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.

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

EPA Science Inventory

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

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

EPA Science Inventory

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

Genomics tools available for unravelling mechanisms underlying agronomical traits in strawberry with more to come

USDA-ARS?s Scientific Manuscript database

In the last few years, high-throughput genomics promised to bridge the gap between plant physiology and plant sciences. In addition, high-throughput genotyping technologies facilitate marker-based selection for better performing genotypes. In strawberry, Fragaria vesca was the first reference sequen...

Diving deeper into Zebrafish development of social behavior: analyzing high resolution data.

PubMed

Buske, Christine; Gerlai, Robert

2014-08-30

Vertebrate model organisms have been utilized in high throughput screening but only with substantial cost and human capital investment. The zebrafish is a vertebrate model species that is a promising and cost effective candidate for efficient high throughput screening. Larval zebrafish have already been successfully employed in this regard (Lessman, 2011), but adult zebrafish also show great promise. High throughput screening requires the use of a large number of subjects and collection of substantial amount of data. Collection of data is only one of the demanding aspects of screening. However, in most screening approaches that involve behavioral data the main bottleneck that slows throughput is the time consuming aspect of analysis of the collected data. Some automated analytical tools do exist, but often they only work for one subject at a time, eliminating the possibility of fully utilizing zebrafish as a screening tool. This is a particularly important limitation for such complex phenotypes as social behavior. Testing multiple fish at a time can reveal complex social interactions but it may also allow the identification of outliers from a group of mutagenized or pharmacologically treated fish. Here, we describe a novel method using a custom software tool developed within our laboratory, which enables tracking multiple fish, in combination with a sophisticated analytical approach for summarizing and analyzing high resolution behavioral data. This paper focuses on the latter, the analytic tool, which we have developed using the R programming language and environment for statistical computing. We argue that combining sophisticated data collection methods with appropriate analytical tools will propel zebrafish into the future of neurobehavioral genetic research. Copyright © 2014. Published by Elsevier B.V.

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

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

Leung, Elo; Huang, Amy; Cadag, Eithon

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

DOE PAGES

Leung, Elo; Huang, Amy; Cadag, Eithon; ...

2016-01-20

In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

The High-Throughput Stochastic Human Exposure and Dose Simulation Model (SHEDS-HT) & The Chemical and Products Database (CPDat)

EPA Science Inventory

The Stochastic Human Exposure and Dose Simulation Model – High-Throughput (SHEDS-HT) is a U.S. Environmental Protection Agency research tool for predicting screening-level (low-tier) exposures to chemicals in consumer products. This course will present an overview of this m...

High Throughput PBTK: Evaluating EPA’s Open-Source Data and Tools for Dosimetry and Exposure Reconstruction

EPA Science Inventory

Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics (TK). While HTS generates in vitro bioactivity d...

A Biologically Informed Framework for the Analysis of the PPAR Signaling Pathway using a Bayesian Network

EPA Science Inventory

The US EPA’s ToxCastTM program seeks to combine advances in high-throughput screening technology with methodologies from statistics and computer science to develop high-throughput decision support tools for assessing chemical hazard and risk. To develop new methods of analysis of...

ToxCast Assay Network (TCAN) Viewer: A Visualization Tool for High-throughput Assay Chemical Data (SOT)

EPA Science Inventory

USEPA’s ToxCast program has generated high-throughput bioactivity screening (HTS) data on thousands of chemicals. The ToxCast program has described and annotated the HTS assay battery with respect to assay design and target information (e.g., gene target). Recent stakeholder and ...

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.

Mosquitoes meet microfluidics: High-throughput microfluidic tools for insect-parasite ecology in field conditions

NASA Astrophysics Data System (ADS)

Prakash, Manu; Mukundarajan, Haripriya

2013-11-01

A simple bite from an insect is the transmission mechanism for many deadly diseases worldwide--including malaria, yellow fever, west nile and dengue. Very little is known about how populations of numerous insect species and disease-causing parasites interact in their natural habitats due to a lack of measurement techniques. At present, vector surveillance techniques involve manual capture by using humans as live bait, which is hard to justify on ethical grounds. Individual mosquitoes are manually dissected to isolate salivary glands to detect sporozites. With typical vector infection rates being very low even in endemic areas, it is almost impossible to get an accurate picture of disease distribution, in both space and time. Here we present novel high-throughput microfluidic tools for vector surveillance, specifically mosquitoes. A two-dimensional high density array with baits provide an integrated platform for multiplex PCR for detection of both vector and parasite species. Combining techniques from engineering and field ecology, methods and tools developed here will enable high-throughput measurement of infection rates for a number of diseases in mosquito populations in field conditions. Pew Foundation.

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.

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

Annotare--a tool for annotating high-throughput biomedical investigations and resulting data.

PubMed

Shankar, Ravi; Parkinson, Helen; Burdett, Tony; Hastings, Emma; Liu, Junmin; Miller, Michael; Srinivasa, Rashmi; White, Joseph; Brazma, Alvis; Sherlock, Gavin; Stoeckert, Christian J; Ball, Catherine A

2010-10-01

Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis. Annotare is available from http://code.google.com/p/annotare/ under the terms of the open-source MIT License (http://www.opensource.org/licenses/mit-license.php). It has been tested on both Mac and Windows.

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.

Improved Data Analysis Tools for the Thermal Emission Spectrometer

NASA Astrophysics Data System (ADS)

Rodriguez, K.; Laura, J.; Fergason, R.; Bogle, R.

2017-06-01

We plan to stand up three different database systems for testing of a new datastore for MGS TES data allowing for more accessible tools supporting high throughput data analysis on the high-dimensionality hyperspectral data set.

Computational Toxicology as Implemented by the U.S. EPA: Providing High Throughput Decision Support Tools for Screening and Assessing Chemical Exposure, Hazard and Risk

EPA Science Inventory

Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environ...

DOSE RESPONSE FROM HIGH THROUGHPUT GENE EXPRESSION STUDIES AND THE INFLUENCE OF TIME AND CELL LINE ON INFERRED MODE OF ACTION BY ONTOLOGIC ENRICHMENT (SOT)

EPA Science Inventory

Gene expression with ontologic enrichment and connectivity mapping tools is widely used to infer modes of action (MOA) for therapeutic drugs. Despite progress in high-throughput (HT) genomic systems, strategies suitable to identify industrial chemical MOA are needed. The L1000 is...

A high-throughput colorimetric assay for glucose detection based on glucose oxidase-catalyzed enlargement of gold nanoparticles

NASA Astrophysics Data System (ADS)

Xiong, Yanmei; Zhang, Yuyan; Rong, Pengfei; Yang, Jie; Wang, Wei; Liu, Dingbin

2015-09-01

We developed a simple high-throughput colorimetric assay to detect glucose based on the glucose oxidase (GOx)-catalysed enlargement of gold nanoparticles (AuNPs). Compared with the currently available glucose kit method, the AuNP-based assay provides higher clinical sensitivity at lower cost, indicating its great potential to be a powerful tool for clinical screening of glucose.We developed a simple high-throughput colorimetric assay to detect glucose based on the glucose oxidase (GOx)-catalysed enlargement of gold nanoparticles (AuNPs). Compared with the currently available glucose kit method, the AuNP-based assay provides higher clinical sensitivity at lower cost, indicating its great potential to be a powerful tool for clinical screening of glucose. Electronic supplementary information (ESI) available: Experimental section and additional figures. See DOI: 10.1039/c5nr03758a

THE RABIT: A RAPID AUTOMATED BIODOSIMETRY TOOL FOR RADIOLOGICAL TRIAGE

PubMed Central

Garty, Guy; Chen, Youhua; Salerno, Alessio; Turner, Helen; Zhang, Jian; Lyulko, Oleksandra; Bertucci, Antonella; Xu, Yanping; Wang, Hongliang; Simaan, Nabil; Randers-Pehrson, Gerhard; Yao, Y. Lawrence; Amundson, Sally A.; Brenner, David J.

2010-01-01

In response to the recognized need for high throughput biodosimetry methods for use after large scale radiological events, a logical approach is complete automation of standard biodosimetric assays that are currently performed manually. We describe progress to date on the RABIT (Rapid Automated BIodosimetry Tool), designed to score micronuclei or γ-H2AX fluorescence in lymphocytes derived from a single drop of blood from a fingerstick. The RABIT system is designed to be completely automated, from the input of the capillary blood sample into the machine, to the output of a dose estimate. Improvements in throughput are achieved through use of a single drop of blood, optimization of the biological protocols for in-situ analysis in multi-well plates, implementation of robotic plate and liquid handling, and new developments in high-speed imaging. Automating well-established bioassays represents a promising approach to high-throughput radiation biodosimetry, both because high throughputs can be achieved, but also because the time to deployment is potentially much shorter than for a new biological assay. Here we describe the development of each of the individual modules of the RABIT system, and show preliminary data from key modules. Ongoing is system integration, followed by calibration and validation. PMID:20065685

Annotare—a tool for annotating high-throughput biomedical investigations and resulting data

PubMed Central

Shankar, Ravi; Parkinson, Helen; Burdett, Tony; Hastings, Emma; Liu, Junmin; Miller, Michael; Srinivasa, Rashmi; White, Joseph; Brazma, Alvis; Sherlock, Gavin; Stoeckert, Christian J.; Ball, Catherine A.

2010-01-01

Summary: Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis. Availability and Implementation: Annotare is available from http://code.google.com/p/annotare/ under the terms of the open-source MIT License (http://www.opensource.org/licenses/mit-license.php). It has been tested on both Mac and Windows. Contact: rshankar@stanford.edu PMID:20733062

New Tools For Understanding Microbial Diversity Using High-throughput Sequence Data

NASA Astrophysics Data System (ADS)

Knight, R.; Hamady, M.; Liu, Z.; Lozupone, C.

2007-12-01

High-throughput sequencing techniques such as 454 are straining the limits of tools traditionally used to build trees, choose OTUs, and perform other essential sequencing tasks. We have developed a workflow for phylogenetic analysis of large-scale sequence data sets that combines existing tools, such as the Arb phylogeny package and the NAST multiple sequence alignment tool, with new methods for choosing and clustering OTUs and for performing phylogenetic community analysis with UniFrac. This talk discusses the cyberinfrastructure we are developing to support the human microbiome project, and the application of these workflows to analyze very large data sets that contrast the gut microbiota with a range of physical environments. These tools will ultimately help to define core and peripheral microbiomes in a range of environments, and will allow us to understand the physical and biotic factors that contribute most to differences in microbial diversity.

GeneSCF: a real-time based functional enrichment tool with support for multiple organisms.

PubMed

Subhash, Santhilal; Kanduri, Chandrasekhar

2016-09-13

High-throughput technologies such as ChIP-sequencing, RNA-sequencing, DNA sequencing and quantitative metabolomics generate a huge volume of data. Researchers often rely on functional enrichment tools to interpret the biological significance of the affected genes from these high-throughput studies. However, currently available functional enrichment tools need to be updated frequently to adapt to new entries from the functional database repositories. Hence there is a need for a simplified tool that can perform functional enrichment analysis by using updated information directly from the source databases such as KEGG, Reactome or Gene Ontology etc. In this study, we focused on designing a command-line tool called GeneSCF (Gene Set Clustering based on Functional annotations), that can predict the functionally relevant biological information for a set of genes in a real-time updated manner. It is designed to handle information from more than 4000 organisms from freely available prominent functional databases like KEGG, Reactome and Gene Ontology. We successfully employed our tool on two of published datasets to predict the biologically relevant functional information. The core features of this tool were tested on Linux machines without the need for installation of more dependencies. GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

PubMed Central

Yang, Wanneng; Guo, Zilong; Huang, Chenglong; Duan, Lingfeng; Chen, Guoxing; Jiang, Ni; Fang, Wei; Feng, Hui; Xie, Weibo; Lian, Xingming; Wang, Gongwei; Luo, Qingming; Zhang, Qifa; Liu, Qian; Xiong, Lizhong

2014-01-01

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. PMID:25295980

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

PubMed

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

2013-02-01

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

Toxicokinetic and Dosimetry Modeling Tools for Exposure ...

EPA Pesticide Factsheets

New technologies and in vitro testing approaches have been valuable additions to risk assessments that have historically relied solely on in vivo test results. Compared to in vivo methods, in vitro high throughput screening (HTS) assays are less expensive, faster and can provide mechanistic insights on chemical action. However, extrapolating from in vitro chemical concentrations to target tissue or blood concentrations in vivo is fraught with uncertainties, and modeling is dependent upon pharmacokinetic variables not measured in in vitro assays. To address this need, new tools have been created for characterizing, simulating, and evaluating chemical toxicokinetics. Physiologically-based pharmacokinetic (PBPK) models provide estimates of chemical exposures that produce potentially hazardous tissue concentrations, while tissue microdosimetry PK models relate whole-body chemical exposures to cell-scale concentrations. These tools rely on high-throughput in vitro measurements, and successful methods exist for pharmaceutical compounds that determine PK from limited in vitro measurements and chemical structure-derived property predictions. These high throughput (HT) methods provide a more rapid and less resource–intensive alternative to traditional PK model development. We have augmented these in vitro data with chemical structure-based descriptors and mechanistic tissue partitioning models to construct HTPBPK models for over three hundred environmental and pharmace

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy.

PubMed

Dreyer, Florian S; Cantone, Martina; Eberhardt, Martin; Jaitly, Tanushree; Walter, Lisa; Wittmann, Jürgen; Gupta, Shailendra K; Khan, Faiz M; Wolkenhauer, Olaf; Pützer, Brigitte M; Jäck, Hans-Martin; Heinzerling, Lucie; Vera, Julio

2018-06-01

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients. Copyright © 2018 Elsevier B.V. All rights reserved.

GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies

PubMed Central

Zhang, Bing; Schmoyer, Denise; Kirov, Stefan; Snoddy, Jay

2004-01-01

Background Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets. Results We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at . Conclusion GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets. PMID:14975175

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.

A comparison of high-throughput techniques for assaying circadian rhythms in plants.

PubMed

Tindall, Andrew J; Waller, Jade; Greenwood, Mark; Gould, Peter D; Hartwell, James; Hall, Anthony

2015-01-01

Over the last two decades, the development of high-throughput techniques has enabled us to probe the plant circadian clock, a key coordinator of vital biological processes, in ways previously impossible. With the circadian clock increasingly implicated in key fitness and signalling pathways, this has opened up new avenues for understanding plant development and signalling. Our tool-kit has been constantly improving through continual development and novel techniques that increase throughput, reduce costs and allow higher resolution on the cellular and subcellular levels. With circadian assays becoming more accessible and relevant than ever to researchers, in this paper we offer a review of the techniques currently available before considering the horizons in circadian investigation at ever higher throughputs and resolutions.

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

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

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

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

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

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

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

DOE PAGES

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

2017-03-28

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

Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data.

PubMed

Devailly, Guillaume; Mantsoki, Anna; Joshi, Anagha

2016-11-01

Better protocols and decreasing costs have made high-throughput sequencing experiments now accessible even to small experimental laboratories. However, comparing one or few experiments generated by an individual lab to the vast amount of relevant data freely available in the public domain might be limited due to lack of bioinformatics expertise. Though several tools, including genome browsers, allow such comparison at a single gene level, they do not provide a genome-wide view. We developed Heat*seq, a web-tool that allows genome scale comparison of high throughput experiments chromatin immuno-precipitation followed by sequencing, RNA-sequencing and Cap Analysis of Gene Expression) provided by a user, to the data in the public domain. Heat*seq currently contains over 12 000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualize user experiments. High quality figures and tables are produced and can be downloaded in multiple formats. Web application: http://www.heatstarseq.roslin.ed.ac.uk/ Source code: https://github.com/gdevailly CONTACT: Guillaume.Devailly@roslin.ed.ac.uk or Anagha.Joshi@roslin.ed.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

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 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

Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

PubMed

Anandkumar, Balakrishna; Haga, Steve W; Wu, Hui-Fen

2014-02-01

The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

GenomicTools: a computational platform for developing high-throughput analytics in genomics.

PubMed

Tsirigos, Aristotelis; Haiminen, Niina; Bilal, Erhan; Utro, Filippo

2012-01-15

Recent advances in sequencing technology have resulted in the dramatic increase of sequencing data, which, in turn, requires efficient management of computational resources, such as computing time, memory requirements as well as prototyping of computational pipelines. We present GenomicTools, a flexible computational platform, comprising both a command-line set of tools and a C++ API, for the analysis and manipulation of high-throughput sequencing data such as DNA-seq, RNA-seq, ChIP-seq and MethylC-seq. GenomicTools implements a variety of mathematical operations between sets of genomic regions thereby enabling the prototyping of computational pipelines that can address a wide spectrum of tasks ranging from pre-processing and quality control to meta-analyses. Additionally, the GenomicTools platform is designed to analyze large datasets of any size by minimizing memory requirements. In practical applications, where comparable, GenomicTools outperforms existing tools in terms of both time and memory usage. The GenomicTools platform (version 2.0.0) was implemented in C++. The source code, documentation, user manual, example datasets and scripts are available online at http://code.google.com/p/ibm-cbc-genomic-tools.

Microfluidics in microbiology: putting a magnifying glass on microbes.

PubMed

Siddiqui, Sanya; Tufenkji, Nathalie; Moraes, Christopher

2016-09-12

Microfluidic technologies enable unique studies in the field of microbiology to facilitate our understanding of microorganisms. Using miniaturized and high-throughput experimental capabilities in microfluidics, devices with controlled microenvironments can be created for microbial studies in research fields such as healthcare and green energy. In this research highlight, we describe recently developed tools for diagnostic assays, high-throughput mutant screening, and the study of human disease development as well as a future outlook on microbes for renewable energy.

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

Detection of IgG aggregation by a high throughput method based on extrinsic fluorescence.

PubMed

He, Feng; Phan, Duke H; Hogan, Sabine; Bailey, Robert; Becker, Gerald W; Narhi, Linda O; Razinkov, Vladimir I

2010-06-01

The utility of extrinsic fluorescence as a tool for high throughput detection of monoclonal antibody aggregates was explored. Several IgG molecules were thermally stressed and the high molecular weight species were fractionated using size-exclusion chromatography (SEC). The isolated aggregates and monomers were studied by following the fluorescence of an extrinsic probe, SYPRO Orange. The dye displayed high sensitivity to structurally altered, aggregated IgG structures compared to the native form, which resulted in very low fluorescence in the presence of the dye. An example of the application is presented here to demonstrate the properties of this detection method. The fluorescence assay was shown to correlate with the SEC method in quantifying IgG aggregates. The fluorescent probe method appears to have potential to detect protein particles that could not be analyzed by SEC. This method may become a powerful high throughput tool to detect IgG aggregates in pharmaceutical solutions and to study other protein properties involving aggregation. It can also be used to study the kinetics of antibody particle formation, and perhaps allow identification of the species, which are the early building blocks of protein particles. (c) 2009 Wiley-Liss, Inc. and the American Pharmacists Association

High Throughput PBPK: Evaluating EPA's Open-Source Data and Tools for Dosimetry and Exposure Reconstruction (SOT)

EPA Science Inventory

To address this need, new tools have been created for characterizing, simulating, and evaluating chemical biokinetics. Physiologically-based pharmacokinetic (PBPK) models provide estimates of chemical exposures that produce potentially hazardous tissue concentrations, while tissu...

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.

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 than 2.8 nm.

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.

Generalized schemes for high throughput manipulation of the Desulfovibrio vulgaris Hildenborough genome

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

Chhabra, S.R.; Butland, G.; Elias, D.

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high- throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA “parts” to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications including gene replacement and creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications inmore » a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.« less

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

PubMed

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

2009-01-01

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

High-throughput 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 screening of filamentous fungi using nanoliter-range droplet-based microfluidics

NASA Astrophysics Data System (ADS)

Beneyton, Thomas; Wijaya, I. Putu Mahendra; Postros, Prexilia; Najah, Majdi; Leblond, Pascal; Couvent, Angélique; Mayot, Estelle; Griffiths, Andrew D.; Drevelle, Antoine

2016-06-01

Filamentous fungi are an extremely important source of industrial enzymes because of their capacity to secrete large quantities of proteins. Currently, functional screening of fungi is associated with low throughput and high costs, which severely limits the discovery of novel enzymatic activities and better production strains. Here, we describe a nanoliter-range droplet-based microfluidic system specially adapted for the high-throughput sceening (HTS) of large filamentous fungi libraries for secreted enzyme activities. The platform allowed (i) compartmentalization of single spores in ~10 nl droplets, (ii) germination and mycelium growth and (iii) high-throughput sorting of fungi based on enzymatic activity. A 104 clone UV-mutated library of Aspergillus niger was screened based on α-amylase activity in just 90 minutes. Active clones were enriched 196-fold after a single round of microfluidic HTS. The platform is a powerful tool for the development of new production strains with low cost, space and time footprint and should bring enormous benefit for improving the viability of biotechnological processes.

High-throughput olfactory conditioning and memory retention test show variation in Nasonia parasitic wasps

PubMed Central

Hoedjes, K M; Steidle, J L M; Werren, J H; Vet, L E M; Smid, H M

2012-01-01

Most of our knowledge on learning and memory formation results from extensive studies on a small number of animal species. Although features and cellular pathways of learning and memory are highly similar in this diverse group of species, there are also subtle differences. Closely related species of parasitic wasps display substantial variation in memory dynamics and can be instrumental to understanding both the adaptive benefit of and mechanisms underlying this variation. Parasitic wasps of the genus Nasonia offer excellent opportunities for multidisciplinary research on this topic. Genetic and genomic resources available for Nasonia are unrivaled among parasitic wasps, providing tools for genetic dissection of mechanisms that cause differences in learning. This study presents a robust, high-throughput method for olfactory conditioning of Nasonia using a host encounter as reward. A T-maze olfactometer facilitates high-throughput memory retention testing and employs standardized odors of equal detectability, as quantified by electroantennogram recordings. Using this setup, differences in memory retention between Nasonia species were shown. In both Nasonia vitripennis and Nasonia longicornis, memory was observed up to at least 5 days after a single conditioning trial, whereas Nasonia giraulti lost its memory after 2 days. This difference in learning may be an adaptation to species-specific differences in ecological factors, for example, host preference. The high-throughput methods for conditioning and memory retention testing are essential tools to study both ultimate and proximate factors that cause variation in learning and memory formation in Nasonia and other parasitic wasp species. PMID:22804968

An Upper Bound for Population Exposure Variability (SOT)

EPA Science Inventory

Tools for the rapid assessment of exposure potential are needed in order to put the results of rapidly-applied tools for assessing biological activity, such as ToxCast® and other high throughput methodologies, into a quantitative exposure context. The ExpoCast models (Wambaugh et...

Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes.

PubMed

Evans, Steven T; Stewart, Kevin D; Afdahl, Chris; Patel, Rohan; Newell, Kelcy J

2017-07-14

In this paper, we discuss the optimization and implementation of a high throughput process development (HTPD) tool that utilizes commercially available micro-liter sized column technology for the purification of multiple clinically significant monoclonal antibodies. Chromatographic profiles generated using this optimized tool are shown to overlay with comparable profiles from the conventional bench-scale and clinical manufacturing scale. Further, all product quality attributes measured are comparable across scales for the mAb purifications. In addition to supporting chromatography process development efforts (e.g., optimization screening), comparable product quality results at all scales makes this tool is an appropriate scale model to enable purification and product quality comparisons of HTPD bioreactors conditions. The ability to perform up to 8 chromatography purifications in parallel with reduced material requirements per run creates opportunities for gathering more process knowledge in less time. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

FusionAnalyser: a new graphical, event-driven tool for fusion rearrangements discovery

PubMed Central

Piazza, Rocco; Pirola, Alessandra; Spinelli, Roberta; Valletta, Simona; Redaelli, Sara; Magistroni, Vera; Gambacorti-Passerini, Carlo

2012-01-01

Gene fusions are common driver events in leukaemias and solid tumours; here we present FusionAnalyser, a tool dedicated to the identification of driver fusion rearrangements in human cancer through the analysis of paired-end high-throughput transcriptome sequencing data. We initially tested FusionAnalyser by using a set of in silico randomly generated sequencing data from 20 known human translocations occurring in cancer and subsequently using transcriptome data from three chronic and three acute myeloid leukaemia samples. in all the cases our tool was invariably able to detect the presence of the correct driver fusion event(s) with high specificity. In one of the acute myeloid leukaemia samples, FusionAnalyser identified a novel, cryptic, in-frame ETS2–ERG fusion. A fully event-driven graphical interface and a flexible filtering system allow complex analyses to be run in the absence of any a priori programming or scripting knowledge. Therefore, we propose FusionAnalyser as an efficient and robust graphical tool for the identification of functional rearrangements in the context of high-throughput transcriptome sequencing data. PMID:22570408

FusionAnalyser: a new graphical, event-driven tool for fusion rearrangements discovery.

PubMed

Piazza, Rocco; Pirola, Alessandra; Spinelli, Roberta; Valletta, Simona; Redaelli, Sara; Magistroni, Vera; Gambacorti-Passerini, Carlo

2012-09-01

Gene fusions are common driver events in leukaemias and solid tumours; here we present FusionAnalyser, a tool dedicated to the identification of driver fusion rearrangements in human cancer through the analysis of paired-end high-throughput transcriptome sequencing data. We initially tested FusionAnalyser by using a set of in silico randomly generated sequencing data from 20 known human translocations occurring in cancer and subsequently using transcriptome data from three chronic and three acute myeloid leukaemia samples. in all the cases our tool was invariably able to detect the presence of the correct driver fusion event(s) with high specificity. In one of the acute myeloid leukaemia samples, FusionAnalyser identified a novel, cryptic, in-frame ETS2-ERG fusion. A fully event-driven graphical interface and a flexible filtering system allow complex analyses to be run in the absence of any a priori programming or scripting knowledge. Therefore, we propose FusionAnalyser as an efficient and robust graphical tool for the identification of functional rearrangements in the context of high-throughput transcriptome sequencing data.

REDItools: high-throughput RNA editing detection made easy.

PubMed

Picardi, Ernesto; Pesole, Graziano

2013-07-15

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

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

Systems-Level Synthetic Biology for Advanced Biofuel Production

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

Ruffing, Anne; Jensen, Travis J.; Strickland, Lucas Marshall

2015-03-01

Cyanobacteria have been shown to be capable of producing a variety of advanced biofuels; however, product yields remain well below those necessary for large scale production. New genetic tools and high throughput metabolic engineering techniques are needed to optimize cyanobacterial metabolisms for enhanced biofuel production. Towards this goal, this project advances the development of a multiple promoter replacement technique for systems-level optimization of gene expression in a model cyanobacterial host: Synechococcus sp. PCC 7002. To realize this multiple-target approach, key capabilities were developed, including a high throughput detection method for advanced biofuels, enhanced transformation efficiency, and genetic tools for Synechococcusmore » sp. PCC 7002. Moreover, several additional obstacles were identified for realization of this multiple promoter replacement technique. The techniques and tools developed in this project will help to enable future efforts in the advancement of cyanobacterial biofuels.« less

TriageTools: tools for partitioning and prioritizing analysis of high-throughput sequencing data.

PubMed

Fimereli, Danai; Detours, Vincent; Konopka, Tomasz

2013-04-01

High-throughput sequencing is becoming a popular research tool but carries with it considerable costs in terms of computation time, data storage and bandwidth. Meanwhile, some research applications focusing on individual genes or pathways do not necessitate processing of a full sequencing dataset. Thus, it is desirable to partition a large dataset into smaller, manageable, but relevant pieces. We present a toolkit for partitioning raw sequencing data that includes a method for extracting reads that are likely to map onto pre-defined regions of interest. We show the method can be used to extract information about genes of interest from DNA or RNA sequencing samples in a fraction of the time and disk space required to process and store a full dataset. We report speedup factors between 2.6 and 96, depending on settings and samples used. The software is available at http://www.sourceforge.net/projects/triagetools/.

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.

Miniaturization of High-Throughput Epigenetic Methyltransferase Assays with Acoustic Liquid Handling.

PubMed

Edwards, Bonnie; Lesnick, John; Wang, Jing; Tang, Nga; Peters, Carl

2016-02-01

Epigenetics continues to emerge as an important target class for drug discovery and cancer research. As programs scale to evaluate many new targets related to epigenetic expression, new tools and techniques are required to enable efficient and reproducible high-throughput epigenetic screening. Assay miniaturization increases screening throughput and reduces operating costs. Echo liquid handlers can transfer compounds, samples, reagents, and beads in submicroliter volumes to high-density assay formats using only acoustic energy-no contact or tips required. This eliminates tip costs and reduces the risk of reagent carryover. In this study, we demonstrate the miniaturization of a methyltransferase assay using Echo liquid handlers and two different assay technologies: AlphaLISA from PerkinElmer and EPIgeneous HTRF from Cisbio. © 2015 Society for Laboratory Automation and Screening.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Serpentinomics-an emerging new field of study

Treesearch

Jessica Wright; Eric von Wettberg

2009-01-01

"Serpentinomics" is an emerging field of study which has the potential to greatly advance our understanding of serpentine ecology. Several newly developing –omic fields, often using high-throughput tools developed for molecular biology, will advance the field of serpentine ecology, or, "serpentinomics." Using tools from the...

Extrapolating toxicity data across species using U.S. EPA SeqAPASS tool

EPA Science Inventory

In vitro high-throughput screening (HTS) and in silico technologies have emerged as 21st century tools for chemical hazard identification. In 2007 the U.S. Environmental Protection Agency (EPA) launched the ToxCast Program, which has screened thousands of chemicals in hundreds of...

Bioconductor | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. R/Bioconductor will be enhanced to meet the increasing complexity of multiassay cancer genomics experiments.

Candidiasis and the impact of flow cytometry on antifungal drug discovery.

PubMed

Ku, Tsun Sheng N; Bernardo, Stella; Walraven, Carla J; Lee, Samuel A

2017-11-01

Invasive candidiasis continues to be associated with significant morbidity and mortality as well as substantial health care costs nationally and globally. One of the contributing factors is the development of resistance to antifungal agents that are already in clinical use. Moreover, there are known treatment limitations with all of the available antifungal agents. Since traditional techniques in novel drug discovery are time consuming, high-throughput screening using flow cytometry presents as a potential tool to identify new antifungal agents that would be useful in the management of these patients. Areas covered: In this review, the authors discuss the use of automated high-throughput screening assays based upon flow cytometry to identify potential antifungals from a library comprised of a large number of bioactive compounds. They also review studies that employed the use of this research methodology that has identified compounds with antifungal activity. Expert opinion: High-throughput screening using flow cytometry has substantially decreased the processing time necessary for screening thousands of compounds, and has helped enhance our understanding of fungal pathogenesis. Indeed, the authors see this technology as a powerful tool to help scientists identify new antifungal agents that can be added to the clinician's arsenal in their fight against invasive candidiasis.

Generalized Schemes for High Throughput Manipulation of the Desulfovibrio vulgaris Hildenborough Genome.

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

Chhabra, Swapnil; Butland, Gareth; Elias, Dwayne A

The ability to conduct advanced functional genomic studies of the thousands of 38 sequenced bacteria has been hampered by the lack of available tools for making high39 throughput chromosomal manipulations in a systematic manner that can be applied across 40 diverse species. In this work, we highlight the use of synthetic biological tools to 41 assemble custom suicide vectors with reusable and interchangeable DNA parts to 42 facilitate chromosomal modification at designated loci. These constructs enable an array 43 of downstream applications including gene replacement and creation of gene fusions with 44 affinity purification or localization tags. We employed thismore » approach to engineer 45 chromosomal modifications in a bacterium that has previously proven difficult to 46 manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of 47 662 strains. Furthermore, we demonstrate how these modifications can be used for 48 examining metabolic pathways, protein-protein interactions, and protein localization. The 49 ubiquity of suicide constructs in gene replacement throughout biology suggests that this 50 approach can be applied to engineer a broad range of species for a diverse array of 51 systems biological applications and is amenable to high-throughput implementation.« less

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

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods

PubMed Central

Wells, Darren M.; French, Andrew P.; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein; Bennett, Malcolm J.; Pridmore, Tony P.

2012-01-01

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana. PMID:22527394

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods.

PubMed

Wells, Darren M; French, Andrew P; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein I; Hijazi, Hussein; Bennett, Malcolm J; Pridmore, Tony P

2012-06-05

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana.

High-throughput automatic defect review for 300mm blank wafers with atomic force microscope

NASA Astrophysics Data System (ADS)

Zandiatashbar, Ardavan; Kim, Byong; Yoo, Young-kook; Lee, Keibock; Jo, Ahjin; Lee, Ju Suk; Cho, Sang-Joon; Park, Sang-il

2015-03-01

While feature size in lithography process continuously becomes smaller, defect sizes on blank wafers become more comparable to device sizes. Defects with nm-scale characteristic size could be misclassified by automated optical inspection (AOI) and require post-processing for proper classification. Atomic force microscope (AFM) is known to provide high lateral and the highest vertical resolution by mechanical probing among all techniques. However, its low throughput and tip life in addition to the laborious efforts for finding the defects have been the major limitations of this technique. In this paper we introduce automatic defect review (ADR) AFM as a post-inspection metrology tool for defect study and classification for 300 mm blank wafers and to overcome the limitations stated above. The ADR AFM provides high throughput, high resolution, and non-destructive means for obtaining 3D information for nm-scale defect review and classification.

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

[Weighted gene co-expression network analysis in biomedicine research].

PubMed

Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

2017-11-25

High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

ClusCo: clustering and comparison of protein models.

PubMed

Jamroz, Michal; Kolinski, Andrzej

2013-02-22

The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline. Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering. The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs.

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

NASA Astrophysics Data System (ADS)

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

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

The latest progress in sugarcane molecular genetics research at the USDA-ARS, Sugarcane Research Laboratory

USDA-ARS?s Scientific Manuscript database

In 2005, two sugar molecular genetics tools were developed in the USDA-ARS, Southeast Area, Sugarcane Research Laboratory at Houma, LA. One is the high throughput fluorescence- and capillary electrophoregrams (CE)-based SSR genotyping tool and the other is single pollen collection and SSR genotyping...

Using exposure prediction tools to link exposure and dosimetry for risk-based decisions: A case study with phthalates

EPA Science Inventory

A few different exposure prediction tools were evaluated for use in the new in vitro-based safety assessment paradigm using di-2-ethylhexyl phthalate (DEHP) and dibutyl phthalate (DnBP) as case compounds. Daily intake of each phthalate was estimated using both high-throughput (HT...

Chemiluminescence analyzer of NOx as a high-throughput screening tool in selective catalytic reduction of NO

PubMed Central

Oh, Kwang Seok; Woo, Seong Ihl

2011-01-01

A chemiluminescence-based analyzer of NOx gas species has been applied for high-throughput screening of a library of catalytic materials. The applicability of the commercial NOx analyzer as a rapid screening tool was evaluated using selective catalytic reduction of NO gas. A library of 60 binary alloys composed of Pt and Co, Zr, La, Ce, Fe or W on Al2O3 substrate was tested for the efficiency of NOx removal using a home-built 64-channel parallel and sequential tubular reactor. The NOx concentrations measured by the NOx analyzer agreed well with the results obtained using micro gas chromatography for a reference catalyst consisting of 1 wt% Pt on γ-Al2O3. Most alloys showed high efficiency at 275 °C, which is typical of Pt-based catalysts for selective catalytic reduction of NO. The screening with NOx analyzer allowed to select Pt-Ce(X) (X=1–3) and Pt–Fe(2) as the optimal catalysts for NOx removal: 73% NOx conversion was achieved with the Pt–Fe(2) alloy, which was much better than the results for the reference catalyst and the other library alloys. This study demonstrates a sequential high-throughput method of practical evaluation of catalysts for the selective reduction of NO. PMID:27877438

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-radiance LDP source for mask inspection and beam line applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Teramoto, Yusuke; Santos, Bárbara; Mertens, Guido; Kops, Ralf; Kops, Margarete; von Wezyk, Alexander; Bergmann, Klaus; Yabuta, Hironobu; Nagano, Akihisa; Ashizawa, Noritaka; Taniguchi, Yuta; Yamatani, Daiki; Shirai, Takahiro; Kasama, Kunihiko

2017-04-01

High-throughput actinic mask inspection tools are needed as EUVL begins to enter into volume production phase. One of the key technologies to realize such inspection tools is a high-radiance EUV source of which radiance is supposed to be as high as 100 W/mm2/sr. Ushio is developing laser-assisted discharge-produced plasma (LDP) sources. Ushio's LDP source is able to provide sufficient radiance as well as cleanliness, stability and reliability. Radiance behind the debris mitigation system was confirmed to be 120 W/mm2/sr at 9 kHz and peak radiance at the plasma was increased to over 200 W/mm2/sr in the recent development which supports high-throughput, high-precision mask inspection in the current and future technology nodes. One of the unique features of Ushio's LDP source is cleanliness. Cleanliness evaluation using both grazing-incidence Ru mirrors and normal-incidence Mo/Si mirrors showed no considerable damage to the mirrors other than smooth sputtering of the surface at the pace of a few nm per Gpulse. In order to prove the system reliability, several long-term tests were performed. Data recorded during the tests was analyzed to assess two-dimensional radiance stability. In addition, several operating parameters were monitored to figure out which contributes to the radiance stability. The latest model that features a large opening angle was recently developed so that the tool can utilize a large number of debris-free photons behind the debris shield. The model was designed both for beam line application and high-throughput mask inspection application. At the time of publication, the first product is supposed to be in use at the customer site.

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.

Ion channel drug discovery and research: the automated Nano-Patch-Clamp technology.

PubMed

Brueggemann, A; George, M; Klau, M; Beckler, M; Steindl, J; Behrends, J C; Fertig, N

2004-01-01

Unlike the genomics revolution, which was largely enabled by a single technological advance (high throughput sequencing), rapid advancement in proteomics will require a broader effort to increase the throughput of a number of key tools for functional analysis of different types of proteins. In the case of ion channels -a class of (membrane) proteins of great physiological importance and potential as drug targets- the lack of adequate assay technologies is felt particularly strongly. The available, indirect, high throughput screening methods for ion channels clearly generate insufficient information. The best technology to study ion channel function and screen for compound interaction is the patch clamp technique, but patch clamping suffers from low throughput, which is not acceptable for drug screening. A first step towards a solution is presented here. The nano patch clamp technology, which is based on a planar, microstructured glass chip, enables automatic whole cell patch clamp measurements. The Port-a-Patch is an automated electrophysiology workstation, which uses planar patch clamp chips. This approach enables high quality and high content ion channel and compound evaluation on a one-cell-at-a-time basis. The presented automation of the patch process and its scalability to an array format are the prerequisites for any higher throughput electrophysiology instruments.

High-Reflectivity Coatings for a Vacuum Ultraviolet Spectropolarimeter

NASA Astrophysics Data System (ADS)

Narukage, Noriyuki; Kubo, Masahito; Ishikawa, Ryohko; Ishikawa, Shin-nosuke; Katsukawa, Yukio; Kobiki, Toshihiko; Giono, Gabriel; Kano, Ryouhei; Bando, Takamasa; Tsuneta, Saku; Auchère, Frédéric; Kobayashi, Ken; Winebarger, Amy; McCandless, Jim; Chen, Jianrong; Choi, Joanne

2017-03-01

Precise polarization measurements in the vacuum ultraviolet (VUV) region are expected to be a new tool for inferring the magnetic fields in the upper atmosphere of the Sun. High-reflectivity coatings are key elements to achieving high-throughput optics for precise polarization measurements. We fabricated three types of high-reflectivity coatings for a solar spectropolarimeter in the hydrogen Lyman-α (Lyα; 121.567 nm) region and evaluated their performance. The first high-reflectivity mirror coating offers a reflectivity of more than 80 % in Lyα optics. The second is a reflective narrow-band filter coating that has a peak reflectivity of 57 % in Lyα, whereas its reflectivity in the visible light range is lower than 1/10 of the peak reflectivity (˜ 5 % on average). This coating can be used to easily realize a visible light rejection system, which is indispensable for a solar telescope, while maintaining high throughput in the Lyα line. The third is a high-efficiency reflective polarizing coating that almost exclusively reflects an s-polarized beam at its Brewster angle of 68° with a reflectivity of 55 %. This coating achieves both high polarizing power and high throughput. These coatings contributed to the high-throughput solar VUV spectropolarimeter called the Chromospheric Lyman-Alpha SpectroPolarimeter (CLASP), which was launched on 3 September, 2015.

PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data.

PubMed

Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho

2017-11-01

High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.

Abbott Physicochemical Tiering (APT)--a unified approach to HTS triage.

PubMed

Cox, Philip B; Gregg, Robert J; Vasudevan, Anil

2012-07-15

The selection of the highest quality chemical matter from high throughput screening (HTS) is the ultimate aim of any triage process. Typically there are many hundreds or thousands of hits capable of modulating a given biological target in HTS with a wide range of physicochemical properties that should be taken into consideration during triage. Given the multitude of physicochemical properties that define drug-like space, a system needs to be in place that allows for a rapid selection of chemical matter based on a prioritized range of these properties. With this goal in mind, we have developed a tool, coined Abbott Physicochemical Tiering (APT) that enables hit prioritization based on ranges of these important physicochemical properties. This tool is now used routinely at Abbott to help prioritize hits out of HTS during the triage process. Herein we describe how this tool was developed and validated using Abbott internal high throughput ADME data (HT-ADME). Copyright © 2012 Elsevier Ltd. All rights reserved.

Model-based high-throughput design of ion exchange protein chromatography.

PubMed

Khalaf, Rushd; Heymann, Julia; LeSaout, Xavier; Monard, Florence; Costioli, Matteo; Morbidelli, Massimo

2016-08-12

This work describes the development of a model-based high-throughput design (MHD) tool for the operating space determination of a chromatographic cation-exchange protein purification process. Based on a previously developed thermodynamic mechanistic model, the MHD tool generates a large amount of system knowledge and thereby permits minimizing the required experimental workload. In particular, each new experiment is designed to generate information needed to help refine and improve the model. Unnecessary experiments that do not increase system knowledge are avoided. Instead of aspiring to a perfectly parameterized model, the goal of this design tool is to use early model parameter estimates to find interesting experimental spaces, and to refine the model parameter estimates with each new experiment until a satisfactory set of process parameters is found. The MHD tool is split into four sections: (1) prediction, high throughput experimentation using experiments in (2) diluted conditions and (3) robotic automated liquid handling workstations (robotic workstation), and (4) operating space determination and validation. (1) Protein and resin information, in conjunction with the thermodynamic model, is used to predict protein resin capacity. (2) The predicted model parameters are refined based on gradient experiments in diluted conditions. (3) Experiments on the robotic workstation are used to further refine the model parameters. (4) The refined model is used to determine operating parameter space that allows for satisfactory purification of the protein of interest on the HPLC scale. Each section of the MHD tool is used to define the adequate experimental procedures for the next section, thus avoiding any unnecessary experimental work. We used the MHD tool to design a polishing step for two proteins, a monoclonal antibody and a fusion protein, on two chromatographic resins, in order to demonstrate it has the ability to strongly accelerate the early phases of process development. Copyright © 2016 Elsevier B.V. All rights reserved.

The iPlant collaborative: cyberinfrastructure for enabling data to discovery for the life sciences

USDA-ARS?s Scientific Manuscript database

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identify management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning m...

Chemical Transformation Simulator

EPA Science Inventory

The Chemical Transformation Simulator (CTS) is a web-based, high-throughput screening tool that automates the calculation and collection of physicochemical properties for an organic chemical of interest and its predicted products resulting from transformations in environmental sy...

NREL to Lead New Consortium to Develop Advanced Water Splitting Materials

Science.gov Websites

said. "Our research strategy integrates computational tools and modeling, material synthesis needs, such as high-throughput synthesis techniques and auxiliary component design. HydroGEN is the

Novel genetic tools for studying food-borne Salmonella.

PubMed

Andrews-Polymenis, Helene L; Santiviago, Carlos A; McClelland, Michael

2009-04-01

Nontyphoidal Salmonellae are highly prevalent food-borne pathogens. High-throughput sequencing of Salmonella genomes is expanding our knowledge of the evolution of serovars and epidemic isolates. Genome sequences have also allowed the creation of complete microarrays. Microarrays have improved the throughput of in vivo expression technology (IVET) used to uncover promoters active during infection. In another method, signature tagged mutagenesis (STM), pools of mutants are subjected to selection. Changes in the population are monitored on a microarray, revealing genes under selection. Complete genome sequences permit the construction of pools of targeted in-frame deletions that have improved STM by minimizing the number of clones and the polarity of each mutant. Together, genome sequences and the continuing development of new tools for functional genomics will drive a revolution in the understanding of Salmonellae in many different niches that are critical for food safety.

Purdue ionomics information management system. An integrated functional genomics platform.

PubMed

Baxter, Ivan; Ouzzani, Mourad; Orcun, Seza; Kennedy, Brad; Jandhyala, Shrinivas S; Salt, David E

2007-02-01

The advent of high-throughput phenotyping technologies has created a deluge of information that is difficult to deal with without the appropriate data management tools. These data management tools should integrate defined workflow controls for genomic-scale data acquisition and validation, data storage and retrieval, and data analysis, indexed around the genomic information of the organism of interest. To maximize the impact of these large datasets, it is critical that they are rapidly disseminated to the broader research community, allowing open access for data mining and discovery. We describe here a system that incorporates such functionalities developed around the Purdue University high-throughput ionomics phenotyping platform. The Purdue Ionomics Information Management System (PiiMS) provides integrated workflow control, data storage, and analysis to facilitate high-throughput data acquisition, along with integrated tools for data search, retrieval, and visualization for hypothesis development. PiiMS is deployed as a World Wide Web-enabled system, allowing for integration of distributed workflow processes and open access to raw data for analysis by numerous laboratories. PiiMS currently contains data on shoot concentrations of P, Ca, K, Mg, Cu, Fe, Zn, Mn, Co, Ni, B, Se, Mo, Na, As, and Cd in over 60,000 shoot tissue samples of Arabidopsis (Arabidopsis thaliana), including ethyl methanesulfonate, fast-neutron and defined T-DNA mutants, and natural accession and populations of recombinant inbred lines from over 800 separate experiments, representing over 1,000,000 fully quantitative elemental concentrations. PiiMS is accessible at www.purdue.edu/dp/ionomics.

High throughput SNP discovery and genotyping in hexaploid wheat.

PubMed

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

2018-01-01

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

Spotlight on Fluorescent Biosensors—Tools for Diagnostics and Drug Discovery

PubMed Central

2013-01-01

Fluorescent biosensors constitute potent tools for probing biomolecules in their natural environment and for visualizing dynamic processes in complex biological samples, living cells, and organisms. They are well suited for highlighting molecular alterations associated with pathological disorders, thereby offering means of implementing sensitive and alternative technologies for diagnostic purposes. They constitute attractive tools for drug discovery programs, from high throughput screening assays to preclinical studies. PMID:24900780

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.

A simple and sensitive high-throughput GFP screening in woody and herbaceous plants.

PubMed

Hily, Jean-Michel; Liu, Zongrang

2009-03-01

Green fluorescent protein (GFP) has been used widely as a powerful bioluminescent reporter, but its visualization by existing methods in tissues or whole plants and its utilization for high-throughput screening remains challenging in many species. Here, we report a fluorescence image analyzer-based method for GFP detection and its utility for high-throughput screening of transformed plants. Of three detection methods tested, the Typhoon fluorescence scanner was able to detect GFP fluorescence in all Arabidopsis thaliana tissues and apple leaves, while regular fluorescence microscopy detected it only in Arabidopsis flowers and siliques but barely in the leaves of either Arabidopsis or apple. The hand-held UV illumination method failed in all tissues of both species. Additionally, the Typhoon imager was able to detect GFP fluorescence in both green and non-green tissues of Arabidopsis seedlings as well as in imbibed seeds, qualifying it as a high-throughput screening tool, which was further demonstrated by screening the seedlings of primary transformed T(0) seeds. Of the 30,000 germinating Arabidopsis seedlings screened, at least 69 GFP-positive lines were identified, accounting for an approximately 0.23% transformation efficiency. About 14,000 seedlings grown in 16 Petri plates could be screened within an hour, making the screening process significantly more efficient and robust than any other existing high-throughput screening method for transgenic plants.

Conceptual dissonance: evaluating the efficacy of natural language processing techniques for validating translational knowledge constructs.

PubMed

Payne, Philip R O; Kwok, Alan; Dhaval, Rakesh; Borlawsky, Tara B

2009-03-01

The conduct of large-scale translational studies presents significant challenges related to the storage, management and analysis of integrative data sets. Ideally, the application of methodologies such as conceptual knowledge discovery in databases (CKDD) provides a means for moving beyond intuitive hypothesis discovery and testing in such data sets, and towards the high-throughput generation and evaluation of knowledge-anchored relationships between complex bio-molecular and phenotypic variables. However, the induction of such high-throughput hypotheses is non-trivial, and requires correspondingly high-throughput validation methodologies. In this manuscript, we describe an evaluation of the efficacy of a natural language processing-based approach to validating such hypotheses. As part of this evaluation, we will examine a phenomenon that we have labeled as "Conceptual Dissonance" in which conceptual knowledge derived from two or more sources of comparable scope and granularity cannot be readily integrated or compared using conventional methods and automated tools.

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.

AmpliVar: mutation detection in high-throughput sequence from amplicon-based libraries.

PubMed

Hsu, Arthur L; Kondrashova, Olga; Lunke, Sebastian; Love, Clare J; Meldrum, Cliff; Marquis-Nicholson, Renate; Corboy, Greg; Pham, Kym; Wakefield, Matthew; Waring, Paul M; Taylor, Graham R

2015-04-01

Conventional means of identifying variants in high-throughput sequencing align each read against a reference sequence, and then call variants at each position. Here, we demonstrate an orthogonal means of identifying sequence variation by grouping the reads as amplicons prior to any alignment. We used AmpliVar to make key-value hashes of sequence reads and group reads as individual amplicons using a table of flanking sequences. Low-abundance reads were removed according to a selectable threshold, and reads above this threshold were aligned as groups, rather than as individual reads, permitting the use of sensitive alignment tools. We show that this approach is more sensitive, more specific, and more computationally efficient than comparable methods for the analysis of amplicon-based high-throughput sequencing data. The method can be extended to enable alignment-free confirmation of variants seen in hybridization capture target-enrichment data. © 2015 WILEY PERIODICALS, INC.

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

PubMed

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

High-throughput assay of oxygen radical absorbance capacity (ORAC) using a multichannel liquid handling system coupled with a microplate fluorescence reader in 96-well format.

PubMed

Huang, Dejian; Ou, Boxin; Hampsch-Woodill, Maureen; Flanagan, Judith A; Prior, Ronald L

2002-07-31

The oxygen radical absorbance capacity (ORAC) assay has been widely accepted as a standard tool to measure the antioxidant activity in the nutraceutical, pharmaceutical, and food industries. However, the ORAC assay has been criticized for a lack of accessibility due to the unavailability of the COBAS FARA II analyzer, an instrument discontinued by the manufacturer. In addition, the manual sample preparation is time-consuming and labor-intensive. The objective of this study was to develop a high-throughput instrument platform that can fully automate the ORAC assay procedure. The new instrument platform consists of a robotic eight-channel liquid handling system and a microplate fluorescence reader. By using the high-throughput platform, the efficiency of the assay is improved with at least a 10-fold increase in sample throughput over the current procedure. The mean of intra- and interday CVs was

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

EPA Science Inventory

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include n...

Application of Genomic Technologies to the Breeding of Trees

PubMed Central

Badenes, Maria L.; Fernández i Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J.

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species. PMID:27895664

Application of Genomic Technologies to the Breeding of Trees.

PubMed

Badenes, Maria L; Fernández I Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the former gap of genetic tools between trees and annual species.

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

PubMed

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

2015-02-01

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

High-throughput search for caloric materials: the CaloriCool approach

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

PubMed

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

2014-09-07

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

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

PubMed Central

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

2015-01-01

The evolutionary conservation of genomic, biochemical and developmental features between zebrafish and humans is gradually coming into focus with the end result that the zebrafish embryo model has emerged as a powerful tool for uncovering the effects of environmental exposures on a multitude of biological processes with direct relevance to human health. In this review, we highlight advances in automation, high-throughput (HT) screening, and analysis that leverage the power of the zebrafish embryo model for unparalleled advances in our understanding of how chemicals in our environment affect our health and wellbeing. PMID:25678986

Targeted Capture and High-Throughput Sequencing Using Molecular Inversion Probes (MIPs).

PubMed

Cantsilieris, Stuart; Stessman, Holly A; Shendure, Jay; Eichler, Evan E

2017-01-01

Molecular inversion probes (MIPs) in combination with massively parallel DNA sequencing represent a versatile, yet economical tool for targeted sequencing of genomic DNA. Several thousand genomic targets can be selectively captured using long oligonucleotides containing unique targeting arms and universal linkers. The ability to append sequencing adaptors and sample-specific barcodes allows large-scale pooling and subsequent high-throughput sequencing at relatively low cost per sample. Here, we describe a "wet bench" protocol detailing the capture and subsequent sequencing of >2000 genomic targets from 192 samples, representative of a single lane on the Illumina HiSeq 2000 platform.

High-throughput search for caloric materials: the CaloriCool approach

DOE PAGES

Zarkevich, Nikolai A.; Johnson, Duane D.; Pecharsky, V. K.

2017-12-13

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

Demonstration of lithography patterns using reflective e-beam direct write

NASA Astrophysics Data System (ADS)

Freed, Regina; Sun, Jeff; Brodie, Alan; Petric, Paul; McCord, Mark; Ronse, Kurt; Haspeslagh, Luc; Vereecke, Bart

2011-04-01

Traditionally, e-beam direct write lithography has been too slow for most lithography applications. E-beam direct write lithography has been used for mask writing rather than wafer processing since the maximum blur requirements limit column beam current - which drives e-beam throughput. To print small features and a fine pitch with an e-beam tool requires a sacrifice in processing time unless one significantly increases the total number of beams on a single writing tool. Because of the uncertainty with regards to the optical lithography roadmap beyond the 22 nm technology node, the semiconductor equipment industry is in the process of designing and testing e-beam lithography tools with the potential for high volume wafer processing. For this work, we report on the development and current status of a new maskless, direct write e-beam lithography tool which has the potential for high volume lithography at and below the 22 nm technology node. A Reflective Electron Beam Lithography (REBL) tool is being developed for high throughput electron beam direct write maskless lithography. The system is targeting critical patterning steps at the 22 nm node and beyond at a capital cost equivalent to conventional lithography. Reflective Electron Beam Lithography incorporates a number of novel technologies to generate and expose lithographic patterns with a throughput and footprint comparable to current 193 nm immersion lithography systems. A patented, reflective electron optic or Digital Pattern Generator (DPG) enables the unique approach. The Digital Pattern Generator is a CMOS ASIC chip with an array of small, independently controllable lens elements (lenslets), which act as an array of electron mirrors. In this way, the REBL system is capable of generating the pattern to be written using massively parallel exposure by ~1 million beams at extremely high data rates (~ 1Tbps). A rotary stage concept using a rotating platen carrying multiple wafers optimizes the writing strategy of the DPG to achieve the capability of high throughput for sparse pattern wafer levels. The lens elements on the DPG are fabricated at IMEC (Leuven, Belgium) under IMEC's CMORE program. The CMOS fabricated DPG contains ~ 1,000,000 lens elements, allowing for 1,000,000 individually controllable beamlets. A single lens element consists of 5 electrodes, each of which can be set at controlled voltage levels to either absorb or reflect the electron beam. A system using a linear movable stage and the DPG integrated into the electron optics module was used to expose patterns on device representative wafers. Results of these exposure tests are discussed.

Prediction of miRNA targets.

PubMed

Oulas, Anastasis; Karathanasis, Nestoras; Louloupi, Annita; Pavlopoulos, Georgios A; Poirazi, Panayiota; Kalantidis, Kriton; Iliopoulos, Ioannis

2015-01-01

Computational methods for miRNA target prediction are currently undergoing extensive review and evaluation. There is still a great need for improvement of these tools and bioinformatics approaches are looking towards high-throughput experiments in order to validate predictions. The combination of large-scale techniques with computational tools will not only provide greater credence to computational predictions but also lead to the better understanding of specific biological questions. Current miRNA target prediction tools utilize probabilistic learning algorithms, machine learning methods and even empirical biologically defined rules in order to build models based on experimentally verified miRNA targets. Large-scale protein downregulation assays and next-generation sequencing (NGS) are now being used to validate methodologies and compare the performance of existing tools. Tools that exhibit greater correlation between computational predictions and protein downregulation or RNA downregulation are considered the state of the art. Moreover, efficiency in prediction of miRNA targets that are concurrently verified experimentally provides additional validity to computational predictions and further highlights the competitive advantage of specific tools and their efficacy in extracting biologically significant results. In this review paper, we discuss the computational methods for miRNA target prediction and provide a detailed comparison of methodologies and features utilized by each specific tool. Moreover, we provide an overview of current state-of-the-art high-throughput methods used in miRNA target prediction.

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

A high throughput array microscope for the mechanical characterization of biomaterials

NASA Astrophysics Data System (ADS)

Cribb, Jeremy; Osborne, Lukas D.; Hsiao, Joe Ping-Lin; Vicci, Leandra; Meshram, Alok; O'Brien, E. Tim; Spero, Richard Chasen; Taylor, Russell; Superfine, Richard

2015-02-01

In the last decade, the emergence of high throughput screening has enabled the development of novel drug therapies and elucidated many complex cellular processes. Concurrently, the mechanobiology community has developed tools and methods to show that the dysregulation of biophysical properties and the biochemical mechanisms controlling those properties contribute significantly to many human diseases. Despite these advances, a complete understanding of the connection between biomechanics and disease will require advances in instrumentation that enable parallelized, high throughput assays capable of probing complex signaling pathways, studying biology in physiologically relevant conditions, and capturing specimen and mechanical heterogeneity. Traditional biophysical instruments are unable to meet this need. To address the challenge of large-scale, parallelized biophysical measurements, we have developed an automated array high-throughput microscope system that utilizes passive microbead diffusion to characterize mechanical properties of biomaterials. The instrument is capable of acquiring data on twelve-channels simultaneously, where each channel in the system can independently drive two-channel fluorescence imaging at up to 50 frames per second. We employ this system to measure the concentration-dependent apparent viscosity of hyaluronan, an essential polymer found in connective tissue and whose expression has been implicated in cancer progression.

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

PubMed

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

2012-01-01

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

An extractive removal step optimized for a high-throughput α-cellulose extraction method for δ 13 C and δ 18 O stable isotope ratio analysis in conifer tree rings

Treesearch

Wen Lin; Asko Noormets; John S. King; Ge Sun; Steve McNulty; Jean-Christophe Domec; Lucas Cernusak

2017-01-01

Stable isotope ratios (δ13C and δ18O) of tree-ring α-cellulose are important tools in paleoclimatology, ecology, plant physiology and genetics. The Multiple Sample Isolation System for Solids (MSISS) was a major advance in the tree-ring α-cellulose extraction methods, offering greater throughput and reduced labor input compared to traditional alternatives. However, the...

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

PubMed

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

2010-09-01

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

A protocatechuate biosensor for Pseudomonas putida KT2440 via promoter and protein evolution.

PubMed

Jha, Ramesh K; Bingen, Jeremy M; Johnson, Christopher W; Kern, Theresa L; Khanna, Payal; Trettel, Daniel S; Strauss, Charlie E M; Beckham, Gregg T; Dale, Taraka

2018-06-01

Robust fluorescence-based biosensors are emerging as critical tools for high-throughput strain improvement in synthetic biology. Many biosensors are developed in model organisms where sophisticated synthetic biology tools are also well established. However, industrial biochemical production often employs microbes with phenotypes that are advantageous for a target process, and biosensors may fail to directly transition outside the host in which they are developed. In particular, losses in sensitivity and dynamic range of sensing often occur, limiting the application of a biosensor across hosts. Here we demonstrate the optimization of an Escherichia coli- based biosensor in a robust microbial strain for the catabolism of aromatic compounds, Pseudomonas putida KT2440, through a generalizable approach of modulating interactions at the protein-DNA interface in the promoter and the protein-protein dimer interface. The high-throughput biosensor optimization approach demonstrated here is readily applicable towards other allosteric regulators.

A protocatechuate biosensor for Pseudomonas putida KT2440 via promoter and protein evolution

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

Jha, Ramesh K.; Bingen, Jeremy M.; Johnson, Christopher W.

Robust fluorescence-based biosensors are emerging as critical tools for high-throughput strain improvement in synthetic biology. Many biosensors are developed in model organisms where sophisticated synthetic biology tools are also well established. However, industrial biochemical production often employs microbes with phenotypes that are advantageous for a target process, and biosensors may fail to directly transition outside the host in which they are developed. In particular, losses in sensitivity and dynamic range of sensing often occur, limiting the application of a biosensor across hosts. In this study, we demonstrate the optimization of an Escherichia coli-based biosensor in a robust microbial strain formore » the catabolism of aromatic compounds, Pseudomonas putida KT2440, through a generalizable approach of modulating interactions at the protein-DNA interface in the promoter and the protein-protein dimer interface. The high-throughput biosensor optimization approach demonstrated here is readily applicable towards other allosteric regulators.« less

A protocatechuate biosensor for Pseudomonas putida KT2440 via promoter and protein evolution

DOE PAGES

Jha, Ramesh K.; Bingen, Jeremy M.; Johnson, Christopher W.; ...

2018-06-01

Robust fluorescence-based biosensors are emerging as critical tools for high-throughput strain improvement in synthetic biology. Many biosensors are developed in model organisms where sophisticated synthetic biology tools are also well established. However, industrial biochemical production often employs microbes with phenotypes that are advantageous for a target process, and biosensors may fail to directly transition outside the host in which they are developed. In particular, losses in sensitivity and dynamic range of sensing often occur, limiting the application of a biosensor across hosts. In this study, we demonstrate the optimization of an Escherichia coli-based biosensor in a robust microbial strain formore » the catabolism of aromatic compounds, Pseudomonas putida KT2440, through a generalizable approach of modulating interactions at the protein-DNA interface in the promoter and the protein-protein dimer interface. The high-throughput biosensor optimization approach demonstrated here is readily applicable towards other allosteric regulators.« less

A three-dimensional in vitro ovarian cancer coculture model using a high-throughput cell patterning platform

PubMed Central

Rizvi, Imran; Moon, Sangjun; Hasan, Tayyaba; Demirci, Utkan

2013-01-01

In vitro 3D cancer models that provide a more accurate representation of disease in vivo are urgently needed to improve our understanding of cancer pathology and to develop better cancer therapies. However, development of 3D models that are based on manual ejection of cells from micropipettes suffer from inherent limitations such as poor control over cell density, limited repeatability, low throughput, and, in the case of coculture models, lack of reproducible control over spatial distance between cell types (e.g., cancer and stromal cells). In this study, we build on a recently introduced 3D model in which human ovarian cancer (OVCAR-5) cells overlaid on Matrigel™ spontaneously form multicellular acini. We introduce a high-throughput automated cell printing system to bioprint a 3D coculture model using cancer cells and normal fibroblasts micropatterned on Matrigel™. Two cell types were patterned within a spatially controlled microenvironment (e.g., cell density, cell-cell distance) in a high-throughput and reproducible manner; both cell types remained viable during printing and continued to proliferate following patterning. This approach enables the miniaturization of an established macro-scale 3D culture model and would allow systematic investigation into the multiple unknown regulatory feedback mechanisms between tumor and stromal cells and provide a tool for high-throughput drug screening. PMID:21298805

Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy

DOE PAGES

Rames, Matthew; Yu, Yadong; Ren, Gang

2014-08-15

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of natural proteins have a molecular mass between 40 - 200 kDa, a robust and high-throughput method with a nanometer resolution capability is needed. Negative staining (NS) electron microscopy (EM) is an easy, rapid, and qualitative approach which has frequently been used in research laboratories to examine protein structure and protein-protein interactions. Unfortunately, conventional NS protocols often generate structural artifacts on proteins, especially with lipoproteins that usually form presenting rouleaux artifacts. By using images of lipoproteins from cryo-electronmore » microscopy (cryo-EM) as a standard, the key parameters in NS specimen preparation conditions were recently screened and reported as the optimized NS protocol (OpNS), a modified conventional NS protocol. Artifacts like rouleaux can be greatly limited by OpNS, additionally providing high contrast along with reasonably high-resolution (near 1 nm) images of small and asymmetric proteins. These high-resolution and high contrast images are even favorable for an individual protein (a single object, no average) 3D reconstruction, such as a 160 kDa antibody, through the method of electron tomography. Moreover, OpNS can be a high-throughput tool to examine hundreds of samples of small proteins. For example, the previously published mechanism of 53 kDa cholesteryl ester transfer protein (CETP) involved the screening and imaging of hundreds of samples. Considering cryo-EM rarely successfully images proteins less than 200 kDa has yet to publish any study involving screening over one hundred sample conditions, it is fair to call OpNS a high-throughput method for studying small proteins. Hopefully the OpNS protocol presented here can be a useful tool to push the boundaries of EM and accelerate EM studies into small protein structure, dynamics and mechanisms.« less

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 medicine and cancer drug development. PMID:24658394

'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:15826298

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

PubMed

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

2016-11-01

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

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).

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

Using ToxCast data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure

EPA Science Inventory

AbstractBackground. High-throughput in vitro screening is an important tool for evaluating the potential biological activity of the thousands of existing chemicals in commerce and the hundreds more introduced each year. Among the assay technologies available, high-content imaging...

Computational tool for the early screening of monoclonal antibodies for their viscosities

PubMed Central

Agrawal, Neeraj J; Helk, Bernhard; Kumar, Sandeep; Mody, Neil; Sathish, Hasige A.; Samra, Hardeep S.; Buck, Patrick M; Li, Li; Trout, Bernhardt L

2016-01-01

Highly concentrated antibody solutions often exhibit high viscosities, which present a number of challenges for antibody-drug development, manufacturing and administration. The antibody sequence is a key determinant for high viscosity of highly concentrated solutions; therefore, a sequence- or structure-based tool that can identify highly viscous antibodies from their sequence would be effective in ensuring that only antibodies with low viscosity progress to the development phase. Here, we present a spatial charge map (SCM) tool that can accurately identify highly viscous antibodies from their sequence alone (using homology modeling to determine the 3-dimensional structures). The SCM tool has been extensively validated at 3 different organizations, and has proved successful in correctly identifying highly viscous antibodies. As a quantitative tool, SCM is amenable to high-throughput automated analysis, and can be effectively implemented during the antibody screening or engineering phase for the selection of low-viscosity antibodies. PMID:26399600

Information management systems for pharmacogenomics.

PubMed

Thallinger, Gerhard G; Trajanoski, Slave; Stocker, Gernot; Trajanoski, Zlatko

2002-09-01

The value of high-throughput genomic research is dramatically enhanced by association with key patient data. These data are generally available but of disparate quality and not typically directly associated. A system that could bring these disparate data sources into a common resource connected with functional genomic data would be tremendously advantageous. However, the integration of clinical and accurate interpretation of the generated functional genomic data requires the development of information management systems capable of effectively capturing the data as well as tools to make that data accessible to the laboratory scientist or to the clinician. In this review these challenges and current information technology solutions associated with the management, storage and analysis of high-throughput data are highlighted. It is suggested that the development of a pharmacogenomic data management system which integrates public and proprietary databases, clinical datasets, and data mining tools embedded in a high-performance computing environment should include the following components: parallel processing systems, storage technologies, network technologies, databases and database management systems (DBMS), and application services.

Purdue Ionomics Information Management System. An Integrated Functional Genomics Platform1[C][W][OA

PubMed Central

Baxter, Ivan; Ouzzani, Mourad; Orcun, Seza; Kennedy, Brad; Jandhyala, Shrinivas S.; Salt, David E.

2007-01-01

The advent of high-throughput phenotyping technologies has created a deluge of information that is difficult to deal with without the appropriate data management tools. These data management tools should integrate defined workflow controls for genomic-scale data acquisition and validation, data storage and retrieval, and data analysis, indexed around the genomic information of the organism of interest. To maximize the impact of these large datasets, it is critical that they are rapidly disseminated to the broader research community, allowing open access for data mining and discovery. We describe here a system that incorporates such functionalities developed around the Purdue University high-throughput ionomics phenotyping platform. The Purdue Ionomics Information Management System (PiiMS) provides integrated workflow control, data storage, and analysis to facilitate high-throughput data acquisition, along with integrated tools for data search, retrieval, and visualization for hypothesis development. PiiMS is deployed as a World Wide Web-enabled system, allowing for integration of distributed workflow processes and open access to raw data for analysis by numerous laboratories. PiiMS currently contains data on shoot concentrations of P, Ca, K, Mg, Cu, Fe, Zn, Mn, Co, Ni, B, Se, Mo, Na, As, and Cd in over 60,000 shoot tissue samples of Arabidopsis (Arabidopsis thaliana), including ethyl methanesulfonate, fast-neutron and defined T-DNA mutants, and natural accession and populations of recombinant inbred lines from over 800 separate experiments, representing over 1,000,000 fully quantitative elemental concentrations. PiiMS is accessible at www.purdue.edu/dp/ionomics. PMID:17189337

High throughput SNP discovery and genotyping in hexaploid wheat

PubMed Central

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

2018-01-01

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

Netest: A Tool to Measure the Maximum Burst Size, Available Bandwidth and Achievable Throughput

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

Jin, Guojun; Tierney, Brian

2003-01-31

Distinguishing available bandwidth and achievable throughput is essential for improving network applications' performance. Achievable throughput is the throughput considering a number of factors such as network protocol, host speed, network path, and TCP buffer space, where as available bandwidth only considers the network path. Without understanding this difference, trying to improve network applications' performance is like ''blind men feeling the elephant'' [4]. In this paper, we define and distinguish bandwidth and throughput, and debate which part of each is achievable and which is available. Also, we introduce and discuss a new concept - Maximum Burst Size that is crucial tomore » the network performance and bandwidth sharing. A tool, netest, is introduced to help users to determine the available bandwidth, and provides information to achieve better throughput with fairness of sharing the available bandwidth, thus reducing misuse of the network.« less

New Tools for Investigating Chemical and Product Use

EPA Science Inventory

- The timely characterization of the human and ecological risk posed by thousands of existing and emerging commercial chemicals is a critical challenge - High throughput (HT) risk prioritization relies on hazard and exposure characterization - While advances have been made ...

21st century tools to prioritize contaminants for monitoring and management

EPA Science Inventory

The webinar focused on ways that ToxCast high throughput screening data and the adverse outcome pathway framework, under development in the CSS program, can be used to prioritize environmental contaminants for monitoring and management.

UPIC + GO: Zeroing in on informative markers

USDA-ARS?s Scientific Manuscript database

Microsatellites/SSRs (simple sequence repeats) have become a powerful tool in genomic biology because of their broad range of applications and availability. An efficient method recently developed to generate microsatellite-enriched libraries used in combination with high throughput DNA pyrosequencin...

Noise Reduction in High-Throughput Gene Perturbation Screens

USDA-ARS?s Scientific Manuscript database

Motivation: Accurate interpretation of perturbation screens is essential for a successful functional investigation. However, the screened phenotypes are often distorted by noise, and their analysis requires specialized statistical analysis tools. The number and scope of statistical methods available...

Unsupervised automated high throughput phenotyping of RNAi time-lapse movies.

PubMed

Failmezger, Henrik; Fröhlich, Holger; Tresch, Achim

2013-10-04

Gene perturbation experiments in combination with fluorescence time-lapse cell imaging are a powerful tool in reverse genetics. High content applications require tools for the automated processing of the large amounts of data. These tools include in general several image processing steps, the extraction of morphological descriptors, and the grouping of cells into phenotype classes according to their descriptors. This phenotyping can be applied in a supervised or an unsupervised manner. Unsupervised methods are suitable for the discovery of formerly unknown phenotypes, which are expected to occur in high-throughput RNAi time-lapse screens. We developed an unsupervised phenotyping approach based on Hidden Markov Models (HMMs) with multivariate Gaussian emissions for the detection of knockdown-specific phenotypes in RNAi time-lapse movies. The automated detection of abnormal cell morphologies allows us to assign a phenotypic fingerprint to each gene knockdown. By applying our method to the Mitocheck database, we show that a phenotypic fingerprint is indicative of a gene's function. Our fully unsupervised HMM-based phenotyping is able to automatically identify cell morphologies that are specific for a certain knockdown. Beyond the identification of genes whose knockdown affects cell morphology, phenotypic fingerprints can be used to find modules of functionally related genes.

WebPrInSeS: automated full-length clone sequence identification and verification using high-throughput sequencing data.

PubMed

Massouras, Andreas; Decouttere, Frederik; Hens, Korneel; Deplancke, Bart

2010-07-01

High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all users.

WebPrInSeS: automated full-length clone sequence identification and verification using high-throughput sequencing data

PubMed Central

Massouras, Andreas; Decouttere, Frederik; Hens, Korneel; Deplancke, Bart

2010-01-01

High-throughput sequencing (HTS) is revolutionizing our ability to obtain cheap, fast and reliable sequence information. Many experimental approaches are expected to benefit from the incorporation of such sequencing features in their pipeline. Consequently, software tools that facilitate such an incorporation should be of great interest. In this context, we developed WebPrInSeS, a web server tool allowing automated full-length clone sequence identification and verification using HTS data. WebPrInSeS encompasses two separate software applications. The first is WebPrInSeS-C which performs automated sequence verification of user-defined open-reading frame (ORF) clone libraries. The second is WebPrInSeS-E, which identifies positive hits in cDNA or ORF-based library screening experiments such as yeast one- or two-hybrid assays. Both tools perform de novo assembly using HTS data from any of the three major sequencing platforms. Thus, WebPrInSeS provides a highly integrated, cost-effective and efficient way to sequence-verify or identify clones of interest. WebPrInSeS is available at http://webprinses.epfl.ch/ and is open to all users. PMID:20501601

A new approach to the rationale discovery of polymeric biomaterials

PubMed Central

Kohn, Joachim; Welsh, William J.; Knight, Doyle

2007-01-01

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

SICLE: a high-throughput tool for extracting evolutionary relationships from phylogenetic trees.

PubMed

DeBlasio, Dan F; Wisecaver, Jennifer H

2016-01-01

We present the phylogeny analysis software SICLE (Sister Clade Extractor), an easy-to-use, high-throughput tool to describe the nearest neighbors to a node of interest in a phylogenetic tree as well as the support value for the relationship. The application is a command line utility that can be embedded into a phylogenetic analysis pipeline or can be used as a subroutine within another C++ program. As a test case, we applied this new tool to the published phylome of Salinibacter ruber, a species of halophilic Bacteriodetes, identifying 13 unique sister relationships to S. ruber across the 4,589 gene phylogenies. S. ruber grouped with bacteria, most often other Bacteriodetes, in the majority of phylogenies, but 91 phylogenies showed a branch-supported sister association between S. ruber and Archaea, an evolutionarily intriguing relationship indicative of horizontal gene transfer. This test case demonstrates how SICLE makes it possible to summarize the phylogenetic information produced by automated phylogenetic pipelines to rapidly identify and quantify the possible evolutionary relationships that merit further investigation. SICLE is available for free for noncommercial use at http://eebweb.arizona.edu/sicle/.

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

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

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

Shi, Cindy

2015-07-17

The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

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

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

PubMed

Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

2018-05-01

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Strain Library Imaging Protocol for high-throughput, automated single-cell microscopy of large bacterial collections arrayed on multiwell plates.

PubMed

Shi, Handuo; Colavin, Alexandre; Lee, Timothy K; Huang, Kerwyn Casey

2017-02-01

Single-cell microscopy is a powerful tool for studying gene functions using strain libraries, but it suffers from throughput limitations. Here we describe the Strain Library Imaging Protocol (SLIP), which is a high-throughput, automated microscopy workflow for large strain collections that requires minimal user involvement. SLIP involves transferring arrayed bacterial cultures from multiwell plates onto large agar pads using inexpensive replicator pins and automatically imaging the resulting single cells. The acquired images are subsequently reviewed and analyzed by custom MATLAB scripts that segment single-cell contours and extract quantitative metrics. SLIP yields rich data sets on cell morphology and gene expression that illustrate the function of certain genes and the connections among strains in a library. For a library arrayed on 96-well plates, image acquisition can be completed within 4 min per plate.

History, applications, and challenges of immune repertoire research.

PubMed

Liu, Xiao; Wu, Jinghua

2018-02-27

The diversity of T and B cells in terms of their receptor sequences is huge in the vertebrate's immune system and provides broad protection against the vast diversity of pathogens. Immune repertoire is defined as the sum of T cell receptors and B cell receptors (also named immunoglobulin) that makes the organism's adaptive immune system. Before the emergence of high-throughput sequencing, the studies on immune repertoire were limited by the underdeveloped methodologies, since it was impossible to capture the whole picture by the low-throughput tools. The massive paralleled sequencing technology suits perfectly the researches on immune repertoire. In this article, we review the history of immune repertoire studies, in terms of technologies and research applications. Particularly, we discuss several aspects of challenges in this field and highlight the efforts to develop potential solutions, in the era of high-throughput sequencing of the immune repertoire.

Bacterial CRISPR: Accomplishments and Prospects

PubMed Central

Peters, Jason M.; Silvis, Melanie R.; Zhao, Dehua; Hawkins, John S.; Gross, Carol A.; Qi, Lei S.

2015-01-01

In this review we briefly describe the development of CRISPR tools for genome editing and control of transcription in bacteria. We focus on the Type II CRISPR/Cas9 system, provide specific examples for use of the system, and highlight the advantages and disadvantages of CRISPR versus other techniques. We suggest potential strategies for combining CRISPR tools with high-throughput approaches to elucidate gene function in bacteria. PMID:26363124

20170915 - EPA’s Rapid Exposure and Dosimetry Project (Alberta Health)

EPA Science Inventory

The Chemical Safety for Sustainability Research Program includes the Rapid Exposure and Dosimetry (RED) project. RED advances high throughput research in exposure modeling and toxicokinetics. This presentation is an overview of publicly available tools developed by the RED projec...

20171015 - Predicting Exposure Pathways with Machine Learning (ISES)

EPA Science Inventory

Prioritizing the risk posed to human health from the thousands of chemicals in the environment requires tools that can estimate exposure rates from limited information. High throughput models exist to make predictions of exposure via specific, important pathways such as residenti...

Perspectives on pathway perturbation: Focused research to enhance 3R objectives

EPA Science Inventory

In vitro high-throughput screening (HTS) and in silico technologies are emerging as 21st century tools for hazard identification. Computational methods that strategically examine cross-species conservation of protein sequence/structural information for chemical molecular targets ...

High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool.

PubMed

Henriques, Dora; Browne, Keith A; Barnett, Mark W; Parejo, Melanie; Kryger, Per; Freeman, Tom C; Muñoz, Irene; Garnery, Lionel; Highet, Fiona; Jonhston, J Spencer; McCormack, Grace P; Pinto, M Alice

2018-06-04

The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.

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.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments.

PubMed

Burdick, David B; Cavnor, Chris C; Handcock, Jeremy; Killcoyne, Sarah; Lin, Jake; Marzolf, Bruz; Ramsey, Stephen A; Rovira, Hector; Bressler, Ryan; Shmulevich, Ilya; Boyle, John

2010-07-14

High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

PubMed Central

2010-01-01

Background High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires. Results Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code. Conclusion The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services. PMID:20630057

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.

Materials Databases Infrastructure Constructed by First Principles Calculations: A Review

DOE PAGES

Lin, Lianshan

2015-10-13

The First Principles calculations, especially the calculation based on High-Throughput Density Functional Theory, have been widely accepted as the major tools in atom scale materials design. The emerging super computers, along with the powerful First Principles calculations, have accumulated hundreds of thousands of crystal and compound records. The exponential growing of computational materials information urges the development of the materials databases, which not only provide unlimited storage for the daily increasing data, but still keep the efficiency in data storage, management, query, presentation and manipulation. This review covers the most cutting edge materials databases in materials design, and their hotmore » applications such as in fuel cells. By comparing the advantages and drawbacks of these high-throughput First Principles materials databases, the optimized computational framework can be identified to fit the needs of fuel cell applications. The further development of high-throughput DFT materials database, which in essence accelerates the materials innovation, is discussed in the summary as well.« less

Dopamine Receptor DOP-4 Modulates Habituation to Repetitive Photoactivation of a "C. elegans" Polymodal Nociceptor

ERIC Educational Resources Information Center

Ardiel, Evan L.; Giles, Andrew C.; Yu, Alex J.; Lindsay, Theodore H.; Lockery, Shawn R.; Rankin, Catharine H.

2016-01-01

Habituation is a highly conserved phenomenon that remains poorly understood at the molecular level. Invertebrate model systems, like "Caenorhabditis elegans," can be a powerful tool for investigating this fundamental process. Here we established a high-throughput learning assay that used real-time computer vision software for behavioral…

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.

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

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.

Applying Genomic and Genetic Tools to Understand and Mitigate Damage from Exposure to Toxins

DTIC Science & Technology

2013-10-01

sequences to the human genome . Genome Biol 10, R25 (2009). 26 Award number: W81XWH-09-1-0715 Title: Applying Genomic and Genetic Tools to Understand...utilizing the high-throughput technology of mRNA-seq. BODY The goal of our research program (W81XWH-09-1-0715) was to utilize genetic and genomic ...also acquired the achetf222a * * * * * 5 Award number: W81XWH-09-1-0715 Title: Applying Genomic and Genetic Tools to Understand and Mitigate

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

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.

Recent advances in quantitative high throughput and high content data analysis.

PubMed

Moutsatsos, Ioannis K; Parker, Christian N

2016-01-01

High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens. This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data. As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.

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.

SCREENING CHEMICALS FOR ESTROGEN RECEPTOR BIOACTIVITY USING A COMPUTATIONAL MODEL

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) is considering the use high-throughput and computational methods for regulatory applications in the Endocrine Disruptor Screening Program (EDSP). To use these new tools for regulatory decision making, computational methods must be a...

Genomics for the identification of novel antimicrobials

USDA-ARS?s Scientific Manuscript database

There is a critical need in animal agriculture for developing novel antimicrobials and alternative strategies to reduce the use of antibiotics and address the challenges of antimicrobial resistance. High-throughput gene expression analysis is providing new tools that are enabling the discovery of h...

solGS: a web-based tool for genomic selection

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, ana...

Elucidation of Adverse Bioactivity Profiles as Predictors of Toxicity Potential

EPA Science Inventory

Toxicity testing in vitro remains a formidable challenge due to lack of understanding of key molecular targets and pathways underlying many pathological events. The combination of genome sequencing and widespread application of high-throughput screening tools have provided the me...

High-throughput ultraviolet photoacoustic microscopy with multifocal excitation

NASA Astrophysics Data System (ADS)

Imai, Toru; Shi, Junhui; Wong, Terence T. W.; Li, Lei; Zhu, Liren; Wang, Lihong V.

2018-03-01

Ultraviolet photoacoustic microscopy (UV-PAM) is a promising intraoperative tool for surgical margin assessment (SMA), one that can provide label-free histology-like images with high resolution. In this study, using a microlens array and a one-dimensional (1-D) array ultrasonic transducer, we developed a high-throughput multifocal UV-PAM (MF-UV-PAM). Our new system achieved a 1.6 ± 0.2 μm lateral resolution and produced images 40 times faster than the previously developed point-by-point scanning UV-PAM. MF-UV-PAM provided a readily comprehensible photoacoustic image of a mouse brain slice with specific absorption contrast in ˜16 min, highlighting cell nuclei. Individual cell nuclei could be clearly resolved, showing its practical potential for intraoperative SMA.

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 fluorescence analysis leads to a substantial extension of the feature spectrum to be assessed in the presented high throughput automated plant phenotyping platforms, thus enabling the simultaneous assessment of plant architectural and biomass-related traits and their relations to physiological features such as PSII operating efficiency. The implemented high throughput protocols are applicable to a broad spectrum of model and crop plants of different sizes (up to 1.80 m height) and architectures. The deeper understanding of the relation of plant architecture, biomass formation and photosynthetic efficiency has a great potential with respect to crop and yield improvement strategies.

Conceptual Framework To Extend Life Cycle Assessment ...

EPA Pesticide Factsheets

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

MultiSense: A Multimodal Sensor Tool Enabling the High-Throughput Analysis of Respiration.

PubMed

Keil, Peter; Liebsch, Gregor; Borisjuk, Ljudmilla; Rolletschek, Hardy

2017-01-01

The high-throughput analysis of respiratory activity has become an important component of many biological investigations. Here, a technological platform, denoted the "MultiSense tool," is described. The tool enables the parallel monitoring of respiration in 100 samples over an extended time period, by dynamically tracking the concentrations of oxygen (O 2 ) and/or carbon dioxide (CO 2 ) and/or pH within an airtight vial. Its flexible design supports the quantification of respiration based on either oxygen consumption or carbon dioxide release, thereby allowing for the determination of the physiologically significant respiratory quotient (the ratio between the quantities of CO 2 released and the O 2 consumed). It requires an LED light source to be mounted above the sample, together with a CCD camera system, adjusted to enable the capture of analyte-specific wavelengths, and fluorescent sensor spots inserted into the sample vial. Here, a demonstration is given of the use of the MultiSense tool to quantify respiration in imbibing plant seeds, for which an appropriate step-by-step protocol is provided. The technology can be easily adapted for a wide range of applications, including the monitoring of gas exchange in any kind of liquid culture system (algae, embryo and tissue culture, cell suspensions, microbial cultures).

MPRAnator: a web-based tool for the design of massively parallel reporter assay experiments

PubMed Central

Georgakopoulos-Soares, Ilias; Jain, Naman; Gray, Jesse M; Hemberg, Martin

2017-01-01

Motivation: With the rapid advances in DNA synthesis and sequencing technologies and the continuing decline in the associated costs, high-throughput experiments can be performed to investigate the regulatory role of thousands of oligonucleotide sequences simultaneously. Nevertheless, designing high-throughput reporter assay experiments such as massively parallel reporter assays (MPRAs) and similar methods remains challenging. Results: We introduce MPRAnator, a set of tools that facilitate rapid design of MPRA experiments. With MPRA Motif design, a set of variables provides fine control of how motifs are placed into sequences, thereby allowing the investigation of the rules that govern transcription factor (TF) occupancy. MPRA single-nucleotide polymorphism design can be used to systematically examine the functional effects of single or combinations of single-nucleotide polymorphisms at regulatory sequences. Finally, the Transmutation tool allows for the design of negative controls by permitting scrambling, reversing, complementing or introducing multiple random mutations in the input sequences or motifs. Availability and implementation: MPRAnator tool set is implemented in Python, Perl and Javascript and is freely available at www.genomegeek.com and www.sanger.ac.uk/science/tools/mpranator. The source code is available on www.github.com/hemberg-lab/MPRAnator/ under the MIT license. The REST API allows programmatic access to MPRAnator using simple URLs. Contact: igs@sanger.ac.uk or mh26@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27605100

MPRAnator: a web-based tool for the design of massively parallel reporter assay experiments.

PubMed

Georgakopoulos-Soares, Ilias; Jain, Naman; Gray, Jesse M; Hemberg, Martin

2017-01-01

With the rapid advances in DNA synthesis and sequencing technologies and the continuing decline in the associated costs, high-throughput experiments can be performed to investigate the regulatory role of thousands of oligonucleotide sequences simultaneously. Nevertheless, designing high-throughput reporter assay experiments such as massively parallel reporter assays (MPRAs) and similar methods remains challenging. We introduce MPRAnator, a set of tools that facilitate rapid design of MPRA experiments. With MPRA Motif design, a set of variables provides fine control of how motifs are placed into sequences, thereby allowing the investigation of the rules that govern transcription factor (TF) occupancy. MPRA single-nucleotide polymorphism design can be used to systematically examine the functional effects of single or combinations of single-nucleotide polymorphisms at regulatory sequences. Finally, the Transmutation tool allows for the design of negative controls by permitting scrambling, reversing, complementing or introducing multiple random mutations in the input sequences or motifs. MPRAnator tool set is implemented in Python, Perl and Javascript and is freely available at www.genomegeek.com and www.sanger.ac.uk/science/tools/mpranator The source code is available on www.github.com/hemberg-lab/MPRAnator/ under the MIT license. The REST API allows programmatic access to MPRAnator using simple URLs. igs@sanger.ac.uk or mh26@sanger.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Process in manufacturing high efficiency AlGaAs/GaAs solar cells by MO-CVD

NASA Technical Reports Server (NTRS)

Yeh, Y. C. M.; Chang, K. I.; Tandon, J.

1984-01-01

Manufacturing technology for mass producing high efficiency GaAs solar cells is discussed. A progress using a high throughput MO-CVD reactor to produce high efficiency GaAs solar cells is discussed. Thickness and doping concentration uniformity of metal oxide chemical vapor deposition (MO-CVD) GaAs and AlGaAs layer growth are discussed. In addition, new tooling designs are given which increase the throughput of solar cell processing. To date, 2cm x 2cm AlGaAs/GaAs solar cells with efficiency up to 16.5% were produced. In order to meet throughput goals for mass producing GaAs solar cells, a large MO-CVD system (Cambridge Instrument Model MR-200) with a susceptor which was initially capable of processing 20 wafers (up to 75 mm diameter) during a single growth run was installed. In the MR-200, the sequencing of the gases and the heating power are controlled by a microprocessor-based programmable control console. Hence, operator errors can be reduced, leading to a more reproducible production sequence.

Genome editing in the mushroom-forming basidiomycete Coprinopsis cinerea, optimized by a high-throughput transformation system.

PubMed

Sugano, Shigeo S; Suzuki, Hiroko; Shimokita, Eisuke; Chiba, Hirofumi; Noji, Sumihare; Osakabe, Yuriko; Osakabe, Keishi

2017-04-28

Mushroom-forming basidiomycetes produce a wide range of metabolites and have great value not only as food but also as an important global natural resource. Here, we demonstrate CRISPR/Cas9-based genome editing in the model species Coprinopsis cinerea. Using a high-throughput reporter assay with cryopreserved protoplasts, we identified a novel promoter, CcDED1 pro , with seven times stronger activity in this assay than the conventional promoter GPD2. To develop highly efficient genome editing using CRISPR/Cas9 in C. cinerea, we used the CcDED1 pro to express Cas9 and a U6-snRNA promoter from C. cinerea to express gRNA. Finally, CRISPR/Cas9-mediated GFP mutagenesis was performed in a stable GFP expression line. Individual genome-edited lines were isolated, and loss of GFP function was detected in hyphae and fruiting body primordia. This novel method of high-throughput CRISPR/Cas9-based genome editing using cryopreserved protoplasts should be a powerful tool in the study of edible mushrooms.

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.

Microplate-Based Method for High-Throughput Screening (HTS) of Chromatographic Conditions Studies for Recombinant Protein Purification.

PubMed

Carvalho, Rimenys J; Cruz, Thayana A

2018-01-01

High-throughput screening (HTS) systems have emerged as important tools to provide fast and low cost evaluation of several conditions at once since it requires small quantities of material and sample volumes. These characteristics are extremely valuable for experiments with large number of variables enabling the application of design of experiments (DoE) strategies or simple experimental planning approaches. Once, the capacity of HTS systems to mimic chromatographic purification steps was established, several studies were performed successfully including scale down purification. Here, we propose a method for studying different purification conditions that can be used for any recombinant protein, including complex and glycosylated proteins, using low binding filter microplates.

Computational Tools for Stem Cell Biology

PubMed Central

Bian, Qin; Cahan, Patrick

2016-01-01

For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the last several years, a new sub-discipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single-cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate. PMID:27318512

Computational Tools for Stem Cell Biology.

PubMed

Bian, Qin; Cahan, Patrick

2016-12-01

For over half a century, the field of developmental biology has leveraged computation to explore mechanisms of developmental processes. More recently, computational approaches have been critical in the translation of high throughput data into knowledge of both developmental and stem cell biology. In the past several years, a new subdiscipline of computational stem cell biology has emerged that synthesizes the modeling of systems-level aspects of stem cells with high-throughput molecular data. In this review, we provide an overview of this new field and pay particular attention to the impact that single cell transcriptomics is expected to have on our understanding of development and our ability to engineer cell fate. Copyright © 2016 Elsevier Ltd. All rights reserved.

The USC Epigenome Center.

PubMed

Laird, Peter W

2009-10-01

The University of Southern California (USC, CA, USA) has a long tradition of excellence in epigenetics. With the recent explosive growth and technological maturation of the field of epigenetics, it became clear that a dedicated high-throughput epigenomic data production facility would be needed to remain at the forefront of epigenetic research. To address this need, USC launched the USC Epigenome Center as the first large-scale center in academics dedicated to epigenomic research. The Center is providing high-throughput data production for large-scale genomic and epigenomic studies, and developing novel analysis tools for epigenomic research. This unique facility promises to be a valuable resource for multidisciplinary research, education and training in genomics, epigenomics, bioinformatics, and translational medicine.

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.

GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping

PubMed Central

Diaz-Garcia, Luis; Covarrubias-Pazaran, Giovanny; Schlautman, Brandon; Zalapa, Juan

2016-01-01

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables. PMID:27529547

GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping.

PubMed

Diaz-Garcia, Luis; Covarrubias-Pazaran, Giovanny; Schlautman, Brandon; Zalapa, Juan

2016-01-01

Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables.

Using leaf optical properties to detect ozone effects on foliar biochemistry

USDA-ARS?s Scientific Manuscript database

Efficient methods for accurate and meaningful high-throughput plant phenotyping are limiting the development and breeding of stress-tolerant crops. A number of emerging techniques, specifically remote sensing methods, have been identified as promising tools for plant phenotyping. These remote-sensin...

Development and Evaluation of an ADME-informed High Throughput Exposure Estimation Tool

EPA Science Inventory

EPA’s Chemical Safety for Sustainability (CSS) research program has been developing new ways to prioritize chemicals used in consumer products and articles. Using a risk-based methodology to account for both toxicity and exposure offers a comprehensive and systematic approa...

ECONOMICS OF SAMPLE COMPOSITING AS A SCREENING TOOL IN GROUND WATER QUALITY MONITORING

EPA Science Inventory

Recent advances in high throughput/automated compositing with robotics/field-screening methods offer seldom-tapped opportunities for achieving cost-reduction in ground water quality monitoring programs. n economic framework is presented in this paper for the evaluation of sample ...

AOP-informed assessment of endocrine disruption in freshwater crustaceans

EPA Science Inventory

To date, most research focused on developing more efficient and cost effective methods to predict toxicity have focused on human biology. However, there is also a need for effective high throughput tools to predict toxicity to other species that perform critical ecosystem functio...

Applying 21st century tools to watersheds of the western US: Sites, bioactivities, and chemicals of concern

EPA Science Inventory

The webinar focused on ways that ToxCast high throughput screening data and the adverse outcome pathway framework, under development in the CSS program, can be used to prioritize environmental contaminants for monitoring and management.

Exposure-Based Screening and Priority-Setting (WC10)

EPA Science Inventory

The U.S. National Academy of Sciences report “Using 21st Century Science to Improve Risk-Related Evaluations” recognized that high-throughput screening (HTS) and exposure prediction tools are necessary to prioritize thousands of chemicals with the potential to pose human health r...

Enzyme catalysis: Evolution made easy

NASA Astrophysics Data System (ADS)

Wee, Eugene J. H.; Trau, Matt

2014-09-01

Directed evolution is a powerful tool for the development of improved enzyme catalysts. Now, a method that enables an enzyme, its encoding DNA and a fluorescent reaction product to be encapsulated in a gel bead enables the application of directed evolution in an ultra-high-throughput format.

So Many Chemicals, So Little Time... Evolution of Computational Toxicology (NCSU Toxicology Lecture Series)

EPA Science Inventory

Current testing is limited by traditional testing models and regulatory systems. An overview is given of high throughput screening approaches to provide broader chemical and biological coverage, toxicokinetics and molecular pathway data and tools to facilitate utilization for reg...

Screening_mgmt: a Python module for managing screening data.

PubMed

Helfenstein, Andreas; Tammela, Päivi

2015-02-01

High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. © 2014 Society for Laboratory Automation and Screening.

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

PubMed

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

2015-01-15

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

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

Software automation tools for increased throughput metabolic soft-spot identification in early drug discovery.

PubMed

Zelesky, Veronica; Schneider, Richard; Janiszewski, John; Zamora, Ismael; Ferguson, James; Troutman, Matthew

2013-05-01

The ability to supplement high-throughput metabolic clearance data with structural information defining the site of metabolism should allow design teams to streamline their synthetic decisions. However, broad application of metabolite identification in early drug discovery has been limited, largely due to the time required for data review and structural assignment. The advent of mass defect filtering and its application toward metabolite scouting paved the way for the development of software automation tools capable of rapidly identifying drug-related material in complex biological matrices. Two semi-automated commercial software applications, MetabolitePilot™ and Mass-MetaSite™, were evaluated to assess the relative speed and accuracy of structural assignments using data generated on a high-resolution MS platform. Review of these applications has demonstrated their utility in providing accurate results in a time-efficient manner, leading to acceleration of metabolite identification initiatives while highlighting the continued need for biotransformation expertise in the interpretation of more complex metabolic reactions.

IAOseq: inferring abundance of overlapping genes using RNA-seq data.

PubMed

Sun, Hong; Yang, Shuang; Tun, Liangliang; Li, Yixue

2015-01-01

Overlapping transcription constitutes a common mechanism for regulating gene expression. A major limitation of the overlapping transcription assays is the lack of high throughput expression data. We developed a new tool (IAOseq) that is based on reads distributions along the transcribed regions to identify the expression levels of overlapping genes from standard RNA-seq data. Compared with five commonly used quantification methods, IAOseq showed better performance in the estimation accuracy of overlapping transcription levels. For the same strand overlapping transcription, currently existing high-throughput methods are rarely available to distinguish which strand was present in the original mRNA template. The IAOseq results showed that the commonly used methods gave an average of 1.6 fold overestimation of the expression levels of same strand overlapping genes. This work provides a useful tool for mining overlapping transcription levels from standard RNA-seq libraries. IAOseq could be used to help us understand the complex regulatory mechanism mediated by overlapping transcripts. IAOseq is freely available at http://lifecenter.sgst.cn/main/en/IAO_seq.jsp.

The Gene Expression Omnibus Database.

PubMed

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.

The Gene Expression Omnibus database

PubMed Central

Clough, Emily; Barrett, Tanya

2016-01-01

The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome–protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/. PMID:27008011

CRISPR-enabled tools for engineering microbial genomes and phenotypes.

PubMed

Tarasava, Katia; Oh, Eun Joong; Eckert, Carrie A; Gill, Ryan T

2018-06-19

In recent years CRISPR-Cas technologies have revolutionized microbial engineering approaches. Genome editing and non-editing applications of various CRISPR-Cas systems have expanded the throughput and scale of engineering efforts, as well as opened up new avenues for manipulating genomes of non-model organisms. As we expand the range of organisms used for biotechnological applications, we need to develop better, more versatile tools for manipulation of these systems. Here we summarize the current advances in microbial gene editing using CRISPR-Cas based tools, and highlight state-of-the-art methods for high-throughput, efficient genome-scale engineering in model organisms Escherichia coli and Saccharomyces cerevisiae. We also review non-editing CRISPR-Cas applications available for gene expression manipulation, epigenetic remodeling, RNA editing, labeling and synthetic gene circuit design. Finally, we point out the areas of research that need further development in order to expand the range of applications and increase the utility of these new methods. This article is protected by copyright. All rights reserved.

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

iCanPlot: Visual Exploration of High-Throughput Omics Data Using Interactive Canvas Plotting

PubMed Central

Sinha, Amit U.; Armstrong, Scott A.

2012-01-01

Increasing use of high throughput genomic scale assays requires effective visualization and analysis techniques to facilitate data interpretation. Moreover, existing tools often require programming skills, which discourages bench scientists from examining their own data. We have created iCanPlot, a compelling platform for visual data exploration based on the latest technologies. Using the recently adopted HTML5 Canvas element, we have developed a highly interactive tool to visualize tabular data and identify interesting patterns in an intuitive fashion without the need of any specialized computing skills. A module for geneset overlap analysis has been implemented on the Google App Engine platform: when the user selects a region of interest in the plot, the genes in the region are analyzed on the fly. The visualization and analysis are amalgamated for a seamless experience. Further, users can easily upload their data for analysis—which also makes it simple to share the analysis with collaborators. We illustrate the power of iCanPlot by showing an example of how it can be used to interpret histone modifications in the context of gene expression. PMID:22393367

Development of nanostencil lithography and its applications for plasmonics and vibrational biospectroscopy

NASA Astrophysics Data System (ADS)

Aksu, Serap

Development of low cost nanolithography tools for precisely creating a variety of nanostructure shapes and arrangements in a high-throughput fashion is crucial for next generation biophotonic technologies. Although existing lithography techniques offer tremendous design flexibility, they have major drawbacks such as low-throughput and fabrication complexity. In addition the demand for the systematic fabrication of sub-100 nm structures on flexible, stretchable, non-planar nanoelectronic/photonic systems and multi-functional materials has fueled the research for innovative fabrication methods in recent years. This thesis research investigates a novel lithography approach for fabrication of engineered plasmonic nanostructures and metamaterials operating at visible and infrared wavelengths. The technique is called Nanostencil Lithography (NSL) and relies on direct deposition of materials through nanoapertures on a stencil. NSL enables high throughput fabrication of engineered antenna arrays with optical qualities similar to the ones fabricated by standard electron beam lithography. Moreover, nanostencils can be reused multiple times to fabricate series of plasmonic nanoantenna arrays with identical optical responses enabling high throughput manufacturing. Using nanostencils, very precise nanostructures could be fabricated with 10 nm accuracy. Furthermore, this technique has flexibility and resolution to create complex plasmonic nanostructure arrays on the substrates that are difficult to work with e-beam and ion beam lithography tools. Combining plasmonics with polymeric materials, biocompatible surfaces or curvilinear and non-planar objects enable unique optical applications since they can preserve normal device operation under large strain. In this work, mechanically tunable flexible optical materials and spectroscopy probes integrated on fiber surfaces that could be used for a wide range of applications are demonstrated. Finally, the first application of NSL fabricated low cost infrared nanoantenna arrays for plasmonically enhanced vibrational biospectroscopy is presented. Detection of immunologically important protein monolayers with thickness as small as 3 nm, and antibody assays are demonstrated using nanoantenna arrays fabricated with reusable nanostencils. The results presented indicate that nanostencil lithography is a promising method for reducing the nano manufacturing cost while enhancing the performance of biospectroscopy tools for biology and medicine. As a single step and low cost nanofabrication technique, NSL could facilitate the manufacturing of biophotonic technologies for real-world applications.

S-MART, a software toolbox to aid RNA-Seq data analysis.

PubMed

Zytnicki, Matthias; Quesneville, Hadi

2011-01-01

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci.

S-MART, A Software Toolbox to Aid RNA-seq Data Analysis

PubMed Central

Zytnicki, Matthias; Quesneville, Hadi

2011-01-01

High-throughput sequencing is now routinely performed in many experiments. But the analysis of the millions of sequences generated, is often beyond the expertise of the wet labs who have no personnel specializing in bioinformatics. Whereas several tools are now available to map high-throughput sequencing data on a genome, few of these can extract biological knowledge from the mapped reads. We have developed a toolbox called S-MART, which handles mapped RNA-Seq data. S-MART is an intuitive and lightweight tool which performs many of the tasks usually required for the analysis of mapped RNA-Seq reads. S-MART does not require any computer science background and thus can be used by all of the biologist community through a graphical interface. S-MART can run on any personal computer, yielding results within an hour even for Gb of data for most queries. S-MART may perform the entire analysis of the mapped reads, without any need for other ad hoc scripts. With this tool, biologists can easily perform most of the analyses on their computer for their RNA-Seq data, from the mapped data to the discovery of important loci. PMID:21998740

Systems metabolic engineering: genome-scale models and beyond.

PubMed

Blazeck, John; Alper, Hal

2010-07-01

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.

How to Compute a Slot Marker - Calculation of Controller Managed Spacing Tools for Efficient Descents with Precision Scheduling

NASA Technical Reports Server (NTRS)

Prevot, Thomas

2012-01-01

This paper describes the underlying principles and algorithms for computing the primary controller managed spacing (CMS) tools developed at NASA for precisely spacing aircraft along efficient descent paths. The trajectory-based CMS tools include slot markers, delay indications and speed advisories. These tools are one of three core NASA technologies integrated in NASAs ATM technology demonstration-1 (ATD-1) that will operationally demonstrate the feasibility of fuel-efficient, high throughput arrival operations using Automatic Dependent Surveillance Broadcast (ADS-B) and ground-based and airborne NASA technologies for precision scheduling and spacing.

An innovative SNP genotyping method adapting to multiple platforms and throughputs

USDA-ARS?s Scientific Manuscript database

Single nucleotide polymorphisms (SNPs) are highly abundant, distributed throughout the genome in various species, and therefore they are widely used as genetic markers. However, the usefulness of this genetic tool relies heavily on the availability of user-friendly SNP genotyping methods. We have d...

Immunochemistry for high-throughput screening of human exhaled breath condensate (EBC) media: implementation of automated quanterix SIMOA instrumentation

EPA Science Inventory

Immunochemistry is an important clinical tool for indicating biological pathways leading towards disease. Standard enzyme-linked immunosorbent assays (ELISA) are labor intensive and lack sensitivity at low-level concentrations. Here we report on emerging technology implementing f...

Implementation of a Flexible Tool for Automated Literature-Mining and Knowledgebase Development (DevToxMine)

EPA Science Inventory

Deriving novel relationships from the scientific literature is an important adjunct to datamining activities for complex datasets in genomics and high-throughput screening activities. Automated text-mining algorithms can be used to extract relevant content from the literature and...

Tools Fit for Chemical Risk Prioritization (EC JRC presentation)

EPA Science Inventory

We would like to know more about the risk posed by thousands of chemicals in the environment – which are most worthy of further study? High throughput screening (HTS) provides a path forward for identifying potential hazard. Exposure and dosimetry provide real world context to ha...

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)

PubMed Central

Dowd, Scot E; Zaragoza, Joaquin; Rodriguez, Javier R; Oliver, Melvin J; Payton, Paxton R

2005-01-01

Background BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. Results W.ND-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN). W.ND-BLAST provides intuitive Graphic User Interfaces (GUI) for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of W.ND-BLAST. W.ND-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes (11 hours) on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV) and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. Conclusion W.ND-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for W.ND-BLAST is freely downloadable from . With registration the software is free, installation, networking, and usage instructions are provided as well as a support forum. PMID:15819992

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.

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

An ultra-HTS process for the identification of small molecule modulators of orphan G-protein-coupled receptors.

PubMed

Cacace, Angela; Banks, Martyn; Spicer, Timothy; Civoli, Francesca; Watson, John

2003-09-01

G-protein-coupled receptors (GPCRs) are the most successful target proteins for drug discovery research to date. More than 150 orphan GPCRs of potential therapeutic interest have been identified for which no activating ligands or biological functions are known. One of the greatest challenges in the pharmaceutical industry is to link these orphan GPCRs with human diseases. Highly automated parallel approaches that integrate ultra-high throughput and focused screening can be used to identify small molecule modulators of orphan GPCRs. These small molecules can then be employed as pharmacological tools to explore the function of orphan receptors in models of human disease. In this review, we describe methods that utilize powerful ultra-high-throughput screening technologies to identify surrogate ligands of orphan GPCRs.

Predicting Novel Bulk Metallic Glasses via High- Throughput Calculations

NASA Astrophysics Data System (ADS)

Perim, E.; Lee, D.; Liu, Y.; Toher, C.; Gong, P.; Li, Y.; Simmons, W. N.; Levy, O.; Vlassak, J.; Schroers, J.; Curtarolo, S.

Bulk metallic glasses (BMGs) are materials which may combine key properties from crystalline metals, such as high hardness, with others typically presented by plastics, such as easy processability. However, the cost of the known BMGs poses a significant obstacle for the development of applications, which has lead to a long search for novel, economically viable, BMGs. The emergence of high-throughput DFT calculations, such as the library provided by the AFLOWLIB consortium, has provided new tools for materials discovery. We have used this data to develop a new glass forming descriptor combining structural factors with thermodynamics in order to quickly screen through a large number of alloy systems in the AFLOWLIB database, identifying the most promising systems and the optimal compositions for glass formation. National Science Foundation (DMR-1436151, DMR-1435820, DMR-1436268).

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

PubMed

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

PubMed Central

Simonyan, Vahan; Mazumder, Raja

2014-01-01

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis. PMID:25271953

Searching for microbial protein over-expression in a complex matrix using automated high throughput MS-based proteomics tools.

PubMed

Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob

2013-03-10

In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.

Robust high-throughput batch screening method in 384-well format with optical in-line resin quantification.

PubMed

Kittelmann, Jörg; Ottens, Marcel; Hubbuch, Jürgen

2015-04-15

High-throughput batch screening technologies have become an important tool in downstream process development. Although continuative miniaturization saves time and sample consumption, there is yet no screening process described in the 384-well microplate format. Several processes are established in the 96-well dimension to investigate protein-adsorbent interactions, utilizing between 6.8 and 50 μL resin per well. However, as sample consumption scales with resin volumes and throughput scales with experiments per microplate, they are limited in costs and saved time. In this work, a new method for in-well resin quantification by optical means, applicable in the 384-well format, and resin volumes as small as 0.1 μL is introduced. A HTS batch isotherm process is described, utilizing this new method in combination with optical sample volume quantification for screening of isotherm parameters in 384-well microplates. Results are qualified by confidence bounds determined by bootstrap analysis and a comprehensive Monte Carlo study of error propagation. This new approach opens the door to a variety of screening processes in the 384-well format on HTS stations, higher quality screening data and an increase in throughput. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient Identification of Murine M2 Macrophage Peptide Targeting Ligands by Phage Display and Next-Generation Sequencing.

PubMed

Liu, Gary W; Livesay, Brynn R; Kacherovsky, Nataly A; Cieslewicz, Maryelise; Lutz, Emi; Waalkes, Adam; Jensen, Michael C; Salipante, Stephen J; Pun, Suzie H

2015-08-19

Peptide ligands are used to increase the specificity of drug carriers to their target cells and to facilitate intracellular delivery. One method to identify such peptide ligands, phage display, enables high-throughput screening of peptide libraries for ligands binding to therapeutic targets of interest. However, conventional methods for identifying target binders in a library by Sanger sequencing are low-throughput, labor-intensive, and provide a limited perspective (<0.01%) of the complete sequence space. Moreover, the small sample space can be dominated by nonspecific, preferentially amplifying "parasitic sequences" and plastic-binding sequences, which may lead to the identification of false positives or exclude the identification of target-binding sequences. To overcome these challenges, we employed next-generation Illumina sequencing to couple high-throughput screening and high-throughput sequencing, enabling more comprehensive access to the phage display library sequence space. In this work, we define the hallmarks of binding sequences in next-generation sequencing data, and develop a method that identifies several target-binding phage clones for murine, alternatively activated M2 macrophages with a high (100%) success rate: sequences and binding motifs were reproducibly present across biological replicates; binding motifs were identified across multiple unique sequences; and an unselected, amplified library accurately filtered out parasitic sequences. In addition, we validate the Multiple Em for Motif Elicitation tool as an efficient and principled means of discovering binding sequences.

New generation pharmacogenomic tools: a SNP linkage disequilibrium Map, validated SNP assay resource, and high-throughput instrumentation system for large-scale genetic studies.

PubMed

De La Vega, Francisco M; Dailey, David; Ziegle, Janet; Williams, Julie; Madden, Dawn; Gilbert, Dennis A

2002-06-01

Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.

Towards roll-to-roll manufacturing of polymer photonic devices

NASA Astrophysics Data System (ADS)

Subbaraman, Harish; Lin, Xiaohui; Ling, Tao; Guo, L. Jay; Chen, Ray T.

2014-03-01

Traditionally, polymer photonic devices are fabricated using clean-room processes such as photolithography, e-beam lithography, reactive ion etching (RIE) and lift-off methods etc, which leads to long fabrication time, low throughput and high cost. We have utilized a novel process for fabricating polymer photonic devices using a combination of imprinting and ink jet printing methods, which provides high throughput on a variety of rigid and flexible substrates with low cost. We discuss the manufacturing challenges that need to be overcome in order to realize true implementation of roll-to-roll manufacturing of flexible polymer photonic systems. Several metrology and instrumentation challenges involved such as availability of particulate-free high quality substrate, development and implementation of high-speed in-line and off-line inspection and diagnostic tools with adaptive control for patterned and unpatterned material films, development of reliable hardware, etc need to be addressed and overcome in order to realize a successful manufacturing process. Due to extreme resolution requirements compared to print media, the burden of software and hardware tools on the throughput also needs to be carefully determined. Moreover, the effect of web wander and variations in web speed need to accurately be determined in the design of the system hardware and software. In this paper, we show the realization of solutions for few challenges, and utilizing these solutions for developing a high-rate R2R dual stage ink-jet printer that can provide alignment accuracy of <10μm at a web speed of 5m/min. The development of a roll-to-roll manufacturing system for polymer photonic systems opens limitless possibilities for the deployment of high performance components in a variety of applications including communication, sensing, medicine, agriculture, energy, lighting etc.

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

PubMed

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

2016-12-23

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

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

PubMed Central

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

2016-01-01

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

FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions

PubMed Central

Li, Hui; Xiao, Li; Zhang, Lili; Wu, Jiarui; Wei, Bin; Sun, Ninghui; Zhao, Yi

2018-01-01

smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP) which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP. PMID:29675032

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

PubMed Central

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

2016-01-01

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

Thrombocalc: implementation and uptake of personalized postpartum venous thromboembolism risk assessment in a high-throughput obstetric environment.

PubMed

O'Shaughnessy, Fergal; Donnelly, Jennifer C; Cooley, Sharon M; Deering, Mary; Raman, Ajita; Gannon, Geraldine; Hickey, Jane; Holland, Alan; Hayes, Niamh; Bennett, Kathleen; Ní Áinle, Fionnuala; Cleary, Brian J

2017-11-01

Venous thromboembolism risk assessment (VTERA) is recommended in all pregnant and postpartum women. Our objective was to develop, pilot and implement a user-friendly electronic VTERA tool. We developed "Thrombocalc", an electronic VTERA tool using Microsoft EXCEL ™ . Thrombocalc was designed as a score-based tool to facilitate rapid assessment of all women after childbirth. Calculation of a total score estimated risk of venous thromboembolism in line with consensus guidelines. Recommendations for thromboprophylaxis were included in the VTERA output. Implementation was phased. Uptake of the VTERA tool was assessed prospectively by monitoring the proportion of women who gave birth in our institution and had a completed risk assessment. Factors affecting completion and accuracy of risk assessments were also assessed. Thrombocalc was used prospectively to risk-assess 8380 women between September 2014 and December 2015. Compliance with this tool increased dramatically throughout the study period; over 92% of women were risk-assessed in the last quarter of data collection. Compliance was not adversely affected if delivery took place out of working hours [adjusted odds ratio (aOR) 1.03, 95% confidence interval (CI) 0.93-1.14]. Risk assessment was less likely in the case of cesarean deliveries (aOR 0.66, 95% CI 0.60-0.73) and stillborn infants (aOR 0.48, 95% CI 0.29-0.79). Misclassification of risk factors led to approximately 207 (2.5%) inaccurate thromboprophylaxis recommendations. Our electronic, score-based VTERA tool provides a highly effective mechanism for rapid assessment of individual postpartum venous thromboembolism risk in a high-throughput environment. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

YeATS- a tool suite for analyzing RNA-seq derived transcriptome identifies a highly transcribed putative extensin in heartwood/sapwood transition zone in black walnut

USDA-ARS?s Scientific Manuscript database

The transcriptome provides a functional footprint of the genome by enumerating the molecular components of cells and tissues. The field of transcript discovery has been revolutionized through high-throughput mRNA sequencing (RNA-seq). Here, we present a methodology that replicates and improves exist...

High-throughput screening and small animal models, where are we?

PubMed Central

Giacomotto, Jean; Ségalat, Laurent

2010-01-01

Current high-throughput screening methods for drug discovery rely on the existence of targets. Moreover, most of the hits generated during screenings turn out to be invalid after further testing in animal models. To by-pass these limitations, efforts are now being made to screen chemical libraries on whole animals. One of the most commonly used animal model in biology is the murine model Mus musculus. However, its cost limit its use in large-scale therapeutic screening. In contrast, the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the fish Danio rerio are gaining momentum as screening tools. These organisms combine genetic amenability, low cost and culture conditions that are compatible with large-scale screens. Their main advantage is to allow high-throughput screening in a whole-animal context. Moreover, their use is not dependent on the prior identification of a target and permits the selection of compounds with an improved safety profile. This review surveys the versatility of these animal models for drug discovery and discuss the options available at this day. PMID:20423335

Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens.

PubMed

Morgens, David W; Wainberg, Michael; Boyle, Evan A; Ursu, Oana; Araya, Carlos L; Tsui, C Kimberly; Haney, Michael S; Hess, Gaelen T; Han, Kyuho; Jeng, Edwin E; Li, Amy; Snyder, Michael P; Greenleaf, William J; Kundaje, Anshul; Bassik, Michael C

2017-05-05

CRISPR-Cas9 screens are powerful tools for high-throughput interrogation of genome function, but can be confounded by nuclease-induced toxicity at both on- and off-target sites, likely due to DNA damage. Here, to test potential solutions to this issue, we design and analyse a CRISPR-Cas9 library with 10 variable-length guides per gene and thousands of negative controls targeting non-functional, non-genic regions (termed safe-targeting guides), in addition to non-targeting controls. We find this library has excellent performance in identifying genes affecting growth and sensitivity to the ricin toxin. The safe-targeting guides allow for proper control of toxicity from on-target DNA damage. Using this toxicity as a proxy to measure off-target cutting, we demonstrate with tens of thousands of guides both the nucleotide position-dependent sensitivity to single mismatches and the reduction of off-target cutting using truncated guides. Our results demonstrate a simple strategy for high-throughput evaluation of target specificity and nuclease toxicity in Cas9 screens.

Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens

PubMed Central

Morgens, David W.; Wainberg, Michael; Boyle, Evan A.; Ursu, Oana; Araya, Carlos L.; Tsui, C. Kimberly; Haney, Michael S.; Hess, Gaelen T.; Han, Kyuho; Jeng, Edwin E.; Li, Amy; Snyder, Michael P.; Greenleaf, William J.; Kundaje, Anshul; Bassik, Michael C.

2017-01-01

CRISPR-Cas9 screens are powerful tools for high-throughput interrogation of genome function, but can be confounded by nuclease-induced toxicity at both on- and off-target sites, likely due to DNA damage. Here, to test potential solutions to this issue, we design and analyse a CRISPR-Cas9 library with 10 variable-length guides per gene and thousands of negative controls targeting non-functional, non-genic regions (termed safe-targeting guides), in addition to non-targeting controls. We find this library has excellent performance in identifying genes affecting growth and sensitivity to the ricin toxin. The safe-targeting guides allow for proper control of toxicity from on-target DNA damage. Using this toxicity as a proxy to measure off-target cutting, we demonstrate with tens of thousands of guides both the nucleotide position-dependent sensitivity to single mismatches and the reduction of off-target cutting using truncated guides. Our results demonstrate a simple strategy for high-throughput evaluation of target specificity and nuclease toxicity in Cas9 screens. PMID:28474669

Epigenetics and Epigenomics of Plants.

PubMed

Yadav, Chandra Bhan; Pandey, Garima; Muthamilarasan, Mehanathan; Prasad, Manoj

2018-01-23

The genetic material DNA in association with histone proteins forms the complex structure called chromatin, which is prone to undergo modification through certain epigenetic mechanisms including cytosine DNA methylation, histone modifications, and small RNA-mediated methylation. Alterations in chromatin structure lead to inaccessibility of genomic DNA to various regulatory proteins such as transcription factors, which eventually modulates gene expression. Advancements in high-throughput sequencing technologies have provided the opportunity to study the epigenetic mechanisms at genome-wide levels. Epigenomic studies using high-throughput technologies will widen the understanding of mechanisms as well as functions of regulatory pathways in plant genomes, which will further help in manipulating these pathways using genetic and biochemical approaches. This technology could be a potential research tool for displaying the systematic associations of genetic and epigenetic variations, especially in terms of cytosine methylation onto the genomic region in a specific cell or tissue. A comprehensive study of plant populations to correlate genotype to epigenotype and to phenotype, and also the study of methyl quantitative trait loci (QTL) or epiGWAS, is possible by using high-throughput sequencing methods, which will further accelerate molecular breeding programs for crop improvement. Graphical Abstract.

Fast and accurate enzyme activity measurements using a chip-based microfluidic calorimeter.

PubMed

van Schie, Morten M C H; Ebrahimi, Kourosh Honarmand; Hagen, Wilfred R; Hagedoorn, Peter-Leon

2018-03-01

Recent developments in microfluidic and nanofluidic technologies have resulted in development of new chip-based microfluidic calorimeters with potential use in different fields. One application would be the accurate high-throughput measurement of enzyme activity. Calorimetry is a generic way to measure activity of enzymes, but unlike conventional calorimeters, chip-based calorimeters can be easily automated and implemented in high-throughput screening platforms. However, application of chip-based microfluidic calorimeters to measure enzyme activity has been limited due to problems associated with miniaturization such as incomplete mixing and a decrease in volumetric heat generated. To address these problems we introduced a calibration method and devised a convenient protocol for using a chip-based microfluidic calorimeter. Using the new calibration method, the progress curve of alkaline phosphatase, which has product inhibition for phosphate, measured by the calorimeter was the same as that recorded by UV-visible spectroscopy. Our results may enable use of current chip-based microfluidic calorimeters in a simple manner as a tool for high-throughput screening of enzyme activity with potential applications in drug discovery and enzyme engineering. Copyright © 2017. Published by Elsevier Inc.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Development and use of molecular markers: past and present.

PubMed

Grover, Atul; Sharma, P C

2016-01-01

Molecular markers, due to their stability, cost-effectiveness and ease of use provide an immensely popular tool for a variety of applications including genome mapping, gene tagging, genetic diversity diversity, phylogenetic analysis and forensic investigations. In the last three decades, a number of molecular marker techniques have been developed and exploited worldwide in different systems. However, only a handful of these techniques, namely RFLPs, RAPDs, AFLPs, ISSRs, SSRs and SNPs have received global acceptance. A recent revolution in DNA sequencing techniques has taken the discovery and application of molecular markers to high-throughput and ultrahigh-throughput levels. Although, the choice of marker will obviously depend on the targeted use, microsatellites, SNPs and genotyping by sequencing (GBS) largely fulfill most of the user requirements. Further, modern transcriptomic and functional markers will lead the ventures onto high-density genetic map construction, identification of QTLs, breeding and conservation strategies in times to come in combination with other high throughput techniques. This review presents an overview of different marker technologies and their variants with a comparative account of their characteristic features and applications.

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

A high-throughput semi-automated preparation for filtered synaptoneurosomes.

PubMed

Murphy, Kathryn M; Balsor, Justin; Beshara, Simon; Siu, Caitlin; Pinto, Joshua G A

2014-09-30

Synaptoneurosomes have become an important tool for studying synaptic proteins. The filtered synaptoneurosomes preparation originally developed by Hollingsworth et al. (1985) is widely used and is an easy method to prepare synaptoneurosomes. The hand processing steps in that preparation, however, are labor intensive and have become a bottleneck for current proteomic studies using synaptoneurosomes. For this reason, we developed new steps for tissue homogenization and filtration that transform the preparation of synaptoneurosomes to a high-throughput, semi-automated process. We implemented a standardized protocol with easy to follow steps for homogenizing multiple samples simultaneously using a FastPrep tissue homogenizer (MP Biomedicals, LLC) and then filtering all of the samples in centrifugal filter units (EMD Millipore, Corp). The new steps dramatically reduce the time to prepare synaptoneurosomes from hours to minutes, increase sample recovery, and nearly double enrichment for synaptic proteins. These steps are also compatible with biosafety requirements for working with pathogen infected brain tissue. The new high-throughput semi-automated steps to prepare synaptoneurosomes are timely technical advances for studies of low abundance synaptic proteins in valuable tissue samples. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

P-TRAP: a Panicle TRAit Phenotyping tool.

PubMed

A L-Tam, Faroq; Adam, Helene; Anjos, António dos; Lorieux, Mathias; Larmande, Pierre; Ghesquière, Alain; Jouannic, Stefan; Shahbazkia, Hamid Reza

2013-08-29

In crops, inflorescence complexity and the shape and size of the seed are among the most important characters that influence yield. For example, rice panicles vary considerably in the number and order of branches, elongation of the axis, and the shape and size of the seed. Manual low-throughput phenotyping methods are time consuming, and the results are unreliable. However, high-throughput image analysis of the qualitative and quantitative traits of rice panicles is essential for understanding the diversity of the panicle as well as for breeding programs. This paper presents P-TRAP software (Panicle TRAit Phenotyping), a free open source application for high-throughput measurements of panicle architecture and seed-related traits. The software is written in Java and can be used with different platforms (the user-friendly Graphical User Interface (GUI) uses Netbeans Platform 7.3). The application offers three main tools: a tool for the analysis of panicle structure, a spikelet/grain counting tool, and a tool for the analysis of seed shape. The three tools can be used independently or simultaneously for analysis of the same image. Results are then reported in the Extensible Markup Language (XML) and Comma Separated Values (CSV) file formats. Images of rice panicles were used to evaluate the efficiency and robustness of the software. Compared to data obtained by manual processing, P-TRAP produced reliable results in a much shorter time. In addition, manual processing is not repeatable because dry panicles are vulnerable to damage. The software is very useful, practical and collects much more data than human operators. P-TRAP is a new open source software that automatically recognizes the structure of a panicle and the seeds on the panicle in numeric images. The software processes and quantifies several traits related to panicle structure, detects and counts the grains, and measures their shape parameters. In short, P-TRAP offers both efficient results and a user-friendly environment for experiments. The experimental results showed very good accuracy compared to field operator, expert verification and well-known academic methods.

P-TRAP: a Panicle Trait Phenotyping tool

PubMed Central

2013-01-01

Background In crops, inflorescence complexity and the shape and size of the seed are among the most important characters that influence yield. For example, rice panicles vary considerably in the number and order of branches, elongation of the axis, and the shape and size of the seed. Manual low-throughput phenotyping methods are time consuming, and the results are unreliable. However, high-throughput image analysis of the qualitative and quantitative traits of rice panicles is essential for understanding the diversity of the panicle as well as for breeding programs. Results This paper presents P-TRAP software (Panicle TRAit Phenotyping), a free open source application for high-throughput measurements of panicle architecture and seed-related traits. The software is written in Java and can be used with different platforms (the user-friendly Graphical User Interface (GUI) uses Netbeans Platform 7.3). The application offers three main tools: a tool for the analysis of panicle structure, a spikelet/grain counting tool, and a tool for the analysis of seed shape. The three tools can be used independently or simultaneously for analysis of the same image. Results are then reported in the Extensible Markup Language (XML) and Comma Separated Values (CSV) file formats. Images of rice panicles were used to evaluate the efficiency and robustness of the software. Compared to data obtained by manual processing, P-TRAP produced reliable results in a much shorter time. In addition, manual processing is not repeatable because dry panicles are vulnerable to damage. The software is very useful, practical and collects much more data than human operators. Conclusions P-TRAP is a new open source software that automatically recognizes the structure of a panicle and the seeds on the panicle in numeric images. The software processes and quantifies several traits related to panicle structure, detects and counts the grains, and measures their shape parameters. In short, P-TRAP offers both efficient results and a user-friendly environment for experiments. The experimental results showed very good accuracy compared to field operator, expert verification and well-known academic methods. PMID:23987653

On-site evaluation of commercial-scale hybrid catfish production using cryopreserved blue catfish sperm

USDA-ARS?s Scientific Manuscript database

Cryopreservation is an effective tool for conservation of genetic resources and is becoming increasingly used worldwide with aquatic species. Broadening the application of this technology to a commercial scale through high-throughput approaches has become essential for use with aquatic species. This...

20180312 - Evaluating the applicability of read-across tools and high throughput screening data for food relevant chemicals (SOT)

EPA Science Inventory

Alternative toxicity assessment methods to characterize the hazards of chemical substances have been proposed to reduce animal testing and screen thousands of chemicals in an efficient manner. Resources to accomplish these goals include utilizing large in vitro chemical screening...

High-throughput interpretation of gene structure changes in human and nonhuman resequencing data, using ACE

USDA-ARS?s Scientific Manuscript database

We describe a suite of software tools for identifying possible functional changes in gene structure that may result from sequence variants. ACE (“Assessing Changes to Exons”) converts phased genotype calls to a collection of explicit haplotype sequences, maps transcript annotations onto them, detect...

Ultra high-throughput nucleic acid sequencing as a tool for virus discovery in the turkey gut.

USDA-ARS?s Scientific Manuscript database

Recently, the use of the next generation of nucleic acid sequencing technology (i.e., 454 pyrosequencing, as developed by Roche/454 Life Sciences) has allowed an in-depth look at the uncultivated microorganisms present in complex environmental samples, including samples with agricultural importance....

Toxicokinetic and Dosimetry Modeling Tools for Exposure Reconstruction: US EPA's Rapid Exposure and Dosimetry (RED) Project

EPA Science Inventory

New technologies and in vitro testing approaches have been valuable additions to risk assessments that have historically relied solely on in vivo test results. Compared to in vivo methods, in vitro high throughput screening (HTS) assays are less expensive, faster and can provide ...

Mixture toxicology in the 21st century: Pathway-based concepts and tools

EPA Science Inventory

The past decade has witnessed notable evolution of approaches focused on predicting chemical hazards and risks in the absence of empirical data from resource-intensive in vivo toxicity tests. In silico models, in vitro high-throughput toxicity assays, and short-term in vivo tests...

EVALUATING TOOLS AND MODELS USED FOR QUANTITATIVE EXTRAPOLATION OF IN VITRO TO IN VIVO DATA FOR NEUROTOXICANTS

EPA Science Inventory

Comparisons of high throughput screening data to human exposures assume that media concentrations are equivalent to steady-state blood concentrations. This assumes the partitioning of the chemical between media and cells is equivalent to the partitioning of the chemical between b...

Biological profiling and dose-response modeling tools, characterizing uncertainty

EPA Science Inventory

Through its ToxCast project, the U.S. EPA has developed a battery of in vitro high throughput screening (HTS) assays designed to assess the potential toxicity of environmental chemicals. At present, over 1800 chemicals have been tested in up to 600 assays, yielding a large number...

Multi-locus mixed model analysis of stem rust resistance in a worldwide collection of winter wheat

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping is a powerful tool for dissecting the relationship between phenotypes and genetic variants in diverse populations. With improved cost efficiency of high-throughput genotyping platforms, association mapping is a desirable method to mine populations for favorable allele...

Predictive Endocrine Testing in the 21st Century Using In Vitro Assays of Estrogen Receptor Signaling Responses

EPA Science Inventory

Thousands of environmental chemicals are subject to regulatory review for their potential to be endocrine disruptors (ED). In vitro high-throughput screening (HTS) assays have emerged as a potential tool for prioritizing chemicals for ED-related whole-animal tests. In this study,...

Holographic femtosecond laser processing and its application to biological materials (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hayasaki, Yoshio

2017-02-01

Femtosecond laser processing is a promising tool for fabricating novel and useful structures on the surfaces of and inside materials. An enormous number of pulse irradiation points will be required for fabricating actual structures with millimeter scale, and therefore, the throughput of femtosecond laser processing must be improved for practical adoption of this technique. One promising method to improve throughput is parallel pulse generation based on a computer-generated hologram (CGH) displayed on a spatial light modulator (SLM), a technique called holographic femtosecond laser processing. The holographic method has the advantages such as high throughput, high light use efficiency, and variable, instantaneous, and 3D patterning. Furthermore, the use of an SLM gives an ability to correct unknown imperfections of the optical system and inhomogeneity in a sample using in-system optimization of the CGH. Furthermore, the CGH can adaptively compensate in response to dynamic unpredictable mechanical movements, air and liquid disturbances, a shape variation and deformation of the target sample, as well as adaptive wavefront control for environmental changes. Therefore, it is a powerful tool for the fabrication of biological cells and tissues, because they have free form, variable, and deformable structures. In this paper, we present the principle and the experimental setup of holographic femtosecond laser processing, and the effective way for processing the biological sample. We demonstrate the femtosecond laser processing of biological materials and the processing properties.

Statistical Approach To Estimate Vaccinia-Specific Neutralizing Antibody Titers Using a High-Throughput Assay▿

PubMed Central

Kennedy, Richard; Pankratz, V. Shane; Swanson, Eric; Watson, David; Golding, Hana; Poland, Gregory A.

2009-01-01

Because of the bioterrorism threat posed by agents such as variola virus, considerable time, resources, and effort have been devoted to biodefense preparation. One avenue of this research has been the development of rapid, sensitive, high-throughput assays to validate immune responses to poxviruses. Here we describe the adaptation of a β-galactosidase reporter-based vaccinia virus neutralization assay to large-scale use in a study that included over 1,000 subjects. We also describe the statistical methods involved in analyzing the large quantity of data generated. The assay and its associated methods should prove useful tools in monitoring immune responses to next-generation smallpox vaccines, studying poxvirus immunity, and evaluating therapeutic agents such as vaccinia virus immune globulin. PMID:19535540

Fixing clearance as early as lead optimization using high throughput in vitro incubations in combination with exact mass detection and automatic structure elucidation of metabolites.

PubMed

Zimmerlin, Alfred; Kiffe, Michael

2013-01-01

New enabling MS technologies have made it possible to elucidate metabolic pathways present in ex vivo (blood, bile and/or urine) or in vitro (liver microsomes, hepatocytes and/or S9) samples. When investigating samples from high throughput assays the challenge that the user is facing now is to extract the appropriate information and compile it so that it is understandable to all. Medicinal chemist may then design the next generation of (better) drug candidates combining the needs for potency and metabolic stability and their synthetic creativity. This review focuses on the comparison of these enabling MS technologies and the IT tools developed for their interpretation.

High-Throughput Nanofabrication of Infra-red and Chiral Metamaterials using Nanospherical-Lens Lithography

PubMed Central

Chang, Yun-Chorng; Lu, Sih-Chen; Chung, Hsin-Chan; Wang, Shih-Ming; Tsai, Tzung-Da; Guo, Tzung-Fang

2013-01-01

Various infra-red and planar chiral metamaterials were fabricated using the modified Nanospherical-Lens Lithography. By replacing the light source with a hand-held ultraviolet lamp, its asymmetric light emission pattern produces the elliptical-shaped photoresist holes after passing through the spheres. The long axis of the ellipse is parallel to the lamp direction. The fabricated ellipse arrays exhibit localized surface plasmon resonance in mid-infra-red and are ideal platforms for surface enhanced infra-red absorption (SEIRA). We also demonstrate a way to design and fabricate complicated patterns by tuning parameters in each exposure step. This method is both high-throughput and low-cost, which is a powerful tool for future infra-red metamaterials applications. PMID:24284941

Xi-CAM v1.2.3

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

PANDOLFI, RONALD; KUMAR, DINESH; VENKATAKRISHNAN, SINGANALLUR

Xi-CAM aims to provide a community driven platform for multimodal analysis in synchrotron science. The platform core provides a robust plugin infrastructure for extensibility, allowing continuing development to simply add further functionality. Current modules include tools for characterization with (GI)SAXS, Tomography, and XAS. This will continue to serve as a development base as algorithms for multimodal analysis develop. Seamless remote data access, visualization and analysis are key elements of Xi-CAM, and will become critical to synchrotron data infrastructure as expectations for future data volume and acquisition rates rise with continuously increasing throughputs. The highly interactive design elements of Xi-cam willmore » similarly support a generation of users which depend on immediate data quality feedback during high-throughput or burst acquisition modes.« less

RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA

PubMed Central

Wright, Imogen A.; Travers, Simon A.

2014-01-01

The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance. PMID:24861618

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

PubMed

Baumann, Pascal; Hahn, Tobias; Hubbuch, Jürgen

2015-10-01

Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance. © 2015 Wiley Periodicals, Inc.

Polymer-Based Dense Fluidic Networks for High Throughput Screening with Ultrasensitive Fluorescence Detection

PubMed Central

Okagbare, Paul I.; Soper, Steven A.

2011-01-01

Microfluidics represents a viable platform for performing High Throughput Screening (HTS) due to its ability to automate fluid handling and generate fluidic networks with high number densities over small footprints appropriate for the simultaneous optical interrogation of many screening assays. While most HTS campaigns depend on fluorescence, readers typically use point detection and serially address the assay results significantly lowering throughput or detection sensitivity due to a low duty cycle. To address this challenge, we present here the fabrication of a high density microfluidic network packed into the imaging area of a large field-of-view (FoV) ultrasensitive fluorescence detection system. The fluidic channels were 1, 5 or 10 μm (width), 1 μm (depth) with a pitch of 1–10 μm and each fluidic processor was individually addressable. The fluidic chip was produced from a molding tool using hot embossing and thermal fusion bonding to enclose the fluidic channels. A 40X microscope objective (numerical aperture = 0.75) created a FoV of 200 μm, providing the ability to interrogate ~25 channels using the current fluidic configuration. An ultrasensitive fluorescence detection system with a large FoV was used to transduce fluorescence signals simultaneously from each fluidic processor onto the active area of an electron multiplying charge-coupled device (EMCCD). The utility of these multichannel networks for HTS was demonstrated by carrying out the high throughput monitoring of the activity of an enzyme, APE1, used as a model screening assay. PMID:20872611

A Perspective on the Future of High-Throughput RNAi Screening: Will CRISPR Cut Out the Competition or Can RNAi Help Guide the Way?

PubMed

Taylor, Jessica; Woodcock, Simon

2015-09-01

For more than a decade, RNA interference (RNAi) has brought about an entirely new approach to functional genomics screening. Enabling high-throughput loss-of-function (LOF) screens against the human genome, identifying new drug targets, and significantly advancing experimental biology, RNAi is a fast, flexible technology that is compatible with existing high-throughput systems and processes; however, the recent advent of clustered regularly interspaced palindromic repeats (CRISPR)-Cas, a powerful new precise genome-editing (PGE) technology, has opened up vast possibilities for functional genomics. CRISPR-Cas is novel in its simplicity: one piece of easily engineered guide RNA (gRNA) is used to target a gene sequence, and Cas9 expression is required in the cells. The targeted double-strand break introduced by the gRNA-Cas9 complex is highly effective at removing gene expression compared to RNAi. Together with the reduced cost and complexity of CRISPR-Cas, there is the realistic opportunity to use PGE to screen for phenotypic effects in a total gene knockout background. This review summarizes the exciting development of CRISPR-Cas as a high-throughput screening tool, comparing its future potential to that of well-established RNAi screening techniques, and highlighting future challenges and opportunities within these disciplines. We conclude that the two technologies actually complement rather than compete with each other, enabling greater understanding of the genome in relation to drug discovery. © 2015 Society for Laboratory Automation and Screening.

Analysis of Illumina Microbial Assemblies

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

Clum, Alicia; Foster, Brian; Froula, Jeff

2010-05-28

Since the emerging of second generation sequencing technologies, the evaluation of different sequencing approaches and their assembly strategies for different types of genomes has become an important undertaken. Next generation sequencing technologies dramatically increase sequence throughput while decreasing cost, making them an attractive tool for whole genome shotgun sequencing. To compare different approaches for de-novo whole genome assembly, appropriate tools and a solid understanding of both quantity and quality of the underlying sequence data are crucial. Here, we performed an in-depth analysis of short-read Illumina sequence assembly strategies for bacterial and archaeal genomes. Different types of Illumina libraries as wellmore » as different trim parameters and assemblers were evaluated. Results of the comparative analysis and sequencing platforms will be presented. The goal of this analysis is to develop a cost-effective approach for the increased throughput of the generation of high quality microbial genomes.« less

Direct Duplex Detection: An Emerging Tool in the RNA Structure Analysis Toolbox.

PubMed

Weidmann, Chase A; Mustoe, Anthony M; Weeks, Kevin M

2016-09-01

While a variety of powerful tools exists for analyzing RNA structure, identifying long-range and intermolecular base-pairing interactions has remained challenging. Recently, three groups introduced a high-throughput strategy that uses psoralen-mediated crosslinking to directly identify RNA-RNA duplexes in cells. Initial application of these methods highlights the preponderance of long-range structures within and between RNA molecules and their widespread structural dynamics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ion beam lithography system

DOEpatents

Leung, Ka-Ngo

2005-08-02

A maskless plasma-formed ion beam lithography tool provides for patterning of sub-50 nm features on large area flat or curved substrate surfaces. The system is very compact and does not require an accelerator column and electrostatic beam scanning components. The patterns are formed by switching beamlets on or off from a two electrode blanking system with the substrate being scanned mechanically in one dimension. This arrangement can provide a maskless nano-beam lithography tool for economic and high throughput processing.

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

PubMed Central

Trapnell, Cole; Roberts, Adam; Goff, Loyal; Pertea, Geo; Kim, Daehwan; Kelley, David R; Pimentel, Harold; Salzberg, Steven L; Rinn, John L; Pachter, Lior

2012-01-01

Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ~1 h of hands-on time. PMID:22383036

Nanostructured plasmonic interferometers for ultrasensitive label-free biosensing

NASA Astrophysics Data System (ADS)

Gao, Yongkang

Optical biosensors that utilize surface plasmon resonance (SPR) technique to analyze the biomolecular interactions have been extensively explored in the last two decades and have become the gold standard for label-free biosensing. These powerful sensing tools allow fast, highly-sensitive monitoring of the interaction between biomolecules in real time, without the need for laborious fluorescent labeling, and have found widely ranging applications from biomedical diagnostics and drug discovery, to environmental sensing and food safety monitoring. However, the prism-coupling SPR geometry is complex and bulky, and has severely limited the integration of this technique into low-cost portable biomedical devices for point-of-care diagnostics and personal healthcare applications. Also, the complex prism-coupling scheme prevents the use of high numerical aperture (NA) optics to increase the spatial resolution for multi-channel, high-throughput detection in SPR imaging mode. This dissertation is focused on the design and fabrication of a promising new class of nanopatterned interferometric SPR sensors that integrate the strengths of miniaturized nanoplasmonic architectures with sensitive optical interferometry techniques to achieve bold advances in SPR biosensing. The nanosensor chips developed provide superior sensing performance comparable to conventional SPR systems, but employing a far simpler collinear optical transmission geometry, which largely facilitates system integration, miniaturization, and low-cost production. Moreover, the fabricated nanostructure-based SPR sensors feature a very small sensor footprint, allowing massive multiplexing on a chip for high-throughput detection. The successful transformation of SPR technique from bulky prism-coupling setup into this low-cost compact plasmonic platform would have a far-reaching impact on point-of-care diagnostic tools and also lead to advances in high-throughput sensing applications in proteomics, immunology, drug discovery, and fundamental cell biology research.

The Stanford Automated Mounter: Enabling High-Throughput Protein Crystal Screening at SSRL

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

Smith, C.A.; Cohen, A.E.

2009-05-26

The macromolecular crystallography experiment lends itself perfectly to high-throughput technologies. The initial steps including the expression, purification, and crystallization of protein crystals, along with some of the later steps involving data processing and structure determination have all been automated to the point where some of the last remaining bottlenecks in the process have been crystal mounting, crystal screening, and data collection. At the Stanford Synchrotron Radiation Laboratory, a National User Facility that provides extremely brilliant X-ray photon beams for use in materials science, environmental science, and structural biology research, the incorporation of advanced robotics has enabled crystals to be screenedmore » in a true high-throughput fashion, thus dramatically accelerating the final steps. Up to 288 frozen crystals can be mounted by the beamline robot (the Stanford Auto-Mounting System) and screened for diffraction quality in a matter of hours without intervention. The best quality crystals can then be remounted for the collection of complete X-ray diffraction data sets. Furthermore, the entire screening and data collection experiment can be controlled from the experimenter's home laboratory by means of advanced software tools that enable network-based control of the highly automated beamlines.« less

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

An evaluation of the accuracy and speed of metagenome analysis tools

PubMed Central

Lindgreen, Stinus; Adair, Karen L.; Gardner, Paul P.

2016-01-01

Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming, and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity. Data sets and results are freely available from http://www.ucbioinformatics.org/metabenchmark.html PMID:26778510

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

PubMed

Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun

2017-09-14

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Multiplexed ChIP-Seq Using Direct Nucleosome Barcoding: A Tool for High-Throughput Chromatin Analysis.

PubMed

Chabbert, Christophe D; Adjalley, Sophie H; Steinmetz, Lars M; Pelechano, Vicent

2018-01-01

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) or microarray hybridization (ChIP-on-chip) are standard methods for the study of transcription factor binding sites and histone chemical modifications. However, these approaches only allow profiling of a single factor or protein modification at a time.In this chapter, we present Bar-ChIP, a higher throughput version of ChIP-Seq that relies on the direct ligation of molecular barcodes to chromatin fragments. Bar-ChIP enables the concurrent profiling of multiple DNA-protein interactions and is therefore amenable to experimental scale-up, without the need for any robotic instrumentation.

UPLC-MS-ELSD-PDA as a powerful dereplication tool to facilitate compound identification from small molecule natural product libraries

USDA-ARS?s Scientific Manuscript database

Generation of natural product libraries containing column fractions, each with only a few small molecules, by a high throughput, automated fractionation system has made it possible to implement an improved dereplication strategy for selection and prioritization of hits in a natural product discovery...

Sensitive genotyping of foodborne-associated human noroviruses and hepatitis A virus using an array-based platform

USDA-ARS?s Scientific Manuscript database

The viral pathogens, human norovirus (NoV) and hepatitis A virus (HAV), are significant contributors of foodborne associated outbreaks. To develop a typing tool for foodborne viruses, a focused, low-density DNA microarray was developed in conjunction with a rapid and high-throughput fluorescent meth...

Extrapolation of mammalian-based ToxCast assay results to non-mammalian species to evaluate endocrine disruption

EPA Science Inventory

In vitro high-throughput screening (HTS) and in silico technologies have emerged as 21st century tools for chemical hazard identification. In 2007 the U.S. Environmental Protection Agency (EPA) launched the ToxCast Program, which has screened thousands of chemicals in hundreds of...

Cross-species extrapolation of mammalian-based ToxCast Data using Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS)

EPA Science Inventory

In vitro high-throughput screening (HTS) and in silico technologies have emerged as 21st century tools for chemical hazard identification. In 2007 the U.S. Environmental Protection Agency (EPA) launched the ToxCast Program, which has screened thousands of chemicals in hundreds of...

So Many Chemicals, So Little Time... Evolution of ...

EPA Pesticide Factsheets

Current testing is limited by traditional testing models and regulatory systems. An overview is given of high throughput screening approaches to provide broader chemical and biological coverage, toxicokinetics and molecular pathway data and tools to facilitate utilization for regulatory application. Presentation at the NCSU Toxicology lecture series on the Evolution of Computational Toxicology

Development of an Influenza virus protein array using Sortagging technology

PubMed Central

Sinisi, Antonia; Popp, Maximilian Wei-Lin; Antos, John M.; Pansegrau, Werner; Savino, Silvana; Nissum, Mikkel; Rappuoli, Rino; Ploegh, Hidde L.; Buti, Ludovico

2013-01-01

Protein array technology is an emerging tool that enables high throughput screening of protein-protein or protein-lipid interactions and identification of immunodominant antigens during the course of a bacterial or viral infection. In this work we developed an Influenza virus protein array using the sortase-mediated transpeptidation reaction known as “Sortagging”. LPETG-tagged Influenza virus proteins from bacterial and eukaryotic cellular extracts were immobilized at their carboxyl-termini onto a pre-activated amine-glass slide coated with a Gly3 linker. Immobilized proteins were revealed by specific antibodies and the newly generated Sortag-protein chip can be used as a device for antigen and/or antibody screening. The specificity of the Sortase A (SrtA) reaction avoids purification steps in array building and allows immobilization of proteins in an oriented fashion. Previously, this versatile technology has been successfully employed for protein labeling and protein conjugation. Here, the tool is implemented to covalently link proteins of a viral genome onto a solid support. The system could readily be scaled up to proteins of larger genomes in order to develop protein arrays for high throughput screening. PMID:22594688

Ticks and Tick-Borne Pathogens of the Caribbean: Current Understanding and Future Directions for More Comprehensive Surveillance.

PubMed

Gondard, Mathilde; Cabezas-Cruz, Alejandro; Charles, Roxanne A; Vayssier-Taussat, Muriel; Albina, Emmanuel; Moutailler, Sara

2017-01-01

Ticks are obligate hematophagous arthropods of significant importance to human and veterinary medicine. They transmit a vast array of pathogens, including bacteria, viruses, protozoa, and helminths. Most epidemiological data on ticks and tick-borne pathogens (TBPs) in the West Indies are limited to common livestock pathogens such as Ehrlichia ruminantium, Babesia spp. (i.e., B. bovis and B. bigemina ), and Anaplasma marginale , and less information is available on companion animal pathogens. Of note, human tick-borne diseases (TBDs) remain almost completely uncharacterized in the West Indies. Information on TBP presence in wildlife is also missing. Herein, we provide a comprehensive review of the ticks and TBPs affecting human and animal health in the Caribbean, and introduce the challenges associated with understanding TBD epidemiology and implementing successful TBD management in this region. In particular, we stress the need for innovative and versatile surveillance tools using high-throughput pathogen detection (e.g., high-throughput real-time microfluidic PCR). The use of such tools in large epidemiological surveys will likely improve TBD prevention and control programs in the Caribbean.

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

STOP using just GO: a multi-ontology hypothesis generation tool for high throughput experimentation

PubMed Central

2013-01-01

Background Gene Ontology (GO) enrichment analysis remains one of the most common methods for hypothesis generation from high throughput datasets. However, we believe that researchers strive to test other hypotheses that fall outside of GO. Here, we developed and evaluated a tool for hypothesis generation from gene or protein lists using ontological concepts present in manually curated text that describes those genes and proteins. Results As a consequence we have developed the method Statistical Tracking of Ontological Phrases (STOP) that expands the realm of testable hypotheses in gene set enrichment analyses by integrating automated annotations of genes to terms from over 200 biomedical ontologies. While not as precise as manually curated terms, we find that the additional enriched concepts have value when coupled with traditional enrichment analyses using curated terms. Conclusion Multiple ontologies have been developed for gene and protein annotation, by using a dataset of both manually curated GO terms and automatically recognized concepts from curated text we can expand the realm of hypotheses that can be discovered. The web application STOP is available at http://mooneygroup.org/stop/. PMID:23409969

21st century tools to prioritize contaminants for monitoring and ...

EPA Pesticide Factsheets

The webinar focused on ways that ToxCast high throughput screening data and the adverse outcome pathway framework, under development in the CSS program, can be used to prioritize environmental contaminants for monitoring and management. The webinar focused on ways that ToxCast high throughput screening data and the adverse outcome pathway framework, under development in the CSS program, can be used to prioritize environmental contaminants for monitoring and management. The work presented focused on case studies conducted in Region 8, in collaboration with EPA Region 8 and NEIC, as well as other federal (USGS, US FWS) and regional partners (Northern Colorado Plateau Network). The Consortium for Research and Education on Emerging Contaminants (CREEC) is a grass-roots 501(c)(3) non-profit organization comprised of world-class scientists and stakeholders with a shared interest in the source, fate, and physiological effects of contaminants of emerging concern (www.creec.net). As such, they represent an important group of stakeholders with an interest in applying the data, approaches, and tools that are being developed by the CSS program.

Applying 21st century tools to watersheds of the western US ...

EPA Pesticide Factsheets

The webinar focused on ways that ToxCast high throughput screening data and the adverse outcome pathway framework, under development in the CSS program, can be used to prioritize environmental contaminants for monitoring and management. The webinar focused on ways that ToxCast high throughput screening data and the adverse outcome pathway framework, under development in the CSS program, can be used to prioritize environmental contaminants for monitoring and management. The work presented focused on case studies conducted in Region 8, in collaboration with EPA Region 8 and NEIC, as well as other federal (USGS, US FWS) and regional partners (Northern Colorado Plateau Network). The Consortium for Research and Education on Emerging Contaminants (CREEC) is a grass-roots 501(c)(3) non-profit organization comprised of world-class scientists and stakeholders with a shared interest in the source, fate, and physiological effects of contaminants of emerging concern (www.creec.net). As such, they represent an important group of stakeholders with an interest in applying the data, approaches, and tools that are being developed by the CSS program.

The identification of complete domains within protein sequences using accurate E-values for semi-global alignment

PubMed Central

Kann, Maricel G.; Sheetlin, Sergey L.; Park, Yonil; Bryant, Stephen H.; Spouge, John L.

2007-01-01

The sequencing of complete genomes has created a pressing need for automated annotation of gene function. Because domains are the basic units of protein function and evolution, a gene can be annotated from a domain database by aligning domains to the corresponding protein sequence. Ideally, complete domains are aligned to protein subsequences, in a ‘semi-global alignment’. Local alignment, which aligns pieces of domains to subsequences, is common in high-throughput annotation applications, however. It is a mature technique, with the heuristics and accurate E-values required for screening large databases and evaluating the screening results. Hidden Markov models (HMMs) provide an alternative theoretical framework for semi-global alignment, but their use is limited because they lack heuristic acceleration and accurate E-values. Our new tool, GLOBAL, overcomes some limitations of previous semi-global HMMs: it has accurate E-values and the possibility of the heuristic acceleration required for high-throughput applications. Moreover, according to a standard of truth based on protein structure, two semi-global HMM alignment tools (GLOBAL and HMMer) had comparable performance in identifying complete domains, but distinctly outperformed two tools based on local alignment. When searching for complete protein domains, therefore, GLOBAL avoids disadvantages commonly associated with HMMs, yet maintains their superior retrieval performance. PMID:17596268

04-ERD-052-Final Report

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

Loots, G G; Ovcharenko, I; Collette, N

2007-02-26

Generating the sequence of the human genome represents a colossal achievement for science and mankind. The technical use for the human genome project information holds great promise to cure disease, prevent bioterror threats, as well as to learn about human origins. Yet converting the sequence data into biological meaningful information has not been immediately obvious, and we are still in the preliminary stages of understanding how the genome is organized, what are the functional building blocks and how do these sequences mediate complex biological processes. The overarching goal of this program was to develop novel methods and high throughput strategiesmore » for determining the functions of ''anonymous'' human genes that are evolutionarily deeply conserved in other vertebrates. We coupled analytical tool development and computational predictions regarding gene function with novel high throughput experimental strategies and tested biological predictions in the laboratory. The tools required for comparative genomic data-mining are fundamentally the same whether they are applied to scientific studies of related microbes or the search for functions of novel human genes. For this reason the tools, conceptual framework and the coupled informatics-experimental biology paradigm we developed in this LDRD has many potential scientific applications relevant to LLNL multidisciplinary research in bio-defense, bioengineering, bionanosciences and microbial and environmental genomics.« less

Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

PubMed Central

Wetmore, Barbara A.; Wambaugh, John F.; Allen, Brittany; Ferguson, Stephen S.; Sochaski, Mark A.; Setzer, R. Woodrow; Houck, Keith A.; Strope, Cory L.; Cantwell, Katherine; Judson, Richard S.; LeCluyse, Edward; Clewell, Harvey J.; Thomas, Russell S.; Andersen, Melvin E.

2015-01-01

We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast efforts expand (ie, Phase II) beyond food-use pesticides toward a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. Environmental Protection Agency (EPA) ExpoCast program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, 3 or 13 chemicals possessed AERs < 1 or < 100, respectively. Diverse bioactivities across a range of assays and concentrations were also noted across the wider chemical space surveyed. The availability of HT exposure estimation and bioactivity screening tools provides an opportunity to incorporate a risk-based strategy for use in testing prioritization. PMID:26251325

FOREWORD: Focus on Combinatorial Materials Science Focus on Combinatorial Materials Science

NASA Astrophysics Data System (ADS)

Chikyo, Toyohiro

2011-10-01

About 15 years have passed since the introduction of modern combinatorial synthesis and high-throughput techniques for the development of novel inorganic materials; however, similar methods existed before. The most famous was reported in 1970 by Hanak who prepared composition-spread films of metal alloys by sputtering mixed-material targets. Although this method was innovative, it was rarely used because of the large amount of data to be processed. This problem is solved in the modern combinatorial material research, which is strongly related to computer data analysis and robotics. This field is still at the developing stage and may be enriched by new methods. Nevertheless, given the progress in measurement equipment and procedures, we believe the combinatorial approach will become a major and standard tool of materials screening and development. The first article of this journal, published in 2000, was titled 'Combinatorial solid state materials science and technology', and this focus issue aims to reintroduce this topic to the Science and Technology of Advanced Materials audience. It covers recent progress in combinatorial materials research describing new results in catalysis, phosphors, polymers and metal alloys for shape memory materials. Sophisticated high-throughput characterization schemes and innovative synthesis tools are also presented, such as spray deposition using nanoparticles or ion plating. On a technical note, data handling systems are introduced to familiarize researchers with the combinatorial methodology. We hope that through this focus issue a wide audience of materials scientists can learn about recent and future trends in combinatorial materials science and high-throughput experimentation.

A new perspective on microbial landscapes within food production

PubMed Central

Bokulich, Nicholas A; Lewis, Zachery T; Boundy-Mills, Kyria; Mills, David A

2016-01-01

High-throughput, ‘next-generation’ sequencing tools offer many exciting new possibilities for food research. From investigating microbial dynamics within food fermentations to the ecosystem of the food-processing built environment, amplicon sequencing, metagenomics, and transcriptomics present novel applications for exploring microbial communities in, on, and around our foods. This review discusses the many uses of these tools for food-related and food facility-related research and highlights where they may yield nuanced insight into the microbial world of food production systems. PMID:26773388

bioalcidae, samjs and vcffilterjs: object-oriented formatters and filters for bioinformatics files.

PubMed

Lindenbaum, Pierre; Redon, Richard

2018-04-01

Reformatting and filtering bioinformatics files are common tasks for bioinformaticians. Standard Linux tools and specific programs are usually used to perform such tasks but there is still a gap between using these tools and the programming interface of some existing libraries. In this study, we developed a set of tools namely bioalcidae, samjs and vcffilterjs that reformat or filter files using a JavaScript engine or a pure java expression and taking advantage of the java API for high-throughput sequencing data (htsjdk). https://github.com/lindenb/jvarkit. pierre.lindenbaum@univ-nantes.fr.

kpLogo: positional k-mer analysis reveals hidden specificity in biological sequences

PubMed Central

2017-01-01

Abstract Motifs of only 1–4 letters can play important roles when present at key locations within macromolecules. Because existing motif-discovery tools typically miss these position-specific short motifs, we developed kpLogo, a probability-based logo tool for integrated detection and visualization of position-specific ultra-short motifs from a set of aligned sequences. kpLogo also overcomes the limitations of conventional motif-visualization tools in handling positional interdependencies and utilizing ranked or weighted sequences increasingly available from high-throughput assays. kpLogo can be found at http://kplogo.wi.mit.edu/. PMID:28460012

Engineering customized TALE nucleases (TALENs) and TALE transcription factors by fast ligation-based automatable solid-phase high-throughput (FLASH) assembly.

PubMed

Reyon, Deepak; Maeder, Morgan L; Khayter, Cyd; Tsai, Shengdar Q; Foley, Jonathan E; Sander, Jeffry D; Joung, J Keith

2013-07-01

Customized DNA-binding domains made using transcription activator-like effector (TALE) repeats are rapidly growing in importance as widely applicable research tools. TALE nucleases (TALENs), composed of an engineered array of TALE repeats fused to the FokI nuclease domain, have been used successfully for directed genome editing in various organisms and cell types. TALE transcription factors (TALE-TFs), consisting of engineered TALE repeat arrays linked to a transcriptional regulatory domain, have been used to up- or downregulate expression of endogenous genes in human cells and plants. This unit describes a detailed protocol for the recently described fast ligation-based automatable solid-phase high-throughput (FLASH) assembly method. FLASH enables automated high-throughput construction of engineered TALE repeats using an automated liquid handling robot or manually using a multichannel pipet. Using the automated approach, a single researcher can construct up to 96 DNA fragments encoding TALE repeat arrays of various lengths in a single day, and then clone these to construct sequence-verified TALEN or TALE-TF expression plasmids in a week or less. Plasmids required for FLASH are available by request from the Joung lab (http://eGenome.org). This unit also describes improvements to the Zinc Finger and TALE Targeter (ZiFiT Targeter) web server (http://ZiFiT.partners.org) that facilitate the design and construction of FLASH TALE repeat arrays in high throughput. © 2013 by John Wiley & Sons, Inc.

Engineering Customized TALE Nucleases (TALENs) and TALE Transcription Factors by Fast Ligation-based Automatable Solid-phase High-throughput (FLASH) Assembly

PubMed Central

Reyon, Deepak; Maeder, Morgan L.; Khayter, Cyd; Tsai, Shengdar Q.; Foley, Jonathan E.; Sander, Jeffry D.; Joung, J. Keith

2013-01-01

Customized DNA-binding domains made using Transcription Activator-Like Effector (TALE) repeats are rapidly growing in importance as widely applicable research tools. TALE nucleases (TALENs), composed of an engineered array of TALE repeats fused to the FokI nuclease domain, have been used successfully for directed genome editing in multiple different organisms and cell types. TALE transcription factors (TALE-TFs), consisting of engineered TALE repeat arrays linked to a transcriptional regulatory domain, have been used to up- or down-regulate expression of endogenous genes in human cells and plants. Here we describe a detailed protocol for practicing the recently described Fast Ligation-based Automatable Solid-phase High-throughput (FLASH) assembly method. FLASH enables automated high-throughput construction of engineered TALE repeats using an automated liquid handling robot or manually using a multi-channel pipet. With the automated version of FLASH, a single researcher can construct up to 96 DNA fragments encoding various length TALE repeat arrays in one day and then clone these to construct sequence-verified TALEN or TALE-TF expression plasmids in one week or less. Plas-mids required to practice FLASH are available by request from the Joung Lab (http://www.jounglab.org/). We also describe here improvements to the Zinc Finger and TALE Targeter (ZiFiT Targeter) webserver (http://ZiFiTBeta.partners.org) that facilitate the design and construction of FLASH TALE repeat arrays in high-throughput. PMID:23821439

Infrastructure to Support Ultra High Throughput Biodosimetry Screening after a Radiological Event

PubMed Central

Garty, G.; Karam, P.A.; Brenner, D. J.

2011-01-01

Purpose After a large-scale radiological event, there will be a pressing need to assess, within a few days, the radiation doses received by tens or hundreds of thousands of individuals. This is for triage, to prevent treatment locations from being overwhelmed, in what is sure to be a resource limited scenario, as well as to facilitate dose-dependent treatment decisions. In addition there are psychosocial considerations, in that active reassurance of minimal exposure is a potentially effective antidote to mass panic, as well as long-term considerations, to facilitate later studies of cancer and other long-term disease risks. Materials and Methods As described elsewhere in this issue, we are developing a Rapid Automated Biodosimetry Tool (RABiT). The RABiT allows high throughput analysis of thousands of blood samples per day, providing a dose estimate that can be used to support clinical triage and treatment decisions. Results Development of the RABiT has motivated us to consider the logistics of incorporating such a system into the existing emergency response scenarios of a large metropolitan area. We present here a view of how one or more centralized biodosimetry readout devices might be incorporated into an infrastructure in which fingerstick blood samples are taken at many distributed locations within an affected city or region and transported to centralized locations. Conclusions High throughput biodosimetry systems offer the opportunity to perform biodosimetric assessments on a large number of persons. As such systems reach a high level of maturity, emergency response scenarios will need to be tweaked to make use of these powerful tools. This can be done relatively easily within the framework of current scenarios. PMID:21675819

Laser processes and system technology for the production of high-efficient crystalline solar cells

NASA Astrophysics Data System (ADS)

Mayerhofer, R.; Hendel, R.; Zhu, Wenjie; Geiger, S.

2012-10-01

The laser as an industrial tool is an essential part of today's solar cell production. Due to the on-going efforts in the solar industry, to increase the cell efficiency, more and more laser-based processes, which have been discussed and tested at lab-scale for many years, are now being implemented in mass production lines. In order to cope with throughput requirements, standard laser concepts have to be improved continuously with respect to available average power levels, repetition rates or beam profile. Some of the laser concepts, that showed high potential in the past couple of years, will be substituted by other, more economic laser types. Furthermore, requirements for processing with less-heat affected zones fuel the development of industry-ready ultra short pulsed lasers with pulse widths even below the picosecond range. In 2011, the German Ministry of Education and Research (BMBF) had launched the program "PV-Innovation Alliance", with the aim to support the rapid transfer of high-efficiency processes out of development departments and research institutes into solar cell production lines. Here, lasers play an important role as production tools, allowing the fast implementation of high-performance solar cell concepts. We will report on the results achieved within the joint project FUTUREFAB, where efficiency optimization, throughput enhancement and cost reduction are the main goals. Here, the presentation will focus on laser processes like selective emitter doping and ablation of dielectric layers. An indispensable part of the efforts towards cost reduction in solar cell production is the improvement of wafer handling and throughput capabilities of the laser processing system. Therefore, the presentation will also elaborate on new developments in the design of complete production machines.

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. High throughput handheld or drone-based measurements of chlorophyll fluorescence provide high quality, quantitative data that can be used to not only connect genotype to phenotype but also quantify how vastly different plant species and genotypes respond to stress and change ecosystem productivity.

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

PubMed Central

Caboche, Ségolène; Audebert, Christophe; Hot, David

2014-01-01

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

Automated sample area definition for high-throughput microscopy.

PubMed

Zeder, M; Ellrott, A; Amann, R

2011-04-01

High-throughput screening platforms based on epifluorescence microscopy are powerful tools in a variety of scientific fields. Although some applications are based on imaging geometrically defined samples such as microtiter plates, multiwell slides, or spotted gene arrays, others need to cope with inhomogeneously located samples on glass slides. The analysis of microbial communities in aquatic systems by sample filtration on membrane filters followed by multiple fluorescent staining, or the investigation of tissue sections are examples. Therefore, we developed a strategy for flexible and fast definition of sample locations by the acquisition of whole slide overview images and automated sample recognition by image analysis. Our approach was tested on different microscopes and the computer programs are freely available (http://www.technobiology.ch). Copyright © 2011 International Society for Advancement of Cytometry.

The Emory Chemical Biology Discovery Center: leveraging academic innovation to advance novel targets through HTS and beyond.

PubMed

Johns, Margaret A; Meyerkord-Belton, Cheryl L; Du, Yuhong; Fu, Haian

2014-03-01

The Emory Chemical Biology Discovery Center (ECBDC) aims to accelerate high throughput biology and translation of biomedical research discoveries into therapeutic targets and future medicines by providing high throughput research platforms to scientific collaborators worldwide. ECBDC research is focused at the interface of chemistry and biology, seeking to fundamentally advance understanding of disease-related biology with its HTS/HCS platforms and chemical tools, ultimately supporting drug discovery. Established HTS/HCS capabilities, university setting, and expertise in diverse assay formats, including protein-protein interaction interrogation, have enabled the ECBDC to contribute to national chemical biology efforts, empower translational research, and serve as a training ground for young scientists. With these resources, the ECBDC is poised to leverage academic innovation to advance biology and therapeutic discovery.

Rapid screening of illicit additives in weight loss dietary supplements with desorption corona beam ionisation (DCBI) mass spectrometry.

PubMed

Wang, H; Wu, Y; Zhao, Y; Sun, W; Ding, L; Guo, B; Chen, B

2012-08-01

Desorption corona beam ionisation (DCBI), the relatively novel ambient mass spectrometry (MS) technique, was utilised to screen for illicit additives in weight-loss food. The five usually abused chemicals - fenfluramine, N-di-desmethyl sibutramine, N-mono-desmethyl sibutramine, sibutramine and phenolphthalein - were detected with the proposed DCBI-MS method. Fast single-sample and high-throughput analysis was demonstrated. Semi-quantification was accomplished based on peak areas in the ion chromatograms. Four illicit additives were identified and semi-quantified in commercial samples. As there was no tedious sample pre-treatment compared with conventional HPLC methods, high-throughput analysis was achieved with DCBI. The results proved that DCBI-MS is a powerful tool for the rapid screening of illicit additives in weight-loss dietary supplements.

Large-scale protein-protein interactions detection by integrating big biosensing data with computational model.

PubMed

You, Zhu-Hong; Li, Shuai; Gao, Xin; Luo, Xin; Ji, Zhen

2014-01-01

Protein-protein interactions are the basis of biological functions, and studying these interactions on a molecular level is of crucial importance for understanding the functionality of a living cell. During the past decade, biosensors have emerged as an important tool for the high-throughput identification of proteins and their interactions. However, the high-throughput experimental methods for identifying PPIs are both time-consuming and expensive. On the other hand, high-throughput PPI data are often associated with high false-positive and high false-negative rates. Targeting at these problems, we propose a method for PPI detection by integrating biosensor-based PPI data with a novel computational model. This method was developed based on the algorithm of extreme learning machine combined with a novel representation of protein sequence descriptor. When performed on the large-scale human protein interaction dataset, the proposed method achieved 84.8% prediction accuracy with 84.08% sensitivity at the specificity of 85.53%. We conducted more extensive experiments to compare the proposed method with the state-of-the-art techniques, support vector machine. The achieved results demonstrate that our approach is very promising for detecting new PPIs, and it can be a helpful supplement for biosensor-based PPI data detection.

MS-REDUCE: an ultrafast technique for reduction of big mass spectrometry data for high-throughput processing.

PubMed

Awan, Muaaz Gul; Saeed, Fahad

2016-05-15

Modern proteomics studies utilize high-throughput mass spectrometers which can produce data at an astonishing rate. These big mass spectrometry (MS) datasets can easily reach peta-scale level creating storage and analytic problems for large-scale systems biology studies. Each spectrum consists of thousands of peaks which have to be processed to deduce the peptide. However, only a small percentage of peaks in a spectrum are useful for peptide deduction as most of the peaks are either noise or not useful for a given spectrum. This redundant processing of non-useful peaks is a bottleneck for streaming high-throughput processing of big MS data. One way to reduce the amount of computation required in a high-throughput environment is to eliminate non-useful peaks. Existing noise removing algorithms are limited in their data-reduction capability and are compute intensive making them unsuitable for big data and high-throughput environments. In this paper we introduce a novel low-complexity technique based on classification, quantization and sampling of MS peaks. We present a novel data-reductive strategy for analysis of Big MS data. Our algorithm, called MS-REDUCE, is capable of eliminating noisy peaks as well as peaks that do not contribute to peptide deduction before any peptide deduction is attempted. Our experiments have shown up to 100× speed up over existing state of the art noise elimination algorithms while maintaining comparable high quality matches. Using our approach we were able to process a million spectra in just under an hour on a moderate server. The developed tool and strategy has been made available to wider proteomics and parallel computing community and the code can be found at https://github.com/pcdslab/MSREDUCE CONTACT: : fahad.saeed@wmich.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

High Throughput ELISAs to Measure a Unique Glycan on Transferrin in Cerebrospinal Fluid: A Possible Extension toward Alzheimer's Disease Biomarker Development

PubMed Central

Shirotani, Keiro; Futakawa, Satoshi; Nara, Kiyomitsu; Hoshi, Kyoka; Saito, Toshie; Tohyama, Yuriko; Kitazume, Shinobu; Yuasa, Tatsuhiko; Miyajima, Masakazu; Arai, Hajime; Kuno, Atsushi; Narimatsu, Hisashi; Hashimoto, Yasuhiro

2011-01-01

We have established high-throughput lectin-antibody ELISAs to measure different glycans on transferrin (Tf) in cerebrospinal fluid (CSF) using lectins and an anti-transferrin antibody (TfAb). Lectin blot and precipitation analysis of CSF revealed that PVL (Psathyrella velutina lectin) bound an unique N-acetylglucosamine-terminated N-glycans on “CSF-type” Tf whereas SSA (Sambucus sieboldiana agglutinin) bound α2,6-N-acetylneuraminic acid-terminated N-glycans on “serum-type” Tf. PVL-TfAb ELISA of 0.5 μL CSF samples detected “CSF-type” Tf but not “serum-type” Tf whereas SSA-TfAb ELISA detected “serum-type” Tf but not “CSF-type” Tf, demonstrating the specificity of the lectin-TfAb ELISAs. In idiopathic normal pressure hydrocephalus (iNPH), a senile dementia associated with ventriculomegaly, amounts of the SSA-reactive Tf were significantly higher than in non-iNPH patients, indicating that Tf glycan analysis by the high-throughput lectin-TfAb ELISAs could become practical diagnostic tools for iNPH. The lectin-antibody ELISAs of CSF proteins might be useful for diagnosis of the other neurological diseases. PMID:21876827

High Throughput ELISAs to Measure a Unique Glycan on Transferrin in Cerebrospinal Fluid: A Possible Extension toward Alzheimer's Disease Biomarker Development.

PubMed

Shirotani, Keiro; Futakawa, Satoshi; Nara, Kiyomitsu; Hoshi, Kyoka; Saito, Toshie; Tohyama, Yuriko; Kitazume, Shinobu; Yuasa, Tatsuhiko; Miyajima, Masakazu; Arai, Hajime; Kuno, Atsushi; Narimatsu, Hisashi; Hashimoto, Yasuhiro

2011-01-01

We have established high-throughput lectin-antibody ELISAs to measure different glycans on transferrin (Tf) in cerebrospinal fluid (CSF) using lectins and an anti-transferrin antibody (TfAb). Lectin blot and precipitation analysis of CSF revealed that PVL (Psathyrella velutina lectin) bound an unique N-acetylglucosamine-terminated N-glycans on "CSF-type" Tf whereas SSA (Sambucus sieboldiana agglutinin) bound α2,6-N-acetylneuraminic acid-terminated N-glycans on "serum-type" Tf. PVL-TfAb ELISA of 0.5 μL CSF samples detected "CSF-type" Tf but not "serum-type" Tf whereas SSA-TfAb ELISA detected "serum-type" Tf but not "CSF-type" Tf, demonstrating the specificity of the lectin-TfAb ELISAs. In idiopathic normal pressure hydrocephalus (iNPH), a senile dementia associated with ventriculomegaly, amounts of the SSA-reactive Tf were significantly higher than in non-iNPH patients, indicating that Tf glycan analysis by the high-throughput lectin-TfAb ELISAs could become practical diagnostic tools for iNPH. The lectin-antibody ELISAs of CSF proteins might be useful for diagnosis of the other neurological diseases.

Computational Approaches to Phenotyping

PubMed Central

Lussier, Yves A.; Liu, Yang

2007-01-01

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

Assessment of DNA damage in car spray painters exposed to organic solvents by the high-throughput comet assay.

PubMed

Londoño-Velasco, Elizabeth; Martínez-Perafán, Fabián; Carvajal-Varona, Silvio; García-Vallejo, Felipe; Hoyos-Giraldo, Luz Stella

2016-05-01

Occupational exposure as a painter is associated with DNA damage and development of cancer. Comet assay has been widely adopted as a sensitive and quantitative tool for DNA damage assessment at the individual cell level in populations exposed to genotoxics. The aim of this study was to assess the application of the high-throughput comet assay, to determine the DNA damage in car spray painters. The study population included 52 car spray painters and 52 unexposed subjects. A significant increase in the %TDNA median (p <  0.001) was observed in the exposed group in comparison to the unexposed group. Neither age (%TDNA: p =  0.913) nor time of exposure (%TDNA: p = 0.398) were significantly correlated with DNA damage. The car spray painters who consumed alcohol did not show a significant increase in DNA damage compared to nonalcohol consumers (p  > 0.05). The results showed an increase in DNA breaks in car spray painters exposed to organic solvents and paints; furthermore, they demonstrated the application of high-throughput comet assay in an occupational exposure study to genotoxic agents.

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

PubMed

Gopakumar, G; Hari Babu, K; Mishra, Deepak; Gorthi, Sai Siva; Sai Subrahmanyam, Gorthi R K

2017-01-01

Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep-learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell lines (K562, MOLT, and HL60). The cell images used in the classification are captured using a low-cost, high-throughput cell imaging technique: microfluidics-based imaging flow cytometry. We demonstrate that without any conventional fine segmentation followed by explicit feature extraction, the proposed deep-learning algorithms effectively classify the coarsely localized cell lines. We show that the designed deep belief network as well as the deeply pretrained convolutional neural network outperform the conventionally used decision systems and are important in the medical domain, where the availability of labeled data is limited for training. We hope that our work enables the development of a clinically significant high-throughput microfluidic microscopy-based tool for disease screening/triaging, especially in resource-limited settings.

Automatic poisson peak harvesting for high throughput protein identification.

PubMed

Breen, E J; Hopwood, F G; Williams, K L; Wilkins, M R

2000-06-01

High throughput identification of proteins by peptide mass fingerprinting requires an efficient means of picking peaks from mass spectra. Here, we report the development of a peak harvester to automatically pick monoisotopic peaks from spectra generated on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometers. The peak harvester uses advanced mathematical morphology and watershed algorithms to first process spectra to stick representations. Subsequently, Poisson modelling is applied to determine which peak in an isotopically resolved group represents the monoisotopic mass of a peptide. We illustrate the features of the peak harvester with mass spectra of standard peptides, digests of gel-separated bovine serum albumin, and with Escherictia coli proteins prepared by two-dimensional polyacrylamide gel electrophoresis. In all cases, the peak harvester proved effective in its ability to pick similar monoisotopic peaks as an experienced human operator, and also proved effective in the identification of monoisotopic masses in cases where isotopic distributions of peptides were overlapping. The peak harvester can be operated in an interactive mode, or can be completely automated and linked through to peptide mass fingerprinting protein identification tools to achieve high throughput automated protein identification.

Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data.

PubMed

Ryall, Karen A; Shin, Jimin; Yoo, Minjae; Hinz, Trista K; Kim, Jihye; Kang, Jaewoo; Heasley, Lynn E; Tan, Aik Choon

2015-12-01

Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. aikchoon.tan@ucdenver.edu. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays

PubMed Central

Aryee, Martin J.; Jaffe, Andrew E.; Corrada-Bravo, Hector; Ladd-Acosta, Christine; Feinberg, Andrew P.; Hansen, Kasper D.; Irizarry, Rafael A.

2014-01-01

Motivation: The recently released Infinium HumanMethylation450 array (the ‘450k’ array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Results: Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. Availability and implementation: http://bioconductor.org/packages/release/bioc/html/minfi.html. Contact: khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24478339

A High Throughput Protein Microarray Approach to Classify HIV Monoclonal Antibodies and Variant Antigens

PubMed Central

Dotsey, Emmanuel Y.; Gorlani, Andrea; Ingale, Sampat; Achenbach, Chad J.; Forthal, Donald N.; Felgner, Philip L.; Gach, Johannes S.

2015-01-01

In recent years, high throughput discovery of human recombinant monoclonal antibodies (mAbs) has been applied to greatly advance our understanding of the specificity, and functional activity of antibodies against HIV. Thousands of antibodies have been generated and screened in functional neutralization assays, and antibodies associated with cross-strain neutralization and passive protection in primates, have been identified. To facilitate this type of discovery, a high throughput-screening tool is needed to accurately classify mAbs, and their antigen targets. In this study, we analyzed and evaluated a prototype microarray chip comprised of the HIV-1 recombinant proteins gp140, gp120, gp41, and several membrane proximal external region peptides. The protein microarray analysis of 11 HIV-1 envelope-specific mAbs revealed diverse binding affinities and specificities across clades. Half maximal effective concentrations, generated by our chip analysis, correlated significantly (P<0.0001) with concentrations from ELISA binding measurements. Polyclonal immune responses in plasma samples from HIV-1 infected subjects exhibited different binding patterns, and reactivity against printed proteins. Examining the totality of the specificity of the humoral response in this way reveals the exquisite diversity, and specificity of the humoral response to HIV. PMID:25938510

Application Of Empirical Phase Diagrams For Multidimensional Data Visualization Of High Throughput Microbatch Crystallization Experiments.

PubMed

Klijn, Marieke E; Hubbuch, Jürgen

2018-04-27

Protein phase diagrams are a tool to investigate cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphological features, such as crystal size, as well as kinetic features, such as crystal growth time. Common used data visualization techniques include individual line graphs or symbols-based phase diagrams. These techniques have limitations in terms of handling large datasets, comprehensiveness or completeness. To eliminate these limitations, morphological and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram (EPD) method. Morphological features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the EPD method can support high throughput crystallization experiments in its data amount as well as its data complexity. Copyright © 2018. Published by Elsevier Inc.

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

Deep sequencing in library selection projects: what insight does it bring?

PubMed

Glanville, J; D'Angelo, S; Khan, T A; Reddy, S T; Naranjo, L; Ferrara, F; Bradbury, A R M

2015-08-01

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Deep sequencing in library selection projects: what insight does it bring?

PubMed Central

Glanville, J; D’Angelo, S; Khan, T.A.; Reddy, S. T.; Naranjo, L.; Ferrara, F.; Bradbury, A.R.M.

2015-01-01

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology. PMID:26451649

RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA.

PubMed

Wright, Imogen A; Travers, Simon A

2014-07-01

The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

Cognitive ergonomics of operational tools

NASA Astrophysics Data System (ADS)

Lüdeke, A.

2012-10-01

Control systems have become increasingly more powerful over the past decades. The availability of high data throughput and sophisticated graphical interactions has opened a variety of new possibilities. But has this helped to provide intuitive, easy to use applications to simplify the operation of modern large scale accelerator facilities? We will discuss what makes an application useful to operation and what is necessary to make a tool easy to use. We will show that even the implementation of a small number of simple application design rules can help to create ergonomic operational tools. The author is convinced that such tools do indeed help to achieve higher beam availability and better beam performance at accelerator facilities.

Test and Evaluation of WiMAX Performance Using Open-Source Modeling and Simulation Software Tools

DTIC Science & Technology

2010-12-01

specific needs. For instance, one may seek to maximize the system throughput while maximizing the number of trans- mitted data packets with hard...seeking to maximize the throughput of the system (Yu 2008; Pishdad and Rabiee 2008; Piro et al. 2010; Wongthavarawat and Ganz 2003; Mohammadi, Akl, and...testing environment provides tools to allow for setting up and running test environments over multiple systems (buildbot) and provides classes to

Update on EPA’s ToxCast Program: Providing High Throughput Decision Support Tools for Chemical Risk Management

EPA Science Inventory

The field of toxicology is on the cusp of a major transformation in how the safety and hazard of chemicals are evaluated for potential effects on human health and the environment. Brought on by the recognition of the limitations of the current paradigm in terms of cost, time, and...

Low-Cost, High-Throughput 3D Pulmonary Imager Using Hyperpolarized Contrast Agents and Low-Field MRI

DTIC Science & Technology

2016-10-01

COMMUNITIES OF INTEREST? ................................................. 8 4. IMPACT...publicize the work performed and also for their exposure to biomedical science. How were the results disseminated to communities of interest? Nothing...biomedical community , expanding the utility of HP methods as a new tool for probing fundamental biomedical questions. Acknowledgments The authors thank

Complementing in vitro screening assays with in silico molecular chemistry tools to examine potential in vivo metabolite-mediated effects

EPA Science Inventory

High-throughput in vitro assays offer a rapid, cost-efficient means to screen thousands of chemicals across hundreds of pathway-based toxicity endpoints. However, one main concern involved with the use of in vitro assays is the erroneous omission of chemicals that are inactive un...

Adverse Outcome Pathways and Systems Biology as Conceptual Approaches to Support Development of 21st Century Test Methods and Extrapolation Tools

EPA Science Inventory

The proposed paradigm for “Toxicity Testing in the 21st Century” supports the development of mechanistically-based, high-throughput in vitro assays as a potential cost effective and scientifically-sound alternative to some whole animal hazard testing. To accomplish this long-term...

[Metabonomics-a useful tool for individualized cancer therapy].

PubMed

Chai, Yanlan; Wang, Juan; Liu, Zi

2013-11-01

Metabonomics has developed rapidly in post-genome era, and becomes a hot topic of omics. The core idea of metabonomics is to determine the metabolites of relatively low-weight molecular in organisms or cells, by a series of analytical methods such as nuclear magnetic resonance, color spectrum and mass spectrogram, then to transform the data of metabolic pattern into useful information, by chemometric tools and pattern recognition software, and to reveal the essence of life activities of the body. With advantages of high-throughput, high-sensitivity and high-accuracy, metabolomics shows great potential and value in cancer individualized treatment. This paper introduces the concept,contents and methods of metabonomics and reviews its application in cancer individualized therapy.

A paper-based microbial fuel cell array for rapid and high-throughput screening of electricity-producing bacteria.

PubMed

Choi, Gihoon; Hassett, Daniel J; Choi, Seokheun

2015-06-21

There is a large global effort to improve microbial fuel cell (MFC) techniques and advance their translational potential toward practical, real-world applications. Significant boosts in MFC performance can be achieved with the development of new techniques in synthetic biology that can regulate microbial metabolic pathways or control their gene expression. For these new directions, a high-throughput and rapid screening tool for microbial biopower production is needed. In this work, a 48-well, paper-based sensing platform was developed for the high-throughput and rapid characterization of the electricity-producing capability of microbes. 48 spatially distinct wells of a sensor array were prepared by patterning 48 hydrophilic reservoirs on paper with hydrophobic wax boundaries. This paper-based platform exploited the ability of paper to quickly wick fluid and promoted bacterial attachment to the anode pads, resulting in instant current generation upon loading of the bacterial inoculum. We validated the utility of our MFC array by studying how strategic genetic modifications impacted the electrochemical activity of various Pseudomonas aeruginosa mutant strains. Within just 20 minutes, we successfully determined the electricity generation capacity of eight isogenic mutants of P. aeruginosa. These efforts demonstrate that our MFC array displays highly comparable performance characteristics and identifies genes in P. aeruginosa that can trigger a higher power density.

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.

Mass spectrometry-driven drug discovery for development of herbal medicine.

PubMed

Zhang, Aihua; Sun, Hui; Wang, Xijun

2018-05-01

Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes. © 2016 Wiley Periodicals, Inc.

The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences.

PubMed

Merchant, Nirav; Lyons, Eric; Goff, Stephen; Vaughn, Matthew; Ware, Doreen; Micklos, David; Antin, Parker

2016-01-01

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant's platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses.

Network pharmacology: reigning in drug attrition?

PubMed

Alian, Osama M; Shah, Minjel; Mohammad, Momin; Mohammad, Ramzi M

2013-06-01

In the process of drug development, there has been an exceptionally high attrition rate in oncological compounds entering late phases of testing. This has seen a concurrent reduction in approved NCEs (new chemical entities) reaching patients. Network pharmacology has become a valuable tool in understanding the fine details of drug-target interactions as well as painting a more practical picture of phenotype relationships to patients and drugs. By utilizing all the tools achieved through molecular medicine and combining it with high throughput data analysis, interactions and mechanisms can be elucidated and treatments reasonably tailored to patients expressing specific phenotypes (or genotypes) of disease, essentially reigning in the phenomenon of drug attrition.

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 for drug screens in industry and academia.

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.

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

PubMed

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

2015-01-01

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

Tumor purity and differential methylation in cancer epigenomics.

PubMed

Wang, Fayou; Zhang, Naiqian; Wang, Jun; Wu, Hao; Zheng, Xiaoqi

2016-11-01

DNA methylation is an epigenetic modification of DNA molecule that plays a vital role in gene expression regulation. It is not only involved in many basic biological processes, but also considered an important factor for tumorigenesis and other human diseases. Study of DNA methylation has been an active field in cancer epigenomics research. With the advances of high-throughput technologies and the accumulation of enormous amount of data, method development for analyzing these data has gained tremendous interests in the fields of computational biology and bioinformatics. In this review, we systematically summarize the recent developments of computational methods and software tools in high-throughput methylation data analysis with focus on two aspects: differential methylation analysis and tumor purity estimation in cancer studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

PubMed

Loeffelholz, Michael; Fofanov, Yuriy

2015-01-01

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

High-throughput sequencing in veterinary infection biology and diagnostics.

PubMed

Belák, S; Karlsson, O E; Leijon, M; Granberg, F

2013-12-01

Sequencing methods have improved rapidly since the first versions of the Sanger techniques, facilitating the development of very powerful tools for detecting and identifying various pathogens, such as viruses, bacteria and other microbes. The ongoing development of high-throughput sequencing (HTS; also known as next-generation sequencing) technologies has resulted in a dramatic reduction in DNA sequencing costs, making the technology more accessible to the average laboratory. In this White Paper of the World Organisation for Animal Health (OIE) Collaborating Centre for the Biotechnology-based Diagnosis of Infectious Diseases in Veterinary Medicine (Uppsala, Sweden), several approaches and examples of HTS are summarised, and their diagnostic applicability is briefly discussed. Selected future aspects of HTS are outlined, including the need for bioinformatic resources, with a focus on improving the diagnosis and control of infectious diseases in veterinary medicine.

Biofuel metabolic engineering with biosensors.

PubMed

Morgan, Stacy-Anne; Nadler, Dana C; Yokoo, Rayka; Savage, David F

2016-12-01

Metabolic engineering offers the potential to renewably produce important classes of chemicals, particularly biofuels, at an industrial scale. DNA synthesis and editing techniques can generate large pathway libraries, yet identifying the best variants is slow and cumbersome. Traditionally, analytical methods like chromatography and mass spectrometry have been used to evaluate pathway variants, but such techniques cannot be performed with high throughput. Biosensors - genetically encoded components that actuate a cellular output in response to a change in metabolite concentration - are therefore a promising tool for rapid and high-throughput evaluation of candidate pathway variants. Applying biosensors can also dynamically tune pathways in response to metabolic changes, improving balance and productivity. Here, we describe the major classes of biosensors and briefly highlight recent progress in applying them to biofuel-related metabolic pathway engineering. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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.

A suite of MATLAB-based computational tools for automated analysis of COPAS Biosort data

PubMed Central

Morton, Elizabeth; Lamitina, Todd

2010-01-01

Complex Object Parametric Analyzer and Sorter (COPAS) devices are large-object, fluorescence-capable flow cytometers used for high-throughput analysis of live model organisms, including Drosophila melanogaster, Caenorhabditis elegans, and zebrafish. The COPAS is especially useful in C. elegans high-throughput genome-wide RNA interference (RNAi) screens that utilize fluorescent reporters. However, analysis of data from such screens is relatively labor-intensive and time-consuming. Currently, there are no computational tools available to facilitate high-throughput analysis of COPAS data. We used MATLAB to develop algorithms (COPAquant, COPAmulti, and COPAcompare) to analyze different types of COPAS data. COPAquant reads single-sample files, filters and extracts values and value ratios for each file, and then returns a summary of the data. COPAmulti reads 96-well autosampling files generated with the ReFLX adapter, performs sample filtering, graphs features across both wells and plates, performs some common statistical measures for hit identification, and outputs results in graphical formats. COPAcompare performs a correlation analysis between replicate 96-well plates. For many parameters, thresholds may be defined through a simple graphical user interface (GUI), allowing our algorithms to meet a variety of screening applications. In a screen for regulators of stress-inducible GFP expression, COPAquant dramatically accelerated data analysis and allowed us to rapidly move from raw data to hit identification. Because the COPAS file structure is standardized and our MATLAB code is freely available, our algorithms should be extremely useful for analysis of COPAS data from multiple platforms and organisms. The MATLAB code is freely available at our web site (www.med.upenn.edu/lamitinalab/downloads.shtml). PMID:20569218

Bringing the light to high throughput screening: use of optogenetic tools for the development of recombinant cellular assays

NASA Astrophysics Data System (ADS)

Agus, Viviana; Di Silvio, Alberto; Rolland, Jean Francois; Mondini, Anna; Tremolada, Sara; Montag, Katharina; Scarabottolo, Lia; Redaelli, Loredana; Lohmer, Stefan

2015-03-01

The use of light-activated proteins represents a powerful tool to control biological processes with high spatial and temporal precision. These so called "optogenetic" technologies have been successfully validated in many recombinant systems, and have been widely applied to the study of cellular mechanisms in intact tissues or behaving animals; to do that, complex, high-intensity, often home-made instrumentations were developed to achieve the optimal power and precision of light stimulation. In our study we sought to determine if this optical modulation can be obtained also in a miniaturized format, such as a 384-well plate, using the instrumentations normally dedicated to fluorescence analysis in High Throughput Screening (HTS) activities, such as for example the FLIPR (Fluorometric Imaging Plate Reader) instrument. We successfully generated optogenetic assays for the study of different ion channel targets: the CaV1.3 calcium channel was modulated by the light-activated Channelrhodopsin-2, the HCN2 cyclic nucleotide gated (CNG) channel was modulated by the light activated bPAC adenylyl cyclase, and finally the genetically encoded voltage indicator ArcLight was efficiently used to measure potassium, sodium or chloride channel activity. Our results showed that stable, robust and miniaturized cellular assays can be developed using different optogenetic tools, and efficiently modulated by the FLIPR instrument LEDs in a 384-well format. The spatial and temporal resolution delivered by this technology might enormously advantage the early stages of drug discovery, leading to the identification of more physiological and effective drug molecules.

A new perspective on microbial landscapes within food production.

PubMed

Bokulich, Nicholas A; Lewis, Zachery T; Boundy-Mills, Kyria; Mills, David A

2016-02-01

High-throughput, 'next-generation' sequencing tools offer many exciting new possibilities for food research. From investigating microbial dynamics within food fermentations to the ecosystem of the food-processing built environment, amplicon sequencing, metagenomics, and transcriptomics present novel applications for exploring microbial communities in, on, and around our foods. This review discusses the many uses of these tools for food-related and food facility-related research and highlights where they may yield nuanced insight into the microbial world of food production systems. Copyright © 2016. Published by Elsevier Ltd.

HTAPP: High-Throughput Autonomous Proteomic Pipeline

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2011-01-01

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic datasets is critically important. The high-throughput autonomous proteomic pipeline (HTAPP) described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is comprised of software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of HTAPP focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples. PMID:20336676

Emerging Genomic Tools for Legume Breeding: Current Status and Future Prospects

PubMed Central

Pandey, Manish K.; Roorkiwal, Manish; Singh, Vikas K.; Ramalingam, Abirami; Kudapa, Himabindu; Thudi, Mahendar; Chitikineni, Anu; Rathore, Abhishek; Varshney, Rajeev K.

2016-01-01

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries. PMID:27199998

ARTS: a web-based tool for the set-up of high-throughput genome-wide mapping panels for the SNP genotyping of mouse mutants.

PubMed

Klaften, Matthias; Hrabé de Angelis, Martin

2005-07-01

Genome-wide mapping in the identification of novel candidate genes has always been the standard method in genetics and genomics to correlate a clinically interesting phenotypic trait with a genotype. However, the performance of a mapping experiment using classical microsatellite approaches can be very time consuming. The high-throughput analysis of single-nucleotide polymorphisms (SNPs) has the potential of being the successor of microsatellite analysis routinely used for these mapping approaches, where one of the major obstacles is the design of the appropriate SNP marker set itself. Here we report on ARTS, an advanced retrieval tool for SNPs, which allows researchers to comb freely the public mouse dbSNP database for multiple reference and test strains. Several filters can be applied in order to improve the sensitivity and the specificity of the search results. By employing the panel generator function of this program, it is possible to abbreviate the extraction of reliable sequence data for a large marker panel including several different mouse strains from days to minutes. The concept of ARTS is easily adaptable to other species for which SNP databases are available, making it a versatile tool for the use of SNPs as markers for genotyping. The web interface is accessible at http://andromeda.gsf.de/arts.

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

Sauter, Nicholas K., E-mail: nksauter@lbl.gov; Hattne, Johan; Grosse-Kunstleve, Ralf W.

The Computational Crystallography Toolbox (cctbx) is a flexible software platform that has been used to develop high-throughput crystal-screening tools for both synchrotron sources and X-ray free-electron lasers. Plans for data-processing and visualization applications are discussed, and the benefits and limitations of using graphics-processing units are evaluated. Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h{sup −1}) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in realmore » time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units.« less

New Web-Based Tools Make Systems Pharmacology More Accessible Using Data from the NCI-60 | Center for Cancer Research

Cancer.gov

High-throughput biological techniques, like microarrays and drug screens, generate an enormous amount of data that may be critically important for cancer researchers and clinicians. Being able to manipulate the data to extract those pieces of interest, however, can require computational or bioinformatics skills beyond those of the average scientist.

Addressing the Digital Divide in Contemporary Biology: Lessons from Teaching UNIX.

PubMed

Mangul, Serghei; Martin, Lana S; Hoffmann, Alexander; Pellegrini, Matteo; Eskin, Eleazar

2017-10-01

Life and medical science researchers increasingly rely on applications that lack a graphical interface. Scientists who are not trained in computer science face an enormous challenge analyzing high-throughput data. We present a training model for use of command-line tools when the learner has little to no prior knowledge of UNIX. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

Kavlock, Robert; Dix, David

2010-02-01

Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environmental Protection Agency EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in air, water, and hazardous-waste sites. The Office of Research and Development (ORD) Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the U.S. EPA Science to Achieve Results (STAR) program. Together these elements form the key components in the implementation of both the initial strategy, A Framework for a Computational Toxicology Research Program (U.S. EPA, 2003), and the newly released The U.S. Environmental Protection Agency's Strategic Plan for Evaluating the Toxicity of Chemicals (U.S. EPA, 2009a). Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast) and exposure (ExpoCast), and creating virtual liver (v-Liver) and virtual embryo (v-Embryo) systems models. U.S. EPA-funded STAR centers are also providing bioinformatics, computational toxicology data and models, and developmental toxicity data and models. The models and underlying data are being made publicly available through the Aggregated Computational Toxicology Resource (ACToR), the Distributed Structure-Searchable Toxicity (DSSTox) Database Network, and other U.S. EPA websites. While initially focused on improving the hazard identification process, the CTRP is placing increasing emphasis on using high-throughput bioactivity profiling data in systems modeling to support quantitative risk assessments, and in developing complementary higher throughput exposure models. This integrated approach will enable analysis of life-stage susceptibility, and understanding of the exposures, pathways, and key events by which chemicals exert their toxicity in developing systems (e.g., endocrine-related pathways). The CTRP will be a critical component in next-generation risk assessments utilizing quantitative high-throughput data and providing a much higher capacity for assessing chemical toxicity than is currently available.

Physiologically Based Pharmacokinetic Models: Integration of In Silico Approaches with Micro Cell Culture Analogues

PubMed Central

Chen, A.; Yarmush, M.L.; Maguire, T.

2014-01-01

There is a large emphasis within the pharmaceutical industry to provide tools that will allow early research and development groups to better predict dose ranges for and metabolic responses of candidate molecules in a high throughput manner, prior to entering clinical trials. These tools incorporate approaches ranging from PBPK, QSAR, and molecular dynamics simulations in the in silico realm, to micro cell culture analogue (CCAs)s in the in vitro realm. This paper will serve to review these areas of high throughput predictive research, and highlight hurdles and potential solutions. In particular we will focus on CCAs, as their incorporation with PBPK modeling has the potential to replace animal testing, with a more predictive assay that can combine multiple organ analogs on one microfluidic platform in physiologically correct volume ratios. While several advantages arise from the current embodiments of CCAS in a microfluidic format that can be exploited for realistic simulations of drug absorption, metabolism and action, we explore some of the concerns with these systems, and provide a potential path forward to realizing animal-free solutions. Furthermore we envision that, together with theoretical modeling, CCAs may produce reliable predictions of the efficacy of newly developed drugs. PMID:22571482

Interoperability of GADU in using heterogeneous Grid resources for bioinformatics applications.

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

Sulakhe, D.; Rodriguez, A.; Wilde, M.

2008-03-01

Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. The genome analysis and database update system (GADU) is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run jobs on different Grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual datamore » system that makes high-throughput computational tools interoperable on heterogeneous Grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid. The paper will not go into the details of problems involved or the lessons learned in using individual Grid resources as it has already been published in our paper on genome analysis research environment (GNARE) and will focus primarily on the architecture that makes GADU resource independent and interoperable across heterogeneous Grid resources.« less

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.

Passive and Active Monitoring on a High Performance Research Network.

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

Matthews, Warren

2001-05-01

The bold network challenges described in ''Internet End-to-end Performance Monitoring for the High Energy and Nuclear Physics Community'' presented at PAM 2000 have been tackled by the intrepid administrators and engineers providing the network services. After less than a year, the BaBar collaboration has collected almost 100 million particle collision events in a database approaching 165TB (Tera=10{sup 12}). Around 20TB has been exported via the Internet to the BaBar regional center at IN2P3 in Lyon, France, for processing and around 40 TB of simulated events have been imported to SLAC from Lawrence Livermore National Laboratory (LLNL). An unforseen challenge hasmore » arisen due to recent events and highlighted security concerns at DoE funded labs. New rules and regulations suggest it is only a matter of time before many active performance measurements may not be possible between many sites. Yet, at the same time, the importance of understanding every aspect of the network and eradicating packet loss for high throughput data transfers has become apparent. Work at SLAC to employ passive monitoring using netflow and OC3MON is underway and techniques to supplement and possibly replace the active measurements are being considered. This paper will detail the special needs and traffic characterization of a remarkable research project, and how the networking hurdles have been resolved (or not!) to achieve the required high data throughput. Results from active and passive measurements will be compared, and methods for achieving high throughput and the effect on the network will be assessed along with tools that directly measure throughput and applications used to actually transfer data.« less

Automated image-based phenotypic analysis in zebrafish embryos

PubMed Central

Vogt, Andreas; Cholewinski, Andrzej; Shen, Xiaoqiang; Nelson, Scott; Lazo, John S.; Tsang, Michael; Hukriede, Neil A.

2009-01-01

Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to utilizing the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes. PMID:19235725

Automation of Technology for Cancer Research.

PubMed

van der Ent, Wietske; Veneman, Wouter J; Groenewoud, Arwin; Chen, Lanpeng; Tulotta, Claudia; Hogendoorn, Pancras C W; Spaink, Herman P; Snaar-Jagalska, B Ewa

2016-01-01

Zebrafish embryos can be obtained for research purposes in large numbers at low cost and embryos develop externally in limited space, making them highly suitable for high-throughput cancer studies and drug screens. Non-invasive live imaging of various processes within the larvae is possible due to their transparency during development, and a multitude of available fluorescent transgenic reporter lines.To perform high-throughput studies, handling large amounts of embryos and larvae is required. With such high number of individuals, even minute tasks may become time-consuming and arduous. In this chapter, an overview is given of the developments in the automation of various steps of large scale zebrafish cancer research for discovering important cancer pathways and drugs for the treatment of human disease. The focus lies on various tools developed for cancer cell implantation, embryo handling and sorting, microfluidic systems for imaging and drug treatment, and image acquisition and analysis. Examples will be given of employment of these technologies within the fields of toxicology research and cancer research.

A high-throughput investigation of Fe-Cr-Al as a novel high-temperature coating for nuclear cladding materials.

PubMed

Bunn, Jonathan Kenneth; Fang, Randy L; Albing, Mark R; Mehta, Apurva; Kramer, Matthew J; Besser, Matthew F; Hattrick-Simpers, Jason R

2015-07-10

High-temperature alloy coatings that can resist oxidation are urgently needed as nuclear cladding materials to mitigate the danger of hydrogen explosions during meltdown. Here we apply a combination of computationally guided materials synthesis, high-throughput structural characterization and data analysis tools to investigate the feasibility of coatings from the Fe–Cr–Al alloy system. Composition-spread samples were synthesized to cover the region of the phase diagram previous bulk studies have identified as forming protective oxides. The metallurgical and oxide phase evolution were studied via in situ synchrotron glancing incidence x-ray diffraction at temperatures up to 690 K. A composition region with an Al concentration greater than 3.08 at%, and between 20.0 at% and 32.9 at% Cr showed the least overall oxide growth. Subsequently, a series of samples were deposited on stubs and their oxidation behavior at 1373 K was observed. The continued presence of a passivating oxide was confirmed in this region over a period of 6 h.

G protein-coupled receptor internalization assays in the high-content screening format.

PubMed

Haasen, Dorothea; Schnapp, Andreas; Valler, Martin J; Heilker, Ralf

2006-01-01

High-content screening (HCS), a combination of fluorescence microscopic imaging and automated image analysis, has become a frequently applied tool to study test compound effects in cellular disease-modeling systems. This chapter describes the measurement of G protein-coupled receptor (GPCR) internalization in the HCS format using a high-throughput, confocal cellular imaging device. GPCRs are the most successful group of therapeutic targets on the pharmaceutical market. Accordingly, the search for compounds that interfere with GPCR function in a specific and selective way is a major focus of the pharmaceutical industry today. This chapter describes methods for the ligand-induced internalization of GPCRs labeled previously with either a fluorophore-conjugated ligand or an antibody directed against an N-terminal tag of the GPCR. Both labeling techniques produce robust assay formats. Complementary to other functional GPCR drug discovery assays, internalization assays enable a pharmacological analysis of test compounds. We conclude that GPCR internalization assays represent a valuable medium/high-throughput screening format to determine the cellular activity of GPCR ligands.

Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems.

PubMed

Choi, Hyungsuk; Choi, Woohyuk; Quan, Tran Minh; Hildebrand, David G C; Pfister, Hanspeter; Jeong, Won-Ki

2014-12-01

As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.

Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci.

PubMed

Canver, Matthew C; Lessard, Samuel; Pinello, Luca; Wu, Yuxuan; Ilboudo, Yann; Stern, Emily N; Needleman, Austen J; Galactéros, Frédéric; Brugnara, Carlo; Kutlar, Abdullah; McKenzie, Colin; Reid, Marvin; Chen, Diane D; Das, Partha Pratim; A Cole, Mitchel; Zeng, Jing; Kurita, Ryo; Nakamura, Yukio; Yuan, Guo-Cheng; Lettre, Guillaume; Bauer, Daniel E; Orkin, Stuart H

2017-04-01

Cas9-mediated, high-throughput, saturating in situ mutagenesis permits fine-mapping of function across genomic segments. Disease- and trait-associated variants identified in genome-wide association studies largely cluster at regulatory loci. Here we demonstrate the use of multiple designer nucleases and variant-aware library design to interrogate trait-associated regulatory DNA at high resolution. We developed a computational tool for the creation of saturating-mutagenesis libraries with single or multiple nucleases with incorporation of variants. We applied this methodology to the HBS1L-MYB intergenic region, which is associated with red-blood-cell traits, including fetal hemoglobin levels. This approach identified putative regulatory elements that control MYB expression. Analysis of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance of off-target analysis in the design of saturating-mutagenesis experiments. Together, these data establish a widely applicable high-throughput and high-resolution methodology to identify minimal functional sequences within large disease- and trait-associated regions.

Using a Fluorescent PCR-capillary Gel Electrophoresis Technique to Genotype CRISPR/Cas9-mediated Knockout Mutants in a High-throughput Format.

PubMed

Ramlee, Muhammad Khairul; Wang, Jing; Cheung, Alice M S; Li, Shang

2017-04-08

The development of programmable genome-editing tools has facilitated the use of reverse genetics to understand the roles specific genomic sequences play in the functioning of cells and whole organisms. This cause has been tremendously aided by the recent introduction of the CRISPR/Cas9 system-a versatile tool that allows researchers to manipulate the genome and transcriptome in order to, among other things, knock out, knock down, or knock in genes in a targeted manner. For the purpose of knocking out a gene, CRISPR/Cas9-mediated double-strand breaks recruit the non-homologous end-joining DNA repair pathway to introduce the frameshift-causing insertion or deletion of nucleotides at the break site. However, an individual guide RNA may cause undesirable off-target effects, and to rule these out, the use of multiple guide RNAs is necessary. This multiplicity of targets also means that a high-volume screening of clones is required, which in turn begs the use of an efficient high-throughput technique to genotype the knockout clones. Current genotyping techniques either suffer from inherent limitations or incur high cost, hence rendering them unsuitable for high-throughput purposes. Here, we detail the protocol for using fluorescent PCR, which uses genomic DNA from crude cell lysate as a template, and then resolving the PCR fragments via capillary gel electrophoresis. This technique is accurate enough to differentiate one base-pair difference between fragments and hence is adequate in indicating the presence or absence of a frameshift in the coding sequence of the targeted gene. This precise knowledge effectively precludes the need for a confirmatory sequencing step and allows users to save time and cost in the process. Moreover, this technique has proven to be versatile in genotyping various mammalian cells of various tissue origins targeted by guide RNAs against numerous genes, as shown here and elsewhere.

Lensless on-chip imaging of cells provides a new tool for high-throughput cell-biology and medical diagnostics.

PubMed

Mudanyali, Onur; Erlinger, Anthony; Seo, Sungkyu; Su, Ting-Wei; Tseng, Derek; Ozcan, Aydogan

2009-12-14

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as approximately 18 cm(2). Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of approximately 5 mm without the need for refocusing which corresponds to up to approximately 9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments.

Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics

PubMed Central

Mudanyali, Onur; Erlinger, Anthony; Seo, Sungkyu; Su, Ting-Wei; Tseng, Derek; Ozcan, Aydogan

2009-01-01

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as ~18 cm2. Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of ~5 mm without the need for refocusing which corresponds to up to ~9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments. PMID:20010542

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.

Environmental microbiology through the lens of high-throughput DNA sequencing: synopsis of current platforms and bioinformatics approaches.

PubMed

Logares, Ramiro; Haverkamp, Thomas H A; Kumar, Surendra; Lanzén, Anders; Nederbragt, Alexander J; Quince, Christopher; Kauserud, Håvard

2012-10-01

The incursion of High-Throughput Sequencing (HTS) in environmental microbiology brings unique opportunities and challenges. HTS now allows a high-resolution exploration of the vast taxonomic and metabolic diversity present in the microbial world, which can provide an exceptional insight on global ecosystem functioning, ecological processes and evolution. This exploration has also economic potential, as we will have access to the evolutionary innovation present in microbial metabolisms, which could be used for biotechnological development. HTS is also challenging the research community, and the current bottleneck is present in the data analysis side. At the moment, researchers are in a sequence data deluge, with sequencing throughput advancing faster than the computer power needed for data analysis. However, new tools and approaches are being developed constantly and the whole process could be depicted as a fast co-evolution between sequencing technology, informatics and microbiologists. In this work, we examine the most popular and recently commercialized HTS platforms as well as bioinformatics methods for data handling and analysis used in microbial metagenomics. This non-exhaustive review is intended to serve as a broad state-of-the-art guide to researchers expanding into this rapidly evolving field. Copyright © 2012 Elsevier B.V. All rights reserved.

Incorporating High-Throughput Exposure Predictions with ...

EPA Pesticide Factsheets

We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast™ HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast™ efforts expand (i.e., Phase II) beyond food-use pesticides towards a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. EPA ExpoCast™ program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, three or 13 chemicals possessed AERs <1 or <100, respectively. Diverse bioactivities y across a range of assays and concentrations was also noted across the wider chemical space su

High-throughput tandem mass spectrometry multiplex analysis for newborn urinary screening of creatine synthesis and transport disorders, Triple H syndrome and OTC deficiency.

PubMed

Auray-Blais, Christiane; Maranda, Bruno; Lavoie, Pamela

2014-09-25

Creatine synthesis and transport disorders, Triple H syndrome and ornithine transcarbamylase deficiency are treatable inborn errors of metabolism. Early screening of patients was found to be beneficial. Mass spectrometry analysis of specific urinary biomarkers might lead to early detection and treatment in the neonatal period. We developed a high-throughput mass spectrometry methodology applicable to newborn screening using dried urine on filter paper for these aforementioned diseases. A high-throughput methodology was devised for the simultaneous analysis of creatine, guanidineacetic acid, orotic acid, uracil, creatinine and respective internal standards, using both positive and negative electrospray ionization modes, depending on the compound. The precision and accuracy varied by <15%. Stability during storage at different temperatures was confirmed for three weeks. The limits of detection and quantification for each biomarker varied from 0.3 to 6.3 μmol/l and from 1.0 to 20.9 μmol/l, respectively. Analyses of urine specimens from affected patients revealed abnormal results. Targeted biomarkers in urine were detected in the first weeks of life. This rapid, simple and robust liquid chromatography/tandem mass spectrometry methodology is an efficient tool applicable to urine screening for inherited disorders by biochemical laboratories. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences

NASA Astrophysics Data System (ADS)

Afzal, Mohammad Atif Faiz; Evangelista, William; Hachmann, Johannes

The discovery of new compounds, materials, and chemical reactions with exceptional properties is the key for the grand challenges in innovation, energy and sustainability. This process can be dramatically accelerated by means of the virtual high-throughput screening (HTPS) of large-scale candidate libraries. The resulting data can further be used to study the underlying structure-property relationships and thus facilitate rational design capability. This approach has been extensively used for many years in the drug discovery community. However, the lack of openly available virtual HTPS tools is limiting the use of these techniques in various other applications such as photovoltaics, optoelectronics, and catalysis. Thus, we developed ChemHTPS, a general-purpose, comprehensive and user-friendly suite, that will allow users to efficiently perform large in silico modeling studies and high-throughput analyses in these applications. ChemHTPS also includes a massively parallel molecular library generator which offers a multitude of options to customize and restrict the scope of the enumerated chemical space and thus tailor it for the demands of specific applications. To streamline the non-combinatorial exploration of chemical space, we incorporate genetic algorithms into the framework. In addition to implementing smarter algorithms, we also focus on the ease of use, workflow, and code integration to make this technology more accessible to the community.

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

Screening Chemicals for Estrogen Receptor Bioactivity Using a Computational Model.

PubMed

Browne, Patience; Judson, Richard S; Casey, Warren M; Kleinstreuer, Nicole C; Thomas, Russell S

2015-07-21

The U.S. Environmental Protection Agency (EPA) is considering high-throughput and computational methods to evaluate the endocrine bioactivity of environmental chemicals. Here we describe a multistep, performance-based validation of new methods and demonstrate that these new tools are sufficiently robust to be used in the Endocrine Disruptor Screening Program (EDSP). Results from 18 estrogen receptor (ER) ToxCast high-throughput screening assays were integrated into a computational model that can discriminate bioactivity from assay-specific interference and cytotoxicity. Model scores range from 0 (no activity) to 1 (bioactivity of 17β-estradiol). ToxCast ER model performance was evaluated for reference chemicals, as well as results of EDSP Tier 1 screening assays in current practice. The ToxCast ER model accuracy was 86% to 93% when compared to reference chemicals and predicted results of EDSP Tier 1 guideline and other uterotrophic studies with 84% to 100% accuracy. The performance of high-throughput assays and ToxCast ER model predictions demonstrates that these methods correctly identify active and inactive reference chemicals, provide a measure of relative ER bioactivity, and rapidly identify chemicals with potential endocrine bioactivities for additional screening and testing. EPA is accepting ToxCast ER model data for 1812 chemicals as alternatives for EDSP Tier 1 ER binding, ER transactivation, and uterotrophic assays.

Electron beam throughput from raster to imaging

NASA Astrophysics Data System (ADS)

Zywno, Marek

2016-12-01

Two architectures of electron beam tools are presented: single beam MEBES Exara designed and built by Etec Systems for mask writing, and the Reflected E-Beam Lithography tool (REBL), designed and built by KLA-Tencor under a DARPA Agreement No. HR0011-07-9-0007. Both tools have implemented technologies not used before to achieve their goals. The MEBES X, renamed Exara for marketing purposes, used an air bearing stage running in vacuum to achieve smooth continuous scanning. The REBL used 2 dimensional imaging to distribute charge to a 4k pixel swath to achieve writing times on the order of 1 wafer per hour, scalable to throughput approaching optical projection tools. Three stage architectures were designed for continuous scanning of wafers: linear maglev, rotary maglev, and dual linear maglev.

Real-time traffic sign detection and recognition

NASA Astrophysics Data System (ADS)

Herbschleb, Ernst; de With, Peter H. N.

2009-01-01

The continuous growth of imaging databases increasingly requires analysis tools for extraction of features. In this paper, a new architecture for the detection of traffic signs is proposed. The architecture is designed to process a large database with tens of millions of images with a resolution up to 4,800x2,400 pixels. Because of the size of the database, a high reliability as well as a high throughput is required. The novel architecture consists of a three-stage algorithm with multiple steps per stage, combining both color and specific spatial information. The first stage contains an area-limitation step which is performance critical in both the detection rate as the overall processing time. The second stage locates suggestions for traffic signs using recently published feature processing. The third stage contains a validation step to enhance reliability of the algorithm. During this stage, the traffic signs are recognized. Experiments show a convincing detection rate of 99%. With respect to computational speed, the throughput for line-of-sight images of 800×600 pixels is 35 Hz and for panorama images it is 4 Hz. Our novel architecture outperforms existing algorithms, with respect to both detection rate and throughput

The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences

PubMed Central

Merchant, Nirav; Lyons, Eric; Goff, Stephen; Vaughn, Matthew; Ware, Doreen; Micklos, David; Antin, Parker

2016-01-01

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant’s platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses. PMID:26752627

Eight-Channel AC Magnetosusceptometer of Magnetic Nanoparticles for High-Throughput and Ultra-High-Sensitivity Immunoassay

PubMed Central

Chieh, Jen-Jie; Wei, Wen-Chun; Chen, Hsin-Hsein; Lee, Yen-Fu; Lin, Feng-Chun; Chiang, Ming-Hsien; Chiu, Ming-Jang; Horng, Herng-Er; Yang, Shieh-Yueh

2018-01-01

An alternating-current magnetosusceptometer of antibody-functionalized magnetic nanoparticles (MNPs) was developed for immunomagnetic reduction (IMR). A high-sensitivity, high-critical-temperature superconducting quantum interference device was used in the magnetosusceptometer. Minute levels of biomarkers of early-stage neurodegeneration diseases were detectable in serum, but measuring each biomarker required approximately 4 h. Hence, an eight-channel platform was developed in this study to fit minimal screening requirements for Alzheimer’s disease. Two consistent results were measured for three biomarkers, namely Aβ40, Aβ42, and tau protein, per human specimen. This paper presents the instrument configuration as well as critical characteristics, such as the low noise level variations among channels, a high signal-to-noise ratio, and the coefficient of variation for the biomarkers’ IMR values. The instrument’s ultrahigh sensitivity levels for the three biomarkers and the substantially shorter total measurement time in comparison with the previous single- and four-channels platforms were also demonstrated in this study. Thus, the eight-channel instrument may serve as a powerful tool for clinical high-throughput screening of Alzheimer’s disease. PMID:29601532

Single-Molecule Flow Platform for the Quantification of Biomolecules Attached to Single Nanoparticles.

PubMed

Jung, Seung-Ryoung; Han, Rui; Sun, Wei; Jiang, Yifei; Fujimoto, Bryant S; Yu, Jiangbo; Kuo, Chun-Ting; Rong, Yu; Zhou, Xing-Hua; Chiu, Daniel T

2018-05-15

We describe here a flow platform for quantifying the number of biomolecules on individual fluorescent nanoparticles. The platform combines line-confocal fluorescence detection with near nanoscale channels (1-2 μm in width and height) to achieve high single-molecule detection sensitivity and throughput. The number of biomolecules present on each nanoparticle was determined by deconvolving the fluorescence intensity distribution of single-nanoparticle-biomolecule complexes with the intensity distribution of single biomolecules. We demonstrate this approach by quantifying the number of streptavidins on individual semiconducting polymer dots (Pdots); streptavidin was rendered fluorescent using biotin-Alexa647. This flow platform has high-throughput (hundreds to thousands of nanoparticles detected per second) and requires minute amounts of sample (∼5 μL at a dilute concentration of 10 pM). This measurement method is an additional tool for characterizing synthetic or biological nanoparticles.

Large-Scale Discovery of Induced Point Mutations With High-Throughput TILLING

PubMed Central

Till, Bradley J.; Reynolds, Steven H.; Greene, Elizabeth A.; Codomo, Christine A.; Enns, Linda C.; Johnson, Jessica E.; Burtner, Chris; Odden, Anthony R.; Young, Kim; Taylor, Nicholas E.; Henikoff, Jorja G.; Comai, Luca; Henikoff, Steven

2003-01-01

TILLING (Targeting Induced Local Lesions in Genomes) is a general reverse-genetic strategy that provides an allelic series of induced point mutations in genes of interest. High-throughput TILLING allows the rapid and low-cost discovery of induced point mutations in populations of chemically mutagenized individuals. As chemical mutagenesis is widely applicable and mutation detection for TILLING is dependent only on sufficient yield of PCR products, TILLING can be applied to most organisms. We have developed TILLING as a service to the Arabidopsis community known as the Arabidopsis TILLING Project (ATP). Our goal is to rapidly deliver allelic series of ethylmethanesulfonate-induced mutations in target 1-kb loci requested by the international research community. In the first year of public operation, ATP has discovered, sequenced, and delivered >1000 mutations in >100 genes ordered by Arabidopsis researchers. The tools and methodologies described here can be adapted to create similar facilities for other organisms. PMID:12618384

Comparison of submerged and unsubmerged printing of ovarian cancer cells.

PubMed

Davidoff, Sherry N; Au, David; Smith, Samuel; Brooks, Amanda E; Brooks, Benjamin D

2015-01-01

A high-throughput cell based assay would greatly aid in the development and screening of ovarian cancer drug candidates. Previously, a three-dimensional microfluidic printer that is not only capable of controlling the location of cell deposition, but also of maintaining a liquid, nutrient rich environment to preserve cellular phenotype has been developed (Wasatch Microfluidics). In this study, we investigated the impact (i.e., viability, density, and phenotype) of depositing cells on a surface submerged in cell culture media. It was determined that submersion of the microfluidic print head in cell media did not alter the cell density, viability, or phenotype.. This article describes an in depth study detailing the impact of one of the fundamental components of a 3D microfluidic cell printer designed to mimic the in vivo cell environment. Development of such a tool holds promise as a high-throughput drug-screening platform for new cancer therapeutics.

RGS17: an emerging therapeutic target for lung and prostate cancers

PubMed Central

Bodle, Christopher R; Mackie, Duncan I; Roman, David L

2013-01-01

Ligands for G-protein-coupled receptors (GPCRs) represent approximately 50% of currently marketed drugs. RGS proteins modulate heterotrimeric G proteins and, thus, GPCR signaling, by accelerating the intrinsic GTPase activity of the Gα subunit. Given the prevalence of GPCR targeted therapeutics and the role RGS proteins play in G protein signaling, some RGS proteins are emerging as targets in their own right. One such RGS protein is RGS17. Increased RGS17 expression in some prostate and lung cancers has been demonstrated to support cancer progression, while reduced expression of RGS17 can lead to development of chemotherapeutic resistance in ovarian cancer. High-throughput screening is a powerful tool for lead compound identification, and utilization of high-throughput technologies has led to the discovery of several RGS inhibitors, thus far. As screening technologies advance, the identification of novel lead compounds the subsequent development of targeted therapeutics appears promising. PMID:23734683

Raspberry Pi-powered imaging for plant phenotyping.

PubMed

Tovar, Jose C; Hoyer, J Steen; Lin, Andy; Tielking, Allison; Callen, Steven T; Elizabeth Castillo, S; Miller, Michael; Tessman, Monica; Fahlgren, Noah; Carrington, James C; Nusinow, Dmitri A; Gehan, Malia A

2018-03-01

Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data. We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi-controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open-source image processing software such as PlantCV. This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.

High throughput dual-wavelength temperature distribution imaging via compressive imaging

NASA Astrophysics Data System (ADS)

Yao, Xu-Ri; Lan, Ruo-Ming; Liu, Xue-Feng; Zhu, Ge; Zheng, Fu; Yu, Wen-Kai; Zhai, Guang-Jie

2018-03-01

Thermal imaging is an essential tool in a wide variety of research areas. In this work we demonstrate high-throughput double-wavelength temperature distribution imaging using a modified single-pixel camera without the requirement of a beam splitter (BS). A digital micro-mirror device (DMD) is utilized to display binary masks and split the incident radiation, which eliminates the necessity of a BS. Because the spatial resolution is dictated by the DMD, this thermal imaging system has the advantage of perfect spatial registration between the two images, which limits the need for the pixel registration and fine adjustments. Two bucket detectors, which measures the total light intensity reflected from the DMD, are employed in this system and yield an improvement in the detection efficiency of the narrow-band radiation. A compressive imaging algorithm is utilized to achieve under-sampling recovery. A proof-of-principle experiment was presented to demonstrate the feasibility of this structure.

A high-throughput technique for determining grain boundary character non-destructively in microstructures with through-thickness grains

DOE PAGES

Seita, Matteo; Volpi, Marco; Patala, Srikanth; ...

2016-06-24

Grain boundaries (GBs) govern many properties of polycrystalline materials. However, because of their structural variability, our knowledge of GB constitutive relations is still very limited. We present a novel method to characterise the complete crystallography of individual GBs non-destructively, with high-throughput, and using commercially available tools. This method combines electron diffraction, optical reflectance and numerical image analysis to determine all five crystallographic parameters of numerous GBs in samples with through-thickness grains. We demonstrate the technique by measuring the crystallographic character of about 1,000 individual GBs in aluminum in a single run. Our method enables cost- and time-effective assembly of crystallography–propertymore » databases for thousands of individual GBs. Furthermore, such databases are essential for identifying GB constitutive relations and for predicting GB-related behaviours of polycrystalline solids.« less

3D-SURFER: software for high-throughput protein surface comparison and analysis

PubMed Central

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-01-01

Summary: We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. Availability: 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19759195

3D-SURFER: software for high-throughput protein surface comparison and analysis.

PubMed

La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-11-01

We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer dkihara@purdue.edu Supplementary data are available at Bioinformatics online.

High-Throughput Amplicon-Based Copy Number Detection of 11 Genes in Formalin-Fixed Paraffin-Embedded Ovarian Tumour Samples by MLPA-Seq

PubMed Central

Kondrashova, Olga; Love, Clare J.; Lunke, Sebastian; Hsu, Arthur L.; Waring, Paul M.; Taylor, Graham R.

2015-01-01

Whilst next generation sequencing can report point mutations in fixed tissue tumour samples reliably, the accurate determination of copy number is more challenging. The conventional Multiplex Ligation-dependent Probe Amplification (MLPA) assay is an effective tool for measurement of gene dosage, but is restricted to around 50 targets due to size resolution of the MLPA probes. By switching from a size-resolved format, to a sequence-resolved format we developed a scalable, high-throughput, quantitative assay. MLPA-seq is capable of detecting deletions, duplications, and amplifications in as little as 5ng of genomic DNA, including from formalin-fixed paraffin-embedded (FFPE) tumour samples. We show that this method can detect BRCA1, BRCA2, ERBB2 and CCNE1 copy number changes in DNA extracted from snap-frozen and FFPE tumour tissue, with 100% sensitivity and >99.5% specificity. PMID:26569395

A high throughput mechanical screening device for cartilage tissue engineering.

PubMed

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

2014-06-27

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

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

PubMed Central

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

2014-01-01

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

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.

FunRich proteomics software analysis, let the fun begin!

PubMed

Benito-Martin, Alberto; Peinado, Héctor

2015-08-01

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small-scale and high-throughput studies. However, user-friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597-2601) report the development of FunRich software, an open-access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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

Eddy current-shielded x-space relaxometer for sensitive magnetic nanoparticle characterization

PubMed Central

Bauer, L. M.; Hensley, D. W.; Zheng, B.; Tay, Z. W.; Goodwill, P. W.; Griswold, M. A.; Conolly, S. M.

2016-01-01

The development of magnetic particle imaging (MPI) has created a need for optimized magnetic nanoparticles. Magnetic particle relaxometry is an excellent tool for characterizing potential tracers for MPI. In this paper, we describe the design and construction of a high-throughput tabletop relaxometer that is able to make sensitive measurements of MPI tracers without the need for a dedicated shield room. PMID:27250472

Eddy current-shielded x-space relaxometer for sensitive magnetic nanoparticle characterization.

PubMed

Bauer, L M; Hensley, D W; Zheng, B; Tay, Z W; Goodwill, P W; Griswold, M A; Conolly, S M

2016-05-01

The development of magnetic particle imaging (MPI) has created a need for optimized magnetic nanoparticles. Magnetic particle relaxometry is an excellent tool for characterizing potential tracers for MPI. In this paper, we describe the design and construction of a high-throughput tabletop relaxometer that is able to make sensitive measurements of MPI tracers without the need for a dedicated shield room.

A dynamic regression analysis tool for quantitative assessment of bacterial growth written in Python.

PubMed

Hoeflinger, Jennifer L; Hoeflinger, Daniel E; Miller, Michael J

2017-01-01

Herein, an open-source method to generate quantitative bacterial growth data from high-throughput microplate assays is described. The bacterial lag time, maximum specific growth rate, doubling time and delta OD are reported. Our method was validated by carbohydrate utilization of lactobacilli, and visual inspection revealed 94% of regressions were deemed excellent. Copyright © 2016 Elsevier B.V. All rights reserved.

Low Cost, High-Throughput 3D Pulmonary Imager Using Hyperpolarized Contrast Agents and Low Field MRI

DTIC Science & Technology

2016-10-01

HAS THE PROJECT PROVIDED? ..... 7 HOW WERE THE RESULTS DISSEMINATED TO COMMUNITIES OF INTEREST? ................................................. 8...the results disseminated to communities of interest? Nothing to Report 4. IMPACT What was the impact on the development of the principal...the broader biomedical community , expanding the utility of HP methods as a new tool for probing fundamental biomedical questions. Acknowledgments The

High-throughput screening of dye-ligands for chromatography.

PubMed

Kumar, Sunil; Punekar, Narayan S

2014-01-01

Dye-ligand-based chromatography has become popular after Cibacron Blue, the first reactive textile dye, found application for protein purification. Many other textile dyes have since been successfully used to purify a number of proteins and enzymes. While the exact nature of their interaction with target proteins is often unclear, dye-ligands are thought to mimic the structural features of their corresponding substrates, cofactors, etc. The dye-ligand affinity matrices are therefore considered pseudo-affinity matrices. In addition, dye-ligands may simply bind with proteins due to electrostatic, hydrophobic, and hydrogen-bonding interactions. Because of their low cost, ready availability, and structural stability, dye-ligand affinity matrices have gained much popularity. Choice of a large number of dye structures offers a range of matrices to be prepared and tested. When presented in the high-throughput screening mode, these dye-ligand matrices provide a formidable tool for protein purification. One could pick from the list of dye-ligands already available or build a systematic library of such structures for use. A high-throughput screen may be set up to choose best dye-ligand matrix as well as ideal conditions for binding and elution, for a given protein. The mode of operation could be either manual or automated. The technology is available to test the performance of dye-ligand matrices in small volumes in an automated liquid-handling workstation. Screening a systematic library of dye-ligand structures can help establish a structure-activity relationship. While the origins of dye-ligand chromatography lay in exploiting pseudo-affinity, it is now possible to design very specific biomimetic dye structures. High-throughput screening will be of value in this endeavor as well.

Life in the fast lane for protein crystallization and X-ray crystallography

NASA Technical Reports Server (NTRS)

Pusey, Marc L.; Liu, Zhi-Jie; Tempel, Wolfram; Praissman, Jeremy; Lin, Dawei; Wang, Bi-Cheng; Gavira, Jose A.; Ng, Joseph D.

2005-01-01

The common goal for structural genomic centers and consortiums is to decipher as quickly as possible the three-dimensional structures for a multitude of recombinant proteins derived from known genomic sequences. Since X-ray crystallography is the foremost method to acquire atomic resolution for macromolecules, the limiting step is obtaining protein crystals that can be useful of structure determination. High-throughput methods have been developed in recent years to clone, express, purify, crystallize and determine the three-dimensional structure of a protein gene product rapidly using automated devices, commercialized kits and consolidated protocols. However, the average number of protein structures obtained for most structural genomic groups has been very low compared to the total number of proteins purified. As more entire genomic sequences are obtained for different organisms from the three kingdoms of life, only the proteins that can be crystallized and whose structures can be obtained easily are studied. Consequently, an astonishing number of genomic proteins remain unexamined. In the era of high-throughput processes, traditional methods in molecular biology, protein chemistry and crystallization are eclipsed by automation and pipeline practices. The necessity for high-rate production of protein crystals and structures has prevented the usage of more intellectual strategies and creative approaches in experimental executions. Fundamental principles and personal experiences in protein chemistry and crystallization are minimally exploited only to obtain "low-hanging fruit" protein structures. We review the practical aspects of today's high-throughput manipulations and discuss the challenges in fast pace protein crystallization and tools for crystallography. Structural genomic pipelines can be improved with information gained from low-throughput tactics that may help us reach the higher-bearing fruits. Examples of recent developments in this area are reported from the efforts of the Southeast Collaboratory for Structural Genomics (SECSG).

Life in the Fast Lane for Protein Crystallization and X-Ray Crystallography

NASA Technical Reports Server (NTRS)

Pusey, Marc L.; Liu, Zhi-Jie; Tempel, Wolfram; Praissman, Jeremy; Lin, Dawei; Wang, Bi-Cheng; Gavira, Jose A.; Ng, Joseph D.

2004-01-01

The common goal for structural genomic centers and consortiums is to decipher as quickly as possible the three-dimensional structures for a multitude of recombinant proteins derived from known genomic sequences. Since X-ray crystallography is the foremost method to acquire atomic resolution for macromolecules, the limiting step is obtaining protein crystals that can be useful of structure determination. High-throughput methods have been developed in recent years to clone, express, purify, crystallize and determine the three-dimensional structure of a protein gene product rapidly using automated devices, commercialized kits and consolidated protocols. However, the average number of protein structures obtained for most structural genomic groups has been very low compared to the total number of proteins purified. As more entire genomic sequences are obtained for different organisms from the three kingdoms of life, only the proteins that can be crystallized and whose structures can be obtained easily are studied. Consequently, an astonishing number of genomic proteins remain unexamined. In the era of high-throughput processes, traditional methods in molecular biology, protein chemistry and crystallization are eclipsed by automation and pipeline practices. The necessity for high rate production of protein crystals and structures has prevented the usage of more intellectual strategies and creative approaches in experimental executions. Fundamental principles and personal experiences in protein chemistry and crystallization are minimally exploited only to obtain "low-hanging fruit" protein structures. We review the practical aspects of today s high-throughput manipulations and discuss the challenges in fast pace protein crystallization and tools for crystallography. Structural genomic pipelines can be improved with information gained from low-throughput tactics that may help us reach the higher-bearing fruits. Examples of recent developments in this area are reported from the efforts of the Southeast Collaboratory for Structural Genomics (SECSG).

High throughput 16SrRNA gene sequencing reveals the correlation between Propionibacterium acnes and sarcoidosis.

PubMed

Zhao, Meng-Meng; Du, Shan-Shan; Li, Qiu-Hong; Chen, Tao; Qiu, Hui; Wu, Qin; Chen, Shan-Shan; Zhou, Ying; Zhang, Yuan; Hu, Yang; Su, Yi-Liang; Shen, Li; Zhang, Fen; Weng, Dong; Li, Hui-Ping

2017-02-01

This study aims to use high throughput 16SrRNA gene sequencing to examine the bacterial profile of lymph node biopsy samples of patients with sarcoidosis and to further verify the association between Propionibacterium acnes (P. acnes) and sarcoidosis. A total of 36 mediastinal lymph node biopsy specimens were collected from 17 cases of sarcoidosis, 8 tuberculosis (TB group), and 11 non-infectious lung diseases (control group). The V4 region of the bacterial 16SrRNA gene in the specimens was amplified and sequenced using the high throughput sequencing platform MiSeq, and bacterial profile was established. The data analysis software QIIME and Metastats were used to compare bacterial relative abundance in the three patient groups. Overall, 545 genera were identified; 38 showed significantly lower and 29 had significantly higher relative abundance in the sarcoidosis group than in the TB and control groups (P < 0.01). P. acnes 16SrRNA was exclusively found in all the 17 samples of the sarcoidosis group, whereas was not detected in the TB and control groups. The relative abundance of P. acnes in the sarcoidosis group (0.16% ± 0. 11%) was significantly higher than that in the TB (Metastats analysis: P = 0.0010, q = 0.0044) and control groups (Metastats analysis: P = 0.0010, q = 0.0038). The relative abundance of P. granulosum was only 0.0022% ± 0. 0044% in the sarcoidosis group. P. granulosum 16SrRNA was not detected in the other two groups. High throughput 16SrRNA gene sequencing appears to be a useful tool to investigate the bacterial profile of sarcoidosis specimens. The results suggest that P. acnes may be involved in sarcoidosis development.

WE-E-BRE-03: Biological Validation of a Novel High-Throughput Irradiator for Predictive Radiation Sensitivity Bioassays

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

Fowler, TL; Martin, JA; Shepard, AJ

2014-06-15

Purpose: The large dose-response variation in both tumor and normal cells between individual patients has led to the recent implementation of predictive bioassays of patient-specific radiation sensitivity in order to personalize radiation therapy. This exciting new clinical paradigm has led us to develop a novel high-throughput, variable dose-rate irradiator to accompany these efforts. Here we present the biological validation of this irradiator through the use of human cells as a relative dosimeter assessed by two metrics, DNA double-strand break repair pathway modulation and intercellular reactive oxygen species production. Methods: Immortalized human tonsilar epithelial cells were cultured in 96-well micro titermore » plates and irradiated in groups of eight wells to absorbed doses of 0, 0.5, 1, 2, 4, and 8 Gy. High-throughput immunofluorescent microscopy was used to detect γH2AX, a DNA double-strand break repair mechanism recruiter. The same analysis was performed with the cells stained with CM-H2DCFDA that produces a fluorescent adduct when exposed to reactive oxygen species during the irradiation cycle. Results: Irradiations of the immortalized human tonsilar epithelial cells at absorbed doses of 0, 0.5, 1, 2, 4, and 8 Gy produced excellent linearity in γH2AX and CM-H2DCFDA with R2 values of 0.9939 and 0.9595 respectively. Single cell gel electrophoresis experimentation for the detection of physical DNA double-strand breaks in ongoing. Conclusions: This work indicates significant potential for our high-throughput variable dose rate irradiator for patient-specific predictive radiation sensitivity bioassays. This irradiator provides a powerful tool by increasing the efficiency and number of assay techniques available to help personalize radiation therapy.« less

Trajectory Assessment and Modification Tools for Next Generation Air Traffic Management Operations

NASA Technical Reports Server (NTRS)

Brasil, Connie; Lee, Paul; Mainini, Matthew; Lee, Homola; Lee, Hwasoo; Prevot, Thomas; Smith, Nancy

2011-01-01

This paper reviews three Next Generation Air Transportation System (NextGen) based high fidelity air traffic control human-in-the-loop (HITL) simulations, with a focus on the expected requirement of enhanced automated trajectory assessment and modification tools to support future air traffic flow management (ATFM) planning positions. The simulations were conducted at the National Aeronautics and Space Administration (NASA) Ames Research Centers Airspace Operations Laboratory (AOL) in 2009 and 2010. The test airspace for all three simulations assumed the mid-term NextGenEn-Route high altitude environment utilizing high altitude sectors from the Kansas City and Memphis Air Route Traffic Control Centers. Trajectory assessment, modification and coordination decision support tools were developed at the AOL in order to perform future ATFM tasks. Overall tool usage results and user acceptability ratings were collected across three areas of NextGen operatoins to evaluate the tools. In addition to the usefulness and usability feedback, feasibility issues, benefits, and future requirements were also addressed. Overall, the tool sets were rated very useful and usable, and many elements of the tools received high scores and were used frequently and successfully. Tool utilization results in all three HITLs showed both user and system benefits including better airspace throughput, reduced controller workload, and highly effective communication protocols in both full Data Comm and mixed-equipage environments.

OpenMSI Arrayed Analysis Tools v2.0

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

BOWEN, BENJAMIN; RUEBEL, OLIVER; DE ROND, TRISTAN

2017-02-07

Mass spectrometry imaging (MSI) enables high-resolution spatial mapping of biomolecules in samples and is a valuable tool for the analysis of tissues from plants and animals, microbial interactions, high-throughput screening, drug metabolism, and a host of other applications. This is accomplished by desorbing molecules from the surface on spatially defined locations, using a laser or ion beam. These ions are analyzed by a mass spectrometry and collected into a MSI 'image', a dataset containing unique mass spectra from the sampled spatial locations. MSI is used in a diverse and increasing number of biological applications. The OpenMSI Arrayed Analysis Tool (OMAAT)more » is a new software method that addresses the challenges of analyzing spatially defined samples in large MSI datasets, by providing support for automatic sample position optimization and ion selection.« less

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

PubMed

Röst, Hannes L; Liu, Yansheng; D'Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-09-01

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

Design and engineering of intracellular-metabolite-sensing/regulation gene circuits in Saccharomyces cerevisiae.

PubMed

Wang, Meng; Li, Sijin; Zhao, Huimin

2016-01-01

The development of high-throughput phenotyping tools is lagging far behind the rapid advances of genotype generation methods. To bridge this gap, we report a new strategy for design, construction, and fine-tuning of intracellular-metabolite-sensing/regulation gene circuits by repurposing bacterial transcription factors and eukaryotic promoters. As proof of concept, we systematically investigated the design and engineering of bacterial repressor-based xylose-sensing/regulation gene circuits in Saccharomyces cerevisiae. We demonstrated that numerous properties, such as induction ratio and dose-response curve, can be fine-tuned at three different nodes, including repressor expression level, operator position, and operator sequence. By applying these gene circuits, we developed a cell sorting based, rapid and robust high-throughput screening method for xylose transporter engineering and obtained a sugar transporter HXT14 mutant with 6.5-fold improvement in xylose transportation capacity. This strategy should be generally applicable and highly useful for evolutionary engineering of proteins, pathways, and genomes in S. cerevisiae. © 2015 Wiley Periodicals, Inc.

Neural network Hilbert transform based filtered backprojection for fast inline x-ray inspection

NASA Astrophysics Data System (ADS)

Janssens, Eline; De Beenhouwer, Jan; Van Dael, Mattias; De Schryver, Thomas; Van Hoorebeke, Luc; Verboven, Pieter; Nicolai, Bart; Sijbers, Jan

2018-03-01

X-ray imaging is an important tool for quality control since it allows to inspect the interior of products in a non-destructive way. Conventional x-ray imaging, however, is slow and expensive. Inline x-ray inspection, on the other hand, can pave the way towards fast and individual quality control, provided that a sufficiently high throughput can be achieved at a minimal cost. To meet these criteria, an inline inspection acquisition geometry is proposed where the object moves and rotates on a conveyor belt while it passes a fixed source and detector. Moreover, for this acquisition geometry, a new neural-network-based reconstruction algorithm is introduced: the neural network Hilbert transform based filtered backprojection. The proposed algorithm is evaluated both on simulated and real inline x-ray data and has shown to generate high quality reconstructions of 400  ×  400 reconstruction pixels within 200 ms, thereby meeting the high throughput criteria.

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

PubMed Central

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

2016-01-01

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

High Content Imaging (HCI) on Miniaturized Three-Dimensional (3D) Cell Cultures

PubMed Central

Joshi, Pranav; Lee, Moo-Yeal

2015-01-01

High content imaging (HCI) is a multiplexed cell staining assay developed for better understanding of complex biological functions and mechanisms of drug action, and it has become an important tool for toxicity and efficacy screening of drug candidates. Conventional HCI assays have been carried out on two-dimensional (2D) cell monolayer cultures, which in turn limit predictability of drug toxicity/efficacy in vivo; thus, there has been an urgent need to perform HCI assays on three-dimensional (3D) cell cultures. Although 3D cell cultures better mimic in vivo microenvironments of human tissues and provide an in-depth understanding of the morphological and functional features of tissues, they are also limited by having relatively low throughput and thus are not amenable to high-throughput screening (HTS). One attempt of making 3D cell culture amenable for HTS is to utilize miniaturized cell culture platforms. This review aims to highlight miniaturized 3D cell culture platforms compatible with current HCI technology. PMID:26694477

Ancient pathogen DNA in archaeological samples detected with a Microbial Detection Array.

PubMed

Devault, Alison M; McLoughlin, Kevin; Jaing, Crystal; Gardner, Shea; Porter, Teresita M; Enk, Jacob M; Thissen, James; Allen, Jonathan; Borucki, Monica; DeWitte, Sharon N; Dhody, Anna N; Poinar, Hendrik N

2014-03-06

Ancient human remains of paleopathological interest typically contain highly degraded DNA in which pathogenic taxa are often minority components, making sequence-based metagenomic characterization costly. Microarrays may hold a potential solution to these challenges, offering a rapid, affordable, and highly informative snapshot of microbial diversity in complex samples without the lengthy analysis and/or high cost associated with high-throughput sequencing. Their versatility is well established for modern clinical specimens, but they have yet to be applied to ancient remains. Here we report bacterial profiles of archaeological and historical human remains using the Lawrence Livermore Microbial Detection Array (LLMDA). The array successfully identified previously-verified bacterial human pathogens, including Vibrio cholerae (cholera) in a 19th century intestinal specimen and Yersinia pestis ("Black Death" plague) in a medieval tooth, which represented only minute fractions (0.03% and 0.08% alignable high-throughput shotgun sequencing reads) of their respective DNA content. This demonstrates that the LLMDA can identify primary and/or co-infecting bacterial pathogens in ancient samples, thereby serving as a rapid and inexpensive paleopathological screening tool to study health across both space and time.

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

NASA Astrophysics Data System (ADS)

Mohanraj, Bhavana

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

Small angle X-ray scattering as a high-throughput method to classify antimicrobial modes of action.

PubMed

von Gundlach, A R; Garamus, V M; Gorniak, T; Davies, H A; Reischl, M; Mikut, R; Hilpert, K; Rosenhahn, A

2016-05-01

Multi-drug resistant bacteria are currently undermining our health care system worldwide. While novel antimicrobial drugs, such as antimicrobial peptides, are urgently needed, identification of new modes of action is money and time consuming, and in addition current approaches are not available in a high throughput manner. Here we explore how small angle X-ray scattering (SAXS) as high throughput method can contribute to classify the mode of action for novel antimicrobials and therefore supports fast decision making in drug development. Using data bases for natural occurring antimicrobial peptides or predicting novel artificial peptides, many candidates can be discovered that will kill a selected target bacterium. However, in order to narrow down the selection it is important to know if these peptides follow all the same mode of action. In addition, the mode of action should be different from conventional antibiotics, in consequence peptide candidates can be developed further into drugs against multi-drug resistant bacteria. Here we used one short antimicrobial peptide with unknown mode of action and compared the ultrastructural changes of Escherichia coli cells after treatment with the peptide to cells treated with classic antibiotics. The key finding is that SAXS as a structure sensitive tool provides a rapid feedback on drug induced ultrastructural alterations in whole E. coli cells. We could demonstrate that ultrastructural changes depend on the used antibiotics and their specific mode of action. This is demonstrated using several well characterized antimicrobial compounds and the analysis of resulting SAXS curves by principal component analysis. To understand the result of the PCA analysis, the data is correlated with TEM images. In contrast to real space imaging techniques, SAXS allows to obtain nanoscale information averaged over approximately one million cells. The measurement takes only seconds, while conventional tests to identify a mode of action require days or weeks per single substance. The antimicrobial peptide showed a different mode of action as all tested antibiotics including polymyxin B and is therefore a good candidate for further drug development. We envision SAXS to become a useful tool within the high-throughput screening pipeline of modern drug discovery. This article is part of a Special Issue entitled: Antimicrobial peptides edited by Karl Lohner and Kai Hilpert. Copyright © 2015 Elsevier B.V. All rights reserved.

Strategic and Operational Plan for Integrating Transcriptomics ...

EPA Pesticide Factsheets

Plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT; the details are in the attached slide presentation presentation on plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT, given at the OECD meeting on June 23, 2016

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

Phase imaging of mechanical properties of live cells (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wax, Adam

2017-02-01

The mechanisms by which cells respond to mechanical stimuli are essential for cell function yet not well understood. Many rheological tools have been developed to characterize cellular viscoelastic properties but these typically require direct mechanical contact, limiting their throughput. We have developed a new approach for characterizing the organization of subcellular structures using a label free, noncontact, single-shot phase imaging method that correlates to measured cellular mechanical stiffness. The new analysis approach measures refractive index variance and relates it to disorder strength. These measurements are compared to cellular stiffness, measured using the same imaging tool to visualize nanoscale responses to flow shear stimulus. The utility of the technique is shown by comparing shear stiffness and phase disorder strength across five cellular populations with varying mechanical properties. An inverse relationship between disorder strength and shear stiffness is shown, suggesting that cell mechanical properties can be assessed in a format amenable to high throughput studies using this novel, non-contact technique. Further studies will be presented which include examination of mechanical stiffness in early carcinogenic events and investigation of the role of specific cellular structural proteins in mechanotransduction.

DPubChem: a web tool for QSAR modeling and high-throughput virtual screening.

PubMed

Soufan, Othman; Ba-Alawi, Wail; Magana-Mora, Arturo; Essack, Magbubah; Bajic, Vladimir B

2018-06-14

High-throughput screening (HTS) performs the experimental testing of a large number of chemical compounds aiming to identify those active in the considered assay. Alternatively, faster and cheaper methods of large-scale virtual screening are performed computationally through quantitative structure-activity relationship (QSAR) models. However, the vast amount of available HTS heterogeneous data and the imbalanced ratio of active to inactive compounds in an assay make this a challenging problem. Although different QSAR models have been proposed, they have certain limitations, e.g., high false positive rates, complicated user interface, and limited utilization options. Therefore, we developed DPubChem, a novel web tool for deriving QSAR models that implement the state-of-the-art machine-learning techniques to enhance the precision of the models and enable efficient analyses of experiments from PubChem BioAssay database. DPubChem also has a simple interface that provides various options to users. DPubChem predicted active compounds for 300 datasets with an average geometric mean and F 1 score of 76.68% and 76.53%, respectively. Furthermore, DPubChem builds interaction networks that highlight novel predicted links between chemical compounds and biological assays. Using such a network, DPubChem successfully suggested a novel drug for the Niemann-Pick type C disease. DPubChem is freely available at www.cbrc.kaust.edu.sa/dpubchem .

Mask pattern generator employing EPL technology

NASA Astrophysics Data System (ADS)

Yoshioka, Nobuyuki; Yamabe, Masaki; Wakamiya, Wataru; Endo, Nobuhiro

2003-08-01

Mask cost is one of crucial issues in device fabrication, especially in SoC (System on a Chip) with small-volume production. The cost mainly depends on productivity of mask manufacturing tools such as mask writers and defect inspection tools. EPL (Electron Projection Lithography) has been developing as a high-throughput electron beam exposure technology that will succeed optical lithography. The application of EPL technology to mask writing will result in high productivity and contribute to decrease the mask cost. The concept of a mask pattern generator employing EPL technology is proposed in this paper. It is very similar to EPL technology used for pattern printing on a wafer. The mask patterns on the glass substrate are exposed by projecting the basic circuit patterns formed on the mother EPL mask. One example of the mother EPL mask is a stencil type made with 200-mm Si wafer. The basic circuit patterns are IP patterns and logical primitive patterns such as cell libraries (AND, OR, Inverter, Flip-Flop and etc.) to express the SoC device patterns. Since the SoC patterns are exposed with its collective units such as IP and logical primitive patterns by using this method, the high throughput will be expected comparing with conventional mask E-beam writers. In this paper, the mask pattern generator with the EPL technology is proposed. The concept, its advantages and issues to be solved are discussed.

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

PubMed

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

2016-01-01

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

Pre-amplification in the context of high-throughput qPCR gene expression experiment.

PubMed

Korenková, Vlasta; Scott, Justin; Novosadová, Vendula; Jindřichová, Marie; Langerová, Lucie; Švec, David; Šídová, Monika; Sjöback, Robert

2015-03-11

With the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm). For evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted. We set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.

Developing science gateways for drug discovery in a grid environment.

PubMed

Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra

2016-01-01

Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

Metrologies for quantitative nanomechanical testing and quality control in semiconductor manufacturing

NASA Astrophysics Data System (ADS)

Pratt, Jon R.; Kramar, John A.; Newell, David B.; Smith, Douglas T.

2005-05-01

If nanomechanical testing is to evolve into a tool for process and quality control in semiconductor fabrication, great advances in throughput, repeatability, and accuracy of the associated instruments and measurements will be required. A recent grant awarded by the NIST Advanced Technology Program seeks to address the throughput issue by developing a high-speed AFM-based platform for quantitative nanomechanical measurements. The following paper speaks to the issue of quantitative accuracy by presenting an overview of various standards and techniques under development at NIST and other national metrology institutes (NMIs) that can provide a metrological basis for nanomechanical testing. The infrastructure we describe places firm emphasis on traceability to the International System of Units, paving the way for truly quantitative, rather than qualitative, physical property testing.

Applying Genomic and Genetic Tools to Understand and Mitigate Damage from Exposure to Toxins

DTIC Science & Technology

2011-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Use of the pyridostigmine bromide during the 1991 Gulf War has been implicated as a contributing...2 EXECUTIVE SUMMARY Treatment of soldiers of the 1991 Gulf War with the drug pyridostigmine bromide for pretreatment against nerve agents has...organism for the characterization of the effects of pyridostigmine bromide (PB) on gene expression using unbiased, high-throughput techniques, specifically

1001 Ways to run AutoDock Vina for virtual screening

NASA Astrophysics Data System (ADS)

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D.

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

1001 Ways to run AutoDock Vina for virtual screening.

PubMed

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

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.

Analysis of Protein Expression in Cell Microarrays: A Tool for Antibody-based Proteomics

PubMed Central

Andersson, Ann-Catrin; Strömberg, Sara; Bäckvall, Helena; Kampf, Caroline; Uhlen, Mathias; Wester, Kenneth; Pontén, Fredrik

2006-01-01

Tissue microarray (TMA) technology provides a possibility to explore protein expression patterns in a multitude of normal and disease tissues in a high-throughput setting. Although TMAs have been used for analysis of tissue samples, robust methods for studying in vitro cultured cell lines and cell aspirates in a TMA format have been lacking. We have adopted a technique to homogeneously distribute cells in an agarose gel matrix, creating an artificial tissue. This enables simultaneous profiling of protein expression in suspension- and adherent-grown cell samples assembled in a microarray. In addition, the present study provides an optimized strategy for the basic laboratory steps to efficiently produce TMAs. Presented modifications resulted in an improved quality of specimens and a higher section yield compared with standard TMA production protocols. Sections from the generated cell TMAs were tested for immunohistochemical staining properties using 20 well-characterized antibodies. Comparison of immunoreactivity in cultured dispersed cells and corresponding cells in tissue samples showed congruent results for all tested antibodies. We conclude that a modified TMA technique, including cell samples, provides a valuable tool for high-throughput analysis of protein expression, and that this technique can be used for global approaches to explore the human proteome. PMID:16957166

Accelerating Adverse Outcome Pathway Development Using ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledgebase, however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally-predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of twenty-first century toxicity testing strategies. This review article describes how effective knowledge management and automated approaches to AOP development can enhance and accelerate the development and use of AOPs. As the principles documented in this review are put into practice, we anticipate that the quality and quantity of AOPs available will increase substantially. This, in turn, will aid in the interpretation of ToxCast and other high-throughput tox

Predicting the future: opportunities and challenges for the chemical industry to apply 21st-century toxicity testing.

PubMed

Settivari, Raja S; Ball, Nicholas; Murphy, Lynea; Rasoulpour, Reza; Boverhof, Darrell R; Carney, Edward W

2015-03-01

Interest in applying 21st-century toxicity testing tools for safety assessment of industrial chemicals is growing. Whereas conventional toxicology uses mainly animal-based, descriptive methods, a paradigm shift is emerging in which computational approaches, systems biology, high-throughput in vitro toxicity assays, and high-throughput exposure assessments are beginning to be applied to mechanism-based risk assessments in a time- and resource-efficient fashion. Here we describe recent advances in predictive safety assessment, with a focus on their strategic application to meet the changing demands of the chemical industry and its stakeholders. The opportunities to apply these new approaches is extensive and include screening of new chemicals, informing the design of safer and more sustainable chemical alternatives, filling information gaps on data-poor chemicals already in commerce, strengthening read-across methodology for categories of chemicals sharing similar modes of action, and optimizing the design of reduced-risk product formulations. Finally, we discuss how these predictive approaches dovetail with in vivo integrated testing strategies within repeated-dose regulatory toxicity studies, which are in line with 3Rs principles to refine, reduce, and replace animal testing. Strategic application of these tools is the foundation for informed and efficient safety assessment testing strategies that can be applied at all stages of the product-development process.

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data.

PubMed

Ambrosini, Giovanna; Dreos, René; Kumar, Sunil; Bucher, Philipp

2016-11-18

ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data. Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade. The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/ .

Detecting Submicron Pattern Defects On Optical Photomasks Using An Enhanced El-3 Electron-Beam Lithography Tool

NASA Astrophysics Data System (ADS)

Simpson, R. A.; Davis, D. E.

1982-09-01

This paper describes techniques to detect submicron pattern defects on optical photomasks with an enhanced direct-write, electron-beam lithographic tool. EL-3 is a third generation, shaped spot, electron-beam lithography tool developed by IBM to fabricate semiconductor devices and masks. This tool is being upgraded to provide 100% inspection of optical photomasks for submicron pattern defects, which are subsequently repaired. Fixed-size overlapped spots are stepped over the mask patterns while a signal derived from the back-scattered electrons is monitored to detect pattern defects. Inspection does not require pattern recognition because the inspection scan patterns are derived from the original design data. The inspection spot is square and larger than the minimum defect to be detected, to improve throughput. A new registration technique provides the beam-to-pattern overlay required to locate submicron defects. The 'guard banding" of inspection shapes prevents mask and system tolerances from producing false alarms that would occur should the spots be mispositioned such that they only partially covered a shape being inspected. A rescanning technique eliminates noise-related false alarms and significantly improves throughput. Data is accumulated during inspection and processed offline, as required for defect repair. EL-3 will detect 0.5 um pattern defects at throughputs compatible with mask manufacturing.

Continuous processing and the applications of online tools in pharmaceutical product manufacture: developments and examples.

PubMed

Ooi, Shing Ming; Sarkar, Srimanta; van Varenbergh, Griet; Schoeters, Kris; Heng, Paul Wan Sia

2013-04-01

Continuous processing and production in pharmaceutical manufacturing has received increased attention in recent years mainly due to the industries' pressing needs for more efficient, cost-effective processes and production, as well as regulatory facilitation. To achieve optimum product quality, the traditional trial-and-error method for the optimization of different process and formulation parameters is expensive and time consuming. Real-time evaluation and the control of product quality using an online process analyzer in continuous processing can provide high-quality production with very high-throughput at low unit cost. This review focuses on continuous processing and the application of different real-time monitoring tools used in the pharmaceutical industry for continuous processing from powder to tablets.

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.

The ChIP-exo Method: Identifying Protein-DNA Interactions with Near Base Pair Precision.

PubMed

Perreault, Andrea A; Venters, Bryan J

2016-12-23

Chromatin immunoprecipitation (ChIP) is an indispensable tool in the fields of epigenetics and gene regulation that isolates specific protein-DNA interactions. ChIP coupled to high throughput sequencing (ChIP-seq) is commonly used to determine the genomic location of proteins that interact with chromatin. However, ChIP-seq is hampered by relatively low mapping resolution of several hundred base pairs and high background signal. The ChIP-exo method is a refined version of ChIP-seq that substantially improves upon both resolution and noise. The key distinction of the ChIP-exo methodology is the incorporation of lambda exonuclease digestion in the library preparation workflow to effectively footprint the left and right 5' DNA borders of the protein-DNA crosslink site. The ChIP-exo libraries are then subjected to high throughput sequencing. The resulting data can be leveraged to provide unique and ultra-high resolution insights into the functional organization of the genome. Here, we describe the ChIP-exo method that we have optimized and streamlined for mammalian systems and next-generation sequencing-by-synthesis platform.

Solution-Phase Photochemical Nanopatterning Enabled by High-Refractive-Index Beam Pen Arrays.

PubMed

Xie, Zhuang; Gordiichuk, Pavlo; Lin, Qing-Yuan; Meckes, Brian; Chen, Peng-Cheng; Sun, Lin; Du, Jingshan S; Zhu, Jinghan; Liu, Yuan; Dravid, Vinayak P; Mirkin, Chad A

2017-08-22

A high-throughput, solution-based, scanning-probe photochemical nanopatterning approach, which does not require the use of probes with subwavelength apertures, is reported. Specifically, pyramid arrays made from high-refractive-index polymeric materials were constructed and studied as patterning tools in a conventional liquid-phase beam pen lithography experiment. Two versions of the arrays were explored with either metal-coated or metal-free tips. Importantly, light can be channeled through both types of tips and the appropriate solution phase (e.g., H 2 O or CH 3 OH) and focused on subwavelength regions of a substrate to effect a photoreaction in solution that results in localized patterning of a self-assembled monolayer (SAM)-coated Au thin film substrate. Arrays with as many as 4500 pyramid-shaped probes were used to simultaneously initiate thousands of localized free-radical photoreactions (decomposition of a lithium acylphosphinate photoinitiator in an aqueous solution) that result in oxidative removal of the SAM. The technique is attractive since it allows one to rapidly generate features less than 200 nm in diameter, and the metal-free tips afford more than 10-fold higher intensity than the tips with nanoapertures over a micrometer propagation length. In principle, this mask-free method can be utilized as a versatile tool for performing a wide variety of photochemistries across multiple scales that may be important in high-throughput combinatorial screening applications related to chemistry, biology, and materials science.

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.

Accelerating evaluation of converged lattice thermal conductivity

NASA Astrophysics Data System (ADS)

Qin, Guangzhao; Hu, Ming

2018-01-01

High-throughput computational materials design is an emerging area in materials science, which is based on the fast evaluation of physical-related properties. The lattice thermal conductivity (κ) is a key property of materials for enormous implications. However, the high-throughput evaluation of κ remains a challenge due to the large resources costs and time-consuming procedures. In this paper, we propose a concise strategy to efficiently accelerate the evaluation process of obtaining accurate and converged κ. The strategy is in the framework of phonon Boltzmann transport equation (BTE) coupled with first-principles calculations. Based on the analysis of harmonic interatomic force constants (IFCs), the large enough cutoff radius (rcutoff), a critical parameter involved in calculating the anharmonic IFCs, can be directly determined to get satisfactory results. Moreover, we find a simple way to largely ( 10 times) accelerate the computations by fast reconstructing the anharmonic IFCs in the convergence test of κ with respect to the rcutof, which finally confirms the chosen rcutoff is appropriate. Two-dimensional graphene and phosphorene along with bulk SnSe are presented to validate our approach, and the long-debate divergence problem of thermal conductivity in low-dimensional systems is studied. The quantitative strategy proposed herein can be a good candidate for fast evaluating the reliable κ and thus provides useful tool for high-throughput materials screening and design with targeted thermal transport properties.

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins.

PubMed

Reddy, Jithender G; Kumar, Dinesh; Hosur, Ramakrishna V

2015-02-01

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.

Screening of HIV-1 Protease Using a Combination of an Ultra-High-Throughput Fluorescent-Based Assay and RapidFire Mass Spectrometry.

PubMed

Meng, Juncai; Lai, Ming-Tain; Munshi, Vandna; Grobler, Jay; McCauley, John; Zuck, Paul; Johnson, Eric N; Uebele, Victor N; Hermes, Jeffrey D; Adam, Gregory C

2015-06-01

HIV-1 protease (PR) represents one of the primary targets for developing antiviral agents for the treatment of HIV-infected patients. To identify novel PR inhibitors, a label-free, high-throughput mass spectrometry (HTMS) assay was developed using the RapidFire platform and applied as an orthogonal assay to confirm hits identified in a fluorescence resonance energy transfer (FRET)-based primary screen of > 1 million compounds. For substrate selection, a panel of peptide substrates derived from natural processing sites for PR was evaluated on the RapidFire platform. As a result, KVSLNFPIL, a new substrate measured to have a ~ 20- and 60-fold improvement in k cat/K m over the frequently used sequences SQNYPIVQ and SQNYPIV, respectively, was identified for the HTMS screen. About 17% of hits from the FRET-based primary screen were confirmed in the HTMS confirmatory assay including all 304 known PR inhibitors in the set, demonstrating that the HTMS assay is effective at triaging false-positives while capturing true hits. Hence, with a sampling rate of ~7 s per well, the RapidFire HTMS assay enables the high-throughput evaluation of peptide substrates and functions as an efficient tool for hits triage in the discovery of novel PR inhibitors. © 2015 Society for Laboratory Automation and Screening.

A mask manufacturer's perspective on maskless lithography

NASA Astrophysics Data System (ADS)

Buck, Peter; Biechler, Charles; Kalk, Franklin

2005-11-01

Maskless Lithography (ML2) is again being considered for use in mainstream CMOS IC manufacturing. Sessions at technical conferences are being devoted to ML2. A multitude of new companies have been formed in the last several years to apply new concepts to breaking the throughput barrier that has in the past prevented ML2 from achieving the cost and cycle time performance necessary to become economically viable, except in rare cases. Has Maskless Lithography's (we used to call it "Direct Write Lithography") time really come? If so, what is the expected impact on the mask manufacturer and does it matter? The lithography tools used today in mask manufacturing are similar in concept to ML2 except for scale, both in throughput and feature size. These mask tools produce highly accurate lithographic images directly from electronic pattern files, perform multi-layer overlay, and mix-n-match across multiple tools, tool types and sites. Mask manufacturers are already accustomed to the ultimate low volume - one substrate per design layer. In order to achieve the economically required throughput, proposed ML2 systems eliminate or greatly reduce some of the functions that are the source of the mask writer's accuracy. Can these ML2 systems meet the demanding lithographic requirements without these functions? ML2 may eliminate the reticle but many of the processes and procedures performed today by the mask manufacturer are still required. Examples include the increasingly complex mask data preparation step and the verification performed to ensure that the pattern on the reticle is accurately representing the design intent. The error sources that are fixed on a reticle are variable with time on an ML2 system. It has been proposed that if ML2 is successful it will become uneconomical to be in the mask business - that ML2, by taking the high profit masks will take all profitability out of mask manufacturing and thereby endanger the entire semiconductor industry. Others suggest that a successful ML2 system solves the mask cost issue and thereby reduces the need and attractiveness of ML2. Are these concerns valid? In this paper we will present a perspective on maskless lithography from the considerable "direct write" experience of a mask manufacturer. We will examine the various business models proposed for ML2 insertion as well as the key technical challenges to achieving simultaneously the throughput and the lithographic quality necessary to become economically viable. We will consider the question of the economic viability of the mask industry in a post-ML2 world and will propose possible models where the mask industry can meaningfully participate.

Plasma Doping—Enabling Technology for High Dose Logic and Memory Applications

NASA Astrophysics Data System (ADS)

Miller, T.; Godet, L.; Papasouliotis, G. D.; Singh, V.

2008-11-01

As logic and memory device dimensions shrink with each generation, there are more high dose implants at lower energies. Examples include dual poly gate (also referred to as counter-doped poly), elevated source drain and contact plug implants. Plasma Doping technology throughput and dopant profile benefits at these ultra high dose and lower energy conditions have been well established [1,2,3]. For the first time a production-worthy plasma doping implanter, the VIISta PLAD tool, has been developed with unique architecture suited for precise and repeatable dopant placement. Critical elements of the architecture include pulsed DC wafer bias, closed-loop dosimetry and a uniform low energy, high density plasma source. In this paper key performance metrics such as dose uniformity, dose repeatability and dopant profile control will be presented that demonstrate the production-worthiness of the VIISta PLAD tool for several high dose applications.

Resolving Off-Nominal Situations in Schedule-Based Terminal Area Operations: Results from a Human-in-the-Loop Simulation

NASA Technical Reports Server (NTRS)

Mercer, Joey; Callantine, Todd; Martin, Lynne

2012-01-01

A recent human-in-the-loop simulation in the Airspace Operations Laboratory (AOL) at NASA's Ames Research Center investigated the robustness of Controller-Managed Spacing (CMS) operations. CMS refers to AOL-developed controller tools and procedures for enabling arrivals to conduct efficient Optimized Profile Descents with sustained high throughput. The simulation provided a rich data set for examining how a traffic management supervisor and terminal-area controller participants used the CMS tools and coordinated to respond to off-nominal events. This paper proposes quantitative measures for characterizing the participants responses. Case studies of go-around events, replicated during the simulation, provide insights into the strategies employed and the role the CMS tools played in supporting them.

Finding Groups in Gene Expression Data

PubMed Central

2005-01-01

The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, high-throughput investigations of gene activity and have thus provided the data analyst with a distinctive, high-dimensional field of study. Many questions in this field relate to finding subgroups of data profiles which are very similar. A popular type of exploratory tool for finding subgroups is cluster analysis, and many different flavors of algorithms have been used and indeed tailored for microarray data. Cluster analysis, however, implies a partitioning of the entire data set, and this does not always match the objective. Sometimes pattern discovery or bump hunting tools are more appropriate. This paper reviews these various tools for finding interesting subgroups. PMID:16046827

Real time software tools and methodologies

NASA Technical Reports Server (NTRS)

Christofferson, M. J.

1981-01-01

Real time systems are characterized by high speed processing and throughput as well as asynchronous event processing requirements. These requirements give rise to particular implementations of parallel or pipeline multitasking structures, of intertask or interprocess communications mechanisms, and finally of message (buffer) routing or switching mechanisms. These mechanisms or structures, along with the data structue, describe the essential character of the system. These common structural elements and mechanisms are identified, their implementation in the form of routines, tasks or macros - in other words, tools are formalized. The tools developed support or make available the following: reentrant task creation, generalized message routing techniques, generalized task structures/task families, standardized intertask communications mechanisms, and pipeline and parallel processing architectures in a multitasking environment. Tools development raise some interesting prospects in the areas of software instrumentation and software portability. These issues are discussed following the description of the tools themselves.

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.

Improving Data Transfer Throughput with Direct Search Optimization

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

Balaprakash, Prasanna; Morozov, Vitali; Kettimuthu, Rajkumar

2016-01-01

Improving data transfer throughput over high-speed long-distance networks has become increasingly difficult. Numerous factors such as nondeterministic congestion, dynamics of the transfer protocol, and multiuser and multitask source and destination endpoints, as well as interactions among these factors, contribute to this difficulty. A promising approach to improving throughput consists in using parallel streams at the application layer.We formulate and solve the problem of choosing the number of such streams from a mathematical optimization perspective. We propose the use of direct search methods, a class of easy-to-implement and light-weight mathematical optimization algorithms, to improve the performance of data transfers by dynamicallymore » adapting the number of parallel streams in a manner that does not require domain expertise, instrumentation, analytical models, or historic data. We apply our method to transfers performed with the GridFTP protocol, and illustrate the effectiveness of the proposed algorithm when used within Globus, a state-of-the-art data transfer tool, on productionWAN links and servers. We show that when compared to user default settings our direct search methods can achieve up to 10x performance improvement under certain conditions. We also show that our method can overcome performance degradation due to external compute and network load on source end points, a common scenario at high performance computing facilities.« less

High-Throughput In Vivo Genotoxicity Testing: An Automated Readout System for the Somatic Mutation and Recombination Test (SMART)

PubMed Central

Kwak, Jihoon; Genovesio, Auguste; Kang, Myungjoo; Hansen, Michael Adsett Edberg; Han, Sung-Jun

2015-01-01

Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods. PMID:25830368

A Triple-Fluorophore-Labeled Nucleic Acid pH Nanosensor to Investigate Non-viral Gene Delivery.

PubMed

Wilson, David R; Routkevitch, Denis; Rui, Yuan; Mosenia, Arman; Wahlin, Karl J; Quinones-Hinojosa, Alfredo; Zack, Donald J; Green, Jordan J

2017-07-05

There is a need for new tools to better quantify intracellular delivery barriers in high-throughput and high-content ways. Here, we synthesized a triple-fluorophore-labeled nucleic acid pH nanosensor for measuring intracellular pH of exogenous DNA at specific time points in a high-throughput manner by flow cytometry following non-viral transfection. By including two pH-sensitive fluorophores and one pH-insensitive fluorophore in the nanosensor, detection of pH was possible over the full physiological range. We further assessed possible correlation between intracellular pH of delivered DNA, cellular uptake of DNA, and DNA reporter gene expression at 24 hr post-transfection for poly-L-lysine and branched polyethylenimine polyplex nanoparticles. While successful transfection was shown to clearly depend on median cellular pH of delivered DNA at the cell population level, surprisingly, on an individual cell basis, there was no significant correlation between intracellular pH and transfection efficacy. To our knowledge, this is the first reported instance of high-throughput single-cell analysis between cellular uptake of DNA, intracellular pH of delivered DNA, and gene expression of the delivered DNA. Using the nanosensor, we demonstrate that the ability of polymeric nanoparticles to avoid an acidic environment is necessary, but not sufficient, for successful transfection. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

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

Novel organosilicone materials and patterning techniques for nanoimprint lithography

NASA Astrophysics Data System (ADS)

Pina, Carlos Alberto

Nanoimprint Lithography (NIL) is a high-throughput patterning technique that allows the fabrication of nanostructures with great precision. It has been listed on the International Technology Roadmap for Semiconductors (ITRS) as a candidate technology for future generation Si chip manufacturing. In nanoimprint Lithography a resist material, e.g. a thermoplastic polymer, is placed in contact with a mold and then mechanically deformed under an applied load to transfer the nano-features on the mold surface into the resist. The success of NIL relies heavily in the capability of fabricating nanostructures on different types of materials. Thus, a key factor for NIL implementation in industrial settings is the development of advanced materials suitable as the nanoimprint resist. This dissertation focuses on the engineering of new polymer materials suitable as NIL resist. A variety of silicone-based polymer precursors were synthesized and formulated for NIL applications. High throughput and high yield nanopatterning was successfully achieved. Furthermore, additional capabilities of the developed materials were explored for a range of NIL applications such as their use as flexible, UV-transparent stamps and silicon compatible etching layers. Finally, new strategies were investigated to expand the NIL potentiality. High throughput, non-residual layer imprinting was achieved with the newly developed resist materials. In addition, several strategies were designed for the precise control of nanoscale size patterned structures with multifunctional resist systems by post-imprinting modification of the pattern size. These developments provide NIL with a new set of tools for a variety of additional important applications.

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.

Field Evaluation of a High Throughput Loop Mediated Isothermal Amplification Test for the Detection of Asymptomatic Plasmodium Infections in Zanzibar

PubMed Central

Morris, Ulrika; Ding, Xavier C.; Jovel, Irina; Msellem, Mwinyi I.; Bergman, Daniel; Islam, Atiqul; Ali, Abdullah S.; Polley, Spencer; Gonzalez, Iveth J.; Mårtensson, Andreas; Björkman, Anders

2017-01-01

Background New field applicable diagnostic tools are needed for highly sensitive detection of residual malaria infections in pre-elimination settings. Field performance of a high throughput DNA extraction system for loop mediated isothermal amplification (HTP-LAMP) was therefore evaluated for detecting malaria parasites among asymptomatic individuals in Zanzibar. Methods HTP-LAMP performance was evaluated against real-time PCR on 3008 paired blood samples collected on filter papers in a community-based survey in 2015. Results The PCR and HTP-LAMP determined malaria prevalences were 1.6% (95%CI 1.3–2.4) and 0.7% (95%CI 0.4–1.1), respectively. The sensitivity of HTP-LAMP compared to PCR was 40.8% (CI95% 27.0–55.8) and the specificity was 99.9% (CI95% 99.8–100). For the PCR positive samples, there was no statistically significant difference between the geometric mean parasite densities among the HTP-LAMP positive (2.5 p/μL, range 0.2–770) and HTP-LAMP negative (1.4 p/μL, range 0.1–7) samples (p = 0.088). Two lab technicians analysed up to 282 samples per day and the HTP-LAMP method was experienced as user friendly. Conclusions Although field applicable, this high throughput format of LAMP as used here was not sensitive enough to be recommended for detection of asymptomatic low-density infections in areas like Zanzibar, approaching malaria elimination. PMID:28095434

Field Evaluation of a High Throughput Loop Mediated Isothermal Amplification Test for the Detection of Asymptomatic Plasmodium Infections in Zanzibar.

PubMed

Aydin-Schmidt, Berit; Morris, Ulrika; Ding, Xavier C; Jovel, Irina; Msellem, Mwinyi I; Bergman, Daniel; Islam, Atiqul; Ali, Abdullah S; Polley, Spencer; Gonzalez, Iveth J; Mårtensson, Andreas; Björkman, Anders

2017-01-01

New field applicable diagnostic tools are needed for highly sensitive detection of residual malaria infections in pre-elimination settings. Field performance of a high throughput DNA extraction system for loop mediated isothermal amplification (HTP-LAMP) was therefore evaluated for detecting malaria parasites among asymptomatic individuals in Zanzibar. HTP-LAMP performance was evaluated against real-time PCR on 3008 paired blood samples collected on filter papers in a community-based survey in 2015. The PCR and HTP-LAMP determined malaria prevalences were 1.6% (95%CI 1.3-2.4) and 0.7% (95%CI 0.4-1.1), respectively. The sensitivity of HTP-LAMP compared to PCR was 40.8% (CI95% 27.0-55.8) and the specificity was 99.9% (CI95% 99.8-100). For the PCR positive samples, there was no statistically significant difference between the geometric mean parasite densities among the HTP-LAMP positive (2.5 p/μL, range 0.2-770) and HTP-LAMP negative (1.4 p/μL, range 0.1-7) samples (p = 0.088). Two lab technicians analysed up to 282 samples per day and the HTP-LAMP method was experienced as user friendly. Although field applicable, this high throughput format of LAMP as used here was not sensitive enough to be recommended for detection of asymptomatic low-density infections in areas like Zanzibar, approaching malaria elimination.

Benchmarking Procedures for High-Throughput Context Specific Reconstruction Algorithms

PubMed Central

Pacheco, Maria P.; Pfau, Thomas; Sauter, Thomas

2016-01-01

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. PMID:26834640

A Fusion Protein of the p53 Transaction Domain and the p53-Binding Domain of the Oncoprotein MdmX as an Efficient System for High-Throughput Screening of MdmX Inhibitors.

PubMed

Chen, Rong; Zhou, Jingjing; Qin, Lingyun; Chen, Yao; Huang, Yongqi; Liu, Huili; Su, Zhengding

2017-06-27

In nearly half of cancers, the anticancer activity of p53 protein is often impaired by the overexpressed oncoprotein Mdm2 and its homologue, MdmX, demanding efficient therapeutics to disrupt the aberrant p53-MdmX/Mdm2 interactions to restore the p53 activity. While many potent Mdm2-specific inhibitors have already undergone clinical investigations, searching for MdmX-specific inhibitors has become very attractive, requiring a more efficient screening strategy for evaluating potential scaffolds or leads. In this work, considering that the intrinsic fluorescence residue Trp23 in the p53 transaction domain (p53p) plays an important role in determining the p53-MdmX/Mdm2 interactions, we constructed a fusion protein to utilize this intrinsic fluorescence signal to monitor high-throughput screening of a compound library. The fusion protein was composed of the p53p followed by the N-terminal domain of MdmX (N-MdmX) through a flexible amino acid linker, while the whole fusion protein contained a sole intrinsic fluorescence probe. The fusion protein was then evaluated using fluorescence spectroscopy against model compounds. Our results revealed that the variation of the fluorescence signal was highly correlated with the concentration of the ligand within 65 μM. The fusion protein was further evaluated with respect to its feasibility for use in high-throughput screening using a model compound library, including controls. We found that the imidazo-indole scaffold was a bona fide scaffold for template-based design of MdmX inhibitors. Thus, the p53p-N-MdmX fusion protein we designed provides a convenient and efficient tool for high-throughput screening of new MdmX inhibitors. The strategy described in this work should be applicable for other protein targets to accelerate drug discovery.

Human papillomavirus detection using the Abbott RealTime high-risk HPV tests compared with conventional nested PCR coupled to high-throughput sequencing of amplification products in cervical smear specimens from a Gabonese female population.

PubMed

Moussavou-Boundzanga, Pamela; Koumakpayi, Ismaël Hervé; Labouba, Ingrid; Leroy, Eric M; Belembaogo, Ernest; Berthet, Nicolas

2017-12-21

Cervical cancer is the fourth most common malignancy in women worldwide. However, screening with human papillomavirus (HPV) molecular tests holds promise for reducing cervical cancer incidence and mortality in low- and middle-income countries. The performance of the Abbott RealTime High-Risk HPV test (AbRT) was evaluated in 83 cervical smear specimens and compared with a conventional nested PCR coupled to high-throughput sequencing (HTS) to identify the amplicons. The AbRT assay detected at least one HPV genotype in 44.57% of women regardless of the grade of cervical abnormalities. Except for one case, good concordance was observed for the genotypes detected with the AbRT assay in the high-risk HPV category determined with HTS of the amplicon generated by conventional nested PCR. The AbRT test is an easy and reliable molecular tool and was as sensitive as conventional nested PCR in cervical smear specimens for detection HPVs associated with high-grade lesions. Moreover, sequencing amplicons using an HTS approach effectively identified the genotype of the hrHPV identified with the AbRT test.

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications

PubMed Central

Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui

2017-01-01

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

Deciphering the glycosaminoglycan code with the help of microarrays.

PubMed

de Paz, Jose L; Seeberger, Peter H

2008-07-01

Carbohydrate microarrays have become a powerful tool to elucidate the biological role of complex sugars. Microarrays are particularly useful for the study of glycosaminoglycans (GAGs), a key class of carbohydrates. The high-throughput chip format enables rapid screening of large numbers of potential GAG sequences produced via a complex biosynthesis while consuming very little sample. Here, we briefly highlight the most recent advances involving GAG microarrays built with synthetic or naturally derived oligosaccharides. These chips are powerful tools for characterizing GAG-protein interactions and determining structure-activity relationships for specific sequences. Thereby, they contribute to decoding the information contained in specific GAG sequences.

A computational image analysis glossary for biologists.

PubMed

Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

2012-09-01

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

Detection and Reconstruction of Circular RNAs from Transcriptomic Data.

PubMed

Zheng, Yi; Zhao, Fangqing

2018-01-01

Recent studies have shown that circular RNAs (circRNAs) are a novel class of abundant, stable, and ubiquitous noncoding RNA molecules in eukaryotic organisms. Comprehensive detection and reconstruction of circRNAs from high-throughput transcriptome data is an initial step to study their biogenesis and function. Several tools have been developed to deal with this issue, but they require many steps and are difficult to use. To solve this problem, we provide a protocol for researchers to detect and reconstruct circRNA by employing CIRI2, CIRI-AS, and CIRI-full. This protocol can not only simplify the usage of above tools but also integrate their results.

Addiction Science: Uncovering Neurobiological Complexity

PubMed Central

Volkow, N. D.; Baler, R. D.

2013-01-01

Until very recently addiction-research was limited by existing tools and strategies that were inadequate for studying the inherent complexity at each of the different phenomenological levels. However, powerful new tools (e.g., optogenetics and designer drug receptors) and high throughput protocols are starting to give researchers the potential to systematically interrogate “all” genes, epigenetic marks, and neuronal circuits. These advances, combined with imaging technologies (both for preclinical and clinical studies) and a paradigm shift towards open access have spurred an unlimited growth of datasets transforming the way we investigate the neurobiology of substance use disorders (SUD) and the factors that modulate risk and resilience. PMID:23688927

GPURFSCREEN: a GPU based virtual screening tool using random forest classifier.

PubMed

Jayaraj, P B; Ajay, Mathias K; Nufail, M; Gopakumar, G; Jaleel, U C A

2016-01-01

In-silico methods are an integral part of modern drug discovery paradigm. Virtual screening, an in-silico method, is used to refine data models and reduce the chemical space on which wet lab experiments need to be performed. Virtual screening of a ligand data model requires large scale computations, making it a highly time consuming task. This process can be speeded up by implementing parallelized algorithms on a Graphical Processing Unit (GPU). Random Forest is a robust classification algorithm that can be employed in the virtual screening. A ligand based virtual screening tool (GPURFSCREEN) that uses random forests on GPU systems has been proposed and evaluated in this paper. This tool produces optimized results at a lower execution time for large bioassay data sets. The quality of results produced by our tool on GPU is same as that on a regular serial environment. Considering the magnitude of data to be screened, the parallelized virtual screening has a significantly lower running time at high throughput. The proposed parallel tool outperforms its serial counterpart by successfully screening billions of molecules in training and prediction phases.

Ranking the in vivo toxicity of nanomaterials in Drosophila melanogaster

NASA Astrophysics Data System (ADS)

Vecchio, G.; Galeone, A.; Malvindi, M. A.; Cingolani, R.; Pompa, P. P.

2013-09-01

In this work, we propose a quantitative assessment of nanoparticles toxicity in vivo. We show a quantitative ranking of several types of nanoparticles (AuNPs, AgNPs, cadmium-based QDs, cadmium-free QDs, and iron oxide NPs, with different coating and/or surface chemistries), providing a categorization of their toxicity outcomes. This strategy may offer an innovative high-throughput screening tool of nanomaterials, of potential and broad interest to the nanoscience community.

Nanoindentation testing as a powerful screening tool for assessing phase stability of nanocrystalline high-entropy alloys

DOE PAGES

Maier-Kiener, Verena; Schuh, Benjamin; George, Easo P.; ...

2016-11-19

The equiatomic high-entropy alloy (HEA), CrMnFeCoNi, has recently been shown to be microstructurally unstable, resulting in a multi-phase microstructure after intermediate-temperature annealing treatments. The decomposition occurs rapidly in the nanocrystalline (NC) state and after longer annealing times in coarse-grained states. To characterize the mechanical properties of differently annealed NC states containing multiple phases, nanoindentation was used in this paper. The results revealed besides drastic changes in hardness, also for the first time significant changes in the Young's modulus and strain rate sensitivity. Finally, nanoindentation of NC HEAs is, therefore, a useful complementary screening tool with high potential as a highmore » throughput approach to detect phase decomposition, which can also be used to qualitatively predict the long-term stability of single-phase HEAs.« less

New Funding Opportunity from the Human Biomolecular Atlas Program (HuBMAP)! | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) aims to develop a framework for functional mapping the human body with cellular resolution to enhance our understanding of cellular organization-function. HuBMAP will accelerate the development of the next generation of tools and techniques to generate 3D tissue maps using validated high-content, high-throughput imaging and omics assays, and establish an open data platform for integrating, visualizing data to build multi-dimensional maps.

Human Leukocyte Antigen Typing Using a Knowledge Base Coupled with a High-Throughput Oligonucleotide Probe Array Analysis

PubMed Central

Zhang, Guang Lan; Keskin, Derin B.; Lin, Hsin-Nan; Lin, Hong Huang; DeLuca, David S.; Leppanen, Scott; Milford, Edgar L.; Reinherz, Ellis L.; Brusic, Vladimir

2014-01-01

Human leukocyte antigens (HLA) are important biomarkers because multiple diseases, drug toxicity, and vaccine responses reveal strong HLA associations. Current clinical HLA typing is an elimination process requiring serial testing. We present an alternative in situ synthesized DNA-based microarray method that contains hundreds of thousands of probes representing a complete overlapping set covering 1,610 clinically relevant HLA class I alleles accompanied by computational tools for assigning HLA type to 4-digit resolution. Our proof-of-concept experiment included 21 blood samples, 18 cell lines, and multiple controls. The method is accurate, robust, and amenable to automation. Typing errors were restricted to homozygous samples or those with very closely related alleles from the same locus, but readily resolved by targeted DNA sequencing validation of flagged samples. High-throughput HLA typing technologies that are effective, yet inexpensive, can be used to analyze the world’s populations, benefiting both global public health and personalized health care. PMID:25505899

Microfluidics-assisted in vitro drug screening and carrier production

PubMed Central

Tsui, Jonathan H.; Lee, Woohyuk; Pun, Suzie H.; Kim, Jungkyu; Kim, Deok-Ho

2013-01-01

Microfluidic platforms provide several unique advantages for drug development. In the production of drug carriers, physical properties such as size and shape, and chemical properties such as drug composition and pharmacokinetic parameters, can be modified simply and effectively by tuning the flow rate and geometries. Large numbers of carriers can then be fabricated with minimal effort and with little to no batch-to-batch variation. Additionally, cell or tissue culture models in microfluidic systems can be used as in vitro drug screening tools. Compared to in vivo animal models, microfluidic drug screening platforms allow for high-throughput and reproducible screening at a significantly lower cost, and when combined with current advances in tissue engineering, are also capable of mimicking native tissues. In this review, various microfluidic platforms for drug and gene carrier fabrication are reviewed to provide guidelines for designing appropriate carriers. In vitro microfluidic drug screening platforms designed for high-throughput analysis and replication of in vivo conditions are also reviewed to highlight future directions for drug research and development. PMID:23856409

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Sophia: A Expedient UMLS Concept Extraction Annotator.

PubMed

Divita, Guy; Zeng, Qing T; Gundlapalli, Adi V; Duvall, Scott; Nebeker, Jonathan; Samore, Matthew H

2014-01-01

An opportunity exists for meaningful concept extraction and indexing from large corpora of clinical notes in the Veterans Affairs (VA) electronic medical record. Currently available tools such as MetaMap, cTAKES and HITex do not scale up to address this big data need. Sophia, a rapid UMLS concept extraction annotator was developed to fulfill a mandate and address extraction where high throughput is needed while preserving performance. We report on the development, testing and benchmarking of Sophia against MetaMap and cTAKEs. Sophia demonstrated improved performance on recall as compared to cTAKES and MetaMap (0.71 vs 0.66 and 0.38). The overall f-score was similar to cTAKES and an improvement over MetaMap (0.53 vs 0.57 and 0.43). With regard to speed of processing records, we noted Sophia to be several fold faster than cTAKES and the scaled-out MetaMap service. Sophia offers a viable alternative for high-throughput information extraction tasks.

NMRbot: Python scripts enable high-throughput data collection on current Bruker BioSpin NMR spectrometers.

PubMed

Clos, Lawrence J; Jofre, M Fransisca; Ellinger, James J; Westler, William M; Markley, John L

2013-06-01

To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on recent advances in Bruker BioSpin NMR spectrometer hardware and software. Given the daunting challenge for non-NMR experts to collect quality spectra, our goal was to increase user accessibility, provide customized functionality, and improve the consistency and reliability of resultant data. This methodology, NMRbot, is encoded in a set of scripts written in the Python programming language accessible within the Bruker BioSpin TopSpin ™ software. NMRbot improves automated data acquisition and offers novel tools for use in optimizing experimental parameters on the fly. This automated procedure has been successfully implemented for investigations in metabolomics, small-molecule library profiling, and protein-ligand titrations on four Bruker BioSpin NMR spectrometers at the National Magnetic Resonance Facility at Madison. The investigators reported benefits from ease of setup, improved spectral quality, convenient customizations, and overall time savings.

High-throughput microscopy must re-invent the microscope rather than speed up its functions

PubMed Central

Oheim, M

2007-01-01

Knowledge gained from the revolutions in genomics and proteomics has helped to identify many of the key molecules involved in cellular signalling. Researchers, both in academia and in the pharmaceutical industry, now screen, at a sub-cellular level, where and when these proteins interact. Fluorescence imaging and molecular labelling combine to provide a powerful tool for real-time functional biochemistry with molecular resolution. However, they traditionally have been work-intensive, required trained personnel, and suffered from low through-put due to sample preparation, loading and handling. The need for speeding up microscopy is apparent from the tremendous complexity of cellular signalling pathways, the inherent biological variability, as well as the possibility that the same molecule plays different roles in different sub-cellular compartments. Research institutes and companies have teamed up to develop imaging cytometers of ever-increasing complexity. However, to truly go high-speed, sub-cellular imaging must free itself from the rigid framework of current microscopes. PMID:17603553

ImmuneDB: a system for the analysis and exploration of high-throughput adaptive immune receptor sequencing data.

PubMed

Rosenfeld, Aaron M; Meng, Wenzhao; Luning Prak, Eline T; Hershberg, Uri

2017-01-15

As high-throughput sequencing of B cells becomes more common, the need for tools to analyze the large quantity of data also increases. This article introduces ImmuneDB, a system for analyzing vast amounts of heavy chain variable region sequences and exploring the resulting data. It can take as input raw FASTA/FASTQ data, identify genes, determine clones, construct lineages, as well as provide information such as selection pressure and mutation analysis. It uses an industry leading database, MySQL, to provide fast analysis and avoid the complexities of using error prone flat-files. ImmuneDB is freely available at http://immunedb.comA demo of the ImmuneDB web interface is available at: http://immunedb.com/demo CONTACT: Uh25@drexel.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A New Versatile Microarray-based Method for High Throughput Screening of Carbohydrate-active Enzymes*

PubMed Central

Vidal-Melgosa, Silvia; Pedersen, Henriette L.; Schückel, Julia; Arnal, Grégory; Dumon, Claire; Amby, Daniel B.; Monrad, Rune Nygaard; Westereng, Bjørge; Willats, William G. T.

2015-01-01

Carbohydrate-active enzymes have multiple biological roles and industrial applications. Advances in genome and transcriptome sequencing together with associated bioinformatics tools have identified vast numbers of putative carbohydrate-degrading and -modifying enzymes including glycoside hydrolases and lytic polysaccharide monooxygenases. However, there is a paucity of methods for rapidly screening the activities of these enzymes. By combining the multiplexing capacity of carbohydrate microarrays with the specificity of molecular probes, we have developed a sensitive, high throughput, and versatile semiquantitative enzyme screening technique that requires low amounts of enzyme and substrate. The method can be used to assess the activities of single enzymes, enzyme mixtures, and crude culture broths against single substrates, substrate mixtures, and biomass samples. Moreover, we show that the technique can be used to analyze both endo-acting and exo-acting glycoside hydrolases, polysaccharide lyases, carbohydrate esterases, and lytic polysaccharide monooxygenases. We demonstrate the potential of the technique by identifying the substrate specificities of purified uncharacterized enzymes and by screening enzyme activities from fungal culture broths. PMID:25657012

A High-Throughput Arabidopsis Reverse Genetics System

PubMed Central

Sessions, Allen; Burke, Ellen; Presting, Gernot; Aux, George; McElver, John; Patton, David; Dietrich, Bob; Ho, Patrick; Bacwaden, Johana; Ko, Cynthia; Clarke, Joseph D.; Cotton, David; Bullis, David; Snell, Jennifer; Miguel, Trini; Hutchison, Don; Kimmerly, Bill; Mitzel, Theresa; Katagiri, Fumiaki; Glazebrook, Jane; Law, Marc; Goff, Stephen A.

2002-01-01

A collection of Arabidopsis lines with T-DNA insertions in known sites was generated to increase the efficiency of functional genomics. A high-throughput modified thermal asymetric interlaced (TAIL)-PCR protocol was developed and used to amplify DNA fragments flanking the T-DNA left borders from ∼100,000 transformed lines. A total of 85,108 TAIL-PCR products from 52,964 T-DNA lines were sequenced and compared with the Arabidopsis genome to determine the positions of T-DNAs in each line. Predicted T-DNA insertion sites, when mapped, showed a bias against predicted coding sequences. Predicted insertion mutations in genes of interest can be identified using Arabidopsis Gene Index name searches or by BLAST (Basic Local Alignment Search Tool) search. Insertions can be confirmed by simple PCR assays on individual lines. Predicted insertions were confirmed in 257 of 340 lines tested (76%). This resource has been named SAIL (Syngenta Arabidopsis Insertion Library) and is available to the scientific community at www.tmri.org. PMID:12468722

High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells.

PubMed

Zhou, Yuexin; Zhu, Shiyou; Cai, Changzu; Yuan, Pengfei; Li, Chunmei; Huang, Yanyi; Wei, Wensheng

2014-05-22

Targeted genome editing technologies are powerful tools for studying biology and disease, and have a broad range of research applications. In contrast to the rapid development of toolkits to manipulate individual genes, large-scale screening methods based on the complete loss of gene expression are only now beginning to be developed. Here we report the development of a focused CRISPR/Cas-based (clustered regularly interspaced short palindromic repeats/CRISPR-associated) lentiviral library in human cells and a method of gene identification based on functional screening and high-throughput sequencing analysis. Using knockout library screens, we successfully identified the host genes essential for the intoxication of cells by anthrax and diphtheria toxins, which were confirmed by functional validation. The broad application of this powerful genetic screening strategy will not only facilitate the rapid identification of genes important for bacterial toxicity but will also enable the discovery of genes that participate in other biological processes.

Real-time reliable determination of binding kinetics of DNA hybridization using a multi-channel graphene biosensor

NASA Astrophysics Data System (ADS)

Xu, Shicai; Zhan, Jian; Man, Baoyuan; Jiang, Shouzhen; Yue, Weiwei; Gao, Shoubao; Guo, Chengang; Liu, Hanping; Li, Zhenhua; Wang, Jihua; Zhou, Yaoqi

2017-03-01

Reliable determination of binding kinetics and affinity of DNA hybridization and single-base mismatches plays an essential role in systems biology, personalized and precision medicine. The standard tools are optical-based sensors that are difficult to operate in low cost and to miniaturize for high-throughput measurement. Biosensors based on nanowire field-effect transistors have been developed, but reliable and cost-effective fabrication remains a challenge. Here, we demonstrate that a graphene single-crystal domain patterned into multiple channels can measure time- and concentration-dependent DNA hybridization kinetics and affinity reliably and sensitively, with a detection limit of 10 pM for DNA. It can distinguish single-base mutations quantitatively in real time. An analytical model is developed to estimate probe density, efficiency of hybridization and the maximum sensor response. The results suggest a promising future for cost-effective, high-throughput screening of drug candidates, genetic variations and disease biomarkers by using an integrated, miniaturized, all-electrical multiplexed, graphene-based DNA array.

Relax with CouchDB - Into the non-relational DBMS era of Bioinformatics

PubMed Central

Manyam, Ganiraju; Payton, Michelle A.; Roth, Jack A.; Abruzzo, Lynne V.; Coombes, Kevin R.

2012-01-01

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. PMID:22609849