a simple and precise method to accurately count a large number of adherent and non-adherent human cells as well as bacteria. Our microfluidic hemocytometer provides statistically relevant data on large populations of cells at a high-throughput, used to characterize cell encapsulation and cell viability during incubation in droplets.

Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model

NASA Astrophysics Data System (ADS)

Mondal, Sudip; Hegarty, Evan; Martin, Chris; Gökçe, Sertan Kutal; Ghorashian, Navid; Ben-Yakar, Adela

2016-10-01

Next generation drug screening could benefit greatly from in vivo studies, using small animal models such as Caenorhabditis elegans for hit identification and lead optimization. Current in vivo assays can operate either at low throughput with high resolution or with low resolution at high throughput. To enable both high-throughput and high-resolution imaging of C. elegans, we developed an automated microfluidic platform. This platform can image 15 z-stacks of ~4,000 C. elegans from 96 different populations using a large-scale chip with a micron resolution in 16 min. Using this platform, we screened ~100,000 animals of the poly-glutamine aggregation model on 25 chips. We tested the efficacy of ~1,000 FDA-approved drugs in improving the aggregation phenotype of the model and identified four confirmed hits. This robust platform now enables high-content screening of various C. elegans disease models at the speed and cost of in vitro cell-based assays.

Toward a Low-Cost System for High-Throughput Image-Based Phenotyping of Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Schneider, D. J.; Cheng, H.; Shaw, N.; Kochian, L. V.; Shaff, J. E.

2015-12-01

Root system architecture is being studied more closely for improved nutrient acquisition, stress tolerance and carbon sequestration by relating the genetic material that corresponds to preferential physical features. This information can help direct plant breeders in addressing the growing concerns regarding the global demand on crops and fossil fuels. To help support this incentive comes a need to make high-throughput image-based phenotyping of plant roots, at the individual plant scale, simpler and more affordable. Our goal is to create an affordable and portable product for simple image collection, processing and management that will extend root phenotyping to institutions with limited funding (e.g., in developing countries). Thus, a new integrated system has been developed using the Raspberry Pi single-board computer. Similar to other 3D-based imaging platforms, the system utilizes a stationary camera to photograph a rotating crop root system (e.g., rice, maize or sorghum) that is suspended either in a gel or on a mesh (for hydroponics). In contrast, the new design takes advantage of powerful open-source hardware and software to reduce the system costs, simplify the imaging process, and manage the large datasets produced by the high-resolution photographs. A newly designed graphical user interface (GUI) unifies the system controls (e.g., adjusting camera and motor settings and orchestrating the motor motion with image capture), making it easier to accommodate a variety of experiments. During each imaging session, integral metadata necessary for reproducing experiment results are collected (e.g., plant type and age, growing conditions and treatments, camera settings) using hierarchical data format files. These metadata are searchable within the GUI and can be selected and extracted for further analysis. The GUI also supports an image previewer that performs limited image processing (e.g., thresholding and cropping). Root skeletonization, 3D reconstruction and

High-Throughput Toxicity Testing: New Strategies for ...

EPA Pesticide Factsheets

In recent years, the food industry has made progress in improving safety testing methods focused on microbial contaminants in order to promote food safety. However, food industry toxicologists must also assess the safety of food-relevant chemicals including pesticides, direct additives, and food contact substances. With the rapidly growing use of new food additives, as well as innovation in food contact substance development, an interest in exploring the use of high-throughput chemical safety testing approaches has emerged. Currently, the field of toxicology is undergoing a paradigm shift in how chemical hazards can be evaluated. Since there are tens of thousands of chemicals in use, many of which have little to no hazard information and there are limited resources (namely time and money) for testing these chemicals, it is necessary to prioritize which chemicals require further safety testing to better protect human health. Advances in biochemistry and computational toxicology have paved the way for animal-free (in vitro) high-throughput screening which can characterize chemical interactions with highly specific biological processes. Screening approaches are not novel; in fact, quantitative high-throughput screening (qHTS) methods that incorporate dose-response evaluation have been widely used in the pharmaceutical industry. For toxicological evaluation and prioritization, it is the throughput as well as the cost- and time-efficient nature of qHTS that makes it

Advanced phenotyping and phenotype data analysis for the study of plant growth and development

PubMed Central

Rahaman, Md. Matiur; Chen, Dijun; Gillani, Zeeshan; Klukas, Christian; Chen, Ming

2015-01-01

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis. PMID:26322060

Advanced phenotyping and phenotype data analysis for the study of plant growth and development.

PubMed

Rahaman, Md Matiur; Chen, Dijun; Gillani, Zeeshan; Klukas, Christian; Chen, Ming

2015-01-01

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

High-Throughput Identification of Loss-of-Function Mutations for Anti-Interferon Activity in the Influenza A Virus NS Segment

PubMed Central

Wu, Nicholas C.; Young, Arthur P.; Al-Mawsawi, Laith Q.; Olson, C. Anders; Feng, Jun; Qi, Hangfei; Luan, Harding H.; Li, Xinmin; Wu, Ting-Ting

2014-01-01

ABSTRACT Viral proteins often display several functions which require multiple assays to dissect their genetic basis. Here, we describe a systematic approach to screen for loss-of-function mutations that confer a fitness disadvantage under a specified growth condition. Our methodology was achieved by genetically monitoring a mutant library under two growth conditions, with and without interferon, by deep sequencing. We employed a molecular tagging technique to distinguish true mutations from sequencing error. This approach enabled us to identify mutations that were negatively selected against, in addition to those that were positively selected for. Using this technique, we identified loss-of-function mutations in the influenza A virus NS segment that were sensitive to type I interferon in a high-throughput fashion. Mechanistic characterization further showed that a single substitution, D92Y, resulted in the inability of NS to inhibit RIG-I ubiquitination. The approach described in this study can be applied under any specified condition for any virus that can be genetically manipulated. IMPORTANCE Traditional genetics focuses on a single genotype-phenotype relationship, whereas high-throughput genetics permits phenotypic characterization of numerous mutants in parallel. High-throughput genetics often involves monitoring of a mutant library with deep sequencing. However, deep sequencing suffers from a high error rate (∼0.1 to 1%), which is usually higher than the occurrence frequency for individual point mutations within a mutant library. Therefore, only mutations that confer a fitness advantage can be identified with confidence due to an enrichment in the occurrence frequency. In contrast, it is impossible to identify deleterious mutations using most next-generation sequencing techniques. In this study, we have applied a molecular tagging technique to distinguish true mutations from sequencing errors. It enabled us to identify mutations that underwent negative

Breeding to adapt agriculture to climate change: affordable phenotyping solutions.

PubMed

Araus, José L; Kefauver, Shawn C

2018-05-28

Breeding is one of the central pillars of adaptation of crops to climate change. However, phenotyping is a key bottleneck that is limiting breeding efficiency. The awareness of phenotyping as a breeding limitation is not only sustained by the lack of adequate approaches, but also by the perception that phenotyping is an expensive activity. Phenotyping is not just dependent on the choice of appropriate traits and tools (e.g. sensors) but relies on how these tools are deployed on their carrying platforms, the speed and volume of data extraction and analysis (throughput), the handling of spatial variability and characterization of environmental conditions, and finally how all the information is integrated and processed. Affordable high throughput phenotyping aims to achieve reasonably priced solutions for all the components comprising the phenotyping pipeline. This mini-review will cover current and imminent solutions for all these components, from the increasing use of conventional digital RGB cameras, within the category of sensors, to open-access cloud-structured data processing and the use of smartphones. Emphasis will be placed on field phenotyping, which is really the main application for day-to-day phenotyping. Copyright © 2018 Elsevier Ltd. All rights reserved.

Phenotypic Characterization of Toxic Compound Effects on Liver Spheroids Derived from iPSC Using Confocal Imaging and Three-Dimensional Image Analysis.

PubMed

Sirenko, Oksana; Hancock, Michael K; Hesley, Jayne; Hong, Dihui; Cohen, Avrum; Gentry, Jason; Carlson, Coby B; Mann, David A

2016-09-01

Cell models are becoming more complex to better mimic the in vivo environment and provide greater predictivity for compound efficacy and toxicity. There is an increasing interest in exploring the use of three-dimensional (3D) spheroids for modeling developmental and tissue biology with the goal of accelerating translational research in these areas. Accordingly, the development of high-throughput quantitative assays using 3D cultures is an active area of investigation. In this study, we have developed and optimized methods for the formation of 3D liver spheroids derived from human iPS cells and used those for toxicity assessment. We used confocal imaging and 3D image analysis to characterize cellular information from a 3D matrix to enable a multi-parametric comparison of different spheroid phenotypes. The assay enables characterization of compound toxicities by spheroid size (volume) and shape, cell number and spatial distribution, nuclear characterization, number and distribution of cells expressing viability, apoptosis, mitochondrial potential, and viability marker intensities. In addition, changes in the content of live, dead, and apoptotic cells as a consequence of compound exposure were characterized. We tested 48 compounds and compared induced pluripotent stem cell (iPSC)-derived hepatocytes and HepG2 cells in both two-dimensional (2D) and 3D cultures. We observed significant differences in the pharmacological effects of compounds across the two cell types and between the different culture conditions. Our results indicate that a phenotypic assay using 3D model systems formed with human iPSC-derived hepatocytes is suitable for high-throughput screening and can be used for hepatotoxicity assessment in vitro.

High Throughput Assays for Exposure Science (NIEHS OHAT ...

EPA Pesticide Factsheets

High throughput screening (HTS) data that characterize chemically induced biological activity have been generated for thousands of chemicals by the US interagency Tox21 and the US EPA ToxCast programs. In many cases there are no data available for comparing bioactivity from HTS with relevant human exposures. The EPA’s ExpoCast program is developing high-throughput approaches to generate the needed exposure estimates using existing databases and new, high-throughput measurements. The exposure pathway (i.e., the route of chemical from manufacture to human intake) significantly impacts the level of exposure. The presence, concentration, and formulation of chemicals in consumer products and articles of commerce (e.g., clothing) can therefore provide critical information for estimating risk. We have found that there are only limited data available on the chemical constituents (e.g., flame retardants, plasticizers) within most articles of commerce. Furthermore, the presence of some chemicals in otherwise well characterized products may be due to product packaging. We are analyzing sample consumer products using 2D gas chromatograph (GC) x GC Time of Flight Mass Spectrometry (GCxGCTOF/MS), which is suited for forensic investigation of chemicals in complex matrices (including toys, cleaners, and food). In parallel, we are working to create a reference library of retention times and spectral information for the entire Tox21 chemical library. In an examination of five p

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

PubMed

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.

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

ScienceCinema

Gore, Brooklin

2018-02-01

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

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

PubMed

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Chlorophyll fluorescence is a rigorous, high throughput tool to analyze the impacts of genotype, species, and stress on plant and ecosystem productivity

NASA Astrophysics Data System (ADS)

Ewers, B. E.; Pleban, J. R.; Aston, T.; Beverly, D.; Speckman, H. N.; Hosseini, A.; Bretfeld, M.; Edwards, C.; Yarkhunova, Y.; Weinig, C.; Mackay, D. S.

2017-12-01

Abiotic and biotic stresses reduce plant productivity, yet high-throughput characterization of plant responses across genotypes, species and stress conditions are limited by both instrumentation and data analysis techniques. Recent developments in chlorophyll a fluorescence measurement at leaf to landscape scales could improve our predictive understanding of plants response to stressors. We analyzed the interaction of species and stress across two crop types, five gymnosperm and two angiosperm tree species from boreal and montane forests, grasses, forbs and shrubs from sagebrush steppe, and 30 tree species from seasonally wet tropical forest. We also analyzed chlorophyll fluorescence and gas exchange data from twelve Brassica rapa crop accessions and 120 recombinant inbred lines to investigate phenotypic responses to drought. These data represent more than 10,000 measurements of fluorescence and allow us to answer two questions 1) are the measurements from high-throughput, hand held and drone-mounted instruments quantitatively similar to lower throughput camera and gas exchange mounted instruments and 2) do the measurements find differences in genotypic, species and environmental stress on plants? We found through regression that the high and low throughput instruments agreed across both individual chlorophyll fluorescence components and calculated ratios and were not different from a 1:1 relationship with correlation greater than 0.9. We used hierarchical Bayesian modeling to test the second question. We found a linear relationship between the fluorescence-derived quantum yield of PSII and the quantum yield of CO2 assimilation from gas-exchange, with a slope of ca. 0.1 indicating that the efficiency of the entire photosynthetic process was about 10% of PSII across genotypes, species and drought stress. Posterior estimates of quantum yield revealed that drought-treatment, genotype and species differences were preserved when accounting for measurement uncertainty

Characterization of a new apple luteovirus identified by high-throughput sequencing.

PubMed

Liu, Huawei; Wu, Liping; Nikolaeva, Ekaterina; Peter, Kari; Liu, Zongrang; Mollov, Dimitre; Cao, Mengji; Li, Ruhui

2018-05-15

'Rapid Apple Decline' (RAD) is a newly emerging problem of young, dwarf apple trees in the Northeastern USA. The affected trees show trunk necrosis, cracking and canker before collapse in summer. In this study, we discovered and characterized a new luteovirus from apple trees in RAD-affected orchards using high-throughput sequencing (HTS) technology and subsequent Sanger sequencing. Illumina NextSeq sequencing was applied to total RNAs prepared from three diseased apple trees. Sequence reads were de novo assembled, and contigs were annotated by BLASTx. RT-PCR and 5'/3' RACE sequencing were used to obtain the complete genome of a new virus. RT-PCR was used to detect the virus. Three common apple viruses and a new luteovirus were identified from the diseased trees by HTS and RT-PCR. Sequence analyses of the complete genome of the new virus show that it is a new species of the genus Luteovirus in the family Luteoviridae. The virus is graft transmissible and detected by RT-PCR in apple trees in a couple of orchards. A new luteovirus and/or three known viruses were found to be associated with RAD. Molecular characterization of the new luteovirus provides important information for further investigation of its distribution and etiological role.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

PubMed

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z -value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values ( H 2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable ( H 2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates

PubMed Central

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z-value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values (H2> 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable (H2> 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed. PMID:29230229

Characterizing visible and invisible cell wall mutant phenotypes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carpita, Nicholas C.; McCann, Maureen C.

2015-04-06

About 10% of a plant's genome is devoted to generating the protein machinery to synthesize, remodel, and deconstruct the cell wall. High-throughput genome sequencing technologies have enabled a reasonably complete inventory of wall-related genes that can be assembled into families of common evolutionary origin. Assigning function to each gene family member has been aided immensely by identification of mutants with visible phenotypes or by chemical and spectroscopic analysis of mutants with ‘invisible’ phenotypes of modified cell wall composition and architecture that do not otherwise affect plant growth or development. This review connects the inference of gene function on the basismore » of deviation from the wild type in genetic functional analyses to insights provided by modern analytical techniques that have brought us ever closer to elucidating the sequence structures of the major polysaccharide components of the plant cell wall.« less

High-Throughput, Motility-Based Sorter for Microswimmers such as C. elegans

PubMed Central

Yuan, Jinzhou; Zhou, Jessie; Raizen, David M.; Bau, Haim H.

2015-01-01

Animal motility varies with genotype, disease, aging, and environmental conditions. In many studies, it is desirable to carry out high throughput motility-based sorting to isolate rare animals for, among other things, forward genetic screens to identify genetic pathways that regulate phenotypes of interest. Many commonly used screening processes are labor-intensive, lack sensitivity, and require extensive investigator training. Here, we describe a sensitive, high throughput, automated, motility-based method for sorting nematodes. Our method is implemented in a simple microfluidic device capable of sorting thousands of animals per hour per module, and is amenable to parallelism. The device successfully enriches for known C. elegans motility mutants. Furthermore, using this device, we isolate low-abundance mutants capable of suppressing the somnogenic effects of the flp-13 gene, which regulates C. elegans sleep. By performing genetic complementation tests, we demonstrate that our motility-based sorting device efficiently isolates mutants for the same gene identified by tedious visual inspection of behavior on an agar surface. Therefore, our motility-based sorter is capable of performing high throughput gene discovery approaches to investigate fundamental biological processes. PMID:26008643

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

PubMed

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.

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms

PubMed Central

Elhadad, N.; Claassen, J.; Perotte, R.; Goldstein, A.; Hripcsak, G.

2018-01-01

We study the question of how to represent or summarize raw laboratory data taken from an electronic health record (EHR) using parametric model selection to reduce or cope with biases induced through clinical care. It has been previously demonstrated that the health care process (Hripcsak and Albers, 2012, 2013), as defined by measurement context (Hripcsak and Albers, 2013; Albers et al., 2012) and measurement patterns (Albers and Hripcsak, 2010, 2012), can influence how EHR data are distributed statistically (Kohane and Weber, 2013; Pivovarov et al., 2014). We construct an algorithm, PopKLD, which is based on information criterion model selection (Burnham and Anderson, 2002; Claeskens and Hjort, 2008), is intended to reduce and cope with health care process biases and to produce an intuitively understandable continuous summary. The PopKLD algorithm can be automated and is designed to be applicable in high-throughput settings; for example, the output of the PopKLD algorithm can be used as input for phenotyping algorithms. Moreover, we develop the PopKLD-CAT algorithm that transforms the continuous PopKLD summary into a categorical summary useful for applications that require categorical data such as topic modeling. We evaluate our methodology in two ways. First, we apply the method to laboratory data collected in two different health care contexts, primary versus intensive care. We show that the PopKLD preserves known physiologic features in the data that are lost when summarizing the data using more common laboratory data summaries such as mean and standard deviation. Second, for three disease-laboratory measurement pairs, we perform a phenotyping task: we use the PopKLD and PopKLD-CAT algorithms to define high and low values of the laboratory variable that are used for defining a disease state. We then compare the relationship between the PopKLD-CAT summary disease predictions and the same predictions using empirically estimated mean and standard deviation to a

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.

PubMed

Albers, D J; Elhadad, N; Claassen, J; Perotte, R; Goldstein, A; Hripcsak, G

2018-02-01

We study the question of how to represent or summarize raw laboratory data taken from an electronic health record (EHR) using parametric model selection to reduce or cope with biases induced through clinical care. It has been previously demonstrated that the health care process (Hripcsak and Albers, 2012, 2013), as defined by measurement context (Hripcsak and Albers, 2013; Albers et al., 2012) and measurement patterns (Albers and Hripcsak, 2010, 2012), can influence how EHR data are distributed statistically (Kohane and Weber, 2013; Pivovarov et al., 2014). We construct an algorithm, PopKLD, which is based on information criterion model selection (Burnham and Anderson, 2002; Claeskens and Hjort, 2008), is intended to reduce and cope with health care process biases and to produce an intuitively understandable continuous summary. The PopKLD algorithm can be automated and is designed to be applicable in high-throughput settings; for example, the output of the PopKLD algorithm can be used as input for phenotyping algorithms. Moreover, we develop the PopKLD-CAT algorithm that transforms the continuous PopKLD summary into a categorical summary useful for applications that require categorical data such as topic modeling. We evaluate our methodology in two ways. First, we apply the method to laboratory data collected in two different health care contexts, primary versus intensive care. We show that the PopKLD preserves known physiologic features in the data that are lost when summarizing the data using more common laboratory data summaries such as mean and standard deviation. Second, for three disease-laboratory measurement pairs, we perform a phenotyping task: we use the PopKLD and PopKLD-CAT algorithms to define high and low values of the laboratory variable that are used for defining a disease state. We then compare the relationship between the PopKLD-CAT summary disease predictions and the same predictions using empirically estimated mean and standard deviation to a

Validation and implementation of a novel high-throughput behavioral phenotyping instrument for mice

PubMed Central

Brodkin, Jesse; Frank, Dana; Grippo, Ryan; Hausfater, Michal; Gulinello, Maria; Achterholt, Nils; Gutzen, Christian

2015-01-01

Background Behavioral assessment of mutant mouse models and novel candidate drugs is a slow and labor intensive process. This limitation produces a significant impediment to CNS drug discovery. New method By combining video and vibration analysis we created an automated system that provides the most detailed description of mouse behavior available. Our system (The Behavioral Spectrometer) allowed for the rapid assessment of behavioral abnormalities in the BTBR model of Autism, the restraint model of stress and the irritant model of inflammatory pain. Results We found that each model produced a unique alteration of the spectrum of behavior emitted by the mice. BTBR mice engaged in more grooming and less rearing behaviors. Prior restraint stress produced dramatic increases in grooming activity at the expense of locomotor behavior. Pain produced profound decreases in emitted behavior that were reversible with analgesic treatment. Comparison with existing method(s) We evaluated our system through a direct comparison on the same subjects with the current “gold standard” of human observation of video recordings. Using the same mice evaluated over the same range of behaviors, the Behavioral Spectrometer produced a quantitative categorization of behavior that was highly correlated with the scores produced by trained human observers (r=0.97). Conclusions Our results show that this new system is a highly valid and sensitive method to characterize behavioral effects in mice. As a fully automated and easily scalable instrument the Behavioral Spectrometer represents a high-throughput behavioral tool that reduces the time and labor involved in behavioral research. PMID:24384067

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets

PubMed Central

Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.

2017-01-01

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787

High Throughput Assays and Exposure Science (ISES annual meeting)

EPA Science Inventory

High throughput screening (HTS) data characterizing chemical-induced biological activity has been generated for thousands of environmentally-relevant chemicals by the US inter-agency Tox21 and the US EPA ToxCast programs. For a limited set of chemicals, bioactive concentrations r...

An Automated High-throughput Array Microscope for Cancer Cell Mechanics

NASA Astrophysics Data System (ADS)

Cribb, Jeremy A.; Osborne, Lukas D.; Beicker, Kellie; Psioda, Matthew; Chen, Jian; O'Brien, E. Timothy; Taylor, Russell M., II; Vicci, Leandra; Hsiao, Joe Ping-Lin; Shao, Chong; Falvo, Michael; Ibrahim, Joseph G.; Wood, Kris C.; Blobe, Gerard C.; Superfine, Richard

2016-06-01

Changes in cellular mechanical properties correlate with the progression of metastatic cancer along the epithelial-to-mesenchymal transition (EMT). Few high-throughput methodologies exist that measure cell compliance, which can be used to understand the impact of genetic alterations or to screen the efficacy of chemotherapeutic agents. We have developed a novel array high-throughput microscope (AHTM) system that combines the convenience of the standard 96-well plate with the ability to image cultured cells and membrane-bound microbeads in twelve independently-focusing channels simultaneously, visiting all wells in eight steps. We use the AHTM and passive bead rheology techniques to determine the relative compliance of human pancreatic ductal epithelial (HPDE) cells, h-TERT transformed HPDE cells (HPNE), and four gain-of-function constructs related to EMT. The AHTM found HPNE, H-ras, Myr-AKT, and Bcl2 transfected cells more compliant relative to controls, consistent with parallel tests using atomic force microscopy and invasion assays, proving the AHTM capable of screening for changes in mechanical phenotype.

Characterization of matrix effects in developing rugged high-throughput LC-MS/MS methods for bioanalysis.

PubMed

Li, Fumin; Wang, Jun; Jenkins, Rand

2016-05-01

There is an ever-increasing demand for high-throughput LC-MS/MS bioanalytical assays to support drug discovery and development. Matrix effects of sofosbuvir (protonated) and paclitaxel (sodiated) were thoroughly evaluated using high-throughput chromatography (defined as having a run time ≤1 min) under 14 elution conditions with extracts from protein precipitation, liquid-liquid extraction and solid-phase extraction. A slight separation, in terms of retention time, between underlying matrix components and sofosbuvir/paclitaxel can greatly alleviate matrix effects. High-throughput chromatography, with proper optimization, can provide rapid and effective chromatographic separation under 1 min to alleviate matrix effects and enhance assay ruggedness for regulated bioanalysis.

Automated phenotype pattern recognition of zebrafish for high-throughput screening.

PubMed

Schutera, Mark; Dickmeis, Thomas; Mione, Marina; Peravali, Ravindra; Marcato, Daniel; Reischl, Markus; Mikut, Ralf; Pylatiuk, Christian

2016-07-03

Over the last years, the zebrafish (Danio rerio) has become a key model organism in genetic and chemical screenings. A growing number of experiments and an expanding interest in zebrafish research makes it increasingly essential to automatize the distribution of embryos and larvae into standard microtiter plates or other sample holders for screening, often according to phenotypical features. Until now, such sorting processes have been carried out by manually handling the larvae and manual feature detection. Here, a prototype platform for image acquisition together with a classification software is presented. Zebrafish embryos and larvae and their features such as pigmentation are detected automatically from the image. Zebrafish of 4 different phenotypes can be classified through pattern recognition at 72 h post fertilization (hpf), allowing the software to classify an embryo into 2 distinct phenotypic classes: wild-type versus variant. The zebrafish phenotypes are classified with an accuracy of 79-99% without any user interaction. A description of the prototype platform and of the algorithms for image processing and pattern recognition is presented.

Identifying apicoplast-targeting antimalarials using high-throughput compatible approaches

PubMed Central

Ekland, Eric H.; Schneider, Jessica; Fidock, David A.

2011-01-01

Malarial parasites have evolved resistance to all previously used therapies, and recent evidence suggests emerging resistance to the first-line artemisinins. To identify antimalarials with novel mechanisms of action, we have developed a high-throughput screen targeting the apicoplast organelle of Plasmodium falciparum. Antibiotics known to interfere with this organelle, such as azithromycin, exhibit an unusual phenotype whereby the progeny of drug-treated parasites die. Our screen exploits this phenomenon by assaying for “delayed death” compounds that exhibit a higher potency after two cycles of intraerythrocytic development compared to one. We report a primary assay employing parasites with an integrated copy of a firefly luciferase reporter gene and a secondary flow cytometry-based assay using a nucleic acid stain paired with a mitochondrial vital dye. Screening of the U.S. National Institutes of Health Clinical Collection identified known and novel antimalarials including kitasamycin. This inexpensive macrolide, used for agricultural applications, exhibited an in vitro IC50 in the 50 nM range, comparable to the 30 nM activity of our control drug, azithromycin. Imaging and pharmacologic studies confirmed kitasamycin action against the apicoplast, and in vivo activity was observed in a murine malaria model. These assays provide the foundation for high-throughput campaigns to identify novel chemotypes for combination therapies to treat multidrug-resistant malaria.—Ekland, E. H., Schneider, J., Fidock, D. A. Identifying apicoplast-targeting antimalarials using high-throughput compatible approaches. PMID:21746861

High Throughput Experimental Materials Database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zakutayev, Andriy; Perkins, John; Schwarting, Marcus

The mission of the High Throughput Experimental Materials Database (HTEM DB) is to enable discovery of new materials with useful properties by releasing large amounts of high-quality experimental data to public. The HTEM DB contains information about materials obtained from high-throughput experiments at the National Renewable Energy Laboratory (NREL).

Automatic Segmentation of High-Throughput RNAi Fluorescent Cellular Images

PubMed Central

Yan, Pingkum; Zhou, Xiaobo; Shah, Mubarak; Wong, Stephen T. C.

2010-01-01

High-throughput genome-wide RNA interference (RNAi) screening is emerging as an essential tool to assist biologists in understanding complex cellular processes. The large number of images produced in each study make manual analysis intractable; hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. In this paper, a fully automatic method for segmentation of cells from genome-wide RNAi screening images is proposed. Nuclei are first extracted from the DNA channel by using a modified watershed algorithm. Cells are then extracted by modeling the interaction between them as well as combining both gradient and region information in the Actin and Rac channels. A new energy functional is formulated based on a novel interaction model for segmenting tightly clustered cells with significant intensity variance and specific phenotypes. The energy functional is minimized by using a multiphase level set method, which leads to a highly effective cell segmentation method. Promising experimental results demonstrate that automatic segmentation of high-throughput genome-wide multichannel screening can be achieved by using the proposed method, which may also be extended to other multichannel image segmentation problems. PMID:18270043

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

PubMed

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.

Evaluation of High-Throughput Chemical Exposure Models ...

EPA Pesticide Factsheets

The U.S. EPA, under its ExpoCast program, is developing high-throughput near-field modeling methods to estimate human chemical exposure and to provide real-world context to high-throughput screening (HTS) hazard data. These novel modeling methods include reverse methods to infer parent chemical exposures from biomonitoring measurements and forward models to predict multi-pathway exposures from chemical use information and/or residential media concentrations. Here, both forward and reverse modeling methods are used to characterize the relationship between matched near-field environmental (air and dust) and biomarker measurements. Indoor air, house dust, and urine samples from a sample of 120 females (aged 60 to 80 years) were analyzed. In the measured data, 78% of the residential media measurements (across 80 chemicals) and 54% of the urine measurements (across 21 chemicals) were censored, i.e. below the limit of quantification (LOQ). Because of the degree of censoring, we applied a Bayesian approach to impute censored values for 69 chemicals having at least 15% of measurements above LOQ. This resulted in 10 chemicals (5 phthalates, 5 pesticides) with matched air, dust, and urine metabolite measurements. The population medians of indoor air and dust concentrations were compared to population median exposures inferred from urine metabolites concentrations using a high-throughput reverse-dosimetry approach. Median air and dust concentrations were found to be correl

High-Throughput Block Optical DNA Sequence Identification.

PubMed

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.

Development of a High-Throughput Ion-Exchange Resin Characterization Workflow.

PubMed

Liu, Chun; Dermody, Daniel; Harris, Keith; Boomgaard, Thomas; Sweeney, Jeff; Gisch, Daryl; Goltz, Bob

2017-06-12

A novel high-throughout (HTR) ion-exchange (IEX) resin workflow has been developed for characterizing ion exchange equilibrium of commercial and experimental IEX resins against a range of different applications where water environment differs from site to site. Because of its much higher throughput, design of experiment (DOE) methodology can be easily applied for studying the effects of multiple factors on resin performance. Two case studies will be presented to illustrate the efficacy of the combined HTR workflow and DOE method. In case study one, a series of anion exchange resins have been screened for selective removal of NO 3 - and NO 2 - in water environments consisting of multiple other anions, varied pH, and ionic strength. The response surface model (RSM) is developed to statistically correlate the resin performance with the water composition and predict the best resin candidate. In case study two, the same HTR workflow and DOE method have been applied for screening different cation exchange resins in terms of the selective removal of Mg 2+ , Ca 2+ , and Ba 2+ from high total dissolved salt (TDS) water. A master DOE model including all of the cation exchange resins is created to predict divalent cation removal by different IEX resins under specific conditions, from which the best resin candidates can be identified. The successful adoption of HTR workflow and DOE method for studying the ion exchange of IEX resins can significantly reduce the resources and time to address industry and application needs.

High-throughput cloning and expression library creation for functional proteomics.

PubMed

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

2013-05-01

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 particularly 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 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(TM) 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). © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microarray-based mutation detection and phenotypic characterization in Korean patients with retinitis pigmentosa

PubMed Central

Kim, Cinoo; Kim, Kwang Joong; Bok, Jeong; Lee, Eun-Ju; Kim, Dong-Joon; Oh, Ji Hee; Park, Sung Pyo; Shin, Joo Young; Lee, Jong-Young

2012-01-01

Purpose To evaluate microarray-based genotyping technology for the detection of mutations responsible for retinitis pigmentosa (RP) and to perform phenotypic characterization of patients with pathogenic mutations. Methods DNA from 336 patients with RP and 360 controls was analyzed using the GoldenGate assay with microbeads containing 95 previously reported disease-associated mutations from 28 RP genes. Mutations identified by microarray-based genotyping were confirmed by direct sequencing. Segregation analysis and phenotypic characterization were performed in patients with mutations. The disease severity was assessed by visual acuity, electroretinography, optical coherence tomography, and kinetic perimetry. Results Ten RP-related mutations of five RP genes (PRP3 pre-mRNA processing factor 3 homolog [PRPF3], rhodopsin [RHO], phosphodiesterase 6B [PDE6B], peripherin 2 [PRPH2], and retinitis pigmentosa 1 [RP1]) were identified in 26 of the 336 patients (7.7%) and in six of the 360 controls (1.7%). The p.H557Y mutation in PDE6B, which was homozygous in four patients and heterozygous in nine patients, was the most frequent mutation (2.5%). Mutation segregation was assessed in four families. Among the patients with missense mutations, the most severe phenotype occurred in patients with p.D984G in RP1; less severe phenotypes occurred in patients with p.R135W in RHO; a relatively moderate phenotype occurred in patients with p.T494M in PRPF3, p.H557Y in PDE6B, or p.W316G in PRPH2; and a mild phenotype was seen in a patient with p.D190N in RHO. Conclusions The results reveal that the GoldenGate assay may not be an efficient method for molecular diagnosis in RP patients with rare mutations, although it has proven to be reliable and efficient for high-throughput genotyping of single-nucleotide polymorphisms. The clinical features varied according to the mutations. Continuous effort to identify novel RP genes and mutations in a population is needed to improve the efficiency and

High-Throughput Experimental Approach Capabilities | Materials Science |

Science.gov Websites

NREL High-Throughput Experimental Approach Capabilities High-Throughput Experimental Approach by yellow and is for materials in the upper right sector. NREL's high-throughput experimental ,Te) and oxysulfide sputtering Combi-5: Nitrides and oxynitride sputtering We also have several non

High-Throughput, Motility-Based Sorter for Microswimmers and Gene Discovery Platform

NASA Astrophysics Data System (ADS)

Yuan, Jinzhou; Raizen, David; Bau, Haim

2015-11-01

Animal motility varies with genotype, disease progression, aging, and environmental conditions. In many studies, it is desirable to carry out high throughput motility-based sorting to isolate rare animals for, among other things, forward genetic screens to identify genetic pathways that regulate phenotypes of interest. Many commonly used screening processes are labor-intensive, lack sensitivity, and require extensive investigator training. Here, we describe a sensitive, high throughput, automated, motility-based method for sorting nematodes. Our method was implemented in a simple microfluidic device capable of sorting many thousands of animals per hour per module, and is amenable to parallelism. The device successfully enriched for known C. elegans motility mutants. Furthermore, using this device, we isolated low-abundance mutants capable of suppressing the somnogenic effects of the flp-13 gene, which regulates sleep-like quiescence in C. elegans. Subsequent genomic sequencing led to the identification of a flp-13-suppressor gene. This research was supported, in part, by NIH NIA Grant 5R03AG042690-02.

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

PubMed Central

Usui, Takuji; Noble, Daniel W.A.; O’Dea, Rose E.; Fangmeier, Melissa L.; Lagisz, Malgorzata; Hesselson, Daniel

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. PMID:29372124

Perspective: Composition–structure–property mapping in high-throughput experiments: Turning data into knowledge

DOE PAGES

Hattrick-Simpers, Jason R.; Gregoire, John M.; Kusne, A. Gilad

2016-05-26

With their ability to rapidly elucidate composition-structure-property relationships, high-throughput experimental studies have revolutionized how materials are discovered, optimized, and commercialized. It is now possible to synthesize and characterize high-throughput libraries that systematically address thousands of individual cuts of fabrication parameter space. An unresolved issue remains transforming structural characterization data into phase mappings. This difficulty is related to the complex information present in diffraction and spectroscopic data and its variation with composition and processing. Here, we review the field of automated phase diagram attribution and discuss the impact that emerging computational approaches will have in the generation of phase diagrams andmore » beyond.« less

[Genotype/phenotype correlation in autism: genetic models and phenotypic characterization].

