High-throughput microarray mapping of cell wall polymers in roots and tubers during the viscosity-reducing process

DEFF Research Database (Denmark)

Huang, Yuhong; Willats, William George Tycho; Lange, Lene

2016-01-01

the viscosity-reducing process are poorly characterized. Comprehensive microarray polymer profiling, which is a high-throughput microarray, was used for the first time to map changes in the cell wall polymers of sweet potato (Ipomoea batatas), cassava (Manihot esculenta), and Canna edulis Ker. over the entire...... viscosity-reducing process. The results indicated that the composition of cell wall polymers among these three roots and tubers was markedly different. The gel-like matrix and glycoprotein network in the C. edulis Ker. cell wall caused difficulty in viscosity reduction. The obvious viscosity reduction......Viscosity reduction has a great impact on the efficiency of ethanol production when using roots and tubers as feedstock. Plant cell wall-degrading enzymes have been successfully applied to overcome the challenges posed by high viscosity. However, the changes in cell wall polymers during...

Metabolic enzyme microarray coupled with miniaturized cell-culture array technology for high-throughput toxicity screening.

Science.gov (United States)

Lee, Moo-Yeal; Dordick, Jonathan S; Clark, Douglas S

2010-01-01

Due to poor drug candidate safety profiles that are often identified late in the drug development process, the clinical progression of new chemical entities to pharmaceuticals remains hindered, thus resulting in the high cost of drug discovery. To accelerate the identification of safer drug candidates and improve the clinical progression of drug candidates to pharmaceuticals, it is important to develop high-throughput tools that can provide early-stage predictive toxicology data. In particular, in vitro cell-based systems that can accurately mimic the human in vivo response and predict the impact of drug candidates on human toxicology are needed to accelerate the assessment of drug candidate toxicity and human metabolism earlier in the drug development process. The in vitro techniques that provide a high degree of human toxicity prediction will be perhaps more important in cosmetic and chemical industries in Europe, as animal toxicity testing is being phased out entirely in the immediate future.We have developed a metabolic enzyme microarray (the Metabolizing Enzyme Toxicology Assay Chip, or MetaChip) and a miniaturized three-dimensional (3D) cell-culture array (the Data Analysis Toxicology Assay Chip, or DataChip) for high-throughput toxicity screening of target compounds and their metabolic enzyme-generated products. The human or rat MetaChip contains an array of encapsulated metabolic enzymes that is designed to emulate the metabolic reactions in the human or rat liver. The human or rat DataChip contains an array of 3D human or rat cells encapsulated in alginate gels for cell-based toxicity screening. By combining the DataChip with the complementary MetaChip, in vitro toxicity results are obtained that correlate well with in vivo rat data.

A cell spot microarray method for production of high density siRNA transfection microarrays

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Mpindi John-Patrick

2011-03-01

Full Text Available Abstract Background High-throughput RNAi screening is widely applied in biological research, but remains expensive, infrastructure-intensive and conversion of many assays to HTS applications in microplate format is not feasible. Results Here, we describe the optimization of a miniaturized cell spot microarray (CSMA method, which facilitates utilization of the transfection microarray technique for disparate RNAi analyses. To promote rapid adaptation of the method, the concept has been tested with a panel of 92 adherent cell types, including primary human cells. We demonstrate the method in the systematic screening of 492 GPCR coding genes for impact on growth and survival of cultured human prostate cancer cells. Conclusions The CSMA method facilitates reproducible preparation of highly parallel cell microarrays for large-scale gene knockdown analyses. This will be critical towards expanding the cell based functional genetic screens to include more RNAi constructs, allow combinatorial RNAi analyses, multi-parametric phenotypic readouts or comparative analysis of many different cell types.

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

International Nuclear Information System (INIS)

Wang, Daqian; Ding, Lili; Zhang, Wei; Zhang, Enyao; Yu, Xinglong; Luo, Zhaofeng; Ou, Huichao

2012-01-01

A new high-throughput surface plasmon resonance (SPR) biosensor based on differential interferometric imaging is reported. The two SPR interferograms of the sensing surface are imaged on two CCD cameras. The phase difference between the two interferograms is 180°. The refractive index related factor (RIRF) of the sensing surface is calculated from the two simultaneously acquired interferograms. The simulation results indicate that the RIRF exhibits a linear relationship with the refractive index of the sensing surface and is unaffected by the noise, drift and intensity distribution of the light source. The affinity and kinetic information can be extracted in real time from continuously acquired RIRF distributions. The results of refractometry experiments show that the dynamic detection range of SPR differential interferometric imaging system can be over 0.015 refractive index unit (RIU). High refractive index resolution is down to 0.45 RU (1 RU = 1 × 10 −6 RIU). Imaging and protein microarray experiments demonstrate the ability of high-throughput detection. The aptamer experiments demonstrate that the SPR sensor based on differential interferometric imaging has a great capability to be implemented for high-throughput aptamer kinetic evaluation. These results suggest that this biosensor has the potential to be utilized in proteomics and drug discovery after further improvement. (paper)

Versatile High Resolution Oligosaccharide Microarrays for Plant Glycobiology and Cell Wall Research

DEFF Research Database (Denmark)

Pedersen, Henriette Lodberg; Fangel, Jonatan Ulrik; McCleary, Barry

2012-01-01

Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less establish...

From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis

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Carsten Denkert

2013-08-01

Full Text Available Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER positive, human epidermal growth factor receptor (HER2 negative (ER+/HER2− breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR to allow for assaying formalin-fixed, paraffin-embedded (FFPE samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257 demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice.

High quality protein microarray using in situ protein purification

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Fleischmann Robert D

2009-08-01

Full Text Available Abstract Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC. This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents

Carbohydrate microarrays

DEFF Research Database (Denmark)

Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola

2012-01-01

In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray...... of substrate specificities of glycosyltransferases. This review covers the construction of carbohydrate microarrays, detection methods of carbohydrate microarrays and their applications in biological and biomedical research....

High-throughput analysis of ammonia oxidiser community composition via a novel, amoA-based functional gene array.

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Guy C J Abell

Full Text Available Advances in microbial ecology research are more often than not limited by the capabilities of available methodologies. Aerobic autotrophic nitrification is one of the most important and well studied microbiological processes in terrestrial and aquatic ecosystems. We have developed and validated a microbial diagnostic microarray based on the ammonia-monooxygenase subunit A (amoA gene, enabling the in-depth analysis of the community structure of bacterial and archaeal ammonia oxidisers. The amoA microarray has been successfully applied to analyse nitrifier diversity in marine, estuarine, soil and wastewater treatment plant environments. The microarray has moderate costs for labour and consumables and enables the analysis of hundreds of environmental DNA or RNA samples per week per person. The array has been thoroughly validated with a range of individual and complex targets (amoA clones and environmental samples, respectively, combined with parallel analysis using traditional sequencing methods. The moderate cost and high throughput of the microarray makes it possible to adequately address broader questions of the ecology of microbial ammonia oxidation requiring high sample numbers and high resolution of the community composition.

MACRO: a combined microchip-PCR and microarray system for high-throughput monitoring of genetically modified organisms.

Science.gov (United States)

Shao, Ning; Jiang, Shi-Meng; Zhang, Miao; Wang, Jing; Guo, Shu-Juan; Li, Yang; Jiang, He-Wei; Liu, Cheng-Xi; Zhang, Da-Bing; Yang, Li-Tao; Tao, Sheng-Ce

2014-01-21

The monitoring of genetically modified organisms (GMOs) is a primary step of GMO regulation. However, there is presently a lack of effective and high-throughput methodologies for specifically and sensitively monitoring most of the commercialized GMOs. Herein, we developed a multiplex amplification on a chip with readout on an oligo microarray (MACRO) system specifically for convenient GMO monitoring. This system is composed of a microchip for multiplex amplification and an oligo microarray for the readout of multiple amplicons, containing a total of 91 targets (18 universal elements, 20 exogenous genes, 45 events, and 8 endogenous reference genes) that covers 97.1% of all GM events that have been commercialized up to 2012. We demonstrate that the specificity of MACRO is ~100%, with a limit of detection (LOD) that is suitable for real-world applications. Moreover, the results obtained of simulated complex samples and blind samples with MACRO were 100% consistent with expectations and the results of independently performed real-time PCRs, respectively. Thus, we believe MACRO is the first system that can be applied for effectively monitoring the majority of the commercialized GMOs in a single test.

Intestinal microbiota in healthy U.S. young children and adults--a high throughput microarray analysis.

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Tamar Ringel-Kulka

Full Text Available It is generally believed that the infant's microbiota is established during the first 1-2 years of life. However, there is scarce data on its characterization and its comparison to the adult-like microbiota in consecutive years.To characterize and compare the intestinal microbiota in healthy young children (1-4 years and healthy adults from the North Carolina region in the U.S. using high-throughput bacterial phylogenetic microarray analysis.Detailed characterization and comparison of the intestinal microbiota of healthy children aged 1-4 years old (n = 28 and healthy adults of 21-60 years (n = 23 was carried out using the Human Intestinal Tract Chip (HITChip phylogenetic microarray targeting the V1 and V6 regions of 16S rRNA and quantitative PCR.The HITChip microarray data indicate that Actinobacteria, Bacilli, Clostridium cluster IV and Bacteroidetes are the predominant phylum-like groups that exhibit differences between young children and adults. The phylum-like group Clostridium cluster XIVa was equally predominant in young children and adults and is thus considered to be established at an early age. The genus-like level show significant 3.6 fold (higher or lower differences in the abundance of 26 genera between young children and adults. Young U.S. children have a significantly 3.5-fold higher abundance of Bifidobacterium species than the adults from the same location. However, the microbiota of young children is less diverse than that of adults.We show that the establishment of an adult-like intestinal microbiota occurs at a later age than previously reported. Characterizing the microbiota and its development in the early years of life may help identify 'windows of opportunity' for interventional strategies that may promote health and prevent or mitigate disease processes.

Versatile High Throughput Microarray Analysis for Marine Glycobiology

DEFF Research Database (Denmark)

Asunción Salmeán, Armando

to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...... in cell development. Another part of this work focused in the development of a novel methodology for the discovery of unknown algal polysaccharides and characterization of carbohydrate binding proteins. Based on the coevolution between alga and marine saprophytic microorganisms, which use the algal...

A bead-based western for high-throughput cellular signal transduction analyses

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Treindl, Fridolin; Ruprecht, Benjamin; Beiter, Yvonne; Schultz, Silke; Döttinger, Anette; Staebler, Annette; Joos, Thomas O.; Kling, Simon; Poetz, Oliver; Fehm, Tanja; Neubauer, Hans; Kuster, Bernhard; Templin, Markus F.

2016-01-01

Dissecting cellular signalling requires the analysis of large number of proteins. The DigiWest approach we describe here transfers the western blot to a bead-based microarray platform. By combining gel-based protein separation with immobilization on microspheres, hundreds of replicas of the initial blot are created, thus enabling the comprehensive analysis of limited material, such as cells collected by laser capture microdissection, and extending traditional western blotting to reach proteomic scales. The combination of molecular weight resolution, sensitivity and signal linearity on an automated platform enables the rapid quantification of hundreds of specific proteins and protein modifications in complex samples. This high-throughput western blot approach allowed us to identify and characterize alterations in cellular signal transduction that occur during the development of resistance to the kinase inhibitor Lapatinib, revealing major changes in the activation state of Ephrin-mediated signalling and a central role for p53-controlled processes. PMID:27659302

A microarray-based genotyping and genetic mapping approach for highly heterozygous outcrossing species enables localization of a large fraction of the unassembled Populus trichocarpa genome sequence.

Science.gov (United States)

Drost, Derek R; Novaes, Evandro; Boaventura-Novaes, Carolina; Benedict, Catherine I; Brown, Ryan S; Yin, Tongming; Tuskan, Gerald A; Kirst, Matias

2009-06-01

Microarrays have demonstrated significant power for genome-wide analyses of gene expression, and recently have also revolutionized the genetic analysis of segregating populations by genotyping thousands of loci in a single assay. Although microarray-based genotyping approaches have been successfully applied in yeast and several inbred plant species, their power has not been proven in an outcrossing species with extensive genetic diversity. Here we have developed methods for high-throughput microarray-based genotyping in such species using a pseudo-backcross progeny of 154 individuals of Populus trichocarpa and P. deltoides analyzed with long-oligonucleotide in situ-synthesized microarray probes. Our analysis resulted in high-confidence genotypes for 719 single-feature polymorphism (SFP) and 1014 gene expression marker (GEM) candidates. Using these genotypes and an established microsatellite (SSR) framework map, we produced a high-density genetic map comprising over 600 SFPs, GEMs and SSRs. The abundance of gene-based markers allowed us to localize over 35 million base pairs of previously unplaced whole-genome shotgun (WGS) scaffold sequence to putative locations in the genome of P. trichocarpa. A high proportion of sampled scaffolds could be verified for their placement with independently mapped SSRs, demonstrating the previously un-utilized power that high-density genotyping can provide in the context of map-based WGS sequence reassembly. Our results provide a substantial contribution to the continued improvement of the Populus genome assembly, while demonstrating the feasibility of microarray-based genotyping in a highly heterozygous population. The strategies presented are applicable to genetic mapping efforts in all plant species with similarly high levels of genetic diversity.

Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants

DEFF Research Database (Denmark)

J. Carmona, Santiago; Nielsen, Morten; Schafer-Nielsen, Claus

2015-01-01

, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than...

High-Throughput Cloning and Expression Library Creation for Functional Proteomics

Science.gov (United States)

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

2013-01-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particular important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single gene experiments, creating the need for fast, flexible and reliable cloning systems. These collections of open reading frame (ORF) clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator™ DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP12). Details can be found at http://www.proteomicstutorials.org. PMID:23457047

Manual evaluation of tissue microarrays in a high-throughput research project: The contribution of Indian surgical pathology to the Human Protein Atlas (HPA) project.

Science.gov (United States)

Navani, Sanjay

2016-04-01

The Human Protein Atlas (HPA) program (www.proteinatlas.org) is an international program that has been set up to allow for a systematic exploration of the human proteome using antibody-based proteomics. This is accomplished by combining high-throughput generation of affinity-purified (mono-specific) antibodies with protein profiling in a multitude of tissues/cell types assembled in tissue microarrays. Twenty-six surgical pathologists over a seven-and-half year period have annotated and curated approximately sixteen million tissue images derived from immunostaining of normal and cancer tissues by approximately 23 000 antibodies. Web-based annotation software that allows for a basic and rapid evaluation of immunoreactivity in tissues has been utilized. Intensity, fraction of immunoreactive cells and subcellular localization were recorded for each given cell population. A text comment summarizing the characteristics for each antibody was added. The methods used and the challenges encountered for this exercise, the largest effort ever by a single group of surgical pathologists, are discussed. Manual annotation of digital images is an important tool that may be successfully utilized in high-throughput research projects. This is the first time an Indian private pathology laboratory has been associated with cutting-edge research internationally providing a classic example of developed and emerging nation collaboration. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-throughput GPU-based LDPC decoding

Science.gov (United States)

Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

2010-08-01

Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

Association Study between BDNF Gene Polymorphisms and Autism by Three-Dimensional Gel-Based Microarray

Directory of Open Access Journals (Sweden)

Zuhong Lu

2009-06-01

Full Text Available Single nucleotide polymorphisms (SNPs are important markers which can be used in association studies searching for susceptible genes of complex diseases. High-throughput methods are needed for SNP genotyping in a large number of samples. In this study, we applied polyacrylamide gel-based microarray combined with dual-color hybridization for association study of four BDNF polymorphisms with autism. All the SNPs in both patients and controls could be analyzed quickly and correctly. Among four SNPs, only C270T polymorphism showed significant differences in the frequency of the allele (χ2 = 7.809, p = 0.005 and genotype (χ2 = 7.800, p = 0.020. In the haplotype association analysis, there was significant difference in global haplotype distribution between the groups (χ2 = 28.19，p = 3.44e-005. We suggest that BDNF has a possible role in the pathogenesis of autism. The study also show that the polyacrylamide gel-based microarray combined with dual-color hybridization is a rapid, simple and high-throughput method for SNPs genotyping, and can be used for association study of susceptible gene with disorders in large samples.

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

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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.

Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

Science.gov (United States)

Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

2017-09-01

High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

Hybridization chain reaction amplification for highly sensitive fluorescence detection of DNA with dextran coated microarrays.

Science.gov (United States)

Chao, Jie; Li, Zhenhua; Li, Jing; Peng, Hongzhen; Su, Shao; Li, Qian; Zhu, Changfeng; Zuo, Xiaolei; Song, Shiping; Wang, Lianhui; Wang, Lihua

2016-07-15

Microarrays of biomolecules hold great promise in the fields of genomics, proteomics, and clinical assays on account of their remarkably parallel and high-throughput assay capability. However, the fluorescence detection used in most conventional DNA microarrays is still limited by sensitivity. In this study, we have demonstrated a novel universal and highly sensitive platform for fluorescent detection of sequence specific DNA at the femtomolar level by combining dextran-coated microarrays with hybridization chain reaction (HCR) signal amplification. Three-dimensional dextran matrix was covalently coated on glass surface as the scaffold to immobilize DNA recognition probes to increase the surface binding capacity and accessibility. DNA nanowire tentacles were formed on the matrix surface for efficient signal amplification by capturing multiple fluorescent molecules in a highly ordered way. By quantifying microscopic fluorescent signals, the synergetic effects of dextran and HCR greatly improved sensitivity of DNA microarrays, with a detection limit of 10fM (1×10(5) molecules). This detection assay could recognize one-base mismatch with fluorescence signals dropped down to ~20%. This cost-effective microarray platform also worked well with samples in serum and thus shows great potential for clinical diagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Parallel scan hyperspectral fluorescence imaging system and biomedical application for microarrays

International Nuclear Information System (INIS)

Liu Zhiyi; Ma Suihua; Liu Le; Guo Jihua; He Yonghong; Ji Yanhong

2011-01-01

Microarray research offers great potential for analysis of gene expression profile and leads to greatly improved experimental throughput. A number of instruments have been reported for microarray detection, such as chemiluminescence, surface plasmon resonance, and fluorescence markers. Fluorescence imaging is popular for the readout of microarrays. In this paper we develop a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. Coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. The mechanism of quasi-confocal imaging provides a high signal-to-noise ratio, and parallel scan makes this approach a high throughput technique for microarray analysis. This system is improved with a specifically designed spectrometer which can offer a spectral resolution of 0.2 nm, and operates with spatial resolutions ranging from 2 to 30 μm . Finally, the application of the system is demonstrated by reading out microarrays for identification of bacteria.

