High-throughput analysis of the protein sequence-stability landscape using a quantitative "yeast surface two-hybrid" system and fragment reconstitution

PubMed Central

Dutta, Sanjib; Koide, Akiko; Koide, Shohei

2008-01-01

Stability evaluation of many mutants can lead to a better understanding of the sequence determinants of a structural motif and of factors governing protein stability and protein evolution. The traditional biophysical analysis of protein stability is low throughput, limiting our ability to widely explore the sequence space in a quantitative manner. In this study, we have developed a high-throughput library screening method for quantifying stability changes, which is based on protein fragment reconstitution and yeast surface display. Our method exploits the thermodynamic linkage between protein stability and fragment reconstitution and the ability of the yeast surface display technique to quantitatively evaluate protein-protein interactions. The method was applied to a fibronectin type III (FN3) domain. Characterization of fragment reconstitution was facilitated by the co-expression of two FN3 fragments, thus establishing a "yeast surface two-hybrid" method. Importantly, our method does not rely on competition between clones and thus eliminates a common limitation of high-throughput selection methods in which the most stable variants are predominantly recovered. Thus, it allows for the isolation of sequences that exhibits a desired level of stability. We identified over one hundred unique sequences for a β-bulge motif, which was significantly more informative than natural sequences of the FN3 family in revealing the sequence determinants for the β-bulge. Our method provides a powerful means to rapidly assess stability of many variants, to systematically assess contribution of different factors to protein stability and to enhance protein stability. PMID:18674545

Multiplex enrichment quantitative PCR (ME-qPCR): a high-throughput, highly sensitive detection method for GMO identification.

PubMed

Fu, Wei; Zhu, Pengyu; Wei, Shuang; Zhixin, Du; Wang, Chenguang; Wu, Xiyang; Li, Feiwu; Zhu, Shuifang

2017-04-01

Among all of the high-throughput detection methods, PCR-based methodologies are regarded as the most cost-efficient and feasible methodologies compared with the next-generation sequencing or ChIP-based methods. However, the PCR-based methods can only achieve multiplex detection up to 15-plex due to limitations imposed by the multiplex primer interactions. The detection throughput cannot meet the demands of high-throughput detection, such as SNP or gene expression analysis. Therefore, in our study, we have developed a new high-throughput PCR-based detection method, multiplex enrichment quantitative PCR (ME-qPCR), which is a combination of qPCR and nested PCR. The GMO content detection results in our study showed that ME-qPCR could achieve high-throughput detection up to 26-plex. Compared to the original qPCR, the Ct values of ME-qPCR were lower for the same group, which showed that ME-qPCR sensitivity is higher than the original qPCR. The absolute limit of detection for ME-qPCR could achieve levels as low as a single copy of the plant genome. Moreover, the specificity results showed that no cross-amplification occurred for irrelevant GMO events. After evaluation of all of the parameters, a practical evaluation was performed with different foods. The more stable amplification results, compared to qPCR, showed that ME-qPCR was suitable for GMO detection in foods. In conclusion, ME-qPCR achieved sensitive, high-throughput GMO detection in complex substrates, such as crops or food samples. In the future, ME-qPCR-based GMO content identification may positively impact SNP analysis or multiplex gene expression of food or agricultural samples. Graphical abstract For the first-step amplification, four primers (A, B, C, and D) have been added into the reaction volume. In this manner, four kinds of amplicons have been generated. All of these four amplicons could be regarded as the target of second-step PCR. For the second-step amplification, three parallels have been taken for

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

PubMed Central

Lutsik, Pavlo; Feuerbach, Lars; Arand, Julia; Lengauer, Thomas; Walter, Jörn; Bock, Christoph

2011-01-01

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data. PMID:21565797

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.

NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis.

PubMed

Markiewicz, Pawel J; Ehrhardt, Matthias J; Erlandsson, Kjell; Noonan, Philip J; Barnes, Anna; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Ourselin, Sebastien

2018-01-01

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

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.

Analysis of JC virus DNA replication using a quantitative and high-throughput assay

PubMed Central

Shin, Jong; Phelan, Paul J.; Chhum, Panharith; Bashkenova, Nazym; Yim, Sung; Parker, Robert; Gagnon, David; Gjoerup, Ole; Archambault, Jacques; Bullock, Peter A.

2015-01-01

Progressive Multifocal Leukoencephalopathy (PML) is caused by lytic replication of JC virus (JCV) in specific cells of the central nervous system. Like other polyomaviruses, JCV encodes a large T-antigen helicase needed for replication of the viral DNA. Here, we report the development of a luciferase-based, quantitative and high-throughput assay of JCV DNA replication in C33A cells, which, unlike the glial cell lines Hs 683 and U87, accumulate high levels of nuclear T-ag needed for robust replication. Using this assay, we investigated the requirement for different domains of T-ag, and for specific sequences within and flanking the viral origin, in JCV DNA replication. Beyond providing validation of the assay, these studies revealed an important stimulatory role of the transcription factor NF1 in JCV DNA replication. Finally, we show that the assay can be used for inhibitor testing, highlighting its value for the identification of antiviral drugs targeting JCV DNA replication. PMID:25155200

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.

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

Quantitative Live-Cell Confocal Imaging of 3D Spheroids in a High-Throughput Format.

PubMed

Leary, Elizabeth; Rhee, Claire; Wilks, Benjamin T; Morgan, Jeffrey R

2018-06-01

Accurately predicting the human response to new compounds is critical to a wide variety of industries. Standard screening pipelines (including both in vitro and in vivo models) often lack predictive power. Three-dimensional (3D) culture systems of human cells, a more physiologically relevant platform, could provide a high-throughput, automated means to test the efficacy and/or toxicity of novel substances. However, the challenge of obtaining high-magnification, confocal z stacks of 3D spheroids and understanding their respective quantitative limitations must be overcome first. To address this challenge, we developed a method to form spheroids of reproducible size at precise spatial locations across a 96-well plate. Spheroids of variable radii were labeled with four different fluorescent dyes and imaged with a high-throughput confocal microscope. 3D renderings of the spheroid had a complex bowl-like appearance. We systematically analyzed these confocal z stacks to determine the depth of imaging and the effect of spheroid size and dyes on quantitation. Furthermore, we have shown that this loss of fluorescence can be addressed through the use of ratio imaging. Overall, understanding both the limitations of confocal imaging and the tools to correct for these limits is critical for developing accurate quantitative assays using 3D spheroids.

High-Throughput Analysis and Automation for Glycomics Studies.

PubMed

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

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

A Robotic Platform for Quantitative High-Throughput Screening

PubMed Central

Michael, Sam; Auld, Douglas; Klumpp, Carleen; Jadhav, Ajit; Zheng, Wei; Thorne, Natasha; Austin, Christopher P.; Inglese, James

2008-01-01

Abstract High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation. PMID:19035846

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.

Quantitative High-Throughput Luciferase Screening in Identifying CAR Modulators.

PubMed

Lynch, Caitlin; Zhao, Jinghua; Wang, Hongbing; Xia, Menghang

2016-01-01

The constitutive androstane receptor (CAR, NR1I3) is responsible for the transcription of multiple drug metabolizing enzymes and transporters. There are two possible methods of activation for CAR, direct ligand binding and a ligand-independent method, which makes this a unique nuclear receptor. Both of these mechanisms require translocation of CAR from the cytoplasm into the nucleus. Interestingly, CAR is constitutively active in immortalized cell lines due to the basal nuclear location of this receptor. This creates an important challenge in most in vitro assay models because immortalized cells cannot be used without inhibiting the high basal activity. In this book chapter, we go into detail of how to perform quantitative high-throughput screens to identify hCAR1 modulators through the employment of a double stable cell line. Using this line, we are able to identify activators, as well as deactivators, of the challenging nuclear receptor, CAR.

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

Validation of high-throughput single cell analysis methodology.

PubMed

Devonshire, Alison S; Baradez, Marc-Olivier; Morley, Gary; Marshall, Damian; Foy, Carole A

2014-05-01

High-throughput quantitative polymerase chain reaction (qPCR) approaches enable profiling of multiple genes in single cells, bringing new insights to complex biological processes and offering opportunities for single cell-based monitoring of cancer cells and stem cell-based therapies. However, workflows with well-defined sources of variation are required for clinical diagnostics and testing of tissue-engineered products. In a study of neural stem cell lines, we investigated the performance of lysis, reverse transcription (RT), preamplification (PA), and nanofluidic qPCR steps at the single cell level in terms of efficiency, precision, and limit of detection. We compared protocols using a separate lysis buffer with cell capture directly in RT-PA reagent. The two methods were found to have similar lysis efficiencies, whereas the direct RT-PA approach showed improved precision. Digital PCR was used to relate preamplified template copy numbers to Cq values and reveal where low-quality signals may affect the analysis. We investigated the impact of calibration and data normalization strategies as a means of minimizing the impact of inter-experimental variation on gene expression values and found that both approaches can improve data comparability. This study provides validation and guidance for the application of high-throughput qPCR workflows for gene expression profiling of single cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of carbon plasma-coated multiwell plates for high-throughput mass spectrometric analysis of highly lipophilic fermentation products.

PubMed

Heinig, Uwe; Scholz, Susanne; Dahm, Pia; Grabowy, Udo; Jennewein, Stefan

2010-08-01

Classical approaches to strain improvement and metabolic engineering rely on rapid qualitative and quantitative analyses of the metabolites of interest. As an analytical tool, mass spectrometry (MS) has proven to be efficient and nearly universally applicable for timely screening of metabolites. Furthermore, gas chromatography (GC)/MS- and liquid chromatography (LC)/MS-based metabolite screens can often be adapted to high-throughput formats. We recently engineered a Saccharomyces cerevisiae strain to produce taxa-4(5),11(12)-diene, the first pathway-committing biosynthetic intermediate for the anticancer drug Taxol, through the heterologous and homologous expression of several genes related to isoprenoid biosynthesis. To date, GC/MS- and LC/MS-based high-throughput methods have been inherently difficult to adapt to the screening of isoprenoid-producing microbial strains due to the need for extensive sample preparation of these often highly lipophilic compounds. In the current work, we examined different approaches to the high-throughput analysis of taxa-4(5),11(12)-diene biosynthesizing yeast strains in a 96-deep-well format. Carbon plasma coating of standard 96-deep-well polypropylene plates allowed us to circumvent the inherent solvent instability of commonly used deep-well plates. In addition, efficient adsorption of the target isoprenoid product by the coated plates allowed rapid and simple qualitative and quantitative analyses of the individual cultures. Copyright 2010 Elsevier Inc. All rights reserved.

High-Throughput RT-PCR for small-molecule screening assays

PubMed Central

Bittker, Joshua A.

2012-01-01

Quantitative measurement of the levels of mRNA expression using real-time reverse transcription polymerase chain reaction (RT-PCR) has long been used for analyzing expression differences in tissue or cell lines of interest. This method has been used somewhat less frequently to measure the changes in gene expression due to perturbagens such as small molecules or siRNA. The availability of new instrumentation for liquid handling and real-time PCR analysis as well as the commercial availability of start-to-finish kits for RT-PCR has enabled the use of this method for high-throughput small-molecule screening on a scale comparable to traditional high-throughput screening (HTS) assays. This protocol focuses on the special considerations necessary for using quantitative RT-PCR as a primary small-molecule screening assay, including the different methods available for mRNA isolation and analysis. PMID:23487248

Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics.

PubMed

Marchand, Jérémy; Martineau, Estelle; Guitton, Yann; Dervilly-Pinel, Gaud; Giraudeau, Patrick

2017-02-01

Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative high throughput screening identifies inhibitors of anthrax-induced cell death

PubMed Central

Zhu, Ping Jun; Hobson, Peyton; Southall, Noel; Qiu, Cunping; Thomas, Craig J.; Lu, Jiamo; Inglese, James; Zheng, Wei; Leppla, Stephen H.; Bugge, Thomas H.; Austin, Christopher P.; Liu, Shihui

2009-01-01

Here, we report the results of a quantitative high-throughput screen (qHTS) measuring the endocytosis and translocation of a β-lactamase-fused-lethal factor and the identification of small molecules capable of obstructing the process of anthrax toxin internalization. Several small molecules protect RAW264.7 macrophages and CHO cells from anthrax lethal toxin and protected cells from an LF-Pseudomonas exotoxin fusion protein and diphtheria toxin. Further efforts demonstrated that these compounds impaired the PA heptamer pre-pore to pore conversion in cells expressing the CMG2 receptor, but not the related TEM8 receptor, indicating that these compounds likely interfere with toxin internalization. PMID:19540764

Quantitative Analysis of Focused A-To-I RNA Editing Sites by Ultra-High-Throughput Sequencing in Psychiatric Disorders

PubMed Central

Zhu, Hu; Urban, Daniel J.; Blashka, Jared; McPheeters, Matthew T.; Kroeze, Wesley K.; Mieczkowski, Piotr; Overholser, James C.; Jurjus, George J.; Dieter, Lesa; Mahajan, Gouri J.; Rajkowska, Grazyna; Wang, Zefeng; Sullivan, Patrick F.; Stockmeier, Craig A.; Roth, Bryan L.

2012-01-01

A-to-I RNA editing is a post-transcriptional modification of single nucleotides in RNA by adenosine deamination, which thereby diversifies the gene products encoded in the genome. Thousands of potential RNA editing sites have been identified by recent studies (e.g. see Li et al, Science 2009); however, only a handful of these sites have been independently confirmed. Here, we systematically and quantitatively examined 109 putative coding region A-to-I RNA editing sites in three sets of normal human brain samples by ultra-high-throughput sequencing (uHTS). Forty of 109 putative sites, including 25 previously confirmed sites, were validated as truly edited in our brain samples, suggesting an overestimation of A-to-I RNA editing in these putative sites by Li et al (2009). To evaluate RNA editing in human disease, we analyzed 29 of the confirmed sites in subjects with major depressive disorder and schizophrenia using uHTS. In striking contrast to many prior studies, we did not find significant alterations in the frequency of RNA editing at any of the editing sites in samples from these patients, including within the 5HT2C serotonin receptor (HTR2C). Our results indicate that uHTS is a fast, quantitative and high-throughput method to assess RNA editing in human physiology and disease and that many prior studies of RNA editing may overestimate both the extent and disease-related variability of RNA editing at the sites we examined in the human brain. PMID:22912834

A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays

PubMed Central

Hsieh, Jui-Hua; Sedykh, Alexander; Huang, Ruili; Xia, Menghang; Tice, Raymond R.

2015-01-01

A main goal of the U.S. Tox21 program is to profile a 10K-compound library for activity against a panel of stress-related and nuclear receptor signaling pathway assays using a quantitative high-throughput screening (qHTS) approach. However, assay artifacts, including nonreproducible signals and assay interference (e.g., autofluorescence), complicate compound activity interpretation. To address these issues, we have developed a data analysis pipeline that includes an updated signal noise–filtering/curation protocol and an assay interference flagging system. To better characterize various types of signals, we adopted a weighted version of the area under the curve (wAUC) to quantify the amount of activity across the tested concentration range in combination with the assay-dependent point-of-departure (POD) concentration. Based on the 32 Tox21 qHTS assays analyzed, we demonstrate that signal profiling using wAUC affords the best reproducibility (Pearson's r = 0.91) in comparison with the POD (0.82) only or the AC50 (i.e., half-maximal activity concentration, 0.81). Among the activity artifacts characterized, cytotoxicity is the major confounding factor; on average, about 8% of Tox21 compounds are affected, whereas autofluorescence affects less than 0.5%. To facilitate data evaluation, we implemented two graphical user interface applications, allowing users to rapidly evaluate the in vitro activity of Tox21 compounds. PMID:25904095

A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays.

PubMed

Hsieh, Jui-Hua; Sedykh, Alexander; Huang, Ruili; Xia, Menghang; Tice, Raymond R

2015-08-01

A main goal of the U.S. Tox21 program is to profile a 10K-compound library for activity against a panel of stress-related and nuclear receptor signaling pathway assays using a quantitative high-throughput screening (qHTS) approach. However, assay artifacts, including nonreproducible signals and assay interference (e.g., autofluorescence), complicate compound activity interpretation. To address these issues, we have developed a data analysis pipeline that includes an updated signal noise-filtering/curation protocol and an assay interference flagging system. To better characterize various types of signals, we adopted a weighted version of the area under the curve (wAUC) to quantify the amount of activity across the tested concentration range in combination with the assay-dependent point-of-departure (POD) concentration. Based on the 32 Tox21 qHTS assays analyzed, we demonstrate that signal profiling using wAUC affords the best reproducibility (Pearson's r = 0.91) in comparison with the POD (0.82) only or the AC(50) (i.e., half-maximal activity concentration, 0.81). Among the activity artifacts characterized, cytotoxicity is the major confounding factor; on average, about 8% of Tox21 compounds are affected, whereas autofluorescence affects less than 0.5%. To facilitate data evaluation, we implemented two graphical user interface applications, allowing users to rapidly evaluate the in vitro activity of Tox21 compounds. © 2015 Society for Laboratory Automation and Screening.

Quantitative High-throughput Luciferase Screening in Identifying CAR Modulators

PubMed Central

Lynch, Caitlin; Zhao, Jinghua; Wang, Hongbing; Xia, Menghang

2017-01-01

Summary The constitutive androstane receptor (CAR, NR1I3) is responsible for the transcription of multiple drug metabolizing enzymes and transporters. There are two possible methods of activation for CAR, direct ligand binding and a ligand-independent method, which makes this a unique nuclear receptor. Both of these mechanisms require translocation of CAR from the cytoplasm into the nucleus. Interestingly, CAR is constitutively active in immortalized cell lines due to the basal nuclear location of this receptor. This creates an important challenge in most in vitro assay models because immortalized cells cannot be used without inhibiting the basal activity. In this book chapter, we go into detail of how to perform quantitative high-throughput screens to identify hCAR1 modulators through the employment of a double stable cell line. Using this line, we are able to identify activators, as well as deactivators, of the challenging nuclear receptor, CAR. PMID:27518621

High-throughput SISCAPA quantitation of peptides from human plasma digests by ultrafast, liquid chromatography-free mass spectrometry.

PubMed

Razavi, Morteza; Frick, Lauren E; LaMarr, William A; Pope, Matthew E; Miller, Christine A; Anderson, N Leigh; Pearson, Terry W

2012-12-07

We investigated the utility of an SPE-MS/MS platform in combination with a modified SISCAPA workflow for chromatography-free MRM analysis of proteotypic peptides in digested human plasma. This combination of SISCAPA and SPE-MS/MS technology allows sensitive, MRM-based quantification of peptides from plasma digests with a sample cycle time of ∼7 s, a 300-fold improvement over typical MRM analyses with analysis times of 30-40 min that use liquid chromatography upstream of MS. The optimized system includes capture and enrichment to near purity of target proteotypic peptides using rigorously selected, high affinity, antipeptide monoclonal antibodies and reduction of background peptides using a novel treatment of magnetic bead immunoadsorbents. Using this method, we have successfully quantitated LPS-binding protein and mesothelin (concentrations of ∼5000 ng/mL and ∼10 ng/mL, respectively) in human plasma. The method eliminates the need for upstream liquid-chromatography and can be multiplexed, thus facilitating quantitative analysis of proteins, including biomarkers, in large sample sets. The method is ideal for high-throughput biomarker validation after affinity enrichment and has the potential for applications in clinical laboratories.

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.

Quantitative digital image analysis of chromogenic assays for high throughput screening of alpha-amylase mutant libraries.

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

An image analysis-based method for high throughput screening of an alpha-amylase mutant library using chromogenic assays was developed. Assays were performed in microplates and high resolution images of the assay plates were read using the Virtual Microplate Reader (VMR) script to quantify the concentration of the chromogen. This method is fast and sensitive in quantifying 0.025-0.3 mg starch/ml as well as 0.05-0.75 mg glucose/ml. It was also an effective screening method for improved alpha-amylase activity with a coefficient of variance of 18%.

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 fabrication and screening improves gold nanoparticle chemiresistor sensor performance.

PubMed

Hubble, Lee J; Cooper, James S; Sosa-Pintos, Andrea; Kiiveri, Harri; Chow, Edith; Webster, Melissa S; Wieczorek, Lech; Raguse, Burkhard

2015-02-09

Chemiresistor sensor arrays are a promising technology to replace current laboratory-based analysis instrumentation, with the advantage of facile integration into portable, low-cost devices for in-field use. To increase the performance of chemiresistor sensor arrays a high-throughput fabrication and screening methodology was developed to assess different organothiol-functionalized gold nanoparticle chemiresistors. This high-throughput fabrication and testing methodology was implemented to screen a library consisting of 132 different organothiol compounds as capping agents for functionalized gold nanoparticle chemiresistor sensors. The methodology utilized an automated liquid handling workstation for the in situ functionalization of gold nanoparticle films and subsequent automated analyte testing of sensor arrays using a flow-injection analysis system. To test the methodology we focused on the discrimination and quantitation of benzene, toluene, ethylbenzene, p-xylene, and naphthalene (BTEXN) mixtures in water at low microgram per liter concentration levels. The high-throughput methodology identified a sensor array configuration consisting of a subset of organothiol-functionalized chemiresistors which in combination with random forests analysis was able to predict individual analyte concentrations with overall root-mean-square errors ranging between 8-17 μg/L for mixtures of BTEXN in water at the 100 μg/L concentration. The ability to use a simple sensor array system to quantitate BTEXN mixtures in water at the low μg/L concentration range has direct and significant implications to future environmental monitoring and reporting strategies. In addition, these results demonstrate the advantages of high-throughput screening to improve the performance of gold nanoparticle based chemiresistors for both new and existing applications.

Parallel Workflow for High-Throughput (>1,000 Samples/Day) Quantitative Analysis of Human Insulin-Like Growth Factor 1 Using Mass Spectrometric Immunoassay

PubMed Central

Oran, Paul E.; Trenchevska, Olgica; Nedelkov, Dobrin; Borges, Chad R.; Schaab, Matthew R.; Rehder, Douglas S.; Jarvis, Jason W.; Sherma, Nisha D.; Shen, Luhui; Krastins, Bryan; Lopez, Mary F.; Schwenke, Dawn C.; Reaven, Peter D.; Nelson, Randall W.

2014-01-01

Insulin-like growth factor 1 (IGF1) is an important biomarker for the management of growth hormone disorders. Recently there has been rising interest in deploying mass spectrometric (MS) methods of detection for measuring IGF1. However, widespread clinical adoption of any MS-based IGF1 assay will require increased throughput and speed to justify the costs of analyses, and robust industrial platforms that are reproducible across laboratories. Presented here is an MS-based quantitative IGF1 assay with performance rating of >1,000 samples/day, and a capability of quantifying IGF1 point mutations and posttranslational modifications. The throughput of the IGF1 mass spectrometric immunoassay (MSIA) benefited from a simplified sample preparation step, IGF1 immunocapture in a tip format, and high-throughput MALDI-TOF MS analysis. The Limit of Detection and Limit of Quantification of the resulting assay were 1.5 μg/L and 5 μg/L, respectively, with intra- and inter-assay precision CVs of less than 10%, and good linearity and recovery characteristics. The IGF1 MSIA was benchmarked against commercially available IGF1 ELISA via Bland-Altman method comparison test, resulting in a slight positive bias of 16%. The IGF1 MSIA was employed in an optimized parallel workflow utilizing two pipetting robots and MALDI-TOF-MS instruments synced into one-hour phases of sample preparation, extraction and MSIA pipette tip elution, MS data collection, and data processing. Using this workflow, high-throughput IGF1 quantification of 1,054 human samples was achieved in approximately 9 hours. This rate of assaying is a significant improvement over existing MS-based IGF1 assays, and is on par with that of the enzyme-based immunoassays. Furthermore, a mutation was detected in ∼1% of the samples (SNP: rs17884626, creating an A→T substitution at position 67 of the IGF1), demonstrating the capability of IGF1 MSIA to detect point mutations and posttranslational modifications. PMID:24664114

High Throughput Protein Quantitation using MRM Viewer Software and Dynamic MRM on a Triple Quadruple Mass Spectrometer

PubMed Central

Miller, C.; Waddell, K.; Tang, N.

2010-01-01

RP-122 Peptide quantitation using Multiple Reaction Monitoring (MRM) has been established as an important methodology for biomarker verification andvalidation.This requires high throughput combined with high sensitivity to analyze potentially thousands of target peptides in each sample.Dynamic MRM allows the system to only acquire the required MRMs of the peptide during a retention window corresponding to when each peptide is eluting. This reduces the number of concurrent MRM and therefore improves quantitation and sensitivity. MRM Selector allows the user to generate an MRM transition list with retention time information from discovery data obtained on a QTOF MS system.This list can be directly imported into the triple quadrupole acquisition software.However, situations can exist where a) the list of MRMs contain an excess of MRM transitions allowable under the ideal acquisition conditions chosen ( allowing for cycle time and chromatography conditions), or b) too many transitions in a certain retention time region which would result in an unacceptably low dwell time and cycle time.A new tool - MRM viewer has been developed to help users automatically generate multiple dynamic MRM methods from a single MRM list.In this study, a list of 3293 MRM transitions from a human plasma sample was compiled.A single dynamic MRM method with 3293 transitions results in a minimum dwell time of 2.18ms.Using MRM viewer we can generate three dynamic MRM methods with a minimum dwell time of 20ms which can give a better quality MRM quantitation.This tool facilitates both high throughput and high sensitivity for MRM quantitation.

A high throughput geocomputing system for remote sensing quantitative retrieval and a case study

NASA Astrophysics Data System (ADS)

Xue, Yong; Chen, Ziqiang; Xu, Hui; Ai, Jianwen; Jiang, Shuzheng; Li, Yingjie; Wang, Ying; Guang, Jie; Mei, Linlu; Jiao, Xijuan; He, Xingwei; Hou, Tingting

2011-12-01

The quality and accuracy of remote sensing instruments have been improved significantly, however, rapid processing of large-scale remote sensing data becomes the bottleneck for remote sensing quantitative retrieval applications. The remote sensing quantitative retrieval is a data-intensive computation application, which is one of the research issues of high throughput computation. The remote sensing quantitative retrieval Grid workflow is a high-level core component of remote sensing Grid, which is used to support the modeling, reconstruction and implementation of large-scale complex applications of remote sensing science. In this paper, we intend to study middleware components of the remote sensing Grid - the dynamic Grid workflow based on the remote sensing quantitative retrieval application on Grid platform. We designed a novel architecture for the remote sensing Grid workflow. According to this architecture, we constructed the Remote Sensing Information Service Grid Node (RSSN) with Condor. We developed a graphic user interface (GUI) tools to compose remote sensing processing Grid workflows, and took the aerosol optical depth (AOD) retrieval as an example. The case study showed that significant improvement in the system performance could be achieved with this implementation. The results also give a perspective on the potential of applying Grid workflow practices to remote sensing quantitative retrieval problems using commodity class PCs.

HiCTMap: Detection and analysis of chromosome territory structure and position by high-throughput imaging.

PubMed

Jowhar, Ziad; Gudla, Prabhakar R; Shachar, Sigal; Wangsa, Darawalee; Russ, Jill L; Pegoraro, Gianluca; Ried, Thomas; Raznahan, Armin; Misteli, Tom

2018-06-01

The spatial organization of chromosomes in the nuclear space is an extensively studied field that relies on measurements of structural features and 3D positions of chromosomes with high precision and robustness. However, no tools are currently available to image and analyze chromosome territories in a high-throughput format. Here, we have developed High-throughput Chromosome Territory Mapping (HiCTMap), a method for the robust and rapid analysis of 2D and 3D chromosome territory positioning in mammalian cells. HiCTMap is a high-throughput imaging-based chromosome detection method which enables routine analysis of chromosome structure and nuclear position. Using an optimized FISH staining protocol in a 384-well plate format in conjunction with a bespoke automated image analysis workflow, HiCTMap faithfully detects chromosome territories and their position in 2D and 3D in a large population of cells per experimental condition. We apply this novel technique to visualize chromosomes 18, X, and Y in male and female primary human skin fibroblasts, and show accurate detection of the correct number of chromosomes in the respective genotypes. Given the ability to visualize and quantitatively analyze large numbers of nuclei, we use HiCTMap to measure chromosome territory area and volume with high precision and determine the radial position of chromosome territories using either centroid or equidistant-shell analysis. The HiCTMap protocol is also compatible with RNA FISH as demonstrated by simultaneous labeling of X chromosomes and Xist RNA in female cells. We suggest HiCTMap will be a useful tool for routine precision mapping of chromosome territories in a wide range of cell types and tissues. Published by Elsevier Inc.

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

Tracking antibiotic resistome during wastewater treatment using high throughput quantitative PCR.

PubMed

An, Xin-Li; Su, Jian-Qiang; Li, Bing; Ouyang, Wei-Ying; Zhao, Yi; Chen, Qing-Lin; Cui, Li; Chen, Hong; Gillings, Michael R; Zhang, Tong; Zhu, Yong-Guan

2018-05-08

Wastewater treatment plants (WWTPs) contain diverse antibiotic resistance genes (ARGs), and thus are considered as a major pathway for the dissemination of these genes into the environments. However, comprehensive evaluations of ARGs dynamic during wastewater treatment process lack extensive investigations on a broad spectrum of ARGs. Here, we investigated the dynamics of ARGs and bacterial community structures in 114 samples from eleven Chinese WWTPs using high-throughput quantitative PCR and 16S rRNA-based Illumina sequencing analysis. Significant shift of ARGs profiles was observed and wastewater treatment process could significantly reduce the abundance and diversity of ARGs, with the removal of ARGs concentration by 1-2 orders of magnitude. Whereas, a considerable number of ARGs were detected and enriched in effluents compared with influents. In particular, seven ARGs mainly conferring resistance to beta-lactams and aminoglycosides and three mobile genetic elements persisted in all WWTPs samples after wastewater treatment. ARGs profiles varied with wastewater treatment processes, seasons and regions. This study tracked the footprint of ARGs during wastewater treatment process, which would support the assessment on the spread of ARGs from WWTPs and provide data for identifying management options to improve ARG mitigation in WWTPs. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

Development of Droplet Microfluidics Enabling High-Throughput Single-Cell Analysis.

PubMed

Wen, Na; Zhao, Zhan; Fan, Beiyuan; Chen, Deyong; Men, Dong; Wang, Junbo; Chen, Jian

2016-07-05

This article reviews recent developments in droplet microfluidics enabling high-throughput single-cell analysis. Five key aspects in this field are included in this review: (1) prototype demonstration of single-cell encapsulation in microfluidic droplets; (2) technical improvements of single-cell encapsulation in microfluidic droplets; (3) microfluidic droplets enabling single-cell proteomic analysis; (4) microfluidic droplets enabling single-cell genomic analysis; and (5) integrated microfluidic droplet systems enabling single-cell screening. We examine the advantages and limitations of each technique and discuss future research opportunities by focusing on key performances of throughput, multifunctionality, and absolute quantification.

PTMScout, a Web Resource for Analysis of High Throughput Post-translational Proteomics Studies*

PubMed Central

Naegle, Kristen M.; Gymrek, Melissa; Joughin, Brian A.; Wagner, Joel P.; Welsch, Roy E.; Yaffe, Michael B.; Lauffenburger, Douglas A.; White, Forest M.

2010-01-01

The rate of discovery of post-translational modification (PTM) sites is increasing rapidly and is significantly outpacing our biological understanding of the function and regulation of those modifications. To help meet this challenge, we have created PTMScout, a web-based interface for viewing, manipulating, and analyzing high throughput experimental measurements of PTMs in an effort to facilitate biological understanding of protein modifications in signaling networks. PTMScout is constructed around a custom database of PTM experiments and contains information from external protein and post-translational resources, including gene ontology annotations, Pfam domains, and Scansite predictions of kinase and phosphopeptide binding domain interactions. PTMScout functionality comprises data set comparison tools, data set summary views, and tools for protein assignments of peptides identified by mass spectrometry. Analysis tools in PTMScout focus on informed subset selection via common criteria and on automated hypothesis generation through subset labeling derived from identification of statistically significant enrichment of other annotations in the experiment. Subset selection can be applied through the PTMScout flexible query interface available for quantitative data measurements and data annotations as well as an interface for importing data set groupings by external means, such as unsupervised learning. We exemplify the various functions of PTMScout in application to data sets that contain relative quantitative measurements as well as data sets lacking quantitative measurements, producing a set of interesting biological hypotheses. PTMScout is designed to be a widely accessible tool, enabling generation of multiple types of biological hypotheses from high throughput PTM experiments and advancing functional assignment of novel PTM sites. PTMScout is available at http://ptmscout.mit.edu. PMID:20631208

A Call for Nominations of Quantitative High-Throughput ...

EPA Pesticide Factsheets

The National Research Council of the United States National Academies of Science has recently released a document outlining a long-range vision and strategy for transforming toxicity testing from largely whole animal-based testing to one based on in vitro assays. “Toxicity Testing in the 21st Century: A Vision and a Strategy” advises a focus on relevant human toxicity pathway assays. Toxicity pathways are defined in the document as “Cellular response pathways that, when sufficiently perturbed, are expected to result in adverse health effects”. Results of such pathway screens would serve as a filter to drive selection of more specific, targeted testing that will complement and validate the pathway assays. In response to this report, the US EPA has partnered with two NIH organizations, the National Toxicology Program and the NIH Chemical Genomics Center (NCGC), in a program named Tox21. A major goal of this collaboration is to screen chemical libraries consisting of known toxicants, chemicals of environmental and occupational exposure concern, and human pharmaceuticals in cell-based pathway assays. Currently, approximately 3000 compounds (increasing to 9000 by the end of 2009) are being validated and screened in quantitative high-throughput (qHTS) format at the NCGC producing extensive concentration-response data for a diverse set of potential toxicity pathways. The Tox21 collaboration is extremely interested in accessing additional toxicity pathway assa

Quantitative monitoring of Arabidopsis thaliana growth and development using high-throughput plant phenotyping

PubMed Central

Arend, Daniel; Lange, Matthias; Pape, Jean-Michel; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Mücke, Ingo; Klukas, Christian; Altmann, Thomas; Scholz, Uwe; Junker, Astrid

2016-01-01

With the implementation of novel automated, high throughput methods and facilities in the last years, plant phenomics has developed into a highly interdisciplinary research domain integrating biology, engineering and bioinformatics. Here we present a dataset of a non-invasive high throughput plant phenotyping experiment, which uses image- and image analysis- based approaches to monitor the growth and development of 484 Arabidopsis thaliana plants (thale cress). The result is a comprehensive dataset of images and extracted phenotypical features. Such datasets require detailed documentation, standardized description of experimental metadata as well as sustainable data storage and publication in order to ensure the reproducibility of experiments, data reuse and comparability among the scientific community. Therefore the here presented dataset has been annotated using the standardized ISA-Tab format and considering the recently published recommendations for the semantical description of plant phenotyping experiments. PMID:27529152

Quantitative monitoring of Arabidopsis thaliana growth and development using high-throughput plant phenotyping.

PubMed

Arend, Daniel; Lange, Matthias; Pape, Jean-Michel; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Mücke, Ingo; Klukas, Christian; Altmann, Thomas; Scholz, Uwe; Junker, Astrid

2016-08-16

With the implementation of novel automated, high throughput methods and facilities in the last years, plant phenomics has developed into a highly interdisciplinary research domain integrating biology, engineering and bioinformatics. Here we present a dataset of a non-invasive high throughput plant phenotyping experiment, which uses image- and image analysis- based approaches to monitor the growth and development of 484 Arabidopsis thaliana plants (thale cress). The result is a comprehensive dataset of images and extracted phenotypical features. Such datasets require detailed documentation, standardized description of experimental metadata as well as sustainable data storage and publication in order to ensure the reproducibility of experiments, data reuse and comparability among the scientific community. Therefore the here presented dataset has been annotated using the standardized ISA-Tab format and considering the recently published recommendations for the semantical description of plant phenotyping experiments.

High-Throughput Quantitation of Neonicotinoids in Lyophilized Surface Water by LC-APCI-MS/MS.

PubMed

Morrison, Lucas M; Renaud, Justin B; Sabourin, Lyne; Sumarah, Mark W; Yeung, Ken K C; Lapen, David R

2018-05-21

Background : Neonicotinoids are among the most widely used insecticides. Recently, there has been concern associated with unintended adverse effects on honeybees and aquatic invertebrates at low parts-per-trillion levels. Objective : There is a need for LC-MS/MS methods that are capable of high-throughput measurements of the most widely used neonicotinoids at environmentally relevant concentrations in surface water. Methods : This method allows for quantitation of acetamiprid, clothianidin, imidacloprid, dinotefuran, nitenpyram, thiacloprid, and thiamethoxam in surface water. Deuterated internal standards are added to 20 mL environmental samples, which are concentrated by lyophilisation and reconstituted with methanol followed by acetonitrile. Results : A large variation of mean recovery efficiencies across five different surface water sampling sites within this study was observed, ranging from 45 to 74%. This demonstrated the need for labelled internal standards to compensate for these differences. Atmospheric pressure chemical ionization (APCI) performed better than electrospray ionization (ESI) with limited matrix suppression, achieving 71-110% of the laboratory fortified blank signal. Neonicotinoids were resolved on a C18 column using a 5 min LC method, in which MQL ranged between 0.93 and 4.88 ng/L. Conclusions : This method enables cost effective, accurate, and reproducible monitoring of these pesticides in the aquatic environment. Highlights : Lyophilization is used for high throughput concentration of neonicotinoids in surface water. Variations in matrix effects between samples was greatly reduced by using APCI compared with ESI. Clothianidin and thiamethoxam were detected in all samples with levels ranging from below method quantitation limit to 65 ng/L.

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 ...

High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

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

Luo, Wei; Shabbir, Faizan; Gong, Chao

2015-04-13

We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processingmore » units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.« less

Comprehensive analysis of RNA-protein interactions by high-throughput sequencing-RNA affinity profiling.

PubMed

Tome, Jacob M; Ozer, Abdullah; Pagano, John M; Gheba, Dan; Schroth, Gary P; Lis, John T

2014-06-01

RNA-protein interactions play critical roles in gene regulation, but methods to quantitatively analyze these interactions at a large scale are lacking. We have developed a high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay by adapting a high-throughput DNA sequencer to quantify the binding of fluorescently labeled protein to millions of RNAs anchored to sequenced cDNA templates. Using HiTS-RAP, we measured the affinity of mutagenized libraries of GFP-binding and NELF-E-binding aptamers to their respective targets and identified critical regions of interaction. Mutations additively affected the affinity of the NELF-E-binding aptamer, whose interaction depended mainly on a single-stranded RNA motif, but not that of the GFP aptamer, whose interaction depended primarily on secondary structure.

High-throughput technology for novel SO2 oxidation catalysts

PubMed Central

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

2011-01-01

We review the state of the art and explain the need for better SO2 oxidation catalysts for the production of sulfuric acid. A high-throughput technology has been developed for the study of potential catalysts in the oxidation of SO2 to SO3. High-throughput methods are reviewed and the problems encountered with their adaptation to the corrosive conditions of SO2 oxidation are described. We show that while emissivity-corrected infrared thermography (ecIRT) can be used for primary screening, it is prone to errors because of the large variations in the emissivity of the catalyst surface. UV-visible (UV-Vis) spectrometry was selected instead as a reliable analysis method of monitoring the SO2 conversion. Installing plain sugar absorbents at reactor outlets proved valuable for the detection and quantitative removal of SO3 from the product gas before the UV-Vis analysis. We also overview some elements used for prescreening and those remaining after the screening of the first catalyst generations. PMID:27877427

High Throughput Sequence Analysis for Disease Resistance in Maize

USDA-ARS?s Scientific Manuscript database

Preliminary results of a computational analysis of high throughput sequencing data from Zea mays and the fungus Aspergillus are reported. The Illumina Genome Analyzer was used to sequence RNA samples from two strains of Z. mays (Va35 and Mp313) collected over a time course as well as several specie...

High-throughput analysis of peptide binding modules

PubMed Central

Liu, Bernard A.; Engelmann, Brett; Nash, Piers D.

2014-01-01

Modular protein interaction domains that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some protein interaction domains such as SH2, 14-3-3, Chromo and Bromo domains serve to recognize post-translational modification of amino acids (such as phosphorylation, acetylation, methylation etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PDZ domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High throughput analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry or other HTP techniques provides new insight into the potential protein-protein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls of high-throughput analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of protein interaction domains and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions. PMID:22610655

Short-read, high-throughput sequencing technology for STR genotyping

PubMed Central

Bornman, Daniel M.; Hester, Mark E.; Schuetter, Jared M.; Kasoji, Manjula D.; Minard-Smith, Angela; Barden, Curt A.; Nelson, Scott C.; Godbold, Gene D.; Baker, Christine H.; Yang, Boyu; Walther, Jacquelyn E.; Tornes, Ivan E.; Yan, Pearlly S.; Rodriguez, Benjamin; Bundschuh, Ralf; Dickens, Michael L.; Young, Brian A.; Faith, Seth A.

2013-01-01

DNA-based methods for human identification principally rely upon genotyping of short tandem repeat (STR) loci. Electrophoretic-based techniques for variable-length classification of STRs are universally utilized, but are limited in that they have relatively low throughput and do not yield nucleotide sequence information. High-throughput sequencing technology may provide a more powerful instrument for human identification, but is not currently validated for forensic casework. Here, we present a systematic method to perform high-throughput genotyping analysis of the Combined DNA Index System (CODIS) STR loci using short-read (150 bp) massively parallel sequencing technology. Open source reference alignment tools were optimized to evaluate PCR-amplified STR loci using a custom designed STR genome reference. Evaluation of this approach demonstrated that the 13 CODIS STR loci and amelogenin (AMEL) locus could be accurately called from individual and mixture samples. Sensitivity analysis showed that as few as 18,500 reads, aligned to an in silico referenced genome, were required to genotype an individual (>99% confidence) for the CODIS loci. The power of this technology was further demonstrated by identification of variant alleles containing single nucleotide polymorphisms (SNPs) and the development of quantitative measurements (reads) for resolving mixed samples. PMID:25621315

Orchestrating high-throughput genomic analysis with Bioconductor

PubMed Central

Huber, Wolfgang; Carey, Vincent J.; Gentleman, Robert; Anders, Simon; Carlson, Marc; Carvalho, Benilton S.; Bravo, Hector Corrada; Davis, Sean; Gatto, Laurent; Girke, Thomas; Gottardo, Raphael; Hahne, Florian; Hansen, Kasper D.; Irizarry, Rafael A.; Lawrence, Michael; Love, Michael I.; MacDonald, James; Obenchain, Valerie; Oleś, Andrzej K.; Pagès, Hervé; Reyes, Alejandro; Shannon, Paul; Smyth, Gordon K.; Tenenbaum, Dan; Waldron, Levi; Morgan, Martin

2015-01-01

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors. PMID:25633503

Pneumatic Microvalve-Based Hydrodynamic Sample Injection for High-Throughput, Quantitative Zone Electrophoresis in Capillaries

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

Kelly, Ryan T.; Wang, Chenchen; Rausch, Sarah J.

2014-07-01

A hybrid microchip/capillary CE system was developed to allow unbiased and lossless sample loading and high throughput repeated injections. This new hybrid CE system consists of a polydimethylsiloxane (PDMS) microchip sample injector featuring a pneumatic microvalve that separates a sample introduction channel from a short sample loading channel and a fused silica capillary separation column that connects seamlessly to the sample loading channel. The sample introduction channel is pressurized such that when the pneumatic microvalve opens briefly, a variable-volume sample plug is introduced into the loading channel. A high voltage for CE separation is continuously applied across the loading channelmore » and the fused silica capillary separation column. Analytes are rapidly separated in the fused silica capillary with high resolution. High sensitivity MS detection after CE separation is accomplished via a sheathless CE/ESI-MS interface. The performance evaluation of the complete CE/ESI-MS platform demonstrated that reproducible sample injection with well controlled sample plug volumes could be achieved by using the PDMS microchip injector. The absence of band broadening from microchip to capillary indicated a minimum dead volume at the junction. The capabilities of the new CE/ESI-MS platform in performing high throughput and quantitative sample analyses were demonstrated by the repeated sample injection without interrupting an ongoing separation and a good linear dependence of the total analyte ion abundance on the sample plug volume using a mixture of peptide standards. The separation efficiency of the new platform was also evaluated systematically at different sample injection times, flow rates and CE separation voltages.« less

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.

Tissue matrix arrays for high throughput screening and systems analysis of cell function

PubMed Central

Beachley, Vince Z.; Wolf, Matthew T.; Sadtler, Kaitlyn; Manda, Srikanth S.; Jacobs, Heather; Blatchley, Michael; Bader, Joel S.; Pandey, Akhilesh; Pardoll, Drew; Elisseeff, Jennifer H.

2015-01-01

Cell and protein arrays have demonstrated remarkable utility in the high-throughput evaluation of biological responses; however, they lack the complexity of native tissue and organs. Here, we describe tissue extracellular matrix (ECM) arrays for screening biological outputs and systems analysis. We spotted processed tissue ECM particles as two-dimensional arrays or incorporated them with cells to generate three-dimensional cell-matrix microtissue arrays. We then investigated the response of human stem, cancer, and immune cells to tissue ECM arrays originating from 11 different tissues, and validated the 2D and 3D arrays as representative of the in vivo microenvironment through quantitative analysis of tissue-specific cellular responses, including matrix production, adhesion and proliferation, and morphological changes following culture. The biological outputs correlated with tissue proteomics, and network analysis identified several proteins linked to cell function. Our methodology enables broad screening of ECMs to connect tissue-specific composition with biological activity, providing a new resource for biomaterials research and translation. PMID:26480475

Pneumatic Microvalve-Based Hydrodynamic Sample Injection for High-Throughput, Quantitative Zone Electrophoresis in Capillaries

PubMed Central

2015-01-01

A hybrid microchip/capillary electrophoresis (CE) system was developed to allow unbiased and lossless sample loading and high-throughput repeated injections. This new hybrid CE system consists of a poly(dimethylsiloxane) (PDMS) microchip sample injector featuring a pneumatic microvalve that separates a sample introduction channel from a short sample loading channel, and a fused-silica capillary separation column that connects seamlessly to the sample loading channel. The sample introduction channel is pressurized such that when the pneumatic microvalve opens briefly, a variable-volume sample plug is introduced into the loading channel. A high voltage for CE separation is continuously applied across the loading channel and the fused-silica capillary separation column. Analytes are rapidly separated in the fused-silica capillary, and following separation, high-sensitivity MS detection is accomplished via a sheathless CE/ESI-MS interface. The performance evaluation of the complete CE/ESI-MS platform demonstrated that reproducible sample injection with well controlled sample plug volumes could be achieved by using the PDMS microchip injector. The absence of band broadening from microchip to capillary indicated a minimum dead volume at the junction. The capabilities of the new CE/ESI-MS platform in performing high-throughput and quantitative sample analyses were demonstrated by the repeated sample injection without interrupting an ongoing separation and a linear dependence of the total analyte ion abundance on the sample plug volume using a mixture of peptide standards. The separation efficiency of the new platform was also evaluated systematically at different sample injection times, flow rates, and CE separation voltages. PMID:24865952

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

PubMed

Zhu, Zhi; Yang, Chaoyong James

2017-01-17

Heterogeneity among individual molecules and cells has posed significant challenges to traditional bulk assays, due to the assumption of average behavior, which would lose important biological information in heterogeneity and result in a misleading interpretation. Single molecule/cell analysis has become an important and emerging field in biological and biomedical research for insights into heterogeneity between large populations at high resolution. Compared with the ensemble bulk method, single molecule/cell analysis explores the information on time trajectories, conformational states, and interactions of individual molecules/cells, all key factors in the study of chemical and biological reaction pathways. Various powerful techniques have been developed for single molecule/cell analysis, including flow cytometry, atomic force microscopy, optical and magnetic tweezers, single-molecule fluorescence spectroscopy, and so forth. However, some of them have the low-throughput issue that has to analyze single molecules/cells one by one. Flow cytometry is a widely used high-throughput technique for single cell analysis but lacks the ability for intercellular interaction study and local environment control. Droplet microfluidics becomes attractive for single molecule/cell manipulation because single molecules/cells can be individually encased in monodisperse microdroplets, allowing high-throughput analysis and manipulation with precise control of the local environment. Moreover, hydrogels, cross-linked polymer networks that swell in the presence of water, have been introduced into droplet microfluidic systems as hydrogel droplet microfluidics. By replacing an aqueous phase with a monomer or polymer solution, hydrogel droplets can be generated on microfluidic chips for encapsulation of single molecules/cells according to the Poisson distribution. The sol-gel transition property endows the hydrogel droplets with new functionalities and diversified applications in single

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

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

PubMed Central

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

2014-01-01

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

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

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...

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

Treesearch

William R. Kenealy; Thomas W. Jeffries

2003-01-01

High-throughput screening requires simple assays that give reliable quantitative results. A microplate assay was developed for reducing sugar analysis that uses a 2,2'-bicinchoninic-based protein reagent. Endo-1,4-â-D-xylanase activity against oat spelt xylan was detected at activities of 0.002 to 0.011 IU ml−1. The assay is linear for sugar...

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine.

PubMed

Chen, Zhidan; Coy, Stephen L; Pannkuk, Evan L; Laiakis, Evagelia C; Fornace, Albert J; Vouros, Paul

2018-05-07

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. Graphical Abstract.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

NASA Astrophysics Data System (ADS)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Fornace, Albert J.; Vouros, Paul

2018-05-01

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. [Figure not available: see fulltext.

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

Structuring intuition with theory: The high-throughput way

NASA Astrophysics Data System (ADS)

Fornari, Marco

2015-03-01

First principles methodologies have grown in accuracy and applicability to the point where large databases can be built, shared, and analyzed with the goal of predicting novel compositions, optimizing functional properties, and discovering unexpected relationships between the data. In order to be useful to a large community of users, data should be standardized, validated, and distributed. In addition, tools to easily manage large datasets should be made available to effectively lead to materials development. Within the AFLOW consortium we have developed a simple frame to expand, validate, and mine data repositories: the MTFrame. Our minimalistic approach complement AFLOW and other existing high-throughput infrastructures and aims to integrate data generation with data analysis. We present few examples from our work on materials for energy conversion. Our intent s to pinpoint the usefulness of high-throughput methodologies to guide the discovery process by quantitatively structuring the scientific intuition. This work was supported by ONR-MURI under Contract N00014-13-1-0635 and the Duke University Center for Materials Genomics.

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

PubMed Central

2010-01-01

Background In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. Results We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve

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

PubMed

Finak, Greg; Perez, Juan-Manuel; Weng, Andrew; Gottardo, Raphael

2010-11-04

In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce

High-Precision Pinpointing of Luminescent Targets in Encoder-Assisted Scanning Microscopy Allowing High-Speed Quantitative Analysis.

PubMed

Zheng, Xianlin; Lu, Yiqing; Zhao, Jiangbo; Zhang, Yuhai; Ren, Wei; Liu, Deming; Lu, Jie; Piper, James A; Leif, Robert C; Liu, Xiaogang; Jin, Dayong

2016-01-19

Compared with routine microscopy imaging of a few analytes at a time, rapid scanning through the whole sample area of a microscope slide to locate every single target object offers many advantages in terms of simplicity, speed, throughput, and potential for robust quantitative analysis. Existing techniques that accommodate solid-phase samples incorporating individual micrometer-sized targets generally rely on digital microscopy and image analysis, with intrinsically low throughput and reliability. Here, we report an advanced on-the-fly stage scanning method to achieve high-precision target location across the whole slide. By integrating X- and Y-axis linear encoders to a motorized stage as the virtual "grids" that provide real-time positional references, we demonstrate an orthogonal scanning automated microscopy (OSAM) technique which can search a coverslip area of 50 × 24 mm(2) in just 5.3 min and locate individual 15 μm lanthanide luminescent microspheres with standard deviations of 1.38 and 1.75 μm in X and Y directions. Alongside implementation of an autofocus unit that compensates the tilt of a slide in the Z-axis in real time, we increase the luminescence detection efficiency by 35% with an improved coefficient of variation. We demonstrate the capability of advanced OSAM for robust quantification of luminescence intensities and lifetimes for a variety of micrometer-scale luminescent targets, specifically single down-shifting and upconversion microspheres, crystalline microplates, and color-barcoded microrods, as well as quantitative suspension array assays of biotinylated-DNA functionalized upconversion nanoparticles.

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

PubMed

Najafov, Jamil; Najafov, Ayaz

2017-07-19

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

Evaluation of a High Throughput Starch Analysis Optimised for Wood

PubMed Central

Bellasio, Chandra; Fini, Alessio; Ferrini, Francesco

2014-01-01

Starch is the most important long-term reserve in trees, and the analysis of starch is therefore useful source of physiological information. Currently published protocols for wood starch analysis impose several limitations, such as long procedures and a neutralization step. The high-throughput standard protocols for starch analysis in food and feed represent a valuable alternative. However, they have not been optimised or tested with woody samples. These have particular chemical and structural characteristics, including the presence of interfering secondary metabolites, low reactivity of starch, and low starch content. In this study, a standard method for starch analysis used for food and feed (AOAC standard method 996.11) was optimised to improve precision and accuracy for the analysis of starch in wood. Key modifications were introduced in the digestion conditions and in the glucose assay. The optimised protocol was then evaluated through 430 starch analyses of standards at known starch content, matrix polysaccharides, and wood collected from three organs (roots, twigs, mature wood) of four species (coniferous and flowering plants). The optimised protocol proved to be remarkably precise and accurate (3%), suitable for a high throughput routine analysis (35 samples a day) of specimens with a starch content between 40 mg and 21 µg. Samples may include lignified organs of coniferous and flowering plants and non-lignified organs, such as leaves, fruits and rhizomes. PMID:24523863

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

High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

PubMed Central

Choudhry, Priya

2016-01-01

Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays. PMID:26848849

High-throughput detection and screening of plants modified by gene editing using quantitative real-time polymerase chain reaction.

PubMed

Peng, Cheng; Wang, Hua; Xu, Xiaoli; Wang, Xiaofu; Chen, Xiaoyun; Wei, Wei; Lai, Yongmin; Liu, Guoquan; Godwin, Ian Douglas; Li, Jieqin; Zhang, Ling; Xu, Junfeng

2018-05-15

Gene editing techniques are becoming powerful tools for modifying target genes in organisms. Although several methods have been developed to detect gene-edited organisms, these techniques are time and labour intensive. Meanwhile, few studies have investigated high-throughput detection and screening strategies for plants modified by gene editing. In this study, we developed a simple, sensitive and high-throughput quantitative real-time (qPCR)-based method. The qPCR-based method exploits two differently labelled probes that are placed within one amplicon at the gene editing target site to simultaneously detect the wild-type and a gene-edited mutant. We showed that the qPCR-based method can accurately distinguish CRISPR/Cas9-induced mutants from the wild-type in several different plant species, such as Oryza sativa, Arabidopsis thaliana, Sorghum bicolor, and Zea mays. Moreover, the method can subsequently determine the mutation type by direct sequencing of the qPCR products of mutations due to gene editing. The qPCR-based method is also sufficiently sensitive to distinguish between heterozygous and homozygous mutations in T 0 transgenic plants. In a 384-well plate format, the method enabled the simultaneous analysis of up to 128 samples in three replicates without handling the post-polymerase chain reaction (PCR) products. Thus, we propose that our method is an ideal choice for screening plants modified by gene editing from many candidates in T 0 transgenic plants, which will be widely used in the area of plant gene editing. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

High-Throughput Method for Strontium Isotope Analysis by Multi-Collector-Inductively Coupled Plasma-Mass Spectrometer

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

Wall, Andrew J.; Capo, Rosemary C.; Stewart, Brian W.

2016-09-22

This technical report presents the details of the Sr column configuration and the high-throughput Sr separation protocol. Data showing the performance of the method as well as the best practices for optimizing Sr isotope analysis by MC-ICP-MS is presented. Lastly, this report offers tools for data handling and data reduction of Sr isotope results from the Thermo Scientific Neptune software to assist in data quality assurance, which help avoid issues of data glut associated with high sample throughput rapid analysis.

High-Throughput Method for Strontium Isotope Analysis by Multi-Collector-Inductively Coupled Plasma-Mass Spectrometer

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

Hakala, Jacqueline Alexandra

2016-11-22

This technical report presents the details of the Sr column configuration and the high-throughput Sr separation protocol. Data showing the performance of the method as well as the best practices for optimizing Sr isotope analysis by MC-ICP-MS is presented. Lastly, this report offers tools for data handling and data reduction of Sr isotope results from the Thermo Scientific Neptune software to assist in data quality assurance, which help avoid issues of data glut associated with high sample throughput rapid analysis.

An improved high-throughput lipid extraction method for the analysis of human brain lipids.

PubMed

Abbott, Sarah K; Jenner, Andrew M; Mitchell, Todd W; Brown, Simon H J; Halliday, Glenda M; Garner, Brett

2013-03-01

We have developed a protocol suitable for high-throughput lipidomic analysis of human brain samples. The traditional Folch extraction (using chloroform and glass-glass homogenization) was compared to a high-throughput method combining methyl-tert-butyl ether (MTBE) extraction with mechanical homogenization utilizing ceramic beads. This high-throughput method significantly reduced sample handling time and increased efficiency compared to glass-glass homogenizing. Furthermore, replacing chloroform with MTBE is safer (less carcinogenic/toxic), with lipids dissolving in the upper phase, allowing for easier pipetting and the potential for automation (i.e., robotics). Both methods were applied to the analysis of human occipital cortex. Lipid species (including ceramides, sphingomyelins, choline glycerophospholipids, ethanolamine glycerophospholipids and phosphatidylserines) were analyzed via electrospray ionization mass spectrometry and sterol species were analyzed using gas chromatography mass spectrometry. No differences in lipid species composition were evident when the lipid extraction protocols were compared, indicating that MTBE extraction with mechanical bead homogenization provides an improved method for the lipidomic profiling of human brain tissue.

Isotonic Regression Based-Method in Quantitative High-Throughput Screenings for Genotoxicity

PubMed Central

Fujii, Yosuke; Narita, Takeo; Tice, Raymond Richard; Takeda, Shunich

2015-01-01

Quantitative high-throughput screenings (qHTSs) for genotoxicity are conducted as part of comprehensive toxicology screening projects. The most widely used method is to compare the dose-response data of a wild-type and DNA repair gene knockout mutants, using model-fitting to the Hill equation (HE). However, this method performs poorly when the observed viability does not fit the equation well, as frequently happens in qHTS. More capable methods must be developed for qHTS where large data variations are unavoidable. In this study, we applied an isotonic regression (IR) method and compared its performance with HE under multiple data conditions. When dose-response data were suitable to draw HE curves with upper and lower asymptotes and experimental random errors were small, HE was better than IR, but when random errors were big, there was no difference between HE and IR. However, when the drawn curves did not have two asymptotes, IR showed better performance (p < 0.05, exact paired Wilcoxon test) with higher specificity (65% in HE vs. 96% in IR). In summary, IR performed similarly to HE when dose-response data were optimal, whereas IR clearly performed better in suboptimal conditions. These findings indicate that IR would be useful in qHTS for comparing dose-response data. PMID:26673567

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

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-07-01

The Bayesian regularization method for high-throughput differential analysis, described in Baldi and Long (A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics 2001: 17: 509-519) and implemented in the Cyber-T web server, is one of the most widely validated. Cyber-T implements a t-test using a Bayesian framework to compute a regularized variance of the measurements associated with each probe under each condition. This regularized estimate is derived by flexibly combining the empirical measurements with a prior, or background, derived from pooling measurements associated with probes in the same neighborhood. This approach flexibly addresses problems associated with low replication levels and technology biases, not only for DNA microarrays, but also for other technologies, such as protein arrays, quantitative mass spectrometry and next-generation sequencing (RNA-seq). Here we present an update to the Cyber-T web server, incorporating several useful new additions and improvements. Several preprocessing data normalization options including logarithmic and (Variance Stabilizing Normalization) VSN transforms are included. To augment two-sample t-tests, a one-way analysis of variance is implemented. Several methods for multiple tests correction, including standard frequentist methods and a probabilistic mixture model treatment, are available. Diagnostic plots allow visual assessment of the results. The web server provides comprehensive documentation and example data sets. The Cyber-T web server, with R source code and data sets, is publicly available at http://cybert.ics.uci.edu/.

Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

PubMed

Wyatt, S K; Barck, K H; Kates, L; Zavala-Solorio, J; Ross, J; Kolumam, G; Sonoda, J; Carano, R A D

2015-11-01

The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition

High-throughput analysis using non-depletive SPME: challenges and applications to the determination of free and total concentrations in small sample volumes.

PubMed

Boyacı, Ezel; Bojko, Barbara; Reyes-Garcés, Nathaly; Poole, Justen J; Gómez-Ríos, Germán Augusto; Teixeira, Alexandre; Nicol, Beate; Pawliszyn, Janusz

2018-01-18

In vitro high-throughput non-depletive quantitation of chemicals in biofluids is of growing interest in many areas. Some of the challenges facing researchers include the limited volume of biofluids, rapid and high-throughput sampling requirements, and the lack of reliable methods. Coupled to the above, growing interest in the monitoring of kinetics and dynamics of miniaturized biosystems has spurred the demand for development of novel and revolutionary methodologies for analysis of biofluids. The applicability of solid-phase microextraction (SPME) is investigated as a potential technology to fulfill the aforementioned requirements. As analytes with sufficient diversity in their physicochemical features, nicotine, N,N-Diethyl-meta-toluamide, and diclofenac were selected as test compounds for the study. The objective was to develop methodologies that would allow repeated non-depletive sampling from 96-well plates, using 100 µL of sample. Initially, thin film-SPME was investigated. Results revealed substantial depletion and consequent disruption in the system. Therefore, new ultra-thin coated fibers were developed. The applicability of this device to the described sampling scenario was tested by determining the protein binding of the analytes. Results showed good agreement with rapid equilibrium dialysis. The presented method allows high-throughput analysis using small volumes, enabling fast reliable free and total concentration determinations without disruption of system equilibrium.

A comparison of sorptive extraction techniques coupled to a new quantitative, sensitive, high throughput GC-MS/MS method for methoxypyrazine analysis in wine.

PubMed

Hjelmeland, Anna K; Wylie, Philip L; Ebeler, Susan E

2016-02-01

Methoxypyrazines are volatile compounds found in plants, microbes, and insects that have potent vegetal and earthy aromas. With sensory detection thresholds in the low ng L(-1) range, modest concentrations of these compounds can profoundly impact the aroma quality of foods and beverages, and high levels can lead to consumer rejection. The wine industry routinely analyzes the most prevalent methoxypyrazine, 2-isobutyl-3-methoxypyrazine (IBMP), to aid in harvest decisions, since concentrations decrease during berry ripening. In addition to IBMP, three other methoxypyrazines IPMP (2-isopropyl-3-methoxypyrazine), SBMP (2-sec-butyl-3-methoxypyrazine), and EMP (2-ethyl-3-methoxypyrazine) have been identified in grapes and/or wine and can impact aroma quality. Despite their routine analysis in the wine industry (mostly IBMP), accurate methoxypyrazine quantitation is hindered by two major challenges: sensitivity and resolution. With extremely low sensory detection thresholds (~8-15 ng L(-1) in wine for IBMP), highly sensitive analytical methods to quantify methoxypyrazines at trace levels are necessary. Here we were able to achieve resolution of IBMP as well as IPMP, EMP, and SBMP from co-eluting compounds using one-dimensional chromatography coupled to positive chemical ionization tandem mass spectrometry. Three extraction techniques HS-SPME (headspace-solid phase microextraction), SBSE (stirbar sorptive extraction), and HSSE (headspace sorptive extraction) were validated and compared. A 30 min extraction time was used for HS-SPME and SBSE extraction techniques, while 120 min was necessary to achieve sufficient sensitivity for HSSE extractions. All extraction methods have limits of quantitation (LOQ) at or below 1 ng L(-1) for all four methoxypyrazines analyzed, i.e., LOQ's at or below reported sensory detection limits in wine. The method is high throughput, with resolution of all compounds possible with a relatively rapid 27 min GC oven program. Copyright © 2015

A high-throughput screening system for barley/powdery mildew interactions based on automated analysis of light micrographs.

PubMed

Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

2008-01-23

To find candidate genes that potentially influence the susceptibility or resistance of crop plants to powdery mildew fungi, an assay system based on transient-induced gene silencing (TIGS) as well as transient over-expression in single epidermal cells of barley has been developed. However, this system relies on quantitative microscopic analysis of the barley/powdery mildew interaction and will only become a high-throughput tool of phenomics upon automation of the most time-consuming steps. We have developed a high-throughput screening system based on a motorized microscope which evaluates the specimens fully automatically. A large-scale double-blind verification of the system showed an excellent agreement of manual and automated analysis and proved the system to work dependably. Furthermore, in a series of bombardment experiments an RNAi construct targeting the Mlo gene was included, which is expected to phenocopy resistance mediated by recessive loss-of-function alleles such as mlo5. In most cases, the automated analysis system recorded a shift towards resistance upon RNAi of Mlo, thus providing proof of concept for its usefulness in detecting gene-target effects. Besides saving labor and enabling a screening of thousands of candidate genes, this system offers continuous operation of expensive laboratory equipment and provides a less subjective analysis as well as a complete and enduring documentation of the experimental raw data in terms of digital images. In general, it proves the concept of enabling available microscope hardware to handle challenging screening tasks fully automatically.

High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Jiang, Yiyue; Tanaka, Yo; Ozeki, Yasuyuki; Goda, Keisuke

2017-05-01

The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO 2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

High throughput and quantitative approaches for measuring circadian rhythms in cyanobacteria using bioluminescence

PubMed Central

Shultzaberger, Ryan K.; Paddock, Mark L.; Katsuki, Takeo; Greenspan, Ralph J.; Golden, Susan S.

2016-01-01

The temporal measurement of a bioluminescent reporter has proven to be one of the most powerful tools for characterizing circadian rhythms in the cyanobacterium Synechococcus elongatus. Primarily, two approaches have been used to automate this process: (1) detection of cell culture bioluminescence in 96-well plates by a photomultiplier tube-based plate-cycling luminometer (TopCount Microplate Scintillation and Luminescence Counter, Perkin Elmer) and (2) detection of individual colony bioluminescence by iteratively rotating a Petri dish under a cooled CCD camera using a computer-controlled turntable. Each approach has distinct advantages. The TopCount provides a more quantitative measurement of bioluminescence, enabling the direct comparison of clock output levels among strains. The computer-controlled turntable approach has a shorter set-up time and greater throughput, making it a more powerful phenotypic screening tool. While the latter approach is extremely useful, only a few labs have been able to build such an apparatus because of technical hurdles involved in coordinating and controlling both the camera and the turntable, and in processing the resulting images. This protocol provides instructions on how to construct, use, and process data from a computer-controlled turntable to measure the temporal changes in bioluminescence of individual cyanobacterial colonies. Furthermore, we describe how to prepare samples for use with the TopCount to minimize experimental noise, and generate meaningful quantitative measurements of clock output levels for advanced analysis. PMID:25662451

Digital pathology and image analysis for robust high-throughput quantitative assessment of Alzheimer disease neuropathologic changes.

PubMed

Neltner, Janna Hackett; Abner, Erin Lynn; Schmitt, Frederick A; Denison, Stephanie Kay; Anderson, Sonya; Patel, Ela; Nelson, Peter T

2012-12-01

Quantitative neuropathologic methods provide information that is important for both research and clinical applications. The technologic advancement of digital pathology and image analysis offers new solutions to enable valid quantification of pathologic severity that is reproducible between raters regardless of experience. Using an Aperio ScanScope XT and its accompanying image analysis software, we designed algorithms for quantitation of amyloid and tau pathologies on 65 β-amyloid (6F/3D antibody) and 48 phospho-tau (PHF-1)-immunostained sections of human temporal neocortex. Quantitative digital pathologic data were compared with manual pathology counts. There were excellent correlations between manually counted and digitally analyzed neuropathologic parameters (R² = 0.56-0.72). Data were highly reproducible among 3 participants with varying degrees of expertise in neuropathology (intraclass correlation coefficient values, >0.910). Digital quantification also provided additional parameters, including average plaque area, which shows statistically significant differences when samples are stratified according to apolipoprotein E allele status (average plaque area, 380.9 μm² in apolipoprotein E [Latin Small Letter Open E]4 carriers vs 274.4 μm² for noncarriers; p < 0.001). Thus, digital pathology offers a rigorous and reproducible method for quantifying Alzheimer disease neuropathologic changes and may provide additional insights into morphologic characteristics that were previously more challenging to assess because of technical limitations.

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

PubMed

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

2008-04-01

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

Improved Selection of Internal Transcribed Spacer-Specific Primers Enables Quantitative, Ultra-High-Throughput Profiling of Fungal Communities

PubMed Central

Bokulich, Nicholas A.

2013-01-01

Ultra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predicted in silico and by sequencing a “mock community” of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities. PMID:23377949

Recent Advances in Nanobiotechnology and High-Throughput Molecular Techniques for Systems Biomedicine

PubMed Central

Kim, Eung-Sam; Ahn, Eun Hyun; Chung, Euiheon; Kim, Deok-Ho

2013-01-01

Nanotechnology-based tools are beginning to emerge as promising platforms for quantitative high-throughput analysis of live cells and tissues. Despite unprecedented progress made over the last decade, a challenge still lies in integrating emerging nanotechnology-based tools into macroscopic biomedical apparatuses for practical purposes in biomedical sciences. In this review, we discuss the recent advances and limitations in the analysis and control of mechanical, biochemical, fluidic, and optical interactions in the interface areas of nanotechnology-based materials and living cells in both in vitro and in vivo settings. PMID:24258011

Recent advances in nanobiotechnology and high-throughput molecular techniques for systems biomedicine.

PubMed

Kim, Eung-Sam; Ahn, Eun Hyun; Chung, Euiheon; Kim, Deok-Ho

2013-12-01

Nanotechnology-based tools are beginning to emerge as promising platforms for quantitative high-throughput analysis of live cells and tissues. Despite unprecedented progress made over the last decade, a challenge still lies in integrating emerging nanotechnology-based tools into macroscopic biomedical apparatuses for practical purposes in biomedical sciences. In this review, we discuss the recent advances and limitations in the analysis and control of mechanical, biochemical, fluidic, and optical interactions in the interface areas of nanotechnologybased materials and living cells in both in vitro and in vivo settings.

A highly efficient, high-throughput lipidomics platform for the quantitative detection of eicosanoids in human whole blood.

PubMed

Song, Jiao; Liu, Xuejun; Wu, Jiejun; Meehan, Michael J; Blevitt, Jonathan M; Dorrestein, Pieter C; Milla, Marcos E

2013-02-15

We have developed an ultra-performance liquid chromatography-multiple reaction monitoring/mass spectrometry (UPLC-MRM/MS)-based, high-content, high-throughput platform that enables simultaneous profiling of multiple lipids produced ex vivo in human whole blood (HWB) on treatment with calcium ionophore and its modulation with pharmacological agents. HWB samples were processed in a 96-well plate format compatible with high-throughput sample processing instrumentation. We employed a scheduled MRM (sMRM) method, with a triple-quadrupole mass spectrometer coupled to a UPLC system, to measure absolute amounts of 122 distinct eicosanoids using deuterated internal standards. In a 6.5-min run, we resolved and detected with high sensitivity (lower limit of quantification in the range of 0.4-460 pg) all targeted analytes from a very small HWB sample (2.5 μl). Approximately 90% of the analytes exhibited a dynamic range exceeding 1000. We also developed a tailored software package that dramatically sped up the overall data quantification and analysis process with superior consistency and accuracy. Matrix effects from HWB and precision of the calibration curve were evaluated using this newly developed automation tool. This platform was successfully applied to the global quantification of changes on all 122 eicosanoids in HWB samples from healthy donors in response to calcium ionophore stimulation. Copyright © 2012 Elsevier Inc. All rights reserved.

High-Throughput Assessment of Cellular Mechanical Properties.

PubMed

Darling, Eric M; Di Carlo, Dino

2015-01-01

Traditionally, cell analysis has focused on using molecular biomarkers for basic research, cell preparation, and clinical diagnostics; however, new microtechnologies are enabling evaluation of the mechanical properties of cells at throughputs that make them amenable to widespread use. We review the current understanding of how the mechanical characteristics of cells relate to underlying molecular and architectural changes, describe how these changes evolve with cell-state and disease processes, and propose promising biomedical applications that will be facilitated by the increased throughput of mechanical testing: from diagnosing cancer and monitoring immune states to preparing cells for regenerative medicine. We provide background about techniques that laid the groundwork for the quantitative understanding of cell mechanics and discuss current efforts to develop robust techniques for rapid analysis that aim to implement mechanophenotyping as a routine tool in biomedicine. Looking forward, we describe additional milestones that will facilitate broad adoption, as well as new directions not only in mechanically assessing cells but also in perturbing them to passively engineer cell state.

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

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy.

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.

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.

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.

Fast multiclonal clusterization of V(D)J recombinations from high-throughput sequencing.

PubMed

Giraud, Mathieu; Salson, Mikaël; Duez, Marc; Villenet, Céline; Quief, Sabine; Caillault, Aurélie; Grardel, Nathalie; Roumier, Christophe; Preudhomme, Claude; Figeac, Martin

2014-05-28

V(D)J recombinations in lymphocytes are essential for immunological diversity. They are also useful markers of pathologies. In leukemia, they are used to quantify the minimal residual disease during patient follow-up. However, the full breadth of lymphocyte diversity is not fully understood. We propose new algorithms that process high-throughput sequencing (HTS) data to extract unnamed V(D)J junctions and gather them into clones for quantification. This analysis is based on a seed heuristic and is fast and scalable because in the first phase, no alignment is performed with germline database sequences. The algorithms were applied to TR γ HTS data from a patient with acute lymphoblastic leukemia, and also on data simulating hypermutations. Our methods identified the main clone, as well as additional clones that were not identified with standard protocols. The proposed algorithms provide new insight into the analysis of high-throughput sequencing data for leukemia, and also to the quantitative assessment of any immunological profile. The methods described here are implemented in a C++ open-source program called Vidjil.

Using Weighted Entropy to Rank Chemicals in Quantitative High Throughput Screening Experiments

PubMed Central

Shockley, Keith R.

2014-01-01

Quantitative high throughput screening (qHTS) experiments can simultaneously produce concentration-response profiles for thousands of chemicals. In a typical qHTS study, a large chemical library is subjected to a primary screen in order to identify candidate hits for secondary screening, validation studies or prediction modeling. Different algorithms, usually based on the Hill equation logistic model, have been used to classify compounds as active or inactive (or inconclusive). However, observed concentration-response activity relationships may not adequately fit a sigmoidal curve. Furthermore, it is unclear how to prioritize chemicals for follow-up studies given the large uncertainties that often accompany parameter estimates from nonlinear models. Weighted Shannon entropy can address these concerns by ranking compounds according to profile-specific statistics derived from estimates of the probability mass distribution of response at the tested concentration levels. This strategy can be used to rank all tested chemicals in the absence of a pre-specified model structure or the approach can complement existing activity call algorithms by ranking the returned candidate hits. The weighted entropy approach was evaluated here using data simulated from the Hill equation model. The procedure was then applied to a chemical genomics profiling data set interrogating compounds for androgen receptor agonist activity. PMID:24056003

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

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Chisholm, Bret J.; Olson, Daniel R.; Brennan, Michael J.; Molaison, Chris A.

2002-02-01

Design, validation, and implementation of an optical spectroscopic system for high-throughput analysis of combinatorially developed protective organic coatings are reported. Our approach replaces labor-intensive coating evaluation steps with an automated system that rapidly analyzes 8x6 arrays of coating elements that are deposited on a plastic substrate. Each coating element of the library is 10 mm in diameter and 2 to 5 micrometers thick. Performance of coatings is evaluated with respect to their resistance to wear abrasion because this parameter is one of the primary considerations in end-use applications. Upon testing, the organic coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Coatings are abraded using industry-accepted abrasion test methods at single-or multiple-abrasion conditions, followed by high- throughput analysis of abrasion-induced light scatter. The developed automated system is optimized for the analysis of diffusively scattered light that corresponds to 0 to 30% haze. System precision of 0.1 to 2.5% relative standard deviation provides capability for the reliable ranking of coatings performance. While the system was implemented for high-throughput screening of combinatorially developed organic protective coatings for automotive applications, it can be applied to a variety of other applications where materials ranking can be achieved using optical spectroscopic tools.

Multispot single-molecule FRET: High-throughput analysis of freely diffusing molecules

PubMed Central

Panzeri, Francesco

2017-01-01

We describe an 8-spot confocal setup for high-throughput smFRET assays and illustrate its performance with two characteristic experiments. First, measurements on a series of freely diffusing doubly-labeled dsDNA samples allow us to demonstrate that data acquired in multiple spots in parallel can be properly corrected and result in measured sample characteristics consistent with those obtained with a standard single-spot setup. We then take advantage of the higher throughput provided by parallel acquisition to address an outstanding question about the kinetics of the initial steps of bacterial RNA transcription. Our real-time kinetic analysis of promoter escape by bacterial RNA polymerase confirms results obtained by a more indirect route, shedding additional light on the initial steps of transcription. Finally, we discuss the advantages of our multispot setup, while pointing potential limitations of the current single laser excitation design, as well as analysis challenges and their solutions. PMID:28419142

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.

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis.

PubMed

Tu, Jing; Ge, Qinyu; Wang, Shengqin; Wang, Lei; Sun, Beili; Yang, Qi; Bai, Yunfei; Lu, Zuhong

2012-01-25

The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand.

High-throughput alternative splicing detection using dually constrained correspondence analysis (DCCA).

PubMed

Baty, Florent; Klingbiel, Dirk; Zappa, Francesco; Brutsche, Martin

2015-12-01

Alternative splicing is an important component of tumorigenesis. Recent advent of exon array technology enables the detection of alternative splicing at a genome-wide scale. The analysis of high-throughput alternative splicing is not yet standard and methodological developments are still needed. We propose a novel statistical approach-Dually Constrained Correspondence Analysis-for the detection of splicing changes in exon array data. Using this methodology, we investigated the genome-wide alteration of alternative splicing in patients with non-small cell lung cancer treated by bevacizumab/erlotinib. Splicing candidates reveal a series of genes related to carcinogenesis (SFTPB), cell adhesion (STAB2, PCDH15, HABP2), tumor aggressiveness (ARNTL2), apoptosis, proliferation and differentiation (PDE4D, FLT3, IL1R2), cell invasion (ETV1), as well as tumor growth (OLFM4, FGF14), tumor necrosis (AFF3) or tumor suppression (TUSC3, CSMD1, RHOBTB2, SERPINB5), with indication of known alternative splicing in a majority of genes. DCCA facilitates the identification of putative biologically relevant alternative splicing events in high-throughput exon array data. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

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

PubMed

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

2017-02-21

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

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...

Chipster: user-friendly analysis software for microarray and other high-throughput data.

PubMed

Kallio, M Aleksi; Tuimala, Jarno T; Hupponen, Taavi; Klemelä, Petri; Gentile, Massimiliano; Scheinin, Ilari; Koski, Mikko; Käki, Janne; Korpelainen, Eija I

2011-10-14

The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available.

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.

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

PubMed Central

Wang, Li; Carnegie, Graeme K.

2013-01-01

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction. PMID:23979513

Flow cytometric analysis of bimolecular fluorescence complementation: a high throughput quantitative method to study protein-protein interaction.

PubMed

Wang, Li; Carnegie, Graeme K

2013-08-15

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy

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

Suzuki, Kazumichi, E-mail: kazumichisuzuki@gmail.c

approximately 30%–40% of total treatment time for the total target volumes exceeding 200 cm{sup 3}, which was the case for more than 80% of the patients in this study. When total treatment time was modeled as a function of the number of fields and total target volume, the model overestimated total treatment time by 12% on average, with a standard deviation of 32%. A sensitivity analysis of throughput capacity for a hypothetical four-room spot scanning proton therapy center identified several priority items for improvements in throughput capacity, including operation time, beam delivery time, and patient immobilization and setup time. Conclusions: The spot scanning port at our proton therapy center has operated at a high performance level and has been used to treat a large number of complex cases. Further improvements in efficiency may be feasible in the areas of facility operation, beam delivery, patient immobilization and setup, and optimization of treatment scheduling.« less

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy.

PubMed

Suzuki, Kazumichi; Palmer, Matthew B; Sahoo, Narayan; Zhang, Xiaodong; Poenisch, Falk; Mackin, Dennis S; Liu, Amy Y; Wu, Richard; Zhu, X Ronald; Frank, Steven J; Gillin, Michael T; Lee, Andrew K

2016-07-01

treatment time for the total target volumes exceeding 200 cm(3), which was the case for more than 80% of the patients in this study. When total treatment time was modeled as a function of the number of fields and total target volume, the model overestimated total treatment time by 12% on average, with a standard deviation of 32%. A sensitivity analysis of throughput capacity for a hypothetical four-room spot scanning proton therapy center identified several priority items for improvements in throughput capacity, including operation time, beam delivery time, and patient immobilization and setup time. The spot scanning port at our proton therapy center has operated at a high performance level and has been used to treat a large number of complex cases. Further improvements in efficiency may be feasible in the areas of facility operation, beam delivery, patient immobilization and setup, and optimization of treatment scheduling.

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

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

Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles

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

Pair-barcode high-throughput sequencing for large-scale multiplexed sample analysis

PubMed Central

2012-01-01

Background The multiplexing becomes the major limitation of the next-generation sequencing (NGS) in application to low complexity samples. Physical space segregation allows limited multiplexing, while the existing barcode approach only permits simultaneously analysis of up to several dozen samples. Results Here we introduce pair-barcode sequencing (PBS), an economic and flexible barcoding technique that permits parallel analysis of large-scale multiplexed samples. In two pilot runs using SOLiD sequencer (Applied Biosystems Inc.), 32 independent pair-barcoded miRNA libraries were simultaneously discovered by the combination of 4 unique forward barcodes and 8 unique reverse barcodes. Over 174,000,000 reads were generated and about 64% of them are assigned to both of the barcodes. After mapping all reads to pre-miRNAs in miRBase, different miRNA expression patterns are captured from the two clinical groups. The strong correlation using different barcode pairs and the high consistency of miRNA expression in two independent runs demonstrates that PBS approach is valid. Conclusions By employing PBS approach in NGS, large-scale multiplexed pooled samples could be practically analyzed in parallel so that high-throughput sequencing economically meets the requirements of samples which are low sequencing throughput demand. PMID:22276739

High-Throughput Quantitation of Proline Betaine in Foods and Suitability as a Valid Biomarker for Citrus Consumption.

PubMed

Lang, Roman; Lang, Tatjana; Bader, Matthias; Beusch, Anja; Schlagbauer, Verena; Hofmann, Thomas

2017-03-01

Proline betaine has been proposed as a candidate dietary biomarker for citrus intake. To validate its suitability as a dietary biomarker and to gain insight into the range of this per-methylated amino acid in foods and beverages, a quick and accurate stable isotope dilution assay was developed for quantitative high-throughput HILIC-MS/MS screening of proline betaine in foods and urine after solvent-mediated matrix precipitation. Quantitative analysis of a variety of foods confirmed substantial amounts of proline betaine in citrus juices (140-1100 mg/L) and revealed high abundance in tubers of the vegetable Stachys affinis, also known as Chinese artichocke (∼700 mg/kg). Seafood including clams, shrimp, and lobster contained limited amounts (1-95 mg/kg), whereas only traces were detected in fish, cuttlefish, fresh meat, dairy products, fresh vegetable (<3 mg/kg), coffee, tea, beer, and wine (<7 mg/L). The human excretion profiles of proline betaine in urine were comparable when common portions of orange juice or fried Stachys tubers were consumed. Neither mussels nor beer provided enough proline betaine to detect significant differences between morning urine samples collected before and after consumption. As Stachys is a rather rare vegetable and not part of peoples' daily diet, the data reported here will help to monitor the subject's compliance in future nutritional human studies on citrus products or the exclusion of citrus products in the wash-out phase of an intervention study. Moreover, proline betaine measurement can contribute to the establishment of a toolbox of valid dietary biomarkers reflecting wider aspects of diet to assess metabolic profiles as measures of dietary exposure and indicators of dietary patterns, dietary changes, or effectiveness of dietary interventions.

High-Throughput Quantification of SH2 Domain-Phosphopeptide Interactions with Cellulose-Peptide Conjugate Microarrays.

PubMed

Engelmann, Brett W

2017-01-01

The Src Homology 2 (SH2) domain family primarily recognizes phosphorylated tyrosine (pY) containing peptide motifs. The relative affinity preferences among competing SH2 domains for phosphopeptide ligands define "specificity space," and underpins many functional pY mediated interactions within signaling networks. The degree of promiscuity exhibited and the dynamic range of affinities supported by individual domains or phosphopeptides is best resolved by a carefully executed and controlled quantitative high-throughput experiment. Here, I describe the fabrication and application of a cellulose-peptide conjugate microarray (CPCMA) platform to the quantitative analysis of SH2 domain specificity space. Included herein are instructions for optimal experimental design with special attention paid to common sources of systematic error, phosphopeptide SPOT synthesis, microarray fabrication, analyte titrations, data capture, and analysis.

A high-throughput assay for DNA topoisomerases and other enzymes, based on DNA triplex formation.

PubMed

Burrell, Matthew R; Burton, Nicolas P; Maxwell, Anthony

2010-01-01

We have developed a rapid, high-throughput assay for measuring the catalytic activity (DNA supercoiling or relaxation) of topoisomerase enzymes that is also capable of monitoring the activity of other enzymes that alter the topology of DNA. The assay utilises intermolecular triplex formation to resolve supercoiled and relaxed forms of DNA, the principle being the greater efficiency of a negatively supercoiled plasmid to form an intermolecular triplex with an immobilised oligonucleotide than the relaxed form. The assay provides a number of advantages over the standard gel-based methods, including greater speed of analysis, reduced sample handling, better quantitation and improved reliability and accuracy of output data. The assay is performed in microtitre plates and can be adapted to high-throughput screening of libraries of potential inhibitors of topoisomerases including bacterial DNA gyrase.

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.

Next Generation MUT-MAP, a High-Sensitivity High-Throughput Microfluidics Chip-Based Mutation Analysis Panel

PubMed Central

Patel, Rajesh; Tsan, Alison; Sumiyoshi, Teiko; Fu, Ling; Desai, Rupal; Schoenbrunner, Nancy; Myers, Thomas W.; Bauer, Keith; Smith, Edward; Raja, Rajiv

2014-01-01

Molecular profiling of tumor tissue to detect alterations, such as oncogenic mutations, plays a vital role in determining treatment options in oncology. Hence, there is an increasing need for a robust and high-throughput technology to detect oncogenic hotspot mutations. Although commercial assays are available to detect genetic alterations in single genes, only a limited amount of tissue is often available from patients, requiring multiplexing to allow for simultaneous detection of mutations in many genes using low DNA input. Even though next-generation sequencing (NGS) platforms provide powerful tools for this purpose, they face challenges such as high cost, large DNA input requirement, complex data analysis, and long turnaround times, limiting their use in clinical settings. We report the development of the next generation mutation multi-analyte panel (MUT-MAP), a high-throughput microfluidic, panel for detecting 120 somatic mutations across eleven genes of therapeutic interest (AKT1, BRAF, EGFR, FGFR3, FLT3, HRAS, KIT, KRAS, MET, NRAS, and PIK3CA) using allele-specific PCR (AS-PCR) and Taqman technology. This mutation panel requires as little as 2 ng of high quality DNA from fresh frozen or 100 ng of DNA from formalin-fixed paraffin-embedded (FFPE) tissues. Mutation calls, including an automated data analysis process, have been implemented to run 88 samples per day. Validation of this platform using plasmids showed robust signal and low cross-reactivity in all of the newly added assays and mutation calls in cell line samples were found to be consistent with the Catalogue of Somatic Mutations in Cancer (COSMIC) database allowing for direct comparison of our platform to Sanger sequencing. High correlation with NGS when compared to the SuraSeq500 panel run on the Ion Torrent platform in a FFPE dilution experiment showed assay sensitivity down to 0.45%. This multiplexed mutation panel is a valuable tool for high-throughput biomarker discovery in personalized

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

Bifrost: a Modular Python/C++ Framework for Development of High-Throughput Data Analysis Pipelines

NASA Astrophysics Data System (ADS)

Cranmer, Miles; Barsdell, Benjamin R.; Price, Danny C.; Garsden, Hugh; Taylor, Gregory B.; Dowell, Jayce; Schinzel, Frank; Costa, Timothy; Greenhill, Lincoln J.

2017-01-01

Large radio interferometers have data rates that render long-term storage of raw correlator data infeasible, thus motivating development of real-time processing software. For high-throughput applications, processing pipelines are challenging to design and implement. Motivated by science efforts with the Long Wavelength Array, we have developed Bifrost, a novel Python/C++ framework that eases the development of high-throughput data analysis software by packaging algorithms as black box processes in a directed graph. This strategy to modularize code allows astronomers to create parallelism without code adjustment. Bifrost uses CPU/GPU ’circular memory’ data buffers that enable ready introduction of arbitrary functions into the processing path for ’streams’ of data, and allow pipelines to automatically reconfigure in response to astrophysical transient detection or input of new observing settings. We have deployed and tested Bifrost at the latest Long Wavelength Array station, in Sevilleta National Wildlife Refuge, NM, where it handles throughput exceeding 10 Gbps per CPU core.

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.

Gold-coated polydimethylsiloxane microwells for high-throughput electrochemiluminescence analysis of intracellular glucose at single cells.

PubMed

Xia, Juan; Zhou, Junyu; Zhang, Ronggui; Jiang, Dechen; Jiang, Depeng

2018-06-04

In this communication, a gold-coated polydimethylsiloxane (PDMS) chip with cell-sized microwells was prepared through a stamping and spraying process that was applied directly for high-throughput electrochemiluminescence (ECL) analysis of intracellular glucose at single cells. As compared with the previous multiple-step fabrication of photoresist-based microwells on the electrode, the preparation process is simple and offers fresh electrode surface for higher luminescence intensity. More luminescence intensity was recorded from cell-retained microwells than that at the planar region among the microwells that was correlated with the content of intracellular glucose. The successful monitoring of intracellular glucose at single cells using this PDMS chip will provide an alternative strategy for high-throughput single-cell analysis. Graphical abstract ᅟ.

Chipster: user-friendly analysis software for microarray and other high-throughput data

PubMed Central

2011-01-01

Background The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Results Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Conclusions Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available. PMID:21999641

ElectroTaxis-on-a-Chip (ETC): an integrated quantitative high-throughput screening platform for electrical field-directed cell migration.

PubMed

Zhao, Siwei; Zhu, Kan; Zhang, Yan; Zhu, Zijie; Xu, Zhengping; Zhao, Min; Pan, Tingrui

2014-11-21

Both endogenous and externally applied electrical stimulation can affect a wide range of cellular functions, including growth, migration, differentiation and division. Among those effects, the electrical field (EF)-directed cell migration, also known as electrotaxis, has received broad attention because it holds great potential in facilitating clinical wound healing. Electrotaxis experiment is conventionally conducted in centimetre-sized flow chambers built in Petri dishes. Despite the recent efforts to adapt microfluidics for electrotaxis studies, the current electrotaxis experimental setup is still cumbersome due to the needs of an external power supply and EF controlling/monitoring systems. There is also a lack of parallel experimental systems for high-throughput electrotaxis studies. In this paper, we present a first independently operable microfluidic platform for high-throughput electrotaxis studies, integrating all functional components for cell migration under EF stimulation (except microscopy) on a compact footprint (the same as a credit card), referred to as ElectroTaxis-on-a-Chip (ETC). Inspired by the R-2R resistor ladder topology in digital signal processing, we develop a systematic approach to design an infinitely expandable microfluidic generator of EF gradients for high-throughput and quantitative studies of EF-directed cell migration. Furthermore, a vacuum-assisted assembly method is utilized to allow direct and reversible attachment of our device to existing cell culture media on biological surfaces, which separates the cell culture and device preparation/fabrication steps. We have demonstrated that our ETC platform is capable of screening human cornea epithelial cell migration under the stimulation of an EF gradient spanning over three orders of magnitude. The screening results lead to the identification of the EF-sensitive range of that cell type, which can provide valuable guidance to the clinical application of EF-facilitated wound healing.

A high-throughput and quantitative method to assess the mutagenic potential of translesion DNA synthesis

PubMed Central

Taggart, David J.; Camerlengo, Terry L.; Harrison, Jason K.; Sherrer, Shanen M.; Kshetry, Ajay K.; Taylor, John-Stephen; Huang, Kun; Suo, Zucai

2013-01-01

Cellular genomes are constantly damaged by endogenous and exogenous agents that covalently and structurally modify DNA to produce DNA lesions. Although most lesions are mended by various DNA repair pathways in vivo, a significant number of damage sites persist during genomic replication. Our understanding of the mutagenic outcomes derived from these unrepaired DNA lesions has been hindered by the low throughput of existing sequencing methods. Therefore, we have developed a cost-effective high-throughput short oligonucleotide sequencing assay that uses next-generation DNA sequencing technology for the assessment of the mutagenic profiles of translesion DNA synthesis catalyzed by any error-prone DNA polymerase. The vast amount of sequencing data produced were aligned and quantified by using our novel software. As an example, the high-throughput short oligonucleotide sequencing assay was used to analyze the types and frequencies of mutations upstream, downstream and at a site-specifically placed cis–syn thymidine–thymidine dimer generated individually by three lesion-bypass human Y-family DNA polymerases. PMID:23470999

Quantitative High-Throughput Identification of Drugs as Modulators of Human Constitutive Androstane Receptor

PubMed Central

Lynch, Caitlin; Zhao, Jinghua; Huang, Ruili; Xiao, Jingwei; Li, Linhao; Heyward, Scott; Xia, Menghang; Wang, Hongbing

2015-01-01

The constitutive androstane receptor (CAR, NR1I3) plays a key role in governing the transcription of numerous hepatic genes that involve xenobiotic metabolism/clearance, energy homeostasis, and cell proliferation. Thus, identification of novel human CAR (hCAR) modulators may not only enhance early prediction of drug-drug interactions but also offer potentially novel therapeutics for diseases such as metabolic disorders and cancer. In this study, we have generated a double stable cell line expressing both hCAR and a CYP2B6-driven luciferase reporter for quantitative high-throughput screening (qHTS) of hCAR modulators. Approximately 2800 compounds from the NIH Chemical Genomics Center Pharmaceutical Collection were screened employing both the activation and deactivation modes of the qHTS. Activators (115) and deactivators (152) of hCAR were identified from the primary qHTS, among which 10 agonists and 10 antagonists were further validated in the physiologically relevant human primary hepatocytes for compound-mediated hCAR nuclear translocation and target gene expression. Collectively, our results reveal that hCAR modulators can be efficiently identified through this newly established qHTS assay. Profiling drug collections for hCAR activity would facilitate the prediction of metabolism-based drug-drug interactions, and may lead to the identification of potential novel therapeutics. PMID:25993555

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 Measurement of Extracellular DNA Release and Quantitative NET Formation in Human Neutrophils In Vitro.

PubMed

Sil, Payel; Yoo, Dae-Goon; Floyd, Madison; Gingerich, Aaron; Rada, Balazs

2016-06-18

Neutrophil granulocytes are the most abundant leukocytes in the human blood. Neutrophils are the first to arrive at the site of infection. Neutrophils developed several antimicrobial mechanisms including phagocytosis, degranulation and formation of neutrophil extracellular traps (NETs). NETs consist of a DNA scaffold decorated with histones and several granule markers including myeloperoxidase (MPO) and human neutrophil elastase (HNE). NET release is an active process involving characteristic morphological changes of neutrophils leading to expulsion of their DNA into the extracellular space. NETs are essential to fight microbes, but uncontrolled release of NETs has been associated with several disorders. To learn more about the clinical relevance and the mechanism of NET formation, there is a need to have reliable tools capable of NET quantitation. Here three methods are presented that can assess NET release from human neutrophils in vitro. The first one is a high throughput assay to measure extracellular DNA release from human neutrophils using a membrane impermeable DNA-binding dye. In addition, two other methods are described capable of quantitating NET formation by measuring levels of NET-specific MPO-DNA and HNE-DNA complexes. These microplate-based methods in combination provide great tools to efficiently study the mechanism and regulation of NET formation of human neutrophils.

Evaluation of Flow-Injection Tandem Mass Spectrometry for Rapid and High-Throughput Quantitative Determination of B-Vitamins in Nutritional Supplements

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

Bhandari, Deepak; Van Berkel, Gary J

2012-01-01

The use of flow-injection electrospray ionization tandem mass spectrometry for rapid and high-throughput mass spectral analysis of selected B-vitamins, viz. B1, B2, B3, B5, and B6, in nutritional formulations was demonstrated. A simple and rapid (~5 min) in-tube sample preparation was performed by adding extraction solvent to a powdered sample aliquot followed by agitation, centrifugation, and filtration to recover an extract for analysis. Automated flow injection introduced 1 L of the extracts directly into the mass spectrometer ion source without chromatographic separation. Sample-to-sample analysis time was 60 s representing significant improvement over conventional liquid chromatography approaches which typically require 25-45more » min, and often require more significant sample preparation procedures. Quantitative capabilities of the flow-injection analysis were tested using the method of standard additions and NIST standard reference material (SRM 3280) multivitamin/multielement tablets. The quantity determined for each B-vitamin in SRM 3280 was within the statistical range provided for the respective certified values. The same sample preparation and analysis approach was also applied to two different commercial vitamin supplement tablets and proved to be successful in the quantification of the selected B-vitamins as evidenced by an agreement with the labels values and the results obtained using isotope dilution liquid chromatography/mass spectrometry.« less

High-throughput gender identification of penguin species using melting curve analysis.

PubMed

Tseng, Chao-Neng; Chang, Yung-Ting; Chiu, Hui-Tzu; Chou, Yii-Cheng; Huang, Hurng-Wern; Cheng, Chien-Chung; Liao, Ming-Hui; Chang, Hsueh-Wei

2014-04-03

Most species of penguins are sexual monomorphic and therefore it is difficult to visually identify their genders for monitoring population stability in terms of sex ratio analysis. In this study, we evaluated the suitability using melting curve analysis (MCA) for high-throughput gender identification of penguins. Preliminary test indicated that the Griffiths's P2/P8 primers were not suitable for MCA analysis. Based on sequence alignment of Chromo-Helicase-DNA binding protein (CHD)-W and CHD-Z genes from four species of penguins (Pygoscelis papua, Aptenodytes patagonicus, Spheniscus magellanicus, and Eudyptes chrysocome), we redesigned forward primers for the CHD-W/CHD-Z-common region (PGU-ZW2) and the CHD-W-specific region (PGU-W2) to be used in combination with the reverse Griffiths's P2 primer. When tested with P. papua samples, PCR using P2/PGU-ZW2 and P2/PGU-W2 primer sets generated two amplicons of 148- and 356-bp, respectively, which were easily resolved in 1.5% agarose gels. MCA analysis indicated the melting temperature (Tm) values for P2/PGU-ZW2 and P2/PGU-W2 amplicons of P. papua samples were 79.75°C-80.5°C and 81.0°C-81.5°C, respectively. Females displayed both ZW-common and W-specific Tm peaks, whereas male was positive only for ZW-common peak. Taken together, our redesigned primers coupled with MCA analysis allows precise high throughput gender identification for P. papua, and potentially for other penguin species such as A. patagonicus, S. magellanicus, and E. chrysocome as well.

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).

Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

PubMed Central

Fujimori, Shigeo; Hirai, Naoya; Ohashi, Hiroyuki; Masuoka, Kazuyo; Nishikimi, Akihiko; Fukui, Yoshinori; Washio, Takanori; Oshikubo, Tomohiro; Yamashita, Tatsuhiro; Miyamoto-Sato, Etsuko

2012-01-01

Next-generation sequencing (NGS) has been applied to various kinds of omics studies, resulting in many biological and medical discoveries. However, high-throughput protein-protein interactome datasets derived from detection by sequencing are scarce, because protein-protein interaction analysis requires many cell manipulations to examine the interactions. The low reliability of the high-throughput data is also a problem. Here, we describe a cell-free display technology combined with NGS that can improve both the coverage and reliability of interactome datasets. The completely cell-free method gives a high-throughput and a large detection space, testing the interactions without using clones. The quantitative information provided by NGS reduces the number of false positives. The method is suitable for the in vitro detection of proteins that interact not only with the bait protein, but also with DNA, RNA and chemical compounds. Thus, it could become a universal approach for exploring the large space of protein sequences and interactome networks. PMID:23056904

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

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

Guo, Xuejiang; Tang, Keqi

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers wouldmore » ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM

The Microbiome and Metabolites in Fermented Pu-erh Tea as Revealed by High-Throughput Sequencing and Quantitative Multiplex Metabolite Analysis

PubMed Central

Sulyok, Michael; Liu, Xingzhong; Rao, Mingyong

2016-01-01

Pu-erh is a tea produced in Yunnan, China by microbial fermentation of fresh Camellia sinensis leaves by two processes, the traditional raw fermentation and the faster, ripened fermentation. We characterized fungal and bacterial communities in leaves and both Pu-erhs by high-throughput, rDNA-amplicon sequencing and we characterized the profile of bioactive extrolite mycotoxins in Pu-erh teas by quantitative liquid chromatography-tandem mass spectrometry. We identified 390 fungal and 629 bacterial OTUs from leaves and both Pu-erhs. Major findings are: 1) fungal diversity drops and bacterial diversity rises due to raw or ripened fermentation, 2) fungal and bacterial community composition changes significantly between fresh leaves and both raw and ripened Pu-erh, 3) aging causes significant changes in the microbial community of raw, but not ripened, Pu-erh, and, 4) ripened and well-aged raw Pu-erh have similar microbial communities that are distinct from those of young, raw Ph-erh tea. Twenty-five toxic metabolites, mainly of fungal origin, were detected, with patulin and asperglaucide dominating and at levels supporting the Chinese custom of discarding the first preparation of Pu-erh and using the wet tea to then brew a pot for consumption. PMID:27337135

A low cost and high throughput magnetic bead-based immuno-agglutination assay in confined droplets.

PubMed

Teste, Bruno; Ali-Cherif, Anaïs; Viovy, Jean Louis; Malaquin, Laurent

2013-06-21

Although passive immuno-agglutination assays consist of one step and simple procedures, they are usually not adapted for high throughput analyses and they require expensive and bulky equipment for quantitation steps. Here we demonstrate a low cost, multimodal and high throughput immuno-agglutination assay that relies on a combination of magnetic beads (MBs), droplets microfluidics and magnetic tweezers. Antibody coated MBs were used as a capture support in the homogeneous phase. Following the immune interaction, water in oil droplets containing MBs and analytes were generated and transported in Teflon tubing. When passing in between magnetic tweezers, the MBs contained in the droplets were magnetically confined in order to enhance the agglutination rate and kinetics. When releasing the magnetic field, the internal recirculation flows in the droplet induce shear forces that favor MBs redispersion. In the presence of the analyte, the system preserves specific interactions and MBs stay in the aggregated state while in the case of a non-specific analyte, redispersion of particles occurs. The analyte quantitation procedure relies on the MBs redispersion rate within the droplet. The influence of different parameters such as magnetic field intensity, flow rate and MBs concentration on the agglutination performances have been investigated and optimized. Although the immuno-agglutination assay described in this work may not compete with enzyme linked immunosorbent assay (ELISA) in terms of sensitivity, it offers major advantages regarding the reagents consumption (analysis is performed in sub microliter droplet) and the platform cost that yields to very cheap analyses. Moreover the fully automated analysis procedure provides reproducible analyses with throughput well above those of existing technologies. We demonstrated the detection of biotinylated phosphatase alkaline in 100 nL sample volumes with an analysis rate of 300 assays per hour and a limit of detection of 100 pM.

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

PubMed

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

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

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

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

PubMed Central

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

2015-01-01

Objective Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Methods Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. Results A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. Conclusion A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC. PMID:26487969

Bacterial Pathogens and Community Composition in Advanced Sewage Treatment Systems Revealed by Metagenomics Analysis Based on High-Throughput Sequencing

PubMed Central

Lu, Xin; Zhang, Xu-Xiang; Wang, Zhu; Huang, Kailong; Wang, Yuan; Liang, Weigang; Tan, Yunfei; Liu, Bo; Tang, Junying

2015-01-01

This study used 454 pyrosequencing, Illumina high-throughput sequencing and metagenomic analysis to investigate bacterial pathogens and their potential virulence in a sewage treatment plant (STP) applying both conventional and advanced treatment processes. Pyrosequencing and Illumina sequencing consistently demonstrated that Arcobacter genus occupied over 43.42% of total abundance of potential pathogens in the STP. At species level, potential pathogens Arcobacter butzleri, Aeromonas hydrophila and Klebsiella pneumonia dominated in raw sewage, which was also confirmed by quantitative real time PCR. Illumina sequencing also revealed prevalence of various types of pathogenicity islands and virulence proteins in the STP. Most of the potential pathogens and virulence factors were eliminated in the STP, and the removal efficiency mainly depended on oxidation ditch. Compared with sand filtration, magnetic resin seemed to have higher removals in most of the potential pathogens and virulence factors. However, presence of the residual A. butzleri in the final effluent still deserves more concerns. The findings indicate that sewage acts as an important source of environmental pathogens, but STPs can effectively control their spread in the environment. Joint use of the high-throughput sequencing technologies is considered a reliable method for deep and comprehensive overview of environmental bacterial virulence. PMID:25938416

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

PubMed

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

2013-08-06

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

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

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.

'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

Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays

EPA Science Inventory

High-throughput metabolomic assays that allow simultaneous targeted screening of hundreds of metabolites have recently become available in kit form. Such assays provide a window into understanding changes to biochemical pathways due to chemical exposure or disease, and are usefu...

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping1[C][W][OPEN

PubMed Central

Klukas, Christian; Chen, Dijun; Pape, Jean-Michel

2014-01-01

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable. PMID:24760818

High-coverage quantitative proteomics using amine-specific isotopic labeling.

PubMed

Melanson, Jeremy E; Avery, Steven L; Pinto, Devanand M

2006-08-01

Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.

Recent developments in software tools for high-throughput in vitro ADME support with high-resolution MS.

PubMed

Paiva, Anthony; Shou, Wilson Z

2016-08-01

The last several years have seen the rapid adoption of the high-resolution MS (HRMS) for bioanalytical support of high throughput in vitro ADME profiling. Many capable software tools have been developed and refined to process quantitative HRMS bioanalysis data for ADME samples with excellent performance. Additionally, new software applications specifically designed for quan/qual soft spot identification workflows using HRMS have greatly enhanced the quality and efficiency of the structure elucidation process for high throughput metabolite ID in early in vitro ADME profiling. Finally, novel approaches in data acquisition and compression, as well as tools for transferring, archiving and retrieving HRMS data, are being continuously refined to tackle the issue of large data file size typical for HRMS analyses.

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

A high-throughput pipeline for the production of synthetic antibodies for analysis of ribonucleoprotein complexes

PubMed Central

Na, Hong; Laver, John D.; Jeon, Jouhyun; Singh, Fateh; Ancevicius, Kristin; Fan, Yujie; Cao, Wen Xi; Nie, Kun; Yang, Zhenglin; Luo, Hua; Wang, Miranda; Rissland, Olivia; Westwood, J. Timothy; Kim, Philip M.; Smibert, Craig A.; Lipshitz, Howard D.; Sidhu, Sachdev S.

2016-01-01

Post-transcriptional regulation of mRNAs plays an essential role in the control of gene expression. mRNAs are regulated in ribonucleoprotein (RNP) complexes by RNA-binding proteins (RBPs) along with associated protein and noncoding RNA (ncRNA) cofactors. A global understanding of post-transcriptional control in any cell type requires identification of the components of all of its RNP complexes. We have previously shown that these complexes can be purified by immunoprecipitation using anti-RBP synthetic antibodies produced by phage display. To develop the large number of synthetic antibodies required for a global analysis of RNP complex composition, we have established a pipeline that combines (i) a computationally aided strategy for design of antigens located outside of annotated domains, (ii) high-throughput antigen expression and purification in Escherichia coli, and (iii) high-throughput antibody selection and screening. Using this pipeline, we have produced 279 antibodies against 61 different protein components of Drosophila melanogaster RNPs. Together with those produced in our low-throughput efforts, we have a panel of 311 antibodies for 67 RNP complex proteins. Tests of a subset of our antibodies demonstrated that 89% immunoprecipitate their endogenous target from embryo lysate. This panel of antibodies will serve as a resource for global studies of RNP complexes in Drosophila. Furthermore, our high-throughput pipeline permits efficient production of synthetic antibodies against any large set of proteins. PMID:26847261

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.

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.

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.

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

Three classes of glucocerebrosidase inhibitors identified by quantitative high-throughput screening are chaperone leads for Gaucher disease

PubMed Central

Zheng, Wei; Padia, Janak; Urban, Daniel J.; Jadhav, Ajit; Goker-Alpan, Ozlem; Simeonov, Anton; Goldin, Ehud; Auld, Douglas; LaMarca, Mary E.; Inglese, James; Austin, Christopher P.; Sidransky, Ellen

2007-01-01

Gaucher disease is an autosomal recessive lysosomal storage disorder caused by mutations in the glucocerebrosidase gene. Missense mutations result in reduced enzyme activity that may be due to misfolding, raising the possibility of small-molecule chaperone correction of the defect. Screening large compound libraries by quantitative high-throughput screening (qHTS) provides comprehensive information on the potency, efficacy, and structure–activity relationships (SAR) of active compounds directly from the primary screen, facilitating identification of leads for medicinal chemistry optimization. We used qHTS to rapidly identify three structural series of potent, selective, nonsugar glucocerebrosidase inhibitors. The three structural classes had excellent potencies and efficacies and, importantly, high selectivity against closely related hydrolases. Preliminary SAR data were used to select compounds with high activity in both enzyme and cell-based assays. Compounds from two of these structural series increased N370S mutant glucocerebrosidase activity by 40–90% in patient cell lines and enhanced lysosomal colocalization, indicating chaperone activity. These small molecules have potential as leads for chaperone therapy for Gaucher disease, and this paradigm promises to accelerate the development of leads for other rare genetic disorders. PMID:17670938

High throughput computing: a solution for scientific analysis

USGS Publications Warehouse

O'Donnell, M.

2011-01-01

handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses High Throughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

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

Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.

PubMed

Kebschull, Moritz; Fittler, Melanie Julia; Demmer, Ryan T; Papapanou, Panos N

2017-01-01

Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.

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.

A High-throughput Assay for mRNA Silencing in Primary Cortical Neurons in vitro with Oligonucleotide Therapeutics.

PubMed

Alterman, Julia F; Coles, Andrew H; Hall, Lauren M; Aronin, Neil; Khvorova, Anastasia; Didiot, Marie-Cécile

2017-08-20

Primary neurons represent an ideal cellular system for the identification of therapeutic oligonucleotides for the treatment of neurodegenerative diseases. However, due to the sensitive nature of primary cells, the transfection of small interfering RNAs (siRNA) using classical methods is laborious and often shows low efficiency. Recent progress in oligonucleotide chemistry has enabled the development of stabilized and hydrophobically modified small interfering RNAs (hsiRNAs). This new class of oligonucleotide therapeutics shows extremely efficient self-delivery properties and supports potent and durable effects in vitro and in vivo . We have developed a high-throughput in vitro assay to identify and test hsiRNAs in primary neuronal cultures. To simply, rapidly, and accurately quantify the mRNA silencing of hundreds of hsiRNAs, we use the QuantiGene 2.0 quantitative gene expression assay. This high-throughput, 96-well plate-based assay can quantify mRNA levels directly from sample lysate. Here, we describe a method to prepare short-term cultures of mouse primary cortical neurons in a 96-well plate format for high-throughput testing of oligonucleotide therapeutics. This method supports the testing of hsiRNA libraries and the identification of potential therapeutics within just two weeks. We detail methodologies of our high throughput assay workflow from primary neuron preparation to data analysis. This method can help identify oligonucleotide therapeutics for treatment of various neurological diseases.

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

PubMed

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

2016-01-01

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

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

PubMed

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Analysis of high-throughput screening reveals the effect of surface topographies on cellular morphology.

PubMed

Hulsman, Marc; Hulshof, Frits; Unadkat, Hemant; Papenburg, Bernke J; Stamatialis, Dimitrios F; Truckenmüller, Roman; van Blitterswijk, Clemens; de Boer, Jan; Reinders, Marcel J T

2015-03-01

Surface topographies of materials considerably impact cellular behavior as they have been shown to affect cell growth, provide cell guidance, and even induce cell differentiation. Consequently, for successful application in tissue engineering, the contact interface of biomaterials needs to be optimized to induce the required cell behavior. However, a rational design of biomaterial surfaces is severely hampered because knowledge is lacking on the underlying biological mechanisms. Therefore, we previously developed a high-throughput screening device (TopoChip) that measures cell responses to large libraries of parameterized topographical material surfaces. Here, we introduce a computational analysis of high-throughput materiome data to capture the relationship between the surface topographies of materials and cellular morphology. We apply robust statistical techniques to find surface topographies that best promote a certain specified cellular response. By augmenting surface screening with data-driven modeling, we determine which properties of the surface topographies influence the morphological properties of the cells. With this information, we build models that predict the cellular response to surface topographies that have not yet been measured. We analyze cellular morphology on 2176 surfaces, and find that the surface topography significantly affects various cellular properties, including the roundness and size of the nucleus, as well as the perimeter and orientation of the cells. Our learned models capture and accurately predict these relationships and reveal a spectrum of topographies that induce various levels of cellular morphologies. Taken together, this novel approach of high-throughput screening of materials and subsequent analysis opens up possibilities for a rational design of biomaterial surfaces. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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.

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

PubMed

Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

2017-08-01

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

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 Assay Optimization and Statistical Interpolation of Rubella-Specific Neutralizing Antibody Titers

PubMed Central

Lambert, Nathaniel D.; Pankratz, V. Shane; Larrabee, Beth R.; Ogee-Nwankwo, Adaeze; Chen, Min-hsin; Icenogle, Joseph P.

2014-01-01

Rubella remains a social and economic burden due to the high incidence of congenital rubella syndrome (CRS) in some countries. For this reason, an accurate and efficient high-throughput measure of antibody response to vaccination is an important tool. In order to measure rubella-specific neutralizing antibodies in a large cohort of vaccinated individuals, a high-throughput immunocolorimetric system was developed. Statistical interpolation models were applied to the resulting titers to refine quantitative estimates of neutralizing antibody titers relative to the assayed neutralizing antibody dilutions. This assay, including the statistical methods developed, can be used to assess the neutralizing humoral immune response to rubella virus and may be adaptable for assessing the response to other viral vaccines and infectious agents. PMID:24391140

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

A systematic study of mitochondrial toxicity of environmental chemicals using quantitative high throughput screening

PubMed Central

Attene-Ramos, Matias S.; Huang, Ruili; Sakamuru, Srilatha; Witt, Kristine L.; Beeson, Gyda C.; Shou, Louie; Schnellmann, Rick G.; Beeson, Craig C.; Tice, Raymond R.; Austin, Christopher P.; Xia, Menghang

2014-01-01

A goal of the Tox21 program is to transit toxicity testing from traditional in vivo models to in vitro assays that assess how chemicals affect cellular responses and toxicity pathways. A critical contribution of the NIH Chemical Genomics center (NCGC) to the Tox21 program is the implementation of a quantitative high throughput screening (qHTS) approach, using cell- and biochemical-based assays to generate toxicological profiles for thousands of environmental compounds. Here, we evaluated the effect of chemical compounds on mitochondrial membrane potential in HepG2 cells by screening a library of 1,408 compounds provided by the National Toxicology Program (NTP) in a qHTS platform. Compounds were screened over 14 concentrations, and results showed that 91 and 88 compounds disrupted mitochondrial membrane potential after treatment for one or five h, respectively. Seventy-six compounds active at both time points were clustered by structural similarity, producing 11 clusters and 23 singletons. Thirty-eight compounds covering most of the active chemical space were more extensively evaluated. Thirty-six of the 38 compounds were confirmed to disrupt mitochondrial membrane potential using a fluorescence plate reader and 35 were confirmed using a high content imaging approach. Among the 38 compounds, 4 and 6 induced LDH release, a measure of cytotoxicity, at 1 or 5 h, respectively. Compounds were further assessed for mechanism of action (MOA) by measuring changes in oxygen consumption rate, which enabled identification of 20 compounds as uncouplers. This comprehensive approach allows for evaluation of thousands of environmental chemicals for mitochondrial toxicity and identification of possible MOAs. PMID:23895456

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.

Quantitative High-Throughput Screen Identifies Inhibitors of the Schistosoma mansoni Redox Cascade

PubMed Central

Simeonov, Anton; Jadhav, Ajit; Sayed, Ahmed A.; Wang, Yuhong; Nelson, Michael E.; Thomas, Craig J.; Inglese, James; Williams, David L.; Austin, Christopher P.

2008-01-01

Schistosomiasis is a tropical disease associated with high morbidity and mortality, currently affecting over 200 million people worldwide. Praziquantel is the only drug used to treat the disease, and with its increased use the probability of developing drug resistance has grown significantly. The Schistosoma parasites can survive for up to decades in the human host due in part to a unique set of antioxidant enzymes that continuously degrade the reactive oxygen species produced by the host's innate immune response. Two principal components of this defense system have been recently identified in S. mansoni as thioredoxin/glutathione reductase (TGR) and peroxiredoxin (Prx) and as such these enzymes present attractive new targets for anti-schistosomiasis drug development. Inhibition of TGR/Prx activity was screened in a dual-enzyme format with reducing equivalents being transferred from NADPH to glutathione via a TGR-catalyzed reaction and then to hydrogen peroxide via a Prx-catalyzed step. A fully automated quantitative high-throughput (qHTS) experiment was performed against a collection of 71,028 compounds tested as 7- to 15-point concentration series at 5 µL reaction volume in 1536-well plate format. In order to generate a robust data set and to minimize the effect of compound autofluorescence, apparent reaction rates derived from a kinetic read were utilized instead of end-point measurements. Actives identified from the screen, along with previously untested analogues, were subjected to confirmatory experiments using the screening assay and subsequently against the individual targets in secondary assays. Several novel active series were identified which inhibited TGR at a range of potencies, with IC50s ranging from micromolar to the assay response limit (∼25 nM). This is, to our knowledge, the first report of a large-scale HTS to identify lead compounds for a helminthic disease, and provides a paradigm that can be used to jump-start development of novel

A high-throughput three-dimensional cell migration assay for toxicity screening with mobile device-based macroscopic image analysis

PubMed Central

Timm, David M.; Chen, Jianbo; Sing, David; Gage, Jacob A.; Haisler, William L.; Neeley, Shane K.; Raphael, Robert M.; Dehghani, Mehdi; Rosenblatt, Kevin P.; Killian, T. C.; Tseng, Hubert; Souza, Glauco R.

2013-01-01

There is a growing demand for in vitro assays for toxicity screening in three-dimensional (3D) environments. In this study, 3D cell culture using magnetic levitation was used to create an assay in which cells were patterned into 3D rings that close over time. The rate of closure was determined from time-lapse images taken with a mobile device and related to drug concentration. Rings of human embryonic kidney cells (HEK293) and tracheal smooth muscle cells (SMCs) were tested with ibuprofen and sodium dodecyl sulfate (SDS). Ring closure correlated with the viability and migration of cells in two dimensions (2D). Images taken using a mobile device were similar in analysis to images taken with a microscope. Ring closure may serve as a promising label-free and quantitative assay for high-throughput in vivo toxicity in 3D cultures. PMID:24141454

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Database-Centric Method for Automated High-Throughput Deconvolution and Analysis of Kinetic Antibody Screening Data.

PubMed

Nobrega, R Paul; Brown, Michael; Williams, Cody; Sumner, Chris; Estep, Patricia; Caffry, Isabelle; Yu, Yao; Lynaugh, Heather; Burnina, Irina; Lilov, Asparouh; Desroches, Jordan; Bukowski, John; Sun, Tingwan; Belk, Jonathan P; Johnson, Kirt; Xu, Yingda

2017-10-01

The state-of-the-art industrial drug discovery approach is the empirical interrogation of a library of drug candidates against a target molecule. The advantage of high-throughput kinetic measurements over equilibrium assessments is the ability to measure each of the kinetic components of binding affinity. Although high-throughput capabilities have improved with advances in instrument hardware, three bottlenecks in data processing remain: (1) intrinsic molecular properties that lead to poor biophysical quality in vitro are not accounted for in commercially available analysis models, (2) processing data through a user interface is time-consuming and not amenable to parallelized data collection, and (3) a commercial solution that includes historical kinetic data in the analysis of kinetic competition data does not exist. Herein, we describe a generally applicable method for the automated analysis, storage, and retrieval of kinetic binding data. This analysis can deconvolve poor quality data on-the-fly and store and organize historical data in a queryable format for use in future analyses. Such database-centric strategies afford greater insight into the molecular mechanisms of kinetic competition, allowing for the rapid identification of allosteric effectors and the presentation of kinetic competition data in absolute terms of percent bound to antigen on the biosensor.

[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 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

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

PubMed Central

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

2011-01-01

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

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.

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.

Novel method for high-throughput colony PCR screening in nanoliter-reactors

PubMed Central

Walser, Marcel; Pellaux, Rene; Meyer, Andreas; Bechtold, Matthias; Vanderschuren, Herve; Reinhardt, Richard; Magyar, Joseph; Panke, Sven; Held, Martin

2009-01-01

We introduce a technology for the rapid identification and sequencing of conserved DNA elements employing a novel suspension array based on nanoliter (nl)-reactors made from alginate. The reactors have a volume of 35 nl and serve as reaction compartments during monoseptic growth of microbial library clones, colony lysis, thermocycling and screening for sequence motifs via semi-quantitative fluorescence analyses. nl-Reactors were kept in suspension during all high-throughput steps which allowed performing the protocol in a highly space-effective fashion and at negligible expenses of consumables and reagents. As a first application, 11 high-quality microsatellites for polymorphism studies in cassava were isolated and sequenced out of a library of 20 000 clones in 2 days. The technology is widely scalable and we envision that throughputs for nl-reactor based screenings can be increased up to 100 000 and more samples per day thereby efficiently complementing protocols based on established deep-sequencing technologies. PMID:19282448

Multivariate Analysis of High Through-Put Adhesively Bonded Single Lap Joints: Experimental and Workflow Protocols

DTIC Science & Technology

2016-06-01

unlimited. v List of Tables Table 1 Single-lap-joint experimental parameters ..............................................7 Table 2 Survey ...Joints: Experimental and Workflow Protocols by Robert E Jensen, Daniel C DeSchepper, and David P Flanagan Approved for...TR-7696 ● JUNE 2016 US Army Research Laboratory Multivariate Analysis of High Through-Put Adhesively Bonded Single Lap Joints: Experimental

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

High-throughput SNP-genotyping analysis of the relationships among Ponto-Caspian sturgeon species

PubMed Central

Rastorguev, Sergey M; Nedoluzhko, Artem V; Mazur, Alexander M; Gruzdeva, Natalia M; Volkov, Alexander A; Barmintseva, Anna E; Mugue, Nikolai S; Prokhortchouk, Egor B

2013-01-01

Abstract Legally certified sturgeon fisheries require population protection and conservation methods, including DNA tests to identify the source of valuable sturgeon roe. However, the available genetic data are insufficient to distinguish between different sturgeon populations, and are even unable to distinguish between some species. We performed high-throughput single-nucleotide polymorphism (SNP)-genotyping analysis on different populations of Russian (Acipenser gueldenstaedtii), Persian (A. persicus), and Siberian (A. baerii) sturgeon species from the Caspian Sea region (Volga and Ural Rivers), the Azov Sea, and two Siberian rivers. We found that Russian sturgeons from the Volga and Ural Rivers were essentially indistinguishable, but they differed from Russian sturgeons in the Azov Sea, and from Persian and Siberian sturgeons. We identified eight SNPs that were sufficient to distinguish these sturgeon populations with 80% confidence, and allowed the development of markers to distinguish sturgeon species. Finally, on the basis of our SNP data, we propose that the A. baerii-like mitochondrial DNA found in some Russian sturgeons from the Caspian Sea arose via an introgression event during the Pleistocene glaciation. In the present study, the high-throughput genotyping analysis of several sturgeon populations was performed. SNP markers for species identification were defined. The possible explanation of the baerii-like mitotype presence in some Russian sturgeons in the Caspian Sea was suggested. PMID:24567827

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)-A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes.

PubMed

Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare . However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop

Adaptation of a Simple Microfluidic Platform for High-Dimensional Quantitative Morphological Analysis of Human Mesenchymal Stromal Cells on Polystyrene-Based Substrates.

PubMed

Lam, Johnny; Marklein, Ross A; Jimenez-Torres, Jose A; Beebe, David J; Bauer, Steven R; Sung, Kyung E

2017-12-01

Multipotent stromal cells (MSCs, often called mesenchymal stem cells) have garnered significant attention within the field of regenerative medicine because of their purported ability to differentiate down musculoskeletal lineages. Given the inherent heterogeneity of MSC populations, recent studies have suggested that cell morphology may be indicative of MSC differentiation potential. Toward improving current methods and developing simple yet effective approaches for the morphological evaluation of MSCs, we combined passive pumping microfluidic technology with high-dimensional morphological characterization to produce robust tools for standardized high-throughput analysis. Using ultraviolet (UV) light as a modality for reproducible polystyrene substrate modification, we show that MSCs seeded on microfluidic straight channel devices incorporating UV-exposed substrates exhibited morphological changes that responded accordingly to the degree of substrate modification. Substrate modification also effected greater morphological changes in MSCs seeded at a lower rather than higher density within microfluidic channels. Despite largely comparable trends in morphology, MSCs seeded in microscale as opposed to traditional macroscale platforms displayed much higher sensitivity to changes in substrate properties. In summary, we adapted and qualified microfluidic cell culture platforms comprising simple straight channel arrays as a viable and robust tool for high-throughput quantitative morphological analysis to study cell-material interactions.

Using adverse outcome pathway analysis to guide development of high-throughput screening assays for thyroid-disruptors

EPA Science Inventory

Using Adverse Outcome Pathway Analysis to Guide Development of High-Throughput Screening Assays for Thyroid-Disruptors Katie B. Paul1,2, Joan M. Hedge2, Daniel M. Rotroff4, Kevin M. Crofton4, Michael W. Hornung3, Steven O. Simmons2 1Oak Ridge Institute for Science Education Post...

High-throughput genotoxicity assay identifies antioxidants as inducers of DNA damage response and cell death

EPA Science Inventory

Human ATAD5 is an excellent biomarker for identifying genotoxic compounds because ATADS protein levels increase post-transcriptionally following exposure to a variety of DNA damaging agents. Here we report a novel quantitative high-throughput ATAD5-Iuciferase assay that can moni...

Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing.

PubMed

Jankowsky, Eckhard; Harris, Michael E

2017-04-15

To function in a biological setting, RNA binding proteins (RBPs) have to discriminate between alternative binding sites in RNAs. This discrimination can occur in the ground state of an RNA-protein binding reaction, in its transition state, or in both. The extent by which RBPs discriminate at these reaction states defines RBP specificity landscapes. Here, we describe the HiTS-Kin and HiTS-EQ techniques, which combine kinetic and equilibrium binding experiments with high throughput sequencing to quantitatively assess substrate discrimination for large numbers of substrate variants at ground and transition states of RNA-protein binding reactions. We discuss experimental design, practical considerations and data analysis and outline how a combination of HiTS-Kin and HiTS-EQ allows the mapping of RBP specificity landscapes. Copyright © 2017 Elsevier Inc. All rights reserved.

Maximizing the quantitative accuracy and reproducibility of Förster resonance energy transfer measurement for screening by high throughput widefield microscopy

PubMed Central

Schaufele, Fred

2013-01-01

Förster resonance energy transfer (FRET) between fluorescent proteins (FPs) provides insights into the proximities and orientations of FPs as surrogates of the biochemical interactions and structures of the factors to which the FPs are genetically fused. As powerful as FRET methods are, technical issues have impeded their broad adoption in the biologic sciences. One hurdle to accurate and reproducible FRET microscopy measurement stems from variable fluorescence backgrounds both within a field and between different fields. Those variations introduce errors into the precise quantification of fluorescence levels on which the quantitative accuracy of FRET measurement is highly dependent. This measurement error is particularly problematic for screening campaigns since minimal well-to-well variation is necessary to faithfully identify wells with altered values. High content screening depends also upon maximizing the numbers of cells imaged, which is best achieved by low magnification high throughput microscopy. But, low magnification introduces flat-field correction issues that degrade the accuracy of background correction to cause poor reproducibility in FRET measurement. For live cell imaging, fluorescence of cell culture media in the fluorescence collection channels for the FPs commonly used for FRET analysis is a high source of background error. These signal-to-noise problems are compounded by the desire to express proteins at biologically meaningful levels that may only be marginally above the strong fluorescence background. Here, techniques are presented that correct for background fluctuations. Accurate calculation of FRET is realized even from images in which a non-flat background is 10-fold higher than the signal. PMID:23927839

Development of New Sensing Materials Using Combinatorial and High-Throughput Experimentation

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Mirsky, Vladimir M.

New sensors with improved performance characteristics are needed for applications as diverse as bedside continuous monitoring, tracking of environmental pollutants, monitoring of food and water quality, monitoring of chemical processes, and safety in industrial, consumer, and automotive settings. Typical requirements in sensor improvement are selectivity, long-term stability, sensitivity, response time, reversibility, and reproducibility. Design of new sensing materials is the important cornerstone in the effort to develop new sensors. Often, sensing materials are too complex to predict their performance quantitatively in the design stage. Thus, combinatorial and high-throughput experimentation methodologies provide an opportunity to generate new required data to discover new sensing materials and/or to optimize existing material compositions. The goal of this chapter is to provide an overview of the key concepts of experimental development of sensing materials using combinatorial and high-throughput experimentation tools, and to promote additional fruitful interactions between computational scientists and experimentalists.

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.

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

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...

High-Throughput Particle Uptake Analysis by Imaging Flow Cytometry

PubMed Central

Smirnov, Asya; Solga, Michael D.; Lannigan, Joanne; Criss, Alison K.

2017-01-01

Quantifying the efficiency of particle uptake by host cells is important in fields including infectious diseases, autoimmunity, cancer, developmental biology, and drug delivery. Here we present a protocol for high-throughput analysis of particle uptake using imaging flow cytometry, using the bacterium Neisseria gonorrhoeae attached and internalized to neutrophils as an example. Cells are exposed to fluorescently labeled bacteria, fixed, and stained with a bacteria-specific antibody of a different fluorophore. Thus in the absence of a permeabilizing agent, extracellular bacteria are double-labeled with two fluorophores while intracellular bacteria remain single-labeled. A spot count algorithm is used to determine the number of single- and double-labeled bacteria in individual cells, to calculate the percent of cells associated with bacteria, percent of cells with internalized bacteria, and percent of cell-associated bacteria that are internalized. These analyses quantify bacterial association and internalization across thousands of cells and can be applied to diverse experimental systems. PMID:28369762

High-throughput microcoil NMR of compound libraries using zero-dispersion segmented flow analysis.

PubMed

Kautz, Roger A; Goetzinger, Wolfgang K; Karger, Barry L

2005-01-01

An automated system for loading samples into a microcoil NMR probe has been developed using segmented flow analysis. This approach enhanced 2-fold the throughput of the published direct injection and flow injection methods, improved sample utilization 3-fold, and was applicable to high-field NMR facilities with long transfer lines between the sample handler and NMR magnet. Sample volumes of 2 microL (10-30 mM, approximately 10 microg) were drawn from a 96-well microtiter plate by a sample handler, then pumped to a 0.5-microL microcoil NMR probe as a queue of closely spaced "plugs" separated by an immiscible fluorocarbon fluid. Individual sample plugs were detected by their NMR signal and automatically positioned for stopped-flow data acquisition. The sample in the NMR coil could be changed within 35 s by advancing the queue. The fluorocarbon liquid wetted the wall of the Teflon transfer line, preventing the DMSO samples from contacting the capillary wall and thus reducing sample losses to below 5% after passage through the 3-m transfer line. With a wash plug of solvent between samples, sample-to-sample carryover was <1%. Significantly, the samples did not disperse into the carrier liquid during loading or during acquisitions of several days for trace analysis. For automated high-throughput analysis using a 16-second acquisition time, spectra were recorded at a rate of 1.5 min/sample and total deuterated solvent consumption was <0.5 mL (1 US dollar) per 96-well plate.

QUANTITATIVE MASS SPECTROMETRIC ANALYSIS OF GLYCOPROTEINS COMBINED WITH ENRICHMENT METHODS

PubMed Central

Ahn, Yeong Hee; Kim, Jin Young; Yoo, Jong Shin

2015-01-01

Mass spectrometry (MS) has been a core technology for high sensitive and high-throughput analysis of the enriched glycoproteome in aspects of quantitative assays as well as qualitative profiling of glycoproteins. Because it has been widely recognized that aberrant glycosylation in a glycoprotein may involve in progression of a certain disease, the development of efficient analysis tool for the aberrant glycoproteins is very important for deep understanding about pathological function of the glycoprotein and new biomarker development. This review first describes the protein glycosylation-targeting enrichment technologies mainly employing solid-phase extraction methods such as hydrizide-capturing, lectin-specific capturing, and affinity separation techniques based on porous graphitized carbon, hydrophilic interaction chromatography, or immobilized boronic acid. Second, MS-based quantitative analysis strategies coupled with the protein glycosylation-targeting enrichment technologies, by using a label-free MS, stable isotope-labeling, or targeted multiple reaction monitoring (MRM) MS, are summarized with recent published studies. © 2014 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc. Rapid Commun. Mass Spec Rev 34:148–165, 2015. PMID:24889823

A high throughput screen for biomining cellulase activity from metagenomic libraries.

PubMed

Mewis, Keith; Taupp, Marcus; Hallam, Steven J

2011-02-01

Cellulose, the most abundant source of organic carbon on the planet, has wide-ranging industrial applications with increasing emphasis on biofuel production (1). Chemical methods to modify or degrade cellulose typically require strong acids and high temperatures. As such, enzymatic methods have become prominent in the bioconversion process. While the identification of active cellulases from bacterial and fungal isolates has been somewhat effective, the vast majority of microbes in nature resist laboratory cultivation. Environmental genomic, also known as metagenomic, screening approaches have great promise in bridging the cultivation gap in the search for novel bioconversion enzymes. Metagenomic screening approaches have successfully recovered novel cellulases from environments as varied as soils (2), buffalo rumen (3) and the termite hind-gut (4) using carboxymethylcellulose (CMC) agar plates stained with congo red dye (based on the method of Teather and Wood (5)). However, the CMC method is limited in throughput, is not quantitative and manifests a low signal to noise ratio (6). Other methods have been reported (7,8) but each use an agar plate-based assay, which is undesirable for high-throughput screening of large insert genomic libraries. Here we present a solution-based screen for cellulase activity using a chromogenic dinitrophenol (DNP)-cellobioside substrate (9). Our library was cloned into the pCC1 copy control fosmid to increase assay sensitivity through copy number induction (10). The method uses one-pot chemistry in 384-well microplates with the final readout provided as an absorbance measurement. This readout is quantitative, sensitive and automated with a throughput of up to 100X 384-well plates per day using a liquid handler and plate reader with attached stacking system.

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.

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 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

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

PubMed Central

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

2015-01-01

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

Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)—A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes

PubMed Central

Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop

HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

PubMed

David, Fabrice P A; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

2014-01-01

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

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.

Micro-patterned agarose gel devices for single-cell high-throughput microscopy of E. coli cells.

PubMed

Priest, David G; Tanaka, Nobuyuki; Tanaka, Yo; Taniguchi, Yuichi

2017-12-21

High-throughput microscopy of bacterial cells elucidated fundamental cellular processes including cellular heterogeneity and cell division homeostasis. Polydimethylsiloxane (PDMS)-based microfluidic devices provide advantages including precise positioning of cells and throughput, however device fabrication is time-consuming and requires specialised skills. Agarose pads are a popular alternative, however cells often clump together, which hinders single cell quantitation. Here, we imprint agarose pads with micro-patterned 'capsules', to trap individual cells and 'lines', to direct cellular growth outwards in a straight line. We implement this micro-patterning into multi-pad devices called CapsuleHotel and LineHotel for high-throughput imaging. CapsuleHotel provides ~65,000 capsule structures per mm 2 that isolate individual Escherichia coli cells. In contrast, LineHotel provides ~300 line structures per mm that direct growth of micro-colonies. With CapsuleHotel, a quantitative single cell dataset of ~10,000 cells across 24 samples can be acquired and analysed in under 1 hour. LineHotel allows tracking growth of > 10 micro-colonies across 24 samples simultaneously for up to 4 generations. These easy-to-use devices can be provided in kit format, and will accelerate discoveries in diverse fields ranging from microbiology to systems and synthetic biology.

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

Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization

PubMed Central

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

2015-01-01

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

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

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.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review.

PubMed

Wu, Qi; Yuan, Huiming; Zhang, Lihua; Zhang, Yukui

2012-06-20

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes. Copyright © 2012 Elsevier B.V. All rights reserved.

High-throughput quantitation of amino acids in rat and mouse biological matrices using stable isotope labeling and UPLC-MS/MS analysis.

PubMed

Takach, Edward; O'Shea, Thomas; Liu, Hanlan

2014-08-01

Quantifying amino acids in biological matrices is typically performed using liquid chromatography (LC) coupled with fluorescent detection (FLD), requiring both derivatization and complete baseline separation of all amino acids. Due to its high specificity and sensitivity, the use of UPLC-MS/MS eliminates the derivatization step and allows for overlapping amino acid retention times thereby shortening the analysis time. Furthermore, combining UPLC-MS/MS with stable isotope labeling (e.g., isobaric tag for relative and absolute quantitation, i.e., iTRAQ) of amino acids enables quantitation while maintaining sensitivity, selectivity and speed of analysis. In this study, we report combining UPLC-MS/MS analysis with iTRAQ labeling of amino acids resulting in the elution and quantitation of 44 amino acids within 5 min demonstrating the speed and convenience of this assay over established approaches. This chromatographic analysis time represented a 5-fold improvement over the conventional HPLC-MS/MS method developed in our laboratory. In addition, the UPLC-MS/MS method demonstrated improvements in both specificity and sensitivity without loss of precision. In comparing UPLC-MS/MS and HPLC-MS/MS results of 32 detected amino acids, only 2 amino acids exhibited imprecision (RSD) >15% using UPLC-MS/MS, while 9 amino acids exhibited RSD >15% using HPLC-MS/MS. Evaluating intra- and inter-assay precision over 3 days, the quantitation range for 32 detected amino acids in rat plasma was 0.90-497 μM, with overall mean intra-day precision of less than 15% and mean inter-day precision of 12%. This UPLC-MS/MS assay was successfully implemented for the quantitative analysis of amino acids in rat and mouse plasma, along with mouse urine and tissue samples, resulting in the following concentration ranges: 0.98-431 μM in mouse plasma for 32 detected amino acids; 0.62-443 μM in rat plasma for 32 detected amino acids; 0.44-8590μM in mouse liver for 33 detected amino acids; 0.61-1241 �

Profiling Cholinesterase Adduction: A High-Throughput Prioritization Method for Organophosphate Exposure Samples

PubMed Central

Carter, Melissa D.; Crow, Brian S.; Pantazides, Brooke G.; Watson, Caroline M.; deCastro, B. Rey; Thomas, Jerry D.; Blake, Thomas A.; Johnson, Rudolph C.

2017-01-01

A high-throughput prioritization method was developed for use with a validated confirmatory method detecting organophosphorus nerve agent exposure by immunomagnetic separation-HPLC-MS/MS. A ballistic gradient was incorporated into this analytical method in order to profile unadducted butyrylcholinesterase (BChE) in clinical samples. With Zhang, et al. 1999’s Z′-factor of 0.88 ± 0.01 (SD) of control analytes and Z-factor of 0.25 ± 0.06 (SD) of serum samples, the assay is rated an “excellent assay” for the synthetic peptide controls used and a “double assay” when used to prioritize clinical samples. Hits, defined as samples containing BChE Ser-198 adducts or no BChE present, were analyzed in a confirmatory method for identification and quantitation of the BChE adduct, if present. The ability to prioritize samples by highest exposure for confirmatory analysis is of particular importance in an exposure to cholinesterase inhibitors such as organophosphorus nerve agents where a large number of clinical samples may be collected. In an initial blind screen, 67 out of 70 samples were accurately identified giving an assay accuracy of 96% and yielded no false negatives. The method is the first to provide a high-throughput prioritization assay for profiling adduction of Ser-198 BChE in clinical samples. PMID:23954929

High Throughput Biological Analysis Using Multi-bit Magnetic Digital Planar Tags

NASA Astrophysics Data System (ADS)

Hong, B.; Jeong, J.-R.; Llandro, J.; Hayward, T. J.; Ionescu, A.; Trypiniotis, T.; Mitrelias, T.; Kopper, K. P.; Steinmuller, S. J.; Bland, J. A. C.

2008-06-01

We report a new magnetic labelling technology for high-throughput biomolecular identification and DNA sequencing. Planar multi-bit magnetic tags have been designed and fabricated, which comprise a magnetic barcode formed by an ensemble of micron-sized thin film Ni80Fe20 bars encapsulated in SU8. We show that by using a globally applied magnetic field and magneto-optical Kerr microscopy the magnetic elements in the multi-bit magnetic tags can be addressed individually and encoded/decoded remotely. The critical steps needed to show the feasibility of this technology are demonstrated, including fabrication, flow transport, remote writing and reading, and successful functionalization of the tags as verified by fluorescence detection. This approach is ideal for encoding information on tags in microfluidic flow or suspension, for such applications as labelling of chemical precursors during drug synthesis and combinatorial library-based high-throughput multiplexed bioassays.

Effectiveness of a high-throughput genetic analysis in the identification of responders/non-responders to CYP2D6-metabolized drugs.

PubMed

Savino, Maria; Seripa, Davide; Gallo, Antonietta P; Garrubba, Maria; D'Onofrio, Grazia; Bizzarro, Alessandra; Paroni, Giulia; Paris, Francesco; Mecocci, Patrizia; Masullo, Carlo; Pilotto, Alberto; Santini, Stefano A

2011-01-01

Recent studies investigating the single cytochrome P450 (CYP) 2D6 allele *2A reported an association with the response to drug treatments. More genetic data can be obtained, however, by high-throughput based-technologies. Aim of this study is the high-throughput analysis of the CYP2D6 polymorphisms to evaluate its effectiveness in the identification of patient responders/non-responders to CYP2D6-metabolized drugs. An attempt to compare our results with those previously obtained with the standard analysis of CYP2D6 allele *2A was also made. Sixty blood samples from patients treated with CYP2D6-metabolized drugs previously genotyped for the allele CYP2D6*2A, were analyzed for the CYP2D6 polymorphisms with the AutoGenomics INFINITI CYP4502D6-I assay on the AutoGenomics INFINITI analyzer. A higher frequency of mutated alleles in responder than in non-responder patients (75.38 % vs 43.48 %; p = 0.015) was observed. Thus, the presence of a mutated allele of CYP2D6 was associated with a response to CYP2D6-metabolized drugs (OR = 4.044 (1.348 - 12.154). No difference was observed in the distribution of allele *2A (p = 0.320). The high-throughput genetic analysis of the CYP2D6 polymorphisms better discriminate responders/non-responders with respect to the standard analysis of the CYP2D6 allele *2A. A high-throughput genetic assay of the CYP2D6 may be useful to identify patients with different clinical responses to CYP2D6-metabolized drugs.

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

PubMed

Yuan, Tiezheng; Huang, Xiaoyi; Dittmar, Rachel L; Du, Meijun; Kohli, Manish; Boardman, Lisa; Thibodeau, Stephen N; Wang, Liang

2014-03-05

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

PubMed

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-08-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

PubMed Central

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-01-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/. PMID:23657089

Enrichment analysis in high-throughput genomics - accounting for dependency in the NULL.

PubMed

Gold, David L; Coombes, Kevin R; Wang, Jing; Mallick, Bani

2007-03-01

Translating the overwhelming amount of data generated in high-throughput genomics experiments into biologically meaningful evidence, which may for example point to a series of biomarkers or hint at a relevant pathway, is a matter of great interest in bioinformatics these days. Genes showing similar experimental profiles, it is hypothesized, share biological mechanisms that if understood could provide clues to the molecular processes leading to pathological events. It is the topic of further study to learn if or how a priori information about the known genes may serve to explain coexpression. One popular method of knowledge discovery in high-throughput genomics experiments, enrichment analysis (EA), seeks to infer if an interesting collection of genes is 'enriched' for a Consortium particular set of a priori Gene Ontology Consortium (GO) classes. For the purposes of statistical testing, the conventional methods offered in EA software implicitly assume independence between the GO classes. Genes may be annotated for more than one biological classification, and therefore the resulting test statistics of enrichment between GO classes can be highly dependent if the overlapping gene sets are relatively large. There is a need to formally determine if conventional EA results are robust to the independence assumption. We derive the exact null distribution for testing enrichment of GO classes by relaxing the independence assumption using well-known statistical theory. In applications with publicly available data sets, our test results are similar to the conventional approach which assumes independence. We argue that the independence assumption is not detrimental.

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

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 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.

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

fluff: exploratory analysis and visualization of high-throughput sequencing data

PubMed Central

Georgiou, Georgios

2016-01-01

Summary. In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org. Availability. fluff is implemented in Python and runs on Linux. The source code is freely available for download at https://github.com/simonvh/fluff. PMID:27547532

Evaluation of High-Throughput Chemical Exposure Models via Analysis of Matched Environmental and Biological Media Measurements

EPA Science Inventory

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 ...

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

HTSstation: A Web Application and Open-Access Libraries for High-Throughput Sequencing Data Analysis

PubMed Central

David, Fabrice P. A.; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J.; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

2014-01-01

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch. PMID:24475057

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

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

PubMed Central

2014-01-01

Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

Application of Computational and High-Throughput in vitro ...

EPA Pesticide Factsheets

Abstract: There are tens of thousands of man-made chemicals to which humans are exposed, but only a fraction of these have the extensive in vivo toxicity data used in most traditional risk assessments. This lack of data, coupled with concerns about testing costs and animal use, are driving the development of new methods for assessing the risk of toxicity. These methods include the use of in vitro high-throughput screening assays and computational models. This talk will review a variety of high-throughput, non-animal methods being used at the U.S. EPA to screen chemicals for a variety of toxicity endpoints, with a focus on their potential to be endocrine disruptors as part of the Endocrine Disruptor Screening Program (EDSP). These methods all start with the use of in vitro assays, e.g. for activity against the estrogen and androgen receptors (ER and AR) and targets in the steroidogenesis and thyroid signaling pathways. Because all individual assays are subject to a variety of noise processes and technology-specific assay artefacts, we have developed methods to create consensus predictions from multiple assays against the same target. The goal of these models is to both robustly predict in vivo activity, and also to provide quantitative estimates of uncertainty. This talk will describe these models, and how they are validated against both in vitro and in vivo reference chemicals. The U.S. EPA has deemed the in vitro ER model results to be of high enough accuracy t

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.

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.

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

Looking towards label-free biomolecular interaction analysis in a high-throughput format: a review of new surface plasmon resonance technologies.

PubMed

Boozer, Christina; Kim, Gibum; Cong, Shuxin; Guan, Hannwen; Londergan, Timothy

2006-08-01

Surface plasmon resonance (SPR) biosensors have enabled a wide range of applications in which researchers can monitor biomolecular interactions in real time. Owing to the fact that SPR can provide affinity and kinetic data, unique features in applications ranging from protein-peptide interaction analysis to cellular ligation experiments have been demonstrated. Although SPR has historically been limited by its throughput, new methods are emerging that allow for the simultaneous analysis of many thousands of interactions. When coupled with new protein array technologies, high-throughput SPR methods give users new and improved methods to analyze pathways, screen drug candidates and monitor protein-protein interactions.

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

High-throughput image analysis of tumor spheroids: a user-friendly software application to measure the size of spheroids automatically and accurately.

PubMed

Chen, Wenjin; Wong, Chung; Vosburgh, Evan; Levine, Arnold J; Foran, David J; Xu, Eugenia Y

2014-07-08

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application - SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary "Manual Initialize" and "Hand Draw" tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model

Protein-RNA specificity by high-throughput principal component analysis of NMR spectra.

PubMed

Collins, Katherine M; Oregioni, Alain; Robertson, Laura E; Kelly, Geoff; Ramos, Andres

2015-03-31

Defining the RNA target selectivity of the proteins regulating mRNA metabolism is a key issue in RNA biology. Here we present a novel use of principal component analysis (PCA) to extract the RNA sequence preference of RNA binding proteins. We show that PCA can be used to compare the changes in the nuclear magnetic resonance (NMR) spectrum of a protein upon binding a set of quasi-degenerate RNAs and define the nucleobase specificity. We couple this application of PCA to an automated NMR spectra recording and processing protocol and obtain an unbiased and high-throughput NMR method for the analysis of nucleobase preference in protein-RNA interactions. We test the method on the RNA binding domains of three important regulators of RNA metabolism. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

High-Throughput Multiplexed Quantitation of Protein Aggregation and Cytotoxicity in a Huntington’s Disease Model

PubMed Central

Titus, Steven A; Southall, Noel; Marugan, Juan; Austin, Christopher P; Zheng, Wei

2012-01-01

A hallmark of Huntington’s disease is the presence of a large polyglutamine expansion in the first exon of the Huntingtin protein and the propensity of protein aggregation by the mutant proteins. Aberrant protein aggregation also occurs in other polyglutamine expansion disorders, as well as in other neurodegenerative diseases including Parkinson’s, Alzheimer’s, and prion diseases. However, the pathophysiological role of these aggregates in the cell death that characterizes the diseases remains unclear. Identification of small molecule probes that modulate protein aggregation and cytotoxicity caused by aggregated proteins may greatly facilitate the studies on pathogenesis of these diseases and potentially lead to development of new therapies. Based on a detergent insoluble property of the Huntingtin protein aggregates, we have developed a homogenous assay to rapidly quantitate the levels of protein aggregates in a cellular model of Huntington’s disease. The protein aggregation assay has also been multiplexed with a protease release assay for the measurement of cytotoxicity resulting from aggregated proteins in the same cells. Through a testing screen of a compound library, we have demonstrated that this multiplexed cytotoxicity and protein aggregation assay has ability to identify active compounds that prevent cell death and/or modulate protein aggregation in cells of the Huntington’s disease model. Therefore, this multiplexed screening approach is also useful for development of high-throughput screening assays for other neurodegenerative diseases involving protein aggregation. PMID:23346268

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 process development: determination of dynamic binding capacity using microtiter filter plates filled with chromatography resin.

PubMed

Bergander, Tryggve; Nilsson-Välimaa, Kristina; Oberg, Katarina; Lacki, Karol M

2008-01-01

Steadily increasing demand for more efficient and more affordable biomolecule-based therapies put a significant burden on biopharma companies to reduce the cost of R&D activities associated with introduction of a new drug to the market. Reducing the time required to develop a purification process would be one option to address the high cost issue. The reduction in time can be accomplished if more efficient methods/tools are available for process development work, including high-throughput techniques. This paper addresses the transitions from traditional column-based process development to a modern high-throughput approach utilizing microtiter filter plates filled with a well-defined volume of chromatography resin. The approach is based on implementing the well-known batch uptake principle into microtiter plate geometry. Two variants of the proposed approach, allowing for either qualitative or quantitative estimation of dynamic binding capacity as a function of residence time, are described. Examples of quantitative estimation of dynamic binding capacities of human polyclonal IgG on MabSelect SuRe and of qualitative estimation of dynamic binding capacity of amyloglucosidase on a prototype of Capto DEAE weak ion exchanger are given. The proposed high-throughput method for determination of dynamic binding capacity significantly reduces time and sample consumption as compared to a traditional method utilizing packed chromatography columns without sacrificing the accuracy of data obtained.

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 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

HPLC-high-resolution mass spectrometry with polarity switching for increasing throughput of human in vitro cocktail drug-drug interaction assay.

PubMed

Ramanathan, Ragu; Ghosal, Anima; Ramanathan, Lakshmi; Comstock, Kate; Shen, Helen; Ramanathan, Dil

2018-05-01

Evaluation of HPLC-high-resolution mass spectrometry (HPLC-HRMS) full scan with polarity switching for increasing throughput of human in vitro cocktail drug-drug interaction assay. Microsomal incubates were analyzed using a high resolution and high mass accuracy Q-Exactive mass spectrometer to collect integrated qualitative and quantitative (qual/quant) data. Within assay, positive-to-negative polarity switching HPLC-HRMS method allowed quantification of eight and two probe compounds in the positive and negative ionization modes, respectively, while monitoring for LOR and its metabolites. LOR-inhibited CYP2C19 and showed higher activity for CYP2D6, CYP2E1 and CYP3A4. Overall, LC-HRMS-based nontargeted full scan quantitation allowed to improve the throughput of the in vitro cocktail drug-drug interaction assay.

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

eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing

PubMed Central

2014-01-01

Background RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. Results We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification” includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module “mRNA identification” includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module “Target screening” provides expression profiling analyses and graphic visualization. The module “Self-testing” offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program’s functionality. Conclusions eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory. PMID:24593312

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

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

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

High-throughput microfluidic single-cell digital polymerase chain reaction.

PubMed

White, A K; Heyries, K A; Doolin, C; Vaninsberghe, M; Hansen, C L

2013-08-06

Here we present an integrated microfluidic device for the high-throughput digital polymerase chain reaction (dPCR) analysis of single cells. This device allows for the parallel processing of single cells and executes all steps of analysis, including cell capture, washing, lysis, reverse transcription, and dPCR analysis. The cDNA from each single cell is distributed into a dedicated dPCR array consisting of 1020 chambers, each having a volume of 25 pL, using surface-tension-based sample partitioning. The high density of this dPCR format (118,900 chambers/cm(2)) allows the analysis of 200 single cells per run, for a total of 204,000 PCR reactions using a device footprint of 10 cm(2). Experiments using RNA dilutions show this device achieves shot-noise-limited performance in quantifying single molecules, with a dynamic range of 10(4). We performed over 1200 single-cell measurements, demonstrating the use of this platform in the absolute quantification of both high- and low-abundance mRNA transcripts, as well as micro-RNAs that are not easily measured using alternative hybridization methods. We further apply the specificity and sensitivity of single-cell dPCR to performing measurements of RNA editing events in single cells. High-throughput dPCR provides a new tool in the arsenal of single-cell analysis methods, with a unique combination of speed, precision, sensitivity, and specificity. We anticipate this approach will enable new studies where high-performance single-cell measurements are essential, including the analysis of transcriptional noise, allelic imbalance, and RNA processing.

Continuous cell introduction and rapid dynamic lysis for high-throughput single-cell analysis on microfludic chips with hydrodynamic focusing.

PubMed

Xu, Chun-Xiu; Yin, Xue-Feng

2011-02-04

A chip-based microfluidic system for high-throughput single-cell analysis is described. The system was integrated with continuous introduction of individual cells, rapid dynamic lysis, capillary electrophoretic (CE) separation and laser induced fluorescence (LIF) detection. A cross microfluidic chip with one sheath-flow channel located on each side of the sampling channel was designed. The labeled cells were hydrodynamically focused by sheath-flow streams and sequentially introduced into the cross section of the microchip under hydrostatic pressure generated by adjusting liquid levels in the reservoirs. Combined with the electric field applied on the separation channel, the aligned cells were driven into the separation channel and rapidly lysed within 33ms at the entry of the separation channel by Triton X-100 added in the sheath-flow solution. The maximum rate for introducing individual cells into the separation channel was about 150cells/min. The introduction of sheath-flow streams also significantly reduced the concentration of phosphate-buffered saline (PBS) injected into the separation channel along with single cells, thus reducing Joule heating during electrophoretic separation. The performance of this microfluidic system was evaluated by analysis of reduced glutathione (GSH) and reactive oxygen species (ROS) in single erythrocytes. A throughput of 38cells/min was obtained. The proposed method is simple and robust for high-throughput single-cell analysis, allowing for analysis of cell population with considerable size to generate results with statistical significance. Copyright © 2010 Elsevier B.V. All rights reserved.

Quantitative assessment of hit detection and confirmation in single and duplicate high-throughput screenings.

PubMed

Wu, Zhijin; Liu, Dongmei; Sui, Yunxia

2008-02-01

The process of identifying active targets (hits) in high-throughput screening (HTS) usually involves 2 steps: first, removing or adjusting for systematic variation in the measurement process so that extreme values represent strong biological activity instead of systematic biases such as plate effect or edge effect and, second, choosing a meaningful cutoff on the calculated statistic to declare positive compounds. Both false-positive and false-negative errors are inevitable in this process. Common control or estimation of error rates is often based on an assumption of normal distribution of the noise. The error rates in hit detection, especially false-negative rates, are hard to verify because in most assays, only compounds selected in primary screening are followed up in confirmation experiments. In this article, the authors take advantage of a quantitative HTS experiment in which all compounds are tested 42 times over a wide range of 14 concentrations so true positives can be found through a dose-response curve. Using the activity status defined by dose curve, the authors analyzed the effect of various data-processing procedures on the sensitivity and specificity of hit detection, the control of error rate, and hit confirmation. A new summary score is proposed and demonstrated to perform well in hit detection and useful in confirmation rate estimation. In general, adjusting for positional effects is beneficial, but a robust test can prevent overadjustment. Error rates estimated based on normal assumption do not agree with actual error rates, for the tails of noise distribution deviate from normal distribution. However, false discovery rate based on empirically estimated null distribution is very close to observed false discovery proportion.

Extended length microchannels for high density high throughput electrophoresis systems

DOEpatents

Davidson, James C.; Balch, Joseph W.

2000-01-01

High throughput electrophoresis systems which provide extended well-to-read distances on smaller substrates, thus compacting the overall systems. The electrophoresis systems utilize a high density array of microchannels for electrophoresis analysis with extended read lengths. The microchannel geometry can be used individually or in conjunction to increase the effective length of a separation channel while minimally impacting the packing density of channels. One embodiment uses sinusoidal microchannels, while another embodiment uses plural microchannels interconnected by a via. The extended channel systems can be applied to virtually any type of channel confined chromatography.

High Throughput Plasmid Sequencing with Illumina and CLC Bio (Seventh Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting 2012)

ScienceCinema

Athavale, Ajay

2018-01-04

Ajay Athavale (Monsanto) presents "High Throughput Plasmid Sequencing with Illumina and CLC Bio" at the 7th Annual Sequencing, Finishing, Analysis in the Future (SFAF) Meeting held in June, 2012 in Santa Fe, NM.

High-throughput 3D whole-brain quantitative histopathology in rodents

PubMed Central

Vandenberghe, Michel E.; Hérard, Anne-Sophie; Souedet, Nicolas; Sadouni, Elmahdi; Santin, Mathieu D.; Briet, Dominique; Carré, Denis; Schulz, Jocelyne; Hantraye, Philippe; Chabrier, Pierre-Etienne; Rooney, Thomas; Debeir, Thomas; Blanchard, Véronique; Pradier, Laurent; Dhenain, Marc; Delzescaux, Thierry

2016-01-01

Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed on a few tissue sections, thus restricting measurements to limited portions of the brain. Recently developed 3D microscopic imaging techniques have allowed in-depth study of neuroanatomy. However, quantitative methods are still lacking for whole-brain analysis of cellular and pathological markers. Here, we propose a ready-to-use, automated, and scalable method to thoroughly quantify histopathological markers in 3D in rodent whole brains. It relies on block-face photography, serial histology and 3D-HAPi (Three Dimensional Histology Analysis Pipeline), an open source image analysis software. We illustrate our method in studies involving mouse models of Alzheimer’s disease and show that it can be broadly applied to characterize animal models of brain diseases, to evaluate therapeutic interventions, to anatomically correlate cellular and pathological markers throughout the entire brain and to validate in vivo imaging techniques. PMID:26876372

Development of a high-throughput assay for rapid screening of butanologenic strains.

PubMed

Agu, Chidozie Victor; Lai, Stella M; Ujor, Victor; Biswas, Pradip K; Jones, Andy; Gopalan, Venkat; Ezeji, Thaddeus Chukwuemeka

2018-02-21

We report a Thermotoga hypogea (Th) alcohol dehydrogenase (ADH)-dependent spectrophotometric assay for quantifying the amount of butanol in growth media, an advance that will facilitate rapid high-throughput screening of hypo- and hyper-butanol-producing strains of solventogenic Clostridium species. While a colorimetric nitroblue tetrazolium chloride-based assay for quantitating butanol in acetone-butanol-ethanol (ABE) fermentation broth has been described previously, we determined that Saccharomyces cerevisiae (Sc) ADH used in this earlier study exhibits approximately 13-fold lower catalytic efficiency towards butanol than ethanol. Any Sc ADH-dependent assay for primary quantitation of butanol in an ethanol-butanol mixture is therefore subject to "ethanol interference". To circumvent this limitation and better facilitate identification of hyper-butanol-producing Clostridia, we searched the literature for native ADHs that preferentially utilize butanol over ethanol and identified Th ADH as a candidate. Indeed, recombinant Th ADH exhibited a 6-fold higher catalytic efficiency with butanol than ethanol, as measured using the reduction of NADP + to NADPH that accompanies alcohol oxidation. Moreover, the assay sensitivity was not affected by the presence of acetone, acetic acid or butyric acid (typical ABE fermentation products). We broadened the utility of our assay by adapting it to a high-throughput microtiter plate-based format, and piloted it successfully in an ongoing metabolic engineering initiative.

High-Throughput Screening To Identify Potent and Specific Inhibitors of Microbial Sulfate Reduction.

PubMed

Carlson, Hans K; Mullan, Mark R; Mosqueda, Lorraine A; Chen, Steven; Arkin, Michelle R; Coates, John D

2017-06-20

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. 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 identify potent and selective inhibitors of SRM, quantitatively ranked the selectivity and potency of hundreds of compounds and identified previously unrecognized SRM selective inhibitors and synergistic interactions between inhibitors. Zinc pyrithione is the most potent inhibitor of sulfidogenesis that we identified, and is several orders of magnitude more potent than commonly used industrial biocides. Both zinc and copper pyrithione are also moderately selective against SRM. The high-throughput (HT) approach we present can be readily adapted to target SRM in diverse environments and similar strategies could be used to quantify the potency and selectivity of inhibitors of a variety of microbial metabolisms. Our findings and approach are relevant to efforts to engineer environmental ecosystems and also to understand the role of natural gradients in shaping microbial niche space.

The combination of gas-phase fluorophore technology and automation to enable high-throughput analysis of plant respiration.

PubMed

Scafaro, Andrew P; Negrini, A Clarissa A; O'Leary, Brendan; Rashid, F Azzahra Ahmad; Hayes, Lucy; Fan, Yuzhen; Zhang, You; Chochois, Vincent; Badger, Murray R; Millar, A Harvey; Atkin, Owen K

2017-01-01

Mitochondrial respiration in the dark ( R dark ) is a critical plant physiological process, and hence a reliable, efficient and high-throughput method of measuring variation in rates of R dark is essential for agronomic and ecological studies. However, currently methods used to measure R dark in plant tissues are typically low throughput. We assessed a high-throughput automated fluorophore system of detecting multiple O 2 consumption rates. The fluorophore technique was compared with O 2 -electrodes, infrared gas analysers (IRGA), and membrane inlet mass spectrometry, to determine accuracy and speed of detecting respiratory fluxes. The high-throughput fluorophore system provided stable measurements of R dark in detached leaf and root tissues over many hours. High-throughput potential was evident in that the fluorophore system was 10 to 26-fold faster per sample measurement than other conventional methods. The versatility of the technique was evident in its enabling: (1) rapid screening of R dark in 138 genotypes of wheat; and, (2) quantification of rarely-assessed whole-plant R dark through dissection and simultaneous measurements of above- and below-ground organs. Variation in absolute R dark was observed between techniques, likely due to variation in sample conditions (i.e. liquid vs. gas-phase, open vs. closed systems), indicating that comparisons between studies using different measuring apparatus may not be feasible. However, the high-throughput protocol we present provided similar values of R dark to the most commonly used IRGA instrument currently employed by plant scientists. Together with the greater than tenfold increase in sample processing speed, we conclude that the high-throughput protocol enables reliable, stable and reproducible measurements of R dark on multiple samples simultaneously, irrespective of plant or tissue type.

Quantitative High-Resolution Genomic Analysis of Single Cancer Cells

PubMed Central

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A.; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics. PMID:22140428

Quantitative high-resolution genomic analysis of single cancer cells.

PubMed

Hannemann, Juliane; Meyer-Staeckling, Sönke; Kemming, Dirk; Alpers, Iris; Joosse, Simon A; Pospisil, Heike; Kurtz, Stefan; Görndt, Jennifer; Püschel, Klaus; Riethdorf, Sabine; Pantel, Klaus; Brandt, Burkhard

2011-01-01

During cancer progression, specific genomic aberrations arise that can determine the scope of the disease and can be used as predictive or prognostic markers. The detection of specific gene amplifications or deletions in single blood-borne or disseminated tumour cells that may give rise to the development of metastases is of great clinical interest but technically challenging. In this study, we present a method for quantitative high-resolution genomic analysis of single cells. Cells were isolated under permanent microscopic control followed by high-fidelity whole genome amplification and subsequent analyses by fine tiling array-CGH and qPCR. The assay was applied to single breast cancer cells to analyze the chromosomal region centred by the therapeutical relevant EGFR gene. This method allows precise quantitative analysis of copy number variations in single cell diagnostics.

A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis.

PubMed

Lee, Hangyeore; Mun, Dong-Gi; Bae, Jingi; Kim, Hokeun; Oh, Se Yeon; Park, Young Soo; Lee, Jae-Hyuk; Lee, Sang-Won

2015-08-21

We report a new and simple design of a fully automated dual-online ultra-high pressure liquid chromatography system. The system employs only two nano-volume switching valves (a two-position four port valve and a two-position ten port valve) that direct solvent flows from two binary nano-pumps for parallel operation of two analytical columns and two solid phase extraction (SPE) columns. Despite the simple design, the sDO-UHPLC offers many advantageous features that include high duty cycle, back flushing sample injection for fast and narrow zone sample injection, online desalting, high separation resolution and high intra/inter-column reproducibility. This system was applied to analyze proteome samples not only in high throughput deep proteome profiling experiments but also in high throughput MRM experiments.

High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics

PubMed Central

2015-01-01

Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of 13C, 15N, and 2H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS2) analysis on an Orbitrap Elite mass spectrometer. PMID:25405479

Application of computational and high-throughput in vitro ...

EPA Pesticide Factsheets

Abstract: There are tens of thousands of man-made chemicals to which humans are exposed, but only a fraction of these have the extensive in vivo toxicity data used in most traditional risk assessments. This lack of data, coupled with concerns about testing costs and animal use, are driving the development of new methods for assessing the risk of toxicity. These methods include the use of in vitro high-throughput screening assays and computational models. This talk will review a variety of high-throughput, non-animal methods being used at the U.S. EPA to screen chemicals for their potential to be endocrine disruptors as part of the Endocrine Disruptor Screening Program (EDSP). These methods all start with the use of in vitro assays, e.g. for activity against the estrogen and androgen receptors (ER and AR) and targets in the steroidogenesis and thyroid signaling pathways. Because all individual assays are subject to a variety of noise processes and technology-specific assay artefacts, we have developed methods to create consensus predictions from multiple assays against the same target. The goal of these models is to both robustly predict in vivo activity, and also to provide quantitative estimates of uncertainty. This talk will describe these models, and how they are validated against both in vitro and in vivo reference chemicals. The U.S. EPA has deemed the in vitro ER model results to be of high enough accuracy to be used as a substitute for the current EDSP Ti

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.

DAnTE: a statistical tool for quantitative analysis of –omics data

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

Polpitiya, Ashoka D.; Qian, Weijun; Jaitly, Navdeep

2008-05-03

DAnTE (Data Analysis Tool Extension) is a statistical tool designed to address challenges unique to quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide to protein rollup methods, an extensive array of plotting functions, and a comprehensive ANOVA scheme that can handle unbalanced data and random effects. The Graphical User Interface (GUI) is designed to be very intuitive and user friendly.

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

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.

Subnuclear foci quantification using high-throughput 3D image cytometry

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

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...

ToxCast Workflow: High-throughput screening assay data processing, analysis and management (SOT)

EPA Science Inventory

US EPA’s ToxCast program is generating data in high-throughput screening (HTS) and high-content screening (HCS) assays for thousands of environmental chemicals, for use in developing predictive toxicity models. Currently the ToxCast screening program includes over 1800 unique c...

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

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

PubMed

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

2017-06-01

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

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

PubMed Central

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

2012-01-01

Biofilms formed on tooth surfaces are comprised of mixed microbiota enmeshed in an extracellular matrix. Oral biofilms are constantly exposed to environmental changes, which influence the microbial composition, matrix formation and expression of virulence. Streptococcus mutans and sucrose are key modulators associated with the evolution of virulent-cariogenic biofilms. In this study, we used a high-throughput quantitative proteomics approach to examine how S. mutans produces relevant proteins that facilitate its establishment and optimal survival during mixed-species biofilms development induced by sucrose. Biofilms of S. mutans, alone or mixed with Actinomyces naeslundii and Streptococcus oralis, were initially formed onto saliva-coated hydroxyapatite surface under carbohydrate-limiting condition. Sucrose (1%, w/v) was then introduced to cause environmental changes, and to induce biofilm accumulation. Multidimensional protein identification technology (MudPIT) approach detected up to 60% of proteins encoded by S. mutans within biofilms. Specific proteins associated with exopolysaccharide matrix assembly, metabolic and stress adaptation processes were highly abundant as the biofilm transit from earlier to later developmental stages following sucrose introduction. Our results indicate that S. mutans within a mixed-species biofilm community increases the expression of specific genes associated with glucan synthesis and remodeling (gtfBC, dexA) and glucan-binding (gbpB) during this transition (P<0.05). Furthermore, S. mutans up-regulates specific adaptation mechanisms to cope with acidic environments (F1F0-ATPase system, fatty acid biosynthesis, branched chain amino acids metabolism), and molecular chaperones (GroEL). Interestingly, the protein levels and gene expression are in general augmented when S. mutans form mixed-species biofilms (vs. single-species biofilms) demonstrating fundamental differences in the matrix assembly, survival and biofilm maintenance in the

High-throughput telomere length quantification by FISH and its application to human population studies.

PubMed

Canela, Andrés; Vera, Elsa; Klatt, Peter; Blasco, María A

2007-03-27

A major limitation of studies of the relevance of telomere length to cancer and age-related diseases in human populations and to the development of telomere-based therapies has been the lack of suitable high-throughput (HT) assays to measure telomere length. We have developed an automated HT quantitative telomere FISH platform, HT quantitative FISH (Q-FISH), which allows the quantification of telomere length as well as percentage of short telomeres in large human sample sets. We show here that this technique provides the accuracy and sensitivity to uncover associations between telomere length and human disease.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Microfluidic system for high throughput characterisation of echogenic particles.

PubMed

Rademeyer, Paul; Carugo, Dario; Lee, Jeong Yu; Stride, Eleanor

2015-01-21

Echogenic particles, such as microbubbles and volatile liquid micro/nano droplets, have shown considerable potential in a variety of clinical diagnostic and therapeutic applications. The accurate prediction of their response to ultrasound excitation is however extremely challenging, and this has hindered the optimisation of techniques such as quantitative ultrasound imaging and targeted drug delivery. Existing characterisation techniques, such as ultra-high speed microscopy provide important insights, but suffer from a number of limitations; most significantly difficulty in obtaining large data sets suitable for statistical analysis and the need to physically constrain the particles, thereby altering their dynamics. Here a microfluidic system is presented that overcomes these challenges to enable the measurement of single echogenic particle response to ultrasound excitation. A co-axial flow focusing device is used to direct a continuous stream of unconstrained particles through the combined focal region of an ultrasound transducer and a laser. Both the optical and acoustic scatter from individual particles are then simultaneously recorded. Calibration of the device and example results for different types of echogenic particle are presented, demonstrating a high throughput of up to 20 particles per second and the ability to resolve changes in particle radius down to 0.1 μm with an uncertainty of less than 3%.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

PubMed

Wan, Cuihong; Liu, Jian; Fong, Vincent; Lugowski, Andrew; Stoilova, Snejana; Bethune-Waddell, Dylan; Borgeson, Blake; Havugimana, Pierre C; Marcotte, Edward M; Emili, Andrew

2013-04-09

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2012 Elsevier B.V. All rights reserved.

Restriction Site Tiling Analysis: accurate discovery and quantitative genotyping of genome-wide polymorphisms using nucleotide arrays

PubMed Central

2010-01-01

High-throughput genotype data can be used to identify genes important for local adaptation in wild populations, phenotypes in lab stocks, or disease-related traits in human medicine. Here we advance microarray-based genotyping for population genomics with Restriction Site Tiling Analysis. The approach simultaneously discovers polymorphisms and provides quantitative genotype data at 10,000s of loci. It is highly accurate and free from ascertainment bias. We apply the approach to uncover genomic differentiation in the purple sea urchin. PMID:20403197

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

High Throughput Light Absorber Discovery, Part 2: Establishing Structure-Band Gap Energy Relationships.

PubMed

Suram, Santosh K; Newhouse, Paul F; Zhou, Lan; Van Campen, Douglas G; Mehta, Apurva; Gregoire, John M

2016-11-14

Combinatorial materials science strategies have accelerated materials development in a variety of fields, and we extend these strategies to enable structure-property mapping for light absorber materials, particularly in high order composition spaces. High throughput optical spectroscopy and synchrotron X-ray diffraction are combined to identify the optical properties of Bi-V-Fe oxides, leading to the identification of Bi 4 V 1.5 Fe 0.5 O 10.5 as a light absorber with direct band gap near 2.7 eV. The strategic combination of experimental and data analysis techniques includes automated Tauc analysis to estimate band gap energies from the high throughput spectroscopy data, providing an automated platform for identifying new optical materials.

Spatial tuning of acoustofluidic pressure nodes by altering net sonic velocity enables high-throughput, efficient cell sorting

DOE PAGES

Jung, Seung-Yong; Notton, Timothy; Fong, Erika; ...

2015-01-07

Particle sorting using acoustofluidics has enormous potential but widespread adoption has been limited by complex device designs and low throughput. Here, we report high-throughput separation of particles and T lymphocytes (600 μL min -1) by altering the net sonic velocity to reposition acoustic pressure nodes in a simple two-channel device. Finally, the approach is generalizable to other microfluidic platforms for rapid, high-throughput analysis.

Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment

DOE PAGES

Yan, Qimin; Yu, Jie; Suram, Santosh K.; ...

2017-03-06

The limited number of known low-band-gap photoelectrocatalytic materials poses a significant challenge for the generation of chemical fuels from sunlight. Here, using high-throughput ab initio theory with experiments in an integrated workflow, we find eight ternary vanadate oxide photoanodes in the target band-gap range (1.2-2.8 eV). Detailed analysis of these vanadate compounds reveals the key role of VO 4 structural motifs and electronic band-edge character in efficient photoanodes, initiating a genome for such materials and paving the way for a broadly applicable high-throughput-discovery and materials-by-design feedback loop. Considerably expanding the number of known photoelectrocatalysts for water oxidation, our study establishesmore » ternary metal vanadates as a prolific class of photoanodematerials for generation of chemical fuels from sunlight and demonstrates our high-throughput theory-experiment pipeline as a prolific approach to materials discovery.« less

Solar fuels photoanode materials discovery by integrating high-throughput theory and experiment

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

Yan, Qimin; Yu, Jie; Suram, Santosh K.

The limited number of known low-band-gap photoelectrocatalytic materials poses a significant challenge for the generation of chemical fuels from sunlight. Here, using high-throughput ab initio theory with experiments in an integrated workflow, we find eight ternary vanadate oxide photoanodes in the target band-gap range (1.2-2.8 eV). Detailed analysis of these vanadate compounds reveals the key role of VO 4 structural motifs and electronic band-edge character in efficient photoanodes, initiating a genome for such materials and paving the way for a broadly applicable high-throughput-discovery and materials-by-design feedback loop. Considerably expanding the number of known photoelectrocatalysts for water oxidation, our study establishesmore » ternary metal vanadates as a prolific class of photoanodematerials for generation of chemical fuels from sunlight and demonstrates our high-throughput theory-experiment pipeline as a prolific approach to materials discovery.« less

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 quantitative luminescence assay of the growth in planta of Pseudomonas syringae chromosomally tagged with Photorhabdus luminescens luxCDABE.

PubMed

Fan, Jun; Crooks, Casey; Lamb, Chris

2008-01-01

Bioluminescent strains of the Arabidopsis thaliana pathogens Pseudomonas syringae pathovar (pv.) tomato and pv. maculicola were made by insertion of the luxCDABE operon from Photorhabdus luminescens into the P. syringae chromosome under the control of a constitutive promoter. Stable integration of luxCDABE did not affect bacterial fitness, growth in planta or disease outcome. Luminescence accurately and reliably reported bacterial growth in infected Arabidopsis leaves both with a fixed inoculum followed over time and with varying inocula assayed at a single time point. Furthermore, the bioluminescence assay could detect a small (1.3-fold) difference in bacterial growth between different plant genotypes with a precision comparable to that of the standard plate assay. Luminescence of luxCDABE-tagged P. syringae allows rapid and convenient quantification of bacterial growth without the tissue extraction, serial dilution, plating and manual scoring involved in standard assays of bacterial growth by colony formation in plate culture of samples from infected tissue. The utility of the bioluminescence assay was illustrated by surveying the 500-fold variation in growth of the universally virulent P. syringae pv. maculicola ES4326 among more than 100 Arabidopsis ecotypes and identification of two quantitative trait loci accounting for 48% and 16%, respectively, of the variance of basal resistance to P. syringae pv. tomato DC3000 in the Col-0 x Fl-1 F(2) population. Luminescence assay of bacteria chromosomally tagged with luxCDABE should greatly facilitate the genetic dissection of quantitative differences in gene-for-gene, basal and acquired disease resistance and other aspects of plant interactions with bacterial pathogens requiring high-throughput assays or large-scale quantitative screens.

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.

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.

Quantitative determination of free/bound atazanavir via high-throughput equilibrium dialysis and LC-MS/MS, and the application in ex vivo samples.

PubMed

Xu, Xiaohui Sophia; Rose, Anne; Demers, Roger; Eley, Timothy; Ryan, John; Stouffer, Bruce; Cojocaru, Laura; Arnold, Mark

2014-01-01

The determination of drug-protein binding is important in the pharmaceutical development process because of the impact of protein binding on both the pharmacokinetics and pharmacodynamics of drugs. Equilibrium dialysis is the preferred method to measure the free drug fraction because it is considered to be more accurate. The throughput of equilibrium dialysis has recently been improved by implementing a 96-well format plate. Results/methodology: This manuscript illustrates the successful application of a 96-well rapid equilibrium dialysis (RED) device in the determination of atazanavir plasma-protein binding. This RED method of measuring free fraction was successfully validated and then applied to the analysis of clinical plasma samples taken from HIV-infected pregnant women administered atazanavir. Combined with LC-MS/MS detection, the 96-well format equilibrium dialysis device was suitable for measuring the free and bound concentration of pharmaceutical molecules in a high-throughput mode.

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...

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

Uncovering leaf rust responsive miRNAs in wheat (Triticum aestivum L.) using high-throughput sequencing and prediction of their targets through degradome analysis.

PubMed

Kumar, Dhananjay; Dutta, Summi; Singh, Dharmendra; Prabhu, Kumble Vinod; Kumar, Manish; Mukhopadhyay, Kunal

2017-01-01

Deep sequencing identified 497 conserved and 559 novel miRNAs in wheat, while degradome analysis revealed 701 targets genes. QRT-PCR demonstrated differential expression of miRNAs during stages of leaf rust progression. Bread wheat (Triticum aestivum L.) is an important cereal food crop feeding 30 % of the world population. Major threat to wheat production is the rust epidemics. This study was targeted towards identification and functional characterizations of micro(mi)RNAs and their target genes in wheat in response to leaf rust ingression. High-throughput sequencing was used for transcriptome-wide identification of miRNAs and their expression profiling in retort to leaf rust using mock and pathogen-inoculated resistant and susceptible near-isogenic wheat plants. A total of 1056 mature miRNAs were identified, of which 497 miRNAs were conserved and 559 miRNAs were novel. The pathogen-inoculated resistant plants manifested more miRNAs compared with the pathogen infected susceptible plants. The miRNA counts increased in susceptible isoline due to leaf rust, conversely, the counts decreased in the resistant isoline in response to pathogenesis illustrating precise spatial tuning of miRNAs during compatible and incompatible interaction. Stem-loop quantitative real-time PCR was used to profile 10 highly differentially expressed miRNAs obtained from high-throughput sequencing data. The spatio-temporal profiling validated the differential expression of miRNAs between the isolines as well as in retort to pathogen infection. Degradome analysis provided 701 predicted target genes associated with defense response, signal transduction, development, metabolism, and transcriptional regulation. The obtained results indicate that wheat isolines employ diverse arrays of miRNAs that modulate their target genes during compatible and incompatible interaction. Our findings contribute to increase knowledge on roles of microRNA in wheat-leaf rust interactions and could help in rust

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

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

Hura, Greg L.; Menon, Angeli L.; Hammel, Michal

2009-07-20

We present an efficient pipeline enabling high-throughput analysis of protein structure in solution with small angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling of microliter volumes, temperature and anaerobic control, rapid data collection and data analysis, and couples structural analysis with automated archiving. We subjected 50 representative proteins, mostly from Pyrococcus furiosus, to this pipeline and found that 30 were multimeric structures in solution. SAXS analysis allowed us to distinguish aggregated and unfolded proteins, define global structural parameters and oligomeric states for most samples, identify shapes and similar structures for 25 unknown structures, and determine envelopes formore » 41 proteins. We believe that high-throughput SAXS is an enabling technology that may change the way that structural genomics research is done.« less

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 Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase

PubMed Central

Babaoglu, Kerim; Simeonov, Anton; Irwin, John J.; Nelson, Michael E.; Feng, Brian; Thomas, Craig J.; Cancian, Laura; Costi, M. Paola; Maltby, David A.; Jadhav, Ajit; Inglese, James; Austin, Christopher P.; Shoichet, Brian K.

2009-01-01

High-throughput screening (HTS) is widely used in drug discovery. Especially for screens of unbiased libraries, false positives can dominate “hit lists”; their origins are much debated. Here we determine the mechanism of every active hit from a screen of 70,563 unbiased molecules against β-lactamase using quantitative HTS (qHTS). Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators. Among the 70 remaining were 25 potent, covalent-acting β-lactams. Mass spectra, counter-screens, and crystallography identified 12 as promiscuous covalent inhibitors. The remaining 33 were either aggregators or irreproducible. No specific reversible inhibitors were found. We turned to molecular docking to prioritize molecules from the same library for testing at higher concentrations. Of 16 tested, 2 were modest inhibitors. Subsequent X-ray structures corresponded to the docking prediction. Analog synthesis improved affinity to 8 µM. These results suggest that it may be the physical behavior of organic molecules, not their reactivity, that accounts for most screening artifacts. Structure-based methods may prioritize weak-but-novel chemotypes in unbiased library screens. PMID:18333608

High throughput light absorber discovery, Part 2: Establishing structure–band gap energy relationships

DOE PAGES

Suram, Santosh K.; Newhouse, Paul F.; Zhou, Lan; ...

2016-09-23

Combinatorial materials science strategies have accelerated materials development in a variety of fields, and we extend these strategies to enable structure-property mapping for light absorber materials, particularly in high order composition spaces. High throughput optical spectroscopy and synchrotron X-ray diffraction are combined to identify the optical properties of Bi-V-Fe oxides, leading to the identification of Bi 4V 1.5Fe 0.5O 10.5 as a light absorber with direct band gap near 2.7 eV. Here, the strategic combination of experimental and data analysis techniques includes automated Tauc analysis to estimate band gap energies from the high throughput spectroscopy data, providing an automated platformmore » for identifying new optical materials.« less

High throughput light absorber discovery, Part 2: Establishing structure–band gap energy relationships

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

Suram, Santosh K.; Newhouse, Paul F.; Zhou, Lan

Combinatorial materials science strategies have accelerated materials development in a variety of fields, and we extend these strategies to enable structure-property mapping for light absorber materials, particularly in high order composition spaces. High throughput optical spectroscopy and synchrotron X-ray diffraction are combined to identify the optical properties of Bi-V-Fe oxides, leading to the identification of Bi 4V 1.5Fe 0.5O 10.5 as a light absorber with direct band gap near 2.7 eV. Here, the strategic combination of experimental and data analysis techniques includes automated Tauc analysis to estimate band gap energies from the high throughput spectroscopy data, providing an automated platformmore » for identifying new optical materials.« less

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.

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

PubMed Central

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

2016-01-01

Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical ‘large p, small n’ problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package “adaptiveHM”, which is freely available from https://github.com/benliemory/adaptiveHM. PMID:28919931

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

PubMed Central

Dong, Huina; Zu, Xin; Zheng, Ping; Zhang, Dawei

2015-01-01

Adenosine is a major local regulator of tissue function and industrially useful as precursor for the production of medicinal nucleoside substances. High-throughput screening of adenosine overproducers is important for industrial microorganism breeding. An enzymatic assay of adenosine was developed by combined adenosine deaminase (ADA) with indophenol method. The ADA catalyzes the cleavage of adenosine to inosine and NH3, the latter can be accurately determined by indophenol method. The assay system was optimized to deliver a good performance and could tolerate the addition of inorganic salts and many nutrition components to the assay mixtures. Adenosine could be accurately determined by this assay using 96-well microplates. Spike and recovery tests showed that this assay can accurately and reproducibly determine increases in adenosine in fermentation broth without any pretreatment to remove proteins and potentially interfering low-molecular-weight molecules. This assay was also applied to high-throughput screening for high adenosine-producing strains. The high selectivity and accuracy of the ADA assay provides rapid and high-throughput analysis of adenosine in large numbers of samples. PMID:25580842

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.

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

PubMed

Keegan, Alissa; Plath, Kathrin; Damoiseaux, Robert

2018-01-01

Assays of luciferase gene activity are a sensitive and quantitative reporter system suited to high-throughput screening. We adapted a luciferase assay to a screening strategy for identifying factors that reactivate epigenetically silenced genes. This epigenetic luciferase reporter is subject to endogenous gene silencing mechanisms on the inactive X chromosome (Xi) in primary mouse cells and thus captures the multilayered nature of chromatin silencing in development. Here, we describe the optimization of an Xi-linked luciferase reactivation assay in 384-well format and adaptation of the assay for high-throughput siRNA and chemical screening. Xi-luciferase reactivation screening has applications in stem cell biology and cancer therapy. We have used the approach described here to identify chromatin-modifying proteins and to identify drug combinations that enhance the gene reactivation activity of the DNA demethylating drug 5-aza-2'-deoxycytidine.

Developing High-Throughput HIV Incidence Assay with Pyrosequencing Platform

PubMed Central

Park, Sung Yong; Goeken, Nolan; Lee, Hyo Jin; Bolan, Robert; Dubé, Michael P.

2014-01-01

ABSTRACT Human immunodeficiency virus (HIV) incidence is an important measure for monitoring the epidemic and evaluating the efficacy of intervention and prevention trials. This study developed a high-throughput, single-measure incidence assay by implementing a pyrosequencing platform. We devised a signal-masking bioinformatics pipeline, which yielded a process error rate of 5.8 × 10−4 per base. The pipeline was then applied to analyze 18,434 envelope gene segments (HXB2 7212 to 7601) obtained from 12 incident and 24 chronic patients who had documented HIV-negative and/or -positive tests. The pyrosequencing data were cross-checked by using the single-genome-amplification (SGA) method to independently obtain 302 sequences from 13 patients. Using two genomic biomarkers that probe for the presence of similar sequences, the pyrosequencing platform correctly classified all 12 incident subjects (100% sensitivity) and 23 of 24 chronic subjects (96% specificity). One misclassified subject's chronic infection was correctly classified by conducting the same analysis with SGA data. The biomarkers were statistically associated across the two platforms, suggesting the assay's reproducibility and robustness. Sampling simulations showed that the biomarkers were tolerant of sequencing errors and template resampling, two factors most likely to affect the accuracy of pyrosequencing results. We observed comparable biomarker scores between AIDS and non-AIDS chronic patients (multivariate analysis of variance [MANOVA], P = 0.12), indicating that the stage of HIV disease itself does not affect the classification scheme. The high-throughput genomic HIV incidence marks a significant step toward determining incidence from a single measure in cross-sectional surveys. IMPORTANCE Annual HIV incidence, the number of newly infected individuals within a year, is the key measure of monitoring the epidemic's rise and decline. Developing reliable assays differentiating recent from chronic

High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples.

PubMed

Reiser, Vladimír; Smith, Ryan C; Xue, Jiyan; Kurtz, Marc M; Liu, Rong; Legrand, Cheryl; He, Xuanmin; Yu, Xiang; Wong, Peggy; Hinchcliffe, John S; Tanen, Michael R; Lazar, Gloria; Zieba, Renata; Ichetovkin, Marina; Chen, Zhu; O'Neill, Edward A; Tanaka, Wesley K; Marton, Matthew J; Liao, Jason; Morris, Mark; Hailman, Eric; Tokiwa, George Y; Plump, Andrew S

2011-11-01

With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD). We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured. The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting. The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

A High-Throughput Method for Direct Detection of Therapeutic Oligonucleotide-Induced Gene Silencing In Vivo

PubMed Central

Coles, Andrew H.; Osborn, Maire F.; Alterman, Julia F.; Turanov, Anton A.; Godinho, Bruno M.D.C.; Kennington, Lori; Chase, Kathryn; Aronin, Neil

2016-01-01

Preclinical development of RNA interference (RNAi)-based therapeutics requires a rapid, accurate, and robust method of simultaneously quantifying mRNA knockdown in hundreds of samples. The most well-established method to achieve this is quantitative real-time polymerase chain reaction (qRT-PCR), a labor-intensive methodology that requires sample purification, which increases the potential to introduce additional bias. Here, we describe that the QuantiGene® branched DNA (bDNA) assay linked to a 96-well Qiagen TissueLyser II is a quick and reproducible alternative to qRT-PCR for quantitative analysis of mRNA expression in vivo directly from tissue biopsies. The bDNA assay is a high-throughput, plate-based, luminescence technique, capable of directly measuring mRNA levels from tissue lysates derived from various biological samples. We have performed a systematic evaluation of this technique for in vivo detection of RNAi-based silencing. We show that similar quality data is obtained from purified RNA and tissue lysates. In general, we observe low intra- and inter-animal variability (around 10% for control samples), and high intermediate precision. This allows minimization of sample size for evaluation of oligonucleotide efficacy in vivo. PMID:26595721

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

qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development.

PubMed

Chen, Si; Weddell, Jared; Gupta, Pavan; Conard, Grace; Parkin, James; Imoukhuede, Princess I

2017-01-01

Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

High-throughput analysis of the satellitome illuminates satellite DNA evolution

NASA Astrophysics Data System (ADS)

Ruiz-Ruano, Francisco J.; López-León, María Dolores; Cabrero, Josefa; Camacho, Juan Pedro M.

2016-07-01

Satellite DNA (satDNA) is a major component yet the great unknown of eukaryote genomes and clearly underrepresented in genome sequencing projects. Here we show the high-throughput analysis of satellite DNA content in the migratory locust by means of the bioinformatic analysis of Illumina reads with the RepeatExplorer and RepeatMasker programs. This unveiled 62 satDNA families and we propose the term “satellitome” for the whole collection of different satDNA families in a genome. The finding that satDNAs were present in many contigs of the migratory locust draft genome indicates that they show many genomic locations invisible by fluorescent in situ hybridization (FISH). The cytological pattern of five satellites showing common descent (belonging to the SF3 superfamily) suggests that non-clustered satDNAs can become into clustered through local amplification at any of the many genomic loci resulting from previous dissemination of short satDNA arrays. The fact that all kinds of satDNA (micro- mini- and satellites) can show the non-clustered and clustered states suggests that all these elements are mostly similar, except for repeat length. Finally, the presence of VNTRs in bacteria, showing similar properties to non-clustered satDNAs in eukaryotes, suggests that this kind of tandem repeats show common properties in all living beings.

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID

A high-throughput microtiter plate based method for the determination of peracetic acid and hydrogen peroxide.

PubMed

Putt, Karson S; Pugh, Randall B

2013-01-01

Peracetic acid is gaining usage in numerous industries who have found a myriad of uses for its antimicrobial activity. However, rapid high throughput quantitation methods for peracetic acid and hydrogen peroxide are lacking. Herein, we describe the development of a high-throughput microtiter plate based assay based upon the well known and trusted titration chemical reactions. The adaptation of these titration chemistries to rapid plate based absorbance methods for the sequential determination of hydrogen peroxide specifically and the total amount of peroxides present in solution are described. The results of these methods were compared to those of a standard titration and found to be in good agreement. Additionally, the utility of the developed method is demonstrated through the generation of degradation curves of both peracetic acid and hydrogen peroxide in a mixed solution.

A High-Throughput Microtiter Plate Based Method for the Determination of Peracetic Acid and Hydrogen Peroxide

PubMed Central

Putt, Karson S.; Pugh, Randall B.

2013-01-01

Peracetic acid is gaining usage in numerous industries who have found a myriad of uses for its antimicrobial activity. However, rapid high throughput quantitation methods for peracetic acid and hydrogen peroxide are lacking. Herein, we describe the development of a high-throughput microtiter plate based assay based upon the well known and trusted titration chemical reactions. The adaptation of these titration chemistries to rapid plate based absorbance methods for the sequential determination of hydrogen peroxide specifically and the total amount of peroxides present in solution are described. The results of these methods were compared to those of a standard titration and found to be in good agreement. Additionally, the utility of the developed method is demonstrated through the generation of degradation curves of both peracetic acid and hydrogen peroxide in a mixed solution. PMID:24260173

High Throughput, Polymeric Aqueous Two-Phase Printing of Tumor Spheroids

PubMed Central

Atefi, Ehsan; Lemmo, Stephanie; Fyffe, Darcy; Luker, Gary D.; Tavana, Hossein

2014-01-01

This paper presents a new 3D culture microtechnology for high throughput production of tumor spheroids and validates its utility for screening anti-cancer drugs. We use two immiscible polymeric aqueous solutions and microprint a submicroliter drop of the “patterning” phase containing cells into a bath of the “immersion” phase. Selecting proper formulations of biphasic systems using a panel of biocompatible polymers results in the formation of a round drop that confines cells to facilitate spontaneous formation of a spheroid without any external stimuli. Adapting this approach to robotic tools enables straightforward generation and maintenance of spheroids of well-defined size in standard microwell plates and biochemical analysis of spheroids in situ, which is not possible with existing techniques for spheroid culture. To enable high throughput screening, we establish a phase diagram to identify minimum cell densities within specific volumes of the patterning drop to result in a single spheroid. Spheroids show normal growth over long-term incubation and dose-dependent decrease in cellular viability when treated with drug compounds, but present significant resistance compared to monolayer cultures. The unprecedented ease of implementing this microtechnology and its robust performance will benefit high throughput studies of drug screening against cancer cells with physiologically-relevant 3D tumor models. PMID:25411577

First quantitative high-throughput screen in zebrafish identifies novel pathways for increasing pancreatic β-cell mass

PubMed Central

Wang, Guangliang; Rajpurohit, Surendra K; Delaspre, Fabien; Walker, Steven L; White, David T; Ceasrine, Alexis; Kuruvilla, Rejji; Li, Ruo-jing; Shim, Joong S; Liu, Jun O; Parsons, Michael J; Mumm, Jeff S

2015-01-01

Whole-organism chemical screening can circumvent bottlenecks that impede drug discovery. However, in vivo screens have not attained throughput capacities possible with in vitro assays. We therefore developed a method enabling in vivo high-throughput screening (HTS) in zebrafish, termed automated reporter quantification in vivo (ARQiv). In this study, ARQiv was combined with robotics to fully actualize whole-organism HTS (ARQiv-HTS). In a primary screen, this platform quantified cell-specific fluorescent reporters in >500,000 transgenic zebrafish larvae to identify FDA-approved (Federal Drug Administration) drugs that increased the number of insulin-producing β cells in the pancreas. 24 drugs were confirmed as inducers of endocrine differentiation and/or stimulators of β-cell proliferation. Further, we discovered novel roles for NF-κB signaling in regulating endocrine differentiation and for serotonergic signaling in selectively stimulating β-cell proliferation. These studies demonstrate the power of ARQiv-HTS for drug discovery and provide unique insights into signaling pathways controlling β-cell mass, potential therapeutic targets for treating diabetes. DOI: http://dx.doi.org/10.7554/eLife.08261.001 PMID:26218223

Methods for processing high-throughput RNA sequencing data.

PubMed

Ares, Manuel

2014-11-03

High-throughput sequencing (HTS) methods for analyzing RNA populations (RNA-Seq) are gaining rapid application to many experimental situations. The steps in an RNA-Seq experiment require thought and planning, especially because the expense in time and materials is currently higher and the protocols are far less routine than those used for other high-throughput methods, such as microarrays. As always, good experimental design will make analysis and interpretation easier. Having a clear biological question, an idea about the best way to do the experiment, and an understanding of the number of replicates needed will make the entire process more satisfying. Whether the goal is capturing transcriptome complexity from a tissue or identifying small fragments of RNA cross-linked to a protein of interest, conversion of the RNA to cDNA followed by direct sequencing using the latest methods is a developing practice, with new technical modifications and applications appearing every day. Even more rapid are the development and improvement of methods for analysis of the very large amounts of data that arrive at the end of an RNA-Seq experiment, making considerations regarding reproducibility, validation, visualization, and interpretation increasingly important. This introduction is designed to review and emphasize a pathway of analysis from experimental design through data presentation that is likely to be successful, with the recognition that better methods are right around the corner. © 2014 Cold Spring Harbor Laboratory Press.

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

PubMed

Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

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

PubMed

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

2011-12-15

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

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.

The promise and challenge of high-throughput sequencing of the antibody repertoire

PubMed Central

Georgiou, George; Ippolito, Gregory C; Beausang, John; Busse, Christian E; Wardemann, Hedda; Quake, Stephen R

2014-01-01

Efforts to determine the antibody repertoire encoded by B cells in the blood or lymphoid organs using high-throughput DNA sequencing technologies have been advancing at an extremely rapid pace and are transforming our understanding of humoral immune responses. Information gained from high-throughput DNA sequencing of immunoglobulin genes (Ig-seq) can be applied to detect B-cell malignancies with high sensitivity, to discover antibodies specific for antigens of interest, to guide vaccine development and to understand autoimmunity. Rapid progress in the development of experimental protocols and informatics analysis tools is helping to reduce sequencing artifacts, to achieve more precise quantification of clonal diversity and to extract the most pertinent biological information. That said, broader application of Ig-seq, especially in clinical settings, will require the development of a standardized experimental design framework that will enable the sharing and meta-analysis of sequencing data generated by different laboratories. PMID:24441474

Creation of a small high-throughput screening facility.

PubMed

Flak, Tod

2009-01-01

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

New High Throughput Methods to Estimate Chemical ...

EPA Pesticide Factsheets

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 and screening chemicals. A recent report by the National Research Council of the National Academies, Exposure Science in the 21st Century: A Vision and a Strategy (NRC 2012) laid out a number of applications in chemical evaluation of both toxicity and risk in critical need of quantitative exposure predictions, including screening and prioritization of chemicals for targeted toxicity testing, focused exposure assessments or monitoring studies, and quantification of population vulnerability. Despite these significant needs, for the majority of chemicals (e.g. non-pesticide environmental compounds) there are no or limited estimates of exposure. For example, exposure estimates exist for only 7% of the ToxCast Phase II chemical list. In addition, the data required for generating exposure estimates for large numbers of chemicals is severely lacking (Egeghy et al. 2012). This SAP reviewed the use of EPA's ExpoCast model to rapidly estimate potential chemical exposures for prioritization and screening purposes. The focus was on bounded chemical exposure values for people and the environment for the Endocrine Disruptor Screening Program (EDSP) Universe of Chemicals. In addition to exposure, the SAP

A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture

PubMed Central

Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis

2015-01-01

A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893

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 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 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.

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.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

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.

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

PubMed Central

Kebschull, Justus M.; Zador, Anthony M.

2015-01-01

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

Automated High-Throughput Permethylation for Glycosylation Analysis of Biologics Using MALDI-TOF-MS.

PubMed

Shubhakar, Archana; Kozak, Radoslaw P; Reiding, Karli R; Royle, Louise; Spencer, Daniel I R; Fernandes, Daryl L; Wuhrer, Manfred

2016-09-06

Monitoring glycoprotein therapeutics for changes in glycosylation throughout the drug's life cycle is vital, as glycans significantly modulate the stability, biological activity, serum half-life, safety, and immunogenicity. Biopharma companies are increasingly adopting Quality by Design (QbD) frameworks for measuring, optimizing, and controlling drug glycosylation. Permethylation of glycans prior to analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is a valuable tool for glycan characterization and for screening of large numbers of samples in QbD drug realization. However, the existing protocols for manual permethylation and liquid-liquid extraction (LLE) steps are labor intensive and are thus not practical for high-throughput (HT) studies. Here we present a glycan permethylation protocol, based on 96-well microplates, that has been developed into a kit suitable for HT work. The workflow is largely automated using a liquid handling robot and includes N-glycan release, enrichment of N-glycans, permethylation, and LLE. The kit has been validated according to industry analytical performance guidelines and applied to characterize biopharmaceutical samples, including IgG4 monoclonal antibodies (mAbs) and recombinant human erythropoietin (rhEPO). The HT permethylation enabled glycan characterization and relative quantitation with minimal side reactions: the MALDI-TOF-MS profiles obtained were in good agreement with hydrophilic liquid interaction chromatography (HILIC) and ultrahigh performance liquid chromatography (UHPLC) data. Automated permethylation and extraction of 96 glycan samples was achieved in less than 5 h and automated data acquisition on MALDI-TOF-MS took on average less than 1 min per sample. This automated and HT glycan preparation and permethylation showed to be convenient, fast, and reliable and can be applied for drug glycan profiling and clinical glycan biomarker studies.

High Resolution Melting (HRM) for High-Throughput Genotyping-Limitations and Caveats in Practical Case Studies.

PubMed

Słomka, Marcin; Sobalska-Kwapis, Marta; Wachulec, Monika; Bartosz, Grzegorz; Strapagiel, Dominik

2017-11-03

High resolution melting (HRM) is a convenient method for gene scanning as well as genotyping of individual and multiple single nucleotide polymorphisms (SNPs). This rapid, simple, closed-tube, homogenous, and cost-efficient approach has the capacity for high specificity and sensitivity, while allowing easy transition to high-throughput scale. In this paper, we provide examples from our laboratory practice of some problematic issues which can affect the performance and data analysis of HRM results, especially with regard to reference curve-based targeted genotyping. We present those examples in order of the typical experimental workflow, and discuss the crucial significance of the respective experimental errors and limitations for the quality and analysis of results. The experimental details which have a decisive impact on correct execution of a HRM genotyping experiment include type and quality of DNA source material, reproducibility of isolation method and template DNA preparation, primer and amplicon design, automation-derived preparation and pipetting inconsistencies, as well as physical limitations in melting curve distinction for alternative variants and careful selection of samples for validation by sequencing. We provide a case-by-case analysis and discussion of actual problems we encountered and solutions that should be taken into account by researchers newly attempting HRM genotyping, especially in a high-throughput setup.

High Resolution Melting (HRM) for High-Throughput Genotyping—Limitations and Caveats in Practical Case Studies

PubMed Central

Słomka, Marcin; Sobalska-Kwapis, Marta; Wachulec, Monika; Bartosz, Grzegorz

2017-01-01

High resolution melting (HRM) is a convenient method for gene scanning as well as genotyping of individual and multiple single nucleotide polymorphisms (SNPs). This rapid, simple, closed-tube, homogenous, and cost-efficient approach has the capacity for high specificity and sensitivity, while allowing easy transition to high-throughput scale. In this paper, we provide examples from our laboratory practice of some problematic issues which can affect the performance and data analysis of HRM results, especially with regard to reference curve-based targeted genotyping. We present those examples in order of the typical experimental workflow, and discuss the crucial significance of the respective experimental errors and limitations for the quality and analysis of results. The experimental details which have a decisive impact on correct execution of a HRM genotyping experiment include type and quality of DNA source material, reproducibility of isolation method and template DNA preparation, primer and amplicon design, automation-derived preparation and pipetting inconsistencies, as well as physical limitations in melting curve distinction for alternative variants and careful selection of samples for validation by sequencing. We provide a case-by-case analysis and discussion of actual problems we encountered and solutions that should be taken into account by researchers newly attempting HRM genotyping, especially in a high-throughput setup. PMID:29099791

High-throughput analysis of sulfatides in cerebrospinal fluid using automated extraction and UPLC-MS/MS.

PubMed

Blomqvist, Maria; Borén, Jan; Zetterberg, Henrik; Blennow, Kaj; Månsson, Jan-Eric; Ståhlman, Marcus

2017-07-01

Sulfatides (STs) are a group of glycosphingolipids that are highly expressed in brain. Due to their importance for normal brain function and their potential involvement in neurological diseases, development of accurate and sensitive methods for their determination is needed. Here we describe a high-throughput oriented and quantitative method for the determination of STs in cerebrospinal fluid (CSF). The STs were extracted using a fully automated liquid/liquid extraction method and quantified using ultra-performance liquid chromatography coupled to tandem mass spectrometry. With the high sensitivity of the developed method, quantification of 20 ST species from only 100 μl of CSF was performed. Validation of the method showed that the STs were extracted with high recovery (90%) and could be determined with low inter- and intra-day variation. Our method was applied to a patient cohort of subjects with an Alzheimer's disease biomarker profile. Although the total ST levels were unaltered compared with an age-matched control group, we show that the ratio of hydroxylated/nonhydroxylated STs was increased in the patient cohort. In conclusion, we believe that the fast, sensitive, and accurate method described in this study is a powerful new tool for the determination of STs in clinical as well as preclinical settings. Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.

High-Throughput Screening and Quantitative Chemical Ranking for Sodium Iodide Symporter Inhibitors in ToxCast Phase 1 Chemical Library

EPA Science Inventory

The U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) and Office of Research and Development (ORD) are currently developing high throughput assays to screen chemicals that may alter the thyroid hormone pathway. One potential target in this pathway is the sodium iodide...

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.

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.

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

PubMed

Sallon, C; Soulet, D; Tremblay, Y

2017-12-01

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

High-throughput analysis of sub-visible mAb aggregate particles using automated fluorescence microscopy imaging.

PubMed

Paul, Albert Jesuran; Bickel, Fabian; Röhm, Martina; Hospach, Lisa; Halder, Bettina; Rettich, Nina; Handrick, René; Herold, Eva Maria; Kiefer, Hans; Hesse, Friedemann

2017-07-01

Aggregation of therapeutic proteins is a major concern as aggregates lower the yield and can impact the efficacy of the drug as well as the patient's safety. It can occur in all production stages; thus, it is essential to perform a detailed analysis for protein aggregates. Several methods such as size exclusion high-performance liquid chromatography (SE-HPLC), light scattering, turbidity, light obscuration, and microscopy-based approaches are used to analyze aggregates. None of these methods allows determination of all types of higher molecular weight (HMW) species due to a limited size range. Furthermore, quantification and specification of different HMW species are often not possible. Moreover, automation is a perspective challenge coming up with automated robotic laboratory systems. Hence, there is a need for a fast, high-throughput-compatible method, which can detect a broad size range and enable quantification and classification. We describe a novel approach for the detection of aggregates in the size range 1 to 1000 μm combining fluorescent dyes for protein aggregate labelling and automated fluorescence microscope imaging (aFMI). After appropriate selection of the dye and method optimization, our method enabled us to detect various types of HMW species of monoclonal antibodies (mAbs). Using 10 μmol L -1 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonate (Bis-ANS) in combination with aFMI allowed the analysis of mAb aggregates induced by different stresses occurring during downstream processing, storage, and administration. Validation of our results was performed by SE-HPLC, UV-Vis spectroscopy, and dynamic light scattering. With this new approach, we could not only reliably detect different HMW species but also quantify and classify them in an automated approach. Our method achieves high-throughput requirements and the selection of various fluorescent dyes enables a broad range of applications.

Probabilistic Assessment of High-Throughput Wireless Sensor Networks

PubMed Central

Kim, Robin E.; Mechitov, Kirill; Sim, Sung-Han; Spencer, Billie F.; Song, Junho

2016-01-01

Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved. PMID:27258270

High-Throughput Screening and Quantitative Chemical Ranking for Sodium Iodide Symporter Inhibitors in ToxCast Phase 1 Chemical Library

EPA Science Inventory

The U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) and Office of Research and Development (ORD) are currently developing high throughput assays to screen chemicals that may alter the thyroid hormone pathway. One potential target in this pathway is the sodium iodide sympo...

Development and Validation of an Automated High-Throughput System for Zebrafish In Vivo Screenings

PubMed Central

Virto, Juan M.; Holgado, Olaia; Diez, Maria; Izpisua Belmonte, Juan Carlos; Callol-Massot, Carles

2012-01-01

The zebrafish is a vertebrate model compatible with the paradigms of drug discovery. The small size and transparency of zebrafish embryos make them amenable for the automation necessary in high-throughput screenings. We have developed an automated high-throughput platform for in vivo chemical screenings on zebrafish embryos that includes automated methods for embryo dispensation, compound delivery, incubation, imaging and analysis of the results. At present, two different assays to detect cardiotoxic compounds and angiogenesis inhibitors can be automatically run in the platform, showing the versatility of the system. A validation of these two assays with known positive and negative compounds, as well as a screening for the detection of unknown anti-angiogenic compounds, have been successfully carried out in the system developed. We present a totally automated platform that allows for high-throughput screenings in a vertebrate organism. PMID:22615792

Assessment of the DNA damaging potential of environmental chemicals using a quantitative high-throughput screening approach to measure p53 activation.

PubMed

Witt, Kristine L; Hsieh, Jui-Hua; Smith-Roe, Stephanie L; Xia, Menghang; Huang, Ruili; Zhao, Jinghua; Auerbach, Scott S; Hur, Junguk; Tice, Raymond R

2017-08-01

Genotoxicity potential is a critical component of any comprehensive toxicological profile. Compounds that induce DNA or chromosomal damage often activate p53, a transcription factor essential to cell cycle regulation. Thus, within the US Tox21 Program, we screened a library of ∼10,000 (∼8,300 unique) environmental compounds and drugs for activation of the p53-signaling pathway using a quantitative high-throughput screening assay employing HCT-116 cells (p53 +/+ ) containing a stably integrated β-lactamase reporter gene under control of the p53 response element (p53RE). Cells were exposed (-S9) for 16 hr at 15 concentrations (generally 1.2 nM to 92 μM) three times, independently. Excluding compounds that failed analytical chemistry analysis or were suspected of inducing assay interference, 365 (4.7%) of 7,849 unique compounds were concluded to activate p53. As part of an in-depth characterization of our results, we first compared them with results from traditional in vitro genotoxicity assays (bacterial mutation, chromosomal aberration); ∼15% of known, direct-acting genotoxicants in our library activated the p53RE. Mining the Comparative Toxicogenomics Database revealed that these p53 actives were significantly associated with increased expression of p53 downstream genes involved in DNA damage responses. Furthermore, 53 chemical substructures associated with genotoxicity were enriched in certain classes of p53 actives, for example, anthracyclines (antineoplastics) and vinca alkaloids (tubulin disruptors). Interestingly, the tubulin disruptors manifested unusual nonmonotonic concentration response curves suggesting activity through a unique p53 regulatory mechanism. Through the analysis of our results, we aim to define a role for this assay as one component of a comprehensive toxicological characterization of large compound libraries. Environ. Mol. Mutagen. 58:494-507, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

NASA Astrophysics Data System (ADS)

Reid, Deseree J.; Diesing, Jessica M.; Miller, Matthew A.; Perry, Scott M.; Wales, Jessica A.; Montfort, William R.; Marty, Michael T.

2018-04-01

The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. [Figure not available: see fulltext.

Graph-based signal integration for high-throughput phenotyping

PubMed Central

2012-01-01

Background Electronic Health Records aggregated in Clinical Data Warehouses (CDWs) promise to revolutionize Comparative Effectiveness Research and suggest new avenues of research. However, the effectiveness of CDWs is diminished by the lack of properly labeled data. We present a novel approach that integrates knowledge from the CDW, the biomedical literature, and the Unified Medical Language System (UMLS) to perform high-throughput phenotyping. In this paper, we automatically construct a graphical knowledge model and then use it to phenotype breast cancer patients. We compare the performance of this approach to using MetaMap when labeling records. Results MetaMap's overall accuracy at identifying breast cancer patients was 51.1% (n=428); recall=85.4%, precision=26.2%, and F1=40.1%. Our unsupervised graph-based high-throughput phenotyping had accuracy of 84.1%; recall=46.3%, precision=61.2%, and F1=52.8%. Conclusions We conclude that our approach is a promising alternative for unsupervised high-throughput phenotyping. PMID:23320851

A DNA fingerprinting procedure for ultra high-throughput genetic analysis of insects.

PubMed

Schlipalius, D I; Waldron, J; Carroll, B J; Collins, P J; Ebert, P R

2001-12-01

Existing procedures for the generation of polymorphic DNA markers are not optimal for insect studies in which the organisms are often tiny and background molecular information is often non-existent. We have used a new high throughput DNA marker generation protocol called randomly amplified DNA fingerprints (RAF) to analyse the genetic variability in three separate strains of the stored grain pest, Rhyzopertha dominica. This protocol is quick, robust and reliable even though it requires minimal sample preparation, minute amounts of DNA and no prior molecular analysis of the organism. Arbitrarily selected oligonucleotide primers routinely produced approximately 50 scoreable polymorphic DNA markers, between individuals of three independent field isolates of R. dominica. Multivariate cluster analysis using forty-nine arbitrarily selected polymorphisms generated from a single primer reliably separated individuals into three clades corresponding to their geographical origin. The resulting clades were quite distinct, with an average genetic difference of 37.5 +/- 6.0% between clades and of 21.0 +/- 7.1% between individuals within clades. As a prelude to future gene mapping efforts, we have also assessed the performance of RAF under conditions commonly used in gene mapping. In this analysis, fingerprints from pooled DNA samples accurately and reproducibly reflected RAF profiles obtained from individual DNA samples that had been combined to create the bulked samples.

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

A Fully Automated High-Throughput Zebrafish Behavioral Ototoxicity Assay.

PubMed

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

2017-08-01

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

High-throughput sample processing and sample management; the functional evolution of classical cytogenetic assay towards automation.

PubMed

Ramakumar, Adarsh; Subramanian, Uma; Prasanna, Pataje G S

2015-11-01

High-throughput individual diagnostic dose assessment is essential for medical management of radiation-exposed subjects after a mass casualty. Cytogenetic assays such as the Dicentric Chromosome Assay (DCA) are recognized as the gold standard by international regulatory authorities. DCA is a multi-step and multi-day bioassay. DCA, as described in the IAEA manual, can be used to assess dose up to 4-6 weeks post-exposure quite accurately but throughput is still a major issue and automation is very essential. The throughput is limited, both in terms of sample preparation as well as analysis of chromosome aberrations. Thus, there is a need to design and develop novel solutions that could utilize extensive laboratory automation for sample preparation, and bioinformatics approaches for chromosome-aberration analysis to overcome throughput issues. We have transitioned the bench-based cytogenetic DCA to a coherent process performing high-throughput automated biodosimetry for individual dose assessment ensuring quality control (QC) and quality assurance (QA) aspects in accordance with international harmonized protocols. A Laboratory Information Management System (LIMS) is designed, implemented and adapted to manage increased sample processing capacity, develop and maintain standard operating procedures (SOP) for robotic instruments, avoid data transcription errors during processing, and automate analysis of chromosome-aberrations using an image analysis platform. Our efforts described in this paper intend to bridge the current technological gaps and enhance the potential application of DCA for a dose-based stratification of subjects following a mass casualty. This paper describes one such potential integrated automated laboratory system and functional evolution of the classical DCA towards increasing critically needed throughput. Published by Elsevier B.V.

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.

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 urinalysis of abused drugs based on a SPE-LC-MS/MS method coupled with an in-house developed post-analysis data treatment system.

PubMed

Cheng, Wing-Chi; Yau, Tsan-Sang; Wong, Ming-Kei; Chan, Lai-Ping; Mok, Vincent King-Kuen

2006-10-16

A rapid urinalysis system based on SPE-LC-MS/MS with an in-house post-analysis data management system has been developed for the simultaneous identification and semi-quantitation of opiates (morphine, codeine), methadone, amphetamines (amphetamine, methylamphetamine (MA), 3,4-methylenedioxyamphetamine (MDA) and 3,4-methylenedioxymethamphetamine (MDMA)), 11-benzodiazepines or their metabolites and ketamine. The urine samples are subjected to automated solid phase extraction prior to analysis by LC-MS (Finnigan Surveyor LC connected to a Finnigan LCQ Advantage) fitted with an Alltech Rocket Platinum EPS C-18 column. With a single point calibration at the cut-off concentration for each analyte, simultaneous identification and semi-quantitation for the above mentioned drugs can be achieved in a 10 min run per urine sample. A computer macro-program package was developed to automatically retrieve appropriate data from the analytical data files, compare results with preset values (such as cut-off concentrations, MS matching scores) of each drug being analyzed and generate user-defined Excel reports to indicate all positive and negative results in batch-wise manner for ease of checking. The final analytical results are automatically copied into an Access database for report generation purposes. Through the use of automation in sample preparation, simultaneous identification and semi-quantitation by LC-MS/MS and a tailored made post-analysis data management system, this new urinalysis system significantly improves the quality of results, reduces the post-data treatment time, error due to data transfer and is suitable for high-throughput laboratory in batch-wise operation.

High throughput gene expression profiling: a molecular approach to integrative physiology

PubMed Central

Liang, Mingyu; Cowley, Allen W; Greene, Andrew S

2004-01-01

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high-throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question-driven profiling research has become a feasible complement to the conventional, hypothesis-driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions. PMID:14678487

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

PubMed Central

Bałut, Magdalena; Buckley, Patrick G.; Ochocka, J. Renata; Bartoszewski, Rafał; Crossman, David K.; Messiaen, Ludwine M.; Piotrowski, Arkadiusz

2018-01-01

High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp). PMID:29432475

Searching for resistance genes to Bursaphelenchus xylophilus using high throughput screening

PubMed Central

2012-01-01

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

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

PubMed

Santos, Carla S; Pinheiro, Miguel; Silva, Ana I; Egas, Conceição; Vasconcelos, Marta W

2012-11-07

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

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

PubMed Central

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

2011-01-01

Motivation: High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein–DNA and protein–RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing. Results: We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. Availability: Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxy Contact: eduardo.eyras@upf.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21994224

Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome

PubMed Central

Chaudhuri, Roy R.; Yu, Lu; Kanji, Alpa; Perkins, Timothy T.; Gardner, Paul P.; Choudhary, Jyoti; Maskell, Duncan J.

2011-01-01

Campylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community. PMID:21816880

Ethoscopes: An open platform for high-throughput ethomics.

PubMed

Geissmann, Quentin; Garcia Rodriguez, Luis; Beckwith, Esteban J; French, Alice S; Jamasb, Arian R; Gilestro, Giorgio F

2017-10-01

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

Inertial-ordering-assisted droplet microfluidics for high-throughput single-cell RNA-sequencing.

PubMed

Moon, Hui-Sung; Je, Kwanghwi; Min, Jae-Woong; Park, Donghyun; Han, Kyung-Yeon; Shin, Seung-Ho; Park, Woong-Yang; Yoo, Chang Eun; Kim, Shin-Hyun

2018-02-27

Single-cell RNA-seq reveals the cellular heterogeneity inherent in the population of cells, which is very important in many clinical and research applications. Recent advances in droplet microfluidics have achieved the automatic isolation, lysis, and labeling of single cells in droplet compartments without complex instrumentation. However, barcoding errors occurring in the cell encapsulation process because of the multiple-beads-in-droplet and insufficient throughput because of the low concentration of beads for avoiding multiple-beads-in-a-droplet remain important challenges for precise and efficient expression profiling of single cells. In this study, we developed a new droplet-based microfluidic platform that significantly improved the throughput while reducing barcoding errors through deterministic encapsulation of inertially ordered beads. Highly concentrated beads containing oligonucleotide barcodes were spontaneously ordered in a spiral channel by an inertial effect, which were in turn encapsulated in droplets one-by-one, while cells were simultaneously encapsulated in the droplets. The deterministic encapsulation of beads resulted in a high fraction of single-bead-in-a-droplet and rare multiple-beads-in-a-droplet although the bead concentration increased to 1000 μl -1 , which diminished barcoding errors and enabled accurate high-throughput barcoding. We successfully validated our device with single-cell RNA-seq. In addition, we found that multiple-beads-in-a-droplet, generated using a normal Drop-Seq device with a high concentration of beads, underestimated transcript numbers and overestimated cell numbers. This accurate high-throughput platform can expand the capability and practicality of Drop-Seq in single-cell analysis.

Protocols and programs for high-throughput growth and aging phenotyping in yeast.

PubMed

Jung, Paul P; Christian, Nils; Kay, Daniel P; Skupin, Alexander; Linster, Carole L

2015-01-01

In microorganisms, and more particularly in yeasts, a standard phenotyping approach consists in the analysis of fitness by growth rate determination in different conditions. One growth assay that combines high throughput with high resolution involves the generation of growth curves from 96-well plate microcultivations in thermostated and shaking plate readers. To push the throughput of this method to the next level, we have adapted it in this study to the use of 384-well plates. The values of the extracted growth parameters (lag time, doubling time and yield of biomass) correlated well between experiments carried out in 384-well plates as compared to 96-well plates or batch cultures, validating the higher-throughput approach for phenotypic screens. The method is not restricted to the use of the budding yeast Saccharomyces cerevisiae, as shown by consistent results for other species selected from the Hemiascomycete class. Furthermore, we used the 384-well plate microcultivations to develop and validate a higher-throughput assay for yeast Chronological Life Span (CLS), a parameter that is still commonly determined by a cumbersome method based on counting "Colony Forming Units". To accelerate analysis of the large datasets generated by the described growth and aging assays, we developed the freely available software tools GATHODE and CATHODE. These tools allow for semi-automatic determination of growth parameters and CLS behavior from typical plate reader output files. The described protocols and programs will increase the time- and cost-efficiency of a number of yeast-based systems genetics experiments as well as various types of screens.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs

PubMed Central

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G.; Rigoutsos, Isidore

2017-01-01

Abstract Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. PMID:28108659

Optimizing ultrafast wide field-of-view illumination for high-throughput multi-photon imaging and screening of mutant fluorescent proteins

NASA Astrophysics Data System (ADS)

Stoltzfus, Caleb; Mikhailov, Alexandr; Rebane, Aleksander

2017-02-01

Fluorescence induced by 1wo-photon absorption (2PA) and three-photon absorption (3PA) is becoming an increasingly important tool for deep-tissue microscopy, especially in conjunction with genetically-encoded functional probes such as fluorescent proteins (FPs). Unfortunately, the efficacy of the multi-photon excitation of FPs is notoriously low, and because relations between a biological fluorophore's nonlinear-optical properties and its molecular structure are inherently complex, there are no practical avenues available that would allow boosting the performance of current FPs. Here we describe a novel method, where we apply directed evolution to optimize the 2PA properties of EGFP. Key to the success of this approach consists in high-throughput screening of mutants that would allow selection of variants with promising 2PA and 3PA properties in a broad near-IR excitation range of wavelength. For this purpose, we construct and test a wide field-of-view (FOV), femtosecond imaging system that we then use to quantify the multi-photon excited fluorescence in the 550- 1600 nm range of tens of thousands of E. coli colonies expressing randomly mutated FPs in a standard 10 cm diameter Petri dish configuration. We present a quantitative analysis of different factors that are currently limiting the maximum throughput of the femtosecond multi-photon screening techniques and also report on quantitative measurement of absolute 2PA and 3PA cross sections spectra.

Atlanta I-85 HOV-to-HOT conversion : analysis of vehicle and person throughput.

DOT National Transportation Integrated Search

2013-10-01

This report summarizes the vehicle and person throughput analysis for the High Occupancy Vehicle to High Occupancy Toll Lane : conversion in Atlanta, GA, undertaken by the Georgia Institute of Technology research team. The team tracked changes in : o...

Synthetic Biomaterials to Rival Nature's Complexity-a Path Forward with Combinatorics, High-Throughput Discovery, and High-Content Analysis.

PubMed

Zhang, Douglas; Lee, Junmin; Kilian, Kristopher A

2017-10-01

Cells in tissue receive a host of soluble and insoluble signals in a context-dependent fashion, where integration of these cues through a complex network of signal transduction cascades will define a particular outcome. Biomaterials scientists and engineers are tasked with designing materials that can at least partially recreate this complex signaling milieu towards new materials for biomedical applications. In this progress report, recent advances in high throughput techniques and high content imaging approaches that are facilitating the discovery of efficacious biomaterials are described. From microarrays of synthetic polymers, peptides and full-length proteins, to designer cell culture systems that present multiple biophysical and biochemical cues in tandem, it is discussed how the integration of combinatorics with high content imaging and analysis is essential to extracting biologically meaningful information from large scale cellular screens to inform the design of next generation biomaterials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Recent development in software and automation tools for high-throughput discovery bioanalysis.

PubMed

Shou, Wilson Z; Zhang, Jun

2012-05-01

Bioanalysis with LC-MS/MS has been established as the method of choice for quantitative determination of drug candidates in biological matrices in drug discovery and development. The LC-MS/MS bioanalytical support for drug discovery, especially for early discovery, often requires high-throughput (HT) analysis of large numbers of samples (hundreds to thousands per day) generated from many structurally diverse compounds (tens to hundreds per day) with a very quick turnaround time, in order to provide important activity and liability data to move discovery projects forward. Another important consideration for discovery bioanalysis is its fit-for-purpose quality requirement depending on the particular experiments being conducted at this stage, and it is usually not as stringent as those required in bioanalysis supporting drug development. These aforementioned attributes of HT discovery bioanalysis made it an ideal candidate for using software and automation tools to eliminate manual steps, remove bottlenecks, improve efficiency and reduce turnaround time while maintaining adequate quality. In this article we will review various recent developments that facilitate automation of individual bioanalytical procedures, such as sample preparation, MS/MS method development, sample analysis and data review, as well as fully integrated software tools that manage the entire bioanalytical workflow in HT discovery bioanalysis. In addition, software tools supporting the emerging high-resolution accurate MS bioanalytical approach are also discussed.

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.

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?

Whole Wiskott‑Aldrich syndrome protein gene deletion identified by high throughput sequencing.

PubMed

He, Xiangling; Zou, Runying; Zhang, Bing; You, Yalan; Yang, Yang; Tian, Xin

2017-11-01

Wiskott‑Aldrich syndrome (WAS) is a rare X‑linked recessive immunodeficiency disorder, characterized by thrombocytopenia, small platelets, eczema and recurrent infections associated with increased risk of autoimmunity and malignancy disorders. Mutations in the WAS protein (WASP) gene are responsible for WAS. To date, WASP mutations, including missense/nonsense, splicing, small deletions, small insertions, gross deletions, and gross insertions have been identified in patients with WAS. In addition, WASP‑interacting proteins are suspected in patients with clinical features of WAS, in whom the WASP gene sequence and mRNA levels are normal. The present study aimed to investigate the application of next generation sequencing in definitive diagnosis and clinical therapy for WAS. A 5 month‑old child with WAS who displayed symptoms of thrombocytopenia was examined. Whole exome sequence analysis of genomic DNA showed that the coverage and depth of WASP were extremely low. Quantitative polymerase chain reaction indicated total WASP gene deletion in the proband. In conclusion, high throughput sequencing is useful for the verification of WAS on the genetic profile, and has implications for family planning guidance and establishment of clinical programs.

Analysis of artifacts suggests DGGE should not be used for quantitative diversity analysis.

PubMed

Neilson, Julia W; Jordan, Fiona L; Maier, Raina M

2013-03-01

PCR-denaturing gradient gel electrophoresis (PCR-DGGE) is widely used in microbial ecology for the analysis of comparative community structure. However, artifacts generated during PCR-DGGE of mixed template communities impede the application of this technique to quantitative analysis of community diversity. The objective of the current study was to employ an artificial bacterial community to document and analyze artifacts associated with multiband signatures and preferential template amplification and to highlight their impacts on the use of this technique for quantitative diversity analysis. Six bacterial species (three Betaproteobacteria, two Alphaproteobacteria, and one Firmicutes) were amplified individually and in combinations with primers targeting the V7/V8 region of the 16S rRNA gene. Two of the six isolates produced multiband profiles demonstrating that band number does not correlate directly with α-diversity. Analysis of the multiple bands from one of these isolates confirmed that both bands had identical sequences which lead to the hypothesis that the multiband pattern resulted from two distinct structural conformations of the same amplicon. In addition, consistent preferential amplification was demonstrated following pairwise amplifications of the six isolates. DGGE and real time PCR analysis identified primer mismatch and PCR inhibition due to 16S rDNA secondary structure as the most probable causes of preferential amplification patterns. Reproducible DGGE community profiles generated in this study confirm that PCR-DGGE provides an excellent high-throughput tool for comparative community structure analysis, but that method-specific artifacts preclude its use for accurate comparative diversity analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

High-Performance Single Cell Genetic Analysis Using Microfluidic Emulsion Generator Arrays

PubMed Central

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T.; Mathies, Richard A.

2010-01-01

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex PCR. Microfabricated emulsion generator array (MEGA) devices containing 4, 32 and 96 channels are developed to confer a flexible capability of generating up to 3.4 × 106 nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed, the beads are pooled and rapidly analyzed by multi-color flow cytometry. Using E. coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1:105. This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations. PMID:20192178

High-performance single cell genetic analysis using microfluidic emulsion generator arrays.

PubMed

Zeng, Yong; Novak, Richard; Shuga, Joe; Smith, Martyn T; Mathies, Richard A

2010-04-15

High-throughput genetic and phenotypic analysis at the single cell level is critical to advance our understanding of the molecular mechanisms underlying cellular function and dysfunction. Here we describe a high-performance single cell genetic analysis (SCGA) technique that combines high-throughput microfluidic emulsion generation with single cell multiplex polymerase chain reaction (PCR). Microfabricated emulsion generator array (MEGA) devices containing 4, 32, and 96 channels are developed to confer a flexible capability of generating up to 3.4 x 10(6) nanoliter-volume droplets per hour. Hybrid glass-polydimethylsiloxane diaphragm micropumps integrated into the MEGA chips afford uniform droplet formation, controlled generation frequency, and effective transportation and encapsulation of primer functionalized microbeads and cells. A multiplex single cell PCR method is developed to detect and quantify both wild type and mutant/pathogenic cells. In this method, microbeads functionalized with multiple forward primers targeting specific genes from different cell types are used for solid-phase PCR in droplets. Following PCR, the droplets are lysed and the beads are pooled and rapidly analyzed by multicolor flow cytometry. Using Escherichia coli bacterial cells as a model, we show that this technique enables digital detection of pathogenic E. coli O157 cells in a high background of normal K12 cells, with a detection limit on the order of 1/10(5). This result demonstrates that multiplex SCGA is a promising tool for high-throughput quantitative digital analysis of genetic variation in complex populations.

Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

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

Su, Hui

2001-01-01

Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitablymore » designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm 2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection.« less

Development of automated high throughput single molecular microfluidic detection platform for signal transduction analysis

NASA Astrophysics Data System (ADS)

Huang, Po-Jung; Baghbani Kordmahale, Sina; Chou, Chao-Kai; Yamaguchi, Hirohito; Hung, Mien-Chie; Kameoka, Jun

2016-03-01

Signal transductions including multiple protein post-translational modifications (PTM), protein-protein interactions (PPI), and protein-nucleic acid interaction (PNI) play critical roles for cell proliferation and differentiation that are directly related to the cancer biology. Traditional methods, like mass spectrometry, immunoprecipitation, fluorescence resonance energy transfer, and fluorescence correlation spectroscopy require a large amount of sample and long processing time. "microchannel for multiple-parameter analysis of proteins in single-complex (mMAPS)"we proposed can reduce the process time and sample volume because this system is composed by microfluidic channels, fluorescence microscopy, and computerized data analysis. In this paper, we will present an automated mMAPS including integrated microfluidic device, automated stage and electrical relay for high-throughput clinical screening. Based on this result, we estimated that this automated detection system will be able to screen approximately 150 patient samples in a 24-hour period, providing a practical application to analyze tissue samples in a clinical setting.

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

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...

High-Throughput Analysis of Methylmalonic Acid in Serum, Plasma, and Urine by LC-MS/MS. Method for Analyzing Isomers Without Chromatographic Separation.

PubMed

Kushnir, Mark M; Nelson, Gordon J; Frank, Elizabeth L; Rockwood, Alan L

2016-01-01

Measurement of methylmalonic acid (MMA) plays an important role in the diagnosis of vitamin B12 deficiency. Vitamin B12 is an essential cofactor for the enzymatic carbon rearrangement of methylmalonyl-CoA (MMA-CoA) to succinyl-CoA (SA-CoA), and the lack of vitamin B12 leads to elevated concentrations of MMA. Presence of succinic acid (SA) complicates the analysis because mass spectra of MMA and SA are indistinguishable, when analyzed in negative ion mode and the peaks are difficult to resolve chromatographically. We developed a method for the selective analysis of MMA that exploits the significant difference in fragmentation patterns of di-butyl derivatives of the isomers MMA and SA in a tandem mass spectrometer when analyzed in positive ion mode. Tandem mass spectra of di-butyl derivatives of MMA and SA are very distinct; this allows selective analysis of MMA in the presence of SA. The instrumental analysis is performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in positive ion mode, which is, in combination with selective extraction of acidic compounds, is highly selective for organic acids with multiple carboxyl groups (dicarboxylic, tricarboxylic, etc.). In this method organic acids with a single carboxyl group are virtually undetectable in the mass spectrometer; the only organic acid, other than MMA, that is detected by this method is its isomer, SA. Quantitative measurement of MMA in this method is performed using a deconvolution algorithm, which mathematically resolves the signal corresponding to MMA and does not require chromatographic resolution of the MMA and SA peaks. Because of its high selectivity, the method utilizes isocratic chromatographic separation; reconditioning and re-equilibration of the chromatographic column between injections is unnecessary. The above features of the method allow high-throughput analysis of MMA with analysis cycle time of 1 min.

Rapid and High-Throughput Detection and Quantitation of Radiation Biomarkers in Human and Nonhuman Primates by Differential Mobility Spectrometry-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Chen, Zhidan; Coy, Stephen L.; Pannkuk, Evan L.; Laiakis, Evagelia C.; Hall, Adam B.; Fornace, Albert J.; Vouros, Paul

2016-10-01

Radiation exposure is an important public health issue due to a range of accidental and intentional threats. Prompt and effective large-scale screening and appropriate use of medical countermeasures (MCM) to mitigate radiation injury requires rapid methods for determining the radiation dose. In a number of studies, metabolomics has identified small-molecule biomarkers responding to the radiation dose. Differential mobility spectrometry-mass spectrometry (DMS-MS) has been used for similar compounds for high-throughput small-molecule detection and quantitation. In this study, we show that DMS-MS can detect and quantify two radiation biomarkers, trimethyl-L-lysine (TML) and hypoxanthine. Hypoxanthine is a human and nonhuman primate (NHP) radiation biomarker and metabolic intermediate, whereas TML is a radiation biomarker in humans but not in NHP, which is involved in carnitine synthesis. They have been analyzed by DMS-MS from urine samples after a simple strong cation exchange-solid phase extraction (SCX-SPE). The dramatic suppression of background and chemical noise provided by DMS-MS results in an approximately 10-fold reduction in time, including sample pretreatment time, compared with liquid chromatography-mass spectrometry (LC-MS). DMS-MS quantitation accuracy has been verified by validation testing for each biomarker. Human samples are not yet available, but for hypoxanthine, selected NHP urine samples (pre- and 7-d-post 10 Gy exposure) were analyzed, resulting in a mean change in concentration essentially identical to that obtained by LC-MS (fold-change 2.76 versus 2.59). These results confirm the potential of DMS-MS for field or clinical first-level rapid screening for radiation exposure.

Combinatorial approach toward high-throughput analysis of direct methanol fuel cells.

PubMed

Jiang, Rongzhong; Rong, Charles; Chu, Deryn

2005-01-01

A 40-member array of direct methanol fuel cells (with stationary fuel and convective air supplies) was generated by electrically connecting the fuel cells in series. High-throughput analysis of these fuel cells was realized by fast screening of voltages between the two terminals of a fuel cell at constant current discharge. A large number of voltage-current curves (200) were obtained by screening the voltages through multiple small-current steps. Gaussian distribution was used to statistically analyze the large number of experimental data. The standard deviation (sigma) of voltages of these fuel cells increased linearly with discharge current. The voltage-current curves at various fuel concentrations were simulated with an empirical equation of voltage versus current and a linear equation of sigma versus current. The simulated voltage-current curves fitted the experimental data well. With increasing methanol concentration from 0.5 to 4.0 M, the Tafel slope of the voltage-current curves (at sigma=0.0), changed from 28 to 91 mV.dec-1, the cell resistance from 2.91 to 0.18 Omega, and the power output from 3 to 18 mW.cm-2.

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

Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing.

PubMed

Duez, Marc; Giraud, Mathieu; Herbert, Ryan; Rocher, Tatiana; Salson, Mikaël; Thonier, Florian

2016-01-01

The B and T lymphocytes are white blood cells playing a key role in the adaptive immunity. A part of their DNA, called the V(D)J recombinations, is specific to each lymphocyte, and enables recognition of specific antigenes. Today, with new sequencing techniques, one can get billions of DNA sequences from these regions. With dedicated Repertoire Sequencing (RepSeq) methods, it is now possible to picture population of lymphocytes, and to monitor more accurately the immune response as well as pathologies such as leukemia. Vidjil is an open-source platform for the interactive analysis of high-throughput sequencing data from lymphocyte recombinations. It contains an algorithm gathering reads into clonotypes according to their V(D)J junctions, a web application made of a sample, experiment and patient database and a visualization for the analysis of clonotypes along the time. Vidjil is implemented in C++, Python and Javascript and licensed under the GPLv3 open-source license. Source code, binaries and a public web server are available at http://www.vidjil.org and at http://bioinfo.lille.inria.fr/vidjil. Using the Vidjil web application consists of four steps: 1. uploading a raw sequence file (typically a FASTQ); 2. running RepSeq analysis software; 3. visualizing the results; 4. annotating the results and saving them for future use. For the end-user, the Vidjil web application needs no specific installation and just requires a connection and a modern web browser. Vidjil is used by labs in hematology or immunology for research and clinical applications.

Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing

PubMed Central

Duez, Marc; Herbert, Ryan; Rocher, Tatiana; Salson, Mikaël; Thonier, Florian

2016-01-01

Background The B and T lymphocytes are white blood cells playing a key role in the adaptive immunity. A part of their DNA, called the V(D)J recombinations, is specific to each lymphocyte, and enables recognition of specific antigenes. Today, with new sequencing techniques, one can get billions of DNA sequences from these regions. With dedicated Repertoire Sequencing (RepSeq) methods, it is now possible to picture population of lymphocytes, and to monitor more accurately the immune response as well as pathologies such as leukemia. Methods and Results Vidjil is an open-source platform for the interactive analysis of high-throughput sequencing data from lymphocyte recombinations. It contains an algorithm gathering reads into clonotypes according to their V(D)J junctions, a web application made of a sample, experiment and patient database and a visualization for the analysis of clonotypes along the time. Vidjil is implemented in C++, Python and Javascript and licensed under the GPLv3 open-source license. Source code, binaries and a public web server are available at http://www.vidjil.org and at http://bioinfo.lille.inria.fr/vidjil. Using the Vidjil web application consists of four steps: 1. uploading a raw sequence file (typically a FASTQ); 2. running RepSeq analysis software; 3. visualizing the results; 4. annotating the results and saving them for future use. For the end-user, the Vidjil web application needs no specific installation and just requires a connection and a modern web browser. Vidjil is used by labs in hematology or immunology for research and clinical applications. PMID:27835690

Ethoscopes: An open platform for high-throughput ethomics

PubMed Central

Geissmann, Quentin; Garcia Rodriguez, Luis; Beckwith, Esteban J.; French, Alice S.; Jamasb, Arian R.

2017-01-01

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope. PMID:29049280

A simple, specific high-throughput enzyme-linked immunosorbent assay (ELISA) for quantitative determination of melatonin in cell culture medium.

PubMed

Li, Ye; Cassone, Vincent M

2015-09-01

A simple, specific, high-throughput enzyme-linked immunosorbent assay (ELISA) for quantitative determination of melatonin was developed for directly measuring melatonin in cell culture medium with 10% FBS. This assay adopts a commercial monoclonal melatonin antibody and melatonin-HRP conjugate, so it can be applied in multiple labs rapidly with low cost compared with commercial RIA and ELISA kits. In addition, the procedure is much simpler with only four steps: 1) sample/conjugate incubation, 2) plate washing, 3) TMB color reaction and 4) reading of results. The standards of the assay cover a wide working range from 100 pg/mL to 10 ng/mL. The sensitivity was 68 pg/mL in cell culture medium with 10% FBS and 26 pg/mL in PBS with as little as 25 μL sample volume. The recovery of melatonin from cell culture medium was 101.0%. The principal cross-reacting compound was 5-methoxytryptophol (0.1%). The variation coefficients of the assay, within and between runs, ranged between 6.68% and 15.76% in cell culture medium. The mean linearity of a series diluted cell culture medium sample was 105% (CV=5%), ranging between 98% and 111%, y=5.5263x+0.0646, R(2)=0.99. The assay enables small research and teaching labs to reliably measure this important neurohormone. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Quantitative analysis of RNA-protein interactions on a massively parallel array for mapping biophysical and evolutionary landscapes

PubMed Central

Buenrostro, Jason D.; Chircus, Lauren M.; Araya, Carlos L.; Layton, Curtis J.; Chang, Howard Y.; Snyder, Michael P.; Greenleaf, William J.

2015-01-01

RNA-protein interactions drive fundamental biological processes and are targets for molecular engineering, yet quantitative and comprehensive understanding of the sequence determinants of affinity remains limited. Here we repurpose a high-throughput sequencing instrument to quantitatively measure binding and dissociation of MS2 coat protein to >107 RNA targets generated on a flow-cell surface by in situ transcription and inter-molecular tethering of RNA to DNA. We decompose the binding energy contributions from primary and secondary RNA structure, finding that differences in affinity are often driven by sequence-specific changes in association rates. By analyzing the biophysical constraints and modeling mutational paths describing the molecular evolution of MS2 from low- to high-affinity hairpins, we quantify widespread molecular epistasis, and a long-hypothesized structure-dependent preference for G:U base pairs over C:A intermediates in evolutionary trajectories. Our results suggest that quantitative analysis of RNA on a massively parallel array (RNAMaP) relationships across molecular variants. PMID:24727714

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...

A high-throughput core sampling device for the evaluation of maize stalk composition

PubMed Central

2012-01-01

Background A major challenge in the identification and development of superior feedstocks for the production of second generation biofuels is the rapid assessment of biomass composition in a large number of samples. Currently, highly accurate and precise robotic analysis systems are available for the evaluation of biomass composition, on a large number of samples, with a variety of pretreatments. However, the lack of an inexpensive and high-throughput process for large scale sampling of biomass resources is still an important limiting factor. Our goal was to develop a simple mechanical maize stalk core sampling device that can be utilized to collect uniform samples of a dimension compatible with robotic processing and analysis, while allowing the collection of hundreds to thousands of samples per day. Results We have developed a core sampling device (CSD) to collect maize stalk samples compatible with robotic processing and analysis. The CSD facilitates the collection of thousands of uniform tissue cores consistent with high-throughput analysis required for breeding, genetics, and production studies. With a single CSD operated by one person with minimal training, more than 1,000 biomass samples were obtained in an eight-hour period. One of the main advantages of using cores is the high level of homogeneity of the samples obtained and the minimal opportunity for sample contamination. In addition, the samples obtained with the CSD can be placed directly into a bath of ice, dry ice, or liquid nitrogen maintaining the composition of the biomass sample for relatively long periods of time. Conclusions The CSD has been demonstrated to successfully produce homogeneous stalk core samples in a repeatable manner with a throughput substantially superior to the currently available sampling methods. Given the variety of maize developmental stages and the diversity of stalk diameter evaluated, it is expected that the CSD will have utility for other bioenergy crops as well. PMID

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.

GlycoExtractor: a web-based interface for high throughput processing of HPLC-glycan data.

PubMed

Artemenko, Natalia V; Campbell, Matthew P; Rudd, Pauline M

2010-04-05

Recently, an automated high-throughput HPLC platform has been developed that can be used to fully sequence and quantify low concentrations of N-linked sugars released from glycoproteins, supported by an experimental database (GlycoBase) and analytical tools (autoGU). However, commercial packages that support the operation of HPLC instruments and data storage lack platforms for the extraction of large volumes of data. The lack of resources and agreed formats in glycomics is now a major limiting factor that restricts the development of bioinformatic tools and automated workflows for high-throughput HPLC data analysis. GlycoExtractor is a web-based tool that interfaces with a commercial HPLC database/software solution to facilitate the extraction of large volumes of processed glycan profile data (peak number, peak areas, and glucose unit values). The tool allows the user to export a series of sample sets to a set of file formats (XML, JSON, and CSV) rather than a collection of disconnected files. This approach not only reduces the amount of manual refinement required to export data into a suitable format for data analysis but also opens the field to new approaches for high-throughput data interpretation and storage, including biomarker discovery and validation and monitoring of online bioprocessing conditions for next generation biotherapeutics.

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.

Development of Glycoprotein Capture-Based Label-Free Method for the High-throughput Screening of Differential Glycoproteins in Hepatocellular Carcinoma*

PubMed Central

Chen, Rui; Tan, Yexiong; Wang, Min; Wang, Fangjun; Yao, Zhenzhen; Dong, Liwei; Ye, Mingliang; Wang, Hongyang; Zou, Hanfa

2011-01-01

A robust, reproducible, and high throughput method was developed for the relative quantitative analysis of glycoprotein abundances in human serum. Instead of quantifying glycoproteins by glycopeptides in conventional quantitative glycoproteomics, glycoproteins were quantified by nonglycosylated peptides derived from the glycoprotein digest, which consists of the capture of glycoproteins in serum samples and the release of nonglycopeptides by trypsin digestion of captured glycoproteins followed by two-dimensional liquid chromatography-tandem MS analysis of released peptides. Protein quantification was achieved by comparing the spectrum counts of identified nonglycosylated peptides of glycoproteins between different samples. This method was demonstrated to have almost the same specificity and sensitivity in glycoproteins quantification as capture at glycopeptides level. The differential abundance of proteins present at as low as nanogram per milliliter levels was quantified with high confidence. The established method was applied to the analysis of human serum samples from healthy people and patients with hepatocellular carcinoma (HCC) to screen differential glycoproteins in HCC. Thirty eight glycoproteins were found with substantial concentration changes between normal and HCC serum samples, including α-fetoprotein, the only clinically used marker for HCC diagnosis. The abundance changes of three glycoproteins, i.e. galectin-3 binding protein, insulin-like growth factor binding protein 3, and thrombospondin 1, which were associated with the development of HCC, were further confirmed by enzyme-linked immunosorbent assay. In conclusion, the developed method was an effective approach to quantitatively analyze glycoproteins in human serum and could be further applied in the biomarker discovery for HCC and other cancers. PMID:21474793

Scaling and automation of a high-throughput single-cell-derived tumor sphere assay chip.

PubMed

Cheng, Yu-Heng; Chen, Yu-Chih; Brien, Riley; Yoon, Euisik

2016-10-07

Recent research suggests that cancer stem-like cells (CSCs) are the key subpopulation for tumor relapse and metastasis. Due to cancer plasticity in surface antigen and enzymatic activity markers, functional tumorsphere assays are promising alternatives for CSC identification. To reliably quantify rare CSCs (1-5%), thousands of single-cell suspension cultures are required. While microfluidics is a powerful tool in handling single cells, previous works provide limited throughput and lack automatic data analysis capability required for high-throughput studies. In this study, we present the scaling and automation of high-throughput single-cell-derived tumor sphere assay chips, facilitating the tracking of up to ∼10 000 cells on a chip with ∼76.5% capture rate. The presented cell capture scheme guarantees sampling a representative population from the bulk cells. To analyze thousands of single-cells with a variety of fluorescent intensities, a highly adaptable analysis program was developed for cell/sphere counting and size measurement. Using a Pluronic® F108 (poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol)) coating on polydimethylsiloxane (PDMS), a suspension culture environment was created to test a controversial hypothesis: whether larger or smaller cells are more stem-like defined by the capability to form single-cell-derived spheres. Different cell lines showed different correlations between sphere formation rate and initial cell size, suggesting heterogeneity in pathway regulation among breast cancer cell lines. More interestingly, by monitoring hundreds of spheres, we identified heterogeneity in sphere growth dynamics, indicating the cellular heterogeneity even within CSCs. These preliminary results highlight the power of unprecedented high-throughput and automation in CSC studies.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.

PubMed

Shigematsu, Megumi; Honda, Shozo; Loher, Phillipe; Telonis, Aristeidis G; Rigoutsos, Isidore; Kirino, Yohei

2017-05-19

Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

High-throughput microfluidics to control and measure signaling dynamics in single yeast cells

PubMed Central

Hansen, Anders S.; Hao, Nan; O'Shea, Erin K.

2015-01-01

Microfluidics coupled to quantitative time-lapse fluorescence microscopy is transforming our ability to control, measure, and understand signaling dynamics in single living cells. Here we describe a pipeline that incorporates multiplexed microfluidic cell culture, automated programmable fluid handling for cell perturbation, quantitative time-lapse microscopy, and computational analysis of time-lapse movies. We illustrate how this setup can be used to control the nuclear localization of the budding yeast transcription factor Msn2. Using this protocol, we generate oscillations of Msn2 localization and measure the dynamic gene expression response of individual genes in single cells. The protocol allows a single researcher to perform up to 20 different experiments in a single day, whilst collecting data for thousands of single cells. Compared to other protocols, the present protocol is relatively easy to adopt and higher-throughput. The protocol can be widely used to control and monitor single-cell signaling dynamics in other signal transduction systems in microorganisms. PMID:26158443

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

Disposable MoS2-Arrayed MALDI MS Chip for High-Throughput and Rapid Quantification of Sulfonamides in Multiple Real Samples.

PubMed

Zhao, Yaju; Tang, Minmin; Liao, Qiaobo; Li, Zhoumin; Li, Hui; Xi, Kai; Tan, Li; Zhang, Mei; Xu, Danke; Chen, Hong-Yuan

2018-04-27

In this work, we demonstrate, for the first time, the development of a disposable MoS 2 -arrayed matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) chip combined with an immunoaffinity enrichment method for high-throughput, rapid, and simultaneous quantitation of multiple sulfonamides (SAs). The disposable MALDI MS chip was designed and fabricated by MoS 2 array formation on a commercial indium tin oxide (ITO) glass slide. A series of SAs were analyzed, and clear deprotonated signals were obtained in negative-ion mode. Compared with MoS 2 -arrayed commercial steel plate, the prepared MALDI MS chip exhibited comparable LDI efficiency, providing a good alternative and disposable substrate for MALDI MS analysis. Furthermore, internal standard (IS) was previously deposited onto the MoS 2 array to simplify the experimental process for MALDI MS quantitation. 96 sample spots could be analyzed within 10 min in one single chip to perform quantitative analysis, recovery studies, and real foodstuff detection. Upon targeted extraction and enrichment by antibody conjugated magnetic beads, five SAs were quantitatively determined by the IS-first method with the linear range of 0.5-10 ng/mL ( R 2 > 0.990). Good recoveries and repeatability were obtained for spiked pork, egg, and milk samples. SAs in several real foodstuffs were successfully identified and quantified. The developed method may provide a promising tool for the routine analysis of antibiotic residues in real samples.

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.

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.

High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu-Chieh; Böhm, Konrad J; Tuckermann, Jan; Ploubidou, Aspasia

2016-07-01

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

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

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...