PubMed

Bonnet-Brilhault, F

2011-02-01

Autism spectrum disorders are a class of conditions categorized by communication problems, ritualistic behaviors, and deficits in social behaviors. This class of disorders merges a heterogeneous group of neurodevelopmental disorders regarding some phenotypic and probably physiopathological aspects. Genetic basis is well admitted, however, considering phenotypic and genotypic heterogeneity, correspondences between genotype and phenotype have yet to be established. To better identify such correspondences, genetic models have to be identified and phenotypic markers have to be characterized. Recent insights show that a variety of genetic mechanisms may be involved in autism spectrum disorders, i.e. single gene disorders, copy number variations and polygenic mechanisms. These current genetic models are described. Regarding clinical aspects, several approaches can be used in genetic studies. Nosographical approach, especially with the concept of autism spectrum disorders, merges a large group of disorders with clinical heterogeneity and may fail to identify clear genotype/phenotype correlations. Dimensional approach referred in genetic studies to the notion of "Broad Autism Phenotype" related to a constellation of language, personality, and social-behavioral features present in relatives that mirror the symptom domains of autism, but are much milder in expression. Studies of this broad autism phenotype may provide a potentially important complementary approach for detecting the genes involved in these domains. However, control population used in those studies need to be well characterized too. Identification of endophenotypes seems to offer more promising results. Endophenotypes, which are supposed to be more proximal markers of gene action in the same biological pathway, linking genes and complex clinical symptoms, are thought to be less genetically complex than the broader disease phenotype, indexing a limited aspect of genetic risk for the disorder as a whole. However

Clinical validation of an ultra high-throughput spiral microfluidics for the detection and enrichment of viable circulating tumor cells.

PubMed

Khoo, Bee Luan; Warkiani, Majid Ebrahimi; Tan, Daniel Shao-Weng; Bhagat, Ali Asgar S; Irwin, Darryl; Lau, Dawn Pingxi; Lim, Alvin S T; Lim, Kiat Hon; Krisna, Sai Sakktee; Lim, Wan-Teck; Yap, Yoon Sim; Lee, Soo Chin; Soo, Ross A; Han, Jongyoon; Lim, Chwee Teck

2014-01-01

Circulating tumor cells (CTCs) are cancer cells that can be isolated via liquid biopsy from blood and can be phenotypically and genetically characterized to provide critical information for guiding cancer treatment. Current analysis of CTCs is hindered by the throughput, selectivity and specificity of devices or assays used in CTC detection and isolation. Here, we enriched and characterized putative CTCs from blood samples of patients with both advanced stage metastatic breast and lung cancers using a novel multiplexed spiral microfluidic chip. This system detected putative CTCs under high sensitivity (100%, n = 56) (Breast cancer samples: 12-1275 CTCs/ml; Lung cancer samples: 10-1535 CTCs/ml) rapidly from clinically relevant blood volumes (7.5 ml under 5 min). Blood samples were completely separated into plasma, CTCs and PBMCs components and each fraction were characterized with immunophenotyping (Pan-cytokeratin/CD45, CD44/CD24, EpCAM), fluorescence in-situ hybridization (FISH) (EML4-ALK) or targeted somatic mutation analysis. We used an ultra-sensitive mass spectrometry based system to highlight the presence of an EGFR-activating mutation in both isolated CTCs and plasma cell-free DNA (cf-DNA), and demonstrate concordance with the original tumor-biopsy samples. We have clinically validated our multiplexed microfluidic chip for the ultra high-throughput, low-cost and label-free enrichment of CTCs. Retrieved cells were unlabeled and viable, enabling potential propagation and real-time downstream analysis using next generation sequencing (NGS) or proteomic analysis.

High-throughput characterization of stresses in thin film materials libraries using Si cantilever array wafers and digital holographic microscopy.

PubMed

Lai, Y W; Hamann, S; Ehmann, M; Ludwig, A

2011-06-01

We report the development of an advanced high-throughput stress characterization method for thin film materials libraries sputter-deposited on micro-machined cantilever arrays consisting of around 1500 cantilevers on 4-inch silicon-on-insulator wafers. A low-cost custom-designed digital holographic microscope (DHM) is employed to simultaneously monitor the thin film thickness, the surface topography and the curvature of each of the cantilevers before and after deposition. The variation in stress state across the thin film materials library is then calculated by Stoney's equation based on the obtained radii of curvature of the cantilevers and film thicknesses. DHM with nanometer-scale out-of-plane resolution allows stress measurements in a wide range, at least from several MPa to several GPa. By using an automatic x-y translation stage, the local stresses within a 4-inch materials library are mapped with high accuracy within 10 min. The speed of measurement is greatly improved compared with the prior laser scanning approach that needs more than an hour of measuring time. A high-throughput stress measurement of an as-deposited Fe-Pd-W materials library was evaluated for demonstration. The fast characterization method is expected to accelerate the development of (functional) thin films, e.g., (magnetic) shape memory materials, whose functionality is greatly stress dependent. © 2011 American Institute of Physics

High-Throughput Simulation of Environmental Chemical Fate for Exposure Prioritization

EPA Science Inventory

The U.S. EPA must consider lists of hundreds to thousands of chemicals when allocating resources to identify risk in human populations and the environment. High-throughput screening assays to characterize biological activity in vitro have allowed the ToxCastTM program to identify...

An Automated High-Throughput System to Fractionate Plant Natural Products for Drug Discovery

PubMed Central

Tu, Ying; Jeffries, Cynthia; Ruan, Hong; Nelson, Cynthia; Smithson, David; Shelat, Anang A.; Brown, Kristin M.; Li, Xing-Cong; Hester, John P.; Smillie, Troy; Khan, Ikhlas A.; Walker, Larry; Guy, Kip; Yan, Bing

2010-01-01

The development of an automated, high-throughput fractionation procedure to prepare and analyze natural product libraries for drug discovery screening is described. Natural products obtained from plant materials worldwide were extracted and first prefractionated on polyamide solid-phase extraction cartridges to remove polyphenols, followed by high-throughput automated fractionation, drying, weighing, and reformatting for screening and storage. The analysis of fractions with UPLC coupled with MS, PDA and ELSD detectors provides information that facilitates characterization of compounds in active fractions. Screening of a portion of fractions yielded multiple assay-specific hits in several high-throughput cellular screening assays. This procedure modernizes the traditional natural product fractionation paradigm by seamlessly integrating automation, informatics, and multimodal analytical interrogation capabilities. PMID:20232897

Characterizing visible and invisible cell wall mutant phenotypes.

PubMed

Carpita, Nicholas C; McCann, Maureen C

2015-07-01

About 10% of a plant's genome is devoted to generating the protein machinery to synthesize, remodel, and deconstruct the cell wall. High-throughput genome sequencing technologies have enabled a reasonably complete inventory of wall-related genes that can be assembled into families of common evolutionary origin. Assigning function to each gene family member has been aided immensely by identification of mutants with visible phenotypes or by chemical and spectroscopic analysis of mutants with 'invisible' phenotypes of modified cell wall composition and architecture that do not otherwise affect plant growth or development. This review connects the inference of gene function on the basis of deviation from the wild type in genetic functional analyses to insights provided by modern analytical techniques that have brought us ever closer to elucidating the sequence structures of the major polysaccharide components of the plant cell wall. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Accounting Artifacts in High-Throughput Toxicity Assays.

PubMed

Hsieh, Jui-Hua

2016-01-01

Compound activity identification is the primary goal in high-throughput screening (HTS) assays. However, assay artifacts including both systematic (e.g., compound auto-fluorescence) and nonsystematic (e.g., noise) complicate activity interpretation. In addition, other than the traditional potency parameter, half-maximal effect concentration (EC50), additional activity parameters (e.g., point-of-departure, POD) could be derived from HTS data for activity profiling. A data analysis pipeline has been developed to handle the artifacts and to provide compound activity characterization with either binary or continuous metrics. This chapter outlines the steps in the pipeline using Tox21 glucocorticoid receptor (GR) β-lactamase assays, including the formats to identify either agonists or antagonists, as well as the counter-screen assays for identifying artifacts as examples. The steps can be applied to other lower-throughput assays with concentration-response data.

High-Throughput Cloning and Expression Library Creation for Functional Proteomics

PubMed Central

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

A high throughput spectral image microscopy system

NASA Astrophysics Data System (ADS)

Gesley, M.; Puri, R.

2018-01-01

A high throughput spectral image microscopy system is configured for rapid detection of rare cells in large populations. To overcome flow cytometry rates and use of fluorophore tags, a system architecture integrates sample mechanical handling, signal processors, and optics in a non-confocal version of light absorption and scattering spectroscopic microscopy. Spectral images with native contrast do not require the use of exogeneous stain to render cells with submicron resolution. Structure may be characterized without restriction to cell clusters of differentiation.

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis.

PubMed

Lee, Jessica J Y; Gottlieb, Michael M; Lever, Jake; Jones, Steven J M; Blau, Nenad; van Karnebeek, Clara D M; Wasserman, Wyeth W

2018-05-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.

High-Throughput Lectin Microarray-Based Analysis of Live Cell Surface Glycosylation

PubMed Central

Li, Yu; Tao, Sheng-ce; Zhu, Heng; Schneck, Jonathan P.

2011-01-01

Lectins, plant-derived glycan-binding proteins, have long been used to detect glycans on cell surfaces. However, the techniques used to characterize serum or cells have largely been limited to mass spectrometry, blots, flow cytometry, and immunohistochemistry. While these lectin-based approaches are well established and they can discriminate a limited number of sugar isomers by concurrently using a limited number of lectins, they are not amenable for adaptation to a high-throughput platform. Fortunately, given the commercial availability of lectins with a variety of glycan specificities, lectins can be printed on a glass substrate in a microarray format to profile accessible cell-surface glycans. This method is an inviting alternative for analysis of a broad range of glycans in a high-throughput fashion and has been demonstrated to be a feasible method of identifying binding-accessible cell surface glycosylation on living cells. The current unit presents a lectin-based microarray approach for analyzing cell surface glycosylation in a high-throughput fashion. PMID:21400689

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

PubMed

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.

High-throughput metagenomic technologies for complex microbial community analysis. Open and closed formats

DOE PAGES

Zhou, Jizhong; He, Zhili; Yang, Yunfeng; ...

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 andmore » 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.« less

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

PubMed

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.

High-Throughput Metagenomic Technologies for Complex Microbial Community Analysis: Open and Closed Formats

PubMed Central

He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G.; Alvarez-Cohen, Lisa

2015-01-01

ABSTRACT   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. PMID:25626903

High-Throughput Sequencing, a Versatile Weapon to Support Genome-Based Diagnosis in Infectious Diseases: Applications to Clinical Bacteriology

PubMed Central

Caboche, Ségolène; Audebert, Christophe; Hot, David

2014-01-01

The recent progresses of high-throughput sequencing (HTS) technologies enable easy and cost-reduced access to whole genome sequencing (WGS) or re-sequencing. HTS associated with adapted, automatic and fast bioinformatics solutions for sequencing applications promises an accurate and timely identification and characterization of pathogenic agents. Many studies have demonstrated that data obtained from HTS analysis have allowed genome-based diagnosis, which has been consistent with phenotypic observations. These proofs of concept are probably the first steps toward the future of clinical microbiology. From concept to routine use, many parameters need to be considered to promote HTS as a powerful tool to help physicians and clinicians in microbiological investigations. This review highlights the milestones to be completed toward this purpose. PMID:25437800

An Automated Method for High-Throughput Screening of Arabidopsis Rosette Growth in Multi-Well Plates and Its Validation in Stress Conditions.

PubMed

De Diego, Nuria; Fürst, Tomáš; Humplík, Jan F; Ugena, Lydia; Podlešáková, Kateřina; Spíchal, Lukáš

2017-01-01

High-throughput plant phenotyping platforms provide new possibilities for automated, fast scoring of several plant growth and development traits, followed over time using non-invasive sensors. Using Arabidops is as a model offers important advantages for high-throughput screening with the opportunity to extrapolate the results obtained to other crops of commercial interest. In this study we describe the development of a highly reproducible high-throughput Arabidopsis in vitro bioassay established using our OloPhen platform, suitable for analysis of rosette growth in multi-well plates. This method was successfully validated on example of multivariate analysis of Arabidopsis rosette growth in different salt concentrations and the interaction with varying nutritional composition of the growth medium. Several traits such as changes in the rosette area, relative growth rate, survival rate and homogeneity of the population are scored using fully automated RGB imaging and subsequent image analysis. The assay can be used for fast screening of the biological activity of chemical libraries, phenotypes of transgenic or recombinant inbred lines, or to search for potential quantitative trait loci. It is especially valuable for selecting genotypes or growth conditions that improve plant stress tolerance.

Blood group genotyping: from patient to high-throughput donor screening.

PubMed

Veldhuisen, B; van der Schoot, C E; de Haas, M

2009-10-01

Blood group antigens, present on the cell membrane of red blood cells and platelets, can be defined either serologically or predicted based on the genotypes of genes encoding for blood group antigens. At present, the molecular basis of many antigens of the 30 blood group systems and 17 human platelet antigens is known. In many laboratories, blood group genotyping assays are routinely used for diagnostics in cases where patient red cells cannot be used for serological typing due to the presence of auto-antibodies or after recent transfusions. In addition, DNA genotyping is used to support (un)-expected serological findings. Fetal genotyping is routinely performed when there is a risk of alloimmune-mediated red cell or platelet destruction. In case of patient blood group antigen typing, it is important that a genotyping result is quickly available to support the selection of donor blood, and high-throughput of the genotyping method is not a prerequisite. In addition, genotyping of blood donors will be extremely useful to obtain donor blood with rare phenotypes, for example lacking a high-frequency antigen, and to obtain a fully typed donor database to be used for a better matching between recipient and donor to prevent adverse transfusion reactions. Serological typing of large cohorts of donors is a labour-intensive and expensive exercise and hampered by the lack of sufficient amounts of approved typing reagents for all blood group systems of interest. Currently, high-throughput genotyping based on DNA micro-arrays is a very feasible method to obtain a large pool of well-typed blood donors. Several systems for high-throughput blood group genotyping are developed and will be discussed in this review.

High Throughput Assays for Exposure Science (NIEHS OHAT Staff Meeting presentation)

EPA Science Inventory

High throughput screening (HTS) data that characterize chemically induced biological activity have been generated for thousands of chemicals by the US interagency Tox21 and the US EPA ToxCast programs. In many cases there are no data available for comparing bioactivity from HTS w...

High-throughput estimation of incident light, light interception and radiation-use efficiency of thousands of plants in a phenotyping platform.

PubMed

Cabrera-Bosquet, Llorenç; Fournier, Christian; Brichet, Nicolas; Welcker, Claude; Suard, Benoît; Tardieu, François

2016-10-01

Light interception and radiation-use efficiency (RUE) are essential components of plant performance. Their genetic dissections require novel high-throughput phenotyping methods. We have developed a suite of methods to evaluate the spatial distribution of incident light, as experienced by hundreds of plants in a glasshouse, by simulating sunbeam trajectories through glasshouse structures every day of the year; the amount of light intercepted by maize (Zea mays) plants via a functional-structural model using three-dimensional (3D) reconstructions of each plant placed in a virtual scene reproducing the canopy in the glasshouse; and RUE, as the ratio of plant biomass to intercepted light. The spatial variation of direct and diffuse incident light in the glasshouse (up to 24%) was correctly predicted at the single-plant scale. Light interception largely varied between maize lines that differed in leaf angles (nearly stable between experiments) and area (highly variable between experiments). Estimated RUEs varied between maize lines, but were similar in two experiments with contrasting incident light. They closely correlated with measured gas exchanges. The methods proposed here identified reproducible traits that might be used in further field studies, thereby opening up the way for large-scale genetic analyses of the components of plant performance. © 2016 INRA New Phytologist © 2016 New Phytologist Trust.

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

PubMed

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.

A Review of Imaging Techniques for Plant Phenotyping

PubMed Central

Li, Lei; Zhang, Qin; Huang, Danfeng

2014-01-01

Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review. PMID:25347588

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

PubMed

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.

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Green, Martin L.; Choi, C. L.; Hattrick-Simpers, J. R.

The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation and modeling of materials. To build on this progress, a large amount of experimental data for validating these models, and informing more sophisticated ones, will be required. High-throughput experimentation generates large volumes of experimental data using combinatorial materials synthesis and rapid measurement techniques, making it an ideal experimental complement to bring the Materials Genome Initiative vision to fruition. This paper reviews the state-of-the-art results, opportunities, and challenges in high-throughput experimentation for materials design. Asmore » a result, a major conclusion is that an effort to deploy a federated network of high-throughput experimental (synthesis and characterization) tools, which are integrated with a modern materials data infrastructure, is needed.« less

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

PubMed

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.

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

DOE PAGES

Green, Martin L.; Choi, C. L.; Hattrick-Simpers, J. R.; ...

2017-03-28

The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation and modeling of materials. To build on this progress, a large amount of experimental data for validating these models, and informing more sophisticated ones, will be required. High-throughput experimentation generates large volumes of experimental data using combinatorial materials synthesis and rapid measurement techniques, making it an ideal experimental complement to bring the Materials Genome Initiative vision to fruition. This paper reviews the state-of-the-art results, opportunities, and challenges in high-throughput experimentation for materials design. Asmore » a result, a major conclusion is that an effort to deploy a federated network of high-throughput experimental (synthesis and characterization) tools, which are integrated with a modern materials data infrastructure, is needed.« less

Overcoming the anaerobic hurdle in phenotypic microarrays: Generation andvisualization of growth curve data for Desulfovibrio vulgaris Hildenborough

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borglin, Sharon E; Joyner, Dominique; Jacobsen, Janet

2008-10-04

Growing anaerobic microorganisms in phenotypic microarrays (PM) and 96-well microtiter plates is an emerging technology that allows high throughput survey of the growth and physiology and/or phenotype of cultivable microorganisms. For non-model bacteria, a method for phenotypic analysis is invaluable, not only to serve as a starting point for further evaluation, but also to provide a broad understanding of the physiology of an uncharacterized wild-type organism or the physiology/phenotype of a newly created mutant of that organism. Given recent advances in genetic characterization and targeted mutations to elucidate genetic networks and metabolic pathways, high-throughput methods for determining phenotypic differences aremore » essential. Here we outline challenges presented in studying the physiology and phenotype of a sulfate reducing anaerobic delta proteobacterium, Desulfovibrio vulgaris Hildenborough. Modifications of the commercially available OmniLog(TM) system (Hayward, CA) for experimental setup, and configuration, as well as considerations in PM data analysis are presented. Also highlighted here is data viewing software that enables users to view and compare multiple PM data sets. The PM method promises to be a valuable strategy in our systems biology approach to D. vulgaris studies and is readily applicable to other anaerobic and aerobic bacteria.« less

Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials

NASA Astrophysics Data System (ADS)

Green, Martin L.; Takeuchi, Ichiro; Hattrick-Simpers, Jason R.

2013-06-01

High throughput (combinatorial) materials science methodology is a relatively new research paradigm that offers the promise of rapid and efficient materials screening, optimization, and discovery. The paradigm started in the pharmaceutical industry but was rapidly adopted to accelerate materials research in a wide variety of areas. High throughput experiments are characterized by synthesis of a "library" sample that contains the materials variation of interest (typically composition), and rapid and localized measurement schemes that result in massive data sets. Because the data are collected at the same time on the same "library" sample, they can be highly uniform with respect to fixed processing parameters. This article critically reviews the literature pertaining to applications of combinatorial materials science for electronic, magnetic, optical, and energy-related materials. It is expected that high throughput methodologies will facilitate commercialization of novel materials for these critically important applications. Despite the overwhelming evidence presented in this paper that high throughput studies can effectively inform commercial practice, in our perception, it remains an underutilized research and development tool. Part of this perception may be due to the inaccessibility of proprietary industrial research and development practices, but clearly the initial cost and availability of high throughput laboratory equipment plays a role. Combinatorial materials science has traditionally been focused on materials discovery, screening, and optimization to combat the extremely high cost and long development times for new materials and their introduction into commerce. Going forward, combinatorial materials science will also be driven by other needs such as materials substitution and experimental verification of materials properties predicted by modeling and simulation, which have recently received much attention with the advent of the Materials Genome

High-throughput determination of structural phase diagram and constituent phases using GRENDEL

NASA Astrophysics Data System (ADS)

Kusne, A. G.; Keller, D.; Anderson, A.; Zaban, A.; Takeuchi, I.

2015-11-01

Advances in high-throughput materials fabrication and characterization techniques have resulted in faster rates of data collection and rapidly growing volumes of experimental data. To convert this mass of information into actionable knowledge of material process-structure-property relationships requires high-throughput data analysis techniques. This work explores the use of the Graph-based endmember extraction and labeling (GRENDEL) algorithm as a high-throughput method for analyzing structural data from combinatorial libraries, specifically, to determine phase diagrams and constituent phases from both x-ray diffraction and Raman spectral data. The GRENDEL algorithm utilizes a set of physical constraints to optimize results and provides a framework by which additional physics-based constraints can be easily incorporated. GRENDEL also permits the integration of database data as shown by the use of critically evaluated data from the Inorganic Crystal Structure Database in the x-ray diffraction data analysis. Also the Sunburst radial tree map is demonstrated as a tool to visualize material structure-property relationships found through graph based analysis.

High Throughput Transcriptomics: From screening to pathways

EPA Science Inventory

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...

Molecular characterization of a novel Luteovirus from peach identified by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Contigs with sequence homologies to Cherry-associated luteovirus were identified by high-throughput sequencing analysis of two peach accessions undergoing quarantine testing. The complete genomic sequences of the two isolates of this virus are 5,819 and 5,814 nucleotides. Their genome organization i...

High throughput screening of particle conditioning operations: I. System design and method development.

PubMed

Noyes, Aaron; Huffman, Ben; Godavarti, Ranga; Titchener-Hooker, Nigel; Coffman, Jonathan; Sunasara, Khurram; Mukhopadhyay, Tarit

2015-08-01

The biotech industry is under increasing pressure to decrease both time to market and development costs. Simultaneously, regulators are expecting increased process understanding. High throughput process development (HTPD) employs small volumes, parallel processing, and high throughput analytics to reduce development costs and speed the development of novel therapeutics. As such, HTPD is increasingly viewed as integral to improving developmental productivity and deepening process understanding. Particle conditioning steps such as precipitation and flocculation may be used to aid the recovery and purification of biological products. In this first part of two articles, we describe an ultra scale-down system (USD) for high throughput particle conditioning (HTPC) composed of off-the-shelf components. The apparatus is comprised of a temperature-controlled microplate with magnetically driven stirrers and integrated with a Tecan liquid handling robot. With this system, 96 individual reaction conditions can be evaluated in parallel, including downstream centrifugal clarification. A comprehensive suite of high throughput analytics enables measurement of product titer, product quality, impurity clearance, clarification efficiency, and particle characterization. HTPC at the 1 mL scale was evaluated with fermentation broth containing a vaccine polysaccharide. The response profile was compared with the Pilot-scale performance of a non-geometrically similar, 3 L reactor. An engineering characterization of the reactors and scale-up context examines theoretical considerations for comparing this USD system with larger scale stirred reactors. In the second paper, we will explore application of this system to industrially relevant vaccines and test different scale-up heuristics. © 2015 Wiley Periodicals, Inc.

Modeling Steroidogenesis Disruption Using High-Throughput ...

EPA Pesticide Factsheets

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

High-throughput syntheses of iron phosphite open frameworks in ionic liquids

NASA Astrophysics Data System (ADS)

Wang, Zhixiu; Mu, Ying; Wang, Yilin; Bing, Qiming; Su, Tan; Liu, Jingyao

2017-02-01

Three open-framework iron phosphites: Feп5(NH4)2(HPO3)6 (1), Feп2Fe♯(NH4)(HPO3)4 (2) and Fe♯2(HPO3)3 (3) have been synthesized under ionothermal conditions. How the different synthesis parameters, such as the gel concentrations, synthetic times, reaction temperatures and solvents affect the products have been monitored by using high-throughput approaches. Within each type of experiment, relevant products have been investigated. The optimal reaction conditions are obtained from a series of experiments by high-throughput approaches. All the structures are determined by single-crystal X-ray diffraction analysis and further characterized by PXRD, TGA and FTIR analyses. Magnetic study reveals that those three compounds show interesting magnetic behavior at low temperature.

Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening

EPA Science Inventory

The EPA ToxCast research program uses high throughput screening for bioactivity profiling and predicting the toxicity of large numbers of chemicals. ToxCast Phase‐I tested 309 well‐characterized chemicals in over 500 assays for a wide range of molecular targets and cellular respo...

GiA Roots: software for the high throughput analysis of plant root system architecture.

PubMed

Galkovskyi, Taras; Mileyko, Yuriy; Bucksch, Alexander; Moore, Brad; Symonova, Olga; Price, Charles A; Topp, Christopher N; Iyer-Pascuzzi, Anjali S; Zurek, Paul R; Fang, Suqin; Harer, John; Benfey, Philip N; Weitz, Joshua S

2012-07-26

Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks. We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user. We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.

Target Discovery for Precision Medicine Using High-Throughput Genome Engineering.

PubMed

Guo, Xinyi; Chitale, Poonam; Sanjana, Neville E

2017-01-01

Over the past few years, programmable RNA-guided nucleases such as the CRISPR/Cas9 system have ushered in a new era of precision genome editing in diverse model systems and in human cells. Functional screens using large libraries of RNA guides can interrogate a large hypothesis space to pinpoint particular genes and genetic elements involved in fundamental biological processes and disease-relevant phenotypes. Here, we review recent high-throughput CRISPR screens (e.g. loss-of-function, gain-of-function, and targeting noncoding elements) and highlight their potential for uncovering novel therapeutic targets, such as those involved in cancer resistance to small molecular drugs and immunotherapies, tumor evolution, infectious disease, inborn genetic disorders, and other therapeutic challenges.

CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging.

PubMed

Held, Michael; Schmitz, Michael H A; Fischer, Bernd; Walter, Thomas; Neumann, Beate; Olma, Michael H; Peter, Matthias; Ellenberg, Jan; Gerlich, Daniel W

2010-09-01

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

Phenotype detection in morphological mutant mice using deformation features.

PubMed

Roy, Sharmili; Liang, Xi; Kitamoto, Asanobu; Tamura, Masaru; Shiroishi, Toshihiko; Brown, Michael S

2013-01-01

Large-scale global efforts are underway to knockout each of the approximately 25,000 mouse genes and interpret their roles in shaping the mammalian embryo. Given the tremendous amount of data generated by imaging mutated prenatal mice, high-throughput image analysis systems are inevitable to characterize mammalian development and diseases. Current state-of-the-art computational systems offer only differential volumetric analysis of pre-defined anatomical structures between various gene-knockout mice strains. For subtle anatomical phenotypes, embryo phenotyping still relies on the laborious histological techniques that are clearly unsuitable in such big data environment. This paper presents a system that automatically detects known phenotypes and assists in discovering novel phenotypes in muCT images of mutant mice. Deformation features obtained from non-linear registration of mutant embryo to a normal consensus average image are extracted and analyzed to compute phenotypic and candidate phenotypic areas. The presented system is evaluated using C57BL/10 embryo images. All cases of ventricular septum defect and polydactyly, well-known to be present in this strain, are successfully detected. The system predicts potential phenotypic areas in the liver that are under active histological evaluation for possible phenotype of this mouse line.

High-throughput electrical measurement and microfluidic sorting of semiconductor nanowires.

PubMed

Akin, Cevat; Feldman, Leonard C; Durand, Corentin; Hus, Saban M; Li, An-Ping; Hui, Ho Yee; Filler, Michael A; Yi, Jingang; Shan, Jerry W

2016-05-24

Existing nanowire electrical characterization tools not only are expensive and require sophisticated facilities, but are far too slow to enable statistical characterization of highly variable samples. They are also generally not compatible with further sorting and processing of nanowires. Here, we demonstrate a high-throughput, solution-based electro-orientation-spectroscopy (EOS) method, which is capable of automated electrical characterization of individual nanowires by direct optical visualization of their alignment behavior under spatially uniform electric fields of different frequencies. We demonstrate that EOS can quantitatively characterize the electrical conductivities of nanowires over a 6-order-of-magnitude range (10(-5) to 10 S m(-1), corresponding to typical carrier densities of 10(10)-10(16) cm(-3)), with different fluids used to suspend the nanowires. By implementing EOS in a simple microfluidic device, continuous electrical characterization is achieved, and the sorting of nanowires is demonstrated as a proof-of-concept. With measurement speeds two orders of magnitude faster than direct-contact methods, the automated EOS instrument enables for the first time the statistical characterization of highly variable 1D nanomaterials.

Lens-free shadow image based high-throughput continuous cell monitoring technique.

PubMed

Jin, Geonsoo; Yoo, In-Hwa; Pack, Seung Pil; Yang, Ji-Woon; Ha, Un-Hwan; Paek, Se-Hwan; Seo, Sungkyu

2012-01-01

A high-throughput continuous cell monitoring technique which does not require any labeling reagents or destruction of the specimen is demonstrated. More than 6000 human alveolar epithelial A549 cells are monitored for up to 72 h simultaneously and continuously with a single digital image within a cost and space effective lens-free shadow imaging platform. In an experiment performed within a custom built incubator integrated with the lens-free shadow imaging platform, the cell nucleus division process could be successfully characterized by calculating the signal-to-noise ratios (SNRs) and the shadow diameters (SDs) of the cell shadow patterns. The versatile nature of this platform also enabled a single cell viability test followed by live cell counting. This study firstly shows that the lens-free shadow imaging technique can provide a continuous cell monitoring without any staining/labeling reagent and destruction of the specimen. This high-throughput continuous cell monitoring technique based on lens-free shadow imaging may be widely utilized as a compact, low-cost, and high-throughput cell monitoring tool in the fields of drug and food screening or cell proliferation and viability testing. Copyright © 2012 Elsevier B.V. All rights reserved.

High-Throughput Models for Exposure-Based Chemical Prioritization in the ExpoCast Project

EPA Science Inventory

The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research pr...

High-Throughput Models for Exposure-Based Chemical ...

EPA Pesticide Factsheets

The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research program to prioritize chemical inventories for potential hazard. Similar capabilities for estimating exposure potential would support rapid risk-based prioritization for chemicals with limited information; here, we propose a framework for high-throughput exposure assessment. To demonstrate application, an analysis was conducted that predicts human exposure potential for chemicals and estimates uncertainty in these predictions by comparison to biomonitoring data. We evaluated 1936 chemicals using far-field mass balance human exposure models (USEtox and RAIDAR) and an indicator for indoor and/or consumer use. These predictions were compared to exposures inferred by Bayesian analysis from urine concentrations for 82 chemicals reported in the National Health and Nutrition Examination Survey (NHANES). Joint regression on all factors provided a calibrated consensus prediction, the variance of which serves as an empirical determination of uncertainty for prioritization on absolute exposure potential. Information on use was found to be most predictive; generally, chemicals above the limit of detection in NHANES had consumer/indoor use. Coupled with hazard HTS, exposure HTS can place risk earlie

Uncommon nucleotide excision repair phenotypes revealed by targeted high-throughput sequencing.

PubMed

Calmels, Nadège; Greff, Géraldine; Obringer, Cathy; Kempf, Nadine; Gasnier, Claire; Tarabeux, Julien; Miguet, Marguerite; Baujat, Geneviève; Bessis, Didier; Bretones, Patricia; Cavau, Anne; Digeon, Béatrice; Doco-Fenzy, Martine; Doray, Bérénice; Feillet, François; Gardeazabal, Jesus; Gener, Blanca; Julia, Sophie; Llano-Rivas, Isabel; Mazur, Artur; Michot, Caroline; Renaldo-Robin, Florence; Rossi, Massimiliano; Sabouraud, Pascal; Keren, Boris; Depienne, Christel; Muller, Jean; Mandel, Jean-Louis; Laugel, Vincent

2016-03-22

Deficient nucleotide excision repair (NER) activity causes a variety of autosomal recessive diseases including xeroderma pigmentosum (XP) a disorder which pre-disposes to skin cancer, and the severe multisystem condition known as Cockayne syndrome (CS). In view of the clinical overlap between NER-related disorders, as well as the existence of multiple phenotypes and the numerous genes involved, we developed a new diagnostic approach based on the enrichment of 16 NER-related genes by multiplex amplification coupled with next-generation sequencing (NGS). Our test cohort consisted of 11 DNA samples, all with known mutations and/or non pathogenic SNPs in two of the tested genes. We then used the same technique to analyse samples from a prospective cohort of 40 patients. Multiplex amplification and sequencing were performed using AmpliSeq protocol on the Ion Torrent PGM (Life Technologies). We identified causative mutations in 17 out of the 40 patients (43%). Four patients showed biallelic mutations in the ERCC6(CSB) gene, five in the ERCC8(CSA) gene: most of them had classical CS features but some had very mild and incomplete phenotypes. A small cohort of 4 unrelated classic XP patients from the Basque country (Northern Spain) revealed a common splicing mutation in POLH (XP-variant), demonstrating a new founder effect in this population. Interestingly, our results also found ERCC2(XPD), ERCC3(XPB) or ERCC5(XPG) mutations in two cases of UV-sensitive syndrome and in two cases with mixed XP/CS phenotypes. Our study confirms that NGS is an efficient technique for the analysis of NER-related disorders on a molecular level. It is particularly useful for phenotypes with combined features or unusually mild symptoms. Targeted NGS used in conjunction with DNA repair functional tests and precise clinical evaluation permits rapid and cost-effective diagnosis in patients with NER-defects.

Molecular characterization of a novel Nucleorhabdovirus from black currant identified by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Contigs with sequence similarities to several nucleorhabdoviruses were identified by high-throughput sequencing analysis from a black currant (Ribes nigrum L.) cultivar. The complete genomic sequence of this new nucleorhabdovirus is 14,432 nucleotides. Its genomic organization is typical of nucleorh...

High Throughput Transcriptomics @ USEPA (Toxicology ...

EPA Pesticide Factsheets

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.

Application of ToxCast High-Throughput Screening and ...

EPA Pesticide Factsheets

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

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

PubMed Central

Hoffmann, Stefanie; Walter, Steffi; Blume, Anne-Kathrin; Fuchs, Stephan; Schmidt, Christiane; Scholz, Annemarie; Gerlach, Roman G.

2018-01-01

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. PMID:29497603

High-throughput tetrad analysis.

PubMed

Ludlow, Catherine L; Scott, Adrian C; Cromie, Gareth A; Jeffery, Eric W; Sirr, Amy; May, Patrick; Lin, Jake; Gilbert, Teresa L; Hays, Michelle; Dudley, Aimée M

2013-07-01

Tetrad analysis has been a gold-standard genetic technique for several decades. Unfortunately, the need to manually isolate, disrupt and space tetrads has relegated its application to small-scale studies and limited its integration with high-throughput DNA sequencing technologies. We have developed a rapid, high-throughput method, called barcode-enabled sequencing of tetrads (BEST), that uses (i) a meiosis-specific GFP fusion protein to isolate tetrads by FACS and (ii) molecular barcodes that are read during genotyping to identify spores derived from the same tetrad. Maintaining tetrad information allows accurate inference of missing genetic markers and full genotypes of missing (and presumably nonviable) individuals. An individual researcher was able to isolate over 3,000 yeast tetrads in 3 h, an output equivalent to that of almost 1 month of manual dissection. BEST is transferable to other microorganisms for which meiotic mapping is significantly more laborious.

PlantCV v2: Image analysis software for high-throughput plant phenotyping

PubMed Central

Abbasi, Arash; Berry, Jeffrey C.; Callen, Steven T.; Chavez, Leonardo; Doust, Andrew N.; Feldman, Max J.; Gilbert, Kerrigan B.; Hodge, John G.; Hoyer, J. Steen; Lin, Andy; Liu, Suxing; Lizárraga, César; Lorence, Argelia; Miller, Michael; Platon, Eric; Tessman, Monica; Sax, Tony

2017-01-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning. PMID:29209576

PlantCV v2: Image analysis software for high-throughput plant phenotyping.