High-Throughput Analysis of Enzyme Activities

Energy Technology Data Exchange (ETDEWEB)

Lu, Guoxin [Iowa State Univ., Ames, IA (United States)

2007-01-01

High-throughput screening (HTS) techniques have been applied to many research fields nowadays. Robot microarray printing technique and automation microtiter handling technique allows HTS performing in both heterogeneous and homogeneous formats, with minimal sample required for each assay element. In this dissertation, new HTS techniques for enzyme activity analysis were developed. First, patterns of immobilized enzyme on nylon screen were detected by multiplexed capillary system. The imaging resolution is limited by the outer diameter of the capillaries. In order to get finer images, capillaries with smaller outer diameters can be used to form the imaging probe. Application of capillary electrophoresis allows separation of the product from the substrate in the reaction mixture, so that the product doesn't have to have different optical properties with the substrate. UV absorption detection allows almost universal detection for organic molecules. Thus, no modifications of either the substrate or the product molecules are necessary. This technique has the potential to be used in screening of local distribution variations of specific bio-molecules in a tissue or in screening of multiple immobilized catalysts. Another high-throughput screening technique is developed by directly monitoring the light intensity of the immobilized-catalyst surface using a scientific charge-coupled device (CCD). Briefly, the surface of enzyme microarray is focused onto a scientific CCD using an objective lens. By carefully choosing the detection wavelength, generation of product on an enzyme spot can be seen by the CCD. Analyzing the light intensity change over time on an enzyme spot can give information of reaction rate. The same microarray can be used for many times. Thus, high-throughput kinetic studies of hundreds of catalytic reactions are made possible. At last, we studied the fluorescence emission spectra of ADP and obtained the detection limits for ADP under three different

Towards a high throughput droplet-based agglutination assay

KAUST Repository

Kodzius, Rimantas; Castro, David; Foulds, Ian G.

2013-01-01

This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

Towards a high throughput droplet-based agglutination assay

KAUST Repository

Kodzius, Rimantas

2013-10-22

This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

DEFF Research Database (Denmark)

Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo

2017-01-01

-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification...

High Throughput, Label-free Screening Small Molecule Compound Libraries for Protein-Ligands using Combination of Small Molecule Microarrays and a Special Ellipsometry-based Optical Scanner.

Science.gov (United States)

Landry, James P; Fei, Yiyan; Zhu, X D

2011-12-01

Small-molecule compounds remain the major source of therapeutic and preventative drugs. Developing new drugs against a protein target often requires screening large collections of compounds with diverse structures for ligands or ligand fragments that exhibit sufficiently affinity and desirable inhibition effect on the target before further optimization and development. Since the number of small molecule compounds is large, high-throughput screening (HTS) methods are needed. Small-molecule microarrays (SMM) on a solid support in combination with a suitable binding assay form a viable HTS platform. We demonstrate that by combining an oblique-incidence reflectivity difference optical scanner with SMM we can screen 10,000 small-molecule compounds on a single glass slide for protein ligands without fluorescence labeling. Furthermore using such a label-free assay platform we can simultaneously acquire binding curves of a solution-phase protein to over 10,000 immobilized compounds, thus enabling full characterization of protein-ligand interactions over a wide range of affinity constants.

Ontology-based meta-analysis of global collections of high-throughput public data.

Directory of Open Access Journals (Sweden)

Ilya Kupershmidt

2010-09-01

Full Text Available The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today.We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets.Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

Ontology-based meta-analysis of global collections of high-throughput public data.

Science.gov (United States)

Kupershmidt, Ilya; Su, Qiaojuan Jane; Grewal, Anoop; Sundaresh, Suman; Halperin, Inbal; Flynn, James; Shekar, Mamatha; Wang, Helen; Park, Jenny; Cui, Wenwu; Wall, Gregory D; Wisotzkey, Robert; Alag, Satnam; Akhtari, Saeid; Ronaghi, Mostafa

2010-09-29

The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

High-Throughput Tools for Characterization of Antibody Epitopes

DEFF Research Database (Denmark)

Christiansen, Anders

mapping. In Chapter 1, it was examined whether combining phage display, a traditional epitope mapping approach, with HTS would improve the method. The developed approach was successfully used to map Ara h 1 epitopes in sera from patients with peanut allergy. Notably, the sera represented difficult...... proliferation advantages. Finally, in Chapter 4, a different emerging technology, next-generation peptide microarrays, was applied for epitope mapping of major peanut allergens using sera from allergic patients. New developments in the peptide microarray have enabled a greatly increased throughput....... In this study, these improvements were utilized to characterize epitopes at high resolution, i.e. determine the importance of each residue for antibody binding, for all major peanut allergens. Epitope reactivity among patients often converged on known epitope hotspots, however the binding patterns were somewhat...

Ultraspecific probes for high throughput HLA typing

Directory of Open Access Journals (Sweden)

Eggers Rick

2009-02-01

Full Text Available Abstract Background The variations within an individual's HLA (Human Leukocyte Antigen genes have been linked to many immunological events, e.g. susceptibility to disease, response to vaccines, and the success of blood, tissue, and organ transplants. Although the microarray format has the potential to achieve high-resolution typing, this has yet to be attained due to inefficiencies of current probe design strategies. Results We present a novel three-step approach for the design of high-throughput microarray assays for HLA typing. This approach first selects sequences containing the SNPs present in all alleles of the locus of interest and next calculates the number of base changes necessary to convert a candidate probe sequences to the closest subsequence within the set of sequences that are likely to be present in the sample including the remainder of the human genome in order to identify those candidate probes which are "ultraspecific" for the allele of interest. Due to the high specificity of these sequences, it is possible that preliminary steps such as PCR amplification are no longer necessary. Lastly, the minimum number of these ultraspecific probes is selected such that the highest resolution typing can be achieved for the minimal cost of production. As an example, an array was designed and in silico results were obtained for typing of the HLA-B locus. Conclusion The assay presented here provides a higher resolution than has previously been developed and includes more alleles than previously considered. Based upon the in silico and preliminary experimental results, we believe that the proposed approach can be readily applied to any highly polymorphic gene system.

Annotating breast cancer microarray samples using ontologies

Science.gov (United States)

Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

2008-01-01

As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

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

Science.gov (United States)

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

2018-01-01

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

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

Directory of Open Access Journals (Sweden)

Beaudoing Emmanuel

2006-09-01

Full Text Available Abstract Background High throughput gene expression profiling (GEP is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking, data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for

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

Directory of Open Access Journals (Sweden)

Russell Kate

2008-08-01

Full Text Available Abstract Background The differentiation of naive T and B cells into memory lymphocytes is essential for immunity to pathogens. Therapeutic manipulation of this cellular differentiation program could improve vaccine efficacy and the in vitro expansion of memory cells. However, chemical screens to identify compounds that induce memory differentiation have been limited by 1 the lack of reporter-gene or functional assays that can distinguish naive and memory-phenotype T cells at high throughput and 2 a suitable cell-line representative of naive T cells. Results Here, we describe a method for gene-expression based screening that allows primary naive and memory-phenotype lymphocytes to be discriminated based on complex genes signatures corresponding to these differentiation states. We used ligation-mediated amplification and a fluorescent, bead-based detection system to quantify simultaneously 55 transcripts representing naive and memory-phenotype signatures in purified populations of human T cells. The use of a multi-gene panel allowed better resolution than any constituent single gene. The method was precise, correlated well with Affymetrix microarray data, and could be easily scaled up for high-throughput. Conclusion This method provides a generic solution for high-throughput differentiation screens in primary human T cells where no single-gene or functional assay is available. This screening platform will allow the identification of small molecules, genes or soluble factors that direct memory differentiation in naive human lymphocytes.

Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA

Directory of Open Access Journals (Sweden)

Chan Alan

2006-06-01

Full Text Available Abstract Background Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. Results In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A. Conclusion Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

Microarray MAPH: accurate array-based detection of relative copy number in genomic DNA.

Science.gov (United States)

Gibbons, Brian; Datta, Parikkhit; Wu, Ying; Chan, Alan; Al Armour, John

2006-06-30

Current methods for measurement of copy number do not combine all the desirable qualities of convenience, throughput, economy, accuracy and resolution. In this study, to improve the throughput associated with Multiplex Amplifiable Probe Hybridisation (MAPH) we aimed to develop a modification based on the 3-Dimensional, Flow-Through Microarray Platform from PamGene International. In this new method, electrophoretic analysis of amplified products is replaced with photometric analysis of a probed oligonucleotide array. Copy number analysis of hybridised probes is based on a dual-label approach by comparing the intensity of Cy3-labelled MAPH probes amplified from test samples co-hybridised with similarly amplified Cy5-labelled reference MAPH probes. The key feature of using a hybridisation-based end point with MAPH is that discrimination of amplified probes is based on sequence and not fragment length. In this study we showed that microarray MAPH measurement of PMP22 gene dosage correlates well with PMP22 gene dosage determined by capillary MAPH and that copy number was accurately reported in analyses of DNA from 38 individuals, 12 of which were known to have Charcot-Marie-Tooth disease type 1A (CMT1A). Measurement of microarray-based endpoints for MAPH appears to be of comparable accuracy to electrophoretic methods, and holds the prospect of fully exploiting the potential multiplicity of MAPH. The technology has the potential to simplify copy number assays for genes with a large number of exons, or of expanded sets of probes from dispersed genomic locations.

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

Science.gov (United States)

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

2009-10-01

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

High-throughput sequencing enhanced phage display enables the identification of patient-specific epitope motifs in serum

DEFF Research Database (Denmark)

Christiansen, Anders; Kringelum, Jens Vindahl; Hansen, Christian Skjødt

2015-01-01

of the bioinformatic approach was demonstrated by identifying epitopes of a prominent peanut allergen, Ara h 1, in sera from patients with severe peanut allergy. The identified epitopes were confirmed by high-density peptide micro-arrays. The present study demonstrates that high-throughput sequencing can empower phage...

Pathway Processor 2.0: a web resource for pathway-based analysis of high-throughput data.

Science.gov (United States)

Beltrame, Luca; Bianco, Luca; Fontana, Paolo; Cavalieri, Duccio

2013-07-15

Pathway Processor 2.0 is a web application designed to analyze high-throughput datasets, including but not limited to microarray and next-generation sequencing, using a pathway centric logic. In addition to well-established methods such as the Fisher's test and impact analysis, Pathway Processor 2.0 offers innovative methods that convert gene expression into pathway expression, leading to the identification of differentially regulated pathways in a dataset of choice. Pathway Processor 2.0 is available as a web service at http://compbiotoolbox.fmach.it/pathwayProcessor/. Sample datasets to test the functionality can be used directly from the application. duccio.cavalieri@fmach.it Supplementary data are available at Bioinformatics online.

Reverse phase protein microarray technology in traumatic brain injury.

Science.gov (United States)

Gyorgy, Andrea B; Walker, John; Wingo, Dan; Eidelman, Ofer; Pollard, Harvey B; Molnar, Andras; Agoston, Denes V

2010-09-30

Antibody based, high throughput proteomics technology represents an exciting new approach in understanding the pathobiologies of complex disorders such as cancer, stroke and traumatic brain injury. Reverse phase protein microarray (RPPA) can complement the classical methods based on mass spectrometry as a high throughput validation and quantification method. RPPA technology can address problematic issues, such as sample complexity, sensitivity, quantification, reproducibility and throughput, which are currently associated with mass spectrometry-based approaches. However, there are technical challenges, predominantly associated with the selection and use of antibodies, preparation and representation of samples and with analyzing and quantifying primary RPPA data. Here we present ways to identify and overcome some of the current issues associated with RPPA. We believe that using stringent quality controls, improved bioinformatics analysis and interpretation of primary RPPA data, this method will significantly contribute in generating new level of understanding about complex disorders at the level of systems biology. Published by Elsevier B.V.

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

Science.gov (United States)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

Nanotechnology: moving from microarrays toward nanoarrays.

Science.gov (United States)

Chen, Hua; Li, Jun

2007-01-01

Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.

Microarrays for Universal Detection and Identification of Phytoplasmas

DEFF Research Database (Denmark)

Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

2013-01-01

Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...... and differentiate all types of phytoplasmas in one assay. The present protocol describes a microarray-based method for identification of phytoplasmas to 16Sr group level....

MARS: Microarray analysis, retrieval, and storage system

Directory of Open Access Journals (Sweden)

Scheideler Marcel

2005-04-01

Full Text Available Abstract Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS, a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.

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

Science.gov (United States)

Podolska, Katerina; Sedlak, David; Bartunek, Petr; Svoboda, Petr

2014-03-01

Production of small RNAs by ribonuclease III Dicer is a key step in microRNA and RNA interference pathways, which employ Dicer-produced small RNAs as sequence-specific silencing guides. Further studies and manipulations of microRNA and RNA interference pathways would benefit from identification of small-molecule modulators. Here, we report a study of a fluorescence-based in vitro Dicer cleavage assay, which was adapted for high-throughput screening. The kinetic assay can be performed under single-turnover conditions (35 nM substrate and 70 nM Dicer) in a small volume (5 µL), which makes it suitable for high-throughput screening in a 1536-well format. As a proof of principle, a small library of bioactive compounds was analyzed, demonstrating potential of the assay.

Novel Protein Microarray Technology to Examine Men with Prostate Cancer

National Research Council Canada - National Science Library

Lilja, Hans

2005-01-01

The authors developed a novel macro and nanoporous silicon surface for protein microarrays to facilitate high-throughput biomarker discovery, and high-density protein-chip array analyses of complex biological samples...

DNA Microarrays in Comparative Genomics and Transcriptomics

DEFF Research Database (Denmark)

Willenbrock, Hanni

2007-01-01

at identifying the exact breakpoints where DNA has been gained or lost. In this thesis, three popular methods are compared and a realistic simulation model is presented for generating artificial data with known breakpoints and known DNA copy number. By using simulated data, we obtain a realistic evaluation......During the past few years, innovations in the DNA sequencing technology has led to an explosion in available DNA sequence information. This has revolutionized biological research and promoted the development of high throughput analysis methods that can take advantage of the vast amount of sequence...... data. For this, the DNA microarray technology has gained enormous popularity due to its ability to measure the presence or the activity of thousands of genes simultaneously. Microarrays for high throughput data analyses are not limited to a few organisms but may be applied to everything from bacteria...

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

Directory of Open Access Journals (Sweden)

Aditi Sengupta

2016-03-01

Full Text Available Amplicon-based sequencing strategies that include 16S rRNA and functional genes, alongside “meta-omics” analyses of communities of microorganisms, have allowed researchers to pose questions and find answers to “who” is present in the environment and “what” they are doing. Next-generation sequencing approaches that aid microbial ecology studies of agricultural systems are fast gaining popularity among agronomy, crop, soil, and environmental science researchers. Given the rapid development of these high-throughput sequencing techniques, researchers with no prior experience will desire information about the best practices that can be used before actually starting high-throughput amplicon-based sequence analyses. We have outlined items that need to be carefully considered in experimental design, sampling, basic bioinformatics, sequencing of mock communities and negative controls, acquisition of metadata, and in standardization of reaction conditions as per experimental requirements. Not all considerations mentioned here may pertain to a particular study. The overall goal is to inform researchers about considerations that must be taken into account when conducting high-throughput microbial DNA sequencing and sequences analysis.

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

Science.gov (United States)

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

2016-06-01

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

Microarray-based whole-genome hybridization as a tool for determining procaryotic species relatedness

Energy Technology Data Exchange (ETDEWEB)

Wu, L.; Liu, X.; Fields, M.W.; Thompson, D.K.; Bagwell, C.E.; Tiedje, J. M.; Hazen, T.C.; Zhou, J.

2008-01-15

The definition and delineation of microbial species are of great importance and challenge due to the extent of evolution and diversity. Whole-genome DNA-DNA hybridization is the cornerstone for defining procaryotic species relatedness, but obtaining pairwise DNA-DNA reassociation values for a comprehensive phylogenetic analysis of procaryotes is tedious and time consuming. A previously described microarray format containing whole-genomic DNA (the community genome array or CGA) was rigorously evaluated as a high-throughput alternative to the traditional DNA-DNA reassociation approach for delineating procaryotic species relationships. DNA similarities for multiple bacterial strains obtained with the CGA-based hybridization were comparable to those obtained with various traditional whole-genome hybridization methods (r=0.87, P<0.01). Significant linear relationships were also observed between the CGA-based genome similarities and those derived from small subunit (SSU) rRNA gene sequences (r=0.79, P<0.0001), gyrB sequences (r=0.95, P<0.0001) or REP- and BOX-PCR fingerprinting profiles (r=0.82, P<0.0001). The CGA hybridization-revealed species relationships in several representative genera, including Pseudomonas, Azoarcus and Shewanella, were largely congruent with previous classifications based on various conventional whole-genome DNA-DNA reassociation, SSU rRNA and/or gyrB analyses. These results suggest that CGA-based DNA-DNA hybridization could serve as a powerful, high-throughput format for determining species relatedness among microorganisms.

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

Science.gov (United States)

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

High-throughput immunophenotyping of 43 ferret lymphomas using tissue microarray technology

DEFF Research Database (Denmark)

Hammer, Anne Sofie; Williams, B.; Dietz, H.H.

2007-01-01

To validate the use of the tissue microarray (TMA) method for immunophenotyping of ferret lymphomas, a TMA was constructed containing duplicate 1-mm cores sampled from 112 paraffin-embedded lymphoma tissue specimens obtained from 43 ferret lymphoma cases. Immunohistochemical (IHC) expression of CD3......, CD79 alpha, and Ki-67 (MIB-1) was determined by TMA and whole mount (WM) staining of each individual case for result comparison. There was a high correlation between CD79 alpha and CD3 results comparing ferret TMA and WM sections (kappa statistic 0.71-0.73 for single-core TMA and 0.......79-0.95 for duplicate-core TMA) and between continuous data from Ki-67 staining of ferret TMA sections and WM sections (concordance correlation coefficients 0.77 for single cores and 0.87 for duplicate cores). Subsequently, a panel of commercially available antibodies was applied to the TMA for the analysis...

Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies

Directory of Open Access Journals (Sweden)

Fedele Vita

2006-06-01

Full Text Available Abstract Background Recent studies indicate that microRNAs (miRNAs are mechanistically involved in the development of various human malignancies, suggesting that they represent a promising new class of cancer biomarkers. However, previously reported methods for measuring miRNA expression consume large amounts of tissue, prohibiting high-throughput miRNA profiling from typically small clinical samples such as excision or core needle biopsies of breast or prostate cancer. Here we describe a novel combination of linear amplification and labeling of miRNA for highly sensitive expression microarray profiling requiring only picogram quantities of purified microRNA. Results Comparison of microarray and qRT-PCR measured miRNA levels from two different prostate cancer cell lines showed concordance between the two platforms (Pearson correlation R2 = 0.81; and extension of the amplification, labeling and microarray platform was successfully demonstrated using clinical core and excision biopsy samples from breast and prostate cancer patients. Unsupervised clustering analysis of the prostate biopsy microarrays separated advanced and metastatic prostate cancers from pooled normal prostatic samples and from a non-malignant precursor lesion. Unsupervised clustering of the breast cancer microarrays significantly distinguished ErbB2-positive/ER-negative, ErbB2-positive/ER-positive, and ErbB2-negative/ER-positive breast cancer phenotypes (Fisher exact test, p = 0.03; as well, supervised analysis of these microarray profiles identified distinct miRNA subsets distinguishing ErbB2-positive from ErbB2-negative and ER-positive from ER-negative breast cancers, independent of other clinically important parameters (patient age; tumor size, node status and proliferation index. Conclusion In sum, these findings demonstrate that optimized high-throughput microRNA expression profiling offers novel biomarker identification from typically small clinical samples such as breast

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

2009-01-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing

Human Leukocyte Antigen Typing Using a Knowledge Base Coupled with a High-Throughput Oligonucleotide Probe Array Analysis

Science.gov (United States)

Zhang, Guang Lan; Keskin, Derin B.; Lin, Hsin-Nan; Lin, Hong Huang; DeLuca, David S.; Leppanen, Scott; Milford, Edgar L.; Reinherz, Ellis L.; Brusic, Vladimir

2014-01-01

Human leukocyte antigens (HLA) are important biomarkers because multiple diseases, drug toxicity, and vaccine responses reveal strong HLA associations. Current clinical HLA typing is an elimination process requiring serial testing. We present an alternative in situ synthesized DNA-based microarray method that contains hundreds of thousands of probes representing a complete overlapping set covering 1,610 clinically relevant HLA class I alleles accompanied by computational tools for assigning HLA type to 4-digit resolution. Our proof-of-concept experiment included 21 blood samples, 18 cell lines, and multiple controls. The method is accurate, robust, and amenable to automation. Typing errors were restricted to homozygous samples or those with very closely related alleles from the same locus, but readily resolved by targeted DNA sequencing validation of flagged samples. High-throughput HLA typing technologies that are effective, yet inexpensive, can be used to analyze the world’s populations, benefiting both global public health and personalized health care. PMID:25505899

HIGH THROUGHPUT SCREENING METHOD AND APPARATUS FOR ANALYSING INTERACTIONS BETWEEN SURFACES WITH DIFFERENT TOPOGRAPHY AND THE ENVIRONMENT

NARCIS (Netherlands)

de Boer, Jan; van Blitterswijk, Clemens; Unadkat, H.V.; Stamatialis, Dimitrios; Papenburg, B.J.; Wessling, Matthias

2009-01-01

The invention is directed to a high throughput screening method for analysing and interaction between a surface of a material and an environment. The screening method of the invention comprises: providing a micro-array comprising said material and having a multitude of units at least part of which

Micropatterned comet assay enables high throughput and sensitive DNA damage quantification.

Science.gov (United States)

Ge, Jing; Chow, Danielle N; Fessler, Jessica L; Weingeist, David M; Wood, David K; Engelward, Bevin P

2015-01-01

The single cell gel electrophoresis assay, also known as the comet assay, is a versatile method for measuring many classes of DNA damage, including base damage, abasic sites, single strand breaks and double strand breaks. However, limited throughput and difficulties with reproducibility have limited its utility, particularly for clinical and epidemiological studies. To address these limitations, we created a microarray comet assay. The use of a micrometer scale array of cells increases the number of analysable comets per square centimetre and enables automated imaging and analysis. In addition, the platform is compatible with standard 24- and 96-well plate formats. Here, we have assessed the consistency and sensitivity of the microarray comet assay. We showed that the linear detection range for H2O2-induced DNA damage in human lymphoblastoid cells is between 30 and 100 μM, and that within this range, inter-sample coefficient of variance was between 5 and 10%. Importantly, only 20 comets were required to detect a statistically significant induction of DNA damage for doses within the linear range. We also evaluated sample-to-sample and experiment-to-experiment variation and found that for both conditions, the coefficient of variation was lower than what has been reported for the traditional comet assay. Finally, we also show that the assay can be performed using a 4× objective (rather than the standard 10× objective for the traditional assay). This adjustment combined with the microarray format makes it possible to capture more than 50 analysable comets in a single image, which can then be automatically analysed using in-house software. Overall, throughput is increased more than 100-fold compared to the traditional assay. Together, the results presented here demonstrate key advances in comet assay technology that improve the throughput, sensitivity, and robustness, thus enabling larger scale clinical and epidemiological studies. © The Author 2014. Published by

Microarray-based ultra-high resolution discovery of genomic deletion mutations

Science.gov (United States)

2014-01-01

Background Oligonucleotide microarray-based comparative genomic hybridization (CGH) offers an attractive possible route for the rapid and cost-effective genome-wide discovery of deletion mutations. CGH typically involves comparison of the hybridization intensities of genomic DNA samples with microarray chip representations of entire genomes, and has widespread potential application in experimental research and medical diagnostics. However, the power to detect small deletions is low. Results Here we use a graduated series of Arabidopsis thaliana genomic deletion mutations (of sizes ranging from 4 bp to ~5 kb) to optimize CGH-based genomic deletion detection. We show that the power to detect smaller deletions (4, 28 and 104 bp) depends upon oligonucleotide density (essentially the number of genome-representative oligonucleotides on the microarray chip), and determine the oligonucleotide spacings necessary to guarantee detection of deletions of specified size. Conclusions Our findings will enhance a wide range of research and clinical applications, and in particular will aid in the discovery of genomic deletions in the absence of a priori knowledge of their existence. PMID:24655320

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

Energy Technology Data Exchange (ETDEWEB)

Van Nostrand, Joy D.; Liang, Yuting; He, Zhili; Li, Guanghe; Zhou, Jizhong

2009-01-30

GeoChip is a comprehensive functional gene array that targets key functional genes involved in the geochemical cycling of N, C, and P, sulfate reduction, metal resistance and reduction, and contaminant degradation. Studies have shown the GeoChip to be a sensitive, specific, and high-throughput tool for microbial community analysis that has the power to link geochemical processes with microbial community structure. However, several challenges remain regarding the development and applications of microarrays for microbial community analysis.

Microarrays for the evaluation of cell-biomaterial surface interactions

Science.gov (United States)

Thissen, H.; Johnson, G.; McFarland, G.; Verbiest, B. C. H.; Gengenbach, T.; Voelcker, N. H.

2007-01-01

The evaluation of cell-material surface interactions is important for the design of novel biomaterials which are used in a variety of biomedical applications. While traditional in vitro test methods have routinely used samples of relatively large size, microarrays representing different biomaterials offer many advantages, including high throughput and reduced sample handling. Here, we describe the simultaneous cell-based testing of matrices of polymeric biomaterials, arrayed on glass slides with a low cell-attachment background coating. Arrays were constructed using a microarray robot at 6 fold redundancy with solid pins having a diameter of 375 μm. Printed solutions contained at least one monomer, an initiator and a bifunctional crosslinker. After subsequent UV polymerisation, the arrays were washed and characterised by X-ray photoelectron spectroscopy. Cell culture experiments were carried out over 24 hours using HeLa cells. After labelling with CellTracker ® Green for the final hour of incubation and subsequent fixation, the arrays were scanned. In addition, individual spots were also viewed by fluorescence microscopy. The evaluation of cell-surface interactions in high-throughput assays as demonstrated here is a key enabling technology for the effective development of future biomaterials.

High-throughput Sequencing Based Immune Repertoire Study during Infectious Disease

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Dongni Hou

2016-08-01

Full Text Available The selectivity of the adaptive immune response is based on the enormous diversity of T and B cell antigen-specific receptors. The immune repertoire, the collection of T and B cells with functional diversity in the circulatory system at any given time, is dynamic and reflects the essence of immune selectivity. In this article, we review the recent advances in immune repertoire study of infectious diseases that achieved by traditional techniques and high-throughput sequencing techniques. High-throughput sequencing techniques enable the determination of complementary regions of lymphocyte receptors with unprecedented efficiency and scale. This progress in methodology enhances the understanding of immunologic changes during pathogen challenge, and also provides a basis for further development of novel diagnostic markers, immunotherapies and vaccines.

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

OpenAIRE

Neto, Ana I.; Custódio, Catarina A.; Wenlong Song; Mano, J. F.

2011-01-01

We propose a new low cost platform for high-throughput analysis that permits screening the biological performance of independent combinations of biomaterials, cells and culture media. Patterned superhydrophobic flat substrates with controlled wettable spots are used to produce microarray chips for accelerated multiplexing evaluation. This work was partially supported by Fundação para a Ciência e Tecnologia (FCT) under project PTDC/FIS/68517/2006.

A multilayer microdevice for cell-based high-throughput drug screening

International Nuclear Information System (INIS)

Liu, Chong; Wang, Lei; Li, Jingmin; Ding, Xiping; Chunyu, Li; Xu, Zheng; Wang, Qi

2012-01-01

A multilayer polydimethylsiloxane microdevice for cell-based high-throughput drug screening is described in this paper. This established microdevice was based on a modularization method and it integrated a drug/medium concentration gradient generator (CGG), pneumatic microvalves and a cell culture microchamber array. The CGG was able to generate five steps of linear concentrations with the same outlet flow rate. The medium/drug flowed through CGG and then into the pear-shaped cell culture microchambers vertically. This vertical perfusion mode was used to reduce the impact of the shear stress on the physiology of cells induced by the fluid flow in the microchambers. Pear-shaped microchambers with two arrays of miropillars at each outlet were adopted in this microdevice, which were beneficial to cell distribution. The chemotherapeutics Cisplatin (DDP)-induced Cisplatin-resistant cell line A549/DDP apoptotic experiments were performed well on this platform. The results showed that this novel microdevice could not only provide well-defined and stable conditions for cell culture, but was also useful for cell-based high-throughput drug screening with less reagents and time consumption. (paper)

High-throughput characterization methods for lithium batteries

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Yingchun Lyu

2017-09-01

Full Text Available The development of high-performance lithium ion batteries requires the discovery of new materials and the optimization of key components. By contrast with traditional one-by-one method, high-throughput method can synthesize and characterize a large number of compositionally varying samples, which is able to accelerate the pace of discovery, development and optimization process of materials. Because of rapid progress in thin film and automatic control technologies, thousands of compounds with different compositions could be synthesized rapidly right now, even in a single experiment. However, the lack of rapid or combinatorial characterization technologies to match with high-throughput synthesis methods, limit the application of high-throughput technology. Here, we review a series of representative high-throughput characterization methods used in lithium batteries, including high-throughput structural and electrochemical characterization methods and rapid measuring technologies based on synchrotron light sources.

Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

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Akshata Datar

2015-10-01

Full Text Available Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS, thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI. In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures.

High-throughput full-automatic synchrotron-based tomographic microscopy

International Nuclear Information System (INIS)

Mader, Kevin; Marone, Federica; Hintermueller, Christoph; Mikuljan, Gordan; Isenegger, Andreas; Stampanoni, Marco

2011-01-01

At the TOMCAT (TOmographic Microscopy and Coherent rAdiology experimenTs) beamline of the Swiss Light Source with an energy range of 8-45 keV and voxel size from 0.37 (micro)m to 7.4 (micro)m, full tomographic datasets are typically acquired in 5 to 10 min. To exploit the speed of the system and enable high-throughput studies to be performed in a fully automatic manner, a package of automation tools has been developed. The samples are automatically exchanged, aligned, moved to the correct region of interest, and scanned. This task is accomplished through the coordination of Python scripts, a robot-based sample-exchange system, sample positioning motors and a CCD camera. The tools are suited for any samples that can be mounted on a standard SEM stub, and require no specific environmental conditions. Up to 60 samples can be analyzed at a time without user intervention. The throughput of the system is dependent on resolution, energy and sample size, but rates of four samples per hour have been achieved with 0.74 (micro)m voxel size at 17.5 keV. The maximum intervention-free scanning time is theoretically unlimited, and in practice experiments have been running unattended as long as 53 h (the average beam time allocation at TOMCAT is 48 h per user). The system is the first fully automated high-throughput tomography station: mounting samples, finding regions of interest, scanning and reconstructing can be performed without user intervention. The system also includes many features which accelerate and simplify the process of tomographic microscopy.

Cross-recognition of a pit viper (Crotalinae) polyspecific antivenom explored through high-density peptide microarray epitope mapping

DEFF Research Database (Denmark)

Engmark, Mikael; Lomonte, Bruno; Gutiérrez, José María

2017-01-01

Snakebite antivenom is a 120 years old invention based on polyclonal mixtures of antibodies purified from the blood of hyper-immunized animals. Knowledge on antibody recognition sites (epitopes) on snake venom proteins is limited, but may be used to provide molecular level explanations...... for antivenom cross-reactivity. In turn, this may help guide antivenom development by elucidating immunological biases in existing antivenoms. In this study, we have identified and characterized linear elements of B-cell epitopes from 870 pit viper venom protein sequences by employing a high......-throughput methodology based on custom designed high-density peptide microarrays. By combining data on antibody-peptide interactions with multiple sequence alignments of homologous toxin sequences and protein modelling, we have determined linear elements of antibody binding sites for snake venom metalloproteases (SVMPs...

High Throughput Neuro-Imaging Informatics

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Michael I Miller

2013-12-01

Full Text Available This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high dimensional neuroinformatic representations index containing O(E3-E4 discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high throughput machine learning methods for supporting (i cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii integration of image and non-image information for diagnosis and prognosis.

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

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Manish Biyani

2015-07-01

Full Text Available Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density, ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era.

High-resolution mapping of linear antibody epitopes using ultrahigh-density peptide microarrays

DEFF Research Database (Denmark)

Buus, Søren; Rockberg, Johan; Forsström, Björn

2012-01-01

Antibodies empower numerous important scientific, clinical, diagnostic, and industrial applications. Ideally, the epitope(s) targeted by an antibody should be identified and characterized, thereby establishing antibody reactivity, highlighting possible cross-reactivities, and perhaps even warning...... against unwanted (e.g. autoimmune) reactivities. Antibodies target proteins as either conformational or linear epitopes. The latter are typically probed with peptides, but the cost of peptide screening programs tends to prohibit comprehensive specificity analysis. To perform high-throughput, high......-resolution mapping of linear antibody epitopes, we have used ultrahigh-density peptide microarrays generating several hundred thousand different peptides per array. Using exhaustive length and substitution analysis, we have successfully examined the specificity of a panel of polyclonal antibodies raised against...

Novel high-throughput cell-based hybridoma screening methodology using the Celigo Image Cytometer.

Science.gov (United States)

Zhang, Haohai; Chan, Leo Li-Ying; Rice, William; Kassam, Nasim; Longhi, Maria Serena; Zhao, Haitao; Robson, Simon C; Gao, Wenda; Wu, Yan

2017-08-01

Hybridoma screening is a critical step for antibody discovery, which necessitates prompt identification of potential clones from hundreds to thousands of hybridoma cultures against the desired immunogen. Technical issues associated with ELISA- and flow cytometry-based screening limit accuracy and diminish high-throughput capability, increasing time and cost. Conventional ELISA screening with coated antigen is also impractical for difficult-to-express hydrophobic membrane antigens or multi-chain protein complexes. Here, we demonstrate novel high-throughput screening methodology employing the Celigo Image Cytometer, which avoids nonspecific signals by contrasting antibody binding signals directly on living cells, with and without recombinant antigen expression. The image cytometry-based high-throughput screening method was optimized by detecting the binding of hybridoma supernatants to the recombinant antigen CD39 expressed on Chinese hamster ovary (CHO) cells. Next, the sensitivity of the image cytometer was demonstrated by serial dilution of purified CD39 antibody. Celigo was used to measure antibody affinities of commercial and in-house antibodies to membrane-bound CD39. This cell-based screening procedure can be completely accomplished within one day, significantly improving throughput and efficiency of hybridoma screening. Furthermore, measuring direct antibody binding to living cells eliminated both false positive and false negative hits. The image cytometry method was highly sensitive and versatile, and could detect positive antibody in supernatants at concentrations as low as ~5ng/mL, with concurrent K d binding affinity coefficient determination. We propose that this screening method will greatly facilitate antibody discovery and screening technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

High Throughput WAN Data Transfer with Hadoop-based Storage

Science.gov (United States)

Amin, A.; Bockelman, B.; Letts, J.; Levshina, T.; Martin, T.; Pi, H.; Sfiligoi, I.; Thomas, M.; Wüerthwein, F.

2011-12-01

Hadoop distributed file system (HDFS) is becoming more popular in recent years as a key building block of integrated grid storage solution in the field of scientific computing. Wide Area Network (WAN) data transfer is one of the important data operations for large high energy physics experiments to manage, share and process datasets of PetaBytes scale in a highly distributed grid computing environment. In this paper, we present the experience of high throughput WAN data transfer with HDFS-based Storage Element. Two protocols, GridFTP and fast data transfer (FDT), are used to characterize the network performance of WAN data transfer.

High Throughput WAN Data Transfer with Hadoop-based Storage

International Nuclear Information System (INIS)

Amin, A; Thomas, M; Bockelman, B; Letts, J; Martin, T; Pi, H; Sfiligoi, I; Wüerthwein, F; Levshina, T

2011-01-01

Hadoop distributed file system (HDFS) is becoming more popular in recent years as a key building block of integrated grid storage solution in the field of scientific computing. Wide Area Network (WAN) data transfer is one of the important data operations for large high energy physics experiments to manage, share and process datasets of PetaBytes scale in a highly distributed grid computing environment. In this paper, we present the experience of high throughput WAN data transfer with HDFS-based Storage Element. Two protocols, GridFTP and fast data transfer (FDT), are used to characterize the network performance of WAN data transfer.

Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

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Lan Shu

2008-07-01

Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE’s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

A continuous high-throughput bioparticle sorter based on 3D traveling-wave dielectrophoresis.

Science.gov (United States)

Cheng, I-Fang; Froude, Victoria E; Zhu, Yingxi; Chang, Hsueh-Chia; Chang, Hsien-Chang

2009-11-21

We present a high throughput (maximum flow rate approximately 10 microl/min or linear velocity approximately 3 mm/s) continuous bio-particle sorter based on 3D traveling-wave dielectrophoresis (twDEP) at an optimum AC frequency of 500 kHz. The high throughput sorting is achieved with a sustained twDEP particle force normal to the continuous through-flow, which is applied over the entire chip by a single 3D electrode array. The design allows continuous fractionation of micron-sized particles into different downstream sub-channels based on differences in their twDEP mobility on both sides of the cross-over. Conventional DEP is integrated upstream to focus the particles into a single levitated queue to allow twDEP sorting by mobility difference and to minimize sedimentation and field-induced lysis. The 3D electrode array design minimizes the offsetting effect of nDEP (negative DEP with particle force towards regions with weak fields) on twDEP such that both forces increase monotonically with voltage to further increase the throughput. Effective focusing and separation of red blood cells from debris-filled heterogeneous samples are demonstrated, as well as size-based separation of poly-dispersed liposome suspensions into two distinct bands at 2.3 to 4.6 microm and 1.5 to 2.7 microm, at the highest throughput recorded in hand-held chips of 6 microl/min.

Broad spectrum microarray for fingerprint-based bacterial species identification

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Frey Jürg E

2010-02-01

Full Text Available Abstract Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups.

Identifying Fishes through DNA Barcodes and Microarrays.

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Marc Kochzius

2010-09-01

Full Text Available International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection.This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S, cytochrome b (cyt b, and cytochrome oxidase subunit I (COI for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90% renders the DNA barcoding marker as rather unsuitable for this high-throughput technology.Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

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Brett Trost

Full Text Available Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA, a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

Science.gov (United States)

Trost, Brett; Kindrachuk, Jason; Määttänen, Pekka; Napper, Scott; Kusalik, Anthony

2013-01-01

Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

Hierarchical information representation and efficient classification of gene expression microarray data

OpenAIRE

Bosio, Mattia

2014-01-01

In the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and eficiently. Even if microarrays are a consolidated research technology nowadays and the trends in high-throughput data analysis are shifting towards new technologies like Next Generation Sequencing (NGS), an optimum method for sample...

Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

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Ile Kristina E

2003-07-01

Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

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

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

2017-01-01

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

glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data

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Andrew Paul Hutchins

2014-01-01

Full Text Available Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data, and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.

glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data.

Science.gov (United States)

Hutchins, Andrew Paul; Jauch, Ralf; Dyla, Mateusz; Miranda-Saavedra, Diego

2014-01-01

Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.

Principles of gene microarray data analysis.

Science.gov (United States)

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

Teolenn: an efficient and customizable workflow to design high-quality probes for microarray experiments

Science.gov (United States)

Jourdren, Laurent; Duclos, Aurélie; Brion, Christian; Portnoy, Thomas; Mathis, Hugues; Margeot, Antoine; Le Crom, Stéphane

2010-01-01

Despite the development of new high-throughput sequencing techniques, microarrays are still attractive tools to study small genome organisms, thanks to sample multiplexing and high-feature densities. However, the oligonucleotide design remains a delicate step for most users. A vast array of software is available to deal with this problem, but each program is developed with its own strategy, which makes the choice of the best solution difficult. Here we describe Teolenn, a universal probe design workflow developed with a flexible and customizable module organization allowing fixed or variable length oligonucleotide generation. In addition, our software is able to supply quality scores for each of the designed probes. In order to assess the relevance of these scores, we performed a real hybridization using a tiling array designed against the Trichoderma reesei fungus genome. We show that our scoring pipeline correlates with signal quality for 97.2% of all the designed probes, allowing for a posteriori comparisons between quality scores and signal intensities. This result is useful in discarding any bad scoring probes during the design step in order to get high-quality microarrays. Teolenn is available at http://transcriptome.ens.fr/teolenn/. PMID:20176570

Validation of tissue microarray technology in squamous cell carcinoma of the esophagus

NARCIS (Netherlands)

Boone, Judith; van Hillegersberg, Richard; van Diest, Paul J.; Offerhaus, G. Johan A.; Borel Rinkes, Inne H. M.; ten Kate, Fiebo J. W.

2008-01-01

Tissue microarray (TMA) technology has been developed to facilitate high-throughput immunohistochemical and in situ hybridization analysis of tissues by inserting small tissue biopsy cores into a single paraffin block. Several studies have revealed novel prognostic biomarkers in esophageal squamous

High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

Science.gov (United States)

High throughput toxicokinetics (HTTK) is an approach that allows for rapid estimations of TK for hundreds of environmental chemicals. HTTK-based reverse dosimetry (i.e, reverse toxicokinetics or RTK) is used in order to convert high throughput in vitro toxicity screening (HTS) da...

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

Science.gov (United States)

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Optimization and high-throughput screening of antimicrobial peptides.

Science.gov (United States)

Blondelle, Sylvie E; Lohner, Karl

2010-01-01

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

Bioinformatics and Microarray Data Analysis on the Cloud.

Science.gov (United States)

Calabrese, Barbara; Cannataro, Mario

2016-01-01

High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

Directory of Open Access Journals (Sweden)

Andrea Flannery

2015-12-01

Full Text Available Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i conventional carbohydrate or glycan microarrays; (ii whole mucin microarrays; and (iii microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments.

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

Science.gov (United States)

Cell-based high throughput screening (HTS) technologies are becoming mainstream in chemical safety evaluations. The US Environmental Protection Agency (EPA) Toxicity Forecaster (ToxCastTM) and the multi-agency Tox21 Programs have been at the forefront in advancing this science, m...

Caveats and limitations of plate reader-based high-throughput kinetic measurements of intracellular calcium levels

International Nuclear Information System (INIS)

Heusinkveld, Harm J.; Westerink, Remco H.S.

2011-01-01

Calcium plays a crucial role in virtually all cellular processes, including neurotransmission. The intracellular Ca 2+ concentration ([Ca 2+ ] i ) is therefore an important readout in neurotoxicological and neuropharmacological studies. Consequently, there is an increasing demand for high-throughput measurements of [Ca 2+ ] i , e.g. using multi-well microplate readers, in hazard characterization, human risk assessment and drug development. However, changes in [Ca 2+ ] i are highly dynamic, thereby creating challenges for high-throughput measurements. Nonetheless, several protocols are now available for real-time kinetic measurement of [Ca 2+ ] i in plate reader systems, though the results of such plate reader-based measurements have been questioned. In view of the increasing use of plate reader systems for measurements of [Ca 2+ ] i a careful evaluation of current technologies is warranted. We therefore performed an extensive set of experiments, using two cell lines (PC12 and B35) and two fluorescent calcium-sensitive dyes (Fluo-4 and Fura-2), for comparison of a linear plate reader system with single cell fluorescence microscopy. Our data demonstrate that the use of plate reader systems for high-throughput real-time kinetic measurements of [Ca 2+ ] i is associated with many pitfalls and limitations, including erroneous sustained increases in fluorescence, limited sensitivity and lack of single cell resolution. Additionally, our data demonstrate that probenecid, which is often used to prevent dye leakage, effectively inhibits the depolarization-evoked increase in [Ca 2+ ] i . Overall, the data indicate that the use of current plate reader-based strategies for high-throughput real-time kinetic measurements of [Ca 2+ ] i is associated with caveats and limitations that require further investigation. - Research highlights: → The use of plate readers for high-throughput screening of intracellular Ca 2+ is associated with many pitfalls and limitations. → Single cell

High Throughput Facility

Data.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

LS Moreira Teixeira

2012-06-01

Full Text Available Cell-based cartilage repair strategies such as matrix-induced autologous chondrocyte implantation (MACI could be improved by enhancing cell performance. We hypothesised that micro-aggregates of chondrocytes generated in high-throughput prior to implantation in a defect could stimulate cartilaginous matrix deposition and remodelling. To address this issue, we designed a micro-mould to enable controlled high-throughput formation of micro-aggregates. Morphology, stability, gene expression profiles and chondrogenic potential of micro-aggregates of human and bovine chondrocytes were evaluated and compared to single-cells cultured in micro-wells and in 3D after encapsulation in Dextran-Tyramine (Dex-TA hydrogels in vitro and in vivo. We successfully formed micro-aggregates of human and bovine chondrocytes with highly controlled size, stability and viability within 24 hours. Micro-aggregates of 100 cells presented a superior balance in Collagen type I and Collagen type II gene expression over single cells and micro-aggregates of 50 and 200 cells. Matrix metalloproteinases 1, 9 and 13 mRNA levels were decreased in micro-aggregates compared to single-cells. Histological and biochemical analysis demonstrated enhanced matrix deposition in constructs seeded with micro-aggregates cultured in vitro and in vivo, compared to single-cell seeded constructs. Whole genome microarray analysis and single gene expression profiles using human chondrocytes confirmed increased expression of cartilage-related genes when chondrocytes were cultured in micro-aggregates. In conclusion, we succeeded in controlled high-throughput formation of micro-aggregates of chondrocytes. Compared to single cell-seeded constructs, seeding of constructs with micro-aggregates greatly improved neo-cartilage formation. Therefore, micro-aggregation prior to chondrocyte implantation in current MACI procedures, may effectively accelerate hyaline cartilage formation.

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

Science.gov (United States)

Moreira Teixeira, L S; Leijten, J C H; Sobral, J; Jin, R; van Apeldoorn, A A; Feijen, J; van Blitterswijk, C; Dijkstra, P J; Karperien, M

2012-06-05

Cell-based cartilage repair strategies such as matrix-induced autologous chondrocyte implantation (MACI) could be improved by enhancing cell performance. We hypothesised that micro-aggregates of chondrocytes generated in high-throughput prior to implantation in a defect could stimulate cartilaginous matrix deposition and remodelling. To address this issue, we designed a micro-mould to enable controlled high-throughput formation of micro-aggregates. Morphology, stability, gene expression profiles and chondrogenic potential of micro-aggregates of human and bovine chondrocytes were evaluated and compared to single-cells cultured in micro-wells and in 3D after encapsulation in Dextran-Tyramine (Dex-TA) hydrogels in vitro and in vivo. We successfully formed micro-aggregates of human and bovine chondrocytes with highly controlled size, stability and viability within 24 hours. Micro-aggregates of 100 cells presented a superior balance in Collagen type I and Collagen type II gene expression over single cells and micro-aggregates of 50 and 200 cells. Matrix metalloproteinases 1, 9 and 13 mRNA levels were decreased in micro-aggregates compared to single-cells. Histological and biochemical analysis demonstrated enhanced matrix deposition in constructs seeded with micro-aggregates cultured in vitro and in vivo, compared to single-cell seeded constructs. Whole genome microarray analysis and single gene expression profiles using human chondrocytes confirmed increased expression of cartilage-related genes when chondrocytes were cultured in micro-aggregates. In conclusion, we succeeded in controlled high-throughput formation of micro-aggregates of chondrocytes. Compared to single cell-seeded constructs, seeding of constructs with micro-aggregates greatly improved neo-cartilage formation. Therefore, micro-aggregation prior to chondrocyte implantation in current MACI procedures, may effectively accelerate hyaline cartilage formation.

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

OpenAIRE

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

2011-01-01

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

Microarray Analysis of Late Response to Boron Toxicity in Barley (Hordeum vulgare L.) Leaves

NARCIS (Netherlands)

Oz, M.T.; Yilmaz, R.; Eyidogan, F.; Graaff, de L.H.; Yucel, M.; Oktem, H.A.

2009-01-01

DNA microarrays, being high-density and high-throughput, allow quantitative analyses of thousands of genes and their expression patterns in parallel. In this study, Barley1 GereChip was used to investigate transcriptome changes associated with boron (B) toxicity in a sensitive barley cultivar

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

Science.gov (United States)

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.

Development and assessment of microarray-based DNA fingerprinting in Eucalyptus grandis.

Science.gov (United States)

Lezar, Sabine; Myburg, A A; Berger, D K; Wingfield, M J; Wingfield, B D

2004-11-01

Development of improved Eucalyptus genotypes involves the routine identification of breeding stock and superior clones. Currently, microsatellites and random amplified polymorphic DNA markers are the most widely used DNA-based techniques for fingerprinting of these trees. While these techniques have provided rapid and powerful fingerprinting assays, they are constrained by their reliance on gel or capillary electrophoresis, and therefore, relatively low throughput of fragment analysis. In contrast, recently developed microarray technology holds the promise of parallel analysis of thousands of markers in plant genomes. The aim of this study was to develop a DNA fingerprinting chip for Eucalyptus grandis and to investigate its usefulness for fingerprinting of eucalypt trees. A prototype chip was prepared using a partial genomic library from total genomic DNA of 23 E. grandis trees, of which 22 were full siblings. A total of 384 cloned genomic fragments were individually amplified and arrayed onto glass slides. DNA fingerprints were obtained for 17 individuals by hybridizing labeled genome representations of the individual trees to the 384-element chip. Polymorphic DNA fragments were identified by evaluating the binary distribution of their background-corrected signal intensities across full-sib individuals. Among 384 DNA fragments on the chip, 104 (27%) were found to be polymorphic. Hybridization of these polymorphic fragments was highly repeatable (R2>0.91) within the E. grandis individuals, and they allowed us to identify all 17 full-sib individuals. Our results suggest that DNA microarrays can be used to effectively fingerprint large numbers of closely related Eucalyptus trees.

A novel method to quantify local CpG methylation density by regional methylation elongation assay on microarray

Directory of Open Access Journals (Sweden)

Qiao Yingjuan

2008-01-01

Full Text Available Abstract Background DNA methylation based techniques are important tools in both clinical diagnostics and therapeutics. But most of these methods only analyze a few CpG sites in a target region. Indeed, difference of site-specific methylation may also lead to a change of methylation density in many cases, and it has been found that the density of methylation is more important than methylation of single CpG site for gene silencing. Results We have developed a novel approach for quantitative analysis of CpG methylation density on the basis of microarray-based hybridization and incorporation of Cy5-dCTP into the Cy3 labeled target DNA by using Taq DNA Polymerase on microarray. The quantification is achieved by measuring Cy5/Cy3 signal ratio which is proportional to methylation density. This methylation-sensitive technique, termed RMEAM (regional methylation elongation assay on microarray, provides several advantages over existing methods used for methylation analysis. It can determine an exact methylation density of the given region, and has potential of high throughput. We demonstrate a use of this method in determining the methylation density of the promoter region of the tumor-related gene MLH1, TERT and MGMT in colorectal carcinoma patients. Conclusion This technique allows for quantitative analysis of regional methylation density, which is the representative of all allelic methylation patterns in the sample. The results show that this technique has the characteristics of simplicity, rapidness, specificity and high-throughput.

A high throughput DNA extraction method with high yield and quality

Directory of Open Access Journals (Sweden)

Xin Zhanguo

2012-07-01

Full Text Available Abstract Background Preparation of large quantity and high quality genomic DNA from a large number of plant samples is a major bottleneck for most genetic and genomic analyses, such as, genetic mapping, TILLING (Targeting Induced Local Lesion IN Genome, and next-generation sequencing directly from sheared genomic DNA. A variety of DNA preparation methods and commercial kits are available. However, they are either low throughput, low yield, or costly. Here, we describe a method for high throughput genomic DNA isolation from sorghum [Sorghum bicolor (L. Moench] leaves and dry seeds with high yield, high quality, and affordable cost. Results We developed a high throughput DNA isolation method by combining a high yield CTAB extraction method with an improved cleanup procedure based on MagAttract kit. The method yielded large quantity and high quality DNA from both lyophilized sorghum leaves and dry seeds. The DNA yield was improved by nearly 30 fold with 4 times less consumption of MagAttract beads. The method can also be used in other plant species, including cotton leaves and pine needles. Conclusion A high throughput system for DNA extraction from sorghum leaves and seeds was developed and validated. The main advantages of the method are low cost, high yield, high quality, and high throughput. One person can process two 96-well plates in a working day at a cost of $0.10 per sample of magnetic beads plus other consumables that other methods will also need.

A Parallel Software Pipeline for DMET Microarray Genotyping Data Analysis

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Giuseppe Agapito

2018-06-01

Full Text Available Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS, Genome-Wide Association Studies (GWAS, Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g., high execution time and required memory to bioinformatic software. Thus a main requirement of modern bioinformatic softwares, is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based Single Nucleotide Polymorphism (SNP genotyping data. A use case in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data. microPipe is available under Creative Commons license, and is freely downloadable for academic and not-for-profit institutions.

Label and Label-Free Detection Techniques for Protein Microarrays

Directory of Open Access Journals (Sweden)

Amir Syahir

2015-04-01

Full Text Available Protein microarray technology has gone through numerous innovative developments in recent decades. In this review, we focus on the development of protein detection methods embedded in the technology. Early microarrays utilized useful chromophores and versatile biochemical techniques dominated by high-throughput illumination. Recently, the realization of label-free techniques has been greatly advanced by the combination of knowledge in material sciences, computational design and nanofabrication. These rapidly advancing techniques aim to provide data without the intervention of label molecules. Here, we present a brief overview of this remarkable innovation from the perspectives of label and label-free techniques in transducing nano‑biological events.

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

DEFF Research Database (Denmark)

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

2015-01-01

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

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

Science.gov (United States)

William R. Kenealy; Thomas W. Jeffries

2003-01-01

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

Study on a digital pulse processing algorithm based on template-matching for high-throughput spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Wen, Xianfei; Yang, Haori

2015-06-01

A major challenge in utilizing spectroscopy techniques for nuclear safeguards is to perform high-resolution measurements at an ultra-high throughput rate. Traditionally, piled-up pulses are rejected to ensure good energy resolution. To improve throughput rate, high-pass filters are normally implemented to shorten pulses. However, this reduces signal-to-noise ratio and causes degradation in energy resolution. In this work, a pulse pile-up recovery algorithm based on template-matching was proved to be an effective approach to achieve high-throughput gamma ray spectroscopy. First, a discussion of the algorithm was given in detail. Second, the algorithm was then successfully utilized to process simulated piled-up pulses from a scintillator detector. Third, the algorithm was implemented to analyze high rate data from a NaI detector, a silicon drift detector and a HPGe detector. The promising results demonstrated the capability of this algorithm to achieve high-throughput rate without significant sacrifice in energy resolution. The performance of the template-matching algorithm was also compared with traditional shaping methods. - Highlights: • A detailed discussion on the template-matching algorithm was given. • The algorithm was tested on data from a NaI and a Si detector. • The algorithm was successfully implemented on high rate data from a HPGe detector. • The performance of the algorithm was compared with traditional shaping methods. • The advantage of the algorithm in active interrogation was discussed.

Bulk segregant analysis by high-throughput sequencing reveals a novel xylose utilization gene from Saccharomyces cerevisiae.

Directory of Open Access Journals (Sweden)

Jared W Wenger

2010-05-01

Full Text Available Fermentation of xylose is a fundamental requirement for the efficient production of ethanol from lignocellulosic biomass sources. Although they aggressively ferment hexoses, it has long been thought that native Saccharomyces cerevisiae strains cannot grow fermentatively or non-fermentatively on xylose. Population surveys have uncovered a few naturally occurring strains that are weakly xylose-positive, and some S. cerevisiae have been genetically engineered to ferment xylose, but no strain, either natural or engineered, has yet been reported to ferment xylose as efficiently as glucose. Here, we used a medium-throughput screen to identify Saccharomyces strains that can increase in optical density when xylose is presented as the sole carbon source. We identified 38 strains that have this xylose utilization phenotype, including strains of S. cerevisiae, other sensu stricto members, and hybrids between them. All the S. cerevisiae xylose-utilizing strains we identified are wine yeasts, and for those that could produce meiotic progeny, the xylose phenotype segregates as a single gene trait. We mapped this gene by Bulk Segregant Analysis (BSA using tiling microarrays and high-throughput sequencing. The gene is a putative xylitol dehydrogenase, which we name XDH1, and is located in the subtelomeric region of the right end of chromosome XV in a region not present in the S288c reference genome. We further characterized the xylose phenotype by performing gene expression microarrays and by genetically dissecting the endogenous Saccharomyces xylose pathway. We have demonstrated that natural S. cerevisiae yeasts are capable of utilizing xylose as the sole carbon source, characterized the genetic basis for this trait as well as the endogenous xylose utilization pathway, and demonstrated the feasibility of BSA using high-throughput sequencing.

High-throughput continuous cryopump

International Nuclear Information System (INIS)

Foster, C.A.

1986-01-01

A cryopump with a unique method of regeneration which allows continuous operation at high throughput has been constructed and tested. Deuterium was pumped continuously at a throughput of 30 Torr.L/s at a speed of 2000 L/s and a compression ratio of 200. Argon was pumped at a throughput of 60 Torr.L/s at a speed of 1275 L/s. To produce continuous operation of the pump, a method of regeneration that does not thermally cycle the pump is employed. A small chamber (the ''snail'') passes over the pumping surface and removes the frost from it either by mechanical action with a scraper or by local heating. The material removed is topologically in a secondary vacuum system with low conductance into the primary vacuum; thus, the exhaust can be pumped at pressures up to an effective compression ratio determined by the ratio of the pumping speed to the leakage conductance of the snail. The pump, which is all-metal-sealed and dry and which regenerates every 60 s, would be an ideal system for pumping tritium. Potential fusion applications are for mpmp limiters, for repeating pneumatic pellet injection lines, and for the centrifuge pellet injector spin tank, all of which will require pumping tritium at high throughput. Industrial applications requiring ultraclean pumping of corrosive gases at high throughput, such as the reactive ion etch semiconductor process, may also be feasible

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

Science.gov (United States)

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

2018-03-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Guo, Xuejiang; Tang, Keqi

2017-06-14

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

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

Energy Technology Data Exchange (ETDEWEB)

Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

High-throughput DNA microarray detection of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley, Nepal.

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Inoue, Daisuke; Hinoura, Takuji; Suzuki, Noriko; Pang, Junqin; Malla, Rabin; Shrestha, Sadhana; Chapagain, Saroj Kumar; Matsuzawa, Hiroaki; Nakamura, Takashi; Tanaka, Yasuhiro; Ike, Michihiko; Nishida, Kei; Sei, Kazunari

2015-01-01

Because of heavy dependence on groundwater for drinking water and other domestic use, microbial contamination of groundwater is a serious problem in the Kathmandu Valley, Nepal. This study investigated comprehensively the occurrence of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley by applying DNA microarray analysis targeting 941 pathogenic bacterial species/groups. Water quality measurements found significant coliform (fecal) contamination in 10 of the 11 investigated groundwater samples and significant nitrogen contamination in some samples. The results of DNA microarray analysis revealed the presence of 1-37 pathogen species/groups, including 1-27 biosafety level 2 ones, in 9 of the 11 groundwater samples. While the detected pathogens included several feces- and animal-related ones, those belonging to Legionella and Arthrobacter, which were considered not to be directly associated with feces, were detected prevalently. This study could provide a rough picture of overall pathogenic bacterial contamination in the Kathmandu Valley, and demonstrated the usefulness of DNA microarray analysis as a comprehensive screening tool of a wide variety of pathogenic bacteria.

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

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Spitzer, James D; Hupert, Nathaniel; Duckart, Jonathan; Xiong, Wei

2007-01-01

Community-based mass prophylaxis is a core public health operational competency, but staffing needs may overwhelm the local trained health workforce. Just-in-time (JIT) training of emergency staff and computer modeling of workforce requirements represent two complementary approaches to address this logistical problem. Multnomah County, Oregon, conducted a high-throughput point of dispensing (POD) exercise to test JIT training and computer modeling to validate POD staffing estimates. The POD had 84% non-health-care worker staff and processed 500 patients per hour. Post-exercise modeling replicated observed staff utilization levels and queue formation, including development and amelioration of a large medical evaluation queue caused by lengthy processing times and understaffing in the first half-hour of the exercise. The exercise confirmed the feasibility of using JIT training for high-throughput antibiotic dispensing clinics staffed largely by nonmedical professionals. Patient processing times varied over the course of the exercise, with important implications for both staff reallocation and future POD modeling efforts. Overall underutilization of staff revealed the opportunity for greater efficiencies and even higher future throughputs.

Inkjet-assisted layer-by-layer printing of quantum dot/enzyme microarrays for highly sensitive detection of organophosphorous pesticides

Energy Technology Data Exchange (ETDEWEB)

Luan, Enxiao; Zheng, Zhaozhu; Li, Xinyu; Gu, Hongxi [State Key Laboratory of Urban Water Resource and Environment, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150080 (China); Micro- and Nanotechnology Research Center, Harbin Institute of Technology, Harbin 150080 (China); Liu, Shaoqin, E-mail: shaoqinliu@hit.edu.cn [Micro- and Nanotechnology Research Center, Harbin Institute of Technology, Harbin 150080 (China)

2016-04-15

We present a facile fabrication of layer-by-layer (LbL) microarrays of quantum dots (QDs) and acetylcholinesterase enzyme (AChE). The resulting arrays had several unique properties, such as low cost, high integration and excellent flexibility and time–saving. The presence of organophosphorous pesticides (OPs) can inhibit the AChE activity and thus changes the fluorescent intensity of QDs/AChE microscopic dot arrays. Therefore, the QDs/AChE microscopic dot arrays were used for the sensitive visual detection of OPs. Linear calibration for parathion and paraoxon was obtained in the range of 5–100 μg L{sup −1} under the optimized conditions with the limit of detection (LOD) of 10 μg L{sup −1}. The arrays have been successfully used for detection of OPs in fruits and water real samples. The new array was validated by comparison with conventional high performance liquid chromatography-mass spectrometry (HPLC-MS). - Graphical abstract: A fluorimetric assay for high-throughput screening of organophosphorous pesticides was developed based on the CdTe QDs/AChE microarrays via inkjet-assisted LbL printing techniques. - Highlights: • The large scale microarrays of CdTe QDs and AChE were fabricated by facile inkjet-assisted LbL printing technique. • The QDs/AChE microscopic dot arrays could be used quantitatively and rapidly for the sensitively visual detection of OPs. • A detection limit of 10 μg L{sup −1} was achieved, much lower than levels specified by standard tests and other colorimetric detection methods. • The low cost, short processing time, sufficient sensitivity, good stability and ease of use make it for a facile platform for on-site screening.

Microarray-based screening of heat shock protein inhibitors.

Science.gov (United States)

Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

2014-06-20

Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

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

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Putt, Karson S; Pugh, Randall B

2013-01-01

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

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

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María Ballester

Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

Development and application of an oligonucleotide microarray and real-time quantitative PCR for detection of wastewater bacterial pathogens

Energy Technology Data Exchange (ETDEWEB)

Lee, Dae-Young [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada)], E-mail: daeyoung.lee@ec.gc.ca; Lauder, Heather; Cruwys, Heather; Falletta, Patricia [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada); Beaudette, Lee A. [Environmental Science and Technology Centre, Environment Canada, 335 River Road South, Ottawa, Ontario, K1A 0H3 (Canada)], E-mail: lee.beaudette@ec.gc.ca

2008-07-15

Conventional microbial water quality test methods are well known for their technical limitations, such as lack of direct pathogen detection capacity and low throughput capability. The microarray assay has recently emerged as a promising alternative for environmental pathogen monitoring. In this study, bacterial pathogens were detected in municipal wastewater using a microarray equipped with short oligonucleotide probes targeting 16S rRNA sequences. To date, 62 probes have been designed against 38 species, 4 genera, and 1 family of pathogens. The detection sensitivity of the microarray for a waterborne pathogen Aeromonas hydrophila was determined to be approximately 1.0% of the total DNA, or approximately 10{sup 3}A. hydrophila cells per sample. The efficacy of the DNA microarray was verified in a parallel study where pathogen genes and E. coli cells were enumerated using real-time quantitative PCR (qPCR) and standard membrane filter techniques, respectively. The microarray and qPCR successfully detected multiple wastewater pathogen species at different stages of the disinfection process (i.e. secondary effluents vs. disinfected final effluents) and at two treatment plants employing different disinfection methods (i.e. chlorination vs. UV irradiation). This result demonstrates the effectiveness of the DNA microarray as a semi-quantitative, high throughput pathogen monitoring tool for municipal wastewater.

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data

Directory of Open Access Journals (Sweden)

Harris Lyndsay N

2006-04-01

Full Text Available Abstract Background Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in the data. Results We developed a recursive support vector machine (R-SVM algorithm to select important genes/biomarkers for the classification of noisy data. We compared its performance to a similar, state-of-the-art method (SVM recursive feature elimination or SVM-RFE, paying special attention to the ability of recovering the true informative genes/biomarkers and the robustness to outliers in the data. Simulation experiments show that a 5 %-~20 % improvement over SVM-RFE can be achieved regard to these properties. The SVM-based methods are also compared with a conventional univariate method and their respective strengths and weaknesses are discussed. R-SVM was applied to two sets of SELDI-TOF-MS proteomics data, one from a human breast cancer study and the other from a study on rat liver cirrhosis. Important biomarkers found by the algorithm were validated by follow-up biological experiments. Conclusion The proposed R-SVM method is suitable for analyzing noisy high-throughput proteomics and microarray data and it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features. The multivariate SVM-based method outperforms the univariate method in the classification performance, but univariate methods can reveal more of the differentially expressed features especially when there are correlations between the features.

Plant-pathogen interactions: what microarray tells about it?

Science.gov (United States)

Lodha, T D; Basak, J

2012-01-01

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

Flexible hemispheric microarrays of highly pressure-sensitive sensors based on breath figure method.

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Wang, Zhihui; Zhang, Ling; Liu, Jin; Jiang, Hao; Li, Chunzhong

2018-05-30

Recently, flexible pressure sensors featuring high sensitivity, broad sensing range and real-time detection have aroused great attention owing to their crucial role in the development of artificial intelligent devices and healthcare systems. Herein, highly sensitive pressure sensors based on hemisphere-microarray flexible substrates are fabricated via inversely templating honeycomb structures deriving from a facile and static breath figure process. The interlocked and subtle microstructures greatly improve the sensing characteristics and compressibility of the as-prepared pressure sensor, endowing it a sensitivity as high as 196 kPa-1 and a wide pressure sensing range (0-100 kPa), as well as other superior performance, including a lower detection limit of 0.5 Pa, fast response time (10 000 cycles). Based on the outstanding sensing performance, the potential capability of our pressure sensor in capturing physiological information and recognizing speech signals has been demonstrated, indicating promising application in wearable and intelligent electronics.

MGI-oriented High-throughput Measurement of Interdiffusion Coefficient Matrices in Ni-based Superalloys

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TANG Ying

2017-01-01

Full Text Available One of the research hotspots in the field of high-temperature alloys was to search the substitutional elements for Re in order to prepare the single-crystal Ni-based superalloys with less or even no Re addition. To find the elements with similar or even lower diffusion coefficients in comparison with that of Re was one of the effective strategies. In multicomponent alloys, the interdiffusivity matrix were used to comprehensively characterize the diffusion ability of any alloying elements. Therefore, accurate determination of the composition-dependant and temperature-dependent interdiffusivities matrices of different elements in γ and γ' phases of Ni-based superalloys was high priority. The paper briefly introduces of the status of the interdiffusivity matrices determination in Ni-based superalloys, and the methods for determining the interdiffusivities in multicomponent alloys, including the traditional Matano-Kirkaldy method and recently proposed numerical inverse method. Because the traditional Matano-Kirkaldy method is of low efficiency, the experimental reports on interdiffusivity matrices in ternary and higher order sub-systems of the Ni-based superalloys were very scarce in the literature. While the numerical inverse method newly proposed in our research group based on Fick's second law can be utilized for high-throughput measurement of accurate interdiffusivity matrices in alloys with any number of components. After that, the successful application of the numerical inverse method in the high-throughput measurement of interdiffusivity matrices in alloys is demonstrated in fcc (γ phase of the ternary Ni-Al-Ta system. Moreover, the validation of the resulting composition-dependant and temperature-dependent interdiffusivity matrices is also comprehensively made. Then, this paper summarizes the recent progress in the measurement of interdiffusivity matrices in γ and γ' phases of a series of core ternary Ni-based superalloys achieved in

HDAT: web-based high-throughput screening data analysis tools

International Nuclear Information System (INIS)

Liu, Rong; Hassan, Taimur; Rallo, Robert; Cohen, Yoram

2013-01-01

The increasing utilization of high-throughput screening (HTS) in toxicity studies of engineered nano-materials (ENMs) requires tools for rapid and reliable processing and analyses of large HTS datasets. In order to meet this need, a web-based platform for HTS data analyses tools (HDAT) was developed that provides statistical methods suitable for ENM toxicity data. As a publicly available computational nanoinformatics infrastructure, HDAT provides different plate normalization methods, various HTS summarization statistics, self-organizing map (SOM)-based clustering analysis, and visualization of raw and processed data using both heat map and SOM. HDAT has been successfully used in a number of HTS studies of ENM toxicity, thereby enabling analysis of toxicity mechanisms and development of structure–activity relationships for ENM toxicity. The online approach afforded by HDAT should encourage standardization of and future advances in HTS as well as facilitate convenient inter-laboratory comparisons of HTS datasets. (paper)

A DVD-ROM based high-throughput cantilever sensing platform

DEFF Research Database (Denmark)

Bosco, Filippo

and October 2011. The project was part of the Xsense research network, funded by the Strategic Danish Research Council, and supervised by Prof. Anja Boisen. The goal of the Xsense project is to design and fabricate a compact and cheap device for explosive sensing in air and liquid. Four different technologies...... of a high-throughput label-free sensor platform utilizing cantilever based sensors. These sensors have often been acclaimed to facilitate highly parallelized operation. Unfortunately, so far no concept has been presented which offers large data sets as well as easy liquid sample handling. We use optics...... and mechanics from a DVD player to handle liquid samples and to read-out cantilever deflection and resonant frequency. In a few minutes, several liquid samples can be analyzed in parallel, measuring over several hundreds of individual cantilevers. Three generations of systems have been developed and tested...

In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

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Andreas Weinhäusel

2012-06-01

Full Text Available The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics.

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

Directory of Open Access Journals (Sweden)

Karson S Putt

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

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

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

2015-09-01

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

Cell-Based Microarrays for In Vitro Toxicology

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Wegener, Joachim

2015-07-01

DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

Surface Plasmon Resonance: New Biointerface Designs and High-Throughput Affinity Screening

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Linman, Matthew J.; Cheng, Quan Jason

Surface plasmon resonance (SPR) is a surface optical technique that measures minute changes in refractive index at a metal-coated surface. It has become increasingly popular in the study of biological and chemical analytes because of its label-free measurement feature. In addition, SPR allows for both quantitative and qualitative assessment of binding interactions in real time, making it ideally suited for probing weak interactions that are often difficult to study with other methods. This chapter presents the biosensor development in the last 3 years or so utilizing SPR as the principal analytical technique, along with a concise background of the technique itself. While SPR has demonstrated many advantages, it is a nonselective method and so, building reproducible and functional interfaces is vital to sensing applications. This chapter, therefore, focuses mainly on unique surface chemistries and assay approaches to examine biological interactions with SPR. In addition, SPR imaging for high-throughput screening based on microarrays and novel hyphenated techniques involving the coupling of SPR to other analytical methods is discussed. The chapter concludes with a commentary on the current state of SPR biosensing technology and the general direction of future biosensor research.

PRIMEGENSw3: a web-based tool for high-throughput primer and probe design.

Science.gov (United States)

Kushwaha, Garima; Srivastava, Gyan Prakash; Xu, Dong

2015-01-01

Highly specific and efficient primer and probe design has been a major hurdle in many high-throughput techniques. Successful implementation of any PCR or probe hybridization technique depends on the quality of primers and probes used in terms of their specificity and cross-hybridization. Here we describe PRIMEGENSw3, a set of web-based utilities for high-throughput primer and probe design. These utilities allow users to select genomic regions and to design primer/probe for selected regions in an interactive, user-friendly, and automatic fashion. The system runs the PRIMEGENS algorithm in the back-end on the high-performance server with the stored genomic database or user-provided custom database for cross-hybridization check. Cross-hybridization is checked not only using BLAST but also by checking mismatch positions and energy calculation of potential hybridization hits. The results can be visualized online and also can be downloaded. The average success rate of primer design using PRIMEGENSw3 is ~90 %. The web server also supports primer design for methylated sequences, which is used in epigenetic studies. Stand-alone version of the software is also available for download at the website.

Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

Science.gov (United States)

Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

2018-03-01

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.

Throughput-Based Traffic Steering in LTE-Advanced HetNet Deployments

DEFF Research Database (Denmark)

Gimenez, Lucas Chavarria; Kovacs, Istvan Z.; Wigard, Jeroen

2015-01-01

The objective of this paper is to propose traffic steering solutions that aim at optimizing the end-user throughput. Two different implementations of an active mode throughput-based traffic steering algorithm for Heterogeneous Networks (HetNet) are introduced. One that always forces handover of t...... throughput is generally higher, reaching values of 36% and 18% for the medium- and high-load conditions....

A high-throughput fluorescence resonance energy transfer (FRET)-based endothelial cell apoptosis assay and its application for screening vascular disrupting agents

International Nuclear Information System (INIS)

Zhu, Xiaoming; Fu, Afu; Luo, Kathy Qian

2012-01-01

Highlights: ► An endothelial cell apoptosis assay using FRET-based biosensor was developed. ► The fluorescence of the cells changed from green to blue during apoptosis. ► This method was developed into a high-throughput assay in 96-well plates. ► This assay was applied to screen vascular disrupting agents. -- Abstract: In this study, we developed a high-throughput endothelial cell apoptosis assay using a fluorescence resonance energy transfer (FRET)-based biosensor. After exposure to apoptotic inducer UV-irradiation or anticancer drugs such as paclitaxel, the fluorescence of the cells changed from green to blue. We developed this method into a high-throughput assay in 96-well plates by measuring the emission ratio of yellow fluorescent protein (YFP) to cyan fluorescent protein (CFP) to monitor the activation of a key protease, caspase-3, during apoptosis. The Z′ factor for this assay was above 0.5 which indicates that this assay is suitable for a high-throughput analysis. Finally, we applied this functional high-throughput assay for screening vascular disrupting agents (VDA) which could induce endothelial cell apoptosis from our in-house compounds library and dioscin was identified as a hit. As this assay allows real time and sensitive detection of cell apoptosis, it will be a useful tool for monitoring endothelial cell apoptosis in living cell situation and for identifying new VDA candidates via a high-throughput screening.

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

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Hu Xiaohua

2011-07-01

Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

High Throughput Analysis of Photocatalytic Water Purification

NARCIS (Netherlands)

Sobral Romao, J.I.; Baiao Barata, David; Habibovic, Pamela; Mul, Guido; Baltrusaitis, Jonas

2014-01-01

We present a novel high throughput photocatalyst efficiency assessment method based on 96-well microplates and UV-Vis spectroscopy. We demonstrate the reproducibility of the method using methyl orange (MO) decomposition, and compare kinetic data obtained with those provided in the literature for

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

Science.gov (United States)

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

High-Throughput Particle Manipulation Based on Hydrodynamic Effects in Microchannels

Directory of Open Access Journals (Sweden)

Chao Liu

2017-03-01

Full Text Available Microfluidic techniques are effective tools for precise manipulation of particles and cells, whose enrichment and separation is crucial for a wide range of applications in biology, medicine, and chemistry. Recently, lateral particle migration induced by the intrinsic hydrodynamic effects in microchannels, such as inertia and elasticity, has shown its promise for high-throughput and label-free particle manipulation. The particle migration can be engineered to realize the controllable focusing and separation of particles based on a difference in size. The widespread use of inertial and viscoelastic microfluidics depends on the understanding of hydrodynamic effects on particle motion. This review will summarize the progress in the fundamental mechanisms and key applications of inertial and viscoelastic particle manipulation.

Fluorescence-based high-throughput screening of dicer cleavage activity

Czech Academy of Sciences Publication Activity Database

Podolská, Kateřina; Sedlák, David; Bartůněk, Petr; Svoboda, Petr

2014-01-01

Roč. 19, č. 3 (2014), s. 417-426 ISSN 1087-0571 R&D Projects: GA ČR GA13-29531S; GA MŠk(CZ) LC06077; GA MŠk LM2011022 Grant - others:EMBO(DE) 1483 Institutional support: RVO:68378050 Keywords : Dicer * siRNA * high-throughput screening Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.423, year: 2014

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

Science.gov (United States)

Kayala, Matthew A; Baldi, Pierre

2012-07-01

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

FiGS: a filter-based gene selection workbench for microarray data

Directory of Open Access Journals (Sweden)

Yun Taegyun

2010-01-01

Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

Analyses of Aloe polysaccharides using carbohydrate microarray profiling

DEFF Research Database (Denmark)

Isager Ahl, Louise; Grace, Olwen M; Pedersen, Henriette Lodberg

2018-01-01

As the popularity of Aloe vera extracts continues to rise, a desire to fully understand the individual polymer components of the leaf mesophyll, their relation to one another and the effects they have on the human body are increasing. Polysaccharides present in the leaf mesophyll have been...... identified as the components responsible for the biological activities of Aloe vera, and they have been widely studied in the past decades. However, the commonly used methods do not provide the desired platform to conduct large comparative studies of polysaccharide compositions as most of them require...... a complete or near-complete fractionation of the polymers. The objective for this study was to assess whether carbohydrate microarrays could be used for the high-throughput analysis of cell wall polysaccharides in Aloe leaf mesophyll. The method we chose is known as Comprehensive Microarray Polymer Profiling...

Detection of the specific binding on protein microarrays by oblique-incidence reflectivity difference method

International Nuclear Information System (INIS)

Lu, Heng; Wen, Juan; Wang, Xu; Yuan, Kun; Lu, Huibin; Zhou, Yueliang; Jin, Kuijuan; Yang, Guozhen; Li, Wei; Ruan, Kangcheng

2010-01-01

The specific binding between Cy5-labeled goat anti-mouse Immunoglobulin G (IgG) and mouse IgG with a concentration range from 625 to 10 4 µg ml −1 has been detected successfully by the oblique-incidence reflectivity difference (OI-RD) method in each procedure of microarray fabrication. The experimental data prove that the OI-RD method can be employed not only to distinguish the different concentrations in label-free fashion but also to detect the antibody–antigen capture. In addition, the differential treatment of the OI-RD signals can decrease the negative influences of glass slide as the microarray upholder. Therefore the OI-RD technique has promising applications for the label-free and high-throughput detection of protein microarrays

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

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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

Development of a high-throughput real time PCR based on a hot-start alternative for Pfu mediated by quantum dots

Science.gov (United States)

Sang, Fuming; Yang, Yang; Yuan, Lin; Ren, Jicun; Zhang, Zhizhou

2015-09-01

Hot start (HS) PCR is an excellent alternative for high-throughput real time PCR due to its ability to prevent nonspecific amplification at low temperature. Development of a cost-effective and simple HS PCR technique to guarantee high-throughput PCR specificity and consistency still remains a great challenge. In this study, we systematically investigated the HS characteristics of QDs triggered in real time PCR with EvaGreen and SYBR Green I dyes by the analysis of amplification curves, standard curves and melting curves. Two different kinds of DNA polymerases, Pfu and Taq, were employed. Here we showed that high specificity and efficiency of real time PCR were obtained in a plasmid DNA and an error-prone two-round PCR assay using QD-based HS PCR, even after an hour preincubation at 50 °C before real time PCR. Moreover, the results obtained by QD-based HS PCR were comparable to a commercial Taq antibody DNA polymerase. However, no obvious HS effect of QDs was found in real time PCR using Taq DNA polymerase. The findings of this study demonstrated that a cost-effective high-throughput real time PCR based on QD triggered HS PCR could be established with high consistency, sensitivity and accuracy.Hot start (HS) PCR is an excellent alternative for high-throughput real time PCR due to its ability to prevent nonspecific amplification at low temperature. Development of a cost-effective and simple HS PCR technique to guarantee high-throughput PCR specificity and consistency still remains a great challenge. In this study, we systematically investigated the HS characteristics of QDs triggered in real time PCR with EvaGreen and SYBR Green I dyes by the analysis of amplification curves, standard curves and melting curves. Two different kinds of DNA polymerases, Pfu and Taq, were employed. Here we showed that high specificity and efficiency of real time PCR were obtained in a plasmid DNA and an error-prone two-round PCR assay using QD-based HS PCR, even after an hour

High throughput sample processing and automated scoring

Directory of Open Access Journals (Sweden)

Gunnar eBrunborg

2014-10-01

Full Text Available The comet assay is a sensitive and versatile method for assessing DNA damage in cells. In the traditional version of the assay, there are many manual steps involved and few samples can be treated in one experiment. High throughput modifications have been developed during recent years, and they are reviewed and discussed. These modifications include accelerated scoring of comets; other important elements that have been studied and adapted to high throughput are cultivation and manipulation of cells or tissues before and after exposure, and freezing of treated samples until comet analysis and scoring. High throughput methods save time and money but they are useful also for other reasons: large-scale experiments may be performed which are otherwise not practicable (e.g., analysis of many organs from exposed animals, and human biomonitoring studies, and automation gives more uniform sample treatment and less dependence on operator performance. The high throughput modifications now available vary largely in their versatility, capacity, complexity and costs. The bottleneck for further increase of throughput appears to be the scoring.

High-Throughput Thermodynamic Modeling and Uncertainty Quantification for ICME

Science.gov (United States)

Otis, Richard A.; Liu, Zi-Kui

2017-05-01

One foundational component of the integrated computational materials engineering (ICME) and Materials Genome Initiative is the computational thermodynamics based on the calculation of phase diagrams (CALPHAD) method. The CALPHAD method pioneered by Kaufman has enabled the development of thermodynamic, atomic mobility, and molar volume databases of individual phases in the full space of temperature, composition, and sometimes pressure for technologically important multicomponent engineering materials, along with sophisticated computational tools for using the databases. In this article, our recent efforts will be presented in terms of developing new computational tools for high-throughput modeling and uncertainty quantification based on high-throughput, first-principles calculations and the CALPHAD method along with their potential propagations to downstream ICME modeling and simulations.

A microliter-scale high-throughput screening system with quantum-dot nanoprobes for amyloid-β aggregation inhibitors.

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Yukako Ishigaki

Full Text Available The aggregation of amyloid β protein (Aβ is a key step in the pathogenesis of Alzheimer's disease (AD, and therefore inhibitory substances for Aβ aggregation may have preventive and/or therapeutic potential for AD. Here we report a novel microliter-scale high-throughput screening system for Aβ aggregation inhibitors based on fluorescence microscopy-imaging technology with quantum-dot Nanoprobes. This screening system could be analyzed with a 5-µl sample volume when a 1536-well plate was used, and the inhibitory activity could be estimated as half-maximal effective concentrations (EC50. We attempted to comprehensively screen Aβ aggregation inhibitors from 52 spices using this system to assess whether this novel screening system is actually useful for screening inhibitors. Screening results indicate that approximately 90% of the ethanolic extracts from the spices showed inhibitory activity for Aβ aggregation. Interestingly, spices belonging to the Lamiaceae, the mint family, showed significantly higher activity than the average of tested spices. Furthermore, we tried to isolate the main inhibitory compound from Saturejahortensis, summer savory, a member of the Lamiaceae, using this system, and revealed that the main active compound was rosmarinic acid. These results demonstrate that this novel microliter-scale high-throughput screening system could be applied to the actual screening of Aβ aggregation inhibitors. Since this system can analyze at a microscopic scale, it is likely that further minimization of the system would easily be possible such as protein microarray technology.

A high-throughput readout architecture based on PCI-Express Gen3 and DirectGMA technology

International Nuclear Information System (INIS)

Rota, L.; Vogelgesang, M.; Perez, L.E. Ardila; Caselle, M.; Chilingaryan, S.; Dritschler, T.; Zilio, N.; Kopmann, A.; Balzer, M.; Weber, M.

2016-01-01

Modern physics experiments produce multi-GB/s data rates. Fast data links and high performance computing stages are required for continuous data acquisition and processing. Because of their intrinsic parallelism and computational power, GPUs emerged as an ideal solution to process this data in high performance computing applications. In this paper we present a high-throughput platform based on direct FPGA-GPU communication. The architecture consists of a Direct Memory Access (DMA) engine compatible with the Xilinx PCI-Express core, a Linux driver for register access, and high- level software to manage direct memory transfers using AMD's DirectGMA technology. Measurements with a Gen3 x8 link show a throughput of 6.4 GB/s for transfers to GPU memory and 6.6 GB/s to system memory. We also assess the possibility of using the architecture in low latency systems: preliminary measurements show a round-trip latency as low as 1 μs for data transfers to system memory, while the additional latency introduced by OpenCL scheduling is the current limitation for GPU based systems. Our implementation is suitable for real-time DAQ system applications ranging from photon science and medical imaging to High Energy Physics (HEP) systems

A high-throughput liquid bead array-based screening technology for Bt presence in GMO manipulation.

Science.gov (United States)

Fu, Wei; Wang, Huiyu; Wang, Chenguang; Mei, Lin; Lin, Xiangmei; Han, Xueqing; Zhu, Shuifang

2016-03-15

The number of species and planting areas of genetically modified organisms (GMOs) has been rapidly developed during the past ten years. For the purpose of GMO inspection, quarantine and manipulation, we have now devised a high-throughput Bt-based GMOs screening method based on the liquid bead array. This novel method is based on the direct competitive recognition between biotinylated antibodies and beads-coupled antigens, searching for Bt presence in samples if it contains Bt Cry1 Aa, Bt Cry1 Ab, Bt Cry1 Ac, Bt Cry1 Ah, Bt Cry1 B, Bt Cry1 C, Bt Cry1 F, Bt Cry2 A, Bt Cry3 or Bt Cry9 C. Our method has a wide GMO species coverage so that more than 90% of the whole commercialized GMO species can be identified throughout the world. Under our optimization, specificity, sensitivity, repeatability and availability validation, the method shows a high specificity and 10-50 ng/mL sensitivity of quantification. We then assessed more than 1800 samples in the field and food market to prove capacity of our method in performing a high throughput screening work for GMO manipulation. Our method offers an applicant platform for further inspection and research on GMO plants. Copyright © 2015 Elsevier B.V. All rights reserved.

Cross-platform comparison of microarray data using order restricted inference

Science.gov (United States)

Klinglmueller, Florian; Tuechler, Thomas; Posch, Martin

2013-01-01

Motivation Titration experiments measuring the gene expression from two different tissues, along with total RNA mixtures of the pure samples, are frequently used for quality evaluation of microarray technologies. Such a design implies that the true mRNA expression of each gene, is either constant or follows a monotonic trend between the mixtures, applying itself to the use of order restricted inference procedures. Exploiting only the postulated monotonicity of titration designs, we propose three statistical analysis methods for the validation of high-throughput genetic data and corresponding preprocessing techniques. Results Our methods allow for inference of accuracy, repeatability and cross-platform agreement, with minimal required assumptions regarding the underlying data generating process. Therefore, they are readily applicable to all sorts of genetic high-throughput data independent of the degree of preprocessing. An application to the EMERALD dataset was used to demonstrate how our methods provide a rich spectrum of easily interpretable quality metrics and allow the comparison of different microarray technologies and normalization methods. The results are on par with previous work, but provide additional new insights that cast doubt on the utility of popular preprocessing techniques, specifically concerning the EMERALD projects dataset. Availability All datasets are available on EBI’s ArrayExpress web site (http://www.ebi.ac.uk/microarray-as/ae/) under accession numbers E-TABM-536, E-TABM-554 and E-TABM-555. Source code implemented in C and R is available at: http://statistics.msi.meduniwien.ac.at/float/cross_platform/. Methods for testing and variance decomposition have been made available in the R-package orQA, which can be downloaded and installed from CRAN http://cran.r-project.org. PMID:21317143

High-throughput sequencing of microRNA transcriptome and expression assay in the sturgeon, Acipenser schrenckii.

Directory of Open Access Journals (Sweden)

Lihong Yuan

Full Text Available Sturgeons are considered as living fossils and have very high evolutionary, economical and conservation values. The multiploidy of sturgeon that has been caused by chromosome duplication may lead to the emergence of new microRNAs (miRNAs involved in the ploidy and physiological processes. In the present study, we performed the first sturgeon miRNAs analysis by RNA-seq high-throughput sequencing combined with expression assay of microarray and real-time PCR, and aimed to discover the sturgeon-specific miRNAs, confirm the expressed pattern of miRNAs and illustrate the potential role of miRNAs-targets on sturgeon biological processes. A total of 103 miRNAs were identified, including 58 miRNAs with strongly detected signals (signal >500 and P≤0.01, which were detected by microarray. Real-time PCR assay supported the expression pattern obtained by microarray. Moreover, co-expression of 21 miRNAs in all five tissues and tissue-specific expression of 16 miRNAs implied the crucial and particular function of them in sturgeon physiological processes. Target gene prediction, especially the enriched functional gene groups (369 GO terms and pathways (37 KEGG regulated by 58 miRNAs (P<0.05, illustrated the interaction of miRNAs and putative mRNAs, and also the potential mechanism involved in these biological processes. Our new findings of sturgeon miRNAs expand the public database of transcriptome information for this species, contribute to our understanding of sturgeon biology, and also provide invaluable data that may be applied in sturgeon breeding.

High-throughput sequencing of microRNA transcriptome and expression assay in the sturgeon, Acipenser schrenckii.

Science.gov (United States)

Yuan, Lihong; Zhang, Xiujuan; Li, Linmiao; Jiang, Haiying; Chen, Jinping

2014-01-01

Sturgeons are considered as living fossils and have very high evolutionary, economical and conservation values. The multiploidy of sturgeon that has been caused by chromosome duplication may lead to the emergence of new microRNAs (miRNAs) involved in the ploidy and physiological processes. In the present study, we performed the first sturgeon miRNAs analysis by RNA-seq high-throughput sequencing combined with expression assay of microarray and real-time PCR, and aimed to discover the sturgeon-specific miRNAs, confirm the expressed pattern of miRNAs and illustrate the potential role of miRNAs-targets on sturgeon biological processes. A total of 103 miRNAs were identified, including 58 miRNAs with strongly detected signals (signal >500 and P≤0.01), which were detected by microarray. Real-time PCR assay supported the expression pattern obtained by microarray. Moreover, co-expression of 21 miRNAs in all five tissues and tissue-specific expression of 16 miRNAs implied the crucial and particular function of them in sturgeon physiological processes. Target gene prediction, especially the enriched functional gene groups (369 GO terms) and pathways (37 KEGG) regulated by 58 miRNAs (P<0.05), illustrated the interaction of miRNAs and putative mRNAs, and also the potential mechanism involved in these biological processes. Our new findings of sturgeon miRNAs expand the public database of transcriptome information for this species, contribute to our understanding of sturgeon biology, and also provide invaluable data that may be applied in sturgeon breeding.

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

Science.gov (United States)

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

2017-06-01

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

A high-throughput multiplex method adapted for GMO detection.

Science.gov (United States)

Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

2008-12-24

A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

A Java-based tool for the design of classification microarrays.

Science.gov (United States)

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for

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

Science.gov (United States)

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.

New high-throughput material-exploration system based on combinatorial chemistry and electrostatic atomization

International Nuclear Information System (INIS)

Fujimoto, K.; Takahashi, H.; Ito, S.; Inoue, S.; Watanabe, M.

2006-01-01

As a tool to facilitate future material explorations, our group has developed a new combinatorial system for the high-throughput preparation of compounds made up of more than three components. The system works in two steps: the atomization of a liquid by a high electric field followed by deposition to a grounded substrate. The combinatorial system based on this method has plural syringe pumps. The each starting materials are fed through the syringe pumps into a manifold, thoroughly mixed as they pass through the manifold, and atomized from the tip of a stainless steel nozzle onto a grounded substrate

A Fisheye Viewer for microarray-based gene expression data.

Science.gov (United States)

Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

2006-10-13

Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

A protein microarray for the rapid screening of patients suspected of infection with various food-borne helminthiases.

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Jia-Xu Chen

Full Text Available BACKGROUND: Food-borne helminthiases (FBHs have become increasingly important due to frequent occurrence and worldwide distribution. There is increasing demand for developing more sensitive, high-throughput techniques for the simultaneous detection of multiple parasitic diseases due to limitations in differential clinical diagnosis of FBHs with similar symptoms. These infections are difficult to diagnose correctly by conventional diagnostic approaches including serological approaches. METHODOLOGY/PRINCIPAL FINDINGS: In this study, antigens obtained from 5 parasite species, namely Cysticercus cellulosae, Angiostrongylus cantonensis, Paragonimus westermani, Trichinella spiralis and Spirometra sp., were semi-purified after immunoblotting. Sera from 365 human cases of helminthiasis and 80 healthy individuals were assayed with semi-purified antigens by both a protein microarray and the enzyme-linked immunosorbent assay (ELISA. The sensitivity, specificity and simplicity of each test for the end-user were evaluated. The specificity of the tests ranged from 97.0% (95% confidence interval (CI: 95.3-98.7% to 100.0% (95% CI: 100.0% in the protein microarray and from 97.7% (95% CI: 96.2-99.2% to 100.0% (95% CI: 100.0% in ELISA. The sensitivity varied from 85.7% (95% CI: 75.1-96.3% to 92.1% (95% CI: 83.5-100.0% in the protein microarray, while the corresponding values for ELISA were 82.0% (95% CI: 71.4-92.6% to 92.1% (95% CI: 83.5-100.0%. Furthermore, the Youden index spanned from 0.83 to 0.92 in the protein microarray and from 0.80 to 0.92 in ELISA. For each parasite, the Youden index from the protein microarray was often slightly higher than the one from ELISA even though the same antigen was used. CONCLUSIONS/SIGNIFICANCE: The protein microarray platform is a convenient, versatile, high-throughput method that can easily be adapted to massive FBH screening.

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

DEFF Research Database (Denmark)

Sastry, Anand; Monk, Jonathan M.; Tegel, Hanna

2017-01-01

and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide...... the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. Availability and implementation: We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template...

Identification of adiponectin receptor agonist utilizing a fluorescence polarization based high throughput assay.

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Yiyi Sun

Full Text Available Adiponectin, the adipose-derived hormone, plays an important role in the suppression of metabolic disorders that can result in type 2 diabetes, obesity, and atherosclerosis. It has been shown that up-regulation of adiponectin or adiponectin receptor has a number of therapeutic benefits. Given that it is hard to convert the full size adiponectin protein into a viable drug, adiponectin receptor agonists could be designed or identified using high-throughput screening. Here, we report on the development of a two-step screening process to identify adiponectin agonists. First step, we developed a high throughput screening assay based on fluorescence polarization to identify adiponectin ligands. The fluorescence polarization assay reported here could be adapted to screening against larger small molecular compound libraries. A natural product library containing 10,000 compounds was screened and 9 hits were selected for validation. These compounds have been taken for the second-step in vitro tests to confirm their agonistic activity. The most active adiponectin receptor 1 agonists are matairesinol, arctiin, (--arctigenin and gramine. The most active adiponectin receptor 2 agonists are parthenolide, taxifoliol, deoxyschizandrin, and syringin. These compounds may be useful drug candidates for hypoadiponectin related diseases.

DNA microarray technique for detecting food-borne pathogens

Directory of Open Access Journals (Sweden)

Xing GAO

2012-08-01

Full Text Available Objective To study the application of DNA microarray technique for screening and identifying multiple food-borne pathogens. Methods The oligonucleotide probes were designed by Clustal X and Oligo 6.0 at the conserved regions of specific genes of multiple food-borne pathogens, and then were validated by bioinformatic analyses. The 5' end of each probe was modified by amino-group and 10 Poly-T, and the optimized probes were synthesized and spotted on aldehyde-coated slides. The bacteria DNA template incubated with Klenow enzyme was amplified by arbitrarily primed PCR, and PCR products incorporated into Aminoallyl-dUTP were coupled with fluorescent dye. After hybridization of the purified PCR products with DNA microarray, the hybridization image and fluorescence intensity analysis was acquired by ScanArray and GenePix Pro 5.1 software. A series of detection conditions such as arbitrarily primed PCR and microarray hybridization were optimized. The specificity of this approach was evaluated by 16 different bacteria DNA, and the sensitivity and reproducibility were verified by 4 food-borne pathogens DNA. The samples of multiple bacteria DNA and simulated water samples of Shigella dysenteriae were detected. Results Nine different food-borne bacteria were successfully discriminated under the same condition. The sensitivity of genomic DNA was 102 －103pg/ μl, and the coefficient of variation (CV of the reproducibility of assay was less than 15%. The corresponding specific hybridization maps of the multiple bacteria DNA samples were obtained, and the detection limit of simulated water sample of Shigella dysenteriae was 3.54×105cfu/ml. Conclusions The DNA microarray detection system based on arbitrarily primed PCR can be employed for effective detection of multiple food-borne pathogens, and this assay may offer a new method for high-throughput platform for detecting bacteria.

High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data.

Science.gov (United States)

Bhargava, Rohit; Fernandez, Daniel C; Hewitt, Stephen M; Levin, Ira W

2006-07-01

Vibrational spectroscopy allows a visualization of tissue constituents based on intrinsic chemical composition and provides a potential route to obtaining diagnostic markers of diseases. Characterizations utilizing infrared vibrational spectroscopy, in particular, are conventionally low throughput in data acquisition, generally lacking in spatial resolution with the resulting data requiring intensive numerical computations to extract information. These factors impair the ability of infrared spectroscopic measurements to represent accurately the spatial heterogeneity in tissue, to incorporate robustly the diversity introduced by patient cohorts or preparative artifacts and to validate developed protocols in large population studies. In this manuscript, we demonstrate a combination of Fourier transform infrared (FTIR) spectroscopic imaging, tissue microarrays (TMAs) and fast numerical analysis as a paradigm for the rapid analysis, development and validation of high throughput spectroscopic characterization protocols. We provide an extended description of the data treatment algorithm and a discussion of various factors that may influence decision-making using this approach. Finally, a number of prostate tissue biopsies, arranged in an array modality, are employed to examine the efficacy of this approach in histologic recognition of epithelial cell polarization in patients displaying a variety of normal, malignant and hyperplastic conditions. An index of epithelial cell polarization, derived from a combined spectral and morphological analysis, is determined to be a potentially useful diagnostic marker.

A Java-based tool for the design of classification microarrays

Directory of Open Access Journals (Sweden)

Broschat Shira L

2008-08-01

Full Text Available Abstract Background Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. Results The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. Conclusion In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays–and mixed-plasmid microarrays in particular–it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm, several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text, and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff. Weights

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

Science.gov (United States)

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

2015-01-01

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

High-Throughput Scoring of Seed Germination.

Science.gov (United States)

Ligterink, Wilco; Hilhorst, Henk W M

2017-01-01

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very informative as it lacks information about start, rate, and uniformity of germination, which are highly indicative of such traits as dormancy, stress tolerance, and seed longevity. The calculation of cumulative germination curves requires information about germination percentage at various time points. We developed the GERMINATOR package: a simple, highly cost-efficient, and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The GERMINATOR package contains three modules: (I) design of experimental setup with various options to replicate and randomize samples; (II) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (III) curve fitting of cumulative germination data and the extraction, recap, and visualization of the various germination parameters. GERMINATOR is a freely available package that allows the monitoring and analysis of several thousands of germination tests, several times a day by a single person.

Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays

Science.gov (United States)

Popescu, Sorina C.; Popescu, George V.; Bachan, Shawn; Zhang, Zimei; Seay, Montrell; Gerstein, Mark; Snyder, Michael; Dinesh-Kumar, S. P.

2007-01-01

Calmodulins (CaMs) are the most ubiquitous calcium sensors in eukaryotes. A number of CaM-binding proteins have been identified through classical methods, and many proteins have been predicted to bind CaMs based on their structural homology with known targets. However, multicellular organisms typically contain many CaM-like (CML) proteins, and a global identification of their targets and specificity of interaction is lacking. In an effort to develop a platform for large-scale analysis of proteins in plants we have developed a protein microarray and used it to study the global analysis of CaM/CML interactions. An Arabidopsis thaliana expression collection containing 1,133 ORFs was generated and used to produce proteins with an optimized medium-throughput plant-based expression system. Protein microarrays were prepared and screened with several CaMs/CMLs. A large number of previously known and novel CaM/CML targets were identified, including transcription factors, receptor and intracellular protein kinases, F-box proteins, RNA-binding proteins, and proteins of unknown function. Multiple CaM/CML proteins bound many binding partners, but the majority of targets were specific to one or a few CaMs/CMLs indicating that different CaM family members function through different targets. Based on our analyses, the emergent CaM/CML interactome is more extensive than previously predicted. Our results suggest that calcium functions through distinct CaM/CML proteins to regulate a wide range of targets and cellular activities. PMID:17360592

Image microarrays derived from tissue microarrays (IMA-TMA: New resource for computer-aided diagnostic algorithm development

Directory of Open Access Journals (Sweden)

Jennifer A Hipp

2012-01-01

bodies, was subsequently carried out on the differing TMA-IMAs, with attainment of excellent discriminant classification between the two diagnostic classes. Conclusion: The TMA-IMA construct enables and accelerates high-throughput multicase, multifield based image feature discovery and classification, thus simplifying the development, validation, and comparison of CAD algorithms in settings where the heterogeneity of diagnostic feature morphologic is a significant factor.

Dynamic, electronically switchable surfaces for membrane protein microarrays.

Science.gov (United States)

Tang, C S; Dusseiller, M; Makohliso, S; Heuschkel, M; Sharma, S; Keller, B; Vörös, J

2006-02-01

Microarray technology is a powerful tool that provides a high throughput of bioanalytical information within a single experiment. These miniaturized and parallelized binding assays are highly sensitive and have found widespread popularity especially during the genomic era. However, as drug diagnostics studies are often targeted at membrane proteins, the current arraying technologies are ill-equipped to handle the fragile nature of the protein molecules. In addition, to understand the complex structure and functions of proteins, different strategies to immobilize the probe molecules selectively onto a platform for protein microarray are required. We propose a novel approach to create a (membrane) protein microarray by using an indium tin oxide (ITO) microelectrode array with an electronic multiplexing capability. A polycationic, protein- and vesicle-resistant copolymer, poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG), is exposed to and adsorbed uniformly onto the microelectrode array, as a passivating adlayer. An electronic stimulation is then applied onto the individual ITO microelectrodes resulting in the localized release of the polymer thus revealing a bare ITO surface. Different polymer and biological moieties are specifically immobilized onto the activated ITO microelectrodes while the other regions remain protein-resistant as they are unaffected by the induced electrical potential. The desorption process of the PLL-g-PEG is observed to be highly selective, rapid, and reversible without compromising on the integrity and performance of the conductive ITO microelectrodes. As such, we have successfully created a stable and heterogeneous microarray of biomolecules by using selective electronic addressing on ITO microelectrodes. Both pharmaceutical diagnostics and biomedical technology are expected to benefit directly from this unique method.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

BASE - 2nd generation software for microarray data management and analysis

Directory of Open Access Journals (Sweden)

Nordborg Nicklas

2009-10-01

Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

BASE--2nd generation software for microarray data management and analysis.

Science.gov (United States)

Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

2009-10-12

Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

The Plasmodium falciparum Sexual Development Transcriptome: A Microarray Analysis using Ontology-Based Pattern Identification

National Research Council Canada - National Science Library

Young, Jason A; Fivelman, Quinton L; Blair, Peter L; de la Vega, Patricia; Le Roch, Karine G; Zhou, Yingyao; Carucci, Daniel J; Baker, David A; Winzeler, Elizabeth A

2005-01-01

... a full-genome high-density oligonucleotide microarray. The interpretation of this transcriptional data was aided by applying a novel knowledge-based data-mining algorithm termed ontology-based pattern identification (OPI...

A fisheye viewer for microarray-based gene expression data

Directory of Open Access Journals (Sweden)

Munson Ethan V

2006-10-01

Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

Science.gov (United States)

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

High-throughput electrical characterization for robust overlay lithography control

Science.gov (United States)

Devender, Devender; Shen, Xumin; Duggan, Mark; Singh, Sunil; Rullan, Jonathan; Choo, Jae; Mehta, Sohan; Tang, Teck Jung; Reidy, Sean; Holt, Jonathan; Kim, Hyung Woo; Fox, Robert; Sohn, D. K.

2017-03-01

Realizing sensitive, high throughput and robust overlay measurement is a challenge in current 14nm and advanced upcoming nodes with transition to 300mm and upcoming 450mm semiconductor manufacturing, where slight deviation in overlay has significant impact on reliability and yield1). Exponentially increasing number of critical masks in multi-patterning lithoetch, litho-etch (LELE) and subsequent LELELE semiconductor processes require even tighter overlay specification2). Here, we discuss limitations of current image- and diffraction- based overlay measurement techniques to meet these stringent processing requirements due to sensitivity, throughput and low contrast3). We demonstrate a new electrical measurement based technique where resistance is measured for a macro with intentional misalignment between two layers. Overlay is quantified by a parabolic fitting model to resistance where minima and inflection points are extracted to characterize overlay control and process window, respectively. Analyses using transmission electron microscopy show good correlation between actual overlay performance and overlay obtained from fitting. Additionally, excellent correlation of overlay from electrical measurements to existing image- and diffraction- based techniques is found. We also discuss challenges of integrating electrical measurement based approach in semiconductor manufacturing from Back End of Line (BEOL) perspective. Our findings open up a new pathway for accessing simultaneous overlay as well as process window and margins from a robust, high throughput and electrical measurement approach.

High Throughput Transcriptomics @ USEPA (Toxicology ...

Science.gov (United States)

The ideal chemical testing approach will provide complete coverage of all relevant toxicological responses. It should be sensitive and specific It should identify the mechanism/mode-of-action (with dose-dependence). It should identify responses relevant to the species of interest. Responses should ideally be translated into tissue-, organ-, and organism-level effects. It must be economical and scalable. Using a High Throughput Transcriptomics platform within US EPA provides broader coverage of biological activity space and toxicological MOAs and helps fill the toxicological data gap. Slide presentation at the 2016 ToxForum on using High Throughput Transcriptomics at US EPA for broader coverage biological activity space and toxicological MOAs.

The use of microarrays in microbial ecology

Energy Technology Data Exchange (ETDEWEB)

Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

2009-09-15

Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

Towards the development of lipid multilayer microarrays for dose dependent in vitro delivery and screening

Science.gov (United States)

Kusi-Appiah, Aubrey Emmanuel

Screening for effects of small molecules on cells grown in culture is a well-established method for drug discovery and testing, and faster throughput at lower cost is needed especially for lipophilic materials. Small-molecule arrays present a promising approach. However, it has been a challenge to use them to obtain quantitative surface based dose-response curves in vitro, especially for lipophilic compounds. This thesis first introduces a simple novel method of surface-mediated delivery of drugs to cells from a microarray of phospholipid multilayers (layers thicker than a bilayer) encapsulating small molecules. The capability of controlling the dosage of the lipophilic molecules delivered to cells using the lipid multilayer microarray assay is further demonstrated using the nanointaglio printing method. This control enabled the variation of the volumes of surface supported lipid micro- and nanostructure arrays fabricated with nanointaglio. The volumes of the lipophilic drug-containing nanostructures were determined using a fluorescence microscope calibrated by atomic-force microscopy. The surface supported lipid volume information was used to obtain EC-50 values for the response of HeLa cells to treatment with three FDA-approved lipophilic anticancer drugs, docetaxel, imiquimod and triethylenemelamine, which were found to be significantly different from neat lipid controls. Features with sub-cellular lateral dimensions were found to be necessary to obtain normal cell adhesion with HeLa cells. Comparison of the microarray data to dose-response curves for the same drugs delivered liposomally from solution revealed quantitative differences in the efficacy values, which may be explained in terms of cell-adhesion playing a more important role in the surface-based assay. Finally, solution encapsulation was done for a library of hydrophilic silicon nanocrystals in order to set a solution standard for comparison with future surface supported delivery of the library. The

Application of ToxCast High-Throughput Screening and ...

Science.gov (United States)

Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenesis Distruptors Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenssis Distruptors

Preliminary High-Throughput Metagenome Assembly

Energy Technology Data Exchange (ETDEWEB)

Dusheyko, Serge; Furman, Craig; Pangilinan, Jasmyn; Shapiro, Harris; Tu, Hank

2007-03-26

Metagenome data sets present a qualitatively different assembly problem than traditional single-organism whole-genome shotgun (WGS) assembly. The unique aspects of such projects include the presence of a potentially large number of distinct organisms and their representation in the data set at widely different fractions. In addition, multiple closely related strains could be present, which would be difficult to assemble separately. Failure to take these issues into account can result in poor assemblies that either jumble together different strains or which fail to yield useful results. The DOE Joint Genome Institute has sequenced a number of metagenomic projects and plans to considerably increase this number in the coming year. As a result, the JGI has a need for high-throughput tools and techniques for handling metagenome projects. We present the techniques developed to handle metagenome assemblies in a high-throughput environment. This includes a streamlined assembly wrapper, based on the JGI?s in-house WGS assembler, Jazz. It also includes the selection of sensible defaults targeted for metagenome data sets, as well as quality control automation for cleaning up the raw results. While analysis is ongoing, we will discuss preliminary assessments of the quality of the assembly results (http://fames.jgi-psf.org).

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

Science.gov (United States)

Tchorowski, Nicole; Murawski, Robert

2014-01-01

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

Microarray Glycan Profiling Reveals Algal Fucoidan Epitopes in Diverse Marine Metazoans

Directory of Open Access Journals (Sweden)

Armando A. Salmeán

2017-09-01

Full Text Available Despite the biological importance and pharmacological potential of glycans from marine organisms, there are many unanswered questions regarding their distribution, function, and evolution. Here we describe microarray-based glycan profiling of a diverse selection of marine animals using antibodies raised against fucoidan isolated from a brown alga. We demonstrate the presence of two fucoidan epitopes in six animals belonging to three phyla including Porifera, Molusca, and Chordata. We studied the spatial distribution of these epitopes in Cliona celata (“boring sponge” and identified their restricted localization on the surface of internal chambers. Our results show the potential of high-throughput screening and probes commonly used in plant and algal cell wall biology to study the diversity and distribution of glycan structures in metazoans.

Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

Directory of Open Access Journals (Sweden)

Eils Roland

2005-11-01

Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

Evaluation of gene importance in microarray data based upon probability of selection

Directory of Open Access Journals (Sweden)

Fu Li M

2005-03-01

Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

DNA microarray-based PCR ribotyping of Clostridium difficile.

Science.gov (United States)

Schneeberg, Alexander; Ehricht, Ralf; Slickers, Peter; Baier, Vico; Neubauer, Heinrich; Zimmermann, Stefan; Rabold, Denise; Lübke-Becker, Antina; Seyboldt, Christian

2015-02-01

This study presents a DNA microarray-based assay for fast and simple PCR ribotyping of Clostridium difficile strains. Hybridization probes were designed to query the modularly structured intergenic spacer region (ISR), which is also the template for conventional and PCR ribotyping with subsequent capillary gel electrophoresis (seq-PCR) ribotyping. The probes were derived from sequences available in GenBank as well as from theoretical ISR module combinations. A database of reference hybridization patterns was set up from a collection of 142 well-characterized C. difficile isolates representing 48 seq-PCR ribotypes. The reference hybridization patterns calculated by the arithmetic mean were compared using a similarity matrix analysis. The 48 investigated seq-PCR ribotypes revealed 27 array profiles that were clearly distinguishable. The most frequent human-pathogenic ribotypes 001, 014/020, 027, and 078/126 were discriminated by the microarray. C. difficile strains related to 078/126 (033, 045/FLI01, 078, 126, 126/FLI01, 413, 413/FLI01, 598, 620, 652, and 660) and 014/020 (014, 020, and 449) showed similar hybridization patterns, confirming their genetic relatedness, which was previously reported. A panel of 50 C. difficile field isolates was tested by seq-PCR ribotyping and the DNA microarray-based assay in parallel. Taking into account that the current version of the microarray does not discriminate some closely related seq-PCR ribotypes, all isolates were typed correctly. Moreover, seq-PCR ribotypes without reference profiles available in the database (ribotype 009 and 5 new types) were correctly recognized as new ribotypes, confirming the performance and expansion potential of the microarray. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Design of an Enterobacteriaceae Pan-genome Microarray Chip

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Lukjancenko, Oksana; Ussery, David

2010-01-01

-density microarray chip has been designed, using 116 Enterobacteriaceae genome sequences, taking into account the enteric pan-genome. Probes for the microarray were checked in silico and performance of the chip, based on experimental strains from four different genera, demonstrate a relatively high ability...... to distinguish those strains on genus, species, and pathotype/serovar levels. Additionally, the microarray performed well when investigating which genes were found in a given strain of interest. The Enterobacteriaceae pan-genome microarray, based on 116 genomes, provides a valuable tool for determination...

Comparison of Fluorescence In Situ Hybridization and Chromogenic In Situ Hybridization for Low and High Throughput HER2 Genetic Testing

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Poulsen, Tim S.; Espersen, Maiken L. M.; Kofoed, Vibeke; Dabetic, Tanja; Høgdall, Estrid; Balslev, Eva

2013-01-01

The purpose was to evaluate and compare 5 different HER2 genetic assays with different characteristics that could affect the performance to analyze the human epidermal growth factor 2 (HER2) gene copy number under low and high throughput conditions. The study included 108 tissue samples from breast cancer patients with HER2 immunohistochemistry (IHC) results scored as 0/1+, 2+, and 3+. HER2 genetic status was analysed using chromogenic in situ hybridization (CISH) and fluorescence in situ hybridization (FISH). Scoring results were documented through digital image analysis. The cancer region of interest was identified from a serial H&E stained slide following tissue cores were transferred to a tissue microarrays (TMA). When using TMA in a routine flow, all patients will be tested for HER2 status with IHC followed by CISH or FISH, thereby providing individual HER2 results. In conclusion, our results show that the differences between the HER2 genetic assays do not have an effect on the analytic performance and the CISH technology is superior to high throughput HER2 genetic testing due to scanning speed, while the IQ-FISH may still be a choice for fast low throughput HER2 genetic testing. PMID:24383005

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

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Sahil Talwar

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

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

International Nuclear Information System (INIS)

Hodzic, Jasmina; Dingjan, Ilse; Maas, Mariëlle JP; Meulen-Muileman, Ida H van der; Menezes, Renee X de; Heukelom, Stan; Verheij, Marcel; Gerritsen, Winald R; Geldof, Albert A; Triest, Baukelien van; Beusechem, Victor W van

2015-01-01

Radiotherapy is one of the mainstays in the treatment for cancer, but its success can be limited due to inherent or acquired resistance. Mechanisms underlying radioresistance in various cancers are poorly understood and available radiosensitizers have shown only modest clinical benefit. There is thus a need to identify new targets and drugs for more effective sensitization of cancer cells to irradiation. Compound and RNA interference high-throughput screening technologies allow comprehensive enterprises to identify new agents and targets for radiosensitization. However, the gold standard assay to investigate radiosensitivity of cancer cells in vitro, the colony formation assay (CFA), is unsuitable for high-throughput screening. We developed a new high-throughput screening method for determining radiation susceptibility. Fast and uniform irradiation of batches up to 30 microplates was achieved using a Perspex container and a clinically employed linear accelerator. The readout was done by automated counting of fluorescently stained nuclei using the Acumen eX3 laser scanning cytometer. Assay performance was compared to that of the CFA and the CellTiter-Blue homogeneous uniform-well cell viability assay. The assay was validated in a whole-genome siRNA library screening setting using PC-3 prostate cancer cells. On 4 different cancer cell lines, the automated cell counting assay produced radiation dose response curves that followed a linear-quadratic equation and that exhibited a better correlation to the results of the CFA than did the cell viability assay. Moreover, the cell counting assay could be used to detect radiosensitization by silencing DNA-PKcs or by adding caffeine. In a high-throughput screening setting, using 4 Gy irradiated and control PC-3 cells, the effects of DNA-PKcs siRNA and non-targeting control siRNA could be clearly discriminated. We developed a simple assay for radiation susceptibility that can be used for high-throughput screening. This will aid

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

DEFF Research Database (Denmark)

Schwämmle, Veit; Vaudel, Marc

2017-01-01

Cell signaling and functions heavily rely on post-translational modifications (PTMs) of proteins. Their high-throughput characterization is thus of utmost interest for multiple biological and medical investigations. In combination with efficient enrichment methods, peptide mass spectrometry analy...

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

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Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

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

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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

A high-throughput screening strategy for nitrile-hydrolyzing enzymes based on ferric hydroxamate spectrophotometry.

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He, Yu-Cai; Ma, Cui-Luan; Xu, Jian-He; Zhou, Li

2011-02-01

Nitrile-hydrolyzing enzymes (nitrilase or nitrile hydratase/amidase) have been widely used in the pharmaceutical industry for the production of carboxylic acids and their derivatives, and it is important to build a method for screening for nitrile-hydrolyzing enzymes. In this paper, a simple, rapid, and high-throughput screening method based on the ferric hydroxamate spectrophotometry has been proposed. To validate the accuracy of this screening strategy, the nitrilases from Rhodococcus erythropolis CGMCC 1.2362 and Alcaligenes sp. ECU0401 were used for evaluating the method. As a result, the accuracy for assaying aliphatic and aromatic carboxylic acids was as high as the HPLC-based method. Therefore, the method may be potentially used in the selection of microorganisms or engineered proteins with nitrile-hydrolyzing enzymes.

Seeded Bayesian Networks: Constructing genetic networks from microarray data

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Quackenbush John

2008-07-01

Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

Centroid based clustering of high throughput sequencing reads based on n-mer counts.

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Solovyov, Alexander; Lipkin, W Ian

2013-09-08

Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read.

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

Energy Technology Data Exchange (ETDEWEB)

Luo, Wei; Shabbir, Faizan; Gong, Chao; Gulec, Cagatay; Pigeon, Jeremy; Shaw, Jessica; Greenbaum, Alon; Tochitsky, Sergei; Joshi, Chandrashekhar [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Ozcan, Aydogan, E-mail: ozcan@ucla.edu [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Bioengineering Department, University of California, Los Angeles, California 90095 (United States); California NanoSystems Institute (CNSI), University of California, Los Angeles, California 90095 (United States)

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 processing 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.

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

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Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy

Spectrophotometric Enzyme Assays for High-Throughput Screening

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Jean-Louis Reymond

2004-01-01

Full Text Available This paper reviews high-throughput screening enzyme assays developed in our laboratory over the last ten years. These enzyme assays were initially developed for the purpose of discovering catalytic antibodies by screening cell culture supernatants, but have proved generally useful for testing enzyme activities. Examples include TLC-based screening using acridone-labeled substrates, fluorogenic assays based on the β-elimination of umbelliferone or nitrophenol, and indirect assays such as the back-titration method with adrenaline and the copper-calcein fluorescence assay for aminoacids.

Improved microarray-based decision support with graph encoded interactome data.

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Anneleen Daemen

Full Text Available In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG, protein-protein interactions (OPHID and miRNA-gene targeting (microRNA.org outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method.

Direct calibration of PICKY-designed microarrays

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Ronald Pamela C

2009-10-01

Full Text Available Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

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

DEFF Research Database (Denmark)

Ståhlman, Marcus; Ejsing, Christer S.; Tarasov, Kirill

2009-01-01

Technological advances in mass spectrometry and meticulous method development have produced several shotgun lipidomic approaches capable of characterizing lipid species by direct analysis of total lipid extracts. Shotgun lipidomics by hybrid quadrupole time-of-flight mass spectrometry allows...... the absolute quantification of hundreds of molecular glycerophospholipid species, glycerolipid species, sphingolipid species and sterol lipids. Future applications in clinical cohort studies demand detailed lipid molecule information and the application of high-throughput lipidomics platforms. In this review...... we describe a novel high-throughput shotgun lipidomic platform based on 96-well robot-assisted lipid extraction, automated sample infusion by mircofluidic-based nanoelectrospray ionization, and quantitative multiple precursor ion scanning analysis on a quadrupole time-of-flight mass spectrometer...

High throughput integrated thermal characterization with non-contact optical calorimetry

Science.gov (United States)

Hou, Sichao; Huo, Ruiqing; Su, Ming

2017-10-01

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

High-throughput identification of potential minor histocompatibility antigens by MHC tetramer-based screening

DEFF Research Database (Denmark)

Hombrink, Pleun; Hadrup, Sine R; Bakker, Arne

2011-01-01

the technical feasibility of high-throughput analysis of antigen-specific T-cell responses in small patient samples. However, the high-sensitivity of this approach requires the use of potential epitope sets that are not solely based on MHC binding, to prevent the frequent detection of T-cell responses that lack......T-cell recognition of minor histocompatibility antigens (MiHA) plays an important role in the graft-versus-tumor (GVT) effect of allogeneic stem cell transplantation (allo-SCT). However, the number of MiHA identified to date remains limited, making clinical application of MiHA reactive T......MHC-tetramer-based enrichment and multi-color flow cytometry. Using this approach, 71 peptide-reactive T-cell populations were generated. The isolation of a T-cell line specifically recognizing target cells expressing the MAP4K1(IMA) antigen demonstrates that identification of MiHA through this approach is in principle...

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

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Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

2017-08-15

The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Vision-based Nano Robotic System for High-throughput Non-embedded Cell Cutting.

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Shang, Wanfeng; Lu, Haojian; Wan, Wenfeng; Fukuda, Toshio; Shen, Yajing

2016-03-04

Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded cell cutting with this system. First, the nano robotic system is developed and integrated with a nanoknife inside an environmental scanning electron microscopy (ESEM). Then, the positions of the nanoknife and the single cell are recognized, and the distance between them is calculated dynamically based on image processing. To guarantee the positioning accuracy and the working efficiency, we propose a distance-regulated speed adapting strategy, in which the moving speed is adjusted intelligently based on the distance between the nanoknife and the target cell. The results indicate that the automatic non-embedded cutting is able to be achieved within 1-2 mins with low invasion benefiting from the high precise nanorobot system and the sharp edge of nanoknife. This research paves a way for the high-throughput cell cutting at cell's natural condition, which is expected to make significant impact on the biology studies, especially for the in-situ analysis at cellular and subcellular scale, such as cell interaction investigation, neural signal transduction and low invasive cell surgery.

Vision-based Nano Robotic System for High-throughput Non-embedded Cell Cutting

Science.gov (United States)

Shang, Wanfeng; Lu, Haojian; Wan, Wenfeng; Fukuda, Toshio; Shen, Yajing

2016-03-01

Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded cell cutting with this system. First, the nano robotic system is developed and integrated with a nanoknife inside an environmental scanning electron microscopy (ESEM). Then, the positions of the nanoknife and the single cell are recognized, and the distance between them is calculated dynamically based on image processing. To guarantee the positioning accuracy and the working efficiency, we propose a distance-regulated speed adapting strategy, in which the moving speed is adjusted intelligently based on the distance between the nanoknife and the target cell. The results indicate that the automatic non-embedded cutting is able to be achieved within 1-2 mins with low invasion benefiting from the high precise nanorobot system and the sharp edge of nanoknife. This research paves a way for the high-throughput cell cutting at cell’s natural condition, which is expected to make significant impact on the biology studies, especially for the in-situ analysis at cellular and subcellular scale, such as cell interaction investigation, neural signal transduction and low invasive cell surgery.

High-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays

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Crenshaw Andrew

2009-01-01

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

Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

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Arpita Nagpal

2017-01-01

Full Text Available Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm based on the tabu search as local search procedures to a Greedy Randomized Adaptive Search Procedure (GRASP for high dimensional microarray data sets. The proposed Tabu based Greedy Randomized Adaptive Search Procedure algorithm is named as TGRASP. In TGRASP, a new parameter has been introduced named as Tabu Tenure and the existing parameters, NumIter and size have been modified. We observed that different parameter settings affect the quality of the optimum. The second proposed algorithm known as FFGRASP (Firefly Greedy Randomized Adaptive Search Procedure uses a firefly optimization algorithm in the local search optimzation phase of the greedy randomized adaptive search procedure (GRASP. Firefly algorithm is one of the powerful algorithms for optimization of multimodal applications. Experimental results show that the proposed TGRASP and FFGRASP algorithms are much better than existing algorithm with respect to three performance parameters viz. accuracy, run time, number of a selected subset of features. We have also compared both the approaches with a unified metric (Extended Adjusted Ratio of Ratios which has shown that TGRASP approach outperforms existing approach for six out of nine cancer microarray datasets and FFGRASP performs better on seven out of nine datasets.

High-throughput screening to enhance oncolytic virus immunotherapy

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Allan KJ

2016-04-01

Full Text Available KJ Allan,1,2 David F Stojdl,1–3 SL Swift1 1Children’s Hospital of Eastern Ontario (CHEO Research Institute, 2Department of Biology, Microbiology and Immunology, 3Department of Pediatrics, University of Ottawa, Ottawa, ON, Canada Abstract: High-throughput screens can rapidly scan and capture large amounts of information across multiple biological parameters. Although many screens have been designed to uncover potential new therapeutic targets capable of crippling viruses that cause disease, there have been relatively few directed at improving the efficacy of viruses that are used to treat disease. Oncolytic viruses (OVs are biotherapeutic agents with an inherent specificity for treating malignant disease. Certain OV platforms – including those based on herpes simplex virus, reovirus, and vaccinia virus – have shown success against solid tumors in advanced clinical trials. Yet, many of these OVs have only undergone minimal engineering to solidify tumor specificity, with few extra modifications to manipulate additional factors. Several aspects of the interaction between an OV and a tumor-bearing host have clear value as targets to improve therapeutic outcomes. At the virus level, these include delivery to the tumor, infectivity, productivity, oncolysis, bystander killing, spread, and persistence. At the host level, these include engaging the immune system and manipulating the tumor microenvironment. Here, we review the chemical- and genome-based high-throughput screens that have been performed to manipulate such parameters during OV infection and analyze their impact on therapeutic efficacy. We further explore emerging themes that represent key areas of focus for future research. Keywords: oncolytic, virus, screen, high-throughput, cancer, chemical, genomic, immunotherapy

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

Science.gov (United States)

Yang, Xu; Jiao, Rui; Yang, Lin; Wu, Li-Ping; Li, Ying-Rui; Wang, Jun

2011-08-01

In recent years, new-generation high-throughput technologies, including next-generation sequencing technