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

PubMed

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

2010-04-05

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

Translational bioinformatics in the cloud: an affordable alternative

PubMed Central

2010-01-01

With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and informatics are becoming vital considerations in genomic medicine. Although cloud computing technology is being heralded as a key enabling technology for the future of genomic research, available case studies are limited to applications in the domain of high-throughput sequence data analysis. The goal of this study was to evaluate the computational and economic characteristics of cloud computing in performing a large-scale data integration and analysis representative of research problems in genomic medicine. We find that the cloud-based analysis compares favorably in both performance and cost in comparison to a local computational cluster, suggesting that cloud computing technologies might be a viable resource for facilitating large-scale translational research in genomic medicine. PMID:20691073

Evaluating and Refining High Throughput Tools for Toxicokinetics

EPA Science Inventory

This poster summarizes efforts of the Chemical Safety for Sustainability's Rapid Exposure and Dosimetry (RED) team to facilitate the development and refinement of toxicokinetics (TK) tools to be used in conjunction with the high throughput toxicity testing data generated as a par...

Raman-Activated Droplet Sorting (RADS) for Label-Free High-Throughput Screening of Microalgal Single-Cells.

PubMed

Wang, Xixian; Ren, Lihui; Su, Yetian; Ji, Yuetong; Liu, Yaoping; Li, Chunyu; Li, Xunrong; Zhang, Yi; Wang, Wei; Hu, Qiang; Han, Danxiang; Xu, Jian; Ma, Bo

2017-11-21

Raman-activated cell sorting (RACS) has attracted increasing interest, yet throughput remains one major factor limiting its broader application. Here we present an integrated Raman-activated droplet sorting (RADS) microfluidic system for functional screening of live cells in a label-free and high-throughput manner, by employing AXT-synthetic industrial microalga Haematococcus pluvialis (H. pluvialis) as a model. Raman microspectroscopy analysis of individual cells is carried out prior to their microdroplet encapsulation, which is then directly coupled to DEP-based droplet sorting. To validate the system, H. pluvialis cells containing different levels of AXT were mixed and underwent RADS. Those AXT-hyperproducing cells were sorted with an accuracy of 98.3%, an enrichment ratio of eight folds, and a throughput of ∼260 cells/min. Of the RADS-sorted cells, 92.7% remained alive and able to proliferate, which is equivalent to the unsorted cells. Thus, the RADS achieves a much higher throughput than existing RACS systems, preserves the vitality of cells, and facilitates seamless coupling with downstream manipulations such as single-cell sequencing and cultivation.

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

PubMed

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

2015-01-01

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

Microfluidics and microbial engineering.

PubMed

Kou, Songzi; Cheng, Danhui; Sun, Fei; Hsing, I-Ming

2016-02-07

The combination of microbial engineering and microfluidics is synergistic in nature. For example, microfluidics is benefiting from the outcome of microbial engineering and many reported point-of-care microfluidic devices employ engineered microbes as functional parts for the microsystems. In addition, microbial engineering is facilitated by various microfluidic techniques, due to their inherent strength in high-throughput screening and miniaturization. In this review article, we firstly examine the applications of engineered microbes for toxicity detection, biosensing, and motion generation in microfluidic platforms. Secondly, we look into how microfluidic technologies facilitate the upstream and downstream processes of microbial engineering, including DNA recombination, transformation, target microbe selection, mutant characterization, and microbial function analysis. Thirdly, we highlight an emerging concept in microbial engineering, namely, microbial consortium engineering, where the behavior of a multicultural microbial community rather than that of a single cell/species is delineated. Integrating the disciplines of microfluidics and microbial engineering opens up many new opportunities, for example in diagnostics, engineering of microbial motors, development of portable devices for genetics, high throughput characterization of genetic mutants, isolation and identification of rare/unculturable microbial species, single-cell analysis with high spatio-temporal resolution, and exploration of natural microbial communities.

Estimating Toxicity Pathway Activating Doses for High Throughput Chemical Risk Assessments

EPA Science Inventory

Estimating a Toxicity Pathway Activating Dose (TPAD) from in vitro assays as an analog to a reference dose (RfD) derived from in vivo toxicity tests would facilitate high throughput risk assessments of thousands of data-poor environmental chemicals. Estimating a TPAD requires def...

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...

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

PubMed Central

2014-01-01

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

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

PubMed

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

2014-03-05

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

Evaluation of In Vitro Biotransformation Using HepaRG Cells to Improve High-Throughput Chemical Hazard Prediction: A Toxicogenomics Analysis (SOT)

EPA Science Inventory

The US EPA’s ToxCast program has generated a wealth of data in >600 in vitro assayson a library of 1060 environmentally relevant chemicals and failed pharmaceuticals to facilitate hazard identification. An inherent criticism of many in vitro-based strategies is the inability of a...

Repurposing a Benchtop Centrifuge for High-Throughput Single-Molecule Force Spectroscopy.

PubMed

Yang, Darren; Wong, Wesley P

2018-01-01

We present high-throughput single-molecule manipulation using a benchtop centrifuge, overcoming limitations common in other single-molecule approaches such as high cost, low throughput, technical difficulty, and strict infrastructure requirements. An inexpensive and compact Centrifuge Force Microscope (CFM) adapted to a commercial centrifuge enables use by nonspecialists, and integration with DNA nanoswitches facilitates both reliable measurements and repeated molecular interrogation. Here, we provide detailed protocols for constructing the CFM, creating DNA nanoswitch samples, and carrying out single-molecule force measurements.

Strategies for cell manipulation and skeletal tissue engineering using high-throughput polymer blend formulation and microarray techniques.

PubMed

Khan, Ferdous; Tare, Rahul S; Kanczler, Janos M; Oreffo, Richard O C; Bradley, Mark

2010-03-01

A combination of high-throughput material formulation and microarray techniques were synergistically applied for the efficient analysis of the biological functionality of 135 binary polymer blends. This allowed the identification of cell-compatible biopolymers permissive for human skeletal stem cell growth in both in vitro and in vivo applications. The blended polymeric materials were developed from commercially available, inexpensive and well characterised biodegradable polymers, which on their own lacked both the structural requirements of a scaffold material and, critically, the ability to facilitate cell growth. Blends identified here proved excellent templates for cell attachment, and in addition, a number of blends displayed remarkable bone-like architecture and facilitated bone regeneration by providing 3D biomimetic scaffolds for skeletal cell growth and osteogenic differentiation. This study demonstrates a unique strategy to generate and identify innovative materials with widespread application in cell biology as well as offering a new reparative platform strategy applicable to skeletal tissues. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-10-01

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

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.

An Automated, High-Throughput System for GISAXS and GIWAXS Measurements of Thin Films

NASA Astrophysics Data System (ADS)

Schaible, Eric; Jimenez, Jessica; Church, Matthew; Lim, Eunhee; Stewart, Polite; Hexemer, Alexander

Grazing incidence small-angle X-ray scattering (GISAXS) and grazing incidence wide-angle X-ray scattering (GIWAXS) are important techniques for characterizing thin films. In order to meet rapidly increasing demand, the SAXSWAXS beamline at the Advanced Light Source (beamline 7.3.3) has implemented a fully automated, high-throughput system to conduct SAXS, GISAXS and GIWAXS measurements. An automated robot arm transfers samples from a holding tray to a measurement stage. Intelligent software aligns each sample in turn, and measures each according to user-defined specifications. Users mail in trays of samples on individually barcoded pucks, and can download and view their data remotely. Data will be pipelined to the NERSC supercomputing facility, and will be available to users via a web portal that facilitates highly parallelized analysis.

Simultaneous UPLC-MS/MS analysis of native catechins and procyanidins and their microbial metabolites in intestinal contents and tissues of male Wistar Furth inbred rats.

PubMed

Goodrich, Katheryn M; Neilson, Andrew P

2014-05-01

Procyanidins have been extensively investigated for their potential health protective activities. However, the potential bioactivities of procyanidins are limited by their poor bioavailability. The majority of the ingested dose remains unabsorbed and reaches the colon where extensive microbial metabolism occurs. Most existing analytical methods measure either native compounds (catechins and procyanidins), or their microbial metabolites. The objectives of this study were to develop a high-throughput extraction and UPLC-MS/MS method for simultaneous measurement of both native procyanidins and their metabolites, facilitating high-throughput analysis of native and metabolite profiles in various regions of the colon. The present UPLC-MS/MS method facilitates simultaneous resolution and detection of authentic standards of 14 native catechin monomers and procyanidins, as well as 24 microbial metabolites. Detection and resolution of an additional 3 procyanidin dimers and 10 metabolites for which standards were not available was achieved. Elution and adequate resolution of both native compounds and metabolites were achieved within 10min. The intraday repeatability for native compounds was between 1.1 and 16.5%, and the interday repeatability for native compounds was between 2.2 and 25%. Intraday and interday repeatability for metabolites was between 0.6 and 24.1% and 1 and 23.9%, respectively. Observed lower limits of quantification for native compounds were ∼9-350fmol on-column, and for the microbial metabolites were ∼0.8-12,000fmol on-column. Observed lower limits of detection for native compounds were ∼4.5-190fmol on-column, and for metabolites were 0.304-6020fmol on-column. For native monomers and procyanidins, extraction recoveries ranged from 38 to 102%. Extraction recoveries for the 9 microbial metabolites tested ranged from 41 to 95%. Data from tissue analysis of rats gavaged with grape seed extract indicate fairly high accumulation of native compounds, primarily monomers and dimers, in the cecum and colon. Metabolite data indicate the progressive nature of microbial metabolism as the digesta moves through the lower GI tract. This method facilitates the high-throughput, sensitive, and simultaneous analysis of both native compounds and their microbial metabolites in biological samples and provides a more efficient means of extraction and analysis than previous methods. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

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.

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

PubMed Central

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

2015-01-01

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

Next-Generation High-Throughput Functional Annotation of Microbial Genomes.

PubMed

Baric, Ralph S; Crosson, Sean; Damania, Blossom; Miller, Samuel I; Rubin, Eric J

2016-10-04

Host infection by microbial pathogens cues global changes in microbial and host cell biology that facilitate microbial replication and disease. The complete maps of thousands of bacterial and viral genomes have recently been defined; however, the rate at which physiological or biochemical functions have been assigned to genes has greatly lagged. The National Institute of Allergy and Infectious Diseases (NIAID) addressed this gap by creating functional genomics centers dedicated to developing high-throughput approaches to assign gene function. These centers require broad-based and collaborative research programs to generate and integrate diverse data to achieve a comprehensive understanding of microbial pathogenesis. High-throughput functional genomics can lead to new therapeutics and better understanding of the next generation of emerging pathogens by rapidly defining new general mechanisms by which organisms cause disease and replicate in host tissues and by facilitating the rate at which functional data reach the scientific community. Copyright © 2016 Baric et al.

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

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

PubMed Central

2011-01-01

The increasing popularity of systems-based approaches to plant research has resulted in a demand for high throughput (HTP) methods to be developed. RNA extraction from multiple samples in an experiment is a significant bottleneck in performing systems-level genomic studies. Therefore we have established a high throughput method of RNA extraction from Arabidopsis thaliana to facilitate gene expression studies in this widely used plant model. We present optimised manual and automated protocols for the extraction of total RNA from 9-day-old Arabidopsis seedlings in a 96 well plate format using silica membrane-based methodology. Consistent and reproducible yields of high quality RNA are isolated averaging 8.9 μg total RNA per sample (~20 mg plant tissue). The purified RNA is suitable for subsequent qPCR analysis of the expression of over 500 genes in triplicate from each sample. Using the automated procedure, 192 samples (2 × 96 well plates) can easily be fully processed (samples homogenised, RNA purified and quantified) in less than half a day. Additionally we demonstrate that plant samples can be stored in RNAlater at -20°C (but not 4°C) for 10 months prior to extraction with no significant effect on RNA yield or quality. Additionally, disrupted samples can be stored in the lysis buffer at -20°C for at least 6 months prior to completion of the extraction procedure providing a flexible sampling and storage scheme to facilitate complex time series experiments. PMID:22136293

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

PubMed

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

2011-12-02

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

Re-engineering adenovirus vector systems to enable high-throughput analyses of gene function.

PubMed

Stanton, Richard J; McSharry, Brian P; Armstrong, Melanie; Tomasec, Peter; Wilkinson, Gavin W G

2008-12-01

With the enhanced capacity of bioinformatics to interrogate extensive banks of sequence data, more efficient technologies are needed to test gene function predictions. Replication-deficient recombinant adenovirus (Ad) vectors are widely used in expression analysis since they provide for extremely efficient expression of transgenes in a wide range of cell types. To facilitate rapid, high-throughput generation of recombinant viruses, we have re-engineered an adenovirus vector (designated AdZ) to allow single-step, directional gene insertion using recombineering technology. Recombineering allows for direct insertion into the Ad vector of PCR products, synthesized sequences, or oligonucleotides encoding shRNAs without requirement for a transfer vector Vectors were optimized for high-throughput applications by making them "self-excising" through incorporating the I-SceI homing endonuclease into the vector removing the need to linearize vectors prior to transfection into packaging cells. AdZ vectors allow genes to be expressed in their native form or with strep, V5, or GFP tags. Insertion of tetracycline operators downstream of the human cytomegalovirus major immediate early (HCMV MIE) promoter permits silencing of transgenes in helper cells expressing the tet repressor thus making the vector compatible with the cloning of toxic gene products. The AdZ vector system is robust, straightforward, and suited to both sporadic and high-throughput applications.

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

Annotate-it: a Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease

PubMed Central

2012-01-01

The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org. PMID:23013645

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

Transfer, imaging, and analysis plate for facile handling of 384 hanging drop 3D tissue spheroids.

PubMed

Cavnar, Stephen P; Salomonsson, Emma; Luker, Kathryn E; Luker, Gary D; Takayama, Shuichi

2014-04-01

Three-dimensional culture systems bridge the experimental gap between in vivo and in vitro physiology. However, nonstandardized formation and limited downstream adaptability of 3D cultures have hindered mainstream adoption of these systems for biological applications, especially for low- and moderate-throughput assays commonly used in biomedical research. Here we build on our recent development of a 384-well hanging drop plate for spheroid culture to design a complementary spheroid transfer and imaging (TRIM) plate. The low-aspect ratio wells of the TRIM plate facilitated high-fidelity, user-independent, contact-based collection of hanging drop spheroids. Using the TRIM plate, we demonstrated several downstream analyses, including bulk tissue collection for flow cytometry, high-resolution low working-distance immersion imaging, and timely reagent delivery for enzymatic studies. Low working-distance multiphoton imaging revealed a cell type-dependent, macroscopic spheroid structure. Unlike ovarian cancer spheroids, which formed loose, disk-shaped spheroids, human mammary fibroblasts formed tight, spherical, and nutrient-limited spheroids. Beyond the applications we describe here, we expect the hanging drop spheroid plate and complementary TRIM plate to facilitate analyses of spheroids across the spectrum of throughput, particularly for bulk collection of spheroids and high-content imaging.

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.

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

PubMed Central

2012-01-01

Background A major challenge in the identification and development of superior feedstocks for the production of second generation biofuels is the rapid assessment of biomass composition in a large number of samples. Currently, highly accurate and precise robotic analysis systems are available for the evaluation of biomass composition, on a large number of samples, with a variety of pretreatments. However, the lack of an inexpensive and high-throughput process for large scale sampling of biomass resources is still an important limiting factor. Our goal was to develop a simple mechanical maize stalk core sampling device that can be utilized to collect uniform samples of a dimension compatible with robotic processing and analysis, while allowing the collection of hundreds to thousands of samples per day. Results We have developed a core sampling device (CSD) to collect maize stalk samples compatible with robotic processing and analysis. The CSD facilitates the collection of thousands of uniform tissue cores consistent with high-throughput analysis required for breeding, genetics, and production studies. With a single CSD operated by one person with minimal training, more than 1,000 biomass samples were obtained in an eight-hour period. One of the main advantages of using cores is the high level of homogeneity of the samples obtained and the minimal opportunity for sample contamination. In addition, the samples obtained with the CSD can be placed directly into a bath of ice, dry ice, or liquid nitrogen maintaining the composition of the biomass sample for relatively long periods of time. Conclusions The CSD has been demonstrated to successfully produce homogeneous stalk core samples in a repeatable manner with a throughput substantially superior to the currently available sampling methods. Given the variety of maize developmental stages and the diversity of stalk diameter evaluated, it is expected that the CSD will have utility for other bioenergy crops as well. PMID:22548834

High-Throughput Functional Validation of Progression Drivers in Lung Adenocarcinoma

DTIC Science & Technology

2013-09-01

2) a novel molecular barcoding approach that facilitates cost- effective detection of driver events following in vitro and in vivo functional screens...aberration construction pipeline, which we named High-Throughput 3 Mutagenesis and Molecular Barcoding (HiTMMoB; Fig.1). We have therefore been able...lentiviral vector specially constructed for this project. This vector is compatible with our flexible molecular barcoding technology (Fig. 1), thus each

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.

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

PubMed

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

2011-12-15

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

Financial analysis for the infusion alliance.

PubMed

Perucca, Roxanne

2010-01-01

Providing high-quality, cost-efficient care is a major strategic initiative of every health care organization. Today's health care environment is transparent; very competitive; and focused upon providing exceptional service, safety, and quality. Establishing an infusion alliance facilitates the achievement of organizational strategic initiatives, that is, increases patient throughput, decreases length of stay, prevents the occurrence of infusion-related complications, enhances customer satisfaction, and provides greater cost-efficiency. This article will discuss how to develop a financial analysis that promotes value and enhances the financial outcomes of an infusion alliance.

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.

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

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

PubMed Central

Dutta, Sanjib; Koide, Akiko; Koide, Shohei

2008-01-01

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

Transfer, Imaging, and Analysis Plate for Facile Handling of 384 Hanging Drop 3D Tissue Spheroids

PubMed Central

Cavnar, Stephen P.; Salomonsson, Emma; Luker, Kathryn E.; Luker, Gary D.; Takayama, Shuichi

2014-01-01

Three-dimensional culture systems bridge the experimental gap between in vivo and in vitro physiology. However, nonstandardized formation and limited downstream adaptability of 3D cultures have hindered mainstream adoption of these systems for biological applications, especially for low- and moderate-throughput assays commonly used in biomedical research. Here we build on our recent development of a 384-well hanging drop plate for spheroid culture to design a complementary spheroid transfer and imaging (TRIM) plate. The low-aspect ratio wells of the TRIM plate facilitated highfidelity, user-independent, contact-based collection of hanging drop spheroids. Using the TRIM plate, we demonstrated several downstream analyses, including bulk tissue collection for flow cytometry, high-resolution low working-distance immersion imaging, and timely reagent delivery for enzymatic studies. Low working-distance multiphoton imaging revealed a cell type–dependent, macroscopic spheroid structure. Unlike ovarian cancer spheroids, which formed loose, disk-shaped spheroids, human mammary fibroblasts formed tight, spherical, and nutrient-limited spheroids. Beyond the applications we describe here, we expect the hanging drop spheroid plate and complementary TRIM plate to facilitate analyses of spheroids across the spectrum of throughput, particularly for bulk collection of spheroids and high-content imaging. PMID:24051516

A new arenavirus in a cluster of fatal transplant-associated diseases.

PubMed

Palacios, Gustavo; Druce, Julian; Du, Lei; Tran, Thomas; Birch, Chris; Briese, Thomas; Conlan, Sean; Quan, Phenix-Lan; Hui, Jeffrey; Marshall, John; Simons, Jan Fredrik; Egholm, Michael; Paddock, Christopher D; Shieh, Wun-Ju; Goldsmith, Cynthia S; Zaki, Sherif R; Catton, Mike; Lipkin, W Ian

2008-03-06

Three patients who received visceral-organ transplants from a single donor on the same day died of a febrile illness 4 to 6 weeks after transplantation. Culture, polymerase-chain-reaction (PCR) and serologic assays, and oligonucleotide microarray analysis for a wide range of infectious agents were not informative. We evaluated RNA obtained from the liver and kidney transplant recipients. Unbiased high-throughput sequencing was used to identify microbial sequences not found by means of other methods. The specificity of sequences for a new candidate pathogen was confirmed by means of culture and by means of PCR, immunohistochemical, and serologic analyses. High-throughput sequencing yielded 103,632 sequences, of which 14 represented an Old World arenavirus. Additional sequence analysis showed that this new arenavirus was related to lymphocytic choriomeningitis viruses. Specific PCR assays based on a unique sequence confirmed the presence of the virus in the kidneys, liver, blood, and cerebrospinal fluid of the recipients. Immunohistochemical analysis revealed arenavirus antigen in the liver and kidney transplants in the recipients. IgM and IgG antiviral antibodies were detected in the serum of the donor. Seroconversion was evident in serum specimens obtained from one recipient at two time points. Unbiased high-throughput sequencing is a powerful tool for the discovery of pathogens. The use of this method during an outbreak of disease facilitated the identification of a new arenavirus transmitted through solid-organ transplantation. Copyright 2008 Massachusetts Medical Society.

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.

Proteomic Analysis of Metabolic Responses to Biofuels and Chemicals in Photosynthetic Cyanobacteria.

PubMed

Sun, T; Chen, L; Zhang, W

2017-01-01

Recent progresses in various "omics" technologies have enabled quantitative measurements of biological molecules in a high-throughput manner. Among them, high-throughput proteomics is a rapidly advancing field that offers a new means to quantify metabolic changes at protein level, which has significantly facilitated our understanding of cellular process, such as protein synthesis, posttranslational modifications, and degradation in responding to environmental perturbations. Cyanobacteria are autotrophic prokaryotes that can perform oxygenic photosynthesis and have recently attracted significant attentions as one promising alternative to traditionally biomass-based "microbial cell factories" to produce green fuels and chemicals. However, early studies have shown that the low tolerance to toxic biofuels and chemicals represented one major hurdle for further improving productivity of the cyanobacterial production systems. To address the issue, metabolic responses and their regulation of cyanobacterial cells to toxic end-products need to be defined. In this chapter, we discuss recent progresses in interpreting cyanobacterial responses to biofuels and chemicals using high-throughput proteomics approach, aiming to provide insights and guidelines on how to enhance tolerance and productivity of biofuels or chemicals in the renewable cyanobacteria systems in the future. © 2017 Elsevier Inc. All rights reserved.

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.

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.

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

GenoCAD Plant Grammar to Design Plant Expression Vectors for Promoter Analysis.

PubMed

Coll, Anna; Wilson, Mandy L; Gruden, Kristina; Peccoud, Jean

2016-01-01

With the rapid advances in prediction tools for discovery of new promoters and their cis-elements, there is a need to improve plant expression methodologies in order to facilitate a high-throughput functional validation of these promoters in planta. The promoter-reporter analysis is an indispensible approach for characterization of plant promoters. It requires the design of complex plant expression vectors, which can be challenging. Here, we describe the use of a plant grammar implemented in GenoCAD that will allow the users to quickly design constructs for promoter analysis experiments but also for other in planta functional studies. The GenoCAD plant grammar includes a library of plant biological parts organized in structural categories to facilitate their use and management and a set of rules that guides the process of assembling these biological parts into large constructs.

High-throughput amplification of mature microRNAs in uncharacterized animal models using polyadenylated RNA and stem-loop reverse transcription polymerase chain reaction.

PubMed

Biggar, Kyle K; Wu, Cheng-Wei; Storey, Kenneth B

2014-10-01

This study makes a significant advancement on a microRNA amplification technique previously used for expression analysis and sequencing in animal models without annotated mature microRNA sequences. As research progresses into the post-genomic era of microRNA prediction and analysis, the need for a rapid and cost-effective method for microRNA amplification is critical to facilitate wide-scale analysis of microRNA expression. To facilitate this requirement, we have reoptimized the design of amplification primers and introduced a polyadenylation step to allow amplification of all mature microRNAs from a single RNA sample. Importantly, this method retains the ability to sequence reverse transcription polymerase chain reaction (RT-PCR) products, validating microRNA-specific amplification. Copyright © 2014 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2014-01-01

With the goal to generate and characterize the phenotypes of null alleles in all genes within an organism and the recent advances in custom nucleases, genome editing limitations have moved from mutation generation to mutation detection. We previously demonstrated that High Resolution Melting (HRM) analysis is a rapid and efficient means of genotyping known zebrafish mutants. Here we establish optimized conditions for HRM based detection of novel mutant alleles. Using these conditions, we demonstrate that HRM is highly efficient at mutation detection across multiple genome editing platforms (ZFNs, TALENs, and CRISPRs); we observed nuclease generated HRM positive targeting in 1 of 6 (16%) open pool derived ZFNs, 14 of 23 (60%) TALENs, and 58 of 77 (75%) CRISPR nucleases. Successful targeting, based on HRM of G0 embryos correlates well with successful germline transmission (46 of 47 nucleases); yet, surprisingly mutations in the somatic tail DNA weakly correlate with mutations in the germline F1 progeny DNA. This suggests that analysis of G0 tail DNA is a good indicator of the efficiency of the nuclease, but not necessarily a good indicator of germline alleles that will be present in the F1s. However, we demonstrate that small amplicon HRM curve profiles of F1 progeny DNA can be used to differentiate between specific mutant alleles, facilitating rare allele identification and isolation; and that HRM is a powerful technique for screening possible off-target mutations that may be generated by the nucleases. Our data suggest that micro-homology based alternative NHEJ repair is primarily utilized in the generation of CRISPR mutant alleles and allows us to predict likelihood of generating a null allele. Lastly, we demonstrate that HRM can be used to quickly distinguish genotype-phenotype correlations within F1 embryos derived from G0 intercrosses. Together these data indicate that custom nucleases, in conjunction with the ease and speed of HRM, will facilitate future high-throughput mutation generation and analysis needed to establish mutants in all genes of an organism. PMID:25503746

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

PubMed

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

2012-12-07

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

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

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.

Library Design-Facilitated High-Throughput Sequencing of Synthetic Peptide Libraries.

PubMed

Vinogradov, Alexander A; Gates, Zachary P; Zhang, Chi; Quartararo, Anthony J; Halloran, Kathryn H; Pentelute, Bradley L

2017-11-13

A methodology to achieve high-throughput de novo sequencing of synthetic peptide mixtures is reported. The approach leverages shotgun nanoliquid chromatography coupled with tandem mass spectrometry-based de novo sequencing of library mixtures (up to 2000 peptides) as well as automated data analysis protocols to filter away incorrect assignments, noise, and synthetic side-products. For increasing the confidence in the sequencing results, mass spectrometry-friendly library designs were developed that enabled unambiguous decoding of up to 600 peptide sequences per hour while maintaining greater than 85% sequence identification rates in most cases. The reliability of the reported decoding strategy was additionally confirmed by matching fragmentation spectra for select authentic peptides identified from library sequencing samples. The methods reported here are directly applicable to screening techniques that yield mixtures of active compounds, including particle sorting of one-bead one-compound libraries and affinity enrichment of synthetic library mixtures performed in solution.

Reverse Ecology: from systems to environments and back.

PubMed

Levy, Roie; Borenstein, Elhanan

2012-01-01

The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.

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.

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

PubMed

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

2012-06-20

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

A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection

PubMed Central

Goodacre, Norman; Aljanahi, Aisha; Nandakumar, Subhiksha; Mikailov, Mike

2018-01-01

ABSTRACT Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. IMPORTANCE To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have developed a new reference viral database (RVDB) that provides a broad representation of different virus species from eukaryotes by including all viral, virus-like, and virus-related sequences (excluding bacteriophages), regardless of their size. In particular, RVDB contains endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Sequences were clustered to reduce redundancy while retaining high viral sequence diversity. A particularly useful feature of RVDB is the reduction of cellular sequences, which can enhance the run efficiency of large transcriptomic and genomic data analysis and increase the specificity of virus detection. PMID:29564396

A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection.

PubMed

Goodacre, Norman; Aljanahi, Aisha; Nandakumar, Subhiksha; Mikailov, Mike; Khan, Arifa S

2018-01-01

Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. IMPORTANCE To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have developed a new reference viral database (RVDB) that provides a broad representation of different virus species from eukaryotes by including all viral, virus-like, and virus-related sequences (excluding bacteriophages), regardless of their size. In particular, RVDB contains endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Sequences were clustered to reduce redundancy while retaining high viral sequence diversity. A particularly useful feature of RVDB is the reduction of cellular sequences, which can enhance the run efficiency of large transcriptomic and genomic data analysis and increase the specificity of virus detection.

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.

Efficient intracellular delivery and improved biocompatibility of colloidal silver nanoparticles towards intracellular SERS immuno-sensing.

PubMed

Bhardwaj, Vinay; Srinivasan, Supriya; McGoron, Anthony J

2015-06-21

High throughput intracellular delivery strategies, electroporation, passive and TATHA2 facilitated diffusion of colloidal silver nanoparticles (AgNPs) are investigated for cellular toxicity and uptake using state-of-art analytical techniques. The TATHA2 facilitated approach efficiently delivered high payload with no toxicity, pre-requisites for intracellular applications of plasmonic metal nanoparticles (PMNPs) in sensing and therapeutics.

Adverse outcome pathway (AOP) development II: Best practices

EPA Science Inventory

Organization of existing and emerging toxicological knowledge into adverse outcome pathway (AOP) descriptions can facilitate greater application of mechanistic data, including high throughput in vitro, high content omics and imaging, and biomarkers, in risk-based decision-making....

Simple Analysis of Deposited Gene Expression Datasets for the Non-Bioinformatician: How to Use GEO for Fibrosis Research.

PubMed

Guo, Yang; Townsend, Richard; Tsoi, Lam C

2017-01-01

In the past decade, high-throughput techniques have facilitated the "-omics" research. Transcriptomic study, for instance, has advanced our understanding on the expression landscape of different human diseases and cellular mechanisms. The National Center for Biotechnology Center (NCBI) initialized Genetic Expression Omnibus (GEO) to promote the sharing of transcriptomic data to facilitate biomedical research. In this chapter, we will illustrate how to use GEO to search and analyze the public available transcriptomic data, and we will provide easy to follow protocol for researchers to data mine the powerful resources in GEO to retrieve relevant information that can be valuable for fibrosis research.

A Family of LIC Vectors for High-Throughput Cloning and Purification of Proteins1

PubMed Central

Eschenfeldt, William H.; Stols, Lucy; Millard, Cynthia Sanville; Joachimiak, Andrzej; Donnelly, Mark I.

2009-01-01

Summary Fifteen related ligation-independent cloning vectors were constructed for high-throughput cloning and purification of proteins. The vectors encode a TEV protease site for removal of tags that facilitate protein purification (his-tag) or improve solubility (MBP, GST). Specialized vectors allow coexpression and copurification of interacting proteins, or in vivo removal of MBP by TVMV protease to improve screening and purification. All target genes and vectors are processed by the same protocols, which we describe here. PMID:18988021

Application of supercritical fluid carbon dioxide to the extraction and analysis of lipids.

PubMed

Lee, Jae Won; Fukusaki, Eiichiro; Bamba, Takeshi

2012-10-01

Supercritical carbon dioxide (SCCO(2)) is an ecofriendly supercritical fluid that is chemically inert, nontoxic, noninflammable and nonpolluting. As a green material, SCCO(2) has desirable properties such as high density, low viscosity and high diffusivity that make it suitable for use as a solvent in supercritical fluid extraction, an effective and environment-friendly analytical method, and as a mobile phase for supercritical fluid chromatography, which facilitates high-throughput, high-resolution analysis. Furthermore, the low polarity of SCCO(2) is suitable for the extraction and analysis of hydrophobic compounds. The growing concern surrounding environmental pollution has triggered the development of green analysis methods based on the use of SCCO(2) in various laboratories and industries. SCCO(2) is becoming an effective alternative to conventional organic solvents. In this review, the usefulness of SCCO(2) in supercritical fluid extraction and supercritical fluid chromatography for the extraction and analysis of lipids is described.

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

NASA Astrophysics Data System (ADS)

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

1999-04-01

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

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.

A high-throughput, simultaneous analysis of carotenoids, chlorophylls and tocopherol using sub two micron core shell technology columns.

PubMed

Chebrolu, Kranthi K; Yousef, Gad G; Park, Ryan; Tanimura, Yoshinori; Brown, Allan F

2015-09-15

A high-throughput, robust and reliable method for simultaneous analysis of five carotenoids, four chlorophylls and one tocopherol was developed for rapid screening large sample populations to facilitate molecular biology and plant breeding. Separation was achieved for 10 known analytes and four unknown carotenoids in a significantly reduced run time of 10min. Identity of the 10 analytes was confirmed by their UV-Vis absorption spectras. Quantification of tocopherol, carotenoids and chlorophylls was performed at 290nm, 460nm and 650nm respectively. In this report, two sub two micron particle core-shell columns, Kinetex from Phenomenex (1.7μm particle size, 12% carbon load) and Cortecs from Waters (1.6μm particle size, 6.6% carbon load) were investigated and their separation efficiencies were evaluated. The peak resolutions were >1.5 for all analytes except for chlorophyll-a' with Cortecs column. The ruggedness of this method was evaluated in two identical but separate instruments that produced CV<2 in peak retentions for nine out of 10 analytes separated. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Advanced Virus Detection Technologies Interest Group (AVDTIG): Efforts on High Throughput Sequencing (HTS) for Virus Detection.

PubMed

Khan, Arifa S; Vacante, Dominick A; Cassart, Jean-Pol; Ng, Siemon H S; Lambert, Christophe; Charlebois, Robert L; King, Kathryn E

Several nucleic-acid based technologies have recently emerged with capabilities for broad virus detection. One of these, high throughput sequencing, has the potential for novel virus detection because this method does not depend upon prior viral sequence knowledge. However, the use of high throughput sequencing for testing biologicals poses greater challenges as compared to other newly introduced tests due to its technical complexities and big data bioinformatics. Thus, the Advanced Virus Detection Technologies Users Group was formed as a joint effort by regulatory and industry scientists to facilitate discussions and provide a forum for sharing data and experiences using advanced new virus detection technologies, with a focus on high throughput sequencing technologies. The group was initiated as a task force that was coordinated by the Parenteral Drug Association and subsequently became the Advanced Virus Detection Technologies Interest Group to continue efforts for using new technologies for detection of adventitious viruses with broader participation, including international government agencies, academia, and technology service providers. © PDA, Inc. 2016.

Improving bed turnover time with a bed management system.

PubMed

Tortorella, Frank; Ukanowicz, Donna; Douglas-Ntagha, Pamela; Ray, Robert; Triller, Maureen

2013-01-01

Efficient patient throughput requires a high degree of coordination and communication. Opportunities abound to improve the patient experience by eliminating waste from the process and improving communication among the multiple disciplines involved in facilitating patient flow. In this article, we demonstrate how an interdisciplinary team at a large tertiary cancer center implemented an electronic bed management system to improve the bed turnover component of the patient throughput process.

YBYRÁ facilitates comparison of large phylogenetic trees.

PubMed

Machado, Denis Jacob

2015-07-01

The number and size of tree topologies that are being compared by phylogenetic systematists is increasing due to technological advancements in high-throughput DNA sequencing. However, we still lack tools to facilitate comparison among phylogenetic trees with a large number of terminals. The "YBYRÁ" project integrates software solutions for data analysis in phylogenetics. It comprises tools for (1) topological distance calculation based on the number of shared splits or clades, (2) sensitivity analysis and automatic generation of sensitivity plots and (3) clade diagnoses based on different categories of synapomorphies. YBYRÁ also provides (4) an original framework to facilitate the search for potential rogue taxa based on how much they affect average matching split distances (using MSdist). YBYRÁ facilitates comparison of large phylogenetic trees and outperforms competing software in terms of usability and time efficiency, specially for large data sets. The programs that comprises this toolkit are written in Python, hence they do not require installation and have minimum dependencies. The entire project is available under an open-source licence at http://www.ib.usp.br/grant/anfibios/researchSoftware.html .

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

PubMed Central

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

2011-01-01

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

Enabling Large-Scale Biomedical Analysis in the Cloud

PubMed Central

Lin, Ying-Chih; Yu, Chin-Sheng; Lin, Yen-Jen

2013-01-01

Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable. PMID:24288665

Networking Omic Data to Envisage Systems Biological Regulation.

PubMed

Kalapanulak, Saowalak; Saithong, Treenut; Thammarongtham, Chinae

To understand how biological processes work, it is necessary to explore the systematic regulation governing the behaviour of the processes. Not only driving the normal behavior of organisms, the systematic regulation evidently underlies the temporal responses to surrounding environments (dynamics) and long-term phenotypic adaptation (evolution). The systematic regulation is, in effect, formulated from the regulatory components which collaboratively work together as a network. In the drive to decipher such a code of lives, a spectrum of technologies has continuously been developed in the post-genomic era. With current advances, high-throughput sequencing technologies are tremendously powerful for facilitating genomics and systems biology studies in the attempt to understand system regulation inside the cells. The ability to explore relevant regulatory components which infer transcriptional and signaling regulation, driving core cellular processes, is thus enhanced. This chapter reviews high-throughput sequencing technologies, including second and third generation sequencing technologies, which support the investigation of genomics and transcriptomics data. Utilization of this high-throughput data to form the virtual network of systems regulation is explained, particularly transcriptional regulatory networks. Analysis of the resulting regulatory networks could lead to an understanding of cellular systems regulation at the mechanistic and dynamics levels. The great contribution of the biological networking approach to envisage systems regulation is finally demonstrated by a broad range of examples.

Detecting DNA double-stranded breaks in mammalian genomes by linear amplification-mediated high-throughput genome-wide translocation sequencing.

PubMed

Hu, Jiazhi; Meyers, Robin M; Dong, Junchao; Panchakshari, Rohit A; Alt, Frederick W; Frock, Richard L

2016-05-01

Unbiased, high-throughput assays for detecting and quantifying DNA double-stranded breaks (DSBs) across the genome in mammalian cells will facilitate basic studies of the mechanisms that generate and repair endogenous DSBs. They will also enable more applied studies, such as those to evaluate the on- and off-target activities of engineered nucleases. Here we describe a linear amplification-mediated high-throughput genome-wide sequencing (LAM-HTGTS) method for the detection of genome-wide 'prey' DSBs via their translocation in cultured mammalian cells to a fixed 'bait' DSB. Bait-prey junctions are cloned directly from isolated genomic DNA using LAM-PCR and unidirectionally ligated to bridge adapters; subsequent PCR steps amplify the single-stranded DNA junction library in preparation for Illumina Miseq paired-end sequencing. A custom bioinformatics pipeline identifies prey sequences that contribute to junctions and maps them across the genome. LAM-HTGTS differs from related approaches because it detects a wide range of broken end structures with nucleotide-level resolution. Familiarity with nucleic acid methods and next-generation sequencing analysis is necessary for library generation and data interpretation. LAM-HTGTS assays are sensitive, reproducible, relatively inexpensive, scalable and straightforward to implement with a turnaround time of <1 week.

Modeling congenital disease and inborn errors of development in Drosophila melanogaster

PubMed Central

Moulton, Matthew J.; Letsou, Anthea

2016-01-01

ABSTRACT Fly models that faithfully recapitulate various aspects of human disease and human health-related biology are being used for research into disease diagnosis and prevention. Established and new genetic strategies in Drosophila have yielded numerous substantial successes in modeling congenital disorders or inborn errors of human development, as well as neurodegenerative disease and cancer. Moreover, although our ability to generate sequence datasets continues to outpace our ability to analyze these datasets, the development of high-throughput analysis platforms in Drosophila has provided access through the bottleneck in the identification of disease gene candidates. In this Review, we describe both the traditional and newer methods that are facilitating the incorporation of Drosophila into the human disease discovery process, with a focus on the models that have enhanced our understanding of human developmental disorders and congenital disease. Enviable features of the Drosophila experimental system, which make it particularly useful in facilitating the much anticipated move from genotype to phenotype (understanding and predicting phenotypes directly from the primary DNA sequence), include its genetic tractability, the low cost for high-throughput discovery, and a genome and underlying biology that are highly evolutionarily conserved. In embracing the fly in the human disease-gene discovery process, we can expect to speed up and reduce the cost of this process, allowing experimental scales that are not feasible and/or would be too costly in higher eukaryotes. PMID:26935104

High-Throughput Epitope Binning Assays on Label-Free Array-Based Biosensors Can Yield Exquisite Epitope Discrimination That Facilitates the Selection of Monoclonal Antibodies with Functional Activity

PubMed Central

Abdiche, Yasmina Noubia; Miles, Adam; Eckman, Josh; Foletti, Davide; Van Blarcom, Thomas J.; Yeung, Yik Andy; Pons, Jaume; Rajpal, Arvind

2014-01-01

Here, we demonstrate how array-based label-free biosensors can be applied to the multiplexed interaction analysis of large panels of analyte/ligand pairs, such as the epitope binning of monoclonal antibodies (mAbs). In this application, the larger the number of mAbs that are analyzed for cross-blocking in a pairwise and combinatorial manner against their specific antigen, the higher the probability of discriminating their epitopes. Since cross-blocking of two mAbs is necessary but not sufficient for them to bind an identical epitope, high-resolution epitope binning analysis determined by high-throughput experiments can enable the identification of mAbs with similar but unique epitopes. We demonstrate that a mAb's epitope and functional activity are correlated, thereby strengthening the relevance of epitope binning data to the discovery of therapeutic mAbs. We evaluated two state-of-the-art label-free biosensors that enable the parallel analysis of 96 unique analyte/ligand interactions and nearly ten thousand total interactions per unattended run. The IBIS-MX96 is a microarray-based surface plasmon resonance imager (SPRi) integrated with continuous flow microspotting technology whereas the Octet-HTX is equipped with disposable fiber optic sensors that use biolayer interferometry (BLI) detection. We compared their throughput, versatility, ease of sample preparation, and sample consumption in the context of epitope binning assays. We conclude that the main advantages of the SPRi technology are its exceptionally low sample consumption, facile sample preparation, and unparalleled unattended throughput. In contrast, the BLI technology is highly flexible because it allows for the simultaneous interaction analysis of 96 independent analyte/ligand pairs, ad hoc sensor replacement and on-line reloading of an analyte- or ligand-array. Thus, the complementary use of these two platforms can expedite applications that are relevant to the discovery of therapeutic mAbs, depending upon the sample availability, and the number and diversity of the interactions being studied. PMID:24651868

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

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

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

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

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

DOE PAGES

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

2015-10-07

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

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

PubMed

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

2009-08-25

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

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.

FLIC: High-Throughput, Continuous Analysis of Feeding Behaviors in Drosophila

PubMed Central

Pletcher, Scott D.

2014-01-01

We present a complete hardware and software system for collecting and quantifying continuous measures of feeding behaviors in the fruit fly, Drosophila melanogaster. The FLIC (Fly Liquid-Food Interaction Counter) detects analog electronic signals as brief as 50 µs that occur when a fly makes physical contact with liquid food. Signal characteristics effectively distinguish between different types of behaviors, such as feeding and tasting events. The FLIC system performs as well or better than popular methods for simple assays, and it provides an unprecedented opportunity to study novel components of feeding behavior, such as time-dependent changes in food preference and individual levels of motivation and hunger. Furthermore, FLIC experiments can persist indefinitely without disturbance, and we highlight this ability by establishing a detailed picture of circadian feeding behaviors in the fly. We believe that the FLIC system will work hand-in-hand with modern molecular techniques to facilitate mechanistic studies of feeding behaviors in Drosophila using modern, high-throughput technologies. PMID:24978054

An efficient and high-throughput protocol for Agrobacterium-mediated transformation based on phosphomannose isomerase positive selection in Japonica rice (Oryza sativa L.).

PubMed

Duan, Yongbo; Zhai, Chenguang; Li, Hao; Li, Juan; Mei, Wenqian; Gui, Huaping; Ni, Dahu; Song, Fengshun; Li, Li; Zhang, Wanggen; Yang, Jianbo

2012-09-01

A number of Agrobacterium-mediated rice transformation systems have been developed and widely used in numerous laboratories and research institutes. However, those systems generally employ antibiotics like kanamycin and hygromycin, or herbicide as selectable agents, and are used for the small-scale experiments. To address high-throughput production of transgenic rice plants via Agrobacterium-mediated transformation, and to eliminate public concern on antibiotic markers, we developed a comprehensive efficient protocol, covering from explant preparation to the acquisition of low copy events by real-time PCR analysis before transplant to field, for high-throughput production of transgenic plants of Japonica rice varieties Wanjing97 and Nipponbare using Escherichia coli phosphomannose isomerase gene (pmi) as a selectable marker. The transformation frequencies (TF) of Wanjing97 and Nipponbare were achieved as high as 54.8 and 47.5%, respectively, in one round of selection of 7.5 or 12.5 g/L mannose appended with 5 g/L sucrose. High-throughput transformation from inoculation to transplant of low copy events was accomplished within 55-60 days. Moreover, the Taqman assay data from a large number of transformants showed 45.2% in Wanjing97 and 31.5% in Nipponbare as a low copy rate, and the transformants are fertile and follow the Mendelian segregation ratio. This protocol facilitates us to perform genome-wide functional annotation of the open reading frames and utilization of the agronomically important genes in rice under a reduced public concern on selectable markers. We describe a comprehensive protocol for large scale production of transgenic Japonica rice plants using non-antibiotic selectable agent, at simplified, cost- and labor-saving manners.

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

PubMed Central

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

2017-01-01

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

Advancements in zebrafish applications for 21st century toxicology.

PubMed

Garcia, Gloria R; Noyes, Pamela D; Tanguay, Robert L

2016-05-01

The zebrafish model is the only available high-throughput vertebrate assessment system, and it is uniquely suited for studies of in vivo cell biology. A sequenced and annotated genome has revealed a large degree of evolutionary conservation in comparison to the human genome. Due to our shared evolutionary history, the anatomical and physiological features of fish are highly homologous to humans, which facilitates studies relevant to human health. In addition, zebrafish provide a very unique vertebrate data stream that allows researchers to anchor hypotheses at the biochemical, genetic, and cellular levels to observations at the structural, functional, and behavioral level in a high-throughput format. In this review, we will draw heavily from toxicological studies to highlight advances in zebrafish high-throughput systems. Breakthroughs in transgenic/reporter lines and methods for genetic manipulation, such as the CRISPR-Cas9 system, will be comprised of reports across diverse disciplines. Copyright © 2016 Elsevier Inc. All rights reserved.

Advancements in zebrafish applications for 21st century toxicology

PubMed Central

Garcia, Gloria R.; Noyes, Pamela D.; Tanguay, Robert L.

2016-01-01

The zebrafish model is the only available high-throughput vertebrate assessment system, and it is uniquely suited for studies of in vivo cell biology. A sequenced and annotated genome has revealed a large degree of evolutionary conservation in comparison to the human genome. Due to our shared evolutionary history, the anatomical and physiological features of fish are highly homologous to humans, which facilitates studies relevant to human health. In addition, zebrafish provide a very unique vertebrate data stream that allows researchers to anchor hypotheses at the biochemical, genetic, and cellular levels to observations at the structural, functional, and behavioral level in a high-throughput format. In this review, we will draw heavily from toxicological studies to highlight advances in zebrafish high-throughput systems. Breakthroughs in transgenic/reporter lines and methods for genetic manipulation, such as the CRISPR-Cas9 system, will be comprised of reports across diverse disciplines. PMID:27016469

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

Measuring molecular biomarkers in epidemiologic studies: laboratory techniques and biospecimen considerations.

PubMed

Erickson, Heidi S

2012-09-28

The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease-specific molecular biomarkers. High-throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population-based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling. Copyright © 2012 John Wiley & Sons, Ltd.

Genome Neighborhood Network Reveals Insights into Enediyne Biosynthesis and Facilitates Prediction and Prioritization for Discovery

PubMed Central

Rudolf, Jeffrey D.; Yan, Xiaohui; Shen, Ben

2015-01-01

The enediynes are one of the most fascinating families of bacterial natural products given their unprecedented molecular architecture and extraordinary cytotoxicity. Enediynes are rare with only 11 structurally characterized members and four additional members isolated in their cycloaromatized form. Recent advances in DNA sequencing have resulted in an explosion of microbial genomes. A virtual survey of the GenBank and JGI genome databases revealed 87 enediyne biosynthetic gene clusters from 78 bacteria strains, implying enediynes are more common than previously thought. Here we report the construction and analysis of an enediyne genome neighborhood network (GNN) as a high-throughput approach to analyze secondary metabolite gene clusters. Analysis of the enediyne GNN facilitated rapid gene cluster annotation, revealed genetic trends in enediyne biosynthetic gene clusters resulting in a simple prediction scheme to determine 9- vs 10-membered enediyne gene clusters, and supported a genomic-based strain prioritization method for enediyne discovery. PMID:26318027

[The future of forensic DNA analysis for criminal justice].

PubMed

Laurent, François-Xavier; Vibrac, Geoffrey; Rubio, Aurélien; Thévenot, Marie-Thérèse; Pène, Laurent

2017-11-01

In the criminal framework, the analysis of approximately 20 DNA microsatellites enables the establishment of a genetic profile with a high statistical power of discrimination. This technique gives us the possibility to establish or exclude a match between a biological trace detected at a crime scene and a suspect whose DNA was collected via an oral swab. However, conventional techniques do tend to complexify the interpretation of complex DNA samples, such as degraded DNA and mixture DNA. The aim of this review is to highlight the powerness of new forensic DNA methods (including high-throughput sequencing or single-cell sequencing) to facilitate the interpretation of the expert with full compliance with existing french legislation. © 2017 médecine/sciences – Inserm.

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

PubMed

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

2018-02-21

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

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

PubMed Central

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

2010-01-01

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

A quantitative and high-throughput assay of human papillomavirus DNA replication.

PubMed

Gagnon, David; Fradet-Turcotte, Amélie; Archambault, Jacques

2015-01-01

Replication of the human papillomavirus (HPV) double-stranded DNA genome is accomplished by the two viral proteins E1 and E2 in concert with host DNA replication factors. HPV DNA replication is an established model of eukaryotic DNA replication and a potential target for antiviral therapy. Assays to measure the transient replication of HPV DNA in transfected cells have been developed, which rely on a plasmid carrying the viral origin of DNA replication (ori) together with expression vectors for E1 and E2. Replication of the ori-plasmid is typically measured by Southern blotting or PCR analysis of newly replicated DNA (i.e., DpnI digested DNA) several days post-transfection. Although extremely valuable, these assays have been difficult to perform in a high-throughput and quantitative manner. Here, we describe a modified version of the transient DNA replication assay that circumvents these limitations by incorporating a firefly luciferase expression cassette in cis of the ori. Replication of this ori-plasmid by E1 and E2 results in increased levels of firefly luciferase activity that can be accurately quantified and normalized to those of Renilla luciferase expressed from a control plasmid, thus obviating the need for DNA extraction, digestion, and analysis. We provide a detailed protocol for performing the HPV type 31 DNA replication assay in a 96-well plate format suitable for small-molecule screening and EC50 determinations. The quantitative and high-throughput nature of the assay should greatly facilitate the study of HPV DNA replication and the identification of inhibitors thereof.

AR-NE3A, a New Macromolecular Crystallography Beamline for Pharmaceutical Applications at the Photon Factory

NASA Astrophysics Data System (ADS)

Yamada, Yusuke; Hiraki, Masahiko; Sasajima, Kumiko; Matsugaki, Naohiro; Igarashi, Noriyuki; Amano, Yasushi; Warizaya, Masaichi; Sakashita, Hitoshi; Kikuchi, Takashi; Mori, Takeharu; Toyoshima, Akio; Kishimoto, Shunji; Wakatsuki, Soichi

2010-06-01

Recent advances in high-throughput techniques for macromolecular crystallography have highlighted the importance of structure-based drug design (SBDD), and the demand for synchrotron use by pharmaceutical researchers has increased. Thus, in collaboration with Astellas Pharma Inc., we have constructed a new high-throughput macromolecular crystallography beamline, AR-NE3A, which is dedicated to SBDD. At AR-NE3A, a photon flux up to three times higher than those at existing high-throughput beams at the Photon Factory, AR-NW12A and BL-5A, can be realized at the same sample positions. Installed in the experimental hutch are a high-precision diffractometer, fast-readout, high-gain CCD detector, and sample exchange robot capable of handling more than two hundred cryo-cooled samples stored in a Dewar. To facilitate high-throughput data collection required for pharmaceutical research, fully automated data collection and processing systems have been developed. Thus, sample exchange, centering, data collection, and data processing are automatically carried out based on the user's pre-defined schedule. Although Astellas Pharma Inc. has a priority access to AR-NE3A, the remaining beam time is allocated to general academic and other industrial users.

HiTC: exploration of high-throughput ‘C’ experiments

PubMed Central

Servant, Nicolas; Lajoie, Bryan R.; Nora, Elphège P.; Giorgetti, Luca; Chen, Chong-Jian; Heard, Edith; Dekker, Job; Barillot, Emmanuel

2012-01-01

Summary: The R/Bioconductor package HiTC facilitates the exploration of high-throughput 3C-based data. It allows users to import and export ‘C’ data, to transform, normalize, annotate and visualize interaction maps. The package operates within the Bioconductor framework and thus offers new opportunities for future development in this field. Availability and implementation: The R package HiTC is available from the Bioconductor website. A detailed vignette provides additional documentation and help for using the package. Contact: nicolas.servant@curie.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22923296

Ultra-rapid auxin metabolite profiling for high-throughput mutant screening in Arabidopsis.

PubMed

Pencík, Aleš; Casanova-Sáez, Rubén; Pilarová, Veronika; Žukauskaite, Asta; Pinto, Rui; Micol, José Luis; Ljung, Karin; Novák, Ondrej

2018-04-27

Auxin (indole-3-acetic acid, IAA) plays fundamental roles as a signalling molecule during numerous plant growth and development processes. The formation of local auxin gradients and auxin maxima/minima, which is very important for these processes, is regulated by auxin metabolism (biosynthesis, degradation, and conjugation) as well as transport. When studying auxin metabolism pathways it is crucial to combine data obtained from genetic investigations with the identification and quantification of individual metabolites. Thus, to facilitate efforts to elucidate auxin metabolism and its roles in plants, we have developed a high-throughput method for simultaneously quantifying IAA and its key metabolites in minute samples (<10 mg FW) of Arabidopsis thaliana tissues by in-tip micro solid-phase extraction and fast LC-tandem MS. As a proof of concept, we applied the method to a collection of Arabidopsis mutant lines and identified lines with altered IAA metabolite profiles using multivariate data analysis. Finally, we explored the correlation between IAA metabolite profiles and IAA-related phenotypes. The developed rapid analysis of large numbers of samples (>100 samples d-1) is a valuable tool to screen for novel regulators of auxin metabolism and homeostasis among large collections of genotypes.

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

PubMed Central

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

2015-01-01

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

Adverse Outcome Pathways – Tailoring Development to Support Use

EPA Science Inventory

Adverse Outcome Pathways (AOPs) represent an ideal framework for connecting high-throughput screening (HTS) data and other toxicity testing results to adverse outcomes of regulatory importance. The AOP Knowledgebase (AOP-KB) captures AOP information to facilitate the development,...

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

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

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

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

PubMed

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

2014-11-21

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

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

2018-01-01

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

High-throughput screening with nanoimprinting 3D culture for efficient drug development by mimicking the tumor environment.

PubMed

Yoshii, Yukie; Furukawa, Takako; Waki, Atsuo; Okuyama, Hiroaki; Inoue, Masahiro; Itoh, Manabu; Zhang, Ming-Rong; Wakizaka, Hidekatsu; Sogawa, Chizuru; Kiyono, Yasushi; Yoshii, Hiroshi; Fujibayashi, Yasuhisa; Saga, Tsuneo

2015-05-01

Anti-cancer drug development typically utilizes high-throughput screening with two-dimensional (2D) cell culture. However, 2D culture induces cellular characteristics different from tumors in vivo, resulting in inefficient drug development. Here, we report an innovative high-throughput screening system using nanoimprinting 3D culture to simulate in vivo conditions, thereby facilitating efficient drug development. We demonstrated that cell line-based nanoimprinting 3D screening can more efficiently select drugs that effectively inhibit cancer growth in vivo as compared to 2D culture. Metabolic responses after treatment were assessed using positron emission tomography (PET) probes, and revealed similar characteristics between the 3D spheroids and in vivo tumors. Further, we developed an advanced method to adopt cancer cells from patient tumor tissues for high-throughput drug screening with nanoimprinting 3D culture, which we termed Cancer tissue-Originated Uniformed Spheroid Assay (COUSA). This system identified drugs that were effective in xenografts of the original patient tumors. Nanoimprinting 3D spheroids showed low permeability and formation of hypoxic regions inside, similar to in vivo tumors. Collectively, the nanoimprinting 3D culture provides easy-handling high-throughput drug screening system, which allows for efficient drug development by mimicking the tumor environment. The COUSA system could be a useful platform for drug development with patient cancer cells. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Strong Cation Exchange Chromatography in Analysis of Posttranslational Modifications: Innovations and Perspectives

PubMed Central

Edelmann, Mariola J.

2011-01-01

Strong cation exchange (SCX) chromatography has been utilized as an excellent separation technique that can be combined with reversed-phase (RP) chromatography, which is frequently used in peptide mass spectrometry. Although SCX is valuable as the second component of such two-dimensional separation methods, its application goes far beyond efficient fractionation of complex peptide mixtures. Here I describe how SCX facilitates mapping of the protein posttranslational modifications (PTMs), specifically phosphorylation and N-terminal acetylation. The SCX chromatography has been mainly used for enrichment of these two PTMs, but it might also be beneficial for high-throughput analysis of other modifications that alter the net charge of a peptide. PMID:22174558

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

PubMed Central

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

2012-01-01

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

Optimization and high-throughput screening of antimicrobial peptides.

PubMed

Blondelle, Sylvie E; Lohner, Karl

2010-01-01

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

CIAN - Cell Imaging and Analysis Network at the Biology Department of McGill University

PubMed Central

Lacoste, J.; Lesage, G.; Bunnell, S.; Han, H.; Küster-Schöck, E.

2010-01-01

CF-31 The Cell Imaging and Analysis Network (CIAN) provides services and tools to researchers in the field of cell biology from within or outside Montreal's McGill University community. CIAN is composed of six scientific platforms: Cell Imaging (confocal and fluorescence microscopy), Proteomics (2-D protein gel electrophoresis and DiGE, fluorescent protein analysis), Automation and High throughput screening (Pinning robot and liquid handler), Protein Expression for Antibody Production, Genomics (real-time PCR), and Data storage and analysis (cluster, server, and workstations). Users submit project proposals, and can obtain training and consultation in any aspect of the facility, or initiate projects with the full-service platforms. CIAN is designed to facilitate training, enhance interactions, as well as share and maintain resources and expertise.

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

PubMed

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

2018-01-01

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

Metagenomic analysis revealed highly diverse microbial arsenic metabolism genes in paddy soils with low-arsenic contents.

PubMed

Xiao, Ke-Qing; Li, Li-Guan; Ma, Li-Ping; Zhang, Si-Yu; Bao, Peng; Zhang, Tong; Zhu, Yong-Guan

2016-04-01

Microbe-mediated arsenic (As) metabolism plays a critical role in global As cycle, and As metabolism involves different types of genes encoding proteins facilitating its biotransformation and transportation processes. Here, we used metagenomic analysis based on high-throughput sequencing and constructed As metabolism protein databases to analyze As metabolism genes in five paddy soils with low-As contents. The results showed that highly diverse As metabolism genes were present in these paddy soils, with varied abundances and distribution for different types and subtypes of these genes. Arsenate reduction genes (ars) dominated in all soil samples, and significant correlation existed between the abundance of arr (arsenate respiration), aio (arsenite oxidation), and arsM (arsenite methylation) genes, indicating the co-existence and close-relation of different As resistance systems of microbes in wetland environments similar to these paddy soils after long-term evolution. Among all soil parameters, pH was an important factor controlling the distribution of As metabolism gene in five paddy soils (p = 0.018). To the best of our knowledge, this is the first study using high-throughput sequencing and metagenomics approach in characterizing As metabolism genes in the five paddy soil, showing their great potential in As biotransformation, and therefore in mitigating arsenic risk to humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Kampmann, Marie-Louise; Buchard, Anders; Børsting, Claus; Morling, Niels

2016-01-01

Here, we demonstrate that punches from buccal swab samples preserved on FTA cards can be used for high-throughput DNA sequencing, also known as massively parallel sequencing (MPS). We typed 44 reference samples with the HID-Ion AmpliSeq Identity Panel using washed 1.2 mm punches from FTA cards with buccal swabs and compared the results with those obtained with DNA extracted using the EZ1 DNA Investigator Kit. Concordant profiles were obtained for all samples. Our protocol includes simple punch, wash, and PCR steps, reducing cost and hands-on time in the laboratory. Furthermore, it facilitates automation of DNA sequencing.

Application of high-throughput sequencing to whole rabies viral genome characterisation and its use for phylogenetic re-evaluation of a raccoon strain incursion into the province of Ontario.

PubMed

Nadin-Davis, Susan A; Colville, Adam; Trewby, Hannah; Biek, Roman; Real, Leslie

2017-03-15

Raccoon rabies remains a serious public health problem throughout much of the eastern seaboard of North America due to the urban nature of the reservoir host and the many challenges inherent in multi-jurisdictional efforts to administer co-ordinated and comprehensive wildlife rabies control programmes. Better understanding of the mechanisms of spread of rabies virus can play a significant role in guiding such control efforts. To facilitate a detailed molecular epidemiological study of raccoon rabies virus movements across eastern North America, we developed a methodology to efficiently determine whole genome sequences of hundreds of viral samples. The workflow combines the generation of a limited number of overlapping amplicons covering the complete viral genome and use of high throughput sequencing technology. The value of this approach is demonstrated through a retrospective phylogenetic analysis of an outbreak of raccoon rabies which occurred in the province of Ontario between 1999 and 2005. As demonstrated by the number of single nucleotide polymorphisms detected, whole genome sequence data were far more effective than single gene sequences in discriminating between samples and this facilitated the generation of more robust and informative phylogenies that yielded insights into the spatio-temporal pattern of viral spread. With minor modification this approach could be applied to other rabies virus variants thereby facilitating greatly improved phylogenetic inference and thus better understanding of the spread of this serious zoonotic disease. Such information will inform the most appropriate strategies for rabies control in wildlife reservoirs. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

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

EPA Science Inventory

The U.S. EPA, under its ExpoCast program, is developing high-throughput near-field modeling methods to estimate human chemical exposure and to provide real-world context to high-throughput screening (HTS) hazard data. These novel modeling methods include reverse methods to infer ...

Printing Proteins as Microarrays for High-Throughput Function Determination

NASA Astrophysics Data System (ADS)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

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

AR-NE3A, a New Macromolecular Crystallography Beamline for Pharmaceutical Applications at the Photon Factory

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

Yamada, Yusuke; Hiraki, Masahiko; Sasajima, Kumiko

2010-06-23

Recent advances in high-throughput techniques for macromolecular crystallography have highlighted the importance of structure-based drug design (SBDD), and the demand for synchrotron use by pharmaceutical researchers has increased. Thus, in collaboration with Astellas Pharma Inc., we have constructed a new high-throughput macromolecular crystallography beamline, AR-NE3A, which is dedicated to SBDD. At AR-NE3A, a photon flux up to three times higher than those at existing high-throughput beams at the Photon Factory, AR-NW12A and BL-5A, can be realized at the same sample positions. Installed in the experimental hutch are a high-precision diffractometer, fast-readout, high-gain CCD detector, and sample exchange robot capable ofmore » handling more than two hundred cryo-cooled samples stored in a Dewar. To facilitate high-throughput data collection required for pharmaceutical research, fully automated data collection and processing systems have been developed. Thus, sample exchange, centering, data collection, and data processing are automatically carried out based on the user's pre-defined schedule. Although Astellas Pharma Inc. has a priority access to AR-NE3A, the remaining beam time is allocated to general academic and other industrial users.« less

Determination of Microbial Extracellular Enzyme Activity in Waters, Soils, and Sediments using High Throughput Microplate Assays

PubMed Central

Jackson, Colin R.; Tyler, Heather L.; Millar, Justin J.

2013-01-01

Much of the nutrient cycling and carbon processing in natural environments occurs through the activity of extracellular enzymes released by microorganisms. Thus, measurement of the activity of these extracellular enzymes can give insights into the rates of ecosystem level processes, such as organic matter decomposition or nitrogen and phosphorus mineralization. Assays of extracellular enzyme activity in environmental samples typically involve exposing the samples to artificial colorimetric or fluorometric substrates and tracking the rate of substrate hydrolysis. Here we describe microplate based methods for these procedures that allow the analysis of large numbers of samples within a short time frame. Samples are allowed to react with artificial substrates within 96-well microplates or deep well microplate blocks, and enzyme activity is subsequently determined by absorption or fluorescence of the resulting end product using a typical microplate reader or fluorometer. Such high throughput procedures not only facilitate comparisons between spatially separate sites or ecosystems, but also substantially reduce the cost of such assays by reducing overall reagent volumes needed per sample. PMID:24121617

Determination of microbial extracellular enzyme activity in waters, soils, and sediments using high throughput microplate assays.

PubMed

Jackson, Colin R; Tyler, Heather L; Millar, Justin J

2013-10-01

Much of the nutrient cycling and carbon processing in natural environments occurs through the activity of extracellular enzymes released by microorganisms. Thus, measurement of the activity of these extracellular enzymes can give insights into the rates of ecosystem level processes, such as organic matter decomposition or nitrogen and phosphorus mineralization. Assays of extracellular enzyme activity in environmental samples typically involve exposing the samples to artificial colorimetric or fluorometric substrates and tracking the rate of substrate hydrolysis. Here we describe microplate based methods for these procedures that allow the analysis of large numbers of samples within a short time frame. Samples are allowed to react with artificial substrates within 96-well microplates or deep well microplate blocks, and enzyme activity is subsequently determined by absorption or fluorescence of the resulting end product using a typical microplate reader or fluorometer. Such high throughput procedures not only facilitate comparisons between spatially separate sites or ecosystems, but also substantially reduce the cost of such assays by reducing overall reagent volumes needed per sample.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

Using high throughput sequencing to explore the biodiversity in oral bacterial communities.

PubMed

Diaz, P I; Dupuy, A K; Abusleme, L; Reese, B; Obergfell, C; Choquette, L; Dongari-Bagtzoglou, A; Peterson, D E; Terzi, E; Strausbaugh, L D

2012-06-01

High throughput sequencing of 16S ribosomal RNA gene amplicons is a cost-effective method for characterization of oral bacterial communities. However, before undertaking large-scale studies, it is necessary to understand the technique-associated limitations and intrinsic variability of the oral ecosystem. In this work we evaluated bias in species representation using an in vitro-assembled mock community of oral bacteria. We then characterized the bacterial communities in saliva and buccal mucosa of five healthy subjects to investigate the power of high throughput sequencing in revealing their diversity and biogeography patterns. Mock community analysis showed primer and DNA isolation biases and an overestimation of diversity that was reduced after eliminating singleton operational taxonomic units (OTUs). Sequencing of salivary and mucosal communities found a total of 455 OTUs (0.3% dissimilarity) with only 78 of these present in all subjects. We demonstrate that this variability was partly the result of incomplete richness coverage even at great sequencing depths, and so comparing communities by their structure was more effective than comparisons based solely on membership. With respect to oral biogeography, we found inter-subject variability in community structure was lower than site differences between salivary and mucosal communities within subjects. These differences were evident at very low sequencing depths and were mostly caused by the abundance of Streptococcus mitis and Gemella haemolysans in mucosa. In summary, we present an experimental and data analysis framework that will facilitate design and interpretation of pyrosequencing-based studies. Despite challenges associated with this technique, we demonstrate its power for evaluation of oral diversity and biogeography patterns. © 2012 John Wiley & Sons A/S.

High-Throughput Genotyping of Single Nucleotide Polymorphisms in the Plasmodium falciparum dhfr Gene by Asymmetric PCR and Melt-Curve Analysis▿

PubMed Central

Cruz, Rochelle E.; Shokoples, Sandra E.; Manage, Dammika P.; Yanow, Stephanie K.

2010-01-01

Mutations within the Plasmodium falciparum dihydrofolate reductase gene (Pfdhfr) contribute to resistance to antimalarials such as sulfadoxine-pyrimethamine (SP). Of particular importance are the single nucleotide polymorphisms (SNPs) within codons 51, 59, 108, and 164 in the Pfdhfr gene that are associated with SP treatment failure. Given that traditional genotyping methods are time-consuming and laborious, we developed an assay that provides the rapid, high-throughput analysis of parasite DNA isolated from clinical samples. This assay is based on asymmetric real-time PCR and melt-curve analysis (MCA) performed on the LightCycler platform. Unlabeled probes specific to each SNP are included in the reaction mixture and hybridize differentially to the mutant and wild-type sequences within the amplicon, generating distinct melting curves. Since the probe is present throughout PCR and MCA, the assay proceeds seamlessly with no further addition of reagents. This assay was validated for analytical sensitivity and specificity using plasmids, purified genomic DNA from reference strains, and parasite cultures. For all four SNPs, correct genotypes were identified with 100 copies of the template. The performance of the assay was evaluated with a blind panel of clinical isolates from travelers with low-level parasitemia. The concordance between our assay and DNA sequencing ranged from 84 to 100% depending on the SNP. We also directly compared our MCA assay to a published TaqMan real-time PCR assay and identified major issues with the specificity of the TaqMan probes. Our assay provides a number of technical improvements that facilitate the high-throughput screening of patient samples to identify SP-resistant malaria. PMID:20631115

Development of a High-Throughput Resequencing Array for the Detection of Pathogenic Mutations in Osteogenesis Imperfecta

PubMed Central

Wang, Yao; Cui, Yazhou; Zhou, Xiaoyan; Han, Jinxiang

2015-01-01

Objective Osteogenesis imperfecta (OI) is a rare inherited skeletal disease, characterized by bone fragility and low bone density. The mutations in this disorder have been widely reported to be on various exonal hotspots of the candidate genes, including COL1A1, COL1A2, CRTAP, LEPRE1, and FKBP10, thus creating a great demand for precise genetic tests. However, large genome sizes make the process daunting and the analyses, inefficient and expensive. Therefore, we aimed at developing a fast, accurate, efficient, and cheaper sequencing platform for OI diagnosis; and to this end, use of an advanced array-based technique was proposed. Method A CustomSeq Affymetrix Resequencing Array was established for high-throughput sequencing of five genes simultaneously. Genomic DNA extraction from 13 OI patients and 85 normal controls and amplification using long-range PCR (LR-PCR) were followed by DNA fragmentation and chip hybridization, according to standard Affymetrix protocols. Hybridization signals were determined using GeneChip Sequence Analysis Software (GSEQ). To examine the feasibility, the outcome from new resequencing approach was validated by conventional capillary sequencing method. Result Overall call rates using resequencing array was 96–98% and the agreement between microarray and capillary sequencing was 99.99%. 11 out of 13 OI patients with pathogenic mutations were successfully detected by the chip analysis without adjustment, and one mutation could also be identified using manual visual inspection. Conclusion A high-throughput resequencing array was developed that detects the disease-associated mutations in OI, providing a potential tool to facilitate large-scale genetic screening for OI patients. Through this method, a novel mutation was also found. PMID:25742658

TAMEE: data management and analysis for tissue microarrays.

PubMed

Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

2007-03-07

With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from http://genome.tugraz.at/Software/TAMEE.

Three applications of backscatter x-ray imaging technology to homeland defense

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2005-05-01

A brief review of backscatter x-ray imaging and a description of three systems currently applying it to homeland defense missions (BodySearch, ZBV and ZBP). These missions include detection of concealed weapons, explosives and contraband on personnel, in vehicles and large cargo containers. An overview of the x-ray imaging subsystems is provided as well as sample images from each system. Key features such as x-ray safety, throughput and detection are discussed. Recent trends in operational modes are described that facilitate 100% inspection at high throughput chokepoints.

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

PubMed

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

2014-12-01

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

OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

PubMed

Van Coillie, Samya; Liang, Lunxi; Zhang, Yao; Wang, Huanbin; Fang, Jing-Yuan; Xu, Jie

2016-04-05

High-throughput methods such as co-immunoprecipitationmass spectrometry (coIP-MS) and yeast 2 hybridization (Y2H) have suggested a broad range of unannotated protein-protein interactions (PPIs), and interpretation of these PPIs remains a challenging task. The advancements in cancer genomic researches allow for the inference of "coactivation pairs" in cancer, which may facilitate the identification of PPIs involved in cancer. Here we present OncoBinder as a tool for the assessment of proteomic interaction data based on the functional synergy of oncoproteins in cancer. This decision tree-based method combines gene mutation, copy number and mRNA expression information to infer the functional status of protein-coding genes. We applied OncoBinder to evaluate the potential binders of EGFR and ERK2 proteins based on the gastric cancer dataset of The Cancer Genome Atlas (TCGA). As a result, OncoBinder identified high confidence interactions (annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) or validated by low-throughput assays) more efficiently than co-expression based method. Taken together, our results suggest that evaluation of gene functional synergy in cancer may facilitate the interpretation of proteomic interaction data. The OncoBinder toolbox for Matlab is freely accessible online.

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

DOE PAGES

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

2015-01-07

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

High throughput light absorber discovery, Part 1: An algorithm for automated tauc analysis

DOE PAGES

Suram, Santosh K.; Newhouse, Paul F.; Gregoire, John M.

2016-09-23

High-throughput experimentation provides efficient mapping of composition-property relationships, and its implementation for the discovery of optical materials enables advancements in solar energy and other technologies. In a high throughput pipeline, automated data processing algorithms are often required to match experimental throughput, and we present an automated Tauc analysis algorithm for estimating band gap energies from optical spectroscopy data. The algorithm mimics the judgment of an expert scientist, which is demonstrated through its application to a variety of high throughput spectroscopy data, including the identification of indirect or direct band gaps in Fe 2O 3, Cu 2V 2O 7, and BiVOmore » 4. Here, the applicability of the algorithm to estimate a range of band gap energies for various materials is demonstrated by a comparison of direct-allowed band gaps estimated by expert scientists and by automated algorithm for 60 optical spectra.« less

Exploring pathway interactions in insulin resistant mouse liver

PubMed Central

2011-01-01

Background Complex phenotypes such as insulin resistance involve different biological pathways that may interact and influence each other. Interpretation of related experimental data would be facilitated by identifying relevant pathway interactions in the context of the dataset. Results We developed an analysis approach to study interactions between pathways by integrating gene and protein interaction networks, biological pathway information and high-throughput data. This approach was applied to a transcriptomics dataset to investigate pathway interactions in insulin resistant mouse liver in response to a glucose challenge. We identified regulated pathway interactions at different time points following the glucose challenge and also studied the underlying protein interactions to find possible mechanisms and key proteins involved in pathway cross-talk. A large number of pathway interactions were found for the comparison between the two diet groups at t = 0. The initial response to the glucose challenge (t = 0.6) was typed by an acute stress response and pathway interactions showed large overlap between the two diet groups, while the pathway interaction networks for the late response were more dissimilar. Conclusions Studying pathway interactions provides a new perspective on the data that complements established pathway analysis methods such as enrichment analysis. This study provided new insights in how interactions between pathways may be affected by insulin resistance. In addition, the analysis approach described here can be generally applied to different types of high-throughput data and will therefore be useful for analysis of other complex datasets as well. PMID:21843341

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

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...

The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

PubMed Central

Bruskiewich, Richard; Senger, Martin; Davenport, Guy; Ruiz, Manuel; Rouard, Mathieu; Hazekamp, Tom; Takeya, Masaru; Doi, Koji; Satoh, Kouji; Costa, Marcos; Simon, Reinhard; Balaji, Jayashree; Akintunde, Akinnola; Mauleon, Ramil; Wanchana, Samart; Shah, Trushar; Anacleto, Mylah; Portugal, Arllet; Ulat, Victor Jun; Thongjuea, Supat; Braak, Kyle; Ritter, Sebastian; Dereeper, Alexis; Skofic, Milko; Rojas, Edwin; Martins, Natalia; Pappas, Georgios; Alamban, Ryan; Almodiel, Roque; Barboza, Lord Hendrix; Detras, Jeffrey; Manansala, Kevin; Mendoza, Michael Jonathan; Morales, Jeffrey; Peralta, Barry; Valerio, Rowena; Zhang, Yi; Gregorio, Sergio; Hermocilla, Joseph; Echavez, Michael; Yap, Jan Michael; Farmer, Andrew; Schiltz, Gary; Lee, Jennifer; Casstevens, Terry; Jaiswal, Pankaj; Meintjes, Ayton; Wilkinson, Mark; Good, Benjamin; Wagner, James; Morris, Jane; Marshall, David; Collins, Anthony; Kikuchi, Shoshi; Metz, Thomas; McLaren, Graham; van Hintum, Theo

2008-01-01

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making. PMID:18483570

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

The impact of the condenser on cytogenetic image quality in digital microscope system.

PubMed

Ren, Liqiang; Li, Zheng; Li, Yuhua; Zheng, Bin; Li, Shibo; Chen, Xiaodong; Liu, Hong

2013-01-01

Optimizing operational parameters of the digital microscope system is an important technique to acquire high quality cytogenetic images and facilitate the process of karyotyping so that the efficiency and accuracy of diagnosis can be improved. This study investigated the impact of the condenser on cytogenetic image quality and system working performance using a prototype digital microscope image scanning system. Both theoretical analysis and experimental validations through objectively evaluating a resolution test chart and subjectively observing large numbers of specimen were conducted. The results show that the optimal image quality and large depth of field (DOF) are simultaneously obtained when the numerical aperture of condenser is set as 60%-70% of the corresponding objective. Under this condition, more analyzable chromosomes and diagnostic information are obtained. As a result, the system shows higher working stability and less restriction for the implementation of algorithms such as autofocusing especially when the system is designed to achieve high throughput continuous image scanning. Although the above quantitative results were obtained using a specific prototype system under the experimental conditions reported in this paper, the presented evaluation methodologies can provide valuable guidelines for optimizing operational parameters in cytogenetic imaging using the high throughput continuous scanning microscopes in clinical practice.

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

DOT National Transportation Integrated Search

2013-10-01

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

iLAP: a workflow-driven software for experimental protocol development, data acquisition and analysis

PubMed Central

2009-01-01

Background In recent years, the genome biology community has expended considerable effort to confront the challenges of managing heterogeneous data in a structured and organized way and developed laboratory information management systems (LIMS) for both raw and processed data. On the other hand, electronic notebooks were developed to record and manage scientific data, and facilitate data-sharing. Software which enables both, management of large datasets and digital recording of laboratory procedures would serve a real need in laboratories using medium and high-throughput techniques. Results We have developed iLAP (Laboratory data management, Analysis, and Protocol development), a workflow-driven information management system specifically designed to create and manage experimental protocols, and to analyze and share laboratory data. The system combines experimental protocol development, wizard-based data acquisition, and high-throughput data analysis into a single, integrated system. We demonstrate the power and the flexibility of the platform using a microscopy case study based on a combinatorial multiple fluorescence in situ hybridization (m-FISH) protocol and 3D-image reconstruction. iLAP is freely available under the open source license AGPL from http://genome.tugraz.at/iLAP/. Conclusion iLAP is a flexible and versatile information management system, which has the potential to close the gap between electronic notebooks and LIMS and can therefore be of great value for a broad scientific community. PMID:19941647

A versatile and efficient high-throughput cloning tool for structural biology.

PubMed

Geertsma, Eric R; Dutzler, Raimund

2011-04-19

Methods for the cloning of large numbers of open reading frames into expression vectors are of critical importance for challenging structural biology projects. Here we describe a system termed fragment exchange (FX) cloning that facilitates the high-throughput generation of expression constructs. The method is based on a class IIS restriction enzyme and negative selection markers. FX cloning combines attractive features of established recombination- and ligation-independent cloning methods: It allows the straightforward transfer of an open reading frame into a variety of expression vectors and is highly efficient and very economic in its use. In addition, FX cloning avoids the common but undesirable feature of significantly extending target open reading frames with cloning related sequences, as it leaves a minimal seam of only a single extra amino acid to either side of the protein. The method has proven to be very robust and suitable for all common pro- and eukaryotic expression systems. It considerably speeds up the generation of expression constructs compared to traditional methods and thus facilitates a broader expression screening.

Bacterial diversity of the Colombian fermented milk "Suero Costeño" assessed by culturing and high-throughput sequencing and DGGE analysis of 16S rRNA gene amplicons.

PubMed

Motato, Karina Edith; Milani, Christian; Ventura, Marco; Valencia, Francia Elena; Ruas-Madiedo, Patricia; Delgado, Susana

2017-12-01

"Suero Costeño" (SC) is a traditional soured cream elaborated from raw milk in the Northern-Caribbean coast of Colombia. The natural microbiota that characterizes this popular Colombian fermented milk is unknown, although several culturing studies have previously been attempted. In this work, the microbiota associated with SC from three manufacturers in two regions, "Planeta Rica" (Córdoba) and "Caucasia" (Antioquia), was analysed by means of culturing methods in combination with high-throughput sequencing and DGGE analysis of 16S rRNA gene amplicons. The bacterial ecosystem of SC samples was revealed to be composed of lactic acid bacteria belonging to the Streptococcaceae and Lactobacillaceae families; the proportions and genera varying among manufacturers and region of elaboration. Members of the Lactobacillus acidophilus group, Lactocococcus lactis, Streptococcus infantarius and Streptococcus salivarius characterized this artisanal product. In comparison with culturing, the use of molecular in deep culture-independent techniques provides a more realistic picture of the overall bacterial communities residing in SC. Besides the descriptive purpose, these approaches will facilitate a rational strategy to follow (culture media and growing conditions) for the isolation of indigenous strains that allow standardization in the manufacture of SC. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-07-05

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

High-throughput gene mapping in Caenorhabditis elegans.

PubMed

Swan, Kathryn A; Curtis, Damian E; McKusick, Kathleen B; Voinov, Alexander V; Mapa, Felipa A; Cancilla, Michael R

2002-07-01

Positional cloning of mutations in model genetic systems is a powerful method for the identification of targets of medical and agricultural importance. To facilitate the high-throughput mapping of mutations in Caenorhabditis elegans, we have identified a further 9602 putative new single nucleotide polymorphisms (SNPs) between two C. elegans strains, Bristol N2 and the Hawaiian mapping strain CB4856, by sequencing inserts from a CB4856 genomic DNA library and using an informatics pipeline to compare sequences with the canonical N2 genomic sequence. When combined with data from other laboratories, our marker set of 17,189 SNPs provides even coverage of the complete worm genome. To date, we have confirmed >1099 evenly spaced SNPs (one every 91 +/- 56 kb) across the six chromosomes and validated the utility of our SNP marker set and new fluorescence polarization-based genotyping methods for systematic and high-throughput identification of genes in C. elegans by cloning several proprietary genes. We illustrate our approach by recombination mapping and confirmation of the mutation in the cloned gene, dpy-18.

TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data.

PubMed

Lim, Jae Hyun; Lee, Soo Youn; Kim, Ju Han

2017-03-01

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

Generation and Characterization of Neurogeninl-GFP Transgenic Medaka for High Throughput Developmental Neurotoxicity Screening

EPA Science Inventory

Fish models such as zebrafish and medaka are increasingly used as alternatives to rodents in developmental and toxicological studies. These developmental and toxicological studies can be facilitated by the use of transgenic reporters that permit the real-time, noninvasive observa...

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.

Genomic-assisted haplotype analysis and the development of high-throughput SNP markers for salinity tolerance in soybean

PubMed Central

Patil, Gunvant; Do, Tuyen; Vuong, Tri D.; Valliyodan, Babu; Lee, Jeong-Dong; Chaudhary, Juhi; Shannon, J. Grover; Nguyen, Henry T.

2016-01-01

Soil salinity is a limiting factor of crop yield. The soybean is sensitive to soil salinity, and a dominant gene, Glyma03g32900 is primarily responsible for salt-tolerance. The identification of high throughput and robust markers as well as the deployment of salt-tolerant cultivars are effective approaches to minimize yield loss under saline conditions. We utilized high quality (15x) whole-genome resequencing (WGRS) on 106 diverse soybean lines and identified three major structural variants and allelic variation in the promoter and genic regions of the GmCHX1 gene. The discovery of single nucleotide polymorphisms (SNPs) associated with structural variants facilitated the design of six KASPar assays. Additionally, haplotype analysis and pedigree tracking of 93 U.S. ancestral lines were performed using publically available WGRS datasets. Identified SNP markers were validated, and a strong correlation was observed between the genotype and salt treatment phenotype (leaf scorch, chlorophyll content and Na+ accumulation) using a panel of 104 soybean lines and, an interspecific bi-parental population (F8) from PI483463 x Hutcheson. These markers precisely identified salt-tolerant/sensitive genotypes (>91%), and different structural-variants (>98%). These SNP assays, supported by accurate phenotyping, haplotype analyses and pedigree tracking information, will accelerate marker-assisted selection programs to enhance the development of salt-tolerant soybean cultivars. PMID:26781337

High-throughput physical mapping of chromosomes using automated in situ hybridization.

PubMed

George, Phillip; Sharakhova, Maria V; Sharakhov, Igor V

2012-06-28

Projects to obtain whole-genome sequences for 10,000 vertebrate species and for 5,000 insect and related arthropod species are expected to take place over the next 5 years. For example, the sequencing of the genomes for 15 malaria mosquitospecies is currently being done using an Illumina platform. This Anopheles species cluster includes both vectors and non-vectors of malaria. When the genome assemblies become available, researchers will have the unique opportunity to perform comparative analysis for inferring evolutionary changes relevant to vector ability. However, it has proven difficult to use next-generation sequencing reads to generate high-quality de novo genome assemblies. Moreover, the existing genome assemblies for Anopheles gambiae, although obtained using the Sanger method, are gapped or fragmented. Success of comparative genomic analyses will be limited if researchers deal with numerous sequencing contigs, rather than with chromosome-based genome assemblies. Fragmented, unmapped sequences create problems for genomic analyses because: (i) unidentified gaps cause incorrect or incomplete annotation of genomic sequences; (ii) unmapped sequences lead to confusion between paralogous genes and genes from different haplotypes; and (iii) the lack of chromosome assignment and orientation of the sequencing contigs does not allow for reconstructing rearrangement phylogeny and studying chromosome evolution. Developing high-resolution physical maps for species with newly sequenced genomes is a timely and cost-effective investment that will facilitate genome annotation, evolutionary analysis, and re-sequencing of individual genomes from natural populations. Here, we present innovative approaches to chromosome preparation, fluorescent in situ hybridization (FISH), and imaging that facilitate rapid development of physical maps. Using An. gambiae as an example, we demonstrate that the development of physical chromosome maps can potentially improve genome assemblies and, thus, the quality of genomic analyses. First, we use a high-pressure method to prepare polytene chromosome spreads. This method, originally developed for Drosophila, allows the user to visualize more details on chromosomes than the regular squashing technique. Second, a fully automated, front-end system for FISH is used for high-throughput physical genome mapping. The automated slide staining system runs multiple assays simultaneously and dramatically reduces hands-on time. Third, an automatic fluorescent imaging system, which includes a motorized slide stage, automatically scans and photographs labeled chromosomes after FISH. This system is especially useful for identifying and visualizing multiple chromosomal plates on the same slide. In addition, the scanning process captures a more uniform FISH result. Overall, the automated high-throughput physical mapping protocol is more efficient than a standard manual protocol.

A modular toolset for recombination transgenesis and neurogenetic analysis of Drosophila.

PubMed

Wang, Ji-Wu; Beck, Erin S; McCabe, Brian D

2012-01-01

Transgenic Drosophila have contributed extensively to our understanding of nervous system development, physiology and behavior in addition to being valuable models of human neurological disease. Here, we have generated a novel series of modular transgenic vectors designed to optimize and accelerate the production and analysis of transgenes in Drosophila. We constructed a novel vector backbone, pBID, that allows both phiC31 targeted transgene integration and incorporates insulator sequences to ensure specific and uniform transgene expression. Upon this framework, we have built a series of constructs that are either backwards compatible with existing restriction enzyme based vectors or utilize Gateway recombination technology for high-throughput cloning. These vectors allow for endogenous promoter or Gal4 targeted expression of transgenic proteins with or without fluorescent protein or epitope tags. In addition, we have generated constructs that facilitate transgenic splice isoform specific RNA inhibition of gene expression. We demonstrate the utility of these constructs to analyze proteins involved in nervous system development, physiology and neurodegenerative disease. We expect that these reagents will facilitate the proficiency and sophistication of Drosophila genetic analysis in both the nervous system and other tissues.

Application of resequencing to rice genomics, functional genomics and evolutionary analysis

PubMed Central

2014-01-01

Rice is a model system used for crop genomics studies. The completion of the rice genome draft sequences in 2002 not only accelerated functional genome studies, but also initiated a new era of resequencing rice genomes. Based on the reference genome in rice, next-generation sequencing (NGS) using the high-throughput sequencing system can efficiently accomplish whole genome resequencing of various genetic populations and diverse germplasm resources. Resequencing technology has been effectively utilized in evolutionary analysis, rice genomics and functional genomics studies. This technique is beneficial for both bridging the knowledge gap between genotype and phenotype and facilitating molecular breeding via gene design in rice. Here, we also discuss the limitation, application and future prospects of rice resequencing. PMID:25006357

A Simple Method for High Throughput Chemical Screening in Caenorhabditis Elegans

PubMed Central

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

2018-01-01

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

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

ScienceCinema

Athavale, Ajay

2018-01-04

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

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-08-09

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

Automated analysis of brain activity for seizure detection in zebrafish models of epilepsy.

PubMed

Hunyadi, Borbála; Siekierska, Aleksandra; Sourbron, Jo; Copmans, Daniëlle; de Witte, Peter A M

2017-08-01

Epilepsy is a chronic neurological condition, with over 30% of cases unresponsive to treatment. Zebrafish larvae show great potential to serve as an animal model of epilepsy in drug discovery. Thanks to their high fecundity and relatively low cost, they are amenable to high-throughput screening. However, the assessment of seizure occurrences in zebrafish larvae remains a bottleneck, as visual analysis is subjective and time-consuming. For the first time, we present an automated algorithm to detect epileptic discharges in single-channel local field potential (LFP) recordings in zebrafish. First, candidate seizure segments are selected based on their energy and length. Afterwards, discriminative features are extracted from each segment. Using a labeled dataset, a support vector machine (SVM) classifier is trained to learn an optimal feature mapping. Finally, this SVM classifier is used to detect seizure segments in new signals. We tested the proposed algorithm both in a chemically-induced seizure model and a genetic epilepsy model. In both cases, the algorithm delivered similar results to visual analysis and found a significant difference in number of seizures between the epileptic and control group. Direct comparison with multichannel techniques or methods developed for different animal models is not feasible. Nevertheless, a literature review shows that our algorithm outperforms state-of-the-art techniques in terms of accuracy, precision and specificity, while maintaining a reasonable sensitivity. Our seizure detection system is a generic, time-saving and objective method to analyze zebrafish LPF, which can replace visual analysis and facilitate true high-throughput studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Implementation of next generation sequencing for high-throughput pathogen detection in sugarcane introductions grown in quarantine

USDA-ARS?s Scientific Manuscript database

The USDA-APHIS Plant Germplasm Quarantine Program (PGQP) safeguards U.S. agriculture and natural resources against the entry, establishment, and spread of economically and environmentally significant pathogens, and facilitates the safe international movement of propagative plant parts. PGQP is the o...

Applications and Case Studies of the Next-Generation Sequencing Technologies in Food, Nutrition and Agriculture.

USDA-ARS?s Scientific Manuscript database

Next-generation sequencing technologies are able to produce high-throughput short sequence reads in a cost-effective fashion. The emergence of these technologies has not only facilitated genome sequencing but also changed the landscape of life sciences. Here I survey their major applications ranging...

Recent Applications of DNA Sequencing Technologies in Food, Nutrition and Agriculture

USDA-ARS?s Scientific Manuscript database

Next-generation DNA sequencing technologies are able to produce millions of short sequence reads in a high-throughput, cost-effective fashion. The emergence of these technologies has not only facilitated genome sequencing but also changed the landscape of life sciences. This review surveys their rec...

Next generation sequencers: methods and applications in food-borne pathogens

USDA-ARS?s Scientific Manuscript database

Next generation sequencers are able to produce millions of short sequence reads in a high-throughput, low-cost way. The emergence of these technologies has not only facilitated genome sequencing but also started to change the landscape of life sciences. This chapter will survey their methods and app...

Prioritizing Environmental Chemicals for Obesity and Diabetes Outcomes Research: A Screening Approach Using ToxCast™ High-Throughput Data

PubMed Central

Auerbach, Scott; Filer, Dayne; Reif, David; Walker, Vickie; Holloway, Alison C.; Schlezinger, Jennifer; Srinivasan, Supriya; Svoboda, Daniel; Judson, Richard; Bucher, John R.; Thayer, Kristina A.

2016-01-01

Background: Diabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program. Objectives: Our aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data. Methods: We identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and β cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest. Discussion: The results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform. Conclusions: More research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses. Citation: Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141–1154; http://dx.doi.org/10.1289/ehp.1510456 PMID:26978842

Prioritizing Environmental Chemicals for Obesity and Diabetes Outcomes Research: A Screening Approach Using ToxCast™ High-Throughput Data.

PubMed

Auerbach, Scott; Filer, Dayne; Reif, David; Walker, Vickie; Holloway, Alison C; Schlezinger, Jennifer; Srinivasan, Supriya; Svoboda, Daniel; Judson, Richard; Bucher, John R; Thayer, Kristina A

2016-08-01

Diabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program. Our aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data. We identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and β cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest. The results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform. More research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses. Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141-1154; http://dx.doi.org/10.1289/ehp.1510456.

A high-throughput lab-on-a-chip interface for zebrafish embryo tests in drug discovery and ecotoxicology

NASA Astrophysics Data System (ADS)

Zhu, Feng; Akagi, Jin; Hall, Chris J.; Crosier, Kathryn E.; Crosier, Philip S.; Delaage, Pierre; Wlodkowic, Donald

2013-12-01

Drug discovery screenings performed on zebrafish embryos mirror with a high level of accuracy. The tests usually performed on mammalian animal models, and the fish embryo toxicity assay (FET) is one of the most promising alternative approaches to acute ecotoxicity testing with adult fish. Notwithstanding this, conventional methods utilising 96-well microtiter plates and manual dispensing of fish embryos are very time-consuming. They rely on laborious and iterative manual pipetting that is a main source of analytical errors and low throughput. In this work, we present development of a miniaturised and high-throughput Lab-on-a-Chip (LOC) platform for automation of FET assays. The 3D high-density LOC array was fabricated in poly-methyl methacrylate (PMMA) transparent thermoplastic using infrared laser micromachining while the off-chip interfaces were fabricated using additive manufacturing processes (FDM and SLA). The system's design facilitates rapid loading and immobilization of a large number of embryos in predefined clusters of traps during continuous microperfusion of drugs/toxins. It has been conceptually designed to seamlessly interface with both upright and inverted fluorescent imaging systems and also to directly interface with conventional microtiter plate readers that accept 96-well plates. We also present proof-of-concept interfacing with a high-speed imaging cytometer Plate RUNNER HD® capable of multispectral image acquisition with resolution of up to 8192 x 8192 pixels and depth of field of about 40 μm. Furthermore, we developed a miniaturized and self-contained analytical device interfaced with a miniaturized USB microscope. This system modification is capable of performing rapid imaging of multiple embryos at a low resolution for drug toxicity analysis.

Rapid analysis and exploration of fluorescence microscopy images.

PubMed

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

2014-03-19

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

Fast and Efficient Fragment-Based Lead Generation by Fully Automated Processing and Analysis of Ligand-Observed NMR Binding Data.

PubMed

Peng, Chen; Frommlet, Alexandra; Perez, Manuel; Cobas, Carlos; Blechschmidt, Anke; Dominguez, Santiago; Lingel, Andreas

2016-04-14

NMR binding assays are routinely applied in hit finding and validation during early stages of drug discovery, particularly for fragment-based lead generation. To this end, compound libraries are screened by ligand-observed NMR experiments such as STD, T1ρ, and CPMG to identify molecules interacting with a target. The analysis of a high number of complex spectra is performed largely manually and therefore represents a limiting step in hit generation campaigns. Here we report a novel integrated computational procedure that processes and analyzes ligand-observed proton and fluorine NMR binding data in a fully automated fashion. A performance evaluation comparing automated and manual analysis results on (19)F- and (1)H-detected data sets shows that the program delivers robust, high-confidence hit lists in a fraction of the time needed for manual analysis and greatly facilitates visual inspection of the associated NMR spectra. These features enable considerably higher throughput, the assessment of larger libraries, and shorter turn-around times.

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.

Alignment-free design of highly discriminatory diagnostic primer sets for Escherichia coli O104:H4 outbreak strains.

PubMed

Pritchard, Leighton; Holden, Nicola J; Bielaszewska, Martina; Karch, Helge; Toth, Ian K

2012-01-01

An Escherichia coli O104:H4 outbreak in Germany in summer 2011 caused 53 deaths, over 4000 individual infections across Europe, and considerable economic, social and political impact. This outbreak was the first in a position to exploit rapid, benchtop high-throughput sequencing (HTS) technologies and crowdsourced data analysis early in its investigation, establishing a new paradigm for rapid response to disease threats. We describe a novel strategy for design of diagnostic PCR primers that exploited this rapid draft bacterial genome sequencing to distinguish between E. coli O104:H4 outbreak isolates and other pathogenic E. coli isolates, including the historical hæmolytic uræmic syndrome (HUSEC) E. coli HUSEC041 O104:H4 strain, which possesses the same serotype as the outbreak isolates. Primers were designed using a novel alignment-free strategy against eleven draft whole genome assemblies of E. coli O104:H4 German outbreak isolates from the E. coli O104:H4 Genome Analysis Crowd-Sourcing Consortium website, and a negative sequence set containing 69 E. coli chromosome and plasmid sequences from public databases. Validation in vitro against 21 'positive' E. coli O104:H4 outbreak and 32 'negative' non-outbreak EHEC isolates indicated that individual primer sets exhibited 100% sensitivity for outbreak isolates, with false positive rates of between 9% and 22%. A minimal combination of two primers discriminated between outbreak and non-outbreak E. coli isolates with 100% sensitivity and 100% specificity. Draft genomes of isolates of disease outbreak bacteria enable high throughput primer design and enhanced diagnostic performance in comparison to traditional molecular assays. Future outbreak investigations will be able to harness HTS rapidly to generate draft genome sequences and diagnostic primer sets, greatly facilitating epidemiology and clinical diagnostics. We expect that high throughput primer design strategies will enable faster, more precise responses to future disease outbreaks of bacterial origin, and help to mitigate their societal impact.

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

PubMed

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

2013-03-01

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

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.

Web-based visual analysis for high-throughput genomics

PubMed Central

2013-01-01

Background Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues. Results We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy. Conclusions Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the framework are useful tools for high-throughput genomics experiments. PMID:23758618

High Throughput Sequence Analysis for Disease Resistance in Maize

USDA-ARS?s Scientific Manuscript database

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

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...

Development of rapid and sensitive high throughput pharmacologic assays for marine phycotoxins.

PubMed

Van Dolah, F M; Finley, E L; Haynes, B L; Doucette, G J; Moeller, P D; Ramsdell, J S

1994-01-01

The lack of rapid, high throughput assays is a major obstacle to many aspects of research on marine phycotoxins. Here we describe the application of microplate scintillation technology to develop high throughput assays for several classes of marine phycotoxin based on their differential pharmacologic actions. High throughput "drug discovery" format microplate receptor binding assays developed for brevetoxins/ciguatoxins and for domoic acid are described. Analysis for brevetoxins/ciguatoxins is carried out by binding competition with [3H] PbTx-3 for site 5 on the voltage dependent sodium channel in rat brain synaptosomes. Analysis of domoic acid is based on binding competition with [3H] kainic acid for the kainate/quisqualate glutamate receptor using frog brain synaptosomes. In addition, a high throughput microplate 45Ca flux assay for determination of maitotoxins is described. These microplate assays can be completed within 3 hours, have sensitivities of less than 1 ng, and can analyze dozens of samples simultaneously. The assays have been demonstrated to be useful for assessing algal toxicity and for assay-guided purification of toxins, and are applicable to the detection of biotoxins in seafood.

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

PubMed

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

2017-05-15

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

Automation of a Nile red staining assay enables high throughput quantification of microalgal lipid production.

PubMed

Morschett, Holger; Wiechert, Wolfgang; Oldiges, Marco

2016-02-09

Within the context of microalgal lipid production for biofuels and bulk chemical applications, specialized higher throughput devices for small scale parallelized cultivation are expected to boost the time efficiency of phototrophic bioprocess development. However, the increasing number of possible experiments is directly coupled to the demand for lipid quantification protocols that enable reliably measuring large sets of samples within short time and that can deal with the reduced sample volume typically generated at screening scale. To meet these demands, a dye based assay was established using a liquid handling robot to provide reproducible high throughput quantification of lipids with minimized hands-on-time. Lipid production was monitored using the fluorescent dye Nile red with dimethyl sulfoxide as solvent facilitating dye permeation. The staining kinetics of cells at different concentrations and physiological states were investigated to successfully down-scale the assay to 96 well microtiter plates. Gravimetric calibration against a well-established extractive protocol enabled absolute quantification of intracellular lipids improving precision from ±8 to ±2 % on average. Implementation into an automated liquid handling platform allows for measuring up to 48 samples within 6.5 h, reducing hands-on-time to a third compared to manual operation. Moreover, it was shown that automation enhances accuracy and precision compared to manual preparation. It was revealed that established protocols relying on optical density or cell number for biomass adjustion prior to staining may suffer from errors due to significant changes of the cells' optical and physiological properties during cultivation. Alternatively, the biovolume was used as a measure for biomass concentration so that errors from morphological changes can be excluded. The newly established assay proved to be applicable for absolute quantification of algal lipids avoiding limitations of currently established protocols, namely biomass adjustment and limited throughput. Automation was shown to improve data reliability, as well as experimental throughput simultaneously minimizing the needed hands-on-time to a third. Thereby, the presented protocol meets the demands for the analysis of samples generated by the upcoming generation of devices for higher throughput phototrophic cultivation and thereby contributes to boosting the time efficiency for setting up algae lipid production processes.

High-throughput genotyping for species identification and diversity assessment in germplasm collections.

PubMed

Mason, Annaliese S; Zhang, Jing; Tollenaere, Reece; Vasquez Teuber, Paula; Dalton-Morgan, Jessica; Hu, Liyong; Yan, Guijun; Edwards, David; Redden, Robert; Batley, Jacqueline

2015-09-01

Germplasm collections provide an extremely valuable resource for breeders and researchers. However, misclassification of accessions by species often hinders the effective use of these collections. We propose that use of high-throughput genotyping tools can provide a fast, efficient and cost-effective way of confirming species in germplasm collections, as well as providing valuable genetic diversity data. We genotyped 180 Brassicaceae samples sourced from the Australian Grains Genebank across the recently released Illumina Infinium Brassica 60K SNP array. Of these, 76 were provided on the basis of suspected misclassification and another 104 were sourced independently from the germplasm collection. Presence of the A- and C-genomes combined with principle components analysis clearly separated Brassica rapa, B. oleracea, B. napus, B. carinata and B. juncea samples into distinct species groups. Several lines were further validated using chromosome counts. Overall, 18% of samples (32/180) were misclassified on the basis of species. Within these 180 samples, 23/76 (30%) supplied on the basis of suspected misclassification were misclassified, and 9/105 (9%) of the samples randomly sourced from the Australian Grains Genebank were misclassified. Surprisingly, several individuals were also found to be the product of interspecific hybridization events. The SNP (single nucleotide polymorphism) array proved effective at confirming species, and provided useful information related to genetic diversity. As similar genomic resources become available for different crops, high-throughput molecular genotyping will offer an efficient and cost-effective method to screen germplasm collections worldwide, facilitating more effective use of these valuable resources by breeders and researchers. © 2015 John Wiley & Sons Ltd.

High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

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

Pan, Jian-Bo; Ji, Nan; Pan, Wen

2014-01-01

Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPsmore » that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified.« less

Sample flow switching techniques on microfluidic chips.

PubMed

Pan, Yu-Jen; Lin, Jin-Jie; Luo, Win-Jet; Yang, Ruey-Jen

2006-02-15

This paper presents an experimental investigation into electrokinetically focused flow injection for bio-analytical applications. A novel microfluidic device for microfluidic sample handling is presented. The microfluidic chip is fabricated on glass substrates using conventional photolithographic and chemical etching processes and is bonded using a high-temperature fusion method. The proposed valve-less device is capable not only of directing a single sample flow to a specified output port, but also of driving multiple samples to separate outlet channels or even to a single outlet to facilitate sample mixing. The experimental results confirm that the sample flow can be electrokinetically pre-focused into a narrow stream and guided to the desired outlet port by means of a simple control voltage model. The microchip presented within this paper has considerable potential for use in a variety of applications, including high-throughput chemical analysis, cell fusion, fraction collection, sample mixing, and many other applications within the micro-total-analysis systems field.

Perspectives on genetically modified crops and food detection.

PubMed

Lin, Chih-Hui; Pan, Tzu-Ming

2016-01-01

Genetically modified (GM) crops are a major product of the global food industry. From 1996 to 2014, 357 GM crops were approved and the global value of the GM crop market reached 35% of the global commercial seed market in 2014. However, the rapid growth of the GM crop-based industry has also created controversies in many regions, including the European Union, Egypt, and Taiwan. The effective detection and regulation of GM crops/foods are necessary to reduce the impact of these controversies. In this review, the status of GM crops and the technology for their detection are discussed. As the primary gap in GM crop regulation exists in the application of detection technology to field regulation, efforts should be made to develop an integrated, standardized, and high-throughput GM crop detection system. We propose the development of an integrated GM crop detection system, to be used in combination with a standardized international database, a decision support system, high-throughput DNA analysis, and automated sample processing. By integrating these technologies, we hope that the proposed GM crop detection system will provide a method to facilitate comprehensive GM crop regulation. Copyright © 2015. Published by Elsevier B.V.

A Novel Hepadnavirus Identified in an Immunocompromised Domestic Cat in Australia.

PubMed

Aghazadeh, Mahdis; Shi, Mang; Barrs, Vanessa R; McLuckie, Alicia J; Lindsay, Scott A; Jameson, Barbara; Hampson, Bronte; Holmes, Edward C; Beatty, Julia A

2018-05-17

High-throughput transcriptome sequencing allows for the unbiased detection of viruses in host tissues. The application of this technique to immunosuppressed animals facilitates the detection of viruses that might otherwise be excluded or contained in immunocompetent individuals. To identify potential viral pathogens infecting domestic cats we performed high-throughput transcriptome sequencing of tissues from cats infected with feline immunodeficiency virus (FIV). A novel member of the Hepadnaviridae , tentatively named domestic cat hepadnavirus, was discovered in a lymphoma sample and its complete 3187 bp genome characterized. Phylogenetic analysis placed the domestic cat hepadnavirus as a divergent member of mammalian orthohepadnaviruses that exhibits no close relationship to any other virus. DNA extracted from whole blood from pet cats was positive for the novel hepadnavirus by PCR in 6 of 60 (10%) FIV-infected cats and 2 of 63 (3.2%) FIV-uninfected cats. The higher prevalence of hepadnavirus viraemia detected in FIV-infected cats mirrors that seen in human immunodeficiency virus-infected humans coinfected with hepatitis B virus. In summary, we report the first hepadnavirus infection in a carnivore and the first in a companion animal. The natural history, epidemiology and pathogenic potential of domestic cat hepadnavirus merits additional investigation.

Molecular Markers and Cotton Genetic Improvement: Current Status and Future Prospects

PubMed Central

Malik, Waqas; Iqbal, Muhammad Zaffar; Ali Khan, Asif; Qayyum, Abdul; Ali Abid, Muhammad; Noor, Etrat; Qadir Ahmad, Muhammad; Hasan Abbasi, Ghulam

2014-01-01

Narrow genetic base and complex allotetraploid genome of cotton (Gossypium hirsutum L.) is stimulating efforts to avail required polymorphism for marker based breeding. The availability of draft genome sequence of G. raimondii and G. arboreum and next generation sequencing (NGS) technologies facilitated the development of high-throughput marker technologies in cotton. The concepts of genetic diversity, QTL mapping, and marker assisted selection (MAS) are evolving into more efficient concepts of linkage disequilibrium, association mapping, and genomic selection, respectively. The objective of the current review is to analyze the pace of evolution in the molecular marker technologies in cotton during the last ten years into the following four areas: (i) comparative analysis of low- and high-throughput marker technologies available in cotton, (ii) genetic diversity in the available wild and improved gene pools of cotton, (iii) identification of the genomic regions within cotton genome underlying economic traits, and (iv) marker based selection methodologies. Moreover, the applications of marker technologies to enhance the breeding efficiency in cotton are also summarized. Aforementioned genomic technologies and the integration of several other omics resources are expected to enhance the cotton productivity and meet the global fiber quantity and quality demands. PMID:25401149

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...

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

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

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

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

2009-07-20

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

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

PubMed

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

2016-01-15

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

Diagnostic Markers of Ovarian Cancer by High-Throughput Antigen Cloning and Detection on Arrays

PubMed Central

Chatterjee, Madhumita; Mohapatra, Saroj; Ionan, Alexei; Bawa, Gagandeep; Ali-Fehmi, Rouba; Wang, Xiaoju; Nowak, James; Ye, Bin; Nahhas, Fatimah A.; Lu, Karen; Witkin, Steven S.; Fishman, David; Munkarah, Adnan; Morris, Robert; Levin, Nancy K.; Shirley, Natalie N.; Tromp, Gerard; Abrams, Judith; Draghici, Sorin; Tainsky, Michael A.

2008-01-01

A noninvasive screening test would significantly facilitate early detection of epithelial ovarian cancer. This study used a combination of high-throughput selection and array-based serologic detection of many antigens indicative of the presence of cancer, thereby using the immune system as a biosensor. This high-throughput selection involved biopanning of an ovarian cancer phage display library using serum immunoglobulins from an ovarian cancer patient as bait. Protein macroarrays containing 480 of these selected antigen clones revealed 65 clones that interacted with immunoglobulins in sera from 32 ovarian cancer patients but not with sera from 25 healthy women or 14 patients having other benign or malignant gynecologic diseases. Sequence analysis data of these 65 clones revealed 62 different antigens. Among the markers, we identified some known antigens, including RCAS1, signal recognition protein-19, AHNAK-related sequence, nuclear autoantogenic sperm protein, Nijmegen breakage syndrome 1 (Nibrin), ribosomal protein L4, Homo sapiens KIAA0419 gene product, eukaryotic initiation factor 5A, and casein kinase II, as well as many previously uncharacterized antigenic gene products. Using these 65 antigens on protein microarrays, we trained neural networks on two-color fluorescent detection of serum IgG binding and found an average sensitivity and specificity of 55% and 98%, respectively. In addition, the top 6 of the most specific clones resulted in an average sensitivity and specificity of 32% and 94%, respectively. This global approach to antigenic profiling, epitomics, has applications to cancer and autoimmune diseases for diagnostic and therapeutic studies. Further work with larger panels of antigens should provide a comprehensive set of markers with sufficient sensitivity and specificity suitable for clinical testing in high-risk populations. PMID:16424057

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

The Impact of the Condenser on Cytogenetic Image Quality in Digital Microscope System

PubMed Central

Ren, Liqiang; Li, Zheng; Li, Yuhua; Zheng, Bin; Li, Shibo; Chen, Xiaodong; Liu, Hong

2013-01-01

Background: Optimizing operational parameters of the digital microscope system is an important technique to acquire high quality cytogenetic images and facilitate the process of karyotyping so that the efficiency and accuracy of diagnosis can be improved. OBJECTIVE: This study investigated the impact of the condenser on cytogenetic image quality and system working performance using a prototype digital microscope image scanning system. Methods: Both theoretical analysis and experimental validations through objectively evaluating a resolution test chart and subjectively observing large numbers of specimen were conducted. Results: The results show that the optimal image quality and large depth of field (DOF) are simultaneously obtained when the numerical aperture of condenser is set as 60%–70% of the corresponding objective. Under this condition, more analyzable chromosomes and diagnostic information are obtained. As a result, the system shows higher working stability and less restriction for the implementation of algorithms such as autofocusing especially when the system is designed to achieve high throughput continuous image scanning. Conclusions: Although the above quantitative results were obtained using a specific prototype system under the experimental conditions reported in this paper, the presented evaluation methodologies can provide valuable guidelines for optimizing operational parameters in cytogenetic imaging using the high throughput continuous scanning microscopes in clinical practice. PMID:23676284

Automating fruit fly Drosophila embryo injection for high throughput transgenic studies

NASA Astrophysics Data System (ADS)

Cornell, E.; Fisher, W. W.; Nordmeyer, R.; Yegian, D.; Dong, M.; Biggin, M. D.; Celniker, S. E.; Jin, J.

2008-01-01

To decipher and manipulate the 14 000 identified Drosophila genes, there is a need to inject a large number of embryos with transgenes. We have developed an automated instrument for high throughput injection of Drosophila embryos. It was built on an inverted microscope, equipped with a motorized xy stage, autofocus, a charge coupled device camera, and an injection needle mounted on a high speed vertical stage. A novel, micromachined embryo alignment device was developed to facilitate the arrangement of a large number of eggs. The control system included intelligent and dynamic imaging and analysis software and an embryo injection algorithm imitating a human operator. Once the injection needle and embryo slide are loaded, the software automatically images and characterizes each embryo and subsequently injects DNA into all suitable embryos. The ability to program needle flushing and monitor needle status after each injection ensures reliable delivery of biomaterials. Using this instrument, we performed a set of transformation injection experiments. The robot achieved injection speeds and transformation efficiencies comparable to those of a skilled human injector. Because it can be programed to allow injection at various locations in the embryo, such as the anterior pole or along the dorsal or ventral axes, this system is also suitable for injection of general biochemicals, including drugs and RNAi.

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

EPA Science Inventory

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-08-01

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

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

PubMed

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

2012-03-01

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

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

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

Luo, Wei; Shabbir, Faizan; Gong, Chao

2015-04-13

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

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.

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

ScienceCinema

Gore, Brooklin

2018-02-01

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

Radiomics: Images Are More than Pictures, They Are Data

PubMed Central

Kinahan, Paul E.; Hricak, Hedvig

2016-01-01

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer. PMID:26579733

Quantification of larval zebrafish motor function in multiwell plates using open-source MATLAB applications.

PubMed

Zhou, Yangzhong; Cattley, Richard T; Cario, Clinton L; Bai, Qing; Burton, Edward A

2014-07-01

This article describes a method to quantify the movements of larval zebrafish in multiwell plates, using the open-source MATLAB applications LSRtrack and LSRanalyze. The protocol comprises four stages: generation of high-quality, flatly illuminated video recordings with exposure settings that facilitate object recognition; analysis of the resulting recordings using tools provided in LSRtrack to optimize tracking accuracy and motion detection; analysis of tracking data using LSRanalyze or custom MATLAB scripts; and implementation of validation controls. The method is reliable, automated and flexible, requires <1 h of hands-on work for completion once optimized and shows excellent signal:noise characteristics. The resulting data can be analyzed to determine the following: positional preference; displacement, velocity and acceleration; and duration and frequency of movement events and rest periods. This approach is widely applicable to the analysis of spontaneous or stimulus-evoked zebrafish larval neurobehavioral phenotypes resulting from a broad array of genetic and environmental manipulations, in a multiwell plate format suitable for high-throughput applications.

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

PubMed Central

Li, Zhijian; Vizeacoumar, Franco J; Bahr, Sondra; Li, Jingjing; Warringer, Jonas; Vizeacoumar, Frederick S; Min, Renqiang; VanderSluis, Benjamin; Bellay, Jeremy; DeVit, Michael; Fleming, James A; Stephens, Andrew; Haase, Julian; Lin, Zhen-Yuan; Baryshnikova, Anastasia; Lu, Hong; Yan, Zhun; Jin, Ke; Barker, Sarah; Datti, Alessandro; Giaever, Guri; Nislow, Corey; Bulawa, Chris; Myers, Chad L; Costanzo, Michael; Gingras, Anne-Claude; Zhang, Zhaolei; Blomberg, Anders; Bloom, Kerry; Andrews, Brenda; Boone, Charles

2012-01-01

Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (~45%) of the 1,101 essential yeast genes, with ~30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes. PMID:21441928

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.

Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples

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

Clair, Geremy; Piehowski, Paul D.; Nicola, Teodora

Global proteomics approaches allow characterization of whole tissue lysates to an impressive depth. However, it is now increasingly recognized that to better understand the complexity of multicellular organisms, global protein profiling of specific spatially defined regions/substructures of tissues (i.e. spatially-resolved proteomics) is essential. Laser capture microdissection (LCM) enables microscopic isolation of defined regions of tissues preserving crucial spatial information. However, current proteomics workflows entail several manual sample preparation steps and are challenged by the microscopic mass-limited samples generated by LCM, and that impact measurement robustness, quantification, and throughput. Here, we coupled LCM with a fully automated sample preparation workflow thatmore » with a single manual step allows: protein extraction, tryptic digestion, peptide cleanup and LC-MS/MS analysis of proteomes from microdissected tissues. Benchmarking against the current state of the art in ultrasensitive global proteomic analysis, our approach demonstrated significant improvements in quantification and throughput. Using our LCM-SNaPP proteomics approach, we characterized to a depth of more than 3,400 proteins, the ontogeny of protein changes during normal lung development in laser capture microdissected alveolar tissue containing ~4,000 cells per sample. Importantly, the data revealed quantitative changes for 350 low abundance transcription factors and signaling molecules, confirming earlier transcript-level observations and defining seven modules of coordinated transcription factor/signaling molecule expression patterns, suggesting that a complex network of temporal regulatory control directs normal lung development with epigenetic regulation fine-tuning pre-natal developmental processes. Our LCM-proteomics approach facilitates efficient, spatially-resolved, ultrasensitive global proteomics analyses in high-throughput that will be enabling for several clinical and biological applications.« less

3D Structure Determination of Native Mammalian Cells using Cryo-FIB and Cryo-electron Tomography

PubMed Central

Wang, Ke; Strunk, Korrinn; Zhao, Gongpu; Gray, Jennifer L.; Zhang, Peijun

2012-01-01

Cryo-electron tomography (cryo-ET) has enabled high resolution three-dimensional (3D) structural analysis of virus and host cell interactions and many cell signaling events; these studies, however, have largely been limited to very thin, peripheral regions of eukaryotic cells or to small prokaryotic cells. Recent efforts to make thin, vitreous sections using cryo-ultramicrotomy have been successful, however, this method is technically very challenging and with many artifacts. Here, we report a simple and robust method for creating in situ, frozen-hydrated cell lamellas using a focused ion beam at cryogenic temperature (cryo-FIB), allowing access to any interior cellular regions of interest. We demonstrate the utility of cryo-FIB with high resolution 3D cellular structures from both bacterial cells and large mammalian cells. The method will not only facilitate high-throughput 3D structural analysis of biological specimens, but is also broadly applicable to sample preparation of thin films and surface materials without the need for FIB “lift-out”. PMID:22796867

Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays

EPA Science Inventory

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

A Modular Toolset for Recombination Transgenesis and Neurogenetic Analysis of Drosophila

PubMed Central

Wang, Ji-Wu; Beck, Erin S.; McCabe, Brian D.

2012-01-01

Transgenic Drosophila have contributed extensively to our understanding of nervous system development, physiology and behavior in addition to being valuable models of human neurological disease. Here, we have generated a novel series of modular transgenic vectors designed to optimize and accelerate the production and analysis of transgenes in Drosophila. We constructed a novel vector backbone, pBID, that allows both phiC31 targeted transgene integration and incorporates insulator sequences to ensure specific and uniform transgene expression. Upon this framework, we have built a series of constructs that are either backwards compatible with existing restriction enzyme based vectors or utilize Gateway recombination technology for high-throughput cloning. These vectors allow for endogenous promoter or Gal4 targeted expression of transgenic proteins with or without fluorescent protein or epitope tags. In addition, we have generated constructs that facilitate transgenic splice isoform specific RNA inhibition of gene expression. We demonstrate the utility of these constructs to analyze proteins involved in nervous system development, physiology and neurodegenerative disease. We expect that these reagents will facilitate the proficiency and sophistication of Drosophila genetic analysis in both the nervous system and other tissues. PMID:22848718

High-Throughput Next-Generation Sequencing of Polioviruses

PubMed Central

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

2016-01-01

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

Automated mini-column solid-phase extraction cleanup for high-throughput analysis of chemical contaminants in foods by low-pressure gas chromatography – tandem mass spectrometry

USDA-ARS?s Scientific Manuscript database

This study demonstrated the application of an automated high-throughput mini-cartridge solid-phase extraction (mini-SPE) cleanup for the rapid low-pressure gas chromatography – tandem mass spectrometry (LPGC-MS/MS) analysis of pesticides and environmental contaminants in QuEChERS extracts of foods. ...

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

DTIC Science & Technology

2016-06-01

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

High-throughput genotyping-by-sequencing facilitates molecular tagging of a novel rust resistance gene, R15, in sunflower (Helianthus annuus L.)

USDA-ARS?s Scientific Manuscript database

The rust virulence gene is co-evolving with the resistance gene in sunflower, leading to the emergence of new physiologic pathotypes. This presents a continuous threat to the sunflower crop necessitating the development of resistant sunflower hybrids providing a more efficient, durable, and environm...

Developing a novel fiber optic fluorescence device for multiplexed high-throughput cytotoxic screening.

PubMed

Lee, Dennis; Barnes, Stephen

2010-01-01

The need for new pharmacological agents is unending. Yet the drug discovery process has changed substantially over the past decade and continues to evolve in response to new technologies. There is presently a high demand to reduce discovery time by improving specific lab disciplines and developing new technology platforms in the area of cell-based assay screening. Here we present the developmental concept and early stage testing of the Ab-Sniffer, a novel fiber optic fluorescence device for high-throughput cytotoxicity screening using an immobilized whole cell approach. The fused silica fibers are chemically functionalized with biotin to provide interaction with fluorescently labeled, streptavidin functionalized alginate-chitosan microspheres. The microspheres are also functionalized with Concanavalin A to facilitate binding to living cells. By using lymphoma cells and rituximab in an adaptation of a well-known cytotoxicity protocol we demonstrate the utility of the Ab-Sniffer for functional screening of potential drug compounds rather than indirect, non-functional screening via binding assay. The platform can be extended to any assay capable of being tied to a fluorescence response including multiple target cells in each well of a multi-well plate for high-throughput screening.

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

PubMed

Kundu, Kousik; Backofen, Rolf

2017-01-01

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

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

USDA-ARS?s Scientific Manuscript database

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

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

EPA Science Inventory

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

Exploration of Panviral Proteome: High-Throughput Cloning and Functional Implications in Virus-host Interactions

PubMed Central

Yu, Xiaobo; Bian, Xiaofang; Throop, Andrea; Song, Lusheng; Moral, Lerys Del; Park, Jin; Seiler, Catherine; Fiacco, Michael; Steel, Jason; Hunter, Preston; Saul, Justin; Wang, Jie; Qiu, Ji; Pipas, James M.; LaBaer, Joshua

2014-01-01

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies. PMID:24955142

Exploration of panviral proteome: high-throughput cloning and functional implications in virus-host interactions.

PubMed

Yu, Xiaobo; Bian, Xiaofang; Throop, Andrea; Song, Lusheng; Moral, Lerys Del; Park, Jin; Seiler, Catherine; Fiacco, Michael; Steel, Jason; Hunter, Preston; Saul, Justin; Wang, Jie; Qiu, Ji; Pipas, James M; LaBaer, Joshua

2014-01-01

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.

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

PubMed

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

2015-11-01

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

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

PubMed

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

2006-08-01

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

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

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

PubMed

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

2018-06-04

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

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

DOE PAGES

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

2016-09-23

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

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

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

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

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

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

PubMed

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

2016-11-14

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

Advances in High-Throughput Speed, Low-Latency Communication for Embedded Instrumentation (7th Annual SFAF Meeting, 2012)

ScienceCinema

Jordan, Scott

2018-01-24

Scott Jordan on "Advances in high-throughput speed, low-latency communication for embedded instrumentation" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.

The development of a general purpose ARM-based processing unit for the ATLAS TileCal sROD

NASA Astrophysics Data System (ADS)

Cox, M. A.; Reed, R.; Mellado, B.

2015-01-01

After Phase-II upgrades in 2022, the data output from the LHC ATLAS Tile Calorimeter will increase significantly. ARM processors are common in mobile devices due to their low cost, low energy consumption and high performance. It is proposed that a cost-effective, high data throughput Processing Unit (PU) can be developed by using several consumer ARM processors in a cluster configuration to allow aggregated processing performance and data throughput while maintaining minimal software design difficulty for the end-user. This PU could be used for a variety of high-level functions on the high-throughput raw data such as spectral analysis and histograms to detect possible issues in the detector at a low level. High-throughput I/O interfaces are not typical in consumer ARM System on Chips but high data throughput capabilities are feasible via the novel use of PCI-Express as the I/O interface to the ARM processors. An overview of the PU is given and the results for performance and throughput testing of four different ARM Cortex System on Chips are presented.

PTESFinder: a computational method to identify post-transcriptional exon shuffling (PTES) events.

PubMed

Izuogu, Osagie G; Alhasan, Abd A; Alafghani, Hani M; Santibanez-Koref, Mauro; Elliott, David J; Elliot, David J; Jackson, Michael S

2016-01-13

Transcripts, which have been subject to Post-transcriptional exon shuffling (PTES), have an exon order inconsistent with the underlying genomic sequence. These have been identified in a wide variety of tissues and cell types from many eukaryotes, and are now known to be mostly circular, cytoplasmic, and non-coding. Although there is no uniformly ascribed function, several have been shown to be involved in gene regulation. Accurate identification of these transcripts can, however, be difficult due to artefacts from a wide variety of sources. Here, we present a computational method, PTESFinder, to identify these transcripts from high throughput RNAseq data. Uniquely, it systematically excludes potential artefacts emanating from pseudogenes, segmental duplications, and template switching, and outputs both PTES and canonical exon junction counts to facilitate comparative analyses. In comparison with four existing methods, PTESFinder achieves highest specificity and comparable sensitivity at a variety of read depths. PTESFinder also identifies between 13 % and 41.6 % more structures, compared to publicly available methods recently used to identify human circular RNAs. With high sensitivity and specificity, user-adjustable filters that target known sources of false positives, and tailored output to facilitate comparison of transcript levels, PTESFinder will facilitate the discovery and analysis of these poorly understood transcripts.

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

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2008-01-01

Background The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms. Conclusion We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens. PMID:18534020

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

Phenotypic approaches to drought in cassava: review

PubMed Central

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

2012-01-01

Cassava is an important crop in Africa, Asia, Latin America, and the Caribbean. Cassava can be produced adequately in drought conditions making it the ideal food security crop in marginal environments. Although cassava can tolerate drought stress, it can be genetically improved to enhance productivity in such environments. Drought adaptation studies in over three decades in cassava have identified relevant mechanisms which have been explored in conventional breeding. Drought is a quantitative trait and its multigenic nature makes it very challenging to effectively manipulate and combine genes in breeding for rapid genetic gain and selection process. Cassava has a long growth cycle of 12–18 months which invariably contributes to a long breeding scheme for the crop. Modern breeding using advances in genomics and improved genotyping, is facilitating the dissection and genetic analysis of complex traits including drought tolerance, thus helping to better elucidate and understand the genetic basis of such traits. A beneficial goal of new innovative breeding strategies is to shorten the breeding cycle using minimized, efficient or fast phenotyping protocols. While high throughput genotyping have been achieved, this is rarely the case for phenotyping for drought adaptation. Some of the storage root phenotyping in cassava are often done very late in the evaluation cycle making selection process very slow. This paper highlights some modified traits suitable for early-growth phase phenotyping that may be used to reduce drought phenotyping cycle in cassava. Such modified traits can significantly complement the high throughput genotyping procedures to fast track breeding of improved drought tolerant varieties. The need for metabolite profiling, improved phenomics to take advantage of next generation sequencing technologies and high throughput phenotyping are basic steps for future direction to improve genetic gain and maximize speed for drought tolerance breeding. PMID:23717282

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.

Courtney E. Payne | NREL

Science.gov Websites

improved and higher throughput methods for analysis of biomass feedstocks Agronomics-using NIR spectroscopy in-house and external client training. She has also developed improved and high-throughput methods

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes.

PubMed

Lochlainn, Seosamh Ó; Amoah, Stephen; Graham, Neil S; Alamer, Khalid; Rios, Juan J; Kurup, Smita; Stoute, Andrew; Hammond, John P; Østergaard, Lars; King, Graham J; White, Phillip J; Broadley, Martin R

2011-12-08

Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

PubMed Central

2011-01-01

Background Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service. PMID:22152063

MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data

PubMed Central

Denis, Jean-Baptiste; Vandenbogaert, Mathias; Caro, Valérie

2016-01-01

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members. PMID:28451381

MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data.

PubMed

Correia, Damien; Doppelt-Azeroual, Olivia; Denis, Jean-Baptiste; Vandenbogaert, Mathias; Caro, Valérie

2015-01-01

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users' input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user's input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy's main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very easily. In the trend of Galaxy, the interface enables the sharing of scientific results to fellow team members.

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

PubMed Central

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

2011-01-01

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

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

Mining collections of compounds with Screening Assistant 2

PubMed Central

2012-01-01

Background High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. Results We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. Conclusions Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/. PMID:23327565

Mining collections of compounds with Screening Assistant 2.

PubMed

Guilloux, Vincent Le; Arrault, Alban; Colliandre, Lionel; Bourg, Stéphane; Vayer, Philippe; Morin-Allory, Luc

2012-08-31

High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/.

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

PubMed

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

2008-04-01

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

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

PubMed

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

2011-01-01

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

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.

Sequencing of the Cheese Microbiome and Its Relevance to Industry.

PubMed

Yeluri Jonnala, Bhagya R; McSweeney, Paul L H; Sheehan, Jeremiah J; Cotter, Paul D

2018-01-01

The microbiota of cheese plays a key role in determining its organoleptic and other physico-chemical properties. It is essential to understand the various contributions, positive or negative, of these microbial components in order to promote the growth of desirable taxa and, thus, characteristics. The recent application of high throughput DNA sequencing (HTS) facilitates an even more accurate identification of these microbes, and their functional properties, and has the potential to reveal those microbes, and associated pathways, responsible for favorable or unfavorable characteristics. This technology also facilitates a detailed analysis of the composition and functional potential of the microbiota of milk, curd, whey, mixed starters, processing environments, and how these contribute to the final cheese microbiota, and associated characteristics. Ultimately, this information can be harnessed by producers to optimize the quality, safety, and commercial value of their products. In this review we highlight a number of key studies in which HTS was employed to study the cheese microbiota, and pay particular attention to those of greatest relevance to industry.

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

USDA-ARS?s Scientific Manuscript database

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

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

Polymerase chain reaction-hybridization method using urease gene sequences for high-throughput Ureaplasma urealyticum and Ureaplasma parvum detection and differentiation.

PubMed

Xu, Chen; Zhang, Nan; Huo, Qianyu; Chen, Minghui; Wang, Rengfeng; Liu, Zhili; Li, Xue; Liu, Yunde; Bao, Huijing

2016-04-15

In this article, we discuss the polymerase chain reaction (PCR)-hybridization assay that we developed for high-throughput simultaneous detection and differentiation of Ureaplasma urealyticum and Ureaplasma parvum using one set of primers and two specific DNA probes based on urease gene nucleotide sequence differences. First, U. urealyticum and U. parvum DNA samples were specifically amplified using one set of biotin-labeled primers. Furthermore, amine-modified DNA probes, which can specifically react with U. urealyticum or U. parvum DNA, were covalently immobilized to a DNA-BIND plate surface. The plate was then incubated with the PCR products to facilitate sequence-specific DNA binding. Horseradish peroxidase-streptavidin conjugation and a colorimetric assay were used. Based on the results, the PCR-hybridization assay we developed can specifically differentiate U. urealyticum and U. parvum with high sensitivity (95%) compared with cultivation (72.5%). Hence, this study demonstrates a new method for high-throughput simultaneous differentiation and detection of U. urealyticum and U. parvum with high sensitivity. Based on these observations, the PCR-hybridization assay developed in this study is ideal for detecting and discriminating U. urealyticum and U. parvum in clinical applications. Copyright © 2016 Elsevier Inc. All rights reserved.

High-Throughput SNP Discovery through Deep Resequencing of a Reduced Representation Library to Anchor and Orient Scaffolds in the Soybean Whole Genome Sequence

USDA-ARS?s Scientific Manuscript database

The soybean Consensus Map 4.0 facilitated the anchoring of 95.6% of the soybean whole genome sequence developed by the Joint Genome Institute, Department of Energy but only properly oriented 66% of the sequence scaffolds. To find additional single nucleotide polymorphism (SNP) markers for additiona...

Noninvasive High-Throughput Single-Cell Analysis of the Intracellular pH of Saccharomyces cerevisiae by Ratiometric Flow Cytometry

PubMed Central

Valkonen, Mari; Mojzita, Dominik; Penttilä, Merja

2013-01-01

The ability of cells to maintain pH homeostasis in response to environmental changes has elicited interest in basic and applied research and has prompted the development of methods for intracellular pH measurements. Many traditional methods provide information at population level and thus the average values of the studied cell physiological phenomena, excluding the fact that cell cultures are very heterogeneous. Single-cell analysis, on the other hand, offers more detailed insight into population variability, thereby facilitating a considerably deeper understanding of cell physiology. Although microscopy methods can address this issue, they suffer from limitations in terms of the small number of individual cells that can be studied and complicated image processing. We developed a noninvasive high-throughput method that employs flow cytometry to analyze large populations of cells that express pHluorin, a genetically encoded ratiometric fluorescent probe that is sensitive to pH. The method described here enables measurement of the intracellular pH of single cells with high sensitivity and speed, which is a clear improvement compared to previously published methods that either require pretreatment of the cells, measure cell populations, or require complex data analysis. The ratios of fluorescence intensities, which correlate to the intracellular pH, are independent of the expression levels of the pH probe, making the use of transiently or extrachromosomally expressed probes possible. We conducted an experiment on the kinetics of the pH homeostasis of Saccharomyces cerevisiae cultures grown to a stationary phase after ethanol or glucose addition and after exposure to weak acid stress and glucose pulse. Minor populations with pH homeostasis behaving differently upon treatments were identified. PMID:24038689

Noninvasive high-throughput single-cell analysis of the intracellular pH of Saccharomyces cerevisiae by ratiometric flow cytometry.

PubMed

Valkonen, Mari; Mojzita, Dominik; Penttilä, Merja; Bencina, Mojca

2013-12-01

The ability of cells to maintain pH homeostasis in response to environmental changes has elicited interest in basic and applied research and has prompted the development of methods for intracellular pH measurements. Many traditional methods provide information at population level and thus the average values of the studied cell physiological phenomena, excluding the fact that cell cultures are very heterogeneous. Single-cell analysis, on the other hand, offers more detailed insight into population variability, thereby facilitating a considerably deeper understanding of cell physiology. Although microscopy methods can address this issue, they suffer from limitations in terms of the small number of individual cells that can be studied and complicated image processing. We developed a noninvasive high-throughput method that employs flow cytometry to analyze large populations of cells that express pHluorin, a genetically encoded ratiometric fluorescent probe that is sensitive to pH. The method described here enables measurement of the intracellular pH of single cells with high sensitivity and speed, which is a clear improvement compared to previously published methods that either require pretreatment of the cells, measure cell populations, or require complex data analysis. The ratios of fluorescence intensities, which correlate to the intracellular pH, are independent of the expression levels of the pH probe, making the use of transiently or extrachromosomally expressed probes possible. We conducted an experiment on the kinetics of the pH homeostasis of Saccharomyces cerevisiae cultures grown to a stationary phase after ethanol or glucose addition and after exposure to weak acid stress and glucose pulse. Minor populations with pH homeostasis behaving differently upon treatments were identified.

Highly scalable, closed-loop synthesis of drug-loaded, layer-by-layer nanoparticles.

PubMed

Correa, Santiago; Choi, Ki Young; Dreaden, Erik C; Renggli, Kasper; Shi, Aria; Gu, Li; Shopsowitz, Kevin E; Quadir, Mohiuddin A; Ben-Akiva, Elana; Hammond, Paula T

2016-02-16

Layer-by-layer (LbL) self-assembly is a versatile technique from which multicomponent and stimuli-responsive nanoscale drug carriers can be constructed. Despite the benefits of LbL assembly, the conventional synthetic approach for fabricating LbL nanoparticles requires numerous purification steps that limit scale, yield, efficiency, and potential for clinical translation. In this report, we describe a generalizable method for increasing throughput with LbL assembly by using highly scalable, closed-loop diafiltration to manage intermediate purification steps. This method facilitates highly controlled fabrication of diverse nanoscale LbL formulations smaller than 150 nm composed from solid-polymer, mesoporous silica, and liposomal vesicles. The technique allows for the deposition of a broad range of polyelectrolytes that included native polysaccharides, linear polypeptides, and synthetic polymers. We also explore the cytotoxicity, shelf life and long-term storage of LbL nanoparticles produced using this approach. We find that LbL coated systems can be reliably and rapidly produced: specifically, LbL-modified liposomes could be lyophilized, stored at room temperature, and reconstituted without compromising drug encapsulation or particle stability, thereby facilitating large scale applications. Overall, this report describes an accessible approach that significantly improves the throughput of nanoscale LbL drug-carriers that show low toxicity and are amenable to clinically relevant storage conditions.

Efficient mouse genome engineering by CRISPR-EZ technology.

PubMed

Modzelewski, Andrew J; Chen, Sean; Willis, Brandon J; Lloyd, K C Kent; Wood, Joshua A; He, Lin

2018-06-01

CRISPR/Cas9 technology has transformed mouse genome editing with unprecedented precision, efficiency, and ease; however, the current practice of microinjecting CRISPR reagents into pronuclear-stage embryos remains rate-limiting. We thus developed CRISPR ribonucleoprotein (RNP) electroporation of zygotes (CRISPR-EZ), an electroporation-based technology that outperforms pronuclear and cytoplasmic microinjection in efficiency, simplicity, cost, and throughput. In C57BL/6J and C57BL/6N mouse strains, CRISPR-EZ achieves 100% delivery of Cas9/single-guide RNA (sgRNA) RNPs, facilitating indel mutations (insertions or deletions), exon deletions, point mutations, and small insertions. In a side-by-side comparison in the high-throughput KnockOut Mouse Project (KOMP) pipeline, CRISPR-EZ consistently outperformed microinjection. Here, we provide an optimized protocol covering sgRNA synthesis, embryo collection, RNP electroporation, mouse generation, and genotyping strategies. Using CRISPR-EZ, a graduate-level researcher with basic embryo-manipulation skills can obtain genetically modified mice in 6 weeks. Altogether, CRISPR-EZ is a simple, economic, efficient, and high-throughput technology that is potentially applicable to other mammalian species.

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

PubMed

Liu, Yun; Grossman, Jeffrey C

2014-12-10

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

Pediatric Glioblastoma Therapies Based on Patient-Derived Stem Cell Resources

DTIC Science & Technology

2014-11-01

genomic DNA and then subjected to Illumina high-throughput sequencing . In this analysis, shRNAs lost in the GSC population represent candidate gene...and genomic DNA and then subjected to Illumina high-throughput sequencing . In this analysis, shRNAs lost in the GSC population represent candidate...PRISM 7900 Sequence Detection System ( Genomics Resource, FHCRC). Relative transcript abundance was analyzed using the 2−ΔΔCt method. TRIzol (Invitrogen

Rice-Map: a new-generation rice genome browser.

PubMed

Wang, Jun; Kong, Lei; Zhao, Shuqi; Zhang, He; Tang, Liang; Li, Zhe; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2011-03-30

The concurrent release of rice genome sequences for two subspecies (Oryza sativa L. ssp. japonica and Oryza sativa L. ssp. indica) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively. More than one hundred annotation tracks (81 for japonica and 82 for indica) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria. Rice-Map delivers abundant up-to-date japonica and indica annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at http://www.ricemap.org/, with all data available for free downloading.

Evaluation of e-liquid toxicity using an open-source high-throughput screening assay

PubMed Central

Keating, James E.; Zorn, Bryan T.; Kochar, Tavleen K.; Wolfgang, Matthew C.; Glish, Gary L.; Tarran, Robert

2018-01-01

The e-liquids used in electronic cigarettes (E-cigs) consist of propylene glycol (PG), vegetable glycerin (VG), nicotine, and chemical additives for flavoring. There are currently over 7,700 e-liquid flavors available, and while some have been tested for toxicity in the laboratory, most have not. Here, we developed a 3-phase, 384-well, plate-based, high-throughput screening (HTS) assay to rapidly triage and validate the toxicity of multiple e-liquids. Our data demonstrated that the PG/VG vehicle adversely affected cell viability and that a large number of e-liquids were more toxic than PG/VG. We also performed gas chromatography–mass spectrometry (GC-MS) analysis on all tested e-liquids. Subsequent nonmetric multidimensional scaling (NMDS) analysis revealed that e-liquids are an extremely heterogeneous group. Furthermore, these data indicated that (i) the more chemicals contained in an e-liquid, the more toxic it was likely to be and (ii) the presence of vanillin was associated with higher toxicity values. Further analysis of common constituents by electron ionization revealed that the concentration of cinnamaldehyde and vanillin, but not triacetin, correlated with toxicity. We have also developed a publicly available searchable website (www.eliquidinfo.org). Given the large numbers of available e-liquids, this website will serve as a resource to facilitate dissemination of this information. Our data suggest that an HTS approach to evaluate the toxicity of multiple e-liquids is feasible. Such an approach may serve as a roadmap to enable bodies such as the Food and Drug Administration (FDA) to better regulate e-liquid composition. PMID:29584716

Overcoming bias and systematic errors in next generation sequencing data.

PubMed

Taub, Margaret A; Corrada Bravo, Hector; Irizarry, Rafael A

2010-12-10

Considerable time and effort has been spent in developing analysis and quality assessment methods to allow the use of microarrays in a clinical setting. As is the case for microarrays and other high-throughput technologies, data from new high-throughput sequencing technologies are subject to technological and biological biases and systematic errors that can impact downstream analyses. Only when these issues can be readily identified and reliably adjusted for will clinical applications of these new technologies be feasible. Although much work remains to be done in this area, we describe consistently observed biases that should be taken into account when analyzing high-throughput sequencing data. In this article, we review current knowledge about these biases, discuss their impact on analysis results, and propose solutions.

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

Toward a mtDNA locus-specific mutation database using the LOVD platform.

PubMed

Elson, Joanna L; Sweeney, Mary G; Procaccio, Vincent; Yarham, John W; Salas, Antonio; Kong, Qing-Peng; van der Westhuizen, Francois H; Pitceathly, Robert D S; Thorburn, David R; Lott, Marie T; Wallace, Douglas C; Taylor, Robert W; McFarland, Robert

2012-09-01

The Human Variome Project (HVP) is a global effort to collect and curate all human genetic variation affecting health. Mutations of mitochondrial DNA (mtDNA) are an important cause of neurogenetic disease in humans; however, identification of the pathogenic mutations responsible can be problematic. In this article, we provide explanations as to why and suggest how such difficulties might be overcome. We put forward a case in support of a new Locus Specific Mutation Database (LSDB) implemented using the Leiden Open-source Variation Database (LOVD) system that will not only list primary mutations, but also present the evidence supporting their role in disease. Critically, we feel that this new database should have the capacity to store information on the observed phenotypes alongside the genetic variation, thereby facilitating our understanding of the complex and variable presentation of mtDNA disease. LOVD supports fast queries of both seen and hidden data and allows storage of sequence variants from high-throughput sequence analysis. The LOVD platform will allow construction of a secure mtDNA database; one that can fully utilize currently available data, as well as that being generated by high-throughput sequencing, to link genotype with phenotype enhancing our understanding of mitochondrial disease, with a view to providing better prognostic information. © 2012 Wiley Periodicals, Inc.

Toward a mtDNA Locus-Specific Mutation Database Using the LOVD Platform

PubMed Central

Elson, Joanna L.; Sweeney, Mary G.; Procaccio, Vincent; Yarham, John W.; Salas, Antonio; Kong, Qing-Peng; van der Westhuizen, Francois H.; Pitceathly, Robert D.S.; Thorburn, David R.; Lott, Marie T.; Wallace, Douglas C.; Taylor, Robert W.; McFarland, Robert

2015-01-01

The Human Variome Project (HVP) is a global effort to collect and curate all human genetic variation affecting health. Mutations of mitochondrial DNA (mtDNA) are an important cause of neurogenetic disease in humans; however, identification of the pathogenic mutations responsible can be problematic. In this article, we provide explanations as to why and suggest how such difficulties might be overcome. We put forward a case in support of a new Locus Specific Mutation Database (LSDB) implemented using the Leiden Open-source Variation Database (LOVD) system that will not only list primary mutations, but also present the evidence supporting their role in disease. Critically, we feel that this new database should have the capacity to store information on the observed phenotypes alongside the genetic variation, thereby facilitating our understanding of the complex and variable presentation of mtDNA disease. LOVD supports fast queries of both seen and hidden data and allows storage of sequence variants from high-throughput sequence analysis. The LOVD platform will allow construction of a secure mtDNA database; one that can fully utilize currently available data, as well as that being generated by high-throughput sequencing, to link genotype with phenotype enhancing our understanding of mitochondrial disease, with a view to providing better prognostic information. PMID:22581690

Human microbiome visualization using 3D technology.

PubMed

Moore, Jason H; Lari, Richard Cowper Sal; Hill, Douglas; Hibberd, Patricia L; Madan, Juliette C

2011-01-01

High-throughput sequencing technology has opened the door to the study of the human microbiome and its relationship with health and disease. This is both an opportunity and a significant biocomputing challenge. We present here a 3D visualization methodology and freely-available software package for facilitating the exploration and analysis of high-dimensional human microbiome data. Our visualization approach harnesses the power of commercial video game development engines to provide an interactive medium in the form of a 3D heat map for exploration of microbial species and their relative abundance in different patients. The advantage of this approach is that the third dimension provides additional layers of information that cannot be visualized using a traditional 2D heat map. We demonstrate the usefulness of this visualization approach using microbiome data collected from a sample of premature babies with and without sepsis.

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

PubMed Central

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

2016-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Emory University: High-Throughput Protein-Protein Interaction Analysis for Hippo Pathway Profiling | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University used high-throughput protein-protein interaction (PPI) mapping for Hippo signaling pathway profiling to rapidly unveil promising PPIs as potential therapeutic targets and advance functional understanding of signaling circuitry in cells. Read the abstract.

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

An economical and effective high-throughput DNA extraction protocol for molecular marker analysis in honey bees

USDA-ARS?s Scientific Manuscript database

Extraction of DNA from tissue samples can be expensive both in time and monetary resources and can often require handling and disposal of hazardous chemicals. We have developed a high throughput protocol for extracting DNA from honey bees that is of a high enough quality and quantity to enable hundr...

Machine learning for Big Data analytics in plants.

PubMed

Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

2014-12-01

Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel LC/MS/MS and High-Throughput Mass Spectrometric Assays for Monoacylglycerol Acyltransferase Inhibitors.

PubMed

Qi, Jenson; Masucci, John A; Lang, Wensheng; Connelly, Margery A; Caldwell, Gary W; Petrounia, Ioanna; Kirkpatrick, Jennifer; Barnakov, Alexander N; Struble, Geoffrey; Miller, Robyn; Dzordzorine, Keli; Kuo, Gee-Hong; Gaul, Michael; Pocai, Alessandro; Lee, Seunghun

2017-04-01

Monoacylglycerol acyltransferase enzymes (MGAT1, MGAT2, and MGAT3) convert monoacylglycerol to diacylglycerol (DAG). MGAT1 and MGAT2 are both implicated in obesity-related metabolic diseases. Conventional MGAT enzyme assays use radioactive substrates, wherein the product of the MGAT-catalyzed reaction is usually resolved by time-consuming thin layer chromatography (TLC) analysis. Furthermore, microsomal membrane preparations typically contain endogenous diacylglycerol acyltransferase (DGAT) from the host cells, and these DGAT activities can further acylate DAG to form triglyceride (TG). Our mass spectrometry (liquid chromatography-tandem mass spectrometry, or LC/MS/MS) MGAT2 assay measures human recombinant MGAT2-catalyzed formation of didecanoyl-glycerol from 1-decanoyl-rac-glycerol and decanoyl-CoA, to produce predominantly 1,3-didecanoyl-glycerol. Unlike 1,2-DAG, 1,3-didecanoyl-glycerol is proved to be not susceptible to further acylation to TG. 1,3-Didecanoyl-glycerol product can be readily solubilized and directly subjected to high-throughput mass spectrometry (HTMS) without further extraction in a 384-well format. We also have established the LC/MS/MS MGAT activity assay in the intestinal microsomes from various species. Our assay is proved to be highly sensitive, and thus it allows measurement of endogenous MGAT activity in cell lysates and tissue preparations. The implementation of the HTMS MGAT activity assay has facilitated the robust screening and evaluation of MGAT inhibitors for the treatment of metabolic diseases.

Genetic Structures of Copy Number Variants Revealed by Genotyping Single Sperm

PubMed Central

Luo, Minjie; Cui, Xiangfeng; Fredman, David; Brookes, Anthony J.; Azaro, Marco A.; Greenawalt, Danielle M.; Hu, Guohong; Wang, Hui-Yun; Tereshchenko, Irina V.; Lin, Yong; Shentu, Yue; Gao, Richeng; Shen, Li; Li, Honghua

2009-01-01

Background Copy number variants (CNVs) occupy a significant portion of the human genome and may have important roles in meiotic recombination, human genome evolution and gene expression. Many genetic diseases may be underlain by CNVs. However, because of the presence of their multiple copies, variability in copy numbers and the diploidy of the human genome, detailed genetic structure of CNVs cannot be readily studied by available techniques. Methodology/Principal Findings Single sperm samples were used as the primary subjects for the study so that CNV haplotypes in the sperm donors could be studied individually. Forty-eight CNVs characterized in a previous study were analyzed using a microarray-based high-throughput genotyping method after multiplex amplification. Seventeen single nucleotide polymorphisms (SNPs) were also included as controls. Two single-base variants, either allelic or paralogous, could be discriminated for all markers. Microarray data were used to resolve SNP alleles and CNV haplotypes, to quantitatively assess the numbers and compositions of the paralogous segments in each CNV haplotype. Conclusions/Significance This is the first study of the genetic structure of CNVs on a large scale. Resulting information may help understand evolution of the human genome, gain insight into many genetic processes, and discriminate between CNVs and SNPs. The highly sensitive high-throughput experimental system with haploid sperm samples as subjects may be used to facilitate detailed large-scale CNV analysis. PMID:19384415

A High-Content Live-Cell Viability Assay and Its Validation on a Diverse 12K Compound Screen.

PubMed

Chiaravalli, Jeanne; Glickman, J Fraser

2017-08-01

We have developed a new high-content cytotoxicity assay using live cells, called "ImageTOX." We used a high-throughput fluorescence microscope system, image segmentation software, and the combination of Hoechst 33342 and SYTO 17 to simultaneously score the relative size and the intensity of the nuclei, the nuclear membrane permeability, and the cell number in a 384-well microplate format. We then performed a screen of 12,668 diverse compounds and compared the results to a standard cytotoxicity assay. The ImageTOX assay identified similar sets of compounds to the standard cytotoxicity assay, while identifying more compounds having adverse effects on cell structure, earlier in treatment time. The ImageTOX assay uses inexpensive commercially available reagents and facilitates the use of live cells in toxicity screens. Furthermore, we show that we can measure the kinetic profile of compound toxicity in a high-content, high-throughput format, following the same set of cells over an extended period of time.

Anaerobic microplate assay for direct microbial conversion of switchgrass and Avicel using Clostridium thermocellum.

PubMed

Oguntimein, Gbekeloluwa B; Rodriguez, Miguel; Dumitrache, Alexandru; Shollenberger, Todd; Decker, Stephen R; Davison, Brian H; Brown, Steven D

2018-02-01

To develop and prototype a high-throughput microplate assay to assess anaerobic microorganisms and lignocellulosic biomasses in a rapid, cost-effective screen for consolidated bioprocessing potential. Clostridium thermocellum parent Δhpt strain deconstructed Avicel to cellobiose, glucose, and generated lactic acid, formic acid, acetic acid and ethanol as fermentation products in titers and ratios similar to larger scale fermentations confirming the suitability of a plate-based method for C. thermocellum growth studies. C. thermocellum strain LL1210, with gene deletions in the key central metabolic pathways, produced higher ethanol titers in the Consolidated Bioprocessing (CBP) plate assay for both Avicel and switchgrass fermentations when compared to the Δhpt strain. A prototype microplate assay system is developed that will facilitate high-throughput bioprospecting for new lignocellulosic biomass types, genetic variants and new microbial strains for bioethanol production.

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.

Identification of antigen-specific human monoclonal antibodies using high-throughput sequencing of the antibody repertoire.

PubMed

Liu, Ju; Li, Ruihua; Liu, Kun; Li, Liangliang; Zai, Xiaodong; Chi, Xiangyang; Fu, Ling; Xu, Junjie; Chen, Wei

2016-04-22

High-throughput sequencing of the antibody repertoire provides a large number of antibody variable region sequences that can be used to generate human monoclonal antibodies. However, current screening methods for identifying antigen-specific antibodies are inefficient. In the present study, we developed an antibody clone screening strategy based on clone dynamics and relative frequency, and used it to identify antigen-specific human monoclonal antibodies. Enzyme-linked immunosorbent assay showed that at least 52% of putative positive immunoglobulin heavy chains composed antigen-specific antibodies. Combining information on dynamics and relative frequency improved identification of positive clones and elimination of negative clones. and increase the credibility of putative positive clones. Therefore the screening strategy could simplify the subsequent experimental screening and may facilitate the generation of antigen-specific antibodies. Copyright © 2016 Elsevier Inc. All rights reserved.

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench

PubMed Central

Beckers, Matthew; Mohorianu, Irina; Stocks, Matthew; Applegate, Christopher; Dalmay, Tamas; Moulton, Vincent

2017-01-01

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information. A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this. PMID:28289155

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

PubMed Central

JR, Luft; EH, Snell; GT, DeTitta

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Zhu, Chenggang; Fei, Yiyan; Zhu, Xiangdong

2017-02-01

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

Characterization of Capsicum annuum Genetic Diversity and Population Structure Based on Parallel Polymorphism Discovery with a 30K Unigene Pepper GeneChip

PubMed Central

Hill, Theresa A.; Ashrafi, Hamid; Reyes-Chin-Wo, Sebastian; Yao, JiQiang; Stoffel, Kevin; Truco, Maria-Jose; Kozik, Alexander; Michelmore, Richard W.; Van Deynze, Allen

2013-01-01

The widely cultivated pepper, Capsicum spp., important as a vegetable and spice crop world-wide, is one of the most diverse crops. To enhance breeding programs, a detailed characterization of Capsicum diversity including morphological, geographical and molecular data is required. Currently, molecular data characterizing Capsicum genetic diversity is limited. The development and application of high-throughput genome-wide markers in Capsicum will facilitate more detailed molecular characterization of germplasm collections, genetic relationships, and the generation of ultra-high density maps. We have developed the Pepper GeneChip® array from Affymetrix for polymorphism detection and expression analysis in Capsicum. Probes on the array were designed from 30,815 unigenes assembled from expressed sequence tags (ESTs). Our array design provides a maximum redundancy of 13 probes per base pair position allowing integration of multiple hybridization values per position to detect single position polymorphism (SPP). Hybridization of genomic DNA from 40 diverse C. annuum lines, used in breeding and research programs, and a representative from three additional cultivated species (C. frutescens, C. chinense and C. pubescens) detected 33,401 SPP markers within 13,323 unigenes. Among the C. annuum lines, 6,426 SPPs covering 3,818 unigenes were identified. An estimated three-fold reduction in diversity was detected in non-pungent compared with pungent lines, however, we were able to detect 251 highly informative markers across these C. annuum lines. In addition, an 8.7 cM region without polymorphism was detected around Pun1 in non-pungent C. annuum. An analysis of genetic relatedness and diversity using the software Structure revealed clustering of the germplasm which was confirmed with statistical support by principle components analysis (PCA) and phylogenetic analysis. This research demonstrates the effectiveness of parallel high-throughput discovery and application of genome-wide transcript-based markers to assess genetic and genomic features among Capsicum annuum. PMID:23409153

Characterization of Capsicum annuum genetic diversity and population structure based on parallel polymorphism discovery with a 30K unigene Pepper GeneChip.

PubMed

Hill, Theresa A; Ashrafi, Hamid; Reyes-Chin-Wo, Sebastian; Yao, JiQiang; Stoffel, Kevin; Truco, Maria-Jose; Kozik, Alexander; Michelmore, Richard W; Van Deynze, Allen

2013-01-01

The widely cultivated pepper, Capsicum spp., important as a vegetable and spice crop world-wide, is one of the most diverse crops. To enhance breeding programs, a detailed characterization of Capsicum diversity including morphological, geographical and molecular data is required. Currently, molecular data characterizing Capsicum genetic diversity is limited. The development and application of high-throughput genome-wide markers in Capsicum will facilitate more detailed molecular characterization of germplasm collections, genetic relationships, and the generation of ultra-high density maps. We have developed the Pepper GeneChip® array from Affymetrix for polymorphism detection and expression analysis in Capsicum. Probes on the array were designed from 30,815 unigenes assembled from expressed sequence tags (ESTs). Our array design provides a maximum redundancy of 13 probes per base pair position allowing integration of multiple hybridization values per position to detect single position polymorphism (SPP). Hybridization of genomic DNA from 40 diverse C. annuum lines, used in breeding and research programs, and a representative from three additional cultivated species (C. frutescens, C. chinense and C. pubescens) detected 33,401 SPP markers within 13,323 unigenes. Among the C. annuum lines, 6,426 SPPs covering 3,818 unigenes were identified. An estimated three-fold reduction in diversity was detected in non-pungent compared with pungent lines, however, we were able to detect 251 highly informative markers across these C. annuum lines. In addition, an 8.7 cM region without polymorphism was detected around Pun1 in non-pungent C. annuum. An analysis of genetic relatedness and diversity using the software Structure revealed clustering of the germplasm which was confirmed with statistical support by principle components analysis (PCA) and phylogenetic analysis. This research demonstrates the effectiveness of parallel high-throughput discovery and application of genome-wide transcript-based markers to assess genetic and genomic features among Capsicum annuum.

Deciphering the genomic targets of alkylating polyamide conjugates using high-throughput sequencing

PubMed Central

Chandran, Anandhakumar; Syed, Junetha; Taylor, Rhys D.; Kashiwazaki, Gengo; Sato, Shinsuke; Hashiya, Kaori; Bando, Toshikazu; Sugiyama, Hiroshi

2016-01-01

Chemically engineered small molecules targeting specific genomic sequences play an important role in drug development research. Pyrrole-imidazole polyamides (PIPs) are a group of molecules that can bind to the DNA minor-groove and can be engineered to target specific sequences. Their biological effects rely primarily on their selective DNA binding. However, the binding mechanism of PIPs at the chromatinized genome level is poorly understood. Herein, we report a method using high-throughput sequencing to identify the DNA-alkylating sites of PIP-indole-seco-CBI conjugates. High-throughput sequencing analysis of conjugate 2 showed highly similar DNA-alkylating sites on synthetic oligos (histone-free DNA) and on human genomes (chromatinized DNA context). To our knowledge, this is the first report identifying alkylation sites across genomic DNA by alkylating PIP conjugates using high-throughput sequencing. PMID:27098039

Quantification of larval zebrafish motor function in multi-well plates using open-source MATLAB® applications

PubMed Central

Zhou, Yangzhong; Cattley, Richard T.; Cario, Clinton L.; Bai, Qing; Burton, Edward A.

2014-01-01

This article describes a method to quantify the movements of larval zebrafish in multi-well plates, using the open-source MATLAB® applications LSRtrack and LSRanalyze. The protocol comprises four stages: generation of high-quality, flatly-illuminated video recordings with exposure settings that facilitate object recognition; analysis of the resulting recordings using tools provided in LSRtrack to optimize tracking accuracy and motion detection; analysis of tracking data using LSRanalyze or custom MATLAB® scripts; implementation of validation controls. The method is reliable, automated and flexible, requires less than one hour of hands-on work for completion once optimized, and shows excellent signal:noise characteristics. The resulting data can be analyzed to determine: positional preference; displacement, velocity and acceleration; duration and frequency of movement events and rest periods. This approach is widely applicable to analyze spontaneous or stimulus-evoked zebrafish larval neurobehavioral phenotypes resulting from a broad array of genetic and environmental manipulations, in a multi-well plate format suitable for high-throughput applications. PMID:24901738

Alignment-Free Design of Highly Discriminatory Diagnostic Primer Sets for Escherichia coli O104:H4 Outbreak Strains

PubMed Central

Bielaszewska, Martina; Karch, Helge; Toth, Ian K.

2012-01-01

Background An Escherichia coli O104:H4 outbreak in Germany in summer 2011 caused 53 deaths, over 4000 individual infections across Europe, and considerable economic, social and political impact. This outbreak was the first in a position to exploit rapid, benchtop high-throughput sequencing (HTS) technologies and crowdsourced data analysis early in its investigation, establishing a new paradigm for rapid response to disease threats. We describe a novel strategy for design of diagnostic PCR primers that exploited this rapid draft bacterial genome sequencing to distinguish between E. coli O104:H4 outbreak isolates and other pathogenic E. coli isolates, including the historical hæmolytic uræmic syndrome (HUSEC) E. coli HUSEC041 O104:H4 strain, which possesses the same serotype as the outbreak isolates. Methodology/Principal Findings Primers were designed using a novel alignment-free strategy against eleven draft whole genome assemblies of E. coli O104:H4 German outbreak isolates from the E. coli O104:H4 Genome Analysis Crowd-Sourcing Consortium website, and a negative sequence set containing 69 E. coli chromosome and plasmid sequences from public databases. Validation in vitro against 21 ‘positive’ E. coli O104:H4 outbreak and 32 ‘negative’ non-outbreak EHEC isolates indicated that individual primer sets exhibited 100% sensitivity for outbreak isolates, with false positive rates of between 9% and 22%. A minimal combination of two primers discriminated between outbreak and non-outbreak E. coli isolates with 100% sensitivity and 100% specificity. Conclusions/Significance Draft genomes of isolates of disease outbreak bacteria enable high throughput primer design and enhanced diagnostic performance in comparison to traditional molecular assays. Future outbreak investigations will be able to harness HTS rapidly to generate draft genome sequences and diagnostic primer sets, greatly facilitating epidemiology and clinical diagnostics. We expect that high throughput primer design strategies will enable faster, more precise responses to future disease outbreaks of bacterial origin, and help to mitigate their societal impact. PMID:22496820

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Sorting Out Antibiotics' Mechanisms of Action: a Double Fluorescent Protein Reporter for High-Throughput Screening of Ribosome and DNA Biosynthesis Inhibitors

PubMed Central

Osterman, Ilya A.; Komarova, Ekaterina S.; Shiryaev, Dmitry I.; Korniltsev, Ilya A.; Khven, Irina M.; Lukyanov, Dmitry A.; Tashlitsky, Vadim N.; Serebryakova, Marina V.; Efremenkova, Olga V.; Ivanenkov, Yan A.; Bogdanov, Alexey A.; Dontsova, Olga A.

2016-01-01

In order to accelerate drug discovery, a simple, reliable, and cost-effective system for high-throughput identification of a potential antibiotic mechanism of action is required. To facilitate such screening of new antibiotics, we created a double-reporter system for not only antimicrobial activity detection but also simultaneous sorting of potential antimicrobials into those that cause ribosome stalling and those that induce the SOS response due to DNA damage. In this reporter system, the red fluorescent protein gene rfp was placed under the control of the SOS-inducible sulA promoter. The gene of the far-red fluorescent protein, katushka2S, was inserted downstream of the tryptophan attenuator in which two tryptophan codons were replaced by alanine codons, with simultaneous replacement of the complementary part of the attenuator to preserve the ability to form secondary structures that influence transcription termination. This genetically modified attenuator makes possible Katushka2S expression only upon exposure to ribosome-stalling compounds. The application of red and far-red fluorescent proteins provides a high signal-to-background ratio without any need of enzymatic substrates for detection of the reporter activity. This reporter was shown to be efficient in high-throughput screening of both synthetic and natural chemicals. PMID:27736765

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

PubMed

Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

2011-09-01

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

A high-throughput direct fluorescence resonance energy transfer-based assay for analyzing apoptotic proteases using flow cytometry and fluorescence lifetime measurements.

PubMed

Suzuki, Miho; Sakata, Ichiro; Sakai, Takafumi; Tomioka, Hiroaki; Nishigaki, Koichi; Tramier, Marc; Coppey-Moisan, Maïté

2015-12-15

Cytometry is a versatile and powerful method applicable to different fields, particularly pharmacology and biomedical studies. Based on the data obtained, cytometric studies are classified into high-throughput (HTP) or high-content screening (HCS) groups. However, assays combining the advantages of both are required to facilitate research. In this study, we developed a high-throughput system to profile cellular populations in terms of time- or dose-dependent responses to apoptotic stimulations because apoptotic inducers are potent anticancer drugs. We previously established assay systems involving protease to monitor live cells for apoptosis using tunable fluorescence resonance energy transfer (FRET)-based bioprobes. These assays can be used for microscopic analyses or fluorescence-activated cell sorting. In this study, we developed FRET-based bioprobes to detect the activity of the apoptotic markers caspase-3 and caspase-9 via changes in bioprobe fluorescence lifetimes using a flow cytometer for direct estimation of FRET efficiencies. Different patterns of changes in the fluorescence lifetimes of these markers during apoptosis were observed, indicating a relationship between discrete steps in the apoptosis process. The findings demonstrate the feasibility of evaluating collective cellular dynamics during apoptosis. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Microengineering Methods for Cell Based Microarrays and High-Throughput Drug Screening Applications

PubMed Central

Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan

2011-01-01

Screening for effective therapeutic agents from millions of drug candidates is costly, time-consuming and often face ethical concerns due to extensive use of animals. To improve cost-effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems have facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell based drug-screening models, which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell based drug screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds a great potential to provide repeatable 3D cell based constructs with high temporal, spatial control and versatility. PMID:21725152

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data.

PubMed

Peterson, Elena S; McCue, Lee Ann; Schrimpe-Rutledge, Alexandra C; Jensen, Jeffrey L; Walker, Hyunjoo; Kobold, Markus A; Webb, Samantha R; Payne, Samuel H; Ansong, Charles; Adkins, Joshua N; Cannon, William R; Webb-Robertson, Bobbie-Jo M

2012-04-05

The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

VESPA: software to facilitate genomic annotation of prokaryotic organisms through integration of proteomic and transcriptomic data

PubMed Central

2012-01-01

Background The procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates. Results VESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data. Conclusions VESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php. PMID:22480257

A time-series method for automated measurement of changes in mitotic and interphase duration from time-lapse movies.

PubMed

Sigoillot, Frederic D; Huckins, Jeremy F; Li, Fuhai; Zhou, Xiaobo; Wong, Stephen T C; King, Randall W

2011-01-01

Automated time-lapse microscopy can visualize proliferation of large numbers of individual cells, enabling accurate measurement of the frequency of cell division and the duration of interphase and mitosis. However, extraction of quantitative information by manual inspection of time-lapse movies is too time-consuming to be useful for analysis of large experiments. Here we present an automated time-series approach that can measure changes in the duration of mitosis and interphase in individual cells expressing fluorescent histone 2B. The approach requires analysis of only 2 features, nuclear area and average intensity. Compared to supervised learning approaches, this method reduces processing time and does not require generation of training data sets. We demonstrate that this method is as sensitive as manual analysis in identifying small changes in interphase or mitotic duration induced by drug or siRNA treatment. This approach should facilitate automated analysis of high-throughput time-lapse data sets to identify small molecules or gene products that influence timing of cell division.

Collaborative Core Research Program for Chemical-Biological Warfare Defense

DTIC Science & Technology

2015-01-04

Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that

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.

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

PubMed

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

2013-08-26

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

Microreactor Cells for High-Throughput X-ray Absorption Spectroscopy

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

Beesley, Angela; Tsapatsaris, Nikolaos; Weiher, Norbert

2007-01-19

High-throughput experimentation has been applied to X-ray Absorption spectroscopy as a novel route for increasing research productivity in the catalysis community. Suitable instrumentation has been developed for the rapid determination of the local structure in the metal component of precursors for supported catalysts. An automated analytical workflow was implemented that is much faster than traditional individual spectrum analysis. It allows the generation of structural data in quasi-real time. We describe initial results obtained from the automated high throughput (HT) data reduction and analysis of a sample library implemented through the 96 well-plate industrial standard. The results show that a fullymore » automated HT-XAS technology based on existing industry standards is feasible and useful for the rapid elucidation of geometric and electronic structure of materials.« less

High-Throughput Printing Process for Flexible Electronics

NASA Astrophysics Data System (ADS)

Hyun, Woo Jin

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

Electron energy loss spectroscopy on semiconductor heterostructures for optoelectronics and photonics applications.

PubMed

Eljarrat, A; López-Conesa, L; Estradé, S; Peiró, F

2016-05-01

In this work, we present characterization methods for the analysis of nanometer-sized devices, based on silicon and III-V nitride semiconductor materials. These methods are devised in order to take advantage of the aberration corrected scanning transmission electron microscope, equipped with a monochromator. This set-up ensures the necessary high spatial and energy resolution for the characterization of the smallest structures. As with these experiments, we aim to obtain chemical and structural information, we use electron energy loss spectroscopy (EELS). The low-loss region of EELS is exploited, which features fundamental electronic properties of semiconductor materials and facilitates a high data throughput. We show how the detailed analysis of these spectra, using theoretical models and computational tools, can enhance the analytical power of EELS. In this sense, initially, results from the model-based fit of the plasmon peak are presented. Moreover, the application of multivariate analysis algorithms to low-loss EELS is explored. Finally, some physical limitations of the technique, such as spatial delocalization, are mentioned. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

High-throughput fabrication and screening improves gold nanoparticle chemiresistor sensor performance.

PubMed

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

2015-02-09

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

The genomic landscape of chronic lymphocytic leukaemia: biological and clinical implications.

PubMed

Strefford, Jonathan C

2015-04-01

Chronic lymphocytic leukaemia (CLL) remains at the forefront of the genetic analysis of human tumours, principally due its prevalence, protracted natural history and accessibility to suitable material for analysis. With the application of high-throughput genetic technologies, we have an unbridled view of the architecture of the CLL genome, including a comprehensive description of the copy number and mutational landscape of the disease, a detailed picture of clonal evolution during pathogenesis, and the molecular mechanisms that drive genomic instability and therapeutic resistance. This work has nuanced the prognostic importance of established copy number alterations, and identified novel prognostically relevant gene mutations that function within biological pathways that are attractive treatment targets. Herein, an overview of recent genomic discoveries will be reviewed, with associated biological and clinical implications, and a view into how clinical implementation may be facilitated. © 2014 John Wiley & Sons Ltd.

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

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

Liu, Y; Grossman, JC

2014-12-01

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

Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments

PubMed Central

Welch, Rene; Chung, Dongjun; Grass, Jeffrey; Landick, Robert

2017-01-01

Abstract ChIP-exo/nexus experiments rely on innovative modifications of the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a novel statistical quality control pipeline and accompanying R/Bioconductor package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics computed over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from Escherichia coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. PMID:28911122

Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments.

PubMed

Welch, Rene; Chung, Dongjun; Grass, Jeffrey; Landick, Robert; Keles, Sündüz

2017-09-06

ChIP-exo/nexus experiments rely on innovative modifications of the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a novel statistical quality control pipeline and accompanying R/Bioconductor package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics computed over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from Escherichia coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Detecting selection signatures between Duroc and Duroc synthetic pig populations using high-density SNP chip.

PubMed

Edea, Z; Hong, J-K; Jung, J-H; Kim, D-W; Kim, Y-M; Kim, E-S; Shin, S S; Jung, Y C; Kim, K-S

2017-08-01

The development of high throughput genotyping techniques has facilitated the identification of selection signatures of pigs. The detection of genomic selection signals in a population subjected to differential selection pressures may provide insights into the genes associated with economically and biologically important traits. To identify genomic regions under selection, we genotyped 488 Duroc (D) pigs and 155 D × Korean native pigs (DKNPs) using the Porcine SNP70K BeadChip. By applying the F ST and extended haplotype homozygosity (EHH-Rsb) methods, we detected genes under directional selection associated with growth/stature (DOCK7, PLCB4, HS2ST1, FBP2 and TG), carcass and meat quality (TG, COL14A1, FBXO5, NR3C1, SNX7, ARHGAP26 and DPYD), number of teats (LOC100153159 and LRRC1), pigmentation (MME) and ear morphology (SOX5), which are all mostly near or at fixation. These results could be a basis for investigating the underlying mutations associated with observed phenotypic variation. Validation using genome-wide association analysis would also facilitate the inclusion of some of these markers in genetic evaluation programs. © 2017 Stichting International Foundation for Animal Genetics.

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.

Cargo identification algorithms facilitating unmanned/unattended inspection at high throughput portals

NASA Astrophysics Data System (ADS)

Chalmers, Alex

2007-10-01

A simple model is presented of a possible inspection regimen applied to each leg of a cargo containers' journey between its point of origin and destination. Several candidate modalities are proposed to be used at multiple remote locations to act as a pre-screen inspection as the target approaches a perimeter and as the primary inspection modality at the portal. Information from multiple data sets are fused to optimize the costs and performance of a network of such inspection systems. A series of image processing algorithms are presented that automatically process X-ray images of containerized cargo. The goal of this processing is to locate the container in a real time stream of traffic traversing a portal without impeding the flow of commerce. Such processing may facilitate the inclusion of unmanned/unattended inspection systems in such a network. Several samples of the processing applied to data collected from deployed systems are included. Simulated data from a notional cargo inspection system with multiple sensor modalities and advanced data fusion algorithms are also included to show the potential increased detection and throughput performance of such a configuration.

High-Throughput Quantitative Lipidomics Analysis of Nonesterified Fatty Acids in Human Plasma.

PubMed

Christinat, Nicolas; Morin-Rivron, Delphine; Masoodi, Mojgan

2016-07-01

We present a high-throughput, nontargeted lipidomics approach using liquid chromatography coupled to high-resolution mass spectrometry for quantitative analysis of nonesterified fatty acids. We applied this method to screen a wide range of fatty acids from medium-chain to very long-chain (8 to 24 carbon atoms) in human plasma samples. The method enables us to chromatographically separate branched-chain species from their straight-chain isomers as well as separate biologically important ω-3 and ω-6 polyunsaturated fatty acids. We used 51 fatty acid species to demonstrate the quantitative capability of this method with quantification limits in the nanomolar range; however, this method is not limited only to these fatty acid species. High-throughput sample preparation was developed and carried out on a robotic platform that allows extraction of 96 samples simultaneously within 3 h. This high-throughput platform was used to assess the influence of different types of human plasma collection and preparation on the nonesterified fatty acid profile of healthy donors. Use of the anticoagulants EDTA and heparin has been compared with simple clotting, and only limited changes have been detected in most nonesterified fatty acid concentrations.

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

Evaluation of Methods for de novo Genome assembly from High-throughput Sequencing Reads Reveals Dependencies that Affect the Quality of the Results

USDA-ARS?s Scientific Manuscript database

Recent developments in high-throughput sequencing technology have made low-cost sequencing an attractive approach for many genome analysis tasks. Increasing read lengths, improving quality and the production of increasingly larger numbers of usable sequences per instrument-run continue to make whole...

Improvement of High-throughput Genotype Analysis After Implementation of a Dual-curve Sybr Green I-based Quantification and Normalization Procedure

USDA-ARS?s Scientific Manuscript database

The ability to rapidly screen a large number of individuals is the key to any successful plant breeding program. One of the primary bottlenecks in high throughput screening is the preparation of DNA samples, particularly the quantification and normalization of samples for downstream processing. A ...

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.

High-throughput detection of ethanol-producing cyanobacteria in a microdroplet platform.

PubMed

Abalde-Cela, Sara; Gould, Anna; Liu, Xin; Kazamia, Elena; Smith, Alison G; Abell, Chris

2015-05-06

Ethanol production by microorganisms is an important renewable energy source. Most processes involve fermentation of sugars from plant feedstock, but there is increasing interest in direct ethanol production by photosynthetic organisms. To facilitate this, a high-throughput screening technique for the detection of ethanol is required. Here, a method for the quantitative detection of ethanol in a microdroplet-based platform is described that can be used for screening cyanobacterial strains to identify those with the highest ethanol productivity levels. The detection of ethanol by enzymatic assay was optimized both in bulk and in microdroplets. In parallel, the encapsulation of engineered ethanol-producing cyanobacteria in microdroplets and their growth dynamics in microdroplet reservoirs were demonstrated. The combination of modular microdroplet operations including droplet generation for cyanobacteria encapsulation, droplet re-injection and pico-injection, and laser-induced fluorescence, were used to create this new platform to screen genetically engineered strains of cyanobacteria with different levels of ethanol production.

Anaerobic microplate assay for direct microbial conversion of switchgrass and Avicel using Clostridium thermocellum

DOE PAGES

Oguntimein, Gbekeloluwa B.; Rodriguez, Jr., Miguel; Dumitrache, Alexandru; ...

2017-11-09

Here, to develop and prototype a high-throughput microplate assay to assess anaerobic microorganisms and lignocellulosic biomasses in a rapid, cost-effective screen for consolidated bioprocessing potential. Clostridium thermocellum parent Δ hpt strain deconstructed Avicel to cellobiose, glucose, and generated lactic acid, formic acid, acetic acid and ethanol as fermentation products in titers and ratios similar to larger scale fermentations confirming the suitability of a plate-based method for C. thermocellum growth studies. C. thermocellum strain LL1210, with gene deletions in the key central metabolic pathways, produced higher ethanol titers in the Consolidated Bioprocessing (CBP) plate assay for both Avicel and switchgrass fermentationsmore » when compared to the Δ hpt strain. A prototype microplate assay system is developed that will facilitate high-throughput bioprospecting for new lignocellulosic biomass types, genetic variants and new microbial strains for bioethanol production.« less

Anaerobic microplate assay for direct microbial conversion of switchgrass and Avicel using Clostridium thermocellum

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

Oguntimein, Gbekeloluwa B.; Rodriguez, Jr., Miguel; Dumitrache, Alexandru

Here, to develop and prototype a high-throughput microplate assay to assess anaerobic microorganisms and lignocellulosic biomasses in a rapid, cost-effective screen for consolidated bioprocessing potential. Clostridium thermocellum parent Δ hpt strain deconstructed Avicel to cellobiose, glucose, and generated lactic acid, formic acid, acetic acid and ethanol as fermentation products in titers and ratios similar to larger scale fermentations confirming the suitability of a plate-based method for C. thermocellum growth studies. C. thermocellum strain LL1210, with gene deletions in the key central metabolic pathways, produced higher ethanol titers in the Consolidated Bioprocessing (CBP) plate assay for both Avicel and switchgrass fermentationsmore » when compared to the Δ hpt strain. A prototype microplate assay system is developed that will facilitate high-throughput bioprospecting for new lignocellulosic biomass types, genetic variants and new microbial strains for bioethanol production.« less

High-throughput and direct measurement of androgen levels using turbulent flow chromatography liquid chromatography-triple quadrupole mass spectrometry (TFC-LC-TQMS) to discover chemicals that modulate dihydrotestosterone production in human prostate cancer cells.

PubMed

Kang, Kyungsu; Peng, Lei; Jung, Yu-Jin; Kim, Joo Yeon; Lee, Eun Ha; Lee, Hee Ju; Kim, Sang Min; Sung, Sang Hyun; Pan, Cheol-Ho; Choi, Yongsoo

2018-02-01

To develop a high-throughput screening system to measure the conversion of testosterone to dihydrotestosterone (DHT) in cultured human prostate cancer cells using turbulent flow chromatography liquid chromatography-triple quadrupole mass spectrometry (TFC-LC-TQMS). After optimizing the cell reaction system, this method demonstrated a screening capability of 103 samples, including 78 single compounds and 25 extracts, in less than 12 h without manual sample preparation. Consequently, fucoxanthin, phenethyl caffeate, and Curcuma longa L. extract were validated as bioactive chemicals that inhibited DHT production in cultured DU145 cells. In addition, naringenin boosted DHT production in DU145 cells. The method can facilitate the discovery of bioactive chemicals that modulate the DHT production, and four phytochemicals are potential candidates of nutraceuticals to adjust DHT levels in male hormonal dysfunction.

Application of whole genome shotgun sequencing for detection and characterization of genetically modified organisms and derived products.

PubMed

Holst-Jensen, Arne; Spilsberg, Bjørn; Arulandhu, Alfred J; Kok, Esther; Shi, Jianxin; Zel, Jana

2016-07-01

The emergence of high-throughput, massive or next-generation sequencing technologies has created a completely new foundation for molecular analyses. Various selective enrichment processes are commonly applied to facilitate detection of predefined (known) targets. Such approaches, however, inevitably introduce a bias and are prone to miss unknown targets. Here we review the application of high-throughput sequencing technologies and the preparation of fit-for-purpose whole genome shotgun sequencing libraries for the detection and characterization of genetically modified and derived products. The potential impact of these new sequencing technologies for the characterization, breeding selection, risk assessment, and traceability of genetically modified organisms and genetically modified products is yet to be fully acknowledged. The published literature is reviewed, and the prospects for future developments and use of the new sequencing technologies for these purposes are discussed.

TMV-Gate vectors: Gateway compatible tobacco mosaic virus based expression vectors for functional analysis of proteins

PubMed Central

Kagale, Sateesh; Uzuhashi, Shihomi; Wigness, Merek; Bender, Tricia; Yang, Wen; Borhan, M. Hossein; Rozwadowski, Kevin

2012-01-01

Plant viral expression vectors are advantageous for high-throughput functional characterization studies of genes due to their capability for rapid, high-level transient expression of proteins. We have constructed a series of tobacco mosaic virus (TMV) based vectors that are compatible with Gateway technology to enable rapid assembly of expression constructs and exploitation of ORFeome collections. In addition to the potential of producing recombinant protein at grams per kilogram FW of leaf tissue, these vectors facilitate either N- or C-terminal fusions to a broad series of epitope tag(s) and fluorescent proteins. We demonstrate the utility of these vectors in affinity purification, immunodetection and subcellular localisation studies. We also apply the vectors to characterize protein-protein interactions and demonstrate their utility in screening plant pathogen effectors. Given its broad utility in defining protein properties, this vector series will serve as a useful resource to expedite gene characterization efforts. PMID:23166857

High-throughput discovery of novel developmental phenotypes.

PubMed

Dickinson, Mary E; Flenniken, Ann M; Ji, Xiao; Teboul, Lydia; Wong, Michael D; White, Jacqueline K; Meehan, Terrence F; Weninger, Wolfgang J; Westerberg, Henrik; Adissu, Hibret; Baker, Candice N; Bower, Lynette; Brown, James M; Caddle, L Brianna; Chiani, Francesco; Clary, Dave; Cleak, James; Daly, Mark J; Denegre, James M; Doe, Brendan; Dolan, Mary E; Edie, Sarah M; Fuchs, Helmut; Gailus-Durner, Valerie; Galli, Antonella; Gambadoro, Alessia; Gallegos, Juan; Guo, Shiying; Horner, Neil R; Hsu, Chih-Wei; Johnson, Sara J; Kalaga, Sowmya; Keith, Lance C; Lanoue, Louise; Lawson, Thomas N; Lek, Monkol; Mark, Manuel; Marschall, Susan; Mason, Jeremy; McElwee, Melissa L; Newbigging, Susan; Nutter, Lauryl M J; Peterson, Kevin A; Ramirez-Solis, Ramiro; Rowland, Douglas J; Ryder, Edward; Samocha, Kaitlin E; Seavitt, John R; Selloum, Mohammed; Szoke-Kovacs, Zsombor; Tamura, Masaru; Trainor, Amanda G; Tudose, Ilinca; Wakana, Shigeharu; Warren, Jonathan; Wendling, Olivia; West, David B; Wong, Leeyean; Yoshiki, Atsushi; MacArthur, Daniel G; Tocchini-Valentini, Glauco P; Gao, Xiang; Flicek, Paul; Bradley, Allan; Skarnes, William C; Justice, Monica J; Parkinson, Helen E; Moore, Mark; Wells, Sara; Braun, Robert E; Svenson, Karen L; de Angelis, Martin Hrabe; Herault, Yann; Mohun, Tim; Mallon, Ann-Marie; Henkelman, R Mark; Brown, Steve D M; Adams, David J; Lloyd, K C Kent; McKerlie, Colin; Beaudet, Arthur L; Bućan, Maja; Murray, Stephen A

2016-09-22

Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

High-throughput discovery of novel developmental phenotypes

PubMed Central

Dickinson, Mary E.; Flenniken, Ann M.; Ji, Xiao; Teboul, Lydia; Wong, Michael D.; White, Jacqueline K.; Meehan, Terrence F.; Weninger, Wolfgang J.; Westerberg, Henrik; Adissu, Hibret; Baker, Candice N.; Bower, Lynette; Brown, James M.; Caddle, L. Brianna; Chiani, Francesco; Clary, Dave; Cleak, James; Daly, Mark J.; Denegre, James M.; Doe, Brendan; Dolan, Mary E.; Edie, Sarah M.; Fuchs, Helmut; Gailus-Durner, Valerie; Galli, Antonella; Gambadoro, Alessia; Gallegos, Juan; Guo, Shiying; Horner, Neil R.; Hsu, Chih-wei; Johnson, Sara J.; Kalaga, Sowmya; Keith, Lance C.; Lanoue, Louise; Lawson, Thomas N.; Lek, Monkol; Mark, Manuel; Marschall, Susan; Mason, Jeremy; McElwee, Melissa L.; Newbigging, Susan; Nutter, Lauryl M.J.; Peterson, Kevin A.; Ramirez-Solis, Ramiro; Rowland, Douglas J.; Ryder, Edward; Samocha, Kaitlin E.; Seavitt, John R.; Selloum, Mohammed; Szoke-Kovacs, Zsombor; Tamura, Masaru; Trainor, Amanda G; Tudose, Ilinca; Wakana, Shigeharu; Warren, Jonathan; Wendling, Olivia; West, David B.; Wong, Leeyean; Yoshiki, Atsushi; MacArthur, Daniel G.; Tocchini-Valentini, Glauco P.; Gao, Xiang; Flicek, Paul; Bradley, Allan; Skarnes, William C.; Justice, Monica J.; Parkinson, Helen E.; Moore, Mark; Wells, Sara; Braun, Robert E.; Svenson, Karen L.; de Angelis, Martin Hrabe; Herault, Yann; Mohun, Tim; Mallon, Ann-Marie; Henkelman, R. Mark; Brown, Steve D.M.; Adams, David J.; Lloyd, K.C. Kent; McKerlie, Colin; Beaudet, Arthur L.; Bucan, Maja; Murray, Stephen A.

2016-01-01

Approximately one third of all mammalian genes are essential for life. Phenotypes resulting from mouse knockouts of these genes have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5000 knockout mouse lines, we have identified 410 lethal genes during the production of the first 1751 unique gene knockouts. Using a standardised phenotyping platform that incorporates high-resolution 3D imaging, we identified novel phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes identified in our screen, thus providing a novel dataset that facilitates prioritization and validation of mutations identified in clinical sequencing efforts. PMID:27626380

Genome-wide analysis of alternative splicing during human heart development

NASA Astrophysics Data System (ADS)

Wang, He; Chen, Yanmei; Li, Xinzhong; Chen, Guojun; Zhong, Lintao; Chen, Gangbing; Liao, Yulin; Liao, Wangjun; Bin, Jianping

2016-10-01

Alternative splicing (AS) drives determinative changes during mouse heart development. Recent high-throughput technological advancements have facilitated genome-wide AS, while its analysis in human foetal heart transition to the adult stage has not been reported. Here, we present a high-resolution global analysis of AS transitions between human foetal and adult hearts. RNA-sequencing data showed extensive AS transitions occurred between human foetal and adult hearts, and AS events occurred more frequently in protein-coding genes than in long non-coding RNA (lncRNA). A significant difference of AS patterns was found between foetal and adult hearts. The predicted difference in AS events was further confirmed using quantitative reverse transcription-polymerase chain reaction analysis of human heart samples. Functional foetal-specific AS event analysis showed enrichment associated with cell proliferation-related pathways including cell cycle, whereas adult-specific AS events were associated with protein synthesis. Furthermore, 42.6% of foetal-specific AS events showed significant changes in gene expression levels between foetal and adult hearts. Genes exhibiting both foetal-specific AS and differential expression were highly enriched in cell cycle-associated functions. In conclusion, we provided a genome-wide profiling of AS transitions between foetal and adult hearts and proposed that AS transitions and deferential gene expression may play determinative roles in human heart development.

High-throughput tetrad analysis.

PubMed

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

2013-07-01

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

An improved ternary vector system for Agrobacterium-mediated rapid maize transformation.

PubMed

Anand, Ajith; Bass, Steven H; Wu, Emily; Wang, Ning; McBride, Kevin E; Annaluru, Narayana; Miller, Michael; Hua, Mo; Jones, Todd J

2018-05-01

A simple and versatile ternary vector system that utilizes improved accessory plasmids for rapid maize transformation is described. This system facilitates high-throughput vector construction and plant transformation. The super binary plasmid pSB1 is a mainstay of maize transformation. However, the large size of the base vector makes it challenging to clone, the process of co-integration is cumbersome and inefficient, and some Agrobacterium strains are known to give rise to spontaneous mutants resistant to tetracycline. These limitations present substantial barriers to high throughput vector construction. Here we describe a smaller, simpler and versatile ternary vector system for maize transformation that utilizes improved accessory plasmids requiring no co-integration step. In addition, the newly described accessory plasmids have restored virulence genes found to be defective in pSB1, as well as added virulence genes. Testing of different configurations of the accessory plasmids in combination with T-DNA binary vector as ternary vectors nearly doubles both the raw transformation frequency and the number of transformation events of usable quality in difficult-to-transform maize inbreds. The newly described ternary vectors enabled the development of a rapid maize transformation method for elite inbreds. This vector system facilitated screening different origins of replication on the accessory plasmid and T-DNA vector, and four combinations were identified that have high (86-103%) raw transformation frequency in an elite maize inbred.

High throughput protein production screening

DOEpatents

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

2009-09-08

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

Orchestrating high-throughput genomic analysis with Bioconductor

PubMed Central

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

2015-01-01

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

A Multidisciplinary Approach to High Throughput Nuclear Magnetic Resonance Spectroscopy

PubMed Central

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

2016-01-01

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

Initial steps towards a production platform for DNA sequence analysis on the grid.

PubMed

Luyf, Angela C M; van Schaik, Barbera D C; de Vries, Michel; Baas, Frank; van Kampen, Antoine H C; Olabarriaga, Silvia D

2010-12-14

Bioinformatics is confronted with a new data explosion due to the availability of high throughput DNA sequencers. Data storage and analysis becomes a problem on local servers, and therefore it is needed to switch to other IT infrastructures. Grid and workflow technology can help to handle the data more efficiently, as well as facilitate collaborations. However, interfaces to grids are often unfriendly to novice users. In this study we reused a platform that was developed in the VL-e project for the analysis of medical images. Data transfer, workflow execution and job monitoring are operated from one graphical interface. We developed workflows for two sequence alignment tools (BLAST and BLAT) as a proof of concept. The analysis time was significantly reduced. All workflows and executables are available for the members of the Dutch Life Science Grid and the VL-e Medical virtual organizations All components are open source and can be transported to other grid infrastructures. The availability of in-house expertise and tools facilitates the usage of grid resources by new users. Our first results indicate that this is a practical, powerful and scalable solution to address the capacity and collaboration issues raised by the deployment of next generation sequencers. We currently adopt this methodology on a daily basis for DNA sequencing and other applications. More information and source code is available via http://www.bioinformaticslaboratory.nl/

Adverse outcome pathways (AOPs) to enhance EDC ...

EPA Pesticide Factsheets

Screening and testing for endocrine active chemicals was mandated under 1996 amendments to the Safe Drinking Water Act and Food Quality Protection Act. Efficiencies can be gained in the endocrine disruptor screening program by using available biological and toxicological knowledge to facilitate greater use of high throughput screening data and other data sources to inform endocrine disruptor assessments. Likewise, existing knowledge, when properly organized, can help aid interpretation of test results. The adverse outcome pathway (AOP) framework, which organizes information concerning measureable changes that link initial biological interactions with a chemical to adverse effects that are meaningful to risk assessment and management, can aid this process. This presentation outlines the ways in which the AOP framework has already been employed to support EDSP and how it may further enhance endocrine disruptor assessments in the future. Screening and testing for endocrine active chemicals was mandated under 1996 amendments to the Safe Drinking Water Act and Food Quality Protection Act. Efficiencies can be gained in the endocrine disruptor screening program by using available biological and toxicological knowledge to facilitate greater use of high throughput screening data and other data sources to inform endocrine disruptor assessments. Likewise, existing knowledge, when properly organized, can help aid interpretation of test results. The adverse outcome pathway

Marine Invertebrate Xenobiotic-Activated Nuclear Receptors: Their Application as Sensor Elements in High-Throughput Bioassays for Marine Bioactive Compounds

PubMed Central

Richter, Ingrid; Fidler, Andrew E.

2014-01-01

Developing high-throughput assays to screen marine extracts for bioactive compounds presents both conceptual and technical challenges. One major challenge is to develop assays that have well-grounded ecological and evolutionary rationales. In this review we propose that a specific group of ligand-activated transcription factors are particularly well-suited to act as sensors in such bioassays. More specifically, xenobiotic-activated nuclear receptors (XANRs) regulate transcription of genes involved in xenobiotic detoxification. XANR ligand-binding domains (LBDs) may adaptively evolve to bind those bioactive, and potentially toxic, compounds to which organisms are normally exposed to through their specific diets. A brief overview of the function and taxonomic distribution of both vertebrate and invertebrate XANRs is first provided. Proof-of-concept experiments are then described which confirm that a filter-feeding marine invertebrate XANR LBD is activated by marine bioactive compounds. We speculate that increasing access to marine invertebrate genome sequence data, in combination with the expression of functional recombinant marine invertebrate XANR LBDs, will facilitate the generation of high-throughput bioassays/biosensors of widely differing specificities, but all based on activation of XANR LBDs. Such assays may find application in screening marine extracts for bioactive compounds that could act as drug lead compounds. PMID:25421319

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.

Rapid high-throughput cloning and stable expression of antibodies in HEK293 cells.

PubMed

Spidel, Jared L; Vaessen, Benjamin; Chan, Yin Yin; Grasso, Luigi; Kline, J Bradford

2016-12-01

Single-cell based amplification of immunoglobulin variable regions is a rapid and powerful technique for cloning antigen-specific monoclonal antibodies (mAbs) for purposes ranging from general laboratory reagents to therapeutic drugs. From the initial screening process involving small quantities of hundreds or thousands of mAbs through in vitro characterization and subsequent in vivo experiments requiring large quantities of only a few, having a robust system for generating mAbs from cloning through stable cell line generation is essential. A protocol was developed to decrease the time, cost, and effort required by traditional cloning and expression methods by eliminating bottlenecks in these processes. Removing the clonal selection steps from the cloning process using a highly efficient ligation-independent protocol and from the stable cell line process by utilizing bicistronic plasmids to generate stable semi-clonal cell pools facilitated an increased throughput of the entire process from plasmid assembly through transient transfections and selection of stable semi-clonal cell pools. Furthermore, the time required by a single individual to clone, express, and select stable cell pools in a high-throughput format was reduced from 4 to 6months to only 4 to 6weeks. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Future technologies for monitoring HIV drug resistance and cure.

PubMed

Parikh, Urvi M; McCormick, Kevin; van Zyl, Gert; Mellors, John W

2017-03-01

Sensitive, scalable and affordable assays are critically needed for monitoring the success of interventions for preventing, treating and attempting to cure HIV infection. This review evaluates current and emerging technologies that are applicable for both surveillance of HIV drug resistance (HIVDR) and characterization of HIV reservoirs that persist despite antiretroviral therapy and are obstacles to curing HIV infection. Next-generation sequencing (NGS) has the potential to be adapted into high-throughput, cost-efficient approaches for HIVDR surveillance and monitoring during continued scale-up of antiretroviral therapy and rollout of preexposure prophylaxis. Similarly, improvements in PCR and NGS are resulting in higher throughput single genome sequencing to detect intact proviruses and to characterize HIV integration sites and clonal expansions of infected cells. Current population genotyping methods for resistance monitoring are high cost and low throughput. NGS, combined with simpler sample collection and storage matrices (e.g. dried blood spots), has considerable potential to broaden global surveillance and patient monitoring for HIVDR. Recent adaptions of NGS to identify integration sites of HIV in the human genome and to characterize the integrated HIV proviruses are likely to facilitate investigations of the impact of experimental 'curative' interventions on HIV reservoirs.

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

PubMed

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

2017-01-01

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

Genetics-based methods for detection of Salmonella spp. in foods.

PubMed

Mozola, Mark A

2006-01-01

Genetic methods are now at the forefront of foodborne pathogen testing. The sensitivity, specificity, and inclusivity advantages offered by deoxyribonucleic acid (DNA) probe technology have driven an intense effort in methods development over the past 20 years. DNA probe-based methods for Salmonella spp. and other pathogens have progressed from time-consuming procedures involving the use of radioisotopes to simple, high throughput, automated assays. The analytical sensitivity of nucleic acid amplification technology has facilitated a reduction in analysis time by allowing enriched samples to be tested for previously undetectable quantities of analyte. This article will trace the evolution of the development of genetic methods for detection of Salmonella in foods, review the basic assay formats and their advantages and limitations, and discuss method performance characteristics and considerations for selection of methods.

Zebrafish models of cardiovascular diseases and their applications in herbal medicine research.

PubMed

Seto, Sai-Wang; Kiat, Hosen; Lee, Simon M Y; Bensoussan, Alan; Sun, Yu-Ting; Hoi, Maggie P M; Chang, Dennis

2015-12-05

The zebrafish (Danio rerio) has recently become a powerful animal model for cardiovascular research and drug discovery due to its ease of maintenance, genetic manipulability and ability for high-throughput screening. Recent advances in imaging techniques and generation of transgenic zebrafish have greatly facilitated in vivo analysis of cellular events of cardiovascular development and pathogenesis. More importantly, recent studies have demonstrated the functional similarity of drug metabolism systems between zebrafish and humans, highlighting the clinical relevance of employing zebrafish in identifying lead compounds in Chinese herbal medicine with potential beneficial cardiovascular effects. This paper seeks to summarise the scope of zebrafish models employed in cardiovascular studies and the application of these research models in Chinese herbal medicine to date. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

ViralEpi v1.0: a high-throughput spectrum of viral epigenomic methylation profiles from diverse diseases.

PubMed

Khan, Mohd Shoaib; Gupta, Amit Kumar; Kumar, Manoj

2016-01-01

To develop a computational resource for viral epigenomic methylation profiles from diverse diseases. Methylation patterns of Epstein-Barr virus and hepatitis B virus genomic regions are provided as web platform developed using open source Linux-Apache-MySQL-PHP (LAMP) bundle: programming and scripting languages, that is, HTML, JavaScript and PERL. A comprehensive and integrated web resource ViralEpi v1.0 is developed providing well-organized compendium of methylation events and statistical analysis associated with several diseases. Additionally, it also facilitates 'Viral EpiGenome Browser' for user-affable browsing experience using JavaScript-based JBrowse. This web resource would be helpful for research community engaged in studying epigenetic biomarkers for appropriate prognosis and diagnosis of diseases and its various stages.

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

DOE PAGES

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

2017-03-06

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

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

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

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

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

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

PubMed Central

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

2012-01-01

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

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

PubMed Central

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

2016-01-01

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

Mobile element biology – new possibilities with high-throughput sequencing

PubMed Central

Xing, Jinchuan; Witherspoon, David J.; Jorde, Lynn B.

2014-01-01

Mobile elements compose more than half of the human genome, but until recently their large-scale detection was time-consuming and challenging. With the development of new high-throughput sequencing technologies, the complete spectrum of mobile element variation in humans can now be identified and analyzed. Thousands of new mobile element insertions have been discovered, yielding new insights into mobile element biology, evolution, and genomic variation. We review several high-throughput methods, with an emphasis on techniques that specifically target mobile element insertions in humans, and we highlight recent applications of these methods in evolutionary studies and in the analysis of somatic alterations in human cancers. PMID:23312846

Advances in high throughput DNA sequence data compression.

PubMed

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

2016-06-01

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

Accelerating Virtual High-Throughput Ligand Docking: current technology and case study on a petascale supercomputer.

PubMed

Ellingson, Sally R; Dakshanamurthy, Sivanesan; Brown, Milton; Smith, Jeremy C; Baudry, Jerome

2014-04-25

In this paper we give the current state of high-throughput virtual screening. We describe a case study of using a task-parallel MPI (Message Passing Interface) version of Autodock4 [1], [2] to run a virtual high-throughput screen of one-million compounds on the Jaguar Cray XK6 Supercomputer at Oak Ridge National Laboratory. We include a description of scripts developed to increase the efficiency of the predocking file preparation and postdocking analysis. A detailed tutorial, scripts, and source code for this MPI version of Autodock4 are available online at http://www.bio.utk.edu/baudrylab/autodockmpi.htm.

Molecular ecological network analyses.

PubMed

Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong

2012-05-30

Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.

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.

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

PubMed Central

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

2015-01-01

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

GobyWeb: Simplified Management and Analysis of Gene Expression and DNA Methylation Sequencing Data

PubMed Central

Dorff, Kevin C.; Chambwe, Nyasha; Zeno, Zachary; Simi, Manuele; Shaknovich, Rita; Campagne, Fabien

2013-01-01

We present GobyWeb, a web-based system that facilitates the management and analysis of high-throughput sequencing (HTS) projects. The software provides integrated support for a broad set of HTS analyses and offers a simple plugin extension mechanism. Analyses currently supported include quantification of gene expression for messenger and small RNA sequencing, estimation of DNA methylation (i.e., reduced bisulfite sequencing and whole genome methyl-seq), or the detection of pathogens in sequenced data. In contrast to previous analysis pipelines developed for analysis of HTS data, GobyWeb requires significantly less storage space, runs analyses efficiently on a parallel grid, scales gracefully to process tens or hundreds of multi-gigabyte samples, yet can be used effectively by researchers who are comfortable using a web browser. We conducted performance evaluations of the software and found it to either outperform or have similar performance to analysis programs developed for specialized analyses of HTS data. We found that most biologists who took a one-hour GobyWeb training session were readily able to analyze RNA-Seq data with state of the art analysis tools. GobyWeb can be obtained at http://gobyweb.campagnelab.org and is freely available for non-commercial use. GobyWeb plugins are distributed in source code and licensed under the open source LGPL3 license to facilitate code inspection, reuse and independent extensions http://github.com/CampagneLaboratory/gobyweb2-plugins. PMID:23936070

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

PubMed

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

2009-08-01

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

A high-throughput single-cell analysis of human CD8+ T cell functions reveals discordance for cytokine secretion and cytolysis

PubMed Central

Varadarajan, Navin; Julg, Boris; Yamanaka, Yvonne J.; Chen, Huabiao; Ogunniyi, Adebola O.; McAndrew, Elizabeth; Porter, Lindsay C.; Piechocka-Trocha, Alicja; Hill, Brenna J.; Douek, Daniel C.; Pereyra, Florencia; Walker, Bruce D.; Love, J. Christopher

2011-01-01

CD8+ T cells are a key component of the adaptive immune response to viral infection. An inadequate CD8+ T cell response is thought to be partly responsible for the persistent chronic infection that arises following infection with HIV. It is therefore critical to identify ways to define what constitutes an adequate or inadequate response. IFN-γ production has been used as a measure of T cell function, but the relationship between cytokine production and the ability of a cell to lyse virus-infected cells is not clear. Moreover, the ability to assess multiple CD8+ T cell functions with single-cell resolution using freshly isolated blood samples, and subsequently to recover these cells for further functional analyses, has not been achieved. As described here, to address this need, we have developed a high-throughput, automated assay in 125-pl microwells to simultaneously evaluate the ability of thousands of individual CD8+ T cells from HIV-infected patients to mediate lysis and to produce cytokines. This concurrent, direct analysis enabled us to investigate the correlation between immediate cytotoxic activity and short-term cytokine secretion. The majority of in vivo primed, circulating HIV-specific CD8+ T cells were discordant for cytolysis and cytokine secretion, notably IFN-γ, when encountering cognate antigen presented on defined numbers of cells. Our approach should facilitate determination of signatures of functional variance among individual effector CD8+ T cells, including those from mucosal samples and those induced by vaccines. PMID:21965332

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).

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.

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

PubMed Central

Panzeri, Francesco

2017-01-01

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

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

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

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

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

PubMed Central

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

2013-01-01

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933

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

PubMed Central

Bittker, Joshua A.

2012-01-01

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

High-throughput sequencing: a failure mode analysis.

PubMed

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

2005-01-04

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

Spotsizer: High-throughput quantitative analysis of microbial growth.

PubMed

Bischof, Leanne; Převorovský, Martin; Rallis, Charalampos; Jeffares, Daniel C; Arzhaeva, Yulia; Bähler, Jürg

2016-10-01

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2018-01-18

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

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

PubMed

Xu, Chun-Xiu; Yin, Xue-Feng

2011-02-04

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

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

EZH2 and CD79B mutational status over time in B-cell non-Hodgkin lymphomas detected by high-throughput sequencing using minimal samples

PubMed Central

Saieg, Mauro Ajaj; Geddie, William R; Boerner, Scott L; Bailey, Denis; Crump, Michael; da Cunha Santos, Gilda

2013-01-01

BACKGROUND: Numerous genomic abnormalities in B-cell non-Hodgkin lymphomas (NHLs) have been revealed by novel high-throughput technologies, including recurrent mutations in EZH2 (enhancer of zeste homolog 2) and CD79B (B cell antigen receptor complex-associated protein beta chain) genes. This study sought to determine the evolution of the mutational status of EZH2 and CD79B over time in different samples from the same patient in a cohort of B-cell NHLs, through use of a customized multiplex mutation assay. METHODS: DNA that was extracted from cytological material stored on FTA cards as well as from additional specimens, including archived frozen and formalin-fixed histological specimens, archived stained smears, and cytospin preparations, were submitted to a multiplex mutation assay specifically designed for the detection of point mutations involving EZH2 and CD79B, using MassARRAY spectrometry followed by Sanger sequencing. RESULTS: All 121 samples from 80 B-cell NHL cases were successfully analyzed. Mutations in EZH2 (Y646) and CD79B (Y196) were detected in 13.2% and 8% of the samples, respectively, almost exclusively in follicular lymphomas and diffuse large B-cell lymphomas. In one-third of the positive cases, a wild type was detected in a different sample from the same patient during follow-up. CONCLUSIONS: Testing multiple minimal tissue samples using a high-throughput multiplex platform exponentially increases tissue availability for molecular analysis and might facilitate future studies of tumor progression and the related molecular events. Mutational status of EZH2 and CD79B may vary in B-cell NHL samples over time and support the concept that individualized therapy should be based on molecular findings at the time of treatment, rather than on results obtained from previous specimens. Cancer (Cancer Cytopathol) 2013;121:377–386. © 2013 American Cancer Society. PMID:23361872

Fluorescent Approaches to High Throughput Crystallography

NASA Technical Reports Server (NTRS)

Pusey, Marc L.; Forsythe, Elizabeth; Achari, Aniruddha

2006-01-01

We have shown that by covalently modifying a subpopulation, less than or equal to 1%, of a macromolecule with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification, and the presence of the probe at low concentrations does not affect the X-ray data quality or the crystallization behavior. The presence of the trace fluorescent label gives a number of advantages when used with high throughput crystallizations. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination crystals show up as bright objects against a dark background. Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Brightly fluorescent crystals are readily found against less bright precipitated phases, which under white light illumination may obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries as the protein or protein structures is all that shows up. Fluorescence intensity is a faster search parameter, whether visually or by automated methods, than looking for crystalline features. We are now testing the use of high fluorescence intensity regions, in the absence of clear crystalline features or "hits", as a means for determining potential lead conditions. A working hypothesis is that kinetics leading to non-structured phases may overwhelm and trap more slowly formed ordered assemblies, which subsequently show up as regions of brighter fluorescence intensity. Preliminary experiments with test proteins have resulted in the extraction of a number of crystallization conditions from screening outcomes based solely on the presence of bright fluorescent regions. Subsequent experiments will test this approach using a wider range of proteins. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons.

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

PubMed

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

2017-04-01

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

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

PubMed

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p < 0.0001, AUC = 0.83, respectively). Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007) but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

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

PubMed

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

2015-08-21

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

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

PubMed Central

Ou, Hong-Yu; He, Xinyi; Harrison, Ewan M.; Kulasekara, Bridget R.; Thani, Ali Bin; Kadioglu, Aras; Lory, Stephen; Hinton, Jay C. D.; Barer, Michael R.; Rajakumar, Kumar

2007-01-01

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands. PMID:17537813

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

Treesearch

William R. Kenealy; Thomas W. Jeffries

2003-01-01

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

High-Performance Computational Analysis of Glioblastoma Pathology Images with Database Support Identifies Molecular and Survival Correlates.

PubMed

Kong, Jun; Wang, Fusheng; Teodoro, George; Cooper, Lee; Moreno, Carlos S; Kurc, Tahsin; Pan, Tony; Saltz, Joel; Brat, Daniel

2013-12-01

In this paper, we present a novel framework for microscopic image analysis of nuclei, data management, and high performance computation to support translational research involving nuclear morphometry features, molecular data, and clinical outcomes. Our image analysis pipeline consists of nuclei segmentation and feature computation facilitated by high performance computing with coordinated execution in multi-core CPUs and Graphical Processor Units (GPUs). All data derived from image analysis are managed in a spatial relational database supporting highly efficient scientific queries. We applied our image analysis workflow to 159 glioblastomas (GBM) from The Cancer Genome Atlas dataset. With integrative studies, we found statistics of four specific nuclear features were significantly associated with patient survival. Additionally, we correlated nuclear features with molecular data and found interesting results that support pathologic domain knowledge. We found that Proneural subtype GBMs had the smallest mean of nuclear Eccentricity and the largest mean of nuclear Extent, and MinorAxisLength. We also found gene expressions of stem cell marker MYC and cell proliferation maker MKI67 were correlated with nuclear features. To complement and inform pathologists of relevant diagnostic features, we queried the most representative nuclear instances from each patient population based on genetic and transcriptional classes. Our results demonstrate that specific nuclear features carry prognostic significance and associations with transcriptional and genetic classes, highlighting the potential of high throughput pathology image analysis as a complementary approach to human-based review and translational research.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-12-01

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

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

PubMed Central

2010-01-01

Background In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. Results We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce variability in the location of discovered cell populations across samples, and decrease the misclassification (mis-gating) of individual events when compared to default-parameter counterparts. Conclusions Our results indicate that the preferred transformation for fluorescence channels is a parameter- optimized biexponential or generalized Box-Cox, in accordance with current best practices. Interestingly, for populations in the scatter channels, we find that the optimized hyperbolic arcsine may be a better choice in a high-throughput setting than current standard practice of no transformation. However, generally speaking, the choice of transformation remains data-dependent. We have implemented our algorithm in the BioConductor package, flowTrans, which is publicly available. PMID:21050468

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

PubMed

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

2010-11-04

In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce variability in the location of discovered cell populations across samples, and decrease the misclassification (mis-gating) of individual events when compared to default-parameter counterparts. Our results indicate that the preferred transformation for fluorescence channels is a parameter- optimized biexponential or generalized Box-Cox, in accordance with current best practices. Interestingly, for populations in the scatter channels, we find that the optimized hyperbolic arcsine may be a better choice in a high-throughput setting than current standard practice of no transformation. However, generally speaking, the choice of transformation remains data-dependent. We have implemented our algorithm in the BioConductor package, flowTrans, which is publicly available.

EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments.

PubMed

Zhou, Bailing; Zhao, Huiying; Yu, Jiafeng; Guo, Chengang; Dou, Xianghua; Song, Feng; Hu, Guodong; Cao, Zanxia; Qu, Yuanxu; Yang, Yuedong; Zhou, Yaoqi; Wang, Jihua

2018-01-04

Long non-coding RNAs (lncRNAs) play important functional roles in various biological processes. Early databases were utilized to deposit all lncRNA candidates produced by high-throughput experimental and/or computational techniques to facilitate classification, assessment and validation. As more lncRNAs are validated by low-throughput experiments, several databases were established for experimentally validated lncRNAs. However, these databases are small in scale (with a few hundreds of lncRNAs only) and specific in their focuses (plants, diseases or interactions). Thus, it is highly desirable to have a comprehensive dataset for experimentally validated lncRNAs as a central repository for all of their structures, functions and phenotypes. Here, we established EVLncRNAs by curating lncRNAs validated by low-throughput experiments (up to 1 May 2016) and integrating specific databases (lncRNAdb, LncRANDisease, Lnc2Cancer and PLNIncRBase) with additional functional and disease-specific information not covered previously. The current version of EVLncRNAs contains 1543 lncRNAs from 77 species that is 2.9 times larger than the current largest database for experimentally validated lncRNAs. Seventy-four percent lncRNA entries are partially or completely new, comparing to all existing experimentally validated databases. The established database allows users to browse, search and download as well as to submit experimentally validated lncRNAs. The database is available at http://biophy.dzu.edu.cn/EVLncRNAs. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments

PubMed Central

Zhao, Huiying; Yu, Jiafeng; Guo, Chengang; Dou, Xianghua; Song, Feng; Hu, Guodong; Cao, Zanxia; Qu, Yuanxu

2018-01-01

Abstract Long non-coding RNAs (lncRNAs) play important functional roles in various biological processes. Early databases were utilized to deposit all lncRNA candidates produced by high-throughput experimental and/or computational techniques to facilitate classification, assessment and validation. As more lncRNAs are validated by low-throughput experiments, several databases were established for experimentally validated lncRNAs. However, these databases are small in scale (with a few hundreds of lncRNAs only) and specific in their focuses (plants, diseases or interactions). Thus, it is highly desirable to have a comprehensive dataset for experimentally validated lncRNAs as a central repository for all of their structures, functions and phenotypes. Here, we established EVLncRNAs by curating lncRNAs validated by low-throughput experiments (up to 1 May 2016) and integrating specific databases (lncRNAdb, LncRANDisease, Lnc2Cancer and PLNIncRBase) with additional functional and disease-specific information not covered previously. The current version of EVLncRNAs contains 1543 lncRNAs from 77 species that is 2.9 times larger than the current largest database for experimentally validated lncRNAs. Seventy-four percent lncRNA entries are partially or completely new, comparing to all existing experimentally validated databases. The established database allows users to browse, search and download as well as to submit experimentally validated lncRNAs. The database is available at http://biophy.dzu.edu.cn/EVLncRNAs. PMID:28985416

High-throughput heterodyne thermoreflectance: Application to thermal conductivity measurements of a Fe-Si-Ge thin film alloy library.

PubMed

d'Acremont, Quentin; Pernot, Gilles; Rampnoux, Jean-Michel; Furlan, Andrej; Lacroix, David; Ludwig, Alfred; Dilhaire, Stefan

2017-07-01

A High-Throughput Time-Domain ThermoReflectance (HT-TDTR) technique was developed to perform fast thermal conductivity measurements with minimum user actions required. This new setup is based on a heterodyne picosecond thermoreflectance system. The use of two different laser oscillators has been proven to reduce the acquisition time by two orders of magnitude and avoid the experimental artefacts usually induced by moving the elements present in TDTR systems. An amplitude modulation associated to a lock-in detection scheme is included to maintain a high sensitivity to thermal properties. We demonstrate the capabilities of the HT-TDTR setup to perform high-throughput thermal analysis by mapping thermal conductivity and interface resistances of a ternary thin film silicide library Fe x Si y Ge 100-x-y (20

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

PubMed

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

2015-01-27

Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied "open-format" and "closed-format" detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. Copyright © 2015 Zhou et al.

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

PubMed Central

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

2015-01-01

ABSTRACT   Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. PMID:25626903

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

DOE PAGES

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

2015-01-27

Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications andmore » focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions.« less

High-throughput heterodyne thermoreflectance: Application to thermal conductivity measurements of a Fe-Si-Ge thin film alloy library

NASA Astrophysics Data System (ADS)

d'Acremont, Quentin; Pernot, Gilles; Rampnoux, Jean-Michel; Furlan, Andrej; Lacroix, David; Ludwig, Alfred; Dilhaire, Stefan

2017-07-01

A High-Throughput Time-Domain ThermoReflectance (HT-TDTR) technique was developed to perform fast thermal conductivity measurements with minimum user actions required. This new setup is based on a heterodyne picosecond thermoreflectance system. The use of two different laser oscillators has been proven to reduce the acquisition time by two orders of magnitude and avoid the experimental artefacts usually induced by moving the elements present in TDTR systems. An amplitude modulation associated to a lock-in detection scheme is included to maintain a high sensitivity to thermal properties. We demonstrate the capabilities of the HT-TDTR setup to perform high-throughput thermal analysis by mapping thermal conductivity and interface resistances of a ternary thin film silicide library FexSiyGe100-x-y (20

Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

PubMed Central

Bodenmiller, Bernd; Zunder, Eli R.; Finck, Rachel; Chen, Tiffany J.; Savig, Erica S.; Bruggner, Robert V.; Simonds, Erin F.; Bendall, Sean C.; Sachs, Karen; Krutzik, Peter O.; Nolan, Garry P.

2013-01-01

The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors, and revealed off-target effects. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease. PMID:22902532

Fabrication of Carbohydrate Microarrays by Boronate Formation.

PubMed

Adak, Avijit K; Lin, Ting-Wei; Li, Ben-Yuan; Lin, Chun-Cheng

2017-01-01

The interactions between soluble carbohydrates and/or surface displayed glycans and protein receptors are essential to many biological processes and cellular recognition events. Carbohydrate microarrays provide opportunities for high-throughput quantitative analysis of carbohydrate-protein interactions. Over the past decade, various techniques have been implemented for immobilizing glycans on solid surfaces in a microarray format. Herein, we describe a detailed protocol for fabricating carbohydrate microarrays that capitalizes on the intrinsic reactivity of boronic acid toward carbohydrates to form stable boronate diesters. A large variety of unprotected carbohydrates ranging in structure from simple disaccharides and trisaccharides to considerably more complex human milk and blood group (oligo)saccharides have been covalently immobilized in a single step on glass slides, which were derivatized with high-affinity boronic acid ligands. The immobilized ligands in these microarrays maintain the receptor-binding activities including those of lectins and antibodies according to the structures of their pendant carbohydrates for rapid analysis of a number of carbohydrate-recognition events within 30 h. This method facilitates the direct construction of otherwise difficult to obtain carbohydrate microarrays from underivatized glycans.

High-throughput liquid-absorption air-sampling apparatus and methods

DOEpatents

Zaromb, Solomon

2000-01-01

A portable high-throughput liquid-absorption air sampler [PHTLAAS] has an asymmetric air inlet through which air is drawn upward by a small and light-weight centrifugal fan driven by a direct current motor that can be powered by a battery. The air inlet is so configured as to impart both rotational and downward components of motion to the sampled air near said inlet. The PHTLAAS comprises a glass tube of relatively small size through which air passes at a high rate in a swirling, highly turbulent motion, which facilitates rapid transfer of vapors and particulates to a liquid film covering the inner walls of the tube. The pressure drop through the glass tube is <10 cm of water, usually <5 cm of water. The sampler's collection efficiency is usually >20% for vapors or airborne particulates in the 2-3.mu. range and >50% for particles larger than 4.mu.. In conjunction with various analyzers, the PHTLAAS can serve to monitor a variety of hazardous or illicit airborne substances, such as lead-containing particulates, tritiated water vapor, biological aerosols, or traces of concealed drugs or explosives.

Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases

PubMed Central

Amos, Christopher I.; Bafna, Vineet; Hauser, Elizabeth R.; Hernandez, Ryan D.; Li, Chun; Liberles, David A.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Papanicolaou, George J.; Peng, Bo; Ritchie, Marylyn D.; Rosenfeld, Gabriel; Witte, John S.

2014-01-01

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled “Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases” at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to: (i) identify opportunities, challenges and resource needs for the development and application of genetic simulation models; (ii) improve the integration of tools for modeling and analysis of simulated data; and (iii) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation. PMID:25371374

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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.

KNIME4NGS: a comprehensive toolbox for next generation sequencing analysis.

PubMed

Hastreiter, Maximilian; Jeske, Tim; Hoser, Jonathan; Kluge, Michael; Ahomaa, Kaarin; Friedl, Marie-Sophie; Kopetzky, Sebastian J; Quell, Jan-Dominik; Mewes, H Werner; Küffner, Robert

2017-05-15

Analysis of Next Generation Sequencing (NGS) data requires the processing of large datasets by chaining various tools with complex input and output formats. In order to automate data analysis, we propose to standardize NGS tasks into modular workflows. This simplifies reliable handling and processing of NGS data, and corresponding solutions become substantially more reproducible and easier to maintain. Here, we present a documented, linux-based, toolbox of 42 processing modules that are combined to construct workflows facilitating a variety of tasks such as DNAseq and RNAseq analysis. We also describe important technical extensions. The high throughput executor (HTE) helps to increase the reliability and to reduce manual interventions when processing complex datasets. We also provide a dedicated binary manager that assists users in obtaining the modules' executables and keeping them up to date. As basis for this actively developed toolbox we use the workflow management software KNIME. See http://ibisngs.github.io/knime4ngs for nodes and user manual (GPLv3 license). robert.kueffner@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

RepExplore: addressing technical replicate variance in proteomics and metabolomics data analysis.

PubMed

Glaab, Enrico; Schneider, Reinhard

2015-07-01

High-throughput omics datasets often contain technical replicates included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses.We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ranking tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. Freely available at http://www.repexplore.tk enrico.glaab@uni.lu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

TAM 2.0: tool for MicroRNA set analysis.

PubMed

Li, Jianwei; Han, Xiaofen; Wan, Yanping; Zhang, Shan; Zhao, Yingshu; Fan, Rui; Cui, Qinghua; Zhou, Yuan

2018-06-06

With the rapid accumulation of high-throughput microRNA (miRNA) expression profile, the up-to-date resource for analyzing the functional and disease associations of miRNAs is increasingly demanded. We here describe the updated server TAM 2.0 for miRNA set enrichment analysis. Through manual curation of over 9000 papers, a more than two-fold growth of reference miRNA sets has been achieved in comparison with previous TAM, which covers 9945 and 1584 newly collected miRNA-disease and miRNA-function associations, respectively. Moreover, TAM 2.0 allows users not only to test the functional and disease annotations of miRNAs by overrepresentation analysis, but also to compare the input de-regulated miRNAs with those de-regulated in other disease conditions via correlation analysis. Finally, the functions for miRNA set query and result visualization are also enabled in the TAM 2.0 server to facilitate the community. The TAM 2.0 web server is freely accessible at http://www.scse.hebut.edu.cn/tam/ or http://www.lirmed.com/tam2/.

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

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

PubMed Central

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

2012-01-01

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

Near-common-path interferometer for imaging Fourier-transform spectroscopy in wide-field microscopy

PubMed Central

Wadduwage, Dushan N.; Singh, Vijay Raj; Choi, Heejin; Yaqoob, Zahid; Heemskerk, Hans; Matsudaira, Paul; So, Peter T. C.

2017-01-01

Imaging Fourier-transform spectroscopy (IFTS) is a powerful method for biological hyperspectral analysis based on various imaging modalities, such as fluorescence or Raman. Since the measurements are taken in the Fourier space of the spectrum, it can also take advantage of compressed sensing strategies. IFTS has been readily implemented in high-throughput, high-content microscope systems based on wide-field imaging modalities. However, there are limitations in existing wide-field IFTS designs. Non-common-path approaches are less phase-stable. Alternatively, designs based on the common-path Sagnac interferometer are stable, but incompatible with high-throughput imaging. They require exhaustive sequential scanning over large interferometric path delays, making compressive strategic data acquisition impossible. In this paper, we present a novel phase-stable, near-common-path interferometer enabling high-throughput hyperspectral imaging based on strategic data acquisition. Our results suggest that this approach can improve throughput over those of many other wide-field spectral techniques by more than an order of magnitude without compromising phase stability. PMID:29392168

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

PubMed Central

Choudhry, Priya

2016-01-01

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

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

PubMed

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

2012-12-01

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

High-Throughput Density Measurement Using Magnetic Levitation.

PubMed

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

2018-06-20

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

Microfluidics for genome-wide studies involving next generation sequencing

PubMed Central

Murphy, Travis W.; Lu, Chang

2017-01-01

Next-generation sequencing (NGS) has revolutionized how molecular biology studies are conducted. Its decreasing cost and increasing throughput permit profiling of genomic, transcriptomic, and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this article, we review recent progress on applying microfluidics to facilitate genome-wide studies. We emphasize on several technical aspects of NGS and how they benefit from coupling with microfluidic technology. We also summarize recent efforts on developing microfluidic technology for genomic, transcriptomic, and epigenomic studies, with emphasis on single cell analysis. We envision rapid growth in these directions, driven by the needs for testing scarce primary cell samples from patients in the context of precision medicine. PMID:28396707

Sequencing of Oligourea Foldamers by Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Bathany, Katell; Owens, Neil W.; Guichard, Gilles; Schmitter, Jean-Marie

2013-03-01

This study is focused on sequence analysis of peptidomimetic helical oligoureas by means of tandem mass spectrometry, to build a basis for de novo sequencing for future high-throughput combinatorial library screening of oligourea foldamers. After the evaluation of MS/MS spectra obtained for model compounds with either MALDI or ESI sources, we found that the MALDI-TOF-TOF instrument gave more satisfactory results. MS/MS spectra of oligoureas generated by decay of singly charged precursor ions show major ion series corresponding to fragmentation across both CO-NH and N'H-CO urea bonds. Oligourea backbones fragment to produce a pattern of a, x, b, and y type fragment ions. De novo decoding of spectral information is facilitated by the occurrence of low mass reporter ions, representative of constitutive monomers, in an analogous manner to the use of immonium ions for peptide sequencing.

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

PubMed Central

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

2015-01-01

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

Assaying gene function by growth competition experiment.

PubMed

Merritt, Joshua; Edwards, Jeremy S

2004-07-01

High-throughput screening and analysis is one of the emerging paradigms in biotechnology. In particular, high-throughput methods are essential in the field of functional genomics because of the vast amount of data generated in recent and ongoing genome sequencing efforts. In this report we discuss integrated functional analysis methodologies which incorporate both a growth competition component and a highly parallel assay used to quantify results of the growth competition. Several applications of the two most widely used technologies in the field, i.e., transposon mutagenesis and deletion strain library growth competition, and individual applications of several developing or less widely reported technologies are presented.

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.

How empowering is hospital care for older people with advanced disease? Barriers and facilitators from a cross-national ethnography in England, Ireland and the USA

PubMed Central

Selman, Lucy Ellen; Daveson, Barbara A.; Smith, Melinda; Johnston, Bridget; Ryan, Karen; Morrison, R. Sean; Pannell, Caty; McQuillan, Regina; de Wolf-Linder, Suzanne; Pantilat, Steven Z.; Klass, Lara; Meier, Diane; Normand, Charles; Higginson, Irene J.

2017-01-01

Abstract Background patient empowerment, through which patients become self-determining agents with some control over their health and healthcare, is a common theme across health policies globally. Most care for older people is in the acute setting, but there is little evidence to inform the delivery of empowering hospital care. Objective we aimed to explore challenges to and facilitators of empowerment among older people with advanced disease in hospital, and the impact of palliative care. Methods we conducted an ethnography in six hospitals in England, Ireland and the USA. The ethnography involved: interviews with patients aged ≥65, informal caregivers, specialist palliative care (SPC) staff and other clinicians who cared for older adults with advanced disease, and fieldwork. Data were analysed using directed thematic analysis. Results analysis of 91 interviews and 340 h of observational data revealed substantial challenges to empowerment: poor communication and information provision, combined with routinised and fragmented inpatient care, restricted patients’ self-efficacy, self-management, choice and decision-making. Information and knowledge were often necessary for empowerment, but not sufficient: empowerment depended on patient-centredness being enacted at an organisational and staff level. SPC facilitated empowerment by prioritising patient-centred care, tailored communication and information provision, and the support of other clinicians. Conclusions empowering older people in the acute setting requires changes throughout the health system. Facilitators of empowerment include excellent staff–patient communication, patient-centred, relational care, an organisational focus on patient experience rather than throughput, and appropriate access to SPC. Findings have relevance for many high- and middle-income countries with a growing population of older patients with advanced disease. PMID:27810850

Development of a Scintillation Proximity Assay (SPA) Based, High Throughput Screening Feasible Method for the Identification of PDE12 Activity Modulators.

PubMed

Mang, Samuel; Bucher, Hannes; Nickolaus, Peter

2016-01-01

The scintillation proximity assay (SPA) technology has been widely used to establish high throughput screens (HTS) for a range of targets in the pharmaceutical industry. PDE12 (aka. 2'- phosphodiesterase) has been published to participate in the degradation of oligoadenylates that are involved in the establishment of an antiviral state via the activation of ribonuclease L (RNAse-L). Degradation of oligoadenylates by PDE12 terminates these antiviral activities, leading to decreased resistance of cells for a variety of viral pathogens. Therefore inhibitors of PDE12 are discussed as antiviral therapy. Here we describe the use of the yttrium silicate SPA bead technology to assess inhibitory activity of compounds against PDE12 in a homogeneous, robust HTS feasible assay using tritiated adenosine-P-adenylate ([3H]ApA) as substrate. We found that the used [3H]ApA educt, was not able to bind to SPA beads, whereas the product [3H]AMP, as known before, was able to bind to SPA beads. This enables the measurement of PDE12 activity on [3H]ApA as a substrate using a wallac microbeta counter. This method describes a robust and high throughput capable format in terms of specificity, commonly used compound solvents, ease of detection and assay matrices. The method could facilitate the search for PDE12 inhibitors as antiviral compounds.

A high-throughput assay for enzymatic polyester hydrolysis activity by fluorimetric detection.

PubMed

Wei, Ren; Oeser, Thorsten; Billig, Susan; Zimmermann, Wolfgang

2012-12-01

A fluorimetric assay for the fast determination of the activity of polyester-hydrolyzing enzymes in a large number of samples has been developed. Terephthalic acid (TPA) is a main product of the enzymatic hydrolysis of polyethylene terephthalate (PET), a synthetic polyester. Terephthalate has been quantified following its conversion to the fluorescent 2-hydroxyterephthalate by an iron autoxidation-mediated generation of free hydroxyl radicals. The assay proved to be robust at different buffer concentrations, reaction times, pH values, and in the presence of proteins. A validation of the assay was performed by analyzing TPA formation from PET films and nanoparticles catalyzed by a polyester hydrolase from Thermobifida fusca KW3 in a 96-well microplate format. The results showed a close correlation (R(2) = 0.99) with those obtained by a considerably more tedious and time-consuming HPLC method, suggesting the aptness of the fluorimetric assay for a high-throughput screening for polyester hydrolases. The method described in this paper will facilitate the detection and development of biocatalysts for the modification and degradation of synthetic polymers. The fluorimetric assay can be used to quantify the amount of TPA obtained as the final degradation product of the enzymatic hydrolysis of PET. In a microplate format, this assay can be applied for the high-throughput screening of polyester hydrolases. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel quantitative high-throughput screen identifies drugs that both activate SUMO conjugation via the inhibition of microRNAs 182 and 183 and facilitate neuroprotection in a model of oxygen and glucose deprivation

PubMed Central

Bernstock, Joshua D; Lee, Yang-ja; Peruzzotti-Jametti, Luca; Southall, Noel; Johnson, Kory R; Maric, Dragan; Volpe, Giulio; Kouznetsova, Jennifer; Zheng, Wei; Pluchino, Stefano

2015-01-01

The conjugation/de-conjugation of Small Ubiquitin-like Modifier (SUMO) has been shown to be associated with a diverse set of physiologic/pathologic conditions. The clinical significance and ostensible therapeutic utility offered via the selective control of the global SUMOylation process has become readily apparent in ischemic pathophysiology. Herein, we describe the development of a novel quantitative high-throughput screening (qHTS) system designed to identify small molecules capable of increasing SUMOylation via the regulation/inhibition of members of the microRNA (miRNA)-182 family. This assay employs a SHSY5Y human neuroblastoma cell line stably transfected with a dual firefly-Renilla luciferase reporter system for identification of specific inhibitors of either miR-182 or miR-183. In this study, we have identified small molecules capable of inducing increased global conjugation of SUMO in both SHSY5Y cells and rat E18-derived primary cortical neurons. The protective effects of a number of the identified compounds were confirmed via an in vitro ischemic model (oxygen/glucose deprivation). Of note, this assay can be easily repurposed to allow high-throughput analyses of the potential drugability of other relevant miRNA(s) in ischemic pathobiology. PMID:26661196

Performance-scalable volumetric data classification for online industrial inspection

NASA Astrophysics Data System (ADS)

Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

2002-03-01

Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

Multipurpose HTS Coagulation Analysis: Assay Development and Assessment of Coagulopathic Snake Venoms

PubMed Central

Still, Kristina B. M.; Nandlal, Randjana S. S.; Slagboom, Julien; Somsen, Govert W.; Kool, Jeroen

2017-01-01

Coagulation assays currently employed are often low throughput, require specialized equipment and/or require large blood/plasma samples. This study describes the development, optimization and early application of a generic low-volume and high-throughput screening (HTS) assay for coagulation activity. The assay is a time-course spectrophotometric measurement which kinetically measures the clotting profile of bovine or human plasma incubated with Ca2+ and a test compound. The HTS assay can be a valuable new tool for coagulation diagnostics in hospitals, for research in coagulation disorders, for drug discovery and for venom research. A major effect following envenomation by many venomous snakes is perturbation of blood coagulation caused by haemotoxic compounds present in the venom. These compounds, such as anticoagulants, are potential leads in drug discovery for cardiovascular diseases. The assay was implemented in an integrated analytical approach consisting of reversed-phase liquid chromatography (LC) for separation of crude venom components in combination with parallel post-column coagulation screening and mass spectrometry (MS). The approach was applied for the rapid assessment and identification of profiles of haemotoxic compounds in snake venoms. Procoagulant and anticoagulant activities were correlated with accurate masses from the parallel MS measurements, facilitating the detection of peptides showing strong anticoagulant activity. PMID:29186818

A global "imaging'' view on systems approaches in immunology.

PubMed

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

2012-12-01

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

clubber: removing the bioinformatics bottleneck in big data analyses.

PubMed

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2017-06-13

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these "big data" analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber's goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment.

clubber: removing the bioinformatics bottleneck in big data analyses

PubMed Central

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2018-01-01

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment. PMID:28609295

Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

PubMed Central

Dasilva, Noelia; Díez, Paula; Matarraz, Sergio; González-González, María; Paradinas, Sara; Orfao, Alberto; Fuentes, Manuel

2012-01-01

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors. PMID:22438764

A universal method for automated gene mapping

PubMed Central

Zipperlen, Peder; Nairz, Knud; Rimann, Ivo; Basler, Konrad; Hafen, Ernst; Hengartner, Michael; Hajnal, Alex

2005-01-01

Small insertions or deletions (InDels) constitute a ubiquituous class of sequence polymorphisms found in eukaryotic genomes. Here, we present an automated high-throughput genotyping method that relies on the detection of fragment-length polymorphisms (FLPs) caused by InDels. The protocol utilizes standard sequencers and genotyping software. We have established genome-wide FLP maps for both Caenorhabditis elegans and Drosophila melanogaster that facilitate genetic mapping with a minimum of manual input and at comparatively low cost. PMID:15693948

Extruder system for high-throughput/steady-state hydrogen ice supply and application for pellet fueling of reactor-scale fusion experiments

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

Combs, S.K.; Foust, C.R.; Qualls, A.L.

Pellet injection systems for the next-generation fusion devices, such as the proposed International Thermonuclear Experimental Reactor (ITER), will require feed systems capable of providing a continuous supply of hydrogen ice at high throughputs. A straightforward concept in which multiple extruder units operate in tandem has been under development at the Oak Ridge National Laboratory. A prototype with three large-volume extruder units has been fabricated and tested in the laboratory. In experiments, it was found that each extruder could provide volumetric ice flow rates of up to {approximately}1.3 cm{sup 3}/s (for {approximately}10 s), which is sufficient for fueling fusion reactors atmore » the gigawatt power level. With the three extruders of the prototype operating in sequence, a steady rate of {approximately}0.33 cm{sup 3}/s was maintained for a duration of 1 h. Even steady-state rates approaching the full ITER design value ({approximately}1 cm{sup 3}/s) may be feasible with the prototype. However, additional extruder units (1{endash}3) would facilitate operations at the higher throughputs and reduce the duty cycle of each unit. The prototype can easily accommodate steady-state pellet fueling of present large tokamaks or other near-term plasma experiments.« less

High-throughput method for the quantitation of metabolites and co-factors from homocysteine-methionine cycle for nutritional status assessment.

PubMed

Da Silva, Laeticia; Collino, Sebastiano; Cominetti, Ornella; Martin, Francois-Pierre; Montoliu, Ivan; Moreno, Sergio Oller; Corthesy, John; Kaput, Jim; Kussmann, Martin; Monteiro, Jacqueline Pontes; Guiraud, Seu Ping

2016-09-01

There is increasing interest in the profiling and quantitation of methionine pathway metabolites for health management research. Currently, several analytical approaches are required to cover metabolites and co-factors. We report the development and the validation of a method for the simultaneous detection and quantitation of 13 metabolites in red blood cells. The method, validated in a cohort of healthy human volunteers, shows a high level of accuracy and reproducibility. This high-throughput protocol provides a robust coverage of central metabolites and co-factors in one single analysis and in a high-throughput fashion. In large-scale clinical settings, the use of such an approach will significantly advance the field of nutritional research in health and disease.

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.

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

PubMed

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

2016-05-01

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

Novel Informatic Approaches to Analyze Gene Expression Data with the ToxCast 320 Chemical Library in Cultures of Primary Human Hepatocytes

EPA Science Inventory

Prevailing methodologies in the analysis of gene expression data often neglect to incorporate full concentration and time response due to limitations in throughput and sensitivity with traditional microarray approaches. We have developed a high throughput assay suite using primar...

From cancer genomes to cancer models: bridging the gaps

PubMed Central

Baudot, Anaïs; Real, Francisco X.; Izarzugaza, José M. G.; Valencia, Alfonso

2009-01-01

Cancer genome projects are now being expanded in an attempt to provide complete landscapes of the mutations that exist in tumours. Although the importance of cataloguing genome variations is well recognized, there are obvious difficulties in bridging the gaps between high-throughput resequencing information and the molecular mechanisms of cancer evolution. Here, we describe the current status of the high-throughput genomic technologies, and the current limitations of the associated computational analysis and experimental validation of cancer genetic variants. We emphasize how the current cancer-evolution models will be influenced by the high-throughput approaches, in particular through efforts devoted to monitoring tumour progression, and how, in turn, the integration of data and models will be translated into mechanistic knowledge and clinical applications. PMID:19305388

Loeffler 4.0: Diagnostic Metagenomics.

PubMed

Höper, Dirk; Wylezich, Claudia; Beer, Martin

2017-01-01

A new world of possibilities for "virus discovery" was opened up with high-throughput sequencing becoming available in the last decade. While scientifically metagenomic analysis was established before the start of the era of high-throughput sequencing, the availability of the first second-generation sequencers was the kick-off for diagnosticians to use sequencing for the detection of novel pathogens. Today, diagnostic metagenomics is becoming the standard procedure for the detection and genetic characterization of new viruses or novel virus variants. Here, we provide an overview about technical considerations of high-throughput sequencing-based diagnostic metagenomics together with selected examples of "virus discovery" for animal diseases or zoonoses and metagenomics for food safety or basic veterinary research. © 2017 Elsevier Inc. All rights reserved.

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.

A data set from flash X-ray imaging of carboxysomes

NASA Astrophysics Data System (ADS)

Hantke, Max F.; Hasse, Dirk; Ekeberg, Tomas; John, Katja; Svenda, Martin; Loh, Duane; Martin, Andrew V.; Timneanu, Nicusor; Larsson, Daniel S. D.; van der Schot, Gijs; Carlsson, Gunilla H.; Ingelman, Margareta; Andreasson, Jakob; Westphal, Daniel; Iwan, Bianca; Uetrecht, Charlotte; Bielecki, Johan; Liang, Mengning; Stellato, Francesco; Deponte, Daniel P.; Bari, Sadia; Hartmann, Robert; Kimmel, Nils; Kirian, Richard A.; Seibert, M. Marvin; Mühlig, Kerstin; Schorb, Sebastian; Ferguson, Ken; Bostedt, Christoph; Carron, Sebastian; Bozek, John D.; Rolles, Daniel; Rudenko, Artem; Foucar, Lutz; Epp, Sascha W.; Chapman, Henry N.; Barty, Anton; Andersson, Inger; Hajdu, Janos; Maia, Filipe R. N. C.

2016-08-01

Ultra-intense femtosecond X-ray pulses from X-ray lasers permit structural studies on single particles and biomolecules without crystals. We present a large data set on inherently heterogeneous, polyhedral carboxysome particles. Carboxysomes are cell organelles that vary in size and facilitate up to 40% of Earth’s carbon fixation by cyanobacteria and certain proteobacteria. Variation in size hinders crystallization. Carboxysomes appear icosahedral in the electron microscope. A protein shell encapsulates a large number of Rubisco molecules in paracrystalline arrays inside the organelle. We used carboxysomes with a mean diameter of 115±26 nm from Halothiobacillus neapolitanus. A new aerosol sample-injector allowed us to record 70,000 low-noise diffraction patterns in 12 min. Every diffraction pattern is a unique structure measurement and high-throughput imaging allows sampling the space of structural variability. The different structures can be separated and phased directly from the diffraction data and open a way for accurate, high-throughput studies on structures and structural heterogeneity in biology and elsewhere.

High throughput exploration of process-property linkages in Al-6061 using instrumented spherical microindentation and microstructurally graded samples

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

Weaver, Jordan S.; Khosravani, Ali; Castillo, Andrew

Recent spherical nanoindentation protocols have proven robust at capturing the local elastic-plastic response of polycrystalline metal samples at length scales much smaller than the grain size. In this work, we extend these protocols to length scales that include multiple grains to recover microindentation stress-strain curves. These new protocols are first established in this paper and then demonstrated for Al-6061 by comparing the measured indentation stress-strain curves with the corresponding measurements from uniaxial tension tests. More specifically, the scaling factors between the uniaxial yield strength and the indentation yield strength was determined to be about 1.9, which is significantly lower thanmore » the value of 2.8 used commonly in literature. Furthermore, the reasons for this difference are discussed. Second, the benefits of these new protocols in facilitating high throughput exploration of process-property relationships are demonstrated through a simple case study.« less

The ESFRI Instruct Core Centre Frankfurt: automated high-throughput crystallization suited for membrane proteins and more.

PubMed

Thielmann, Yvonne; Koepke, Juergen; Michel, Hartmut

2012-06-01

Structure determination of membrane proteins and membrane protein complexes is still a very challenging field. To facilitate the work on membrane proteins the Core Centre follows a strategy that comprises four labs of protein analytics and crystal handling, covering mass spectrometry, calorimetry, crystallization and X-ray diffraction. This general workflow is presented and a capacity of 20% of the operating time of all systems is provided to the European structural biology community within the ESFRI Instruct program. A description of the crystallization service offered at the Core Centre is given with detailed information on screening strategy, screens used and changes to adapt high throughput for membrane proteins. Our aim is to constantly develop the Core Centre towards the usage of more efficient methods. This strategy might also include the ability to automate all steps from crystallization trials to crystal screening; here we look ahead how this aim might be realized at the Core Centre.

High throughput exploration of process-property linkages in Al-6061 using instrumented spherical microindentation and microstructurally graded samples

DOE PAGES

Weaver, Jordan S.; Khosravani, Ali; Castillo, Andrew; ...

2016-06-14

Recent spherical nanoindentation protocols have proven robust at capturing the local elastic-plastic response of polycrystalline metal samples at length scales much smaller than the grain size. In this work, we extend these protocols to length scales that include multiple grains to recover microindentation stress-strain curves. These new protocols are first established in this paper and then demonstrated for Al-6061 by comparing the measured indentation stress-strain curves with the corresponding measurements from uniaxial tension tests. More specifically, the scaling factors between the uniaxial yield strength and the indentation yield strength was determined to be about 1.9, which is significantly lower thanmore » the value of 2.8 used commonly in literature. Furthermore, the reasons for this difference are discussed. Second, the benefits of these new protocols in facilitating high throughput exploration of process-property relationships are demonstrated through a simple case study.« less

Automated solid-phase subcloning based on beads brought into proximity by magnetic force.

PubMed

Hudson, Elton P; Nikoshkov, Andrej; Uhlen, Mathias; Rockberg, Johan

2012-01-01

In the fields of proteomics, metabolic engineering and synthetic biology there is a need for high-throughput and reliable cloning methods to facilitate construction of expression vectors and genetic pathways. Here, we describe a new approach for solid-phase cloning in which both the vector and the gene are immobilized to separate paramagnetic beads and brought into proximity by magnetic force. Ligation events were directly evaluated using fluorescent-based microscopy and flow cytometry. The highest ligation efficiencies were obtained when gene- and vector-coated beads were brought into close contact by application of a magnet during the ligation step. An automated procedure was developed using a laboratory workstation to transfer genes into various expression vectors and more than 95% correct clones were obtained in a number of various applications. The method presented here is suitable for efficient subcloning in an automated manner to rapidly generate a large number of gene constructs in various vectors intended for high throughput applications.

High-throughput detection of ethanol-producing cyanobacteria in a microdroplet platform

PubMed Central

Abalde-Cela, Sara; Gould, Anna; Liu, Xin; Kazamia, Elena; Smith, Alison G.; Abell, Chris

2015-01-01

Ethanol production by microorganisms is an important renewable energy source. Most processes involve fermentation of sugars from plant feedstock, but there is increasing interest in direct ethanol production by photosynthetic organisms. To facilitate this, a high-throughput screening technique for the detection of ethanol is required. Here, a method for the quantitative detection of ethanol in a microdroplet-based platform is described that can be used for screening cyanobacterial strains to identify those with the highest ethanol productivity levels. The detection of ethanol by enzymatic assay was optimized both in bulk and in microdroplets. In parallel, the encapsulation of engineered ethanol-producing cyanobacteria in microdroplets and their growth dynamics in microdroplet reservoirs were demonstrated. The combination of modular microdroplet operations including droplet generation for cyanobacteria encapsulation, droplet re-injection and pico-injection, and laser-induced fluorescence, were used to create this new platform to screen genetically engineered strains of cyanobacteria with different levels of ethanol production. PMID:25878135

High-throughput platform assay technology for the discovery of pre-microrna-selective small molecule probes.

PubMed

Lorenz, Daniel A; Song, James M; Garner, Amanda L

2015-01-21

MicroRNAs (miRNA) play critical roles in human development and disease. As such, the targeting of miRNAs is considered attractive as a novel therapeutic strategy. A major bottleneck toward this goal, however, has been the identification of small molecule probes that are specific for select RNAs and methods that will facilitate such discovery efforts. Using pre-microRNAs as proof-of-concept, herein we report a conceptually new and innovative approach for assaying RNA-small molecule interactions. Through this platform assay technology, which we term catalytic enzyme-linked click chemistry assay or cat-ELCCA, we have designed a method that can be implemented in high throughput, is virtually free of false readouts, and is general for all nucleic acids. Through cat-ELCCA, we envision the discovery of selective small molecule ligands for disease-relevant miRNAs to promote the field of RNA-targeted drug discovery and further our understanding of the role of miRNAs in cellular biology.

A real-time high-throughput fluorescence assay for sphingosine kinases

PubMed Central

Lima, Santiago; Milstien, Sheldon; Spiegel, Sarah

2014-01-01

Sphingosine kinases (SphKs), of which there are two isoforms, SphK1 and SphK2, have been implicated in regulation of many important cellular processes. We have developed an assay for monitoring SphK1 and SphK2 activity in real time without the need for organic partitioning of products, radioactive materials, or specialized equipment. The assay conveniently follows SphK-dependent changes in 7-nitro-2-1,3-benzoxadiazol-4-yl (NBD)-labeled sphingosine (Sph) fluorescence and can be easily performed in 384-well plate format with small reaction volumes. We present data showing dose-proportional responses to enzyme, substrate, and inhibitor concentrations. The SphK1 and SphK2 binding affinities for NBD-Sph and the IC50 values of inhibitors determined were consistent with those reported with other methods. Because of the versatility and simplicity of the assay, it should facilitate the routine characterization of inhibitors and SphK mutants and can be readily used for compound library screening in high-throughput format. PMID:24792926

Automated Solid-Phase Subcloning Based on Beads Brought into Proximity by Magnetic Force

PubMed Central

Hudson, Elton P.; Nikoshkov, Andrej; Uhlen, Mathias; Rockberg, Johan

2012-01-01

In the fields of proteomics, metabolic engineering and synthetic biology there is a need for high-throughput and reliable cloning methods to facilitate construction of expression vectors and genetic pathways. Here, we describe a new approach for solid-phase cloning in which both the vector and the gene are immobilized to separate paramagnetic beads and brought into proximity by magnetic force. Ligation events were directly evaluated using fluorescent-based microscopy and flow cytometry. The highest ligation efficiencies were obtained when gene- and vector-coated beads were brought into close contact by application of a magnet during the ligation step. An automated procedure was developed using a laboratory workstation to transfer genes into various expression vectors and more than 95% correct clones were obtained in a number of various applications. The method presented here is suitable for efficient subcloning in an automated manner to rapidly generate a large number of gene constructs in various vectors intended for high throughput applications. PMID:22624028

Real-time detection and analysis of Whispering gallery mode resonance in high-throughput flowing monodisperse microdroplets

NASA Astrophysics Data System (ADS)

El Abed, Abdel I.; Taly, Valérie

2013-11-01

We investigate light coupling into highly monodisperse liquid microdroplets, which are produced and manipulated at kHz rates in a microfluidic device. We show that such coupling leads to Whispering gallery mode resonances (WGMs) which are detected and analyzed versus time during the fast displacement of microdroplets into the microfluidic channel. Our results show that droplet-based microfluidics may be applied advantageously in the promising field of high-throughput label-free biosensing.

Subnuclear foci quantification using high-throughput 3D image cytometry

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Who's for dinner? High-throughput sequencing reveals bat dietary differentiation in a biodiversity hotspot where prey taxonomy is largely undescribed.

PubMed

Burgar, Joanna M; Murray, Daithi C; Craig, Michael D; Haile, James; Houston, Jayne; Stokes, Vicki; Bunce, Michael

2014-08-01

Effective management and conservation of biodiversity requires understanding of predator-prey relationships to ensure the continued existence of both predator and prey populations. Gathering dietary data from predatory species, such as insectivorous bats, often presents logistical challenges, further exacerbated in biodiversity hot spots because prey items are highly speciose, yet their taxonomy is largely undescribed. We used high-throughput sequencing (HTS) and bioinformatic analyses to phylogenetically group DNA sequences into molecular operational taxonomic units (MOTUs) to examine predator-prey dynamics of three sympatric insectivorous bat species in the biodiversity hotspot of south-western Australia. We could only assign between 4% and 20% of MOTUs to known genera or species, depending on the method used, underscoring the importance of examining dietary diversity irrespective of taxonomic knowledge in areas lacking a comprehensive genetic reference database. MOTU analysis confirmed that resource partitioning occurred, with dietary divergence positively related to the ecomorphological divergence of the three bat species. We predicted that bat species' diets would converge during times of high energetic requirements, that is, the maternity season for females and the mating season for males. There was an interactive effect of season on female, but not male, bat species' diets, although small sample sizes may have limited our findings. Contrary to our predictions, females of two ecomorphologically similar species showed dietary convergence during the mating season rather than the maternity season. HTS-based approaches can help elucidate complex predator-prey relationships in highly speciose regions, which should facilitate the conservation of biodiversity in genetically uncharacterized areas, such as biodiversity hotspots. © 2013 John Wiley & Sons Ltd.

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

PubMed

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

2017-11-03

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc) transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids) or genome mutation (e.g., gene mutation, deletion, epitope tagging) is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

Tox21 Enricher: Web-based Chemical/Biological Functional Annotation Analysis Tool Based on Tox21 Toxicity Screening Platform.

PubMed

Hur, Junguk; Danes, Larson; Hsieh, Jui-Hua; McGregor, Brett; Krout, Dakota; Auerbach, Scott

2018-05-01

The US Toxicology Testing in the 21st Century (Tox21) program was established to develop more efficient and human-relevant toxicity assessment methods. The Tox21 program screens >10,000 chemicals using quantitative high-throughput screening (qHTS) of assays that measure effects on toxicity pathways. To date, more than 70 assays have yielded >12 million concentration-response curves. The patterns of activity across assays can be used to define similarity between chemicals. Assuming chemicals with similar activity profiles have similar toxicological properties, we may infer toxicological properties based on its neighbourhood. One approach to inference is chemical/biological annotation enrichment analysis. Here, we present Tox21 Enricher, a web-based chemical annotation enrichment tool for the Tox21 toxicity screening platform. Tox21 Enricher identifies over-represented chemical/biological annotations among lists of chemicals (neighbourhoods), facilitating the identification of the toxicological properties and mechanisms in the chemical set. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metabonomics and its role in amino acid nutrition research.

PubMed

He, Qinghua; Yin, Yulong; Zhao, Feng; Kong, Xiangfeng; Wu, Guoyao; Ren, Pingping

2011-06-01

Metabonomics combines metabolic profiling and multivariate data analysis to facilitate the high-throughput analysis of metabolites in biological samples. This technique has been developed as a powerful analytical tool and hence has found successful widespread applications in many areas of bioscience. Metabonomics has also become an important part of systems biology. As a sensitive and powerful method, metabonomics can quantitatively measure subtle dynamic perturbations of metabolic pathways in organisms due to changes in pathophysiological, nutritional, and epigenetic states. Therefore, metabonomics holds great promise to enhance our understanding of the complex relationship between amino acids and metabolism to define the roles for dietary amino acids in maintaining health and the development of disease. Such a technique also aids in the studies of functions, metabolic regulation, safety, and individualized requirements of amino acids. Here, we highlight the common workflow of metabonomics and some of the applications to amino acid nutrition research to illustrate the great potential of this exciting new frontier in bioscience.

Is this the real time for genomics?

PubMed

Guarnaccia, Maria; Gentile, Giulia; Alessi, Enrico; Schneider, Claudio; Petralia, Salvatore; Cavallaro, Sebastiano

2014-01-01

In the last decades, molecular biology has moved from gene-by-gene analysis to more complex studies using a genome-wide scale. Thanks to high-throughput genomic technologies, such as microarrays and next-generation sequencing, a huge amount of information has been generated, expanding our knowledge on the genetic basis of various diseases. Although some of this information could be transferred to clinical diagnostics, the technologies available are not suitable for this purpose. In this review, we will discuss the drawbacks associated with the use of traditional DNA microarrays in diagnostics, pointing out emerging platforms that could overcome these obstacles and offer a more reproducible, qualitative and quantitative multigenic analysis. New miniaturized and automated devices, called Lab-on-Chip, begin to integrate PCR and microarray on the same platform, offering integrated sample-to-result systems. The introduction of this kind of innovative devices may facilitate the transition of genome-based tests into clinical routine. Copyright © 2014. Published by Elsevier Inc.

Haplotag: Software for Haplotype-Based Genotyping-by-Sequencing Analysis

PubMed Central

Tinker, Nicholas A.; Bekele, Wubishet A.; Hattori, Jiro

2016-01-01

Genotyping-by-sequencing (GBS), and related methods, are based on high-throughput short-read sequencing of genomic complexity reductions followed by discovery of single nucleotide polymorphisms (SNPs) within sequence tags. This provides a powerful and economical approach to whole-genome genotyping, facilitating applications in genomics, diversity analysis, and molecular breeding. However, due to the complexity of analyzing large data sets, applications of GBS may require substantial time, expertise, and computational resources. Haplotag, the novel GBS software described here, is freely available, and operates with minimal user-investment on widely available computer platforms. Haplotag is unique in fulfilling the following set of criteria: (1) operates without a reference genome; (2) can be used in a polyploid species; (3) provides a discovery mode, and a production mode; (4) discovers polymorphisms based on a model of tag-level haplotypes within sequenced tags; (5) reports SNPs as well as haplotype-based genotypes; and (6) provides an intuitive visual “passport” for each inferred locus. Haplotag is optimized for use in a self-pollinating plant species. PMID:26818073

Phage phenomics: Physiological approaches to characterize novel viral proteins

ScienceCinema

Sanchez, Savannah E. [San Diego State Univ., San Diego, CA (United States); Cuevas, Daniel A. [San Diego State Univ., San Diego, CA (United States); Rostron, Jason E. [San Diego State Univ., San Diego, CA (United States); Liang, Tiffany Y. [San Diego State Univ., San Diego, CA (United States); Pivaroff, Cullen G. [San Diego State Univ., San Diego, CA (United States); Haynes, Matthew R. [San Diego State Univ., San Diego, CA (United States); Nulton, Jim [San Diego State Univ., San Diego, CA (United States); Felts, Ben [San Diego State Univ., San Diego, CA (United States); Bailey, Barbara A. [San Diego State Univ., San Diego, CA (United States); Salamon, Peter [San Diego State Univ., San Diego, CA (United States); Edwards, Robert A. [San Diego State Univ., San Diego, CA (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Burgin, Alex B. [Broad Institute, Cambridge, MA (United States); Segall, Anca M. [San Diego State Univ., San Diego, CA (United States); Rohwer, Forest [San Diego State Univ., San Diego, CA (United States)

2018-06-21

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Thus, representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.

Micro-optics for microfluidic analytical applications.

PubMed

Yang, Hui; Gijs, Martin A M

2018-02-19

This critical review summarizes the developments in the integration of micro-optical elements with microfluidic platforms for facilitating detection and automation of bio-analytical applications. Micro-optical elements, made by a variety of microfabrication techniques, advantageously contribute to the performance of an analytical system, especially when the latter has microfluidic features. Indeed the easy integration of optical control and detection modules with microfluidic technology helps to bridge the gap between the macroscopic world and chip-based analysis, paving the way for automated and high-throughput applications. In our review, we start the discussion with an introduction of microfluidic systems and micro-optical components, as well as aspects of their integration. We continue with a detailed description of different microfluidic and micro-optics technologies and their applications, with an emphasis on the realization of optical waveguides and microlenses. The review continues with specific sections highlighting the advantages of integrated micro-optical components in microfluidic systems for tackling a variety of analytical problems, like cytometry, nucleic acid and protein detection, cell biology, and chemical analysis applications.

Simultaneous fecal microbial and metabolite profiling enables accurate classification of pediatric irritable bowel syndrome.

PubMed

Shankar, Vijay; Reo, Nicholas V; Paliy, Oleg

2015-12-09

We previously showed that stool samples of pre-adolescent and adolescent US children diagnosed with diarrhea-predominant IBS (IBS-D) had different compositions of microbiota and metabolites compared to healthy age-matched controls. Here we explored whether observed fecal microbiota and metabolite differences between these two adolescent populations can be used to discriminate between IBS and health. We constructed individual microbiota- and metabolite-based sample classification models based on the partial least squares multivariate analysis and then applied a Bayesian approach to integrate individual models into a single classifier. The resulting combined classification achieved 84 % accuracy of correct sample group assignment and 86 % prediction for IBS-D in cross-validation tests. The performance of the cumulative classification model was further validated by the de novo analysis of stool samples from a small independent IBS-D cohort. High-throughput microbial and metabolite profiling of subject stool samples can be used to facilitate IBS diagnosis.

Uniform, optimal signal processing of mapped deep-sequencing data.

PubMed

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

Exploiting the Proteome to Improve the Genome-Wide Genetic Analysis of Epistasis in Common Human Diseases

PubMed Central

Pattin, Kristine A.; Moore, Jason H.

2009-01-01

One of the central goals of human genetics is the identification of loci with alleles or genotypes that confer increased susceptibility. The availability of dense maps of single-nucleotide polymorphisms (SNPs) along with high-throughput genotyping technologies has set the stage for routine genome-wide association studies that are expected to significantly improve our ability to identify susceptibility loci. Before this promise can be realized, there are some significant challenges that need to be addressed. We address here the challenge of detecting epistasis or gene-gene interactions in genome-wide association studies. Discovering epistatic interactions in high dimensional datasets remains a challenge due to the computational complexity resulting from the analysis of all possible combinations of SNPs. One potential way to overcome the computational burden of a genome-wide epistasis analysis would be to devise a logical way to prioritize the many SNPs in a dataset so that the data may be analyzed more efficiently and yet still retain important biological information. One of the strongest demonstrations of the functional relationship between genes is protein-protein interaction. Thus, it is plausible that the expert knowledge extracted from protein interaction databases may allow for a more efficient analysis of genome-wide studies as well as facilitate the biological interpretation of the data. In this review we will discuss the challenges of detecting epistasis in genome-wide genetic studies and the means by which we propose to apply expert knowledge extracted from protein interaction databases to facilitate this process. We explore some of the fundamentals of protein interactions and the databases that are publicly available. PMID:18551320

HDX Workbench: Software for the Analysis of H/D Exchange MS Data

NASA Astrophysics Data System (ADS)

Pascal, Bruce D.; Willis, Scooter; Lauer, Janelle L.; Landgraf, Rachelle R.; West, Graham M.; Marciano, David; Novick, Scott; Goswami, Devrishi; Chalmers, Michael J.; Griffin, Patrick R.

2012-09-01

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) is an established method for the interrogation of protein conformation and dynamics. While the data analysis challenge of HDX-MS has been addressed by a number of software packages, new computational tools are needed to keep pace with the improved methods and throughput of this technique. To address these needs, we report an integrated desktop program titled HDX Workbench, which facilitates automation, management, visualization, and statistical cross-comparison of large HDX data sets. Using the software, validated data analysis can be achieved at the rate of generation. The application is available at the project home page http://hdx.florida.scripps.edu.

A noninvasive, direct real-time PCR method for sex determination in multiple avian species

USGS Publications Warehouse

Brubaker, Jessica L.; Karouna-Renier, Natalie K.; Chen, Yu; Jenko, Kathryn; Sprague, Daniel T.; Henry, Paula F.P.

2011-01-01

Polymerase chain reaction (PCR)-based methods to determine the sex of birds are well established and have seen few modifications since they were first introduced in the 1990s. Although these methods allowed for sex determination in species that were previously difficult to analyse, they were not conducive to high-throughput analysis because of the laboriousness of DNA extraction and gel electrophoresis. We developed a high-throughput real-time PCR-based method for analysis of sex in birds, which uses noninvasive sample collection and avoids DNA extraction and gel electrophoresis.

Creation of a small high-throughput screening facility.

PubMed

Flak, Tod

2009-01-01

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

Using In Vitro High-Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards.

PubMed

Burgoon, Lyle D; Druwe, Ingrid L; Painter, Kyle; Yost, Erin E

2017-02-01

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high-throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline-based meta-regression can be used to integrate data across multiple assay replicates to generate a concentration-response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk-specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta-regression, may allow risk assessors to identify points of departure and risk-specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods. © 2016 Society for Risk Analysis.

MPact: the MIPS protein interaction resource on yeast.

PubMed

Güldener, Ulrich; Münsterkötter, Martin; Oesterheld, Matthias; Pagel, Philipp; Ruepp, Andreas; Mewes, Hans-Werner; Stümpflen, Volker

2006-01-01

In recent years, the Munich Information Center for Protein Sequences (MIPS) yeast protein-protein interaction (PPI) dataset has been used in numerous analyses of protein networks and has been called a gold standard because of its quality and comprehensiveness [H. Yu, N. M. Luscombe, H. X. Lu, X. Zhu, Y. Xia, J. D. Han, N. Bertin, S. Chung, M. Vidal and M. Gerstein (2004) Genome Res., 14, 1107-1118]. MPact and the yeast protein localization catalog provide information related to the proximity of proteins in yeast. Beside the integration of high-throughput data, information about experimental evidence for PPIs in the literature was compiled by experts adding up to 4300 distinct PPIs connecting 1500 proteins in yeast. As the interaction data is a complementary part of CYGD, interactive mapping of data on other integrated data types such as the functional classification catalog [A. Ruepp, A. Zollner, D. Maier, K. Albermann, J. Hani, M. Mokrejs, I. Tetko, U. Güldener, G. Mannhaupt, M. Münsterkötter and H. W. Mewes (2004) Nucleic Acids Res., 32, 5539-5545] is possible. A survey of signaling proteins and comparison with pathway data from KEGG demonstrates that based on these manually annotated data only an extensive overview of the complexity of this functional network can be obtained in yeast. The implementation of a web-based PPI-analysis tool allows analysis and visualization of protein interaction networks and facilitates integration of our curated data with high-throughput datasets. The complete dataset as well as user-defined sub-networks can be retrieved easily in the standardized PSI-MI format. The resource can be accessed through http://mips.gsf.de/genre/proj/mpact.

MG-RAST version 4-lessons learned from a decade of low-budget ultra-high-throughput metagenome analysis.

PubMed

Meyer, Folker; Bagchi, Saurabh; Chaterji, Somali; Gerlach, Wolfgang; Grama, Ananth; Harrison, Travis; Paczian, Tobias; Trimble, William L; Wilke, Andreas

2017-09-26

As technologies change, MG-RAST is adapting. Newly available software is being included to improve accuracy and performance. As a computational service constantly running large volume scientific workflows, MG-RAST is the right location to perform benchmarking and implement algorithmic or platform improvements, in many cases involving trade-offs between specificity, sensitivity and run-time cost. The work in [Glass EM, Dribinsky Y, Yilmaz P, et al. ISME J 2014;8:1-3] is an example; we use existing well-studied data sets as gold standards representing different environments and different technologies to evaluate any changes to the pipeline. Currently, we use well-understood data sets in MG-RAST as platform for benchmarking. The use of artificial data sets for pipeline performance optimization has not added value, as these data sets are not presenting the same challenges as real-world data sets. In addition, the MG-RAST team welcomes suggestions for improvements of the workflow. We are currently working on versions 4.02 and 4.1, both of which contain significant input from the community and our partners that will enable double barcoding, stronger inferences supported by longer-read technologies, and will increase throughput while maintaining sensitivity by using Diamond and SortMeRNA. On the technical platform side, the MG-RAST team intends to support the Common Workflow Language as a standard to specify bioinformatics workflows, both to facilitate development and efficient high-performance implementation of the community's data analysis tasks. Published by Oxford University Press on behalf of Entomological Society of America 2017. This work is written by US Government employees and is in the public domain in the US.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens

PubMed Central

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-01-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue® mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents. PMID:22735701

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens.

PubMed

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-08-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents.

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

High-throughput technology for novel SO2 oxidation catalysts

PubMed Central

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

2011-01-01

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

Extended length microchannels for high density high throughput electrophoresis systems

DOEpatents

Davidson, James C.; Balch, Joseph W.

2000-01-01

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

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.

Arrayed water-in-oil droplet bilayers for membrane transport analysis.

PubMed

Watanabe, R; Soga, N; Hara, M; Noji, H

2016-08-02

The water-in-oil droplet bilayer is a simple and useful lipid bilayer system for membrane transport analysis. The droplet interface bilayer is readily formed by the contact of two water-in-oil droplets enwrapped by a phospholipid monolayer. However, the size of individual droplets with femtoliter volumes in a high-throughput manner is difficult to control, resulting in low sensitivity and throughput of membrane transport analysis. To overcome this drawback, in this study, we developed a novel micro-device in which a large number of droplet interface bilayers (>500) are formed at a time by using femtoliter-sized droplet arrays immobilized on a hydrophobic/hydrophilic substrate. The droplet volume was controllable from 3.5 to 350 fL by changing the hydrophobic/hydrophilic pattern on the device, allowing high-throughput analysis of membrane transport mechanisms including membrane permeability to solutes (e.g., ions or small molecules) with or without the aid of transport proteins. Thus, this novel platform broadens the versatility of water-in-oil droplet bilayers and will pave the way for novel analytical and pharmacological applications such as drug screening.

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

PubMed

Zhu, Zhi; Yang, Chaoyong James

2017-01-17

Heterogeneity among individual molecules and cells has posed significant challenges to traditional bulk assays, due to the assumption of average behavior, which would lose important biological information in heterogeneity and result in a misleading interpretation. Single molecule/cell analysis has become an important and emerging field in biological and biomedical research for insights into heterogeneity between large populations at high resolution. Compared with the ensemble bulk method, single molecule/cell analysis explores the information on time trajectories, conformational states, and interactions of individual molecules/cells, all key factors in the study of chemical and biological reaction pathways. Various powerful techniques have been developed for single molecule/cell analysis, including flow cytometry, atomic force microscopy, optical and magnetic tweezers, single-molecule fluorescence spectroscopy, and so forth. However, some of them have the low-throughput issue that has to analyze single molecules/cells one by one. Flow cytometry is a widely used high-throughput technique for single cell analysis but lacks the ability for intercellular interaction study and local environment control. Droplet microfluidics becomes attractive for single molecule/cell manipulation because single molecules/cells can be individually encased in monodisperse microdroplets, allowing high-throughput analysis and manipulation with precise control of the local environment. Moreover, hydrogels, cross-linked polymer networks that swell in the presence of water, have been introduced into droplet microfluidic systems as hydrogel droplet microfluidics. By replacing an aqueous phase with a monomer or polymer solution, hydrogel droplets can be generated on microfluidic chips for encapsulation of single molecules/cells according to the Poisson distribution. The sol-gel transition property endows the hydrogel droplets with new functionalities and diversified applications in single molecule/cell analysis. The hydrogel can act as a 3D cell culture matrix to mimic the extracellular environment for long-term single cell culture, which allows further heterogeneity study in proliferation, drug screening, and metastasis at the single-cell level. The sol-gel transition allows reactions in solution to be performed rapidly and efficiently with product storage in the gel for flexible downstream manipulation and analysis. More importantly, controllable sol-gel regulation provides a new way to maintain phenotype-genotype linkages in the hydrogel matrix for high throughput molecular evolution. In this Account, we will review the hydrogel droplet generation on microfluidics, single molecule/cell encapsulation in hydrogel droplets, as well as the progress made by our group and others in the application of hydrogel droplet microfluidics for single molecule/cell analysis, including single cell culture, single molecule/cell detection, single cell sequencing, and molecular evolution.

Accelerated Combinatorial High Throughput Star Polymer Synthesis via a Rapid One-Pot Sequential Aqueous RAFT (rosa-RAFT) Polymerization Scheme.

PubMed

Cosson, Steffen; Danial, Maarten; Saint-Amans, Julien Rosselgong; Cooper-White, Justin J

2017-04-01

Advanced polymerization methodologies, such as reversible addition-fragmentation transfer (RAFT), allow unprecedented control over star polymer composition, topology, and functionality. However, using RAFT to produce high throughput (HTP) combinatorial star polymer libraries remains, to date, impracticable due to several technical limitations. Herein, the methodology "rapid one-pot sequential aqueous RAFT" or "rosa-RAFT," in which well-defined homo-, copolymer, and mikto-arm star polymers can be prepared in very low to medium reaction volumes (50 µL to 2 mL) via an "arm-first" approach in air within minutes, is reported. Due to the high conversion of a variety of acrylamide/acrylate monomers achieved during each successive short reaction step (each taking 3 min), the requirement for intermediary purification is avoided, drastically facilitating and accelerating the star synthesis process. The presented methodology enables RAFT to be applied to HTP polymeric bio/nanomaterials discovery pipelines, in which hundreds of complex polymeric formulations can be rapidly produced, screened, and scaled up for assessment in a wide range of applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2017-10-01

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

A standardized framework for accurate, high-throughput genotyping of recombinant and non-recombinant viral sequences.

PubMed

Alcantara, Luiz Carlos Junior; Cassol, Sharon; Libin, Pieter; Deforche, Koen; Pybus, Oliver G; Van Ranst, Marc; Galvão-Castro, Bernardo; Vandamme, Anne-Mieke; de Oliveira, Tulio

2009-07-01

Human immunodeficiency virus type-1 (HIV-1), hepatitis B and C and other rapidly evolving viruses are characterized by extremely high levels of genetic diversity. To facilitate diagnosis and the development of prevention and treatment strategies that efficiently target the diversity of these viruses, and other pathogens such as human T-lymphotropic virus type-1 (HTLV-1), human herpes virus type-8 (HHV8) and human papillomavirus (HPV), we developed a rapid high-throughput-genotyping system. The method involves the alignment of a query sequence with a carefully selected set of pre-defined reference strains, followed by phylogenetic analysis of multiple overlapping segments of the alignment using a sliding window. Each segment of the query sequence is assigned the genotype and sub-genotype of the reference strain with the highest bootstrap (>70%) and bootscanning (>90%) scores. Results from all windows are combined and displayed graphically using color-coded genotypes. The new Virus-Genotyping Tools provide accurate classification of recombinant and non-recombinant viruses and are currently being assessed for their diagnostic utility. They have incorporated into several HIV drug resistance algorithms including the Stanford (http://hivdb.stanford.edu) and two European databases (http://www.umcutrecht.nl/subsite/spread-programme/ and http://www.hivrdb.org.uk/) and have been successfully used to genotype a large number of sequences in these and other databases. The tools are a PHP/JAVA web application and are freely accessible on a number of servers including: http://bioafrica.mrc.ac.za/rega-genotype/html/, http://lasp.cpqgm.fiocruz.br/virus-genotype/html/, http://jose.med.kuleuven.be/genotypetool/html/.

Target genes discovery through copy number alteration analysis in human hepatocellular carcinoma.

PubMed

Gu, De-Leung; Chen, Yen-Hsieh; Shih, Jou-Ho; Lin, Chi-Hung; Jou, Yuh-Shan; Chen, Chian-Feng

2013-12-21

High-throughput short-read sequencing of exomes and whole cancer genomes in multiple human hepatocellular carcinoma (HCC) cohorts confirmed previously identified frequently mutated somatic genes, such as TP53, CTNNB1 and AXIN1, and identified several novel genes with moderate mutation frequencies, including ARID1A, ARID2, MLL, MLL2, MLL3, MLL4, IRF2, ATM, CDKN2A, FGF19, PIK3CA, RPS6KA3, JAK1, KEAP1, NFE2L2, C16orf62, LEPR, RAC2, and IL6ST. Functional classification of these mutated genes suggested that alterations in pathways participating in chromatin remodeling, Wnt/β-catenin signaling, JAK/STAT signaling, and oxidative stress play critical roles in HCC tumorigenesis. Nevertheless, because there are few druggable genes used in HCC therapy, the identification of new therapeutic targets through integrated genomic approaches remains an important task. Because a large amount of HCC genomic data genotyped by high density single nucleotide polymorphism arrays is deposited in the public domain, copy number alteration (CNA) analyses of these arrays is a cost-effective way to reveal target genes through profiling of recurrent and overlapping amplicons, homozygous deletions and potentially unbalanced chromosomal translocations accumulated during HCC progression. Moreover, integration of CNAs with other high-throughput genomic data, such as aberrantly coding transcriptomes and non-coding gene expression in human HCC tissues and rodent HCC models, provides lines of evidence that can be used to facilitate the identification of novel HCC target genes with the potential of improving the survival of HCC patients.

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification.

PubMed

Beirnaert, Charlie; Meysman, Pieter; Vu, Trung Nghia; Hermans, Nina; Apers, Sandra; Pieters, Luc; Covaci, Adrian; Laukens, Kris

2018-03-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification

PubMed Central

Pieters, Luc; Covaci, Adrian

2018-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq). PMID:29494588

Evaluation of a High Throughput Starch Analysis Optimised for Wood

PubMed Central

Bellasio, Chandra; Fini, Alessio; Ferrini, Francesco

2014-01-01

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

Automated detection system of single nucleotide polymorphisms using two kinds of functional magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Hongna; Li, Song; Wang, Zhifei; Li, Zhiyang; Deng, Yan; Wang, Hua; Shi, Zhiyang; He, Nongyue

2008-11-01

Single nucleotide polymorphisms (SNPs) comprise the most abundant source of genetic variation in the human genome wide codominant SNPs identification. Therefore, large-scale codominant SNPs identification, especially for those associated with complex diseases, has induced the need for completely high-throughput and automated SNP genotyping method. Herein, we present an automated detection system of SNPs based on two kinds of functional magnetic nanoparticles (MNPs) and dual-color hybridization. The amido-modified MNPs (NH 2-MNPs) modified with APTES were used for DNA extraction from whole blood directly by electrostatic reaction, and followed by PCR, was successfully performed. Furthermore, biotinylated PCR products were captured on the streptavidin-coated MNPs (SA-MNPs) and interrogated by hybridization with a pair of dual-color probes to determine SNP, then the genotype of each sample can be simultaneously identified by scanning the microarray printed with the denatured fluorescent probes. This system provided a rapid, sensitive and highly versatile automated procedure that will greatly facilitate the analysis of different known SNPs in human genome.

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

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.

Line-Focused Optical Excitation of Parallel Acoustic Focused Sample Streams for High Volumetric and Analytical Rate Flow Cytometry.

PubMed

Kalb, Daniel M; Fencl, Frank A; Woods, Travis A; Swanson, August; Maestas, Gian C; Juárez, Jaime J; Edwards, Bruce S; Shreve, Andrew P; Graves, Steven W

2017-09-19

Flow cytometry provides highly sensitive multiparameter analysis of cells and particles but has been largely limited to the use of a single focused sample stream. This limits the analytical rate to ∼50K particles/s and the volumetric rate to ∼250 μL/min. Despite the analytical prowess of flow cytometry, there are applications where these rates are insufficient, such as rare cell analysis in high cellular backgrounds (e.g., circulating tumor cells and fetal cells in maternal blood), detection of cells/particles in large dilute samples (e.g., water quality, urine analysis), or high-throughput screening applications. Here we report a highly parallel acoustic flow cytometer that uses an acoustic standing wave to focus particles into 16 parallel analysis points across a 2.3 mm wide optical flow cell. A line-focused laser and wide-field collection optics are used to excite and collect the fluorescence emission of these parallel streams onto a high-speed camera for analysis. With this instrument format and fluorescent microsphere standards, we obtain analysis rates of 100K/s and flow rates of 10 mL/min, while maintaining optical performance comparable to that of a commercial flow cytometer. The results with our initial prototype instrument demonstrate that the integration of key parallelizable components, including the line-focused laser, particle focusing using multinode acoustic standing waves, and a spatially arrayed detector, can increase analytical and volumetric throughputs by orders of magnitude in a compact, simple, and cost-effective platform. Such instruments will be of great value to applications in need of high-throughput yet sensitive flow cytometry analysis.

ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level

PubMed Central

Rocca-Serra, Philippe; Brandizi, Marco; Maguire, Eamonn; Sklyar, Nataliya; Taylor, Chris; Begley, Kimberly; Field, Dawn; Harris, Stephen; Hide, Winston; Hofmann, Oliver; Neumann, Steffen; Sterk, Peter; Tong, Weida; Sansone, Susanna-Assunta

2010-01-01

Summary: The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories. Availability and Implementation: Software, documentation, case studies and implementations at http://www.isa-tools.org Contact: isatools@googlegroups.com PMID:20679334

Managing the genomic revolution in cancer diagnostics.

PubMed

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.

Dana-Farber Cancer Institute: Identification of Therapeutic Targets Across Cancer Types | Office of Cancer Genomics

Cancer.gov

The Dana Farber Cancer Institute CTD2 Center focuses on the use of high-throughput genetic and bioinformatic approaches to identify and credential oncogenes and co-dependencies in cancers. This Center aims to provide the cancer research community with information that will facilitate the prioritization of targets based on both genomic and functional evidence, inform the most appropriate genetic context for downstream mechanistic and validation studies, and enable the translation of this information into therapeutics and diagnostics.

Surface acoustic wave nebulization facilitating lipid mass spectrometric analysis.

PubMed

Yoon, Sung Hwan; Huang, Yue; Edgar, J Scott; Ting, Ying S; Heron, Scott R; Kao, Yuchieh; Li, Yanyan; Masselon, Christophe D; Ernst, Robert K; Goodlett, David R

2012-08-07

Surface acoustic wave nebulization (SAWN) is a novel method to transfer nonvolatile analytes directly from the aqueous phase to the gas phase for mass spectrometric analysis. The lower ion energetics of SAWN and its planar nature make it appealing for analytically challenging lipid samples. This challenge is a result of their amphipathic nature, labile nature, and tendency to form aggregates, which readily precipitate clogging capillaries used for electrospray ionization (ESI). Here, we report the use of SAWN to characterize the complex glycolipid, lipid A, which serves as the membrane anchor component of lipopolysaccharide (LPS) and has a pronounced tendency to clog nano-ESI capillaries. We also show that unlike ESI SAWN is capable of ionizing labile phospholipids without fragmentation. Lastly, we compare the ease of use of SAWN to the more conventional infusion-based ESI methods and demonstrate the ability to generate higher order tandem mass spectral data of lipid A for automated structure assignment using our previously reported hierarchical tandem mass spectrometry (HiTMS) algorithm. The ease of generating SAWN-MS(n) data combined with HiTMS interpretation offers the potential for high throughput lipid A structure analysis.

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

PubMed

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

2007-11-13

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

High Throughput 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.

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

PubMed

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

2014-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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