PubMed

Gehan, Malia A; Fahlgren, Noah; Abbasi, Arash; Berry, Jeffrey C; Callen, Steven T; Chavez, Leonardo; Doust, Andrew N; Feldman, Max J; Gilbert, Kerrigan B; Hodge, John G; Hoyer, J Steen; Lin, Andy; Liu, Suxing; Lizárraga, César; Lorence, Argelia; Miller, Michael; Platon, Eric; Tessman, Monica; Sax, Tony

2017-01-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

PlantCV v2: Image analysis software for high-throughput plant phenotyping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gehan, Malia A.; Fahlgren, Noah; Abbasi, Arash

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here in this paper we present the details andmore » rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.« less

PlantCV v2: Image analysis software for high-throughput plant phenotyping

DOE PAGES

Gehan, Malia A.; Fahlgren, Noah; Abbasi, Arash; ...

2017-12-01

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here in this paper we present the details andmore » rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.« less

Phenotypic approaches to drought in cassava: review

PubMed Central

Okogbenin, Emmanuel; Setter, Tim L.; Ferguson, Morag; Mutegi, Rose; Ceballos, Hernan; Olasanmi, Bunmi; Fregene, Martin

2012-01-01

Cassava is an important crop in Africa, Asia, Latin America, and the Caribbean. Cassava can be produced adequately in drought conditions making it the ideal food security crop in marginal environments. Although cassava can tolerate drought stress, it can be genetically improved to enhance productivity in such environments. Drought adaptation studies in over three decades in cassava have identified relevant mechanisms which have been explored in conventional breeding. Drought is a quantitative trait and its multigenic nature makes it very challenging to effectively manipulate and combine genes in breeding for rapid genetic gain and selection process. Cassava has a long growth cycle of 12–18 months which invariably contributes to a long breeding scheme for the crop. Modern breeding using advances in genomics and improved genotyping, is facilitating the dissection and genetic analysis of complex traits including drought tolerance, thus helping to better elucidate and understand the genetic basis of such traits. A beneficial goal of new innovative breeding strategies is to shorten the breeding cycle using minimized, efficient or fast phenotyping protocols. While high throughput genotyping have been achieved, this is rarely the case for phenotyping for drought adaptation. Some of the storage root phenotyping in cassava are often done very late in the evaluation cycle making selection process very slow. This paper highlights some modified traits suitable for early-growth phase phenotyping that may be used to reduce drought phenotyping cycle in cassava. Such modified traits can significantly complement the high throughput genotyping procedures to fast track breeding of improved drought tolerant varieties. The need for metabolite profiling, improved phenomics to take advantage of next generation sequencing technologies and high throughput phenotyping are basic steps for future direction to improve genetic gain and maximize speed for drought tolerance breeding. PMID

FIM, a Novel FTIR-Based Imaging Method for High Throughput Locomotion Analysis

PubMed Central

Otto, Nils; Löpmeier, Tim; Valkov, Dimitar; Jiang, Xiaoyi; Klämbt, Christian

2013-01-01

We designed a novel imaging technique based on frustrated total internal reflection (FTIR) to obtain high resolution and high contrast movies. This FTIR-based Imaging Method (FIM) is suitable for a wide range of biological applications and a wide range of organisms. It operates at all wavelengths permitting the in vivo detection of fluorescent proteins. To demonstrate the benefits of FIM, we analyzed large groups of crawling Drosophila larvae. The number of analyzable locomotion tracks was increased by implementing a new software module capable of preserving larval identity during most collision events. This module is integrated in our new tracking program named FIMTrack which subsequently extracts a number of features required for the analysis of complex locomotion phenotypes. FIM enables high throughput screening for even subtle behavioral phenotypes. We tested this newly developed setup by analyzing locomotion deficits caused by the glial knockdown of several genes. Suppression of kinesin heavy chain (khc) or rab30 function led to contraction pattern or head sweeping defects, which escaped in previous analysis. Thus, FIM permits forward genetic screens aimed to unravel the neural basis of behavior. PMID:23349775

A Simple Method for High Throughput Chemical Screening in Caenorhabditis Elegans

PubMed Central

Lucanic, Mark; Garrett, Theo; Gill, Matthew S.; Lithgow, Gordon J.

2018-01-01

Caenorhabditis elegans is a useful organism for testing chemical effects on physiology. Whole organism small molecule screens offer significant advantages for identifying biologically active chemical structures that can modify complex phenotypes such as lifespan. Described here is a simple protocol for producing hundreds of 96-well culture plates with fairly consistent numbers of C. elegans in each well. Next, we specified how to use these cultures to screen thousands of chemicals for effects on the lifespan of the nematode C. elegans. This protocol makes use of temperature sensitive sterile strains, agar plate conditions, and simple animal handling to facilitate the rapid and high throughput production of synchronized animal cultures for screening. PMID:29630057

Crystal Symmetry Algorithms in a High-Throughput Framework for Materials

NASA Astrophysics Data System (ADS)

Taylor, Richard

The high-throughput framework AFLOW that has been developed and used successfully over the last decade is improved to include fully-integrated software for crystallographic symmetry characterization. The standards used in the symmetry algorithms conform with the conventions and prescriptions given in the International Tables of Crystallography (ITC). A standard cell choice with standard origin is selected, and the space group, point group, Bravais lattice, crystal system, lattice system, and representative symmetry operations are determined. Following the conventions of the ITC, the Wyckoff sites are also determined and their labels and site symmetry are provided. The symmetry code makes no assumptions on the input cell orientation, origin, or reduction and has been integrated in the AFLOW high-throughput framework for materials discovery by adding to the existing code base and making use of existing classes and functions. The software is written in object-oriented C++ for flexibility and reuse. A performance analysis and examination of the algorithms scaling with cell size and symmetry is also reported.

High Throughput Plasma Water Treatment

NASA Astrophysics Data System (ADS)

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).

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

PubMed

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

Pipeline for illumination correction of images for high-throughput microscopy.

PubMed

Singh, S; Bray, M-A; Jones, T R; Carpenter, A E

2014-12-01

The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

High-throughput sequencing reveals unprecedented diversities of Aspergillus species in outdoor air.

PubMed

Lee, S; An, C; Xu, S; Lee, S; Yamamoto, N

2016-09-01

This study used the Illumina MiSeq to analyse compositions and diversities of Aspergillus species in outdoor air. The seasonal air samplings were performed at two locations in Seoul, South Korea. The results showed the relative abundances of all Aspergillus species combined ranging from 0·20 to 18% and from 0·19 to 21% based on the number of the internal transcribed spacer 1 (ITS1) and β-tubulin (BenA) gene sequences respectively. Aspergillus fumigatus was the most dominant species with the mean relative abundances of 1·2 and 5·5% based on the number of the ITS1 and BenA sequences respectively. A total of 29 Aspergillus species were detected and identified down to the species rank, among which nine species were known opportunistic pathogens. Remarkably, eight of the nine pathogenic species were detected by either one of the two markers, suggesting the need of using multiple markers and/or primer pairs when the assessments are made based on the high-throughput sequencing. Due to diversity of species within the genus Aspergillus, the high-throughput sequencing was useful to characterize their compositions and diversities in outdoor air, which are thought to be difficult to be accurately characterized by conventional culture and/or Sanger sequencing-based techniques. Aspergillus is a diverse genus of fungi with more than 300 species reported in literature. Aspergillus is important since some species are known allergens and opportunistic human pathogens. Traditionally, growth-dependent methods have been used to detect Aspergillus species in air. However, these methods are limited in the number of isolates that can be analysed for their identities, resulting in inaccurate characterizations of Aspergillus diversities. This study used the high-throughput sequencing to explore Aspergillus diversities in outdoor, which are thought to be difficult to be accurately characterized by traditional growth-dependent techniques. © 2016 The Society for Applied Microbiology.

'PACLIMS': a component LIM system for high-throughput functional genomic analysis.

PubMed

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-04-12

Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

'PACLIMS': A component LIM system for high-throughput functional genomic analysis

PubMed Central

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-01-01

Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors. PMID

Novel method for high-throughput phenotyping of sleep in mice.

PubMed

Pack, Allan I; Galante, Raymond J; Maislin, Greg; Cater, Jacqueline; Metaxas, Dimitris; Lu, Shan; Zhang, Lin; Von Smith, Randy; Kay, Timothy; Lian, Jie; Svenson, Karen; Peters, Luanne L

2007-01-17

Assessment of sleep in mice currently requires initial implantation of chronic electrodes for assessment of electroencephalogram (EEG) and electromyogram (EMG) followed by time to recover from surgery. Hence, it is not ideal for high-throughput screening. To address this deficiency, a method of assessment of sleep and wakefulness in mice has been developed based on assessment of activity/inactivity either by digital video analysis or by breaking infrared beams in the mouse cage. It is based on the algorithm that any episode of continuous inactivity of > or =40 s is predicted to be sleep. The method gives excellent agreement in C57BL/6J male mice with simultaneous assessment of sleep by EEG/EMG recording. The average agreement over 8,640 10-s epochs in 24 h is 92% (n = 7 mice) with agreement in individual mice being 88-94%. Average EEG/EMG determined sleep per 2-h interval across the day was 59.4 min. The estimated mean difference (bias) per 2-h interval between inactivity-defined sleep and EEG/EMG-defined sleep was only 1.0 min (95% confidence interval for mean bias -0.06 to +2.6 min). The standard deviation of differences (precision) was 7.5 min per 2-h interval with 95% limits of agreement ranging from -13.7 to +15.7 min. Although bias significantly varied by time of day (P = 0.0007), the magnitude of time-of-day differences was not large (average bias during lights on and lights off was +5.0 and -3.0 min per 2-h interval, respectively). This method has applications in chemical mutagenesis and for studies of molecular changes in brain with sleep/wakefulness.

Multi-step high-throughput conjugation platform for the development of antibody-drug conjugates.

PubMed

Andris, Sebastian; Wendeler, Michaela; Wang, Xiangyang; Hubbuch, Jürgen

2018-07-20

Antibody-drug conjugates (ADCs) form a rapidly growing class of biopharmaceuticals which attracts a lot of attention throughout the industry due to its high potential for cancer therapy. They combine the specificity of a monoclonal antibody (mAb) and the cell-killing capacity of highly cytotoxic small molecule drugs. Site-specific conjugation approaches involve a multi-step process for covalent linkage of antibody and drug via a linker. Despite the range of parameters that have to be investigated, high-throughput methods are scarcely used so far in ADC development. In this work an automated high-throughput platform for a site-specific multi-step conjugation process on a liquid-handling station is presented by use of a model conjugation system. A high-throughput solid-phase buffer exchange was successfully incorporated for reagent removal by utilization of a batch cation exchange step. To ensure accurate screening of conjugation parameters, an intermediate UV/Vis-based concentration determination was established including feedback to the process. For conjugate characterization, a high-throughput compatible reversed-phase chromatography method with a runtime of 7 min and no sample preparation was developed. Two case studies illustrate the efficient use for mapping the operating space of a conjugation process. Due to the degree of automation and parallelization, the platform is capable of significantly reducing process development efforts and material demands and shorten development timelines for antibody-drug conjugates. Copyright © 2018 Elsevier B.V. All rights reserved.

A genome-wide CRISPR library for high-throughput genetic screening in Drosophila cells.

PubMed

Bassett, Andrew R; Kong, Lesheng; Liu, Ji-Long

2015-06-20

The simplicity of the CRISPR/Cas9 system of genome engineering has opened up the possibility of performing genome-wide targeted mutagenesis in cell lines, enabling screening for cellular phenotypes resulting from genetic aberrations. Drosophila cells have proven to be highly effective in identifying genes involved in cellular processes through similar screens using partial knockdown by RNAi. This is in part due to the lower degree of redundancy between genes in this organism, whilst still maintaining highly conserved gene networks and orthologs of many human disease-causing genes. The ability of CRISPR to generate genetic loss of function mutations not only increases the magnitude of any effect over currently employed RNAi techniques, but allows analysis over longer periods of time which can be critical for certain phenotypes. In this study, we have designed and built a genome-wide CRISPR library covering 13,501 genes, among which 8989 genes are targeted by three or more independent single guide RNAs (sgRNAs). Moreover, we describe strategies to monitor the population of guide RNAs by high throughput sequencing (HTS). We hope that this library will provide an invaluable resource for the community to screen loss of function mutations for cellular phenotypes, and as a source of guide RNA designs for future studies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

PubMed Central

Shi, Yeyin; Thomasson, J. Alex; Murray, Seth C.; Pugh, N. Ace; Rooney, William L.; Shafian, Sanaz; Rajan, Nithya; Rouze, Gregory; Morgan, Cristine L. S.; Neely, Haly L.; Rana, Aman; Bagavathiannan, Muthu V.; Henrickson, James; Bowden, Ezekiel; Valasek, John; Olsenholler, Jeff; Bishop, Michael P.; Sheridan, Ryan; Putman, Eric B.; Popescu, Sorin; Burks, Travis; Cope, Dale; Ibrahim, Amir; McCutchen, Billy F.; Baltensperger, David D.; Avant, Robert V.; Vidrine, Misty; Yang, Chenghai

2016-01-01

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first

High-Throughput Simulation of Environmental Chemical Fate for Exposure Prioritization (Annual Meeting of ISES)

EPA Science Inventory

The U.S. EPA must consider thousands of chemicals when allocating resources to assess risk in human populations and the environment. High-throughput screening assays to characterize biological activity in vitro are being implemented in the ToxCastTM program to rapidly characteri...

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

EPA Pesticide Factsheets

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

Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes

DOE PAGES

Cruz, Jeffrey A.; Savage, Linda J.; Zegarac, Robert; ...

2016-06-22

Understanding and improving the productivity and robustness of plant photosynthesis requires high-throughput phenotyping under environmental conditions that are relevant to the field. Here we demonstrate the dynamic environmental photosynthesis imager (DEPI), an experimental platform for integrated, continuous, and high-throughput measurements of photosynthetic parameters during plant growth under reproducible yet dynamic environmental conditions. Using parallel imagers obviates the need to move plants or sensors, reducing artifacts and allowing simultaneous measurement on large numbers of plants. As a result, DEPI can reveal phenotypes that are not evident under standard laboratory conditions but emerge under progressively more dynamic illumination. We show examples inmore » mutants of Arabidopsis of such “emergent phenotypes” that are highly transient and heterogeneous, appearing in different leaves under different conditions and depending in complex ways on both environmental conditions and plant developmental age. Finally, these emergent phenotypes appear to be caused by a range of phenomena, suggesting that such previously unseen processes are critical for plant responses to dynamic environments.« less

Determination of equilibrium dissociation constants for recombinant antibodies by high-throughput affinity electrophoresis.

PubMed

Pan, Yuchen; Sackmann, Eric K; Wypisniak, Karolina; Hornsby, Michael; Datwani, Sammy S; Herr, Amy E

2016-12-23

High-quality immunoreagents enhance the performance and reproducibility of immunoassays and, in turn, the quality of both biological and clinical measurements. High quality recombinant immunoreagents are generated using antibody-phage display. One metric of antibody quality - the binding affinity - is quantified through the dissociation constant (K D ) of each recombinant antibody and the target antigen. To characterize the K D of recombinant antibodies and target antigen, we introduce affinity electrophoretic mobility shift assays (EMSAs) in a high-throughput format suitable for small volume samples. A microfluidic card comprised of free-standing polyacrylamide gel (fsPAG) separation lanes supports 384 concurrent EMSAs in 30 s using a single power source. Sample is dispensed onto the microfluidic EMSA card by acoustic droplet ejection (ADE), which reduces EMSA variability compared to sample dispensing using manual or pin tools. The K D for each of a six-member fragment antigen-binding fragment library is reported using ~25-fold less sample mass and ~5-fold less time than conventional heterogeneous assays. Given the form factor and performance of this micro- and mesofluidic workflow, we have developed a sample-sparing, high-throughput, solution-phase alternative for biomolecular affinity characterization.

Determination of equilibrium dissociation constants for recombinant antibodies by high-throughput affinity electrophoresis

PubMed Central

Pan, Yuchen; Sackmann, Eric K.; Wypisniak, Karolina; Hornsby, Michael; Datwani, Sammy S.; Herr, Amy E.

2016-01-01

High-quality immunoreagents enhance the performance and reproducibility of immunoassays and, in turn, the quality of both biological and clinical measurements. High quality recombinant immunoreagents are generated using antibody-phage display. One metric of antibody quality – the binding affinity – is quantified through the dissociation constant (KD) of each recombinant antibody and the target antigen. To characterize the KD of recombinant antibodies and target antigen, we introduce affinity electrophoretic mobility shift assays (EMSAs) in a high-throughput format suitable for small volume samples. A microfluidic card comprised of free-standing polyacrylamide gel (fsPAG) separation lanes supports 384 concurrent EMSAs in 30 s using a single power source. Sample is dispensed onto the microfluidic EMSA card by acoustic droplet ejection (ADE), which reduces EMSA variability compared to sample dispensing using manual or pin tools. The KD for each of a six-member fragment antigen-binding fragment library is reported using ~25-fold less sample mass and ~5-fold less time than conventional heterogeneous assays. Given the form factor and performance of this micro- and mesofluidic workflow, we have developed a sample-sparing, high-throughput, solution-phase alternative for biomolecular affinity characterization. PMID:28008969

High-throughput microfluidic line scan imaging for cytological characterization

NASA Astrophysics Data System (ADS)

Hutcheson, Joshua A.; Powless, Amy J.; Majid, Aneeka A.; Claycomb, Adair; Fritsch, Ingrid; Balachandran, Kartik; Muldoon, Timothy J.

2015-03-01

Imaging cells in a microfluidic chamber with an area scan camera is difficult due to motion blur and data loss during frame readout causing discontinuity of data acquisition as cells move at relatively high speeds through the chamber. We have developed a method to continuously acquire high-resolution images of cells in motion through a microfluidics chamber using a high-speed line scan camera. The sensor acquires images in a line-by-line fashion in order to continuously image moving objects without motion blur. The optical setup comprises an epi-illuminated microscope with a 40X oil immersion, 1.4 NA objective and a 150 mm tube lens focused on a microfluidic channel. Samples containing suspended cells fluorescently stained with 0.01% (w/v) proflavine in saline are introduced into the microfluidics chamber via a syringe pump; illumination is provided by a blue LED (455 nm). Images were taken of samples at the focal plane using an ELiiXA+ 8k/4k monochrome line-scan camera at a line rate of up to 40 kHz. The system's line rate and fluid velocity are tightly controlled to reduce image distortion and are validated using fluorescent microspheres. Image acquisition was controlled via MATLAB's Image Acquisition toolbox. Data sets comprise discrete images of every detectable cell which may be subsequently mined for morphological statistics and definable features by a custom texture analysis algorithm. This high-throughput screening method, comparable to cell counting by flow cytometry, provided efficient examination including counting, classification, and differentiation of saliva, blood, and cultured human cancer cells.

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

PubMed

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.

High Throughput Determination of Critical Human Dosing ...

EPA Pesticide Factsheets

High throughput toxicokinetics (HTTK) is a rapid approach that uses in vitro data to estimate TK for hundreds of environmental chemicals. Reverse dosimetry (i.e., reverse toxicokinetics or RTK) based on HTTK data converts high throughput in vitro toxicity screening (HTS) data into predicted human equivalent doses that can be linked with biologically relevant exposure scenarios. Thus, HTTK provides essential data for risk prioritization for thousands of chemicals that lack TK data. One critical HTTK parameter that can be measured in vitro is the unbound fraction of a chemical in plasma (Fub). However, for chemicals that bind strongly to plasma, Fub is below the limits of detection (LOD) for high throughput analytical chemistry, and therefore cannot be quantified. A novel method for quantifying Fub was implemented for 85 strategically selected chemicals: measurement of Fub was attempted at 10%, 30%, and 100% of physiological plasma concentrations using rapid equilibrium dialysis assays. Varying plasma concentrations instead of chemical concentrations makes high throughput analytical methodology more likely to be successful. Assays at 100% plasma concentration were unsuccessful for 34 chemicals. For 12 of these 34 chemicals, Fub could be quantified at 10% and/or 30% plasma concentrations; these results imply that the assay failure at 100% plasma concentration was caused by plasma protein binding for these chemicals. Assay failure for the remaining 22 chemicals may

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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.

Evaluation of Sequencing Approaches for High-Throughput Transcriptomics - (BOSC)

EPA Science Inventory

Whole-genome in vitro transcriptomics has shown the capability to identify mechanisms of action and estimates of potency for chemical-mediated effects in a toxicological framework, but with limited throughput and high cost. The generation of high-throughput global gene expression...

A new image-based tool for the high throughput phenotyping of pollen viability: evaluation of inter- and intra-cultivar diversity in grapevine.

PubMed

Tello, Javier; Montemayor, María Ignacia; Forneck, Astrid; Ibáñez, Javier

2018-01-01

Low pollen viability may limit grapevine yield under certain conditions, causing relevant economic losses to grape-growers. It is usually evaluated by the quantification of the number of viable and non-viable pollen grains that are present in a sample after an adequate pollen grain staining procedure. Although the manual counting of both types of grains is the simplest and most sensitive approach, it is a laborious and time-demanding process. In this regard, novel image-based approaches can assist in the objective, accurate and cost-effective phenotyping of this trait. Here, we introduce PollenCounter, an open-source macro implemented as a customizable Fiji tool for the high-throughput phenotyping of pollen viability. This tool splits RGB images of stained pollen grains into its primary channels, retaining red and green color fractionated images (which contain information on total and only viable pollen grains, respectively) for the subsequent isolation and counting of the regions of interest (pollen grains). This framework was successfully used for the analysis of pollen viability of a high number of samples collected in a large collection of grapevine cultivars. Results revealed a great genetic variability, from cultivars having very low pollen viability (like Corinto Bianco; viability: 14.1 ± 1.3%) to others with a very low presence of sterile pollen grains (Cuelga; viability: 98.2 ± 0.5%). A wide range of variability was also observed among several clones of cv. Tempranillo Tinto (from 97.9 ± 0.9 to 60.6 ± 5.9%, in the first season). Interestingly, the evaluation of this trait in a second season revealed differential genotype-specific sensitivity to environment. The use of PollenCounter is expected to aid in different areas, including genetics research studies, crop improvement and breeding strategies that need of fast, precise and accurate results. Considering its flexibility, it can be used not only in grapevine, but also in other species showing

Development and Application of a High Throughput Protein Unfolding Kinetic Assay

PubMed Central

Wang, Qiang; Waterhouse, Nicklas; Feyijinmi, Olusegun; Dominguez, Matthew J.; Martinez, Lisa M.; Sharp, Zoey; Service, Rachel; Bothe, Jameson R.; Stollar, Elliott J.

2016-01-01

The kinetics of folding and unfolding underlie protein stability and quantification of these rates provides important insights into the folding process. Here, we present a simple high throughput protein unfolding kinetic assay using a plate reader that is applicable to the studies of the majority of 2-state folding proteins. We validate the assay by measuring kinetic unfolding data for the SH3 (Src Homology 3) domain from Actin Binding Protein 1 (AbpSH3) and its stabilized mutants. The results of our approach are in excellent agreement with published values. We further combine our kinetic assay with a plate reader equilibrium assay, to obtain indirect estimates of folding rates and use these approaches to characterize an AbpSH3-peptide hybrid. Our high throughput protein unfolding kinetic assays allow accurate screening of libraries of mutants by providing both kinetic and equilibrium measurements and provide a means for in-depth ϕ-value analyses. PMID:26745729

A High Throughput Phenotypic Screening reveals compounds that counteract premature osteogenic differentiation of HGPS iPS-derived mesenchymal stem cells.

PubMed

Lo Cicero, Alessandra; Jaskowiak, Anne-Laure; Egesipe, Anne-Laure; Tournois, Johana; Brinon, Benjamin; Pitrez, Patricia R; Ferreira, Lino; de Sandre-Giovannoli, Annachiara; Levy, Nicolas; Nissan, Xavier

2016-10-14

Hutchinson-Gilford progeria syndrome (HGPS) is a rare fatal genetic disorder that causes systemic accelerated aging in children. Thanks to the pluripotency and self-renewal properties of induced pluripotent stem cells (iPSC), HGPS iPSC-based modeling opens up the possibility of access to different relevant cell types for pharmacological approaches. In this study, 2800 small molecules were explored using high-throughput screening, looking for compounds that could potentially reduce the alkaline phosphatase activity of HGPS mesenchymal stem cells (MSCs) committed into osteogenic differentiation. Results revealed seven compounds that normalized the osteogenic differentiation process and, among these, all-trans retinoic acid and 13-cis-retinoic acid, that also decreased progerin expression. This study highlights the potential of high-throughput drug screening using HGPS iPS-derived cells, in order to find therapeutic compounds for HGPS and, potentially, for other aging-related disorders.

High-Throughput Analysis of T-DNA Location and Structure Using Sequence Capture.

PubMed

Inagaki, Soichi; Henry, Isabelle M; Lieberman, Meric C; Comai, Luca

2015-01-01

Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA-genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously, using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. Our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.

High Throughput Determination of Critical Human Dosing Parameters (SOT)

EPA Science Inventory

High throughput toxicokinetics (HTTK) is a rapid approach that uses in vitro data to estimate TK for hundreds of environmental chemicals. Reverse dosimetry (i.e., reverse toxicokinetics or RTK) based on HTTK data converts high throughput in vitro toxicity screening (HTS) data int...

High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

EPA Science Inventory

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...

Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.

PubMed

Harper, Marc; Gronenberg, Luisa; Liao, James; Lee, Christopher

2014-01-01

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

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

PubMed

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.

Hydrogel Droplet Microfluidics for High-Throughput Single Molecule/Cell Analysis.

PubMed

Zhu, Zhi; Yang, Chaoyong James

2017-01-17

molecule/cell analysis. The hydrogel can act as a 3D cell culture matrix to mimic the extracellular environment for long-term single cell culture, which allows further heterogeneity study in proliferation, drug screening, and metastasis at the single-cell level. The sol-gel transition allows reactions in solution to be performed rapidly and efficiently with product storage in the gel for flexible downstream manipulation and analysis. More importantly, controllable sol-gel regulation provides a new way to maintain phenotype-genotype linkages in the hydrogel matrix for high throughput molecular evolution. In this Account, we will review the hydrogel droplet generation on microfluidics, single molecule/cell encapsulation in hydrogel droplets, as well as the progress made by our group and others in the application of hydrogel droplet microfluidics for single molecule/cell analysis, including single cell culture, single molecule/cell detection, single cell sequencing, and molecular evolution.

A High Throughput Phenotypic Screening reveals compounds that counteract premature osteogenic differentiation of HGPS iPS-derived mesenchymal stem cells

PubMed Central

Lo Cicero, Alessandra; Jaskowiak, Anne-Laure; Egesipe, Anne-Laure; Tournois, Johana; Brinon, Benjamin; Pitrez, Patricia R.; Ferreira, Lino; de Sandre-Giovannoli, Annachiara; Levy, Nicolas; Nissan, Xavier

2016-01-01

Hutchinson-Gilford progeria syndrome (HGPS) is a rare fatal genetic disorder that causes systemic accelerated aging in children. Thanks to the pluripotency and self-renewal properties of induced pluripotent stem cells (iPSC), HGPS iPSC-based modeling opens up the possibility of access to different relevant cell types for pharmacological approaches. In this study, 2800 small molecules were explored using high-throughput screening, looking for compounds that could potentially reduce the alkaline phosphatase activity of HGPS mesenchymal stem cells (MSCs) committed into osteogenic differentiation. Results revealed seven compounds that normalized the osteogenic differentiation process and, among these, all-trans retinoic acid and 13-cis-retinoic acid, that also decreased progerin expression. This study highlights the potential of high-throughput drug screening using HGPS iPS-derived cells, in order to find therapeutic compounds for HGPS and, potentially, for other aging-related disorders. PMID:27739443

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

EPA Pesticide Factsheets

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

Robust and Sensitive Analysis of Mouse Knockout Phenotypes

PubMed Central

Karp, Natasha A.; Melvin, David; Mott, Richard F.

2012-01-01

A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student’s t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene’s function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained. PMID:23300663

iPSC-derived neurons as a higher-throughput readout for autism: Promises and pitfalls

PubMed Central

Prilutsky, Daria; Palmer, Nathan P.; Smedemark-Margulies, Niklas; Schlaeger, Thorsten M.; Margulies, David M.; Kohane, Isaac S.

2014-01-01

The elucidation of disease etiologies and establishment of robust, scalable, high-throughput screening assays for autism spectrum disorders (ASDs) have been impeded by both inaccessibility of disease-relevant neuronal tissue and the genetic heterogeneity of the disorder. Neuronal cells derived from induced pluripotent stem cells (iPSCs) from autism patients may circumvent these obstacles and serve as relevant cell models. To date, derived cells are characterized and screened by assessing their neuronal phenotypes. These characterizations are often etiology-specific or lack reproducibility and stability. In this manuscript, we present an overview of efforts to study iPSC-derived neurons as a model for autism, and we explore the plausibility of gene expression profiling as a reproducible and stable disease marker. PMID:24374161

Professor: A motorized field-based phenotyping cart

USDA-ARS?s Scientific Manuscript database

An easy-to-customize, low-cost, low disturbance, motorized proximal sensing cart for field-based high-throughput phenotyping is described. General dimensions, motor specifications, and a remote operation application are given. The cart, named Professor, supports mounting multiple proximal sensors an...

Field-Based High-Throughput Plant Phenotyping Reveals the Temporal Patterns of Quantitative Trait Loci Associated with Stress-Responsive Traits in Cotton

PubMed Central

Pauli, Duke; Andrade-Sanchez, Pedro; Carmo-Silva, A. Elizabete; Gazave, Elodie; French, Andrew N.; Heun, John; Hunsaker, Douglas J.; Lipka, Alexander E.; Setter, Tim L.; Strand, Robert J.; Thorp, Kelly R.; Wang, Sam; White, Jeffrey W.; Gore, Michael A.

2016-01-01

The application of high-throughput plant phenotyping (HTPP) to continuously study plant populations under relevant growing conditions creates the possibility to more efficiently dissect the genetic basis of dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. The evaluation trials were conducted under well-watered and water-limited conditions in a replicated field experiment at a hot, arid location in central Arizona, with trait measurements taken at different times on multiple days across 2010–2012. Canopy temperature, normalized difference vegetation index (NDVI), height, and leaf area index (LAI) displayed moderate-to-high broad-sense heritabilities, as well as varied interactions among genotypes with water regime and time of day. Distinct temporal patterns of quantitative trait loci (QTL) expression were mostly observed for canopy temperature and NDVI, and varied across plant developmental stages. In addition, the strength of correlation between HTPP canopy traits and agronomic traits, such as lint yield, displayed a time-dependent relationship. We also found that the genomic position of some QTL controlling HTPP canopy traits were shared with those of QTL identified for agronomic and physiological traits. This work demonstrates the novel use of a field-based HTPP system to study the genetic basis of stress-adaptive traits in cotton, and these results have the potential to facilitate the development of stress-resilient cotton cultivars. PMID:26818078

web cellHTS2: a web-application for the analysis of high-throughput screening data.

PubMed

Pelz, Oliver; Gilsdorf, Moritz; Boutros, Michael

2010-04-12

The analysis of high-throughput screening data sets is an expanding field in bioinformatics. High-throughput screens by RNAi generate large primary data sets which need to be analyzed and annotated to identify relevant phenotypic hits. Large-scale RNAi screens are frequently used to identify novel factors that influence a broad range of cellular processes, including signaling pathway activity, cell proliferation, and host cell infection. Here, we present a web-based application utility for the end-to-end analysis of large cell-based screening experiments by cellHTS2. The software guides the user through the configuration steps that are required for the analysis of single or multi-channel experiments. The web-application provides options for various standardization and normalization methods, annotation of data sets and a comprehensive HTML report of the screening data analysis, including a ranked hit list. Sessions can be saved and restored for later re-analysis. The web frontend for the cellHTS2 R/Bioconductor package interacts with it through an R-server implementation that enables highly parallel analysis of screening data sets. web cellHTS2 further provides a file import and configuration module for common file formats. The implemented web-application facilitates the analysis of high-throughput data sets and provides a user-friendly interface. web cellHTS2 is accessible online at http://web-cellHTS2.dkfz.de. A standalone version as a virtual appliance and source code for platforms supporting Java 1.5.0 can be downloaded from the web cellHTS2 page. web cellHTS2 is freely distributed under GPL.

High-Throughput Industrial Coatings Research at The Dow Chemical Company.

PubMed

Kuo, Tzu-Chi; Malvadkar, Niranjan A; Drumright, Ray; Cesaretti, Richard; Bishop, Matthew T

2016-09-12

At The Dow Chemical Company, high-throughput research is an active area for developing new industrial coatings products. Using the principles of automation (i.e., using robotic instruments), parallel processing (i.e., prepare, process, and evaluate samples in parallel), and miniaturization (i.e., reduce sample size), high-throughput tools for synthesizing, formulating, and applying coating compositions have been developed at Dow. In addition, high-throughput workflows for measuring various coating properties, such as cure speed, hardness development, scratch resistance, impact toughness, resin compatibility, pot-life, surface defects, among others have also been developed in-house. These workflows correlate well with the traditional coatings tests, but they do not necessarily mimic those tests. The use of such high-throughput workflows in combination with smart experimental designs allows accelerated discovery and commercialization.

High Throughput Screening For Hazard and Risk of Environmental Contaminants

EPA Science Inventory

High throughput toxicity testing provides detailed mechanistic information on the concentration response of environmental contaminants in numerous potential toxicity pathways. High throughput screening (HTS) has several key advantages: (1) expense orders of magnitude less than an...

High-throughput analysis of T-DNA location and structure using sequence capture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Inagaki, Soichi; Henry, Isabelle M.; Lieberman, Meric C.

Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA—genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously,more » using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. As a result, our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.« less

High-throughput analysis of T-DNA location and structure using sequence capture

DOE PAGES

Inagaki, Soichi; Henry, Isabelle M.; Lieberman, Meric C.; ...

2015-10-07

Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA—genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously,more » using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. As a result, our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.« less

Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis

PubMed Central

Paintdakhi, Ahmad; Parry, Bradley; Campos, Manuel; Irnov, Irnov; Elf, Johan; Surovtsev, Ivan; Jacobs-Wagner, Christine

2016-01-01

Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today’s single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals, and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis, and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills. PMID:26538279

Empirical analysis of RNA robustness and evolution using high-throughput sequencing of ribozyme reactions.

PubMed

Hayden, Eric J

2016-08-15

RNA molecules provide a realistic but tractable model of a genotype to phenotype relationship. This relationship has been extensively investigated computationally using secondary structure prediction algorithms. Enzymatic RNA molecules, or ribozymes, offer access to genotypic and phenotypic information in the laboratory. Advancements in high-throughput sequencing technologies have enabled the analysis of sequences in the lab that now rivals what can be accomplished computationally. This has motivated a resurgence of in vitro selection experiments and opened new doors for the analysis of the distribution of RNA functions in genotype space. A body of computational experiments has investigated the persistence of specific RNA structures despite changes in the primary sequence, and how this mutational robustness can promote adaptations. This article summarizes recent approaches that were designed to investigate the role of mutational robustness during the evolution of RNA molecules in the laboratory, and presents theoretical motivations, experimental methods and approaches to data analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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.

Phenotypic mutant library: potential for gene discovery

USDA-ARS?s Scientific Manuscript database

The rapid development of high throughput and affordable Next- Generation Sequencing (NGS) techniques has renewed interest in gene discovery using forward genetics. The conventional forward genetic approach starts with isolation of mutants with a phenotype of interest, mapping the mutation within a s...

Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae)

PubMed Central

2011-01-01

Background Cucurbita pepo belongs to the Cucurbitaceae family. The "Zucchini" types rank among the highest-valued vegetables worldwide, and other C. pepo and related Cucurbita spp., are food staples and rich sources of fat and vitamins. A broad range of genomic tools are today available for other cucurbits that have become models for the study of different metabolic processes. However, these tools are still lacking in the Cucurbita genus, thus limiting gene discovery and the process of breeding. Results We report the generation of a total of 512,751 C. pepo EST sequences, using 454 GS FLX Titanium technology. ESTs were obtained from normalized cDNA libraries (root, leaves, and flower tissue) prepared using two varieties with contrasting phenotypes for plant, flowering and fruit traits, representing the two C. pepo subspecies: subsp. pepo cv. Zucchini and subsp. ovifera cv Scallop. De novo assembling was performed to generate a collection of 49,610 Cucurbita unigenes (average length of 626 bp) that represent the first transcriptome of the species. Over 60% of the unigenes were functionally annotated and assigned to one or more Gene Ontology terms. The distributions of Cucurbita unigenes followed similar tendencies than that reported for Arabidopsis or melon, suggesting that the dataset may represent the whole Cucurbita transcriptome. About 34% unigenes were detected to have known orthologs of Arabidopsis or melon, including genes potentially involved in disease resistance, flowering and fruit quality. Furthermore, a set of 1,882 unigenes with SSR motifs and 9,043 high confidence SNPs between Zucchini and Scallop were identified, of which 3,538 SNPs met criteria for use with high throughput genotyping platforms, and 144 could be detected as CAPS. A set of markers were validated, being 80% of them polymorphic in a set of variable C. pepo and C. moschata accessions. Conclusion We present the first broad survey of gene sequences and allelic variation in C. pepo, where

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype-phenotype relationships and its relevance to crop improvement.

PubMed

Cobb, Joshua N; Declerck, Genevieve; Greenberg, Anthony; Clark, Randy; McCouch, Susan

2013-04-01

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

Optimization and high-throughput screening of antimicrobial peptides.

PubMed

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.

HTP-OligoDesigner: An Online Primer Design Tool for High-Throughput Gene Cloning and Site-Directed Mutagenesis.

PubMed

Camilo, Cesar M; Lima, Gustavo M A; Maluf, Fernando V; Guido, Rafael V C; Polikarpov, Igor

2016-01-01

Following burgeoning genomic and transcriptomic sequencing data, biochemical and molecular biology groups worldwide are implementing high-throughput cloning and mutagenesis facilities in order to obtain a large number of soluble proteins for structural and functional characterization. Since manual primer design can be a time-consuming and error-generating step, particularly when working with hundreds of targets, the automation of primer design process becomes highly desirable. HTP-OligoDesigner was created to provide the scientific community with a simple and intuitive online primer design tool for both laboratory-scale and high-throughput projects of sequence-independent gene cloning and site-directed mutagenesis and a Tm calculator for quick queries.

Mapper: high throughput maskless lithography

NASA Astrophysics Data System (ADS)

Kuiper, V.; Kampherbeek, B. J.; Wieland, M. J.; de Boer, G.; ten Berge, G. F.; Boers, J.; Jager, R.; van de Peut, T.; Peijster, J. J. M.; Slot, E.; Steenbrink, S. W. H. K.; Teepen, T. F.; van Veen, A. H. V.

2009-01-01

Maskless electron beam lithography, or electron beam direct write, has been around for a long time in the semiconductor industry and was pioneered from the mid-1960s onwards. This technique has been used for mask writing applications as well as device engineering and in some cases chip manufacturing. However because of its relatively low throughput compared to optical lithography, electron beam lithography has never been the mainstream lithography technology. To extend optical lithography double patterning, as a bridging technology, and EUV lithography are currently explored. Irrespective of the technical viability of both approaches, one thing seems clear. They will be expensive [1]. MAPPER Lithography is developing a maskless lithography technology based on massively-parallel electron-beam writing with high speed optical data transport for switching the electron beams. In this way optical columns can be made with a throughput of 10-20 wafers per hour. By clustering several of these columns together high throughputs can be realized in a small footprint. This enables a highly cost-competitive alternative to double patterning and EUV alternatives. In 2007 MAPPER obtained its Proof of Lithography milestone by exposing in its Demonstrator 45 nm half pitch structures with 110 electron beams in parallel, where all the beams where individually switched on and off [2]. In 2008 MAPPER has taken a next step in its development by building several tools. A new platform has been designed and built which contains a 300 mm wafer stage, a wafer handler and an electron beam column with 110 parallel electron beams. This manuscript describes the first patterning results with this 300 mm platform.

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

EPA Science Inventory

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...

Experimental Design for Combinatorial and High Throughput Materials Development

NASA Astrophysics Data System (ADS)

Cawse, James N.

2002-12-01

In the past decade, combinatorial and high throughput experimental methods have revolutionized the pharmaceutical industry, allowing researchers to conduct more experiments in a week than was previously possible in a year. Now high throughput experimentation is rapidly spreading from its origins in the pharmaceutical world to larger industrial research establishments such as GE and DuPont, and even to smaller companies and universities. Consequently, researchers need to know the kinds of problems, desired outcomes, and appropriate patterns for these new strategies. Editor James Cawse's far-reaching study identifies and applies, with specific examples, these important new principles and techniques. Experimental Design for Combinatorial and High Throughput Materials Development progresses from methods that are now standard, such as gradient arrays, to mathematical developments that are breaking new ground. The former will be particularly useful to researchers entering the field, while the latter should inspire and challenge advanced practitioners. The book's contents are contributed by leading researchers in their respective fields. Chapters include: -High Throughput Synthetic Approaches for the Investigation of Inorganic Phase Space -Combinatorial Mapping of Polymer Blends Phase Behavior -Split-Plot Designs -Artificial Neural Networks in Catalyst Development -The Monte Carlo Approach to Library Design and Redesign This book also contains over 200 useful charts and drawings. Industrial chemists, chemical engineers, materials scientists, and physicists working in combinatorial and high throughput chemistry will find James Cawse's study to be an invaluable resource.

High Throughput Screening for Anti–Trypanosoma cruzi Drug Discovery

PubMed Central

Alonso-Padilla, Julio; Rodríguez, Ana

2014-01-01

The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti–T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti–T. cruzi drug entities in the near future, are reviewed here. PMID:25474364

High throughput screening for anti-Trypanosoma cruzi drug discovery.

PubMed

Alonso-Padilla, Julio; Rodríguez, Ana

2014-12-01

The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti-T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for high throughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti-T. cruzi drug entities in the near future, are reviewed here.

Characterization of a Wheat Breeders' Array suitable for high-throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum).

PubMed

Allen, Alexandra M; Winfield, Mark O; Burridge, Amanda J; Downie, Rowena C; Benbow, Harriet R; Barker, Gary L A; Wilkinson, Paul A; Coghill, Jane; Waterfall, Christy; Davassi, Alessandro; Scopes, Geoff; Pirani, Ali; Webster, Teresa; Brew, Fiona; Bloor, Claire; Griffiths, Simon; Bentley, Alison R; Alda, Mark; Jack, Peter; Phillips, Andrew L; Edwards, Keith J

2017-03-01

Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism-based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high-density Affymetrix Axiom ® genotyping array (the Wheat Breeders' Array), in a high-throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders' Array is also suitable for generating high-density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site 'CerealsDB'. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Improvement of uridine production of Bacillus subtilis by atmospheric and room temperature plasma mutagenesis and high-throughput screening

PubMed Central

Li, Guoliang; Yuan, Hui; Zhang, Hongchao; Li, Yanjun; Xie, Xixian; Chen, Ning

2017-01-01

In the present study, a novel breeding strategy of atmospheric and room temperature plasma (ARTP) mutagenesis was used to improve the uridine production of engineered Bacillus subtilis TD12np. A high-throughput screening method was established using both resistant plates and 96-well microplates to select the ideal mutants with diverse phenotypes. Mutant F126 accumulated 5.7 and 30.3 g/L uridine after 30 h in shake-flask and 48 h in fed-batch fermentation, respectively, which represented a 4.4- and 8.7-fold increase over the parent strain. Sequence analysis of the pyrimidine nucleotide biosynthetic operon in the representative mutants showed that proline 1016 and glutamate 949 in the large subunit of B. subtilis carbamoyl phosphate synthetase were of importance for the allosteric regulation caused by uridine 5′-monophosphate. The proposed mutation method with efficient high-throughput screening assay was proved to be an appropriate strategy to obtain uridine-overproducing strain. PMID:28472077

Improvement of uridine production of Bacillus subtilis by atmospheric and room temperature plasma mutagenesis and high-throughput screening.

PubMed

Fan, Xiaoguang; Wu, Heyun; Li, Guoliang; Yuan, Hui; Zhang, Hongchao; Li, Yanjun; Xie, Xixian; Chen, Ning

2017-01-01

In the present study, a novel breeding strategy of atmospheric and room temperature plasma (ARTP) mutagenesis was used to improve the uridine production of engineered Bacillus subtilis TD12np. A high-throughput screening method was established using both resistant plates and 96-well microplates to select the ideal mutants with diverse phenotypes. Mutant F126 accumulated 5.7 and 30.3 g/L uridine after 30 h in shake-flask and 48 h in fed-batch fermentation, respectively, which represented a 4.4- and 8.7-fold increase over the parent strain. Sequence analysis of the pyrimidine nucleotide biosynthetic operon in the representative mutants showed that proline 1016 and glutamate 949 in the large subunit of B. subtilis carbamoyl phosphate synthetase were of importance for the allosteric regulation caused by uridine 5'-monophosphate. The proposed mutation method with efficient high-throughput screening assay was proved to be an appropriate strategy to obtain uridine-overproducing strain.

High-throughput sequence alignment using Graphics Processing Units

PubMed Central

Schatz, Michael C; Trapnell, Cole; Delcher, Arthur L; Varshney, Amitabh

2007-01-01

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. PMID:18070356

Direct assembling methodologies for high-throughput bioscreening

PubMed Central

Rodríguez-Dévora, Jorge I.; Shi, Zhi-dong; Xu, Tao

2012-01-01

Over the last few decades, high-throughput (HT) bioscreening, a technique that allows rapid screening of biochemical compound libraries against biological targets, has been widely used in drug discovery, stem cell research, development of new biomaterials, and genomics research. To achieve these ambitions, scaffold-free (or direct) assembly of biological entities of interest has become critical. Appropriate assembling methodologies are required to build an efficient HT bioscreening platform. The development of contact and non-contact assembling systems as a practical solution has been driven by a variety of essential attributes of the bioscreening system, such as miniaturization, high throughput, and high precision. The present article reviews recent progress on these assembling technologies utilized for the construction of HT bioscreening platforms. PMID:22021162

Database for High Throughput Screening Hits (dHITS): a simple tool to retrieve gene specific phenotypes from systematic screens done in yeast.

PubMed

Chuartzman, Silvia G; Schuldiner, Maya

2018-03-25

In the last decade several collections of Saccharomyces cerevisiae yeast strains have been created. In these collections every gene is modified in a similar manner such as by a deletion or the addition of a protein tag. Such libraries have enabled a diversity of systematic screens, giving rise to large amounts of information regarding gene functions. However, often papers describing such screens focus on a single gene or a small set of genes and all other loci affecting the phenotype of choice ('hits') are only mentioned in tables that are provided as supplementary material and are often hard to retrieve or search. To help unify and make such data accessible, we have created a Database of High Throughput Screening Hits (dHITS). The dHITS database enables information to be obtained about screens in which genes of interest were found as well as the other genes that came up in that screen - all in a readily accessible and downloadable format. The ability to query large lists of genes at the same time provides a platform to easily analyse hits obtained from transcriptional analyses or other screens. We hope that this platform will serve as a tool to facilitate investigation of protein functions to the yeast community. © 2018 The Authors Yeast Published by John Wiley & Sons Ltd.

The micro-Petri dish, a million-well growth chip for the culture and high-throughput screening of microorganisms.

PubMed

Ingham, Colin J; Sprenkels, Ad; Bomer, Johan; Molenaar, Douwe; van den Berg, Albert; van Hylckama Vlieg, Johan E T; de Vos, Willem M

2007-11-13

A miniaturized, disposable microbial culture chip has been fabricated by microengineering a highly porous ceramic sheet with up to one million growth compartments. This versatile culture format, with discrete compartments as small as 7 x 7 mum, allowed the growth of segregated microbial samples at an unprecedented density. The chip has been used for four complementary applications in microbiology. (i) As a fast viable counting system that showed a dynamic range of over 10,000, a low degree of bias, and a high culturing efficiency. (ii) In high-throughput screening, with the recovery of 1 fluorescent microcolony in 10,000. (iii) In screening for an enzyme-based, nondominant phenotype by the targeted recovery of Escherichia coli transformed with the plasmid pUC18, based on expression of the lacZ reporter gene without antibiotic-resistance selection. The ease of rapid, successive changes in the environment of the organisms on the chip, needed for detection of beta-galactosidase activity, highlights an advantageous feature that was also used to screen a metagenomic library for the same activity. (iv) In high-throughput screening of >200,000 isolates from Rhine water based on metabolism of a fluorogenic organophosphate compound, resulting in the recovery of 22 microcolonies with the desired phenotype. These isolates were predicted, on the basis of rRNA sequence, to include six new species. These four applications suggest that the potential for such simple, readily manufactured chips to impact microbial culture is extensive and may facilitate the full automation and multiplexing of microbial culturing, screening, counting, and selection.

High throughput imaging cytometer with acoustic focussing.

PubMed

Zmijan, Robert; Jonnalagadda, Umesh S; Carugo, Dario; Kochi, Yu; Lemm, Elizabeth; Packham, Graham; Hill, Martyn; Glynne-Jones, Peter

2015-10-31

We demonstrate an imaging flow cytometer that uses acoustic levitation to assemble cells and other particles into a sheet structure. This technique enables a high resolution, low noise CMOS camera to capture images of thousands of cells with each frame. While ultrasonic focussing has previously been demonstrated for 1D cytometry systems, extending the technology to a planar, much higher throughput format and integrating imaging is non-trivial, and represents a significant jump forward in capability, leading to diagnostic possibilities not achievable with current systems. A galvo mirror is used to track the images of the moving cells permitting exposure times of 10 ms at frame rates of 50 fps with motion blur of only a few pixels. At 80 fps, we demonstrate a throughput of 208 000 beads per second. We investigate the factors affecting motion blur and throughput, and demonstrate the system with fluorescent beads, leukaemia cells and a chondrocyte cell line. Cells require more time to reach the acoustic focus than beads, resulting in lower throughputs; however a longer device would remove this constraint.

High-throughput GPU-based LDPC decoding

NASA Astrophysics Data System (ADS)

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.

High-throughput protein analysis integrating bioinformatics and experimental assays

PubMed Central

del Val, Coral; Mehrle, Alexander; Falkenhahn, Mechthild; Seiler, Markus; Glatting, Karl-Heinz; Poustka, Annemarie; Suhai, Sandor; Wiemann, Stefan

2004-01-01

The wealth of transcript information that has been made publicly available in recent years requires the development of high-throughput functional genomics and proteomics approaches for its analysis. Such approaches need suitable data integration procedures and a high level of automation in order to gain maximum benefit from the results generated. We have designed an automatic pipeline to analyse annotated open reading frames (ORFs) stemming from full-length cDNAs produced mainly by the German cDNA Consortium. The ORFs are cloned into expression vectors for use in large-scale assays such as the determination of subcellular protein localization or kinase reaction specificity. Additionally, all identified ORFs undergo exhaustive bioinformatic analysis such as similarity searches, protein domain architecture determination and prediction of physicochemical characteristics and secondary structure, using a wide variety of bioinformatic methods in combination with the most up-to-date public databases (e.g. PRINTS, BLOCKS, INTERPRO, PROSITE SWISSPROT). Data from experimental results and from the bioinformatic analysis are integrated and stored in a relational database (MS SQL-Server), which makes it possible for researchers to find answers to biological questions easily, thereby speeding up the selection of targets for further analysis. The designed pipeline constitutes a new automatic approach to obtaining and administrating relevant biological data from high-throughput investigations of cDNAs in order to systematically identify and characterize novel genes, as well as to comprehensively describe the function of the encoded proteins. PMID:14762202

A Low-Cost, Reliable, High-Throughput System for Rodent Behavioral Phenotyping in a Home Cage Environment

PubMed Central

Parkison, Steven A.; Carlson, Jay D.; Chaudoin, Tammy R.; Hoke, Traci A.; Schenk, A. Katrin; Goulding, Evan H.; Pérez, Lance C.; Bonasera, Stephen J.

2016-01-01

Inexpensive, high-throughput, low maintenance systems for precise temporal and spatial measurement of mouse home cage behavior (including movement, feeding, and drinking) are required to evaluate products from large scale pharmaceutical design and genetic lesion programs. These measurements are also required to interpret results from more focused behavioral assays. We describe the design and validation of a highly-scalable, reliable mouse home cage behavioral monitoring system modeled on a previously described, one-of-a-kind system [1]. Mouse position was determined by solving static equilibrium equations describing the force and torques acting on the system strain gauges; feeding events were detected by a photobeam across the food hopper, and drinking events were detected by a capacitive lick sensor. Validation studies show excellent agreement between mouse position and drinking events measured by the system compared with video-based observation – a gold standard in neuroscience. PMID:23366406

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

PubMed

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

2017-10-01

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

High throughput platforms for structural genomics of integral membrane proteins.

PubMed

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.

Molecular characterization of a novel rhabdovirus infecting blackcurrant identified by high-throughput sequencing.

PubMed

Wu, L-P; Yang, T; Liu, H-W; Postman, J; Li, R

2018-05-01

A large contig with sequence similarities to several nucleorhabdoviruses was identified by high-throughput sequencing analysis from a black currant (Ribes nigrum L.) cultivar. The complete genome sequence of this new nucleorhabdovirus is 14,432 nucleotides long. Its genomic organization is very similar to those of unsegmented plant rhabdoviruses, containing six open reading frames in the order 3'-N-P-P3-M-G-L-5. The virus, which is provisionally named "black currant-associated rhabdovirus", is 41-52% identical in its genome nucleotide sequence to other nucleorhabdoviruses and may represent a new species in the genus Nucleorhabdovirus.

A high-throughput comparative characterization of laser-induced soft tissue damage using 3D digital microscopy.

PubMed

Das, Debobrato; Reed, Stephanie; Klokkevold, Perry R; Wu, Benjamin M

2013-02-01

3D digital microscopy was used to develop a rapid alternative approach to quantify the effects of specific laser parameters on soft tissue ablation and charring in vitro without the use of conventional tissue processing techniques. Two diode lasers operating at 810 and 980 nm wavelengths were used to ablate three tissue types (bovine liver, turkey breast, and bovine muscle) at varying laser power (0.3, 1.0, and 2.0 W) and velocities (1-50 mm/s). Spectrophotometric analyses were performed on each tissue to determine tissue-specific absorption coefficients and were considered in creating wavelength-dependent energy attenuation models to evaluate minimum heat of tissue ablations. 3D surface contour profiles characterizing tissue damage revealed that ablation depth and tissue charring increased with laser power and decreased with lateral velocity independent of wavelength and tissue type. While bovine liver ablation and charring were statistically higher at 810 than 980 nm (p < 0.05), turkey breast and bovine muscle ablated and charred more at 980 than 810 nm (p < 0.05). Spectrophotometric analysis revealed that bovine liver tissue had a greater tissue-specific absorption coefficient at 810 than 980 nm, while turkey breast and bovine muscle had a larger absorption coefficient at 980 nm (p < 0.05). This rapid 3D microscopic analysis of robot-driven laser ablation yielded highly reproducible data that supported well-defined trends related to laser-tissue interactions and enabled high throughput characterization of many laser-tissue permutations. Since 3D microscopy quantifies entire lesions without altering the tissue specimens, conventional and immunohistologic techniques can be used, if desired, to further interrogate specific sections of the digitized lesions.

Discovery of New Compounds Active against Plasmodium falciparum by High Throughput Screening of Microbial Natural Products.

PubMed

Pérez-Moreno, Guiomar; Cantizani, Juan; Sánchez-Carrasco, Paula; Ruiz-Pérez, Luis Miguel; Martín, Jesús; El Aouad, Noureddine; Pérez-Victoria, Ignacio; Tormo, José Rubén; González-Menendez, Víctor; González, Ignacio; de Pedro, Nuria; Reyes, Fernando; Genilloud, Olga; Vicente, Francisca; González-Pacanowska, Dolores

2016-01-01

Due to the low structural diversity within the set of antimalarial drugs currently available in the clinic and the increasing number of cases of resistance, there is an urgent need to find new compounds with novel modes of action to treat the disease. Microbial natural products are characterized by their large diversity provided in terms of the chemical complexity of the compounds and the novelty of structures. Microbial natural products extracts have been underexplored in the search for new antiparasitic drugs and even more so in the discovery of new antimalarials. Our objective was to find new druggable natural products with antimalarial properties from the MEDINA natural products collection, one of the largest natural product libraries harboring more than 130,000 microbial extracts. In this work, we describe the optimization process and the results of a phenotypic high throughput screen (HTS) based on measurements of Plasmodium lactate dehydrogenase. A subset of more than 20,000 extracts from the MEDINA microbial products collection has been explored, leading to the discovery of 3 new compounds with antimalarial activity. In addition, we report on the novel antiplasmodial activity of 4 previously described natural products.

Characterization of the fecal microbiota using high-throughput sequencing reveals a stable microbial community during storage.

PubMed

Carroll, Ian M; Ringel-Kulka, Tamar; Siddle, Jennica P; Klaenhammer, Todd R; Ringel, Yehuda

2012-01-01

The handling and treatment of biological samples is critical when characterizing the composition of the intestinal microbiota between different ecological niches or diseases. Specifically, exposure of fecal samples to room temperature or long term storage in deep freezing conditions may alter the composition of the microbiota. Thus, we stored fecal samples at room temperature and monitored the stability of the microbiota over twenty four hours. We also investigated the stability of the microbiota in fecal samples during a six month storage period at -80°C. As the stability of the fecal microbiota may be affected by intestinal disease, we analyzed two healthy controls and two patients with irritable bowel syndrome (IBS). We used high-throughput pyrosequencing of the 16S rRNA gene to characterize the microbiota in fecal samples stored at room temperature or -80°C at six and seven time points, respectively. The composition of microbial communities in IBS patients and healthy controls were determined and compared using the Quantitative Insights Into Microbial Ecology (QIIME) pipeline. The composition of the microbiota in fecal samples stored for different lengths of time at room temperature or -80°C clustered strongly based on the host each sample originated from. Our data demonstrates that fecal samples exposed to room or deep freezing temperatures for up to twenty four hours and six months, respectively, exhibit a microbial composition and diversity that shares more identity with its host of origin than any other sample.

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

High-Throughput Density Measurement Using Magnetic Levitation.

PubMed

Ge, Shencheng; Wang, Yunzhe; Deshler, Nicolas J; Preston, Daniel J; Whitesides, George M

2018-06-20

This work describes the development of an integrated analytical system that enables high-throughput density measurements of diamagnetic particles (including cells) using magnetic levitation (MagLev), 96-well plates, and a flatbed scanner. MagLev is a simple and useful technique with which to carry out density-based analysis and separation of a broad range of diamagnetic materials with different physical forms (e.g., liquids, solids, gels, pastes, gums, etc.); one major limitation, however, is the capacity to perform high-throughput density measurements. This work addresses this limitation by (i) re-engineering the shape of the magnetic fields so that the MagLev system is compatible with 96-well plates, and (ii) integrating a flatbed scanner (and simple optical components) to carry out imaging of the samples that levitate in the system. The resulting system is compatible with both biological samples (human erythrocytes) and nonbiological samples (simple liquids and solids, such as 3-chlorotoluene, cholesterol crystals, glass beads, copper powder, and polymer beads). The high-throughput capacity of this integrated MagLev system will enable new applications in chemistry (e.g., analysis and separation of materials) and biochemistry (e.g., cellular responses under environmental stresses) in a simple and label-free format on the basis of a universal property of all matter, i.e., density.

RhizoTubes as a new tool for high throughput imaging of plant root development and architecture: test, comparison with pot grown plants and validation.

PubMed

Jeudy, Christian; Adrian, Marielle; Baussard, Christophe; Bernard, Céline; Bernaud, Eric; Bourion, Virginie; Busset, Hughes; Cabrera-Bosquet, Llorenç; Cointault, Frédéric; Han, Simeng; Lamboeuf, Mickael; Moreau, Delphine; Pivato, Barbara; Prudent, Marion; Trouvelot, Sophie; Truong, Hoai Nam; Vernoud, Vanessa; Voisin, Anne-Sophie; Wipf, Daniel; Salon, Christophe

2016-01-01

In order to maintain high yields while saving water and preserving non-renewable resources and thus limiting the use of chemical fertilizer, it is crucial to select plants with more efficient root systems. This could be achieved through an optimization of both root architecture and root uptake ability and/or through the improvement of positive plant interactions with microorganisms in the rhizosphere. The development of devices suitable for high-throughput phenotyping of root structures remains a major bottleneck. Rhizotrons suitable for plant growth in controlled conditions and non-invasive image acquisition of plant shoot and root systems (RhizoTubes) are described. These RhizoTubes allow growing one to six plants simultaneously, having a maximum height of 1.1 m, up to 8 weeks, depending on plant species. Both shoot and root compartment can be imaged automatically and non-destructively throughout the experiment thanks to an imaging cabin (RhizoCab). RhizoCab contains robots and imaging equipment for obtaining high-resolution pictures of plant roots. Using this versatile experimental setup, we illustrate how some morphometric root traits can be determined for various species including model (Medicago truncatula), crops (Pisum sativum, Brassica napus, Vitis vinifera, Triticum aestivum) and weed (Vulpia myuros) species grown under non-limiting conditions or submitted to various abiotic and biotic constraints. The measurement of the root phenotypic traits using this system was compared to that obtained using "classic" growth conditions in pots. This integrated system, to include 1200 Rhizotubes, will allow high-throughput phenotyping of plant shoots and roots under various abiotic and biotic environmental conditions. Our system allows an easy visualization or extraction of roots and measurement of root traits for high-throughput or kinetic analyses. The utility of this system for studying root system architecture will greatly facilitate the identification of

Economic consequences of high throughput maskless lithography

NASA Astrophysics Data System (ADS)

Hartley, John G.; Govindaraju, Lakshmi

2005-11-01

Many people in the semiconductor industry bemoan the high costs of masks and view mask cost as one of the significant barriers to bringing new chip designs to market. All that is needed is a viable maskless technology and the problem will go away. Numerous sites around the world are working on maskless lithography but inevitably, the question asked is "Wouldn't a one wafer per hour maskless tool make a really good mask writer?" Of course, the answer is yes, the hesitation you hear in the answer isn't based on technology concerns, it's financial. The industry needs maskless lithography because mask costs are too high. Mask costs are too high because mask pattern generators (PG's) are slow and expensive. If mask PG's become much faster, mask costs go down, the maskless market goes away and the PG supplier is faced with an even smaller tool demand from the mask shops. Technical success becomes financial suicide - or does it? In this paper we will present the results of a model that examines some of the consequences of introducing high throughput maskless pattern generation. Specific features in the model include tool throughput for masks and wafers, market segmentation by node for masks and wafers and mask cost as an entry barrier to new chip designs. How does the availability of low cost masks and maskless tools affect the industries tool makeup and what is the ultimate potential market for high throughput maskless pattern generators?

A high-throughput virus-induced gene silencing protocol identifies genes involved in multi-stress tolerance

PubMed Central

2013-01-01

Background Understanding the function of a particular gene under various stresses is important for engineering plants for broad-spectrum stress tolerance. Although virus-induced gene silencing (VIGS) has been used to characterize genes involved in abiotic stress tolerance, currently available gene silencing and stress imposition methodology at the whole plant level is not suitable for high-throughput functional analyses of genes. This demands a robust and reliable methodology for characterizing genes involved in abiotic and multi-stress tolerance. Results Our methodology employs VIGS-based gene silencing in leaf disks combined with simple stress imposition and effect quantification methodologies for easy and faster characterization of genes involved in abiotic and multi-stress tolerance. By subjecting leaf disks from gene-silenced plants to various abiotic stresses and inoculating silenced plants with various pathogens, we show the involvement of several genes for multi-stress tolerance. In addition, we demonstrate that VIGS can be used to characterize genes involved in thermotolerance. Our results also showed the functional relevance of NtEDS1 in abiotic stress, NbRBX1 and NbCTR1 in oxidative stress; NtRAR1 and NtNPR1 in salinity stress; NbSOS1 and NbHSP101 in biotic stress; and NtEDS1, NbETR1, NbWRKY2 and NbMYC2 in thermotolerance. Conclusions In addition to widening the application of VIGS, we developed a robust, easy and high-throughput methodology for functional characterization of genes involved in multi-stress tolerance. PMID:24289810

Identification and Characterization of Influenza Virus Entry Inhibitors through Dual Myxovirus High-Throughput Screening.

PubMed

Weisshaar, Marco; Cox, Robert; Morehouse, Zachary; Kumar Kyasa, Shiva; Yan, Dan; Oberacker, Phil; Mao, Shuli; Golden, Jennifer E; Lowen, Anice C; Natchus, Michael G; Plemper, Richard K

2016-08-15

fully replication-competent third-generation IAV reporter strain to a large-scale high-throughput screen (HTS) drug discovery campaign, allowing multicycle infection and screening in physiologically relevant human respiratory cells. A large number of potential druggable targets was thus chemically interrogated, but mechanistic characterization, positive target identification, and resistance profiling demonstrated that three chemically promising and structurally distinct hit classes selected for further analysis all block HA-mediated membrane fusion. Viral escape from inhibition could be achieved through primary and secondary resistance mechanisms. In silico docking predicted compound binding to a microdomain located at the membrane-distal site of the prefusion HA stalk that was also previously suggested as a target site for chemically unrelated HA inhibitors. This study identifies an unexpected chemodominance of the HA stalk microdomain for small-molecule inhibitors in IAV inhibitor screening campaigns and highlights a novel mechanism of cooperative resistance to IAV entry blockers. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Identification and Characterization of Influenza Virus Entry Inhibitors through Dual Myxovirus High-Throughput Screening

PubMed Central

Weisshaar, Marco; Cox, Robert; Morehouse, Zachary; Kumar Kyasa, Shiva; Yan, Dan; Oberacker, Phil; Mao, Shuli; Lowen, Anice C.; Natchus, Michael G.

2016-01-01

the first to apply a fully replication-competent third-generation IAV reporter strain to a large-scale high-throughput screen (HTS) drug discovery campaign, allowing multicycle infection and screening in physiologically relevant human respiratory cells. A large number of potential druggable targets was thus chemically interrogated, but mechanistic characterization, positive target identification, and resistance profiling demonstrated that three chemically promising and structurally distinct hit classes selected for further analysis all block HA-mediated membrane fusion. Viral escape from inhibition could be achieved through primary and secondary resistance mechanisms. In silico docking predicted compound binding to a microdomain located at the membrane-distal site of the prefusion HA stalk that was also previously suggested as a target site for chemically unrelated HA inhibitors. This study identifies an unexpected chemodominance of the HA stalk microdomain for small-molecule inhibitors in IAV inhibitor screening campaigns and highlights a novel mechanism of cooperative resistance to IAV entry blockers. PMID:27252534

Unbiased Characterization of Anopheles Mosquito Blood Meals by Targeted High-Throughput Sequencing

PubMed Central

Logue, Kyle; Keven, John Bosco; Cannon, Matthew V.; Reimer, Lisa; Siba, Peter; Walker, Edward D.; Zimmerman, Peter A.; Serre, David

2016-01-01

Understanding mosquito host choice is important for assessing vector competence or identifying disease reservoirs. Unfortunately, the availability of an unbiased method for comprehensively evaluating the composition of insect blood meals is very limited, as most current molecular assays only test for the presence of a few pre-selected species. These approaches also have limited ability to identify the presence of multiple mammalian hosts in a single blood meal. Here, we describe a novel high-throughput sequencing method that enables analysis of 96 mosquitoes simultaneously and provides a comprehensive and quantitative perspective on the composition of each blood meal. We validated in silico that universal primers targeting the mammalian mitochondrial 16S ribosomal RNA genes (16S rRNA) should amplify more than 95% of the mammalian 16S rRNA sequences present in the NCBI nucleotide database. We applied this method to 442 female Anopheles punctulatus s. l. mosquitoes collected in Papua New Guinea (PNG). While human (52.9%), dog (15.8%) and pig (29.2%) were the most common hosts identified in our study, we also detected DNA from mice, one marsupial species and two bat species. Our analyses also revealed that 16.3% of the mosquitoes fed on more than one host. Analysis of the human mitochondrial hypervariable region I in 102 human blood meals showed that 5 (4.9%) of the mosquitoes unambiguously fed on more than one person. Overall, analysis of PNG mosquitoes illustrates the potential of this approach to identify unsuspected hosts and characterize mixed blood meals, and shows how this approach can be adapted to evaluate inter-individual variations among human blood meals. Furthermore, this approach can be applied to any disease-transmitting arthropod and can be easily customized to investigate non-mammalian host sources. PMID:26963245

A high-throughput fluorescence polarization assay for inhibitors of gyrase B.

PubMed

Glaser, Bryan T; Malerich, Jeremiah P; Duellman, Sarah J; Fong, Julie; Hutson, Christopher; Fine, Richard M; Keblansky, Boris; Tang, Mary J; Madrid, Peter B

2011-02-01

DNA gyrase, a type II topoisomerase that introduces negative supercoils into DNA, is a validated antibacterial drug target. The holoenzyme is composed of 2 subunits, gyrase A (GyrA) and gyrase B (GyrB), which form a functional A(2)B(2) heterotetramer required for bacterial viability. A novel fluorescence polarization (FP) assay has been developed and optimized to detect inhibitors that bind to the adenosine triphosphate (ATP) binding domain of GyrB. Guided by the crystal structure of the natural product novobiocin bound to GyrB, a novel novobiocin-Texas Red probe (Novo-TRX) was designed and synthesized for use in a high-throughput FP assay. The binding kinetics of the interaction of Novo-TRX with GyrB from Francisella tularensis has been characterized, as well as the effect of common buffer additives on the interaction. The assay was developed into a 21-µL, 384-well assay format and has been validated for use in high-throughput screening against a collection of Food and Drug Administration-approved compounds. The assay performed with an average Z' factor of 0.80 and was able to identify GyrB inhibitors from a screening library.

High- and low-throughput scoring of fat mass and body fat distribution in C. elegans

PubMed Central

Wählby, Carolina; Lee-Conery, Annie; Bray, Mark-Anthony; Kamentsky, Lee; Larkins-Ford, Jonah; Sokolnicki, Katherine L.; Veneskey, Matthew; Michaels, Kerry; Carpenter, Anne E.; O’Rourke, Eyleen J.

2014-01-01

Fat accumulation is a complex phenotype affected by factors such as neuroendocrine signaling, feeding, activity, and reproductive output. Accordingly, the most informative screens for genes and compounds affecting fat accumulation would be those carried out in whole living animals. Caenorhabditis elegans is a well-established and effective model organism, especially for biological processes that involve organ systems and multicellular interactions, such as metabolism. Every cell in the transparent body of C. elegans is visible under a light microscope. Consequently, an accessible and reliable method to visualize worm lipid-droplet fat depots would make C. elegans the only metazoan in which genes affecting not only fat mass but also body fat distribution could be assessed at a genome-wide scale. Here we present a radical improvement in oil red O worm staining together with high-throughput image-based phenotyping. The three-step sample preparation method is robust, formaldehyde-free, and inexpensive, and requires only 15 minutes of hands-on time to process a 96-well plate. Together with our free and user-friendly automated image analysis package, this method enables C. elegans sample preparation and phenotype scoring at a scale that is compatible with genome-wide screens. Thus we present a feasible approach to small-scale phenotyping and large-scale screening for genetic and/or chemical perturbations that lead to alterations in fat quantity and distribution in whole animals. PMID:24784529

Characterization of biomolecular nanoconjugates by high-throughput delivery and spectroscopic difference

PubMed Central

DeLong, Robert K; Risor, Azure; Kanomata, Masaaki; Laymon, Amanda; Jones, Brooke; Zimmerman, Scott D; Williams, Joseph; Witkowski, Colette; Warner, Mathew; Ruff, Michael; Garrad, Richard; Fallon, John K; Hickey, Anthony J; Sedaghat-Herati, Reza

2013-01-01

Aims Nanoparticle conjugates have the potential for delivering siRNA, splice-shifting oligomers or nucleic acid vaccines, and can be applicable to anticancer therapeutics. This article compares tripartite conjugates with gold nanoparticles or synthetic methoxypoly(ethylene glycol)-block-polyamidoamine dendrimers. Materials & methods Interactions with model liposomes of a 1:1 molar ratio of tripalmitin:cholesterol or phospholipid:cholesterol were investigated by high-throughput absorbance, as well as fluorescence difference and cellular luminescence assays. Results Spectral differences and dynamic light-scattering spectroscopy shifts demonstrated the interaction of conjugates with liposomes. Biological activity was demonstrated by upregulation of gene expression via splice-shifting oligomers, delivery of anti-B-Raf siRNA in cultured human cancer cells or tuberculosis antigen 85B plasmid expression vector in a coculture model of antigen presentation. Conclusion The data suggests that gold nanoparticles and methoxypoly(ethylene glycol)-block-polyamidoamine dendrimer nanoconjugates may have potential for binding, stabilization and delivery of splice-shifting oligomers, siRNA and nucleic acid vaccines for preclinical trials. PMID:22943129

A BSL-4 high-throughput screen identifies sulfonamide inhibitors of Nipah virus.

PubMed

Tigabu, Bersabeh; Rasmussen, Lynn; White, E Lucile; Tower, Nichole; Saeed, Mohammad; Bukreyev, Alexander; Rockx, Barry; LeDuc, James W; Noah, James W

2014-04-01

Nipah virus is a biosafety level 4 (BSL-4) pathogen that causes severe respiratory illness and encephalitis in humans. To identify novel small molecules that target Nipah virus replication as potential therapeutics, Southern Research Institute and Galveston National Laboratory jointly developed an automated high-throughput screening platform that is capable of testing 10,000 compounds per day within BSL-4 biocontainment. Using this platform, we screened a 10,080-compound library using a cell-based, high-throughput screen for compounds that inhibited the virus-induced cytopathic effect. From this pilot effort, 23 compounds were identified with EC50 values ranging from 3.9 to 20.0 μM and selectivities >10. Three sulfonamide compounds with EC50 values <12 μM were further characterized for their point of intervention in the viral replication cycle and for broad antiviral efficacy. Development of HTS capability under BSL-4 containment changes the paradigm for drug discovery for highly pathogenic agents because this platform can be readily modified to identify prophylactic and postexposure therapeutic candidates against other BSL-4 pathogens, particularly Ebola, Marburg, and Lassa viruses.

A BSL-4 High-Throughput Screen Identifies Sulfonamide Inhibitors of Nipah Virus

PubMed Central

Tigabu, Bersabeh; Rasmussen, Lynn; White, E. Lucile; Tower, Nichole; Saeed, Mohammad; Bukreyev, Alexander; Rockx, Barry; LeDuc, James W.

2014-01-01

Abstract Nipah virus is a biosafety level 4 (BSL-4) pathogen that causes severe respiratory illness and encephalitis in humans. To identify novel small molecules that target Nipah virus replication as potential therapeutics, Southern Research Institute and Galveston National Laboratory jointly developed an automated high-throughput screening platform that is capable of testing 10,000 compounds per day within BSL-4 biocontainment. Using this platform, we screened a 10,080-compound library using a cell-based, high-throughput screen for compounds that inhibited the virus-induced cytopathic effect. From this pilot effort, 23 compounds were identified with EC50 values ranging from 3.9 to 20.0 μM and selectivities >10. Three sulfonamide compounds with EC50 values <12 μM were further characterized for their point of intervention in the viral replication cycle and for broad antiviral efficacy. Development of HTS capability under BSL-4 containment changes the paradigm for drug discovery for highly pathogenic agents because this platform can be readily modified to identify prophylactic and postexposure therapeutic candidates against other BSL-4 pathogens, particularly Ebola, Marburg, and Lassa viruses. PMID:24735442

Identification of a subset of human natural killer cells expressing high levels of programmed death 1: A phenotypic and functional characterization.

PubMed

Pesce, Silvia; Greppi, Marco; Tabellini, Giovanna; Rampinelli, Fabio; Parolini, Silvia; Olive, Daniel; Moretta, Lorenzo; Moretta, Alessandro; Marcenaro, Emanuela

2017-01-01

Programmed death 1 (PD-1) is an immunologic checkpoint that limits immune responses by delivering potent inhibitory signals to T cells on interaction with specific ligands expressed on tumor/virus-infected cells, thus contributing to immune escape mechanisms. Therapeutic PD-1 blockade has been shown to mediate tumor eradication with impressive clinical results. Little is known about the expression/function of PD-1 on human natural killer (NK) cells. We sought to clarify whether human NK cells can express PD-1 and analyze their phenotypic/functional features. We performed multiparametric cytofluorimetric analysis of PD-1 + NK cells and their functional characterization using degranulation, cytokine production, and proliferation assays. We provide unequivocal evidence that PD-1 is highly expressed (PD-1 bright ) on an NK cell subset detectable in the peripheral blood of approximately one fourth of healthy subjects. These donors are always serologically positive for human cytomegalovirus. PD-1 is expressed by CD56 dim but not CD56 bright NK cells and is confined to fully mature NK cells characterized by the NKG2A - KIR + CD57 + phenotype. Proportions of PD-1 bright NK cells were higher in the ascites of a cohort of patients with ovarian carcinoma, suggesting their possible induction/expansion in tumor environments. Functional analysis revealed a reduced proliferative capability in response to cytokines, low degranulation, and impaired cytokine production on interaction with tumor targets. We have identified and characterized a novel subpopulation of human NK cells expressing high levels of PD-1. These cells have the phenotypic characteristics of fully mature NK cells and are increased in patients with ovarian carcinoma. They display low proliferative responses and impaired antitumor activity that can be partially restored by antibody-mediated disruption of PD-1/programmed death ligand interaction. Copyright © 2016 American Academy of Allergy, Asthma & Immunology

A high-throughput screen for single gene activities: isolation of apoptosis inducers.

PubMed

Albayrak, Timur; Grimm, Stefan

2003-05-16

We describe a novel genetic screen that is performed by transfecting every individual clone of an expression library into a separate population of cells in a high-throughput mode. The screen allows one to achieve a hitherto unattained sensitivity in expression cloning which was exploited in a first read-out to clone apoptosis-inducing genes. This led to the isolation of several genes whose proteins induce distinct phenotypes of apoptosis in 293T cells. One of the isolated genes is the tumor suppressor cytochrome b(L) (cybL), a component of the respiratory chain complex II, that diminishes the activity of this complex for apoptosis induction. This gene is more efficient and specific for causing cell death than a drug with the same activity. These results suggest further applications, both of the isolated genes and the screen.

High-throughput screening for bioactive components from traditional Chinese medicine.

PubMed

Zhu, Yanhui; Zhang, Zhiyun; Zhang, Meng; Mais, Dale E; Wang, Ming-Wei

2010-12-01

Throughout the centuries, traditional Chinese medicine has been a rich resource in the development of new drugs. Modern drug discovery, which relies increasingly on automated high throughput screening and quick hit-to-lead development, however, is confronted with the challenges of the chemical complexity associated with natural products. New technologies for biological screening as well as library building are in great demand in order to meet the requirements. Here we review the developments in these techniques under the perspective of their applicability in natural product drug discovery. Methods in library building, component characterizing, biological evaluation, and other screening methods including NMR and X-ray diffraction are discussed.

Prevalence of sexual dimorphism in mammalian phenotypic traits.

PubMed

Karp, Natasha A; Mason, Jeremy; Beaudet, Arthur L; Benjamini, Yoav; Bower, Lynette; Braun, Robert E; Brown, Steve D M; Chesler, Elissa J; Dickinson, Mary E; Flenniken, Ann M; Fuchs, Helmut; Angelis, Martin Hrabe de; Gao, Xiang; Guo, Shiying; Greenaway, Simon; Heller, Ruth; Herault, Yann; Justice, Monica J; Kurbatova, Natalja; Lelliott, Christopher J; Lloyd, K C Kent; Mallon, Ann-Marie; Mank, Judith E; Masuya, Hiroshi; McKerlie, Colin; Meehan, Terrence F; Mott, Richard F; Murray, Stephen A; Parkinson, Helen; Ramirez-Solis, Ramiro; Santos, Luis; Seavitt, John R; Smedley, Damian; Sorg, Tania; Speak, Anneliese O; Steel, Karen P; Svenson, Karen L; Wakana, Shigeharu; West, David; Wells, Sara; Westerberg, Henrik; Yaacoby, Shay; White, Jacqueline K

2017-06-26

The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans.

Combinatorial and high-throughput screening of materials libraries: review of state of the art.

PubMed

Potyrailo, Radislav; Rajan, Krishna; Stoewe, Klaus; Takeuchi, Ichiro; Chisholm, Bret; Lam, Hubert

2011-11-14

Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and functional materials, polymer-based industrial coatings, sensing materials, and biomaterials.

MAPPER: high-throughput maskless lithography

NASA Astrophysics Data System (ADS)

Wieland, M. J.; de Boer, G.; ten Berge, G. F.; Jager, R.; van de Peut, T.; Peijster, J. J. M.; Slot, E.; Steenbrink, S. W. H. K.; Teepen, T. F.; van Veen, A. H. V.; Kampherbeek, B. J.

2009-03-01

Maskless electron beam lithography, or electron beam direct write, has been around for a long time in the semiconductor industry and was pioneered from the mid-1960s onwards. This technique has been used for mask writing applications as well as device engineering and in some cases chip manufacturing. However because of its relatively low throughput compared to optical lithography, electron beam lithography has never been the mainstream lithography technology. To extend optical lithography double patterning, as a bridging technology, and EUV lithography are currently explored. Irrespective of the technical viability of both approaches, one thing seems clear. They will be expensive [1]. MAPPER Lithography is developing a maskless lithography technology based on massively-parallel electron-beam writing with high speed optical data transport for switching the electron beams. In this way optical columns can be made with a throughput of 10-20 wafers per hour. By clustering several of these columns together high throughputs can be realized in a small footprint. This enables a highly cost-competitive alternative to double patterning and EUV alternatives. In 2007 MAPPER obtained its Proof of Lithography milestone by exposing in its Demonstrator 45 nm half pitch structures with 110 electron beams in parallel, where all the beams where individually switched on and off [2]. In 2008 MAPPER has taken a next step in its development by building several tools. The objective of building these tools is to involve semiconductor companies to be able to verify tool performance in their own environment. To enable this, the tools will have a 300 mm wafer stage in addition to a 110-beam optics column. First exposures at 45 nm half pitch resolution have been performed and analyzed. On the same wafer it is observed that all beams print and based on analysis of 11 beams the CD for the different patterns is within 2.2 nm from target and the CD uniformity for the different patterns is better

Identification of functional modules using network topology and high-throughput data.

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

With the advent of systems biology, biological knowledge is often represented today by networks. These include regulatory and metabolic networks, protein-protein interaction networks, and many others. At the same time, high-throughput genomics and proteomics techniques generate very large data sets, which require sophisticated computational analysis. Usually, separate and different analysis methodologies are applied to each of the two data types. An integrated investigation of network and high-throughput information together can improve the quality of the analysis by accounting simultaneously for topological network properties alongside intrinsic features of the high-throughput data. We describe a novel algorithmic framework for this challenge. We first transform the high-throughput data into similarity values, (e.g., by computing pairwise similarity of gene expression patterns from microarray data). Then, given a network of genes or proteins and similarity values between some of them, we seek connected sub-networks (or modules) that manifest high similarity. We develop algorithms for this problem and evaluate their performance on the osmotic shock response network in S. cerevisiae and on the human cell cycle network. We demonstrate that focused, biologically meaningful and relevant functional modules are obtained. In comparison with extant algorithms, our approach has higher sensitivity and higher specificity. We have demonstrated that our method can accurately identify functional modules. Hence, it carries the promise to be highly useful in analysis of high throughput data.

Adaptation to high throughput batch chromatography enhances multivariate screening.

PubMed

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.

Lights, camera, action: high-throughput plant phenotyping is ready for a close-up

USDA-ARS?s Scientific Manuscript database

Modern techniques for crop improvement rely on both DNA sequencing and accurate quantification of plant traits to identify genes and germplasm of interest. With rapid advances in DNA sequencing technologies, plant phenotyping is now a bottleneck in advancing crop yields [1,2]. Furthermore, the envir...

High-throughput process development: I. Process chromatography.

PubMed

Rathore, Anurag S; Bhambure, Rahul

2014-01-01

Chromatographic separation serves as "a workhorse" for downstream process development and plays a key role in removal of product-related, host cell-related, and process-related impurities. Complex and poorly characterized raw materials and feed material, low feed concentration, product instability, and poor mechanistic understanding of the processes are some of the critical challenges that are faced during development of a chromatographic step. Traditional process development is performed as trial-and-error-based evaluation and often leads to a suboptimal process. High-throughput process development (HTPD) platform involves an integration of miniaturization, automation, and parallelization and provides a systematic approach for time- and resource-efficient chromatography process development. Creation of such platforms requires integration of mechanistic knowledge of the process with various statistical tools for data analysis. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today. This protocol describes the steps involved in performing HTPD of process chromatography step. It described operation of a commercially available device (PreDictor™ plates from GE Healthcare). This device is available in 96-well format with 2 or 6 μL well size. We also discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that is gathered from such a platform. A case study involving use of the protocol for examining ion-exchange chromatography of granulocyte colony-stimulating factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that is representative of the data obtained at the traditional lab scale. The agreement in the

High-throughput identification of the microbial biodiversity of cocoa bean fermentation by MALDI-TOF MS.

PubMed

Miescher Schwenninger, S; Freimüller Leischtfeld, S; Gantenbein-Demarchi, C

2016-11-01

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a powerful biotyping tool increasingly used for high-throughput identification of clinical microbial isolates, however, in food fermentation research this approach is still not well established. This study examines the microbial biodiversity of cocoa bean fermentation based on the isolation of micro-organisms in cocoa-producing regions, followed by MALDI-TOF MS in Switzerland. A preceding 6-week storage test to mimic lengthy transport of microbial samples from cocoa-producing regions to Switzerland was performed with strains of Lactobacillus plantarum, Acetobacter pasteurianus and Saccharomyces cerevisiae. Weekly MALDI-TOF MS analysis was able to successfully identify microbiota to the species level after storing live cultures on slant agar at mild temperatures (7°C) and/or in 75% aqueous ethanol at differing temperatures (-20, 7 and 30°C). The efficacy of this method was confirmed by on-site recording of the microbial biodiversity in cocoa bean fermentation in Bolivia and Brazil, with a total of 1126 randomly selected isolates. MALDI-TOF MS analyses revealed known dominant cocoa bean fermentation species with Lact. plantarum and Lactobacillus fermentum in the lactic acid bacteria taxon, Hanseniaspora opuntiae and S. cerevisiae in the yeast taxon, and Acet. pasteurianus, Acetobacter fabarum, Acetobacter ghanensis and Acetobacter senegalensis in the acetic acid bacteria taxon. Microbial identification with MALDI-TOF MS has increased the number of samples that can be analysed in a given time, a prerequisite for high-throughput methods. This method is already widely used for the identification of clinical microbial isolates, whereas in food fermentation research, including cocoa bean fermentation, microbiota is mostly identified by time-consuming, biochemical-based phenotyping and molecular approaches. This study presents the use of MALDI-TOF MS for characterizing the

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

NASA Astrophysics Data System (ADS)

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.

High-throughput screening to identify selective inhibitors of microbial sulfate reduction (and beyond)

NASA Astrophysics Data System (ADS)

Carlson, H. K.; Coates, J. D.; Deutschbauer, A. M.

2015-12-01

The selective perturbation of complex microbial ecosystems to predictably influence outcomes in engineered and industrial environments remains a grand challenge for geomicrobiology. In some industrial ecosystems, such as oil reservoirs, sulfate reducing microorganisms (SRM) produce hydrogen sulfide which is toxic, explosive and corrosive. Current strategies to selectively inhibit sulfidogenesis are based on non-specific biocide treatments, bio-competitive exclusion by alternative electron acceptors or sulfate-analogs which are competitive inhibitors or futile/alternative substrates of the sulfate reduction pathway. Despite the economic cost of sulfidogenesis, there has been minimal exploration of the chemical space of possible inhibitory compounds, and very little work has quantitatively assessed the selectivity of putative souring treatments. We have developed a high-throughput screening strategy to target SRM, quantitatively ranked the selectivity and potency of hundreds of compounds and identified previously unrecognized SRM selective inhibitors and synergistic interactions between inhibitors. Once inhibitor selectivity is defined, high-throughput characterization of microbial community structure across compound gradients and identification of fitness determinants using isolate bar-coded transposon mutant libraries can give insights into the genetic mechanisms whereby compounds structure microbial communities. The high-throughput (HT) approach we present can be readily applied to target SRM in diverse environments and more broadly, could be used to identify and quantify the potency and selectivity of inhibitors of a variety of microbial metabolisms. Our findings and approach are relevant for engineering environmental ecosystems and also to understand the role of natural gradients in shaping microbial niche space.

High-throughput countercurrent microextraction in passive mode.

PubMed

Xie, Tingliang; Xu, Cong

2018-05-15

Although microextraction is much more efficient than conventional macroextraction, its practical application has been limited by low throughputs and difficulties in constructing robust countercurrent microextraction (CCME) systems. In this work, a robust CCME process was established based on a novel passive microextractor with four units without any moving parts. The passive microextractor has internal recirculation and can efficiently mix two immiscible liquids. The hydraulic characteristics as well as the extraction and back-extraction performance of the passive CCME were investigated experimentally. The recovery efficiencies of the passive CCME were 1.43-1.68 times larger than the best values achieved using cocurrent extraction. Furthermore, the total throughput of the passive CCME developed in this work was about one to three orders of magnitude higher than that of other passive CCME systems reported in the literature. Therefore, a robust CCME process with high throughputs has been successfully constructed, which may promote the application of passive CCME in a wide variety of fields.

High throughput system for magnetic manipulation of cells, polymers, and biomaterials

PubMed Central

Spero, Richard Chasen; Vicci, Leandra; Cribb, Jeremy; Bober, David; Swaminathan, Vinay; O’Brien, E. Timothy; Rogers, Stephen L.; Superfine, R.

2008-01-01

In the past decade, high throughput screening (HTS) has changed the way biochemical assays are performed, but manipulation and mechanical measurement of micro- and nanoscale systems have not benefited from this trend. Techniques using microbeads (particles ∼0.1–10 μm) show promise for enabling high throughput mechanical measurements of microscopic systems. We demonstrate instrumentation to magnetically drive microbeads in a biocompatible, multiwell magnetic force system. It is based on commercial HTS standards and is scalable to 96 wells. Cells can be cultured in this magnetic high throughput system (MHTS). The MHTS can apply independently controlled forces to 16 specimen wells. Force calibrations demonstrate forces in excess of 1 nN, predicted force saturation as a function of pole material, and powerlaw dependence of F∼r−2.7±0.1. We employ this system to measure the stiffness of SR2+ Drosophila cells. MHTS technology is a key step toward a high throughput screening system for micro- and nanoscale biophysical experiments. PMID:19044357

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis.

PubMed

Lee, Hyokyeong; Moody-Davis, Asher; Saha, Utsab; Suzuki, Brian M; Asarnow, Daniel; Chen, Steven; Arkin, Michelle; Caffrey, Conor R; Singh, Rahul

2012-01-01

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis

PubMed Central

2012-01-01

Background Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. Method We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. Results We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. Conclusions The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs

Lessons from high-throughput protein crystallization screening: 10 years of practical experience

PubMed Central

JR, Luft; EH, Snell; GT, DeTitta

2011-01-01

Introduction X-ray crystallography provides the majority of our structural biological knowledge at a molecular level and in terms of pharmaceutical design is a valuable tool to accelerate discovery. It is the premier technique in the field, but its usefulness is significantly limited by the need to grow well-diffracting crystals. It is for this reason that high-throughput crystallization has become a key technology that has matured over the past 10 years through the field of structural genomics. Areas covered The authors describe their experiences in high-throughput crystallization screening in the context of structural genomics and the general biomedical community. They focus on the lessons learnt from the operation of a high-throughput crystallization screening laboratory, which to date has screened over 12,500 biological macromolecules. They also describe the approaches taken to maximize the success while minimizing the effort. Through this, the authors hope that the reader will gain an insight into the efficient design of a laboratory and protocols to accomplish high-throughput crystallization on a single-, multiuser-laboratory or industrial scale. Expert Opinion High-throughput crystallization screening is readily available but, despite the power of the crystallographic technique, getting crystals is still not a solved problem. High-throughput approaches can help when used skillfully; however, they still require human input in the detailed analysis and interpretation of results to be more successful. PMID:22646073

High-throughput screening based on label-free detection of small molecule microarrays

NASA Astrophysics Data System (ADS)

Zhu, Chenggang; Fei, Yiyan; Zhu, Xiangdong

2017-02-01

Based on small-molecule microarrays (SMMs) and oblique-incidence reflectivity difference (OI-RD) scanner, we have developed a novel high-throughput drug preliminary screening platform based on label-free monitoring of direct interactions between target proteins and immobilized small molecules. The screening platform is especially attractive for screening compounds against targets of unknown function and/or structure that are not compatible with functional assay development. In this screening platform, OI-RD scanner serves as a label-free detection instrument which is able to monitor about 15,000 biomolecular interactions in a single experiment without the need to label any biomolecule. Besides, SMMs serves as a novel format for high-throughput screening by immobilization of tens of thousands of different compounds on a single phenyl-isocyanate functionalized glass slide. Based on the high-throughput screening platform, we sequentially screened five target proteins (purified target proteins or cell lysate containing target protein) in high-throughput and label-free mode. We found hits for respective target protein and the inhibition effects for some hits were confirmed by following functional assays. Compared to traditional high-throughput screening assay, the novel high-throughput screening platform has many advantages, including minimal sample consumption, minimal distortion of interactions through label-free detection, multi-target screening analysis, which has a great potential to be a complementary screening platform in the field of drug discovery.

Advances in high throughput DNA sequence data compression.

PubMed

Sardaraz, Muhammad; Tahir, Muhammad; Ikram, Ataul Aziz

2016-06-01

Advances in high throughput sequencing technologies and reduction in cost of sequencing have led to exponential growth in high throughput DNA sequence data. This growth has posed challenges such as storage, retrieval, and transmission of sequencing data. Data compression is used to cope with these challenges. Various methods have been developed to compress genomic and sequencing data. In this article, we present a comprehensive review of compression methods for genome and reads compression. Algorithms are categorized as referential or reference free. Experimental results and comparative analysis of various methods for data compression are presented. Finally, key challenges and research directions in DNA sequence data compression are highlighted.

Dissecting the contribution of actin and vimentin intermediate filaments to mechanical phenotype of suspended cells using high-throughput deformability measurements and computational modeling.

PubMed

Gladilin, Evgeny; Gonzalez, Paula; Eils, Roland

2014-08-22

Mechanical cell properties play an important role in many basic biological functions, including motility, adhesion, proliferation and differentiation. There is a growing body of evidence that the mechanical cell phenotype can be used for detection and, possibly, treatment of various diseases, including cancer. Understanding of pathological mechanisms requires investigation of the relationship between constitutive properties and major structural components of cells, i.e., the nucleus and cytoskeleton. While the contribution of actin und microtubules to cellular rheology has been extensively studied in the past, the role of intermediate filaments has been scarcely investigated up to now. Here, for the first time we compare the effects of drug-induced disruption of actin and vimentin intermediate filaments on mechanical properties of suspended NK cells using high-throughput deformability measurements and computational modeling. Although, molecular mechanisms of actin and vimentin disruption by the applied cytoskeletal drugs, Cytochalasin-D and Withaferin-A, are different, cell softening in both cases can be attributed to reduction of the effective density and stiffness of filament networks. Our experimental data suggest that actin and vimentin deficient cells exhibit, in average, 41% and 20% higher deformability in comparison to untreated control. 3D Finite Element simulation is performed to quantify the contribution of cortical actin and perinuclear vimentin to mechanical phenotype of the whole cell. Our simulation provides quantitative estimates for decreased filament stiffness in drug-treated cells and predicts more than two-fold increase of the strain magnitude in the perinuclear vimentin layer of actin deficient cells relatively to untreated control. Thus, the mechanical function of vimentin becomes particularly essential in motile and proliferating cells that have to dynamically remodel the cortical actin network. These insights add functional cues to frequently

High-Throughput Assay and Discovery of Small Molecules that Interrupt Malaria Transmission

PubMed Central

Plouffe, David M.; Wree, Melanie; Du, Alan Y.; Meister, Stephan; Li, Fengwu; Patra, Kailash; Lubar, Aristea; Okitsu, Shinji L.; Flannery, Erika L.; Kato, Nobutaka; Tanaseichuk, Olga; Comer, Eamon; Zhou, Bin; Kuhen, Kelli; Zhou, Yingyao; Leroy, Didier; Schreiber, Stuart L.; Scherer, Christina A.; Vinetz, Joseph; Winzeler, Elizabeth A.

2016-01-01

Summary Preventing transmission is an important element of malaria control. However, most of the current available methods to assay for malaria transmission blocking are relatively low throughput and cannot be applied to large chemical libraries. We have developed a high-throughput and cost-effective assay, the Saponin-lysis Sexual Stage Assay (SaLSSA), for identifying small molecules with transmission-blocking capacity. SaLSSA analysis of 13,983 unique compounds uncovered that >90% of well-characterized antimalarials, including endoperoxides and 4-aminoquinolines, as well as compounds active against asexual blood stages, lost most of their killing activity when parasites developed into metabolically quiescent stage V gametocytes. On the other hand, we identified compounds with consistent low nanomolar transmission-blocking activity, some of which showed cross-reactivity against asexual blood and liver stages. The data clearly emphasize substantial physiological differences between sexual and asexual parasites and provide a tool and starting points for the discovery and development of transmission-blocking drugs. PMID:26749441

Functional approach to high-throughput plant growth analysis

PubMed Central

2013-01-01

Method Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. Results Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. Availability HPGA is available at http://www.msu.edu/~jinchen/HPGA. PMID:24565437

Prevalence of sexual dimorphism in mammalian phenotypic traits

PubMed Central

Karp, Natasha A.; Mason, Jeremy; Beaudet, Arthur L.; Benjamini, Yoav; Bower, Lynette; Braun, Robert E.; Brown, Steve D.M.; Chesler, Elissa J.; Dickinson, Mary E.; Flenniken, Ann M.; Fuchs, Helmut; Angelis, Martin Hrabe de; Gao, Xiang; Guo, Shiying; Greenaway, Simon; Heller, Ruth; Herault, Yann; Justice, Monica J.; Kurbatova, Natalja; Lelliott, Christopher J.; Lloyd, K.C. Kent; Mallon, Ann-Marie; Mank, Judith E.; Masuya, Hiroshi; McKerlie, Colin; Meehan, Terrence F.; Mott, Richard F.; Murray, Stephen A.; Parkinson, Helen; Ramirez-Solis, Ramiro; Santos, Luis; Seavitt, John R.; Smedley, Damian; Sorg, Tania; Speak, Anneliese O.; Steel, Karen P.; Svenson, Karen L.; Obata, Yuichi; Suzuki, Tomohiro; Tamura, Masaru; Kaneda, Hideki; Furuse, Tamio; Kobayashi, Kimio; Miura, Ikuo; Yamada, Ikuko; Tanaka, Nobuhiko; Yoshiki, Atsushi; Ayabe, Shinya; Clary, David A.; Tolentino, Heather A.; Schuchbauer, Michael A.; Tolentino, Todd; Aprile, Joseph Anthony; Pedroia, Sheryl M.; Kelsey, Lois; Vukobradovic, Igor; Berberovic, Zorana; Owen, Celeste; Qu, Dawei; Guo, Ruolin; Newbigging, Susan; Morikawa, Lily; Law, Napoleon; Shang, Xueyuan; Feugas, Patricia; Wang, Yanchun; Eskandarian, Mohammad; Zhu, Yingchun; Nutter, Lauryl M. J.; Penton, Patricia; Laurin, Valerie; Clarke, Shannon; Lan, Qing; Sohel, Khondoker; Miller, David; Clark, Greg; Hunter, Jane; Cabezas, Jorge; Bubshait, Mohammed; Carroll, Tracy; Tondat, Sandra; MacMaster, Suzanne; Pereira, Monica; Gertsenstein, Marina; Danisment, Ozge; Jacob, Elsa; Creighton, Amie; Sleep, Gillian; Clark, James; Teboul, Lydia; Fray, Martin; Caulder, Adam; Loeffler, Jorik; Codner, Gemma; Cleak, James; Johnson, Sara; Szoke-Kovacs, Zsombor; Radage, Adam; Maritati, Marina; Mianne, Joffrey; Gardiner, Wendy; Allen, Susan; Cater, Heather; Stewart, Michelle; Keskivali-Bond, Piia; Sinclair, Caroline; Brown, Ellen; Doe, Brendan; Wardle-Jones, Hannah; Grau, Evelyn; Griggs, Nicola; Woods, Mike; Kundi, Helen; Griffiths, Mark N. D.; Kipp, Christian; Melvin, David G.; Raj, Navis P. S.; Holroyd, Simon A.; Gannon, David J.; Alcantara, Rafael; Galli, Antonella; Hooks, Yvette E.; Tudor, Catherine L.; Green, Angela L.; Kussy, Fiona L.; Tuck, Elizabeth J.; Siragher, Emma J.; Maguire, Simon A.; Lafont, David T.; Vancollie, Valerie E.; Pearson, Selina A.; Gates, Amy S.; Sanderson, Mark; Shannon, Carl; Anthony, Lauren F. E.; Sumowski, Maksymilian T.; McLaren, Robbie S. B.; Swiatkowska, Agnieszka; Isherwood, Christopher M.; Cambridge, Emma L; Wilson, Heather M.; Caetano, Susana S.; Mazzeo, Cecilia Icoresi; Dabrowska, Monika H.; Lillistone, Charlotte; Estabel, Jeanne; Maguire, Anna Karin B.; Roberson, Laura-Anne; Pavlovic, Guillaume; Birling, Marie-Christine; Marie, Wattenhofer-Donze; Jacquot, Sylvie; Ayadi, Abdel; Ali-Hadji, Dalila; Charles, Philippe; André, Philippe; Le Marchand, Elise; El Amri, Amal; Vasseur, Laurent; Aguilar-Pimentel, Antonio; Becker, Lore; Treise, Irina; Moreth, Kristin; Stoeger, Tobias; Amarie, Oana V.; Neff, Frauke; Wurst, Wolfgang; Bekeredjian, Raffi; Ollert, Markus; Klopstock, Thomas; Calzada-Wack, Julia; Marschall, Susan; Brommage, Robert; Steinkamp, Ralph; Lengger, Christoph; Östereicher, Manuela A.; Maier, Holger; Stoeger, Claudia; Leuchtenberger, Stefanie; Yildrim, AliÖ; Garrett, Lillian; Hölter, Sabine M; Zimprich, Annemarie; Seisenberger, Claudia; Bürger, Antje; Graw, Jochen; Eickelberg, Oliver; Zimmer, Andreas; Wolf, Eckhard; Busch, Dirk H; Klingenspor, Martin; Schmidt-Weber, Carsten; Gailus-Durner, Valérie; Beckers, Johannes; Rathkolb, Birgit; Rozman, Jan; Wakana, Shigeharu; West, David; Wells, Sara; Westerberg, Henrik; Yaacoby, Shay; White, Jacqueline K.

2017-01-01

The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans. PMID:28650954

Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

NASA Astrophysics Data System (ADS)

Mohd Asaari, Mohd Shahrimie; Mishra, Puneet; Mertens, Stien; Dhondt, Stijn; Inzé, Dirk; Wuyts, Nathalie; Scheunders, Paul

2018-04-01

The potential of close-range hyperspectral imaging (HSI) as a tool for detecting early drought stress responses in plants grown in a high-throughput plant phenotyping platform (HTPPP) was explored. Reflectance spectra from leaves in close-range imaging are highly influenced by plant geometry and its specific alignment towards the imaging system. This induces high uninformative variability in the recorded signals, whereas the spectral signature informing on plant biological traits remains undisclosed. A linear reflectance model that describes the effect of the distance and orientation of each pixel of a plant with respect to the imaging system was applied. By solving this model for the linear coefficients, the spectra were corrected for the uninformative illumination effects. This approach, however, was constrained by the requirement of a reference spectrum, which was difficult to obtain. As an alternative, the standard normal variate (SNV) normalisation method was applied to reduce this uninformative variability. Once the envisioned illumination effects were eliminated, the remaining differences in plant spectra were assumed to be related to changes in plant traits. To distinguish the stress-related phenomena from regular growth dynamics, a spectral analysis procedure was developed based on clustering, a supervised band selection, and a direct calculation of a spectral similarity measure against a reference. To test the significance of the discrimination between healthy and stressed plants, a statistical test was conducted using a one-way analysis of variance (ANOVA) technique. The proposed analysis techniques was validated with HSI data of maize plants (Zea mays L.) acquired in a HTPPP for early detection of drought stress in maize plant. Results showed that the pre-processing of reflectance spectra with the SNV effectively reduces the variability due to the expected illumination effects. The proposed spectral analysis method on the normalized spectra successfully

High-Content, High-Throughput Screening for the Identification of Cytotoxic Compounds Based on Cell Morphology and Cell Proliferation Markers

PubMed Central

Martin, Heather L.; Adams, Matthew; Higgins, Julie; Bond, Jacquelyn; Morrison, Ewan E.; Bell, Sandra M.; Warriner, Stuart; Nelson, Adam; Tomlinson, Darren C.

2014-01-01

Toxicity is a major cause of failure in drug discovery and development, and whilst robust toxicological testing occurs, efficiency could be improved if compounds with cytotoxic characteristics were identified during primary compound screening. The use of high-content imaging in primary screening is becoming more widespread, and by utilising phenotypic approaches it should be possible to incorporate cytotoxicity counter-screens into primary screens. Here we present a novel phenotypic assay that can be used as a counter-screen to identify compounds with adverse cellular effects. This assay has been developed using U2OS cells, the PerkinElmer Operetta high-content/high-throughput imaging system and Columbus image analysis software. In Columbus, algorithms were devised to identify changes in nuclear morphology, cell shape and proliferation using DAPI, TOTO-3 and phosphohistone H3 staining, respectively. The algorithms were developed and tested on cells treated with doxorubicin, taxol and nocodazole. The assay was then used to screen a novel, chemical library, rich in natural product-like molecules of over 300 compounds, 13.6% of which were identified as having adverse cellular effects. This assay provides a relatively cheap and rapid approach for identifying compounds with adverse cellular effects during screening assays, potentially reducing compound rejection due to toxicity in subsequent in vitro and in vivo assays. PMID:24505478

[Current applications of high-throughput DNA sequencing technology in antibody drug research].

PubMed

Yu, Xin; Liu, Qi-Gang; Wang, Ming-Rong

2012-03-01

Since the publication of a high-throughput DNA sequencing technology based on PCR reaction was carried out in oil emulsions in 2005, high-throughput DNA sequencing platforms have been evolved to a robust technology in sequencing genomes and diverse DNA libraries. Antibody libraries with vast numbers of members currently serve as a foundation of discovering novel antibody drugs, and high-throughput DNA sequencing technology makes it possible to rapidly identify functional antibody variants with desired properties. Herein we present a review of current applications of high-throughput DNA sequencing technology in the analysis of antibody library diversity, sequencing of CDR3 regions, identification of potent antibodies based on sequence frequency, discovery of functional genes, and combination with various display technologies, so as to provide an alternative approach of discovery and development of antibody drugs.

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

2014-01-01

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize

High-throughput linear optical stretcher for mechanical characterization of blood cells.

PubMed

Roth, Kevin B; Neeves, Keith B; Squier, Jeff; Marr, David W M

2016-04-01

This study describes a linear optical stretcher as a high-throughput mechanical property cytometer. Custom, inexpensive, and scalable optics image a linear diode bar source into a microfluidic channel, where cells are hydrodynamically focused into the optical stretcher. Upon entering the stretching region, antipodal optical forces generated by the refraction of tightly focused laser light at the cell membrane deform each cell in flow. Each cell relaxes as it flows out of the trap and is compared to the stretched state to determine deformation. The deformation response of untreated red blood cells and neutrophils were compared to chemically treated cells. Statistically significant differences were observed between normal, diamide-treated, and glutaraldehyde-treated red blood cells, as well as between normal and cytochalasin D-treated neutrophils. Based on the behavior of the pure, untreated populations of red cells and neutrophils, a mixed population of these cells was tested and the discrete populations were identified by deformability. © 2015 International Society for Advancement of Cytometry. © 2015 International Society for Advancement of Cytometry.

Characterization and complete genome sequence of a previously uncharacterized panicovirus from Bermuda grass detected by high throughput sequencing

USDA-ARS?s Scientific Manuscript database

Bermuda grass samples were examined by transmission electron microscopy and 28-30 nm spherical virus particles were observed. Total RNA from these plants was subjected to high throughput sequencing (HTS). The nearly full genome sequence of a previously uncharacterized Panicovirus was identified from...

High-throughput characterization of Echinococcus spp. metacestode miRNomes.

PubMed

Cucher, Marcela; Macchiaroli, Natalia; Kamenetzky, Laura; Maldonado, Lucas; Brehm, Klaus; Rosenzvit, Mara Cecilia

2015-03-01

Echinococcosis is a worldwide zoonosis of great public health concern, considered a neglected disease by the World Health Organisation. The cestode parasites Echinococcus granulosus sensu lato (s. l.) and Echinococcus multilocularis are the main aetiological agents. In the intermediate host, these parasites display particular developmental traits that lead to different patterns of disease progression. In an attempt to understand the causes of these differences, we focused on the analysis of microRNAs (miRNAs), small non-coding regulatory RNAs with major roles in development of animals and plants. In this work, we analysed the small RNA expression pattern of the metacestode, the stage of sanitary relevance, and provide a detailed description of Echinococcus miRNAs. Using high-throughput small RNA sequencing, we believe that we have carried out the first experimental identification of miRNAs in E. multilocularis and have expanded the Echinococcus miRNA catalogue to 38 miRNA genes, including one miRNA only present in E. granulosus s. l. Our findings show that although both species share the top five highest expressed miRNAs, 13 are differentially expressed, which could be related to developmental differences. We also provide evidence that uridylation is the main miRNA processing mechanism in Echinococcus spp. These results provide detailed information on Echinococcus miRNAs, which is the first step in understanding their role in parasite biology and disease establishment and/or progression, and their future potential use as drug or diagnostic targets. Copyright © 2015 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

High-throughput quantification of hydroxyproline for determination of collagen.

PubMed

Hofman, Kathleen; Hall, Bronwyn; Cleaver, Helen; Marshall, Susan

2011-10-15

An accurate and high-throughput assay for collagen is essential for collagen research and development of collagen products. Hydroxyproline is routinely assayed to provide a measurement for collagen quantification. The time required for sample preparation using acid hydrolysis and neutralization prior to assay is what limits the current method for determining hydroxyproline. This work describes the conditions of alkali hydrolysis that, when combined with the colorimetric assay defined by Woessner, provide a high-throughput, accurate method for the measurement of hydroxyproline. Copyright © 2011 Elsevier Inc. All rights reserved.

Quality Control Test for Sequence-Phenotype Assignments

PubMed Central

Ortiz, Maria Teresa Lara; Rosario, Pablo Benjamín Leon; Luna-Nevarez, Pablo; Gamez, Alba Savin; Martínez-del Campo, Ana; Del Rio, Gabriel

2015-01-01

Relating a gene mutation to a phenotype is a common task in different disciplines such as protein biochemistry. In this endeavour, it is common to find false relationships arising from mutations introduced by cells that may be depurated using a phenotypic assay; yet, such phenotypic assays may introduce additional false relationships arising from experimental errors. Here we introduce the use of high-throughput DNA sequencers and statistical analysis aimed to identify incorrect DNA sequence-phenotype assignments and observed that 10–20% of these false assignments are expected in large screenings aimed to identify critical residues for protein function. We further show that this level of incorrect DNA sequence-phenotype assignments may significantly alter our understanding about the structure-function relationship of proteins. We have made available an implementation of our method at http://bis.ifc.unam.mx/en/software/chispas. PMID:25700273

Web-based visual analysis for high-throughput genomics

PubMed Central

2013-01-01

Background Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues. Results We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy. Conclusions Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the

High-Throughput Pharmacokinetics for Environmental Chemicals (SOT)

EPA Science Inventory

High throughput screening (HTS) promises to allow prioritization of thousands of environmental chemicals with little or no in vivo information. For bioactivity identified by HTS, toxicokinetic (TK) models are essential to predict exposure thresholds below which no significant bio...

Effort versus Reward: Preparing Samples for Fungal Community Characterization in High-Throughput Sequencing Surveys of Soils

PubMed Central

Song, Zewei; Schlatter, Dan; Kennedy, Peter; Kinkel, Linda L.; Kistler, H. Corby; Nguyen, Nhu; Bates, Scott T.

2015-01-01

Next generation fungal amplicon sequencing is being used with increasing frequency to study fungal diversity in various ecosystems; however, the influence of sample preparation on the characterization of fungal community is poorly understood. We investigated the effects of four procedural modifications to library preparation for high-throughput sequencing (HTS). The following treatments were considered: 1) the amount of soil used in DNA extraction, 2) the inclusion of additional steps (freeze/thaw cycles, sonication, or hot water bath incubation) in the extraction procedure, 3) the amount of DNA template used in PCR, and 4) the effect of sample pooling, either physically or computationally. Soils from two different ecosystems in Minnesota, USA, one prairie and one forest site, were used to assess the generality of our results. The first three treatments did not significantly influence observed fungal OTU richness or community structure at either site. Physical pooling captured more OTU richness compared to individual samples, but total OTU richness at each site was highest when individual samples were computationally combined. We conclude that standard extraction kit protocols are well optimized for fungal HTS surveys, but because sample pooling can significantly influence OTU richness estimates, it is important to carefully consider the study aims when planning sampling procedures. PMID:25974078

Traceless Immobilization of Analytes for High-Throughput Experiments with SAMDI Mass Spectrometry.

PubMed

Helal, Kazi Y; Alamgir, Azmain; Berns, Eric J; Mrksich, Milan

2018-06-21

Label-free assays, and particularly those based on the combination of mass spectroscopy with surface chemistries, enable high-throughput experiments of a broad range of reactions. However, these methods can still require the incorporation of functional groups that allow immobilization of reactants and products to surfaces prior to analysis. In this paper, we report a traceless method for attaching molecules to a self-assembled monolayer for matrix-assisted laser desorption and ionization (SAMDI) mass spectrometry. This method uses monolayers that are functionalized with a 3-trifluoromethyl-3-phenyl-diazirine group that liberates nitrogen when irradiated and gives a carbene that inserts into a wide range of bonds to covalently immobilize molecules. Analysis of the monolayer with SAMDI then reveals peaks for each of the adducts formed from molecules in the sample. This method is applied to characterize a P450 drug metabolizing enzyme and to monitor a Suzuki-Miyaura coupling chemical reaction and is important because modification of the substrates with a functional group would alter their activities. This method will be important for high-throughput experiments in many areas, including reaction discovery and optimization.

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

PubMed

Liu, Guangbo; Lanham, Clayton; Buchan, J Ross; Kaplan, Matthew E

2017-01-01

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.

Optimizing multi-dimensional high throughput screening using zebrafish

PubMed Central

Truong, Lisa; Bugel, Sean M.; Chlebowski, Anna; Usenko, Crystal Y.; Simonich, Michael T.; Massey Simonich, Staci L.; Tanguay, Robert L.

2016-01-01

The use of zebrafish for high throughput screening (HTS) for chemical bioactivity assessments is becoming routine in the fields of drug discovery and toxicology. Here we report current recommendations from our experiences in zebrafish HTS. We compared the effects of different high throughput chemical delivery methods on nominal water concentration, chemical sorption to multi-well polystyrene plates, transcription responses, and resulting whole animal responses. We demonstrate that digital dispensing consistently yields higher data quality and reproducibility compared to standard plastic tip-based liquid handling. Additionally, we illustrate the challenges in using this sensitive model for chemical assessment when test chemicals have trace impurities. Adaptation of these better practices for zebrafish HTS should increase reproducibility across laboratories. PMID:27453428

Combinatorial and high-throughput approaches in polymer science

NASA Astrophysics Data System (ADS)

Zhang, Huiqi; Hoogenboom, Richard; Meier, Michael A. R.; Schubert, Ulrich S.

2005-01-01

Combinatorial and high-throughput approaches have become topics of great interest in the last decade due to their potential ability to significantly increase research productivity. Recent years have witnessed a rapid extension of these approaches in many areas of the discovery of new materials including pharmaceuticals, inorganic materials, catalysts and polymers. This paper mainly highlights our progress in polymer research by using an automated parallel synthesizer, microwave synthesizer and ink-jet printer. The equipment and methodologies in our experiments, the high-throughput experimentation of different polymerizations (such as atom transfer radical polymerization, cationic ring-opening polymerization and emulsion polymerization) and the automated matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy (MALDI-TOF MS) sample preparation are described.

Genomic and Phenotypic Characterization of Yeast Biosensor for Deep-space Radiation

NASA Technical Reports Server (NTRS)

Marina, Diana B.; Santa Maria, Sergio; Bhattacharya, Sharmila

2016-01-01

without losing radiation sensitivity. We employed Next-Generation Sequencing technology to better understand this phenotypic variation. Current effort is focusing on the analysis of high-throughput sequencing data to look for genomic changes in these reisolated clones compared to their original isolate.

A high-throughput multiplex method adapted for GMO detection.

PubMed

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.

High-throughput electrophysiological assays for voltage gated ion channels using SyncroPatch 768PE.

PubMed

Li, Tianbo; Lu, Gang; Chiang, Eugene Y; Chernov-Rogan, Tania; Grogan, Jane L; Chen, Jun

2017-01-01

Ion channels regulate a variety of physiological processes and represent an important class of drug target. Among the many methods of studying ion channel function, patch clamp electrophysiology is considered the gold standard by providing the ultimate precision and flexibility. However, its utility in ion channel drug discovery is impeded by low throughput. Additionally, characterization of endogenous ion channels in primary cells remains technical challenging. In recent years, many automated patch clamp (APC) platforms have been developed to overcome these challenges, albeit with varying throughput, data quality and success rate. In this study, we utilized SyncroPatch 768PE, one of the latest generation APC platforms which conducts parallel recording from two-384 modules with giga-seal data quality, to push these 2 boundaries. By optimizing various cell patching parameters and a two-step voltage protocol, we developed a high throughput APC assay for the voltage-gated sodium channel Nav1.7. By testing a group of Nav1.7 reference compounds' IC50, this assay was proved to be highly consistent with manual patch clamp (R > 0.9). In a pilot screening of 10,000 compounds, the success rate, defined by > 500 MΩ seal resistance and >500 pA peak current, was 79%. The assay was robust with daily throughput ~ 6,000 data points and Z' factor 0.72. Using the same platform, we also successfully recorded endogenous voltage-gated potassium channel Kv1.3 in primary T cells. Together, our data suggest that SyncroPatch 768PE provides a powerful platform for ion channel research and drug discovery.

Comparative analysis and validation of the malachite green assay for the high throughput biochemical characterization of terpene synthases

PubMed Central

Vardakou, Maria; Salmon, Melissa; Faraldos, Juan A.; O’Maille, Paul E.

2014-01-01

Terpenes are the largest group of natural products with important and diverse biological roles, while of tremendous economic value as fragrances, flavours and pharmaceutical agents. Class-I terpene synthases (TPSs), the dominant type of TPS enzymes, catalyze the conversion of prenyl diphosphates to often structurally diverse bioactive terpene hydrocarbons, and inorganic pyrophosphate (PPi). To measure their kinetic properties, current bio-analytical methods typically rely on the direct detection of hydrocarbon products by radioactivity measurements or gas chromatography–mass spectrometry (GC–MS). In this study we employed an established, rapid colorimetric assay, the pyrophosphate/malachite green assay (MG), as an alternative means for the biochemical characterization of class I TPSs activity.•We describe the adaptation of the MG assay for turnover and catalytic efficiency measurements of TPSs.•We validate the method by direct comparison with established assays. The agreement of kcat/KM among methods makes this adaptation optimal for rapid evaluation of TPSs.•We demonstrate the application of the MG assay for the high-throughput screening of TPS gene libraries. PMID:26150952

Comparative analysis and validation of the malachite green assay for the high throughput biochemical characterization of terpene synthases.

PubMed

Vardakou, Maria; Salmon, Melissa; Faraldos, Juan A; O'Maille, Paul E

2014-01-01

Terpenes are the largest group of natural products with important and diverse biological roles, while of tremendous economic value as fragrances, flavours and pharmaceutical agents. Class-I terpene synthases (TPSs), the dominant type of TPS enzymes, catalyze the conversion of prenyl diphosphates to often structurally diverse bioactive terpene hydrocarbons, and inorganic pyrophosphate (PPi). To measure their kinetic properties, current bio-analytical methods typically rely on the direct detection of hydrocarbon products by radioactivity measurements or gas chromatography-mass spectrometry (GC-MS). In this study we employed an established, rapid colorimetric assay, the pyrophosphate/malachite green assay (MG), as an alternative means for the biochemical characterization of class I TPSs activity.•We describe the adaptation of the MG assay for turnover and catalytic efficiency measurements of TPSs.•We validate the method by direct comparison with established assays. The agreement of k cat/K M among methods makes this adaptation optimal for rapid evaluation of TPSs.•We demonstrate the application of the MG assay for the high-throughput screening of TPS gene libraries.

Global phenotypic characterisation of human platelet lysate expanded MSCs by high-throughput flow cytometry.

PubMed

Reis, Monica; McDonald, David; Nicholson, Lindsay; Godthardt, Kathrin; Knobel, Sebastian; Dickinson, Anne M; Filby, Andrew; Wang, Xiao-Nong

2018-03-02

Mesenchymal stromal cells (MSCs) are a promising cell source to develop cell therapy for many diseases. Human platelet lysate (PLT) is increasingly used as an alternative to foetal calf serum (FCS) for clinical-scale MSC production. To date, the global surface protein expression of PLT-expended MSCs (MSC-PLT) is not known. To investigate this, paired MSC-PLT and MSC-FCS were analysed in parallel using high-throughput flow cytometry for the expression of 356 cell surface proteins. MSC-PLT showed differential surface protein expression compared to their MSC-FCS counterpart. Higher percentage of positive cells was observed in MSC-PLT for 48 surface proteins, of which 13 were significantly enriched on MSC-PLT. This finding was validated using multiparameter flow cytometry and further confirmed by quantitative staining intensity analysis. The enriched surface proteins are relevant to increased proliferation and migration capacity, as well as enhanced chondrogenic and osteogenic differentiation properties. In silico network analysis revealed that these enriched surface proteins are involved in three distinct networks that are associated with inflammatory responses, carbohydrate metabolism and cellular motility. This is the first study reporting differential cell surface protein expression between MSC-PLT and MSC-FSC. Further studies are required to uncover the impact of those enriched proteins on biological functions of MSC-PLT.

Outlook for Development of High-throughput Cryopreservation for Small-bodied Biomedical Model Fishes★

PubMed Central

Tiersch, Terrence R.; Yang, Huiping; Hu, E.

2011-01-01

With the development of genomic research technologies, comparative genome studies among vertebrate species are becoming commonplace for human biomedical research. Fish offer unlimited versatility for biomedical research. Extensive studies are done using these fish models, yielding tens of thousands of specific strains and lines, and the number is increasing every day. Thus, high-throughput sperm cryopreservation is urgently needed to preserve these genetic resources. Although high-throughput processing has been widely applied for sperm cryopreservation in livestock for decades, application in biomedical model fishes is still in the concept-development stage because of the limited sample volumes and the biological characteristics of fish sperm. High-throughput processing in livestock was developed based on advances made in the laboratory and was scaled up for increased processing speed, capability for mass production, and uniformity and quality assurance. Cryopreserved germplasm combined with high-throughput processing constitutes an independent industry encompassing animal breeding, preservation of genetic diversity, and medical research. Currently, there is no specifically engineered system available for high-throughput of cryopreserved germplasm for aquatic species. This review is to discuss the concepts and needs for high-throughput technology for model fishes, propose approaches for technical development, and overview future directions of this approach. PMID:21440666

NCBI GEO: archive for high-throughput functional genomic data.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Edgar, Ron

2009-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

High-throughput sequencing methods to study neuronal RNA-protein interactions.

PubMed

Ule, Jernej

2009-12-01

UV-cross-linking and RNase protection, combined with high-throughput sequencing, have provided global maps of RNA sites bound by individual proteins or ribosomes. Using a stringent purification protocol, UV-CLIP (UV-cross-linking and immunoprecipitation) was able to identify intronic and exonic sites bound by splicing regulators in mouse brain tissue. Ribosome profiling has been used to quantify ribosome density on budding yeast mRNAs under different environmental conditions. Post-transcriptional regulation in neurons requires high spatial and temporal precision, as is evident from the role of localized translational control in synaptic plasticity. It remains to be seen if the high-throughput methods can be applied quantitatively to study the dynamics of RNP (ribonucleoprotein) remodelling in specific neuronal populations during the neurodegenerative process. It is certain, however, that applications of new biochemical techniques followed by high-throughput sequencing will continue to provide important insights into the mechanisms of neuronal post-transcriptional regulation.

High throughput SNP discovery and genotyping in hexaploid wheat.

PubMed

Rimbert, Hélène; Darrier, Benoît; Navarro, Julien; Kitt, Jonathan; Choulet, Frédéric; Leveugle, Magalie; Duarte, Jorge; Rivière, Nathalie; Eversole, Kellye; Le Gouis, Jacques; Davassi, Alessandro; Balfourier, François; Le Paslier, Marie-Christine; Berard, Aurélie; Brunel, Dominique; Feuillet, Catherine; Poncet, Charles; Sourdille, Pierre; Paux, Etienne

2018-01-01

Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.

High throughput SNP discovery and genotyping in hexaploid wheat

PubMed Central

Navarro, Julien; Kitt, Jonathan; Choulet, Frédéric; Leveugle, Magalie; Duarte, Jorge; Rivière, Nathalie; Eversole, Kellye; Le Gouis, Jacques; Davassi, Alessandro; Balfourier, François; Le Paslier, Marie-Christine; Berard, Aurélie; Brunel, Dominique; Feuillet, Catherine; Poncet, Charles; Sourdille, Pierre

2018-01-01

Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research. PMID:29293495

Droplet microfluidic technology for single-cell high-throughput screening.

PubMed

Brouzes, Eric; Medkova, Martina; Savenelli, Neal; Marran, Dave; Twardowski, Mariusz; Hutchison, J Brian; Rothberg, Jonathan M; Link, Darren R; Perrimon, Norbert; Samuels, Michael L

2009-08-25

We present a droplet-based microfluidic technology that enables high-throughput screening of single mammalian cells. This integrated platform allows for the encapsulation of single cells and reagents in independent aqueous microdroplets (1 pL to 10 nL volumes) dispersed in an immiscible carrier oil and enables the digital manipulation of these reactors at a very high-throughput. Here, we validate a full droplet screening workflow by conducting a droplet-based cytotoxicity screen. To perform this screen, we first developed a droplet viability assay that permits the quantitative scoring of cell viability and growth within intact droplets. Next, we demonstrated the high viability of encapsulated human monocytic U937 cells over a period of 4 days. Finally, we developed an optically-coded droplet library enabling the identification of the droplets composition during the assay read-out. Using the integrated droplet technology, we screened a drug library for its cytotoxic effect against U937 cells. Taken together our droplet microfluidic platform is modular, robust, uses no moving parts, and has a wide range of potential applications including high-throughput single-cell analyses, combinatorial screening, and facilitating small sample analyses.

Precise, High-throughput Analysis of Bacterial Growth.

PubMed

Kurokawa, Masaomi; Ying, Bei-Wen

2017-09-19

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the systems level. Recent studies have reported correlations between bacterial growth and genome-wide events, such as genome reduction and transcriptome reorganization. Correctly analyzing bacterial growth is crucial for understanding the growth-dependent coordination of gene functions and cellular components. Accordingly, the precise quantitative evaluation of bacterial growth in a high-throughput manner is required. Emerging technological developments offer new experimental tools that allow updates of the methods used for studying bacterial growth. The protocol introduced here employs a microplate reader with a highly optimized experimental procedure for the reproducible and precise evaluation of bacterial growth. This protocol was used to evaluate the growth of several previously described Escherichia coli strains. The main steps of the protocol are as follows: the preparation of a large number of cell stocks in small vials for repeated tests with reproducible results, the use of 96-well plates for high-throughput growth evaluation, and the manual calculation of two major parameters (i.e., maximal growth rate and population density) representing the growth dynamics. In comparison to the traditional colony-forming unit (CFU) assay, which counts the cells that are cultured in glass tubes over time on agar plates, the present method is more efficient and provides more detailed temporal records of growth changes, but has a stricter detection limit at low population densities. In summary, the described method is advantageous for the precise and reproducible high-throughput analysis of bacterial growth, which can be used to draw conceptual conclusions or to make theoretical observations.

High-throughput sequencing: a failure mode analysis.

PubMed

Yang, George S; Stott, Jeffery M; Smailus, Duane; Barber, Sarah A; Balasundaram, Miruna; Marra, Marco A; Holt, Robert A

2005-01-04

Basic manufacturing principles are becoming increasingly important in high-throughput sequencing facilities where there is a constant drive to increase quality, increase efficiency, and decrease operating costs. While high-throughput centres report failure rates typically on the order of 10%, the causes of sporadic sequencing failures are seldom analyzed in detail and have not, in the past, been formally reported. Here we report the results of a failure mode analysis of our production sequencing facility based on detailed evaluation of 9,216 ESTs generated from two cDNA libraries. Two categories of failures are described; process-related failures (failures due to equipment or sample handling) and template-related failures (failures that are revealed by close inspection of electropherograms and are likely due to properties of the template DNA sequence itself). Preventative action based on a detailed understanding of failure modes is likely to improve the performance of other production sequencing pipelines.

Hydrogen storage materials discovery via high throughput ball milling and gas sorption.

PubMed

Li, Bin; Kaye, Steven S; Riley, Conor; Greenberg, Doron; Galang, Daniel; Bailey, Mark S

2012-06-11

The lack of a high capacity hydrogen storage material is a major barrier to the implementation of the hydrogen economy. To accelerate discovery of such materials, we have developed a high-throughput workflow for screening of hydrogen storage materials in which candidate materials are synthesized and characterized via highly parallel ball mills and volumetric gas sorption instruments, respectively. The workflow was used to identify mixed imides with significantly enhanced absorption rates relative to Li2Mg(NH)2. The most promising material, 2LiNH2:MgH2 + 5 atom % LiBH4 + 0.5 atom % La, exhibits the best balance of absorption rate, capacity, and cycle-life, absorbing >4 wt % H2 in 1 h at 120 °C after 11 absorption-desorption cycles.

Pot binding as a variable confounding plant phenotype: theoretical derivation and experimental observations.

PubMed

Sinclair, Thomas R; Manandhar, Anju; Shekoofa, Avat; Rosas-Anderson, Pablo; Bagherzadi, Laleh; Schoppach, Remy; Sadok, Walid; Rufty, Thomas W

2017-04-01

Theoretical derivation predicted growth retardation due to pot water limitations, i.e., pot binding. Experimental observations were consistent with these limitations. Combined, these results indicate a need for caution in high-throughput screening and phenotyping. Pot experiments are a mainstay in many plant studies, including the current emphasis on developing high-throughput, phenotyping systems. Pot studies can be vulnerable to decreased physiological activity of the plants particularly when pot volume is small, i.e., "pot binding". It is necessary to understand the conditions under which pot binding may exist to avoid the confounding influence of pot binding in interpreting experimental results. In this paper, a derivation is offered that gives well-defined conditions for the occurrence of pot binding based on restricted water availability. These results showed that not only are pot volume and plant size important variables, but the potting media is critical. Artificial potting mixtures used in many studies, including many high-throughput phenotyping systems, are particularly susceptible to the confounding influences of pot binding. Experimental studies for several crop species are presented that clearly show the existence of thresholds of plant leaf area at which various pot sizes and potting media result in the induction of pot binding even though there may be no immediate, visual plant symptoms. The derivation and experimental results showed that pot binding can readily occur in plant experiments if care is not given to have sufficiently large pots, suitable potting media, and maintenance of pot water status. Clear guidelines are provided for avoiding the confounding effects of water-limited pot binding in studying plant phenotype.

Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data

PubMed Central

Goldstein, Theodore; Paull, Evan O.; Ellis, Matthew J.; Stuart, Joshua M.

2013-01-01

High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes. How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care – which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the “activitome,” help connect genomic events to clinical factors in order to predict the drivers of poor outcome. PMID:23430023

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong

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 unverifiedmore » 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.« less

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

PubMed Central

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. PMID:25540776

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

PubMed

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.

Microfluidics for cell-based high throughput screening platforms - A review.

PubMed

Du, Guansheng; Fang, Qun; den Toonder, Jaap M J

2016-01-15

In the last decades, the basic techniques of microfluidics for the study of cells such as cell culture, cell separation, and cell lysis, have been well developed. Based on cell handling techniques, microfluidics has been widely applied in the field of PCR (Polymerase Chain Reaction), immunoassays, organ-on-chip, stem cell research, and analysis and identification of circulating tumor cells. As a major step in drug discovery, high-throughput screening allows rapid analysis of thousands of chemical, biochemical, genetic or pharmacological tests in parallel. In this review, we summarize the application of microfluidics in cell-based high throughput screening. The screening methods mentioned in this paper include approaches using the perfusion flow mode, the droplet mode, and the microarray mode. We also discuss the future development of microfluidic based high throughput screening platform for drug discovery. Copyright © 2015 Elsevier B.V. All rights reserved.

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

EPA Science Inventory

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...

A high-throughput microRNA expression profiling system.

PubMed

Guo, Yanwen; Mastriano, Stephen; Lu, Jun

2014-01-01

As small noncoding RNAs, microRNAs (miRNAs) regulate diverse biological functions, including physiological and pathological processes. The expression and deregulation of miRNA levels contain rich information with diagnostic and prognostic relevance and can reflect pharmacological responses. The increasing interest in miRNA-related research demands global miRNA expression profiling on large numbers of samples. We describe here a robust protocol that supports high-throughput sample labeling and detection on hundreds of samples simultaneously. This method employs 96-well-based miRNA capturing from total RNA samples and on-site biochemical reactions, coupled with bead-based detection in 96-well format for hundreds of miRNAs per sample. With low-cost, high-throughput, high detection specificity, and flexibility to profile both small and large numbers of samples, this protocol can be adapted in a wide range of laboratory settings.

Optimizing multi-dimensional high throughput screening using zebrafish.

PubMed

Truong, Lisa; Bugel, Sean M; Chlebowski, Anna; Usenko, Crystal Y; Simonich, Michael T; Simonich, Staci L Massey; Tanguay, Robert L

2016-10-01

The use of zebrafish for high throughput screening (HTS) for chemical bioactivity assessments is becoming routine in the fields of drug discovery and toxicology. Here we report current recommendations from our experiences in zebrafish HTS. We compared the effects of different high throughput chemical delivery methods on nominal water concentration, chemical sorption to multi-well polystyrene plates, transcription responses, and resulting whole animal responses. We demonstrate that digital dispensing consistently yields higher data quality and reproducibility compared to standard plastic tip-based liquid handling. Additionally, we illustrate the challenges in using this sensitive model for chemical assessment when test chemicals have trace impurities. Adaptation of these better practices for zebrafish HTS should increase reproducibility across laboratories. Copyright © 2016 Elsevier Inc. All rights reserved.

Development of a central nervous system axonal myelination assay for high throughput screening.

PubMed

Lariosa-Willingham, Karen D; Rosler, Elen S; Tung, Jay S; Dugas, Jason C; Collins, Tassie L; Leonoudakis, Dmitri

2016-04-22

Regeneration of new myelin is impaired in persistent multiple sclerosis (MS) lesions, leaving neurons unable to function properly and subject to further degeneration. Current MS therapies attempt to ameliorate autoimmune-mediated demyelination, but none directly promote the regeneration of lost and damaged myelin of the central nervous system (CNS). Development of new drugs that stimulate remyelination has been hampered by the inability to evaluate axonal myelination in a rapid CNS culture system. We established a high throughput cell-based assay to identify compounds that promote myelination. Culture methods were developed for initiating myelination in vitro using primary embryonic rat cortical cells. We developed an immunofluorescent phenotypic image analysis method to quantify the morphological alignment of myelin characteristic of the initiation of myelination. Using γ-secretase inhibitors as promoters of myelination, the optimal growth, time course and compound treatment conditions were established in a 96 well plate format. We have characterized the cortical myelination assay by evaluating the cellular composition of the cultures and expression of markers of differentiation over the time course of the assay. We have validated the assay scalability and consistency by screening the NIH clinical collection library of 727 compounds and identified ten compounds that promote myelination. Half maximal effective concentration (EC50) values for these compounds were determined to rank them according to potency. We have designed the first high capacity in vitro assay that assesses myelination of live axons. This assay will be ideal for screening large compound libraries to identify new drugs that stimulate myelination. Identification of agents capable of promoting the myelination of axons will likely lead to the development of new therapeutics for MS patients.

HTTK: R Package for High-Throughput Toxicokinetics

EPA Science Inventory

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...

A Multidisciplinary Approach to High Throughput Nuclear Magnetic Resonance Spectroscopy

PubMed Central

Pourmodheji, Hossein; Ghafar-Zadeh, Ebrahim; Magierowski, Sebastian

2016-01-01

Nuclear Magnetic Resonance (NMR) is a non-contact, powerful structure-elucidation technique for biochemical analysis. NMR spectroscopy is used extensively in a variety of life science applications including drug discovery. However, existing NMR technology is limited in that it cannot run a large number of experiments simultaneously in one unit. Recent advances in micro-fabrication technologies have attracted the attention of researchers to overcome these limitations and significantly accelerate the drug discovery process by developing the next generation of high-throughput NMR spectrometers using Complementary Metal Oxide Semiconductor (CMOS). In this paper, we examine this paradigm shift and explore new design strategies for the development of the next generation of high-throughput NMR spectrometers using CMOS technology. A CMOS NMR system consists of an array of high sensitivity micro-coils integrated with interfacing radio-frequency circuits on the same chip. Herein, we first discuss the key challenges and recent advances in the field of CMOS NMR technology, and then a new design strategy is put forward for the design and implementation of highly sensitive and high-throughput CMOS NMR spectrometers. We thereafter discuss the functionality and applicability of the proposed techniques by demonstrating the results. For microelectronic researchers starting to work in the field of CMOS NMR technology, this paper serves as a tutorial with comprehensive review of state-of-the-art technologies and their performance levels. Based on these levels, the CMOS NMR approach offers unique advantages for high resolution, time-sensitive and high-throughput bimolecular analysis required in a variety of life science applications including drug discovery. PMID:27294925

Phenotypic Characterization of a Diversity Panel of Tomato

USDA-ARS?s Scientific Manuscript database

At the USDA, ARS Plant Genetic Resources Unit (PGRU) we have phenotypically characterized more than 2,000 accessions of tomato (Solanum lycopersicum L.) for which data are publically available on the National Plant Germplasm System (NPGS) Germplasm Resources Information Network (GRIN) (http://www.ar...

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity.

PubMed

Seamon, Kyle J; Light, Yooli K; Saada, Edwin A; Schoeniger, Joseph S; Harmon, Brooke

2018-06-05

The RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate its utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seamon, Kyle Jeffrey; Light, Yooli Kim; Saada, Edwin A.

Here, the RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate itsmore » utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.« less

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity

DOE PAGES

Seamon, Kyle Jeffrey; Light, Yooli Kim; Saada, Edwin A.; ...

2018-05-14

Here, the RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate itsmore » utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.« less

Accelerating the Design of Solar Thermal Fuel Materials through High Throughput Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Grossman, JC

2014-12-01

Solar thermal fuels (STF) store the energy of sunlight, which can then be released later in the form of heat, offering an emission-free and renewable solution for both solar energy conversion and storage. However, this approach is currently limited by the lack of low-cost materials with high energy density and high stability. In this Letter, we present an ab initio high-throughput computational approach to accelerate the design process and allow for searches over a broad class of materials. The high-throughput screening platform we have developed can run through large numbers of molecules composed of earth-abundant elements and identifies possible metastablemore » structures of a given material. Corresponding isomerization enthalpies associated with the metastable structures are then computed. Using this high-throughput simulation approach, we have discovered molecular structures with high isomerization enthalpies that have the potential to be new candidates for high-energy density STF. We have also discovered physical principles to guide further STF materials design through structural analysis. More broadly, our results illustrate the potential of using high-throughput ab initio simulations to design materials that undergo targeted structural transitions.« less

Accelerating the design of solar thermal fuel materials through high throughput simulations.

PubMed

Liu, Yun; Grossman, Jeffrey C

2014-12-10

Solar thermal fuels (STF) store the energy of sunlight, which can then be released later in the form of heat, offering an emission-free and renewable solution for both solar energy conversion and storage. However, this approach is currently limited by the lack of low-cost materials with high energy density and high stability. In this Letter, we present an ab initio high-throughput computational approach to accelerate the design process and allow for searches over a broad class of materials. The high-throughput screening platform we have developed can run through large numbers of molecules composed of earth-abundant elements and identifies possible metastable structures of a given material. Corresponding isomerization enthalpies associated with the metastable structures are then computed. Using this high-throughput simulation approach, we have discovered molecular structures with high isomerization enthalpies that have the potential to be new candidates for high-energy density STF. We have also discovered physical principles to guide further STF materials design through structural analysis. More broadly, our results illustrate the potential of using high-throughput ab initio simulations to design materials that undergo targeted structural transitions.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oleynik, D; Panitkin, S; Matteo, Turilli

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

High-throughput Titration of Luciferase-expressing Recombinant Viruses

PubMed Central

Garcia, Vanessa; Krishnan, Ramya; Davis, Colin; Batenchuk, Cory; Le Boeuf, Fabrice; Abdelbary, Hesham; Diallo, Jean-Simon

2014-01-01

Standard plaque assays to determine infectious viral titers can be time consuming, are not amenable to a high volume of samples, and cannot be done with viruses that do not form plaques. As an alternative to plaque assays, we have developed a high-throughput titration method that allows for the simultaneous titration of a high volume of samples in a single day. This approach involves infection of the samples with a Firefly luciferase tagged virus, transfer of the infected samples onto an appropriate permissive cell line, subsequent addition of luciferin, reading of plates in order to obtain luminescence readings, and finally the conversion from luminescence to viral titers. The assessment of cytotoxicity using a metabolic viability dye can be easily incorporated in the workflow in parallel and provide valuable information in the context of a drug screen. This technique provides a reliable, high-throughput method to determine viral titers as an alternative to a standard plaque assay. PMID:25285536

Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections

NASA Technical Reports Server (NTRS)

Tchorowski, Nicole; Murawski, Robert

2014-01-01

New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option

Combining high-throughput sequencing with fruit body surveys reveals contrasting life-history strategies in fungi

PubMed Central

Ovaskainen, Otso; Schigel, Dmitry; Ali-Kovero, Heini; Auvinen, Petri; Paulin, Lars; Nordén, Björn; Nordén, Jenni

2013-01-01

Before the recent revolution in molecular biology, field studies on fungal communities were mostly confined to fruit bodies, whereas mycelial interactions were studied in the laboratory. Here we combine high-throughput sequencing with a fruit body inventory to study simultaneously mycelial and fruit body occurrences in a community of fungi inhabiting dead wood of Norway spruce. We studied mycelial occurrence by extracting DNA from wood samples followed by 454-sequencing of the ITS1 and ITS2 regions and an automated procedure for species identification. In total, we detected 198 species as mycelia and 137 species as fruit bodies. The correlation between mycelial and fruit body occurrences was high for the majority of the species, suggesting that high-throughput sequencing can successfully characterize the dominating fungal communities, despite possible biases related to sampling, PCR, sequencing and molecular identification. We used the fruit body and molecular data to test hypothesized links between life history and population dynamic parameters. We show that the species that have on average a high mycelial abundance also have a high fruiting rate and produce large fruit bodies, leading to a positive feedback loop in their population dynamics. Earlier studies have shown that species with specialized resource requirements are rarely seen fruiting, for which reason they are often classified as red-listed. We show with the help of high-throughput sequencing that some of these species are more abundant as mycelium in wood than what could be expected from their occurrence as fruit bodies. PMID:23575372

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

NASA Astrophysics Data System (ADS)

Sesha Sarath Pokuri, Balaji; Ganapathysubramanian, Baskar

2016-08-01

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

High-Throughput/High-Content Screening Assays with Engineered Nanomaterials in ToxCast

EPA Science Inventory

High-throughput and high-content screens are attractive approaches for prioritizing nanomaterial hazards and informing targeted testing due to the impracticality of using traditional toxicological testing on the large numbers and varieties of nanomaterials. The ToxCast program a...

Application of Unmanned Aircraft Systems (UAS) for phenotypic mapping of white spruce genotypes along environmental gradients

NASA Astrophysics Data System (ADS)

D'Odorico, P.; Wong, C. Y.; Besik, A.; Earon, E.; Isabel, N.; Ensminger, I.

2017-12-01

Rapid climate change is expected to cause a mismatch between locally adapted tree populations and the optimal climatic conditions to which they have adapted. Plant breeding and reforestation programs will increasingly need to rely on high-throughput precision phenotyping tools for the selection of genotypes with increased drought and stress tolerance. In this work, we present the possibilities offered by Unmanned Aircraft Systems (UAS) carrying optical sensors to monitor and assess differences in performance among white spruce genotypes. While high-throughput precision phenotyping using UAS has gained traction in agronomic crop research during the last few years, to our knowledge it is still at its infancy in forestry applications. UAS surveys were performed at different times during the growing season over large white spruce common garden experiments established by the Canadian Forest Service at four different sites, each characterized by 2000 clonally replicated genotypes. Sites are distributed over a latitudinal gradient, in Ontario and Quebec, Canada. The UAS payload consisted of a custom-bands multispectral sensor acquiring radiation at wavelength at which the reflectance spectrum of vegetation is known to capture physiological change under disturbance and stress. Ground based tree-top spectral reflectances and leaf level functional traits were also acquired for validation purposes parallel to UAS surveys. We will discuss the potential and the challenges of using optical sensors on UAS to infer genotypic variation in tree response to stress events and show how spectral data can function as the link between large-scale phenotype and genotype data.

Use of early passage fetal intestinal epithelial cells in semi-high-throughput screening assays: an approach to identify new innate immune system adjuvants.

PubMed

Buckner, Diana; Wilson, Suzanne; Kurk, Sandra; Hardy, Michele; Miessner, Nicole; Jutila, Mark A

2006-09-01

Innate immune system stimulants (innate adjuvants) offer complementary approaches to vaccines and antimicrobial compounds to increase host resistance to infection. The authors established fetal bovine intestinal epithelial cell (BIEC) cultures to screen natural product and synthetic compound libraries for novel mucosal adjuvants. They showed that BIECs from fetal intestine maintained an in vivo phenotype as reflected in cytokeratin expression, expression of antigens restricted to intestinal enterocytes, and induced interleukin-8 (IL-8) production. BIECs could be infected by and support replication of bovine rotavirus. A semi-high-throughput enzyme-linked immunosorbent assay-based assay that measured IL-8 production by BIECs was established and used to screen commercially available natural compounds for novel adjuvant activity. Five novel hits were identified, demonstrating the utility of the assay for selecting and screening new epithelial cell adjuvants. Although the identified compounds had not previously been shown to induce IL-8 production in epithelial cells, other known functions for 3 of the 5 were consistent with this activity. Statistical analysis of the throughput data demonstrated that the assay is adaptable to a high-throughput format for screening both synthetic and natural product derived compound libraries.

Automated crystallographic system for high-throughput protein structure determination.

PubMed

Brunzelle, Joseph S; Shafaee, Padram; Yang, Xiaojing; Weigand, Steve; Ren, Zhong; Anderson, Wayne F

2003-07-01

High-throughput structural genomic efforts require software that is highly automated, distributive and requires minimal user intervention to determine protein structures. Preliminary experiments were set up to test whether automated scripts could utilize a minimum set of input parameters and produce a set of initial protein coordinates. From this starting point, a highly distributive system was developed that could determine macromolecular structures at a high throughput rate, warehouse and harvest the associated data. The system uses a web interface to obtain input data and display results. It utilizes a relational database to store the initial data needed to start the structure-determination process as well as generated data. A distributive program interface administers the crystallographic programs which determine protein structures. Using a test set of 19 protein targets, 79% were determined automatically.

High throughput protein production screening

DOEpatents

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.

GBM heterogeneity characterization by radiomic analysis of phenotype anatomical planes

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

Glioblastoma multiforme (GBM) is the most common malignant primary tumor of the central nervous system, characterized among other traits by rapid metastatis. Three tissue phenotypes closely associated with GBMs, namely, necrosis (N), contrast enhancement (CE), and edema/invasion (E), exhibit characteristic patterns of texture heterogeneity in magnetic resonance images (MRI). In this study, we propose a novel model to characterize GBM tissue phenotypes using gray level co-occurrence matrices (GLCM) in three anatomical planes. The GLCM encodes local image patches in terms of informative, orientation-invariant texture descriptors, which are used here to sub-classify GBM tissue phenotypes. Experiments demonstrate the model on MRI data of 41 GBM patients, obtained from the cancer genome atlas (TCGA). Intensity-based automatic image registration is applied to align corresponding pairs of fixed T1˗weighted (T1˗WI) post-contrast and fluid attenuated inversion recovery (FLAIR) images. GBM tissue regions are then segmented using the 3D Slicer tool. Texture features are computed from 12 quantifier functions operating on GLCM descriptors, that are generated from MRI intensities within segmented GBM tissue regions. Various classifier models are used to evaluate the effectiveness of texture features for discriminating between GBM phenotypes. Results based on T1-WI scans showed a phenotype classification accuracy of over 88.14%, a sensitivity of 85.37% and a specificity of 96.1%, using the linear discriminant analysis (LDA) classifier. This model has the potential to provide important characteristics of tumors, which can be used for the sub-classification of GBM phenotypes.

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

NASA Astrophysics Data System (ADS)

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.

Characterization of the indigenous microflora in raw and pasteurized buffalo milk during storage at refrigeration temperature by high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

The effect of refrigeration on bacterial communities within raw and pasteurized buffalo milk was studied using high-throughput sequencing. High quality samples of raw buffalo milk were obtained from five dairy farms in the Guangxi province of China. A sample of each milk was pasteurized, and both r...

HIGH THROUGHPUT ASSESSMENTS OF CONVENTIONAL AND ALTERNATIVE COMPOUNDS

EPA Science Inventory

High throughput approaches for quantifying chemical hazard, exposure, and sustainability have the potential to dramatically impact the pace and nature of risk assessments. Integrated evaluation strategies developed at the US EPA incorporate inherency,bioactivity,bioavailability, ...

High-throughput methods for electron crystallography.

PubMed

Stokes, David L; Ubarretxena-Belandia, Iban; Gonen, Tamir; Engel, Andreas

2013-01-01

Membrane proteins play a tremendously important role in cell physiology and serve as a target for an increasing number of drugs. Structural information is key to understanding their function and for developing new strategies for combating disease. However, the complex physical chemistry associated with membrane proteins has made them more difficult to study than their soluble cousins. Electron crystallography has historically been a successful method for solving membrane protein structures and has the advantage of providing a native lipid environment for these proteins. Specifically, when membrane proteins form two-dimensional arrays within a lipid bilayer, electron microscopy can be used to collect images and diffraction and the corresponding data can be combined to produce a three-dimensional reconstruction, which under favorable conditions can extend to atomic resolution. Like X-ray crystallography, the quality of the structures are very much dependent on the order and size of the crystals. However, unlike X-ray crystallography, high-throughput methods for screening crystallization trials for electron crystallography are not in general use. In this chapter, we describe two alternative methods for high-throughput screening of membrane protein crystallization within the lipid bilayer. The first method relies on the conventional use of dialysis for removing detergent and thus reconstituting the bilayer; an array of dialysis wells in the standard 96-well format allows the use of a liquid-handling robot and greatly increases throughput. The second method relies on titration of cyclodextrin as a chelating agent for detergent; a specialized pipetting robot has been designed not only to add cyclodextrin in a systematic way, but to use light scattering to monitor the reconstitution process. In addition, the use of liquid-handling robots for making negatively stained grids and methods for automatically imaging samples in the electron microscope are described.

MRI phenotypes with high neurodegeneration are associated with peripheral blood B-cell changes.

PubMed

Comabella, Manuel; Cantó, Ester; Nurtdinov, Ramil; Río, Jordi; Villar, Luisa M; Picón, Carmen; Castilló, Joaquín; Fissolo, Nicolás; Aymerich, Xavier; Auger, Cristina; Rovira, Alex; Montalban, Xavier

2016-01-15

Little is known about the mechanisms leading to neurodegeneration in multiple sclerosis (MS) and the role of peripheral blood cells in this neurodegenerative component. We aimed to correlate brain radiological phenotypes defined by high and low neurodegeneration with gene expression profiling of peripheral blood mononuclear cells (PBMC) from MS patients. Magnetic resonance imaging (MRI) scans from 64 patients with relapsing-remitting MS (RRMS) were classified into radiological phenotypes characterized by low (N = 27) and high (N = 37) neurodegeneration according to the number of contrast-enhancing lesions, the relative volume of non-enhancing black holes on T1-weighted images, and the brain parenchymal fraction. Gene expression profiling was determined in PBMC using microarrays, and validation of selected genes was performed by polymerase chain reaction (PCR). B-cell immunophenotyping was conducted by flow cytometry. Microarray analysis revealed the B-cell specific genes FCRL1, FCRL2, FCRL5 (Fc receptor-like 1, 2 and 5 respectively), and CD22 as the top differentially expressed genes between patients with high and low neurodegeneration. Levels for these genes were significantly down-regulated in PBMC from patients with MRI phenotypes characterized by high neurodegeneration and microarray findings were validated by PCR. In patients with high neurodegeneration, immunophenotyping showed a significant increase in the expression of the B-cell activation markers CD80 in naïve B cells (CD45+/CD19+/CD27-/IgD+), unswitched memory B cells (CD45+/CD19+/CD27+/IgD+), and switched memory B cells (CD45+/CD19+/CD27+/IgD-), and CD86 in naïve and switched memory B cells. These results suggest that RRMS patients with radiological phenotypes showing high neurodegeneration have changes in B cells characterized by down-regulation of B-cell-specific genes and increased activation status. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions

Identification of optimal solar fuel electrocatalysts via high throughput in situ optical measurements

DOE PAGES

Shinde, Aniketa; Guevarra, Dan; Haber, Joel A.; ...

2014-10-21

For many solar fuel generator designs involve illumination of a photoabsorber stack coated with a catalyst for the oxygen evolution reaction (OER). In this design, impinging light must pass through the catalyst layer before reaching the photoabsorber(s), and thus optical transmission is an important function of the OER catalyst layer. Many oxide catalysts, such as those containing elements Ni and Co, form oxide or oxyhydroxide phases in alkaline solution at operational potentials that differ from the phases observed in ambient conditions. To characterize the transparency of such catalysts during OER operation, 1031 unique compositions containing the elements Ni, Co, Ce,more » La, and Fe were prepared by a high throughput inkjet printing technique. Moreover, the catalytic current of each composition was recorded at an OER overpotential of 0.33 V with simultaneous measurement of the spectral transmission. By combining the optical and catalytic properties, the combined catalyst efficiency was calculated to identify the optimal catalysts for solar fuel applications within the material library. Our measurements required development of a new high throughput instrument with integrated electrochemistry and spectroscopy measurements, which enables various spectroelectrochemistry experiments.« less

Metagenomic analysis and functional characterization of the biogas microbiome using high throughput shotgun sequencing and a novel binning strategy.

PubMed

Campanaro, Stefano; Treu, Laura; Kougias, Panagiotis G; De Francisci, Davide; Valle, Giorgio; Angelidaki, Irini

2016-01-01

Biogas production is an economically attractive technology that has gained momentum worldwide over the past years. Biogas is produced by a biologically mediated process, widely known as "anaerobic digestion." This process is performed by a specialized and complex microbial community, in which different members have distinct roles in the establishment of a collective organization. Deciphering the complex microbial community engaged in this process is interesting both for unraveling the network of bacterial interactions and for applicability potential to the derived knowledge. In this study, we dissect the bioma involved in anaerobic digestion by means of high throughput Illumina sequencing (~51 gigabases of sequence data), disclosing nearly one million genes and extracting 106 microbial genomes by a novel strategy combining two binning processes. Microbial phylogeny and putative taxonomy performed using >400 proteins revealed that the biogas community is a trove of new species. A new approach based on functional properties as per network representation was developed to assign roles to the microbial species. The organization of the anaerobic digestion microbiome is resembled by a funnel concept, in which the microbial consortium presents a progressive functional specialization while reaching the final step of the process (i.e., methanogenesis). Key microbial genomes encoding enzymes involved in specific metabolic pathways, such as carbohydrates utilization, fatty acids degradation, amino acids fermentation, and syntrophic acetate oxidation, were identified. Additionally, the analysis identified a new uncultured archaeon that was putatively related to Methanomassiliicoccales but surprisingly having a methylotrophic methanogenic pathway. This study is a pioneer research on the phylogenetic and functional characterization of the microbial community populating biogas reactors. By applying for the first time high-throughput sequencing and a novel binning strategy, the

High-throughput continuous hydrothermal synthesis of nanomaterials (part II): unveiling the as-prepared CexZryYzO2-δ phase diagram.

PubMed

Quesada-Cabrera, Raul; Weng, Xiaole; Hyett, Geoff; Clark, Robin J H; Wang, Xue Z; Darr, Jawwad A

2013-09-09

High-throughput continuous hydrothermal flow synthesis was used to manufacture 66 unique nanostructured oxide samples in the Ce-Zr-Y-O system. This synthesis approach resulted in a significant increase in throughput compared to that of conventional batch or continuous hydrothermal synthesis methods. The as-prepared library samples were placed into a wellplate for both automated high-throughput powder X-ray diffraction and Raman spectroscopy data collection, which allowed comprehensive structural characterization and phase mapping. The data suggested that a continuous cubic-like phase field connects all three Ce-Zr-O, Ce-Y-O, and Y-Zr-O binary systems together with a smooth and steady transition between the structures of neighboring compositions. The continuous hydrothermal process led to as-prepared crystallite sizes in the range of 2-7 nm (as determined by using the Scherrer equation).

Using high throughput sequencing to explore the biodiversity in oral bacterial communities.

PubMed

Diaz, P I; Dupuy, A K; Abusleme, L; Reese, B; Obergfell, C; Choquette, L; Dongari-Bagtzoglou, A; Peterson, D E; Terzi, E; Strausbaugh, L D

2012-06-01

High throughput sequencing of 16S ribosomal RNA gene amplicons is a cost-effective method for characterization of oral bacterial communities. However, before undertaking large-scale studies, it is necessary to understand the technique-associated limitations and intrinsic variability of the oral ecosystem. In this work we evaluated bias in species representation using an in vitro-assembled mock community of oral bacteria. We then characterized the bacterial communities in saliva and buccal mucosa of five healthy subjects to investigate the power of high throughput sequencing in revealing their diversity and biogeography patterns. Mock community analysis showed primer and DNA isolation biases and an overestimation of diversity that was reduced after eliminating singleton operational taxonomic units (OTUs). Sequencing of salivary and mucosal communities found a total of 455 OTUs (0.3% dissimilarity) with only 78 of these present in all subjects. We demonstrate that this variability was partly the result of incomplete richness coverage even at great sequencing depths, and so comparing communities by their structure was more effective than comparisons based solely on membership. With respect to oral biogeography, we found inter-subject variability in community structure was lower than site differences between salivary and mucosal communities within subjects. These differences were evident at very low sequencing depths and were mostly caused by the abundance of Streptococcus mitis and Gemella haemolysans in mucosa. In summary, we present an experimental and data analysis framework that will facilitate design and interpretation of pyrosequencing-based studies. Despite challenges associated with this technique, we demonstrate its power for evaluation of oral diversity and biogeography patterns. © 2012 John Wiley & Sons A/S.

Condor-COPASI: high-throughput computing for biochemical networks

PubMed Central

2012-01-01

Background Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. Results We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays. Conclusions Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage. PMID:22834945

High throughput and miniaturised systems for biodegradability assessments.

PubMed

Cregut, Mickael; Jouanneau, Sulivan; Brillet, François; Durand, Marie-José; Sweetlove, Cyril; Chenèble, Jean-Charles; L'Haridon, Jacques; Thouand, Gérald

2014-01-01

The society demands safer products with a better ecological profile. Regulatory criteria have been developed to prevent risks for human health and the environment, for example, within the framework of the European regulation REACH (Regulation (EC) No 1907, 2006). This has driven industry to consider the development of high throughput screening methodologies for assessing chemical biodegradability. These new screening methodologies must be scalable for miniaturisation, reproducible and as reliable as existing procedures for enhanced biodegradability assessment. Here, we evaluate two alternative systems that can be scaled for high throughput screening and conveniently miniaturised to limit costs in comparison with traditional testing. These systems are based on two dyes as follows: an invasive fluorescent dyes that serves as a cellular activity marker (a resazurin-like dye reagent) and a noninvasive fluorescent oxygen optosensor dye (an optical sensor). The advantages and limitations of these platforms for biodegradability assessment are presented. Our results confirm the feasibility of these systems for evaluating and screening chemicals for ready biodegradability. The optosensor is a miniaturised version of a component already used in traditional ready biodegradability testing, whereas the resazurin dye offers an interesting new screening mechanism for chemical concentrations greater than 10 mg/l that are not amenable to traditional closed bottle tests. The use of these approaches allows generalisation of high throughput screening methodologies to meet the need of developing new compounds with a favourable ecological profile and also assessment for regulatory purpose.

High-throughput characterization of sediment organic matter by pyrolysis-gas chromatography/mass spectrometry and multivariate curve resolution: A promising analytical tool in (paleo)limnology.

PubMed

Tolu, Julie; Gerber, Lorenz; Boily, Jean-François; Bindler, Richard

2015-06-23

Molecular-level chemical information about organic matter (OM) in sediments helps to establish the sources of OM and the prevalent degradation/diagenetic processes, both essential for understanding the cycling of carbon (C) and of the elements associated with OM (toxic trace metals and nutrients) in lake ecosystems. Ideally, analytical methods for characterizing OM should allow high sample throughput, consume small amounts of sample and yield relevant chemical information, which are essential for multidisciplinary, high-temporal resolution and/or large spatial scale investigations. We have developed a high-throughput analytical method based on pyrolysis-gas chromatography/mass spectrometry and automated data processing to characterize sedimentary OM in sediments. Our method consumes 200 μg of freeze-dried and ground sediment sample. Pyrolysis was performed at 450°C, which was found to avoid degradation of specific biomarkers (e.g., lignin compounds, fresh carbohydrates/cellulose) compared to 650°C, which is in the range of temperatures commonly applied for environmental samples. The optimization was conducted using the top ten sediment samples of an annually resolved sediment record (containing 16-18% and 1.3-1.9% of total carbon and nitrogen, respectively). Several hundred pyrolytic compound peaks were detected of which over 200 were identified, which represent different classes of organic compounds (i.e., n-alkanes, n-alkenes, 2-ketones, carboxylic acids, carbohydrates, proteins, other N compounds, (methoxy)phenols, (poly)aromatics, chlorophyll and steroids/hopanoids). Technical reproducibility measured as relative standard deviation of the identified peaks in triplicate analyses was 5.5±4.3%, with 90% of the RSD values within 10% and 98% within 15%. Finally, a multivariate calibration model was calculated between the pyrolytic degradation compounds and the sediment depth (i.e., sediment age), which is a function of degradation processes and changes in OM

MIPHENO: Data normalization for high throughput metabolic analysis.

EPA Science Inventory

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...

High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME

NASA Astrophysics Data System (ADS)

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.

High-throughput search of ternary chalcogenides for p-type transparent electrodes

PubMed Central

Shi, Jingming; Cerqueira, Tiago F. T.; Cui, Wenwen; Nogueira, Fernando; Botti, Silvana; Marques, Miguel A. L.

2017-01-01

Delafossite crystals are fascinating ternary oxides that have demonstrated transparent conductivity and ambipolar doping. Here we use a high-throughput approach based on density functional theory to find delafossite and related layered phases of composition ABX2, where A and B are elements of the periodic table, and X is a chalcogen (O, S, Se, and Te). From the 15 624 compounds studied in the trigonal delafossite prototype structure, 285 are within 50 meV/atom from the convex hull of stability. These compounds are further investigated using global structural prediction methods to obtain their lowest-energy crystal structure. We find 79 systems not present in the materials project database that are thermodynamically stable and crystallize in the delafossite or in closely related structures. These novel phases are then characterized by calculating their band gaps and hole effective masses. This characterization unveils a large diversity of properties, ranging from normal metals, magnetic metals, and some candidate compounds for p-type transparent electrodes. PMID:28266587

High-throughput genotyping assay for the large-scale genetic characterization of Cryptosporidium parasites from human and bovine samples.

PubMed

Abal-Fabeiro, J L; Maside, X; Llovo, J; Bello, X; Torres, M; Treviño, M; Moldes, L; Muñoz, A; Carracedo, A; Bartolomé, C

2014-04-01

The epidemiological study of human cryptosporidiosis requires the characterization of species and subtypes involved in human disease in large sample collections. Molecular genotyping is costly and time-consuming, making the implementation of low-cost, highly efficient technologies increasingly necessary. Here, we designed a protocol based on MALDI-TOF mass spectrometry for the high-throughput genotyping of a panel of 55 single nucleotide variants (SNVs) selected as markers for the identification of common gp60 subtypes of four Cryptosporidium species that infect humans. The method was applied to a panel of 608 human and 63 bovine isolates and the results were compared with control samples typed by Sanger sequencing. The method allowed the identification of species in 610 specimens (90·9%) and gp60 subtype in 605 (90·2%). It displayed excellent performance, with sensitivity and specificity values of 87·3 and 98·0%, respectively. Up to nine genotypes from four different Cryptosporidium species (C. hominis, C. parvum, C. meleagridis and C. felis) were detected in humans; the most common ones were C. hominis subtype Ib, and C. parvum IIa (61·3 and 28·3%, respectively). 96·5% of the bovine samples were typed as IIa. The method performs as well as the widely used Sanger sequencing and is more cost-effective and less time consuming.

Controlling high-throughput manufacturing at the nano-scale

NASA Astrophysics Data System (ADS)

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.

NIR and Py-mbms coupled with multivariate data analysis as a high-throughput biomass characterization technique: a review

PubMed Central

Xiao, Li; Wei, Hui; Himmel, Michael E.; Jameel, Hasan; Kelley, Stephen S.

2014-01-01

Optimizing the use of lignocellulosic biomass as the feedstock for renewable energy production is currently being developed globally. Biomass is a complex mixture of cellulose, hemicelluloses, lignins, extractives, and proteins; as well as inorganic salts. Cell wall compositional analysis for biomass characterization is laborious and time consuming. In order to characterize biomass fast and efficiently, several high through-put technologies have been successfully developed. Among them, near infrared spectroscopy (NIR) and pyrolysis-molecular beam mass spectrometry (Py-mbms) are complementary tools and capable of evaluating a large number of raw or modified biomass in a short period of time. NIR shows vibrations associated with specific chemical structures whereas Py-mbms depicts the full range of fragments from the decomposition of biomass. Both NIR vibrations and Py-mbms peaks are assigned to possible chemical functional groups and molecular structures. They provide complementary information of chemical insight of biomaterials. However, it is challenging to interpret the informative results because of the large amount of overlapping bands or decomposition fragments contained in the spectra. In order to improve the efficiency of data analysis, multivariate analysis tools have been adapted to define the significant correlations among data variables, so that the large number of bands/peaks could be replaced by a small number of reconstructed variables representing original variation. Reconstructed data variables are used for sample comparison (principal component analysis) and for building regression models (partial least square regression) between biomass chemical structures and properties of interests. In this review, the important biomass chemical structures measured by NIR and Py-mbms are summarized. The advantages and disadvantages of conventional data analysis methods and multivariate data analysis methods are introduced, compared and evaluated. This review

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

High-throughput bioinformatics with the Cyrille2 pipeline system

PubMed Central

Fiers, Mark WEJ; van der Burgt, Ate; Datema, Erwin; de Groot, Joost CW; van Ham, Roeland CHJ

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 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. PMID:18269742

New High Throughput Methods to Estimate Chemical Exposure

EPA Science Inventory

EPA has made many recent advances in high throughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing an...

High-throughput gene mapping in Caenorhabditis elegans.

PubMed

Swan, Kathryn A; Curtis, Damian E; McKusick, Kathleen B; Voinov, Alexander V; Mapa, Felipa A; Cancilla, Michael R

2002-07-01

Positional cloning of mutations in model genetic systems is a powerful method for the identification of targets of medical and agricultural importance. To facilitate the high-throughput mapping of mutations in Caenorhabditis elegans, we have identified a further 9602 putative new single nucleotide polymorphisms (SNPs) between two C. elegans strains, Bristol N2 and the Hawaiian mapping strain CB4856, by sequencing inserts from a CB4856 genomic DNA library and using an informatics pipeline to compare sequences with the canonical N2 genomic sequence. When combined with data from other laboratories, our marker set of 17,189 SNPs provides even coverage of the complete worm genome. To date, we have confirmed >1099 evenly spaced SNPs (one every 91 +/- 56 kb) across the six chromosomes and validated the utility of our SNP marker set and new fluorescence polarization-based genotyping methods for systematic and high-throughput identification of genes in C. elegans by cloning several proprietary genes. We illustrate our approach by recombination mapping and confirmation of the mutation in the cloned gene, dpy-18.

Classification of large circulating tumor cells isolated with ultra-high throughput microfluidic Vortex technology.

PubMed

Che, James; Yu, Victor; Dhar, Manjima; Renier, Corinne; Matsumoto, Melissa; Heirich, Kyra; Garon, Edward B; Goldman, Jonathan; Rao, Jianyu; Sledge, George W; Pegram, Mark D; Sheth, Shruti; Jeffrey, Stefanie S; Kulkarni, Rajan P; Sollier, Elodie; Di Carlo, Dino

2016-03-15

Circulating tumor cells (CTCs) are emerging as rare but clinically significant non-invasive cellular biomarkers for cancer patient prognosis, treatment selection, and treatment monitoring. Current CTC isolation approaches, such as immunoaffinity, filtration, or size-based techniques, are often limited by throughput, purity, large output volumes, or inability to obtain viable cells for downstream analysis. For all technologies, traditional immunofluorescent staining alone has been employed to distinguish and confirm the presence of isolated CTCs among contaminating blood cells, although cells isolated by size may express vastly different phenotypes. Consequently, CTC definitions have been non-trivial, researcher-dependent, and evolving. Here we describe a complete set of objective criteria, leveraging well-established cytomorphological features of malignancy, by which we identify large CTCs. We apply the criteria to CTCs enriched from stage IV lung and breast cancer patient blood samples using the High Throughput Vortex Chip (Vortex HT), an improved microfluidic technology for the label-free, size-based enrichment and concentration of rare cells. We achieve improved capture efficiency (up to 83%), high speed of processing (8 mL/min of 10x diluted blood, or 800 μL/min of whole blood), and high purity (avg. background of 28.8±23.6 white blood cells per mL of whole blood). We show markedly improved performance of CTC capture (84% positive test rate) in comparison to previous Vortex designs and the current FDA-approved gold standard CellSearch assay. The results demonstrate the ability to quickly collect viable and pure populations of abnormal large circulating cells unbiased by molecular characteristics, which helps uncover further heterogeneity in these cells.

Classification of large circulating tumor cells isolated with ultra-high throughput microfluidic Vortex technology

PubMed Central

Che, James; Yu, Victor; Dhar, Manjima; Renier, Corinne; Matsumoto, Melissa; Heirich, Kyra; Garon, Edward B.; Goldman, Jonathan; Rao, Jianyu; Sledge, George W.; Pegram, Mark D.; Sheth, Shruti; Jeffrey, Stefanie S.; Kulkarni, Rajan P.; Sollier, Elodie; Di Carlo, Dino

2016-01-01

Circulating tumor cells (CTCs) are emerging as rare but clinically significant non-invasive cellular biomarkers for cancer patient prognosis, treatment selection, and treatment monitoring. Current CTC isolation approaches, such as immunoaffinity, filtration, or size-based techniques, are often limited by throughput, purity, large output volumes, or inability to obtain viable cells for downstream analysis. For all technologies, traditional immunofluorescent staining alone has been employed to distinguish and confirm the presence of isolated CTCs among contaminating blood cells, although cells isolated by size may express vastly different phenotypes. Consequently, CTC definitions have been non-trivial, researcher-dependent, and evolving. Here we describe a complete set of objective criteria, leveraging well-established cytomorphological features of malignancy, by which we identify large CTCs. We apply the criteria to CTCs enriched from stage IV lung and breast cancer patient blood samples using the High Throughput Vortex Chip (Vortex HT), an improved microfluidic technology for the label-free, size-based enrichment and concentration of rare cells. We achieve improved capture efficiency (up to 83%), high speed of processing (8 mL/min of 10x diluted blood, or 800 μL/min of whole blood), and high purity (avg. background of 28.8±23.6 white blood cells per mL of whole blood). We show markedly improved performance of CTC capture (84% positive test rate) in comparison to previous Vortex designs and the current FDA-approved gold standard CellSearch assay. The results demonstrate the ability to quickly collect viable and pure populations of abnormal large circulating cells unbiased by molecular characteristics, which helps uncover further heterogeneity in these cells. PMID:26863573

High-throughput label-free screening of euglena gracilis with optofluidic time-stretch quantitative phase microscopy

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Yaxiaer, Yalikun; Kobayashi, Hirofumi; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-02-01

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis - an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

Selective phenotyping traits related to multiple stress and drought response in dry bean

USDA-ARS?s Scientific Manuscript database

Dry bean (Phaseolus vulgaris L.) tolerance to stressful environments is not well understood. Moreover, the increasing population sizes necessary for improving genomic resolution of QTL conditioning stress response has made it difficult for phenotyping to keep pace with high throughput genotyping. ...

Characterization and complete genome sequence of a panicovirus from Bermuda grass by high-throughput sequencing.

PubMed

Tahir, Muhammad N; Lockhart, Ben; Grinstead, Samuel; Mollov, Dimitre

2017-04-01

Bermuda grass samples were examined by transmission electron microscopy and 28-30 nm spherical virus particles were observed. Total RNA from these plants was subjected to high-throughput sequencing (HTS). The nearly full genome sequence of a panicovirus was identified from one HTS scaffold. Sanger sequencing was used to confirm the HTS results and complete the genome sequence of 4404 nt. This virus was provisionally named Bermuda grass latent virus (BGLV). Its predicted open reading frames follow the typical arrangement of the genus Panicovirus. Based on sequence comparisons and phylogenetic analyses BGLV differs from other viruses and therefore taxonomically it is a new member of the genus Panicovirus, family Tombusviridae.

The autism sequencing consortium: large-scale, high-throughput sequencing in autism spectrum disorders.

PubMed

Buxbaum, Joseph D; Daly, Mark J; Devlin, Bernie; Lehner, Thomas; Roeder, Kathryn; State, Matthew W

2012-12-20

Research during the past decade has seen significant progress in the understanding of the genetic architecture of autism spectrum disorders (ASDs), with gene discovery accelerating as the characterization of genomic variation has become increasingly comprehensive. At the same time, this research has highlighted ongoing challenges. Here we address the enormous impact of high-throughput sequencing (HTS) on ASD gene discovery, outline a consensus view for leveraging this technology, and describe a large multisite collaboration developed to accomplish these goals. Similar approaches could prove effective for severe neurodevelopmental disorders more broadly. Copyright © 2012 Elsevier Inc. All rights reserved.

Development of high-throughput and high sensitivity capillary gel electrophoresis platform method for Western, Eastern, and Venezuelan equine encephalitis (WEVEE) virus like particles (VLPs) purity determination and characterization.

PubMed

Gollapudi, Deepika; Wycuff, Diane L; Schwartz, Richard M; Cooper, Jonathan W; Cheng, K C

2017-10-01

In this paper, we describe development of a high-throughput, highly sensitive method based on Lab Chip CGE-SDS platform for purity determination and characterization of virus-like particle (VLP) vaccines. A capillary gel electrophoresis approach requiring about 41 s per sample for analysis and demonstrating sensitivity to protein initial concentrations as low as 20 μg/mL, this method has been used previously to evaluate monoclonal antibodies, but this application for lot release assay of VLPs using this platform is unique. The method was qualified and shown to be accurate for the quantitation of VLP purity. Assay repeatability was confirmed to be less than 2% relative standard deviation of the mean (% RSD) with interday precision less than 2% RSD. The assay can evaluate purified VLPs in a concentration range of 20-249 μg/mL for VEE and 20-250 μg/mL for EEE and WEE VLPs. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

NASA Astrophysics Data System (ADS)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

The JCSG high-throughput structural biology pipeline.

PubMed

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

2010-10-01

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. 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.

High Throughput Exposure Estimation Using NHANES Data (SOT)

EPA Science Inventory

In the ExpoCast project, high throughput (HT) exposure models enable rapid screening of large numbers of chemicals for exposure potential. Evaluation of these models requires empirical exposure data and due to the paucity of human metabolism/exposure data such evaluations includ...

Evaluating and Refining High Throughput Tools for Toxicokinetics

EPA Science Inventory

This poster summarizes efforts of the Chemical Safety for Sustainability's Rapid Exposure and Dosimetry (RED) team to facilitate the development and refinement of toxicokinetics (TK) tools to be used in conjunction with the high throughput toxicity testing data generated as a par...

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

NASA Astrophysics Data System (ADS)

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

2009-06-01

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

Development of rapid and sensitive high throughput pharmacologic assays for marine phycotoxins.

PubMed

Van Dolah, F M; Finley, E L; Haynes, B L; Doucette, G J; Moeller, P D; Ramsdell, J S

1994-01-01

The lack of rapid, high throughput assays is a major obstacle to many aspects of research on marine phycotoxins. Here we describe the application of microplate scintillation technology to develop high throughput assays for several classes of marine phycotoxin based on their differential pharmacologic actions. High throughput "drug discovery" format microplate receptor binding assays developed for brevetoxins/ciguatoxins and for domoic acid are described. Analysis for brevetoxins/ciguatoxins is carried out by binding competition with [3H] PbTx-3 for site 5 on the voltage dependent sodium channel in rat brain synaptosomes. Analysis of domoic acid is based on binding competition with [3H] kainic acid for the kainate/quisqualate glutamate receptor using frog brain synaptosomes. In addition, a high throughput microplate 45Ca flux assay for determination of maitotoxins is described. These microplate assays can be completed within 3 hours, have sensitivities of less than 1 ng, and can analyze dozens of samples simultaneously. The assays have been demonstrated to be useful for assessing algal toxicity and for assay-guided purification of toxins, and are applicable to the detection of biotoxins in seafood.

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing

PubMed Central

Morgan, Horatio H.; du Toit, Maret; Setati, Mathabatha E.

2017-01-01

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity. PMID:28553266

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing.

PubMed

Morgan, Horatio H; du Toit, Maret; Setati, Mathabatha E

2017-01-01

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity.

Deciphering the genomic targets of alkylating polyamide conjugates using high-throughput sequencing

PubMed Central

Chandran, Anandhakumar; Syed, Junetha; Taylor, Rhys D.; Kashiwazaki, Gengo; Sato, Shinsuke; Hashiya, Kaori; Bando, Toshikazu; Sugiyama, Hiroshi

2016-01-01

Chemically engineered small molecules targeting specific genomic sequences play an important role in drug development research. Pyrrole-imidazole polyamides (PIPs) are a group of molecules that can bind to the DNA minor-groove and can be engineered to target specific sequences. Their biological effects rely primarily on their selective DNA binding. However, the binding mechanism of PIPs at the chromatinized genome level is poorly understood. Herein, we report a method using high-throughput sequencing to identify the DNA-alkylating sites of PIP-indole-seco-CBI conjugates. High-throughput sequencing analysis of conjugate 2 showed highly similar DNA-alkylating sites on synthetic oligos (histone-free DNA) and on human genomes (chromatinized DNA context). To our knowledge, this is the first report identifying alkylation sites across genomic DNA by alkylating PIP conjugates using high-throughput sequencing. PMID:27098039

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

PubMed

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.

Repurposing a Benchtop Centrifuge for High-Throughput Single-Molecule Force Spectroscopy.

PubMed

Yang, Darren; Wong, Wesley P

2018-01-01

We present high-throughput single-molecule manipulation using a benchtop centrifuge, overcoming limitations common in other single-molecule approaches such as high cost, low throughput, technical difficulty, and strict infrastructure requirements. An inexpensive and compact Centrifuge Force Microscope (CFM) adapted to a commercial centrifuge enables use by nonspecialists, and integration with DNA nanoswitches facilitates both reliable measurements and repeated molecular interrogation. Here, we provide detailed protocols for constructing the CFM, creating DNA nanoswitch samples, and carrying out single-molecule force measurements.

Integrated crystal mounting and alignment system for high-throughput biological crystallography

DOEpatents

Nordmeyer, Robert A.; Snell, Gyorgy P.; Cornell, Earl W.; Kolbe, William F.; Yegian, Derek T.; Earnest, Thomas N.; Jaklevich, Joseph M.; Cork, Carl W.; Santarsiero, Bernard D.; Stevens, Raymond C.

2007-09-25

A method and apparatus for the transportation, remote and unattended mounting, and visual alignment and monitoring of protein crystals for synchrotron generated x-ray diffraction analysis. The protein samples are maintained at liquid nitrogen temperatures at all times: during shipment, before mounting, mounting, alignment, data acquisition and following removal. The samples must additionally be stably aligned to within a few microns at a point in space. The ability to accurately perform these tasks remotely and automatically leads to a significant increase in sample throughput and reliability for high-volume protein characterization efforts. Since the protein samples are placed in a shipping-compatible layered stack of sample cassettes each holding many samples, a large number of samples can be shipped in a single cryogenic shipping container.

Integrated crystal mounting and alignment system for high-throughput biological crystallography

DOEpatents

Nordmeyer, Robert A.; Snell, Gyorgy P.; Cornell, Earl W.; Kolbe, William; Yegian, Derek; Earnest, Thomas N.; Jaklevic, Joseph M.; Cork, Carl W.; Santarsiero, Bernard D.; Stevens, Raymond C.

2005-07-19

A method and apparatus for the transportation, remote and unattended mounting, and visual alignment and monitoring of protein crystals for synchrotron generated x-ray diffraction analysis. The protein samples are maintained at liquid nitrogen temperatures at all times: during shipment, before mounting, mounting, alignment, data acquisition and following removal. The samples must additionally be stably aligned to within a few microns at a point in space. The ability to accurately perform these tasks remotely and automatically leads to a significant increase in sample throughput and reliability for high-volume protein characterization efforts. Since the protein samples are placed in a shipping-compatible layered stack of sample cassettes each holding many samples, a large number of samples can be shipped in a single cryogenic shipping container.

High throughput light absorber discovery, Part 1: An algorithm for automated tauc analysis

DOE PAGES

Suram, Santosh K.; Newhouse, Paul F.; Gregoire, John M.

2016-09-23

High-throughput experimentation provides efficient mapping of composition-property relationships, and its implementation for the discovery of optical materials enables advancements in solar energy and other technologies. In a high throughput pipeline, automated data processing algorithms are often required to match experimental throughput, and we present an automated Tauc analysis algorithm for estimating band gap energies from optical spectroscopy data. The algorithm mimics the judgment of an expert scientist, which is demonstrated through its application to a variety of high throughput spectroscopy data, including the identification of indirect or direct band gaps in Fe 2O 3, Cu 2V 2O 7, and BiVOmore » 4. Here, the applicability of the algorithm to estimate a range of band gap energies for various materials is demonstrated by a comparison of direct-allowed band gaps estimated by expert scientists and by automated algorithm for 60 optical spectra.« less

SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states.

PubMed

Wu, Jian; Dai, Wei; Wu, Lin; Wang, Jinke

2018-02-13

Next-generation sequencing (NGS) is fundamental to the current biological and biomedical research. Construction of sequencing library is a key step of NGS. Therefore, various library construction methods have been explored. However, the current methods are still limited by some shortcomings. This study developed a new NGS library construction method, Single strand Adaptor Library Preparation (SALP), by using a novel single strand adaptor (SSA). SSA is a double-stranded oligonucleotide with a 3' overhang of 3 random nucleotides, which can be efficiently ligated to the 3' end of single strand DNA by T4 DNA ligase. SALP can be started with any denatured DNA fragments such as those sheared by Tn5 tagmentation, enzyme digestion and sonication. When started with Tn5-tagmented chromatin, SALP can overcome a key limitation of ATAC-seq and become a high-throughput NGS library construction method, SALP-seq, which can be used to comparatively characterize the chromatin openness state of multiple cells unbiasly. In this way, this study successfully characterized the comparative chromatin openness states of four different cell lines, including GM12878, HepG2, HeLa and 293T, with SALP-seq. Similarly, this study also successfully characterized the chromatin openness states of HepG2 cells with SALP-seq by using 10 5 to 500 cells. This study developed a new NGS library construction method, SALP, by using a novel kind of single strand adaptor (SSA), which should has wide applications in the future due to its unique performance.

High-throughput measurements of the optical redox ratio using a commercial microplate reader.

PubMed

Cannon, Taylor M; Shah, Amy T; Walsh, Alex J; Skala, Melissa C

2015-01-01

There is a need for accurate, high-throughput, functional measures to gauge the efficacy of potential drugs in living cells. As an early marker of drug response in cells, cellular metabolism provides an attractive platform for high-throughput drug testing. Optical techniques can noninvasively monitor NADH and FAD, two autofluorescent metabolic coenzymes. The autofluorescent redox ratio, defined as the autofluorescence intensity of NADH divided by that of FAD, quantifies relative rates of cellular glycolysis and oxidative phosphorylation. However, current microscopy methods for redox ratio quantification are time-intensive and low-throughput, limiting their practicality in drug screening. Alternatively, high-throughput commercial microplate readers quickly measure fluorescence intensities for hundreds of wells. This study found that a commercial microplate reader can differentiate the receptor status of breast cancer cell lines (p < 0.05) based on redox ratio measurements without extrinsic contrast agents. Furthermore, microplate reader redox ratio measurements resolve response (p < 0.05) and lack of response (p > 0.05) in cell lines that are responsive and nonresponsive, respectively, to the breast cancer drug trastuzumab. These studies indicate that the microplate readers can be used to measure the redox ratio in a high-throughput manner and are sensitive enough to detect differences in cellular metabolism that are consistent with microscopy results.

Fun with High Throughput Toxicokinetics (CalEPA webinar)

EPA Science Inventory

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 ...

High-throughput screening, predictive modeling and computational embryology

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to profile thousands of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition to projects worldwide,...

Investigation of Human Cancers for Retrovirus by Low-Stringency Target Enrichment and High-Throughput Sequencing.

PubMed

Vinner, Lasse; Mourier, Tobias; Friis-Nielsen, Jens; Gniadecki, Robert; Dybkaer, Karen; Rosenberg, Jacob; Langhoff, Jill Levin; Cruz, David Flores Santa; Fonager, Jannik; Izarzugaza, Jose M G; Gupta, Ramneek; Sicheritz-Ponten, Thomas; Brunak, Søren; Willerslev, Eske; Nielsen, Lars Peter; Hansen, Anders Johannes

2015-08-19

Although nearly one fifth of all human cancers have an infectious aetiology, the causes for the majority of cancers remain unexplained. Despite the enormous data output from high-throughput shotgun sequencing, viral DNA in a clinical sample typically constitutes a proportion of host DNA that is too small to be detected. Sequence variation among virus genomes complicates application of sequence-specific, and highly sensitive, PCR methods. Therefore, we aimed to develop and characterize a method that permits sensitive detection of sequences despite considerable variation. We demonstrate that our low-stringency in-solution hybridization method enables detection of <100 viral copies. Furthermore, distantly related proviral sequences may be enriched by orders of magnitude, enabling discovery of hitherto unknown viral sequences by high-throughput sequencing. The sensitivity was sufficient to detect retroviral sequences in clinical samples. We used this method to conduct an investigation for novel retrovirus in samples from three cancer types. In accordance with recent studies our investigation revealed no retroviral infections in human B-cell lymphoma cells, cutaneous T-cell lymphoma or colorectal cancer biopsies. Nonetheless, our generally applicable method makes sensitive detection possible and permits sequencing of distantly related sequences from complex material.

High-throughput behavioral screening method for detecting auditory response defects in zebrafish.

PubMed

Bang, Pascal I; Yelick, Pamela C; Malicki, Jarema J; Sewell, William F

2002-08-30

We have developed an automated, high-throughput behavioral screening method for detecting hearing defects in zebrafish. Our assay monitors a rapid escape reflex in response to a loud sound. With this approach, 36 adult zebrafish, restrained in visually isolated compartments, can be simultaneously assessed for responsiveness to near-field 400 Hz sinusoidal tone bursts. Automated, objective determinations of responses are achieved with a computer program that obtains images at precise times relative to the acoustic stimulus. Images taken with a CCD video camera before and after stimulus presentation are subtracted to reveal a response to the sound. Up to 108 fish can be screened per hour. Over 6500 fish were tested to validate the reliability of the assay. We found that 1% of these animals displayed hearing deficits. The phenotypes of non-responders were further assessed with radiological analysis for defects in the gross morphology of the auditory system. Nearly all of those showed abnormalities in conductive elements of the auditory system: the swim bladder or Weberian ossicles. Copyright 2002 Elsevier Science B.V.

High-Throughput Screening of HECT E3 Ubiquitin Ligases Using UbFluor.

PubMed

Foote, Peter K; Krist, David T; Statsyuk, Alexander V

2017-09-14

HECT E3 ubiquitin ligases are responsible for many human disease phenotypes and are promising drug targets; however, screening assays for HECT E3 inhibitors are inherently complex, requiring upstream E1 and E2 enzymes as well as ubiquitin, ATP, and detection reagents. Intermediate ubiquitin thioesters and a complex mixture of polyubiquitin products provide further opportunities for off-target inhibition and increase the complexity of the assay. UbFluor is a novel ubiquitin thioester that bypasses the E1 and E2 enzymes and undergoes direct transthiolation with HECT E3 ligases. The release of fluorophore upon transthiolation allows fluorescence polarization detection of HECT E3 activity. In the presence of inhibitors, HECT E3 activity is ablated, and thus no reaction and no change in FP are observed. This assay has been adapted for high-throughput screening of small molecules against HECT E3 ligases, and its utility has been proven in the discovery of HECT E3 ligase inhibitors. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Molecular characterization of the Fy(a-b-) phenotype in a Polish family.

PubMed

Karolak, Ewa; Grodecka, Magdalena; Suchanowska, Anna; Klausa, Elżbieta; Bochenek, Stanisława; Majorczyk, Edyta; Czerwiński, Marcin; Waśniowska, Kazimiera

2013-10-01

The Fy(a-b-) phenotype, very rare in Caucasians and defined by the homozygous FY(*)B-33 allele, is associated with the -33T>C mutation in the promoter region of the FY gene. The allele FY(*)X is correlated with weak expression of Fy(b) antigen due to 265C>T and 298G>A mutations in FY(*)B allele. The purpose of this study was molecular characterization of Fy blood group antigens in Fy(a-b-) members of a Polish family. High-resolution melting analysis was performed to detect single nucleotide polymorphisms in amplified fragments of the FY gene. The Fy(a-b-) phenotype in three siblings of the Polish family was caused by the FY(*)X/FY(*)B-33 genotype. Copyright © 2013 Elsevier Ltd. All rights reserved.

Noninvasive High-Throughput Single-Cell Analysis of HIV Protease Activity Using Ratiometric Flow Cytometry

PubMed Central

Gaber, Rok; Majerle, Andreja; Jerala, Roman; Benčina, Mojca

2013-01-01

To effectively fight against the human immunodeficiency virus infection/acquired immunodeficiency syndrome (HIV/AIDS) epidemic, ongoing development of novel HIV protease inhibitors is required. Inexpensive high-throughput screening assays are needed to quickly scan large sets of chemicals for potential inhibitors. We have developed a Förster resonance energy transfer (FRET)-based, HIV protease-sensitive sensor using a combination of a fluorescent protein pair, namely mCerulean and mCitrine. Through extensive in vitro characterization, we show that the FRET-HIV sensor can be used in HIV protease screening assays. Furthermore, we have used the FRET-HIV sensor for intracellular quantitative detection of HIV protease activity in living cells, which more closely resembles an actual viral infection than an in vitro assay. We have developed a high-throughput method that employs a ratiometric flow cytometry for analyzing large populations of cells that express the FRET-HIV sensor. The method enables FRET measurement of single cells with high sensitivity and speed and should be used when subpopulation-specific intracellular activity of HIV protease needs to be estimated. In addition, we have used a confocal microscopy sensitized emission FRET technique to evaluate the usefulness of the FRET-HIV sensor for spatiotemporal detection of intracellular HIV protease activity. PMID:24287545

Rapid high-throughput cloning and stable expression of antibodies in HEK293 cells.

PubMed

Spidel, Jared L; Vaessen, Benjamin; Chan, Yin Yin; Grasso, Luigi; Kline, J Bradford

2016-12-01

Single-cell based amplification of immunoglobulin variable regions is a rapid and powerful technique for cloning antigen-specific monoclonal antibodies (mAbs) for purposes ranging from general laboratory reagents to therapeutic drugs. From the initial screening process involving small quantities of hundreds or thousands of mAbs through in vitro characterization and subsequent in vivo experiments requiring large quantities of only a few, having a robust system for generating mAbs from cloning through stable cell line generation is essential. A protocol was developed to decrease the time, cost, and effort required by traditional cloning and expression methods by eliminating bottlenecks in these processes. Removing the clonal selection steps from the cloning process using a highly efficient ligation-independent protocol and from the stable cell line process by utilizing bicistronic plasmids to generate stable semi-clonal cell pools facilitated an increased throughput of the entire process from plasmid assembly through transient transfections and selection of stable semi-clonal cell pools. Furthermore, the time required by a single individual to clone, express, and select stable cell pools in a high-throughput format was reduced from 4 to 6months to only 4 to 6weeks. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Development of a high-throughput screen to detect inhibitors of TRPS1 sumoylation.

PubMed

Brandt, Martin; Szewczuk, Lawrence M; Zhang, Hong; Hong, Xuan; McCormick, Patricia M; Lewis, Tia S; Graham, Taylor I; Hung, Sunny T; Harper-Jones, Amber D; Kerrigan, John J; Wang, Da-Yuan; Dul, Edward; Hou, Wangfang; Ho, Thau F; Meek, Thomas D; Cheung, Mui H; Johanson, Kyung O; Jones, Christopher S; Schwartz, Benjamin; Kumar, Sanjay; Oliff, Allen I; Kirkpatrick, Robert B

2013-06-01

Small ubiquitin-like modifier (SUMO) belongs to the family of ubiquitin-like proteins (Ubls) that can be reversibly conjugated to target-specific lysines on substrate proteins. Although covalently sumoylated products are readily detectible in gel-based assays, there has been little progress toward the development of robust quantitative sumoylation assay formats for the evaluation of large compound libraries. In an effort to identify inhibitors of ubiquitin carrier protein 9 (Ubc9)-dependent sumoylation, a high-throughput fluorescence polarization assay was developed, which allows detection of Lys-1201 sumoylation, corresponding to the major site of functional sumoylation within the transcriptional repressor trichorhino-phalangeal syndrome type I protein (TRPS1). A minimal hexapeptide substrate peptide, TMR-VVK₁₂₀₁TEK, was used in this assay format to afford high-throughput screening of the GlaxoSmithKline diversity compound collection. A total of 728 hits were confirmed but no specific noncovalent inhibitors of Ubc9 dependent trans-sumoylation were found. However, several diaminopyrimidine compounds were identified as inhibitors in the assay with IC₅₀ values of 12.5 μM. These were further characterized to be competent substrates which were subject to sumoylation by SUMO-Ubc9 and which were competitive with the sumoylation of the TRPS1 peptide substrates.

A Barcoding Strategy Enabling Higher-Throughput Library Screening by Microscopy.

PubMed

Chen, Robert; Rishi, Harneet S; Potapov, Vladimir; Yamada, Masaki R; Yeh, Vincent J; Chow, Thomas; Cheung, Celia L; Jones, Austin T; Johnson, Terry D; Keating, Amy E; DeLoache, William C; Dueber, John E

2015-11-20

Dramatic progress has been made in the design and build phases of the design-build-test cycle for engineering cells. However, the test phase usually limits throughput, as many outputs of interest are not amenable to rapid analytical measurements. For example, phenotypes such as motility, morphology, and subcellular localization can be readily measured by microscopy, but analysis of these phenotypes is notoriously slow. To increase throughput, we developed microscopy-readable barcodes (MiCodes) composed of fluorescent proteins targeted to discernible organelles. In this system, a unique barcode can be genetically linked to each library member, making possible the parallel analysis of phenotypes of interest via microscopy. As a first demonstration, we MiCoded a set of synthetic coiled-coil leucine zipper proteins to allow an 8 × 8 matrix to be tested for specific interactions in micrographs consisting of mixed populations of cells. A novel microscopy-readable two-hybrid fluorescence localization assay for probing candidate interactions in the cytosol was also developed using a bait protein targeted to the peroxisome and a prey protein tagged with a fluorescent protein. This work introduces a generalizable, scalable platform for making microscopy amenable to higher-throughput library screening experiments, thereby coupling the power of imaging with the utility of combinatorial search paradigms.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

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

2017-01-01

Abstract Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure–property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure–property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure–property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials. PMID:28458737

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

PubMed

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

2017-01-01

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

Incorporating High-Throughput Exposure Predictions with ...

EPA Pesticide Factsheets

We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast™ HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast™ efforts expand (i.e., Phase II) beyond food-use pesticides towards a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. EPA ExpoCast™ program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, three or 13 chemicals possessed AERs <1 or <100, respectively. Diverse bioactivities y across a range of assays and concentrations was also noted across the wider chemical space su

3D Laser Triangulation for Plant Phenotyping in Challenging Environments

PubMed Central

Kjaer, Katrine Heinsvig; Ottosen, Carl-Otto

2015-01-01

To increase the understanding of how the plant phenotype is formed by genotype and environmental interactions, simple and robust high-throughput plant phenotyping methods should be developed and considered. This would not only broaden the application range of phenotyping in the plant research community, but also increase the ability for researchers to study plants in their natural environments. By studying plants in their natural environment in high temporal resolution, more knowledge on how multiple stresses interact in defining the plant phenotype could lead to a better understanding of the interaction between plant responses and epigenetic regulation. In the present paper, we evaluate a commercial 3D NIR-laser scanner (PlantEye, Phenospex B.V., Herleen, The Netherlands) to track daily changes in plant growth with high precision in challenging environments. Firstly, we demonstrate that the NIR laser beam of the scanner does not affect plant photosynthetic performance. Secondly, we demonstrate that it is possible to estimate phenotypic variation amongst the growth pattern of ten genotypes of Brassica napus L. (rapeseed), using a simple linear correlation between scanned parameters and destructive growth measurements. Our results demonstrate the high potential of 3D laser triangulation for simple measurements of phenotypic variation in challenging environments and in a high temporal resolution. PMID:26066990

Mobile element biology – new possibilities with high-throughput sequencing

PubMed Central

Xing, Jinchuan; Witherspoon, David J.; Jorde, Lynn B.

2014-01-01

Mobile elements compose more than half of the human genome, but until recently their large-scale detection was time-consuming and challenging. With the development of new high-throughput sequencing technologies, the complete spectrum of mobile element variation in humans can now be identified and analyzed. Thousands of new mobile element insertions have been discovered, yielding new insights into mobile element biology, evolution, and genomic variation. We review several high-throughput methods, with an emphasis on techniques that specifically target mobile element insertions in humans, and we highlight recent applications of these methods in evolutionary studies and in the analysis of somatic alterations in human cancers. PMID:23312846

High-Throughput Single-Cell RNA Sequencing and Data Analysis.

PubMed

Sagar; Herman, Josip Stefan; Pospisilik, John Andrew; Grün, Dominic

2018-01-01

Understanding biological systems at a single cell resolution may reveal several novel insights which remain masked by the conventional population-based techniques providing an average readout of the behavior of cells. Single-cell transcriptome sequencing holds the potential to identify novel cell types and characterize the cellular composition of any organ or tissue in health and disease. Here, we describe a customized high-throughput protocol for single-cell RNA-sequencing (scRNA-seq) combining flow cytometry and a nanoliter-scale robotic system. Since scRNA-seq requires amplification of a low amount of endogenous cellular RNA, leading to substantial technical noise in the dataset, downstream data filtering and analysis require special care. Therefore, we also briefly describe in-house state-of-the-art data analysis algorithms developed to identify cellular subpopulations including rare cell types as well as to derive lineage trees by ordering the identified subpopulations of cells along the inferred differentiation trajectories.

Piezo-thermal Probe Array for High Throughput Applications

PubMed Central

Gaitas, Angelo; French, Paddy

2012-01-01

Microcantilevers are used in a number of applications including atomic-force microscopy (AFM). In this work, deflection-sensing elements along with heating elements are integrated onto micromachined cantilever arrays to increase sensitivity, and reduce complexity and cost. An array of probes with 5–10 nm gold ultrathin film sensors on silicon substrates for high throughput scanning probe microscopy is developed. The deflection sensitivity is 0.2 ppm/nm. Plots of the change in resistance of the sensing element with displacement are used to calibrate the probes and determine probe contact with the substrate. Topographical scans demonstrate high throughput and nanometer resolution. The heating elements are calibrated and the thermal coefficient of resistance (TCR) is 655 ppm/K. The melting temperature of a material is measured by locally heating the material with the heating element of the cantilever while monitoring the bending with the deflection sensing element. The melting point value measured with this method is in close agreement with the reported value in literature. PMID:23641125

Spotsizer: High-throughput quantitative analysis of microbial growth.

PubMed

Bischof, Leanne; Převorovský, Martin; Rallis, Charalampos; Jeffares, Daniel C; Arzhaeva, Yulia; Bähler, Jürg

2016-10-01

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

Genome-wide association study of rice (Oryza sativa L.) leaf traits with a high-throughput leaf scorer.

PubMed

Yang, Wanneng; Guo, Zilong; Huang, Chenglong; Wang, Ke; Jiang, Ni; Feng, Hui; Chen, Guoxing; Liu, Qian; Xiong, Lizhong

2015-09-01

Leaves are the plant's solar panel and food factory, and leaf traits are always key issues to investigate in plant research. Traditional methods for leaf trait measurement are time-consuming. In this work, an engineering prototype has been established for high-throughput leaf scoring (HLS) of a large number of Oryza sativa accessions. The mean absolute per cent of errors in traditional measurements versus HLS were below 5% for leaf number, area, shape, and colour. Moreover, HLS can measure up to 30 leaves per minute. To demonstrate the usefulness of HLS in dissecting the genetic bases of leaf traits, a genome-wide association study (GWAS) was performed for 29 leaf traits related to leaf size, shape, and colour at three growth stages using HLS on a panel of 533 rice accessions. Nine associated loci contained known leaf-related genes, such as Nal1 for controlling the leaf width. In addition, a total of 73, 123, and 177 new loci were detected for traits associated with leaf size, colour, and shape, respectively. In summary, after evaluating the performance with a large number of rice accessions, the combination of GWAS and high-throughput leaf phenotyping (HLS) has proven a valuable strategy to identify the genetic loci controlling rice leaf traits. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Solid optical ring interferometer for high-throughput feedback-free spectral analysis and filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrak, B.; Peiris, M.; Muller, A., E-mail: mullera@usf.edu

2015-02-15

We describe a simple and inexpensive optical ring interferometer for use in high-resolution spectral analysis and filtering. It consists of a solid cuboid, reflection-coated on two opposite sides, in which constructive interference occurs for waves in a rhombic trajectory. Due to its monolithic design, the interferometer’s resonance frequencies are insensitive to environmental disturbances over time. Additional advantages are its simplicity of alignment, high-throughput, and feedback-free operation. If desired, it can be stabilized with a secondary laser without disturbance of the primary signal. We illustrate the use of the interferometer for the measurement of the spectral Mollow triplet from a quantummore » dot and characterize its long-term stability for filtering applications.« less

Microreactor Cells for High-Throughput X-ray Absorption Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beesley, Angela; Tsapatsaris, Nikolaos; Weiher, Norbert

2007-01-19

High-throughput experimentation has been applied to X-ray Absorption spectroscopy as a novel route for increasing research productivity in the catalysis community. Suitable instrumentation has been developed for the rapid determination of the local structure in the metal component of precursors for supported catalysts. An automated analytical workflow was implemented that is much faster than traditional individual spectrum analysis. It allows the generation of structural data in quasi-real time. We describe initial results obtained from the automated high throughput (HT) data reduction and analysis of a sample library implemented through the 96 well-plate industrial standard. The results show that a fullymore » automated HT-XAS technology based on existing industry standards is feasible and useful for the rapid elucidation of geometric and electronic structure of materials.« less

Rapid and label-free microfluidic neutrophil purification and phenotyping in diabetes mellitus

NASA Astrophysics Data System (ADS)

Hou, Han Wei; Petchakup, Chayakorn; Tay, Hui Min; Tam, Zhi Yang; Dalan, Rinkoo; Chew, Daniel Ek Kwang; Li, King Ho Holden; Boehm, Bernhard O.

2016-07-01

Advanced management of dysmetabolic syndromes such as diabetes will benefit from a timely mechanistic insight enabling personalized medicine approaches. Herein, we present a rapid microfluidic neutrophil sorting and functional phenotyping strategy for type 2 diabetes mellitus (T2DM) patients using small blood volumes (fingerprick ~100 μL). The developed inertial microfluidics technology enables single-step neutrophil isolation (>90% purity) without immuno-labeling and sorted neutrophils are used to characterize their rolling behavior on E-selectin, a critical step in leukocyte recruitment during inflammation. The integrated microfluidics testing methodology facilitates high throughput single-cell quantification of neutrophil rolling to detect subtle differences in speed distribution. Higher rolling speed was observed in T2DM patients (P < 0.01) which strongly correlated with neutrophil activation, rolling ligand P-selectin glycoprotein ligand 1 (PSGL-1) expression, as well as established cardiovascular risk factors (cholesterol, high-sensitive C-reactive protein (CRP) and HbA1c). Rolling phenotype can be modulated by common disease risk modifiers (metformin and pravastatin). Receiver operating characteristics (ROC) and principal component analysis (PCA) revealed neutrophil rolling as an important functional phenotype in T2DM diagnostics. These results suggest a new point-of-care testing methodology, and neutrophil rolling speed as a functional biomarker for rapid profiling of dysmetabolic subjects in clinical and patient-oriented settings.

High-throughput 96-well solvent mediated sonic blending synthesis and on-plate solid/solution stability characterization of pharmaceutical cocrystals.

PubMed

Luu, Van; Jona, Janan; Stanton, Mary K; Peterson, Matthew L; Morrison, Henry G; Nagapudi, Karthik; Tan, Helming

2013-01-30

A 96-well high-throughput cocrystal screening workflow has been developed consisting of solvent-mediated sonic blending synthesis and on-plate solid/solution stability characterization by XRPD. A strategy of cocrystallization screening in selected blend solvents including water mixtures is proposed to not only manipulate solubility of the cocrystal components but also differentiate physical stability of the cocrystal products. Caffeine-oxalic acid and theophylline-oxalic acid cocrystals were prepared and evaluated in relation to saturation levels of the cocrystal components and stability of the cocrystal products in anhydrous and hydrous solvents. AMG 517 was screened with a number of coformers, and solid/solution stability of the resulting cocrystals on the 96-well plate was investigated. A stability trend was observed and confirmed that cocrystals comprised of lower aqueous solubility coformers tended to be more stable in water. Furthermore, cocrystals which could be isolated under hydrous solvent blending condition exhibited superior physical stability to those which could only be obtained under anhydrous condition. This integrated HTS workflow provides an efficient route in an API-sparing approach to screen and identify cocrystal candidates with proper solubility and solid/solution stability properties. Copyright © 2012 Elsevier B.V. All rights reserved.

A Perspective on the Future of High-Throughput RNAi Screening: Will CRISPR Cut Out the Competition or Can RNAi Help Guide the Way?

PubMed

Taylor, Jessica; Woodcock, Simon

2015-09-01

For more than a decade, RNA interference (RNAi) has brought about an entirely new approach to functional genomics screening. Enabling high-throughput loss-of-function (LOF) screens against the human genome, identifying new drug targets, and significantly advancing experimental biology, RNAi is a fast, flexible technology that is compatible with existing high-throughput systems and processes; however, the recent advent of clustered regularly interspaced palindromic repeats (CRISPR)-Cas, a powerful new precise genome-editing (PGE) technology, has opened up vast possibilities for functional genomics. CRISPR-Cas is novel in its simplicity: one piece of easily engineered guide RNA (gRNA) is used to target a gene sequence, and Cas9 expression is required in the cells. The targeted double-strand break introduced by the gRNA-Cas9 complex is highly effective at removing gene expression compared to RNAi. Together with the reduced cost and complexity of CRISPR-Cas, there is the realistic opportunity to use PGE to screen for phenotypic effects in a total gene knockout background. This review summarizes the exciting development of CRISPR-Cas as a high-throughput screening tool, comparing its future potential to that of well-established RNAi screening techniques, and highlighting future challenges and opportunities within these disciplines. We conclude that the two technologies actually complement rather than compete with each other, enabling greater understanding of the genome in relation to drug discovery. © 2015 Society for Laboratory Automation and Screening.

Parallelization of a spatial random field characterization process using the Method of Anchored Distributions and the HTCondor high throughput computing system

NASA Astrophysics Data System (ADS)

Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.

2013-12-01

A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)

Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT)

EPA Science Inventory

High throughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the ...

Applying a High-Throughput PBTK Model for IVIVE

EPA Science Inventory

The ability to link in vitro and in vivo toxicity enables the use of high-throughput in vitro assays as an alternative to resource intensive animal studies. Toxicokinetics (TK) should help describe this link, but prior work found weak correlation when using a TK model for in vitr...

High-throughput optofluidic profiling of Euglena gracilis with morphological and chemical specificity

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Jiang, Yiyue; Ozeki, Yasuyuki; Goda, Keisuke

2016-11-01

The world is faced with environmental problems and the energy crisis due to the combustion and depletion of fossil fuels. The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate a high-throughput optofluidic Euglena gracilis profiler which consists of an optical time-stretch microscope and a fluorescence analyzer on top of an inertial-focusing microfluidic device that can detect fluorescence from lipid droplets in their cell body and provide images of E. gracilis cells simultaneously at a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method provides a promise for evaluating the efficiency of lipid-inducing techniques for biofuel production, which is also applicable for identifying biomedical samples such as blood cells and cancer cells.

Genotypic and phenotypic characterization of the O-linked protein glycosylation system reveals high glycan diversity in paired meningococcal carriage isolates.

PubMed

Børud, Bente; Bårnes, Guro K; Brynildsrud, Ola Brønstad; Fritzsønn, Elisabeth; Caugant, Dominique A

2018-03-19

Species within the genus Neisseria display significant glycan diversity associated with the O -linked protein glycosylation ( pgl ) systems due to phase variation, polymorphic genes and gene content. The aim of this study was to examine in detail the pgl genotype and glycosylation phenotype in meningococcal isolates and the changes occurring during short-term asymptomatic carriage. Paired meningococcal isolates derived from 50 asymptomatic meningococcal carriers, taken about two months apart, were analyzed with whole genome sequencing. The O -linked protein glycosylation genes were characterized in detail using the Genome Comparator tool at the PubMLST.org database. Immunoblotting with glycan specific antibodies were used to investigate the protein glycosylation phenotype. All major pgl locus polymorphisms identified in N. meningitidis to date were present in our isolate collection, with the variable presence of pglG-pglH, both in combination with either pglB or pglB2. We identified significant changes and diversity in the pgl genotype and/or glycan phenotype in 96% of the paired isolates. There was also a high degree of glycan microheterogeneity, in which different variants of glycan structures were found at a given glycoprotein. The main mechanism responsible for the observed differences was phase variable expression of the involved glycosyltransferases and the O-acetyltransferase. To our knowledge, this is the first characterization of the pgl genotype and glycosylation phenotype in a larger strain collection. This study thus provides important insight into glycan diversity in N. meningitidis and phase variability changes that influence the expressed glycoform repertoire during meningococcal carriage. Importance Bacterial meningitis is a serious global health problem and one of the major causative organisms is Neisseria meningitidis , which is also a common commensal in the upper respiratory tract of healthy humans. In bacteria, numerous loci involved in

Quality control methodology for high-throughput protein-protein interaction screening.

PubMed

Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha

2011-01-01

Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.

High-throughput screening of dye-ligands for chromatography.

PubMed

Kumar, Sunil; Punekar, Narayan S

2014-01-01

Dye-ligand-based chromatography has become popular after Cibacron Blue, the first reactive textile dye, found application for protein purification. Many other textile dyes have since been successfully used to purify a number of proteins and enzymes. While the exact nature of their interaction with target proteins is often unclear, dye-ligands are thought to mimic the structural features of their corresponding substrates, cofactors, etc. The dye-ligand affinity matrices are therefore considered pseudo-affinity matrices. In addition, dye-ligands may simply bind with proteins due to electrostatic, hydrophobic, and hydrogen-bonding interactions. Because of their low cost, ready availability, and structural stability, dye-ligand affinity matrices have gained much popularity. Choice of a large number of dye structures offers a range of matrices to be prepared and tested. When presented in the high-throughput screening mode, these dye-ligand matrices provide a formidable tool for protein purification. One could pick from the list of dye-ligands already available or build a systematic library of such structures for use. A high-throughput screen may be set up to choose best dye-ligand matrix as well as ideal conditions for binding and elution, for a given protein. The mode of operation could be either manual or automated. The technology is available to test the performance of dye-ligand matrices in small volumes in an automated liquid-handling workstation. Screening a systematic library of dye-ligand structures can help establish a structure-activity relationship. While the origins of dye-ligand chromatography lay in exploiting pseudo-affinity, it is now possible to design very specific biomimetic dye structures. High-throughput screening will be of value in this endeavor as well.

Development and Characterization of a High Throughput Screen to investigate the delayed Effects of Radiations Commonly Encountered in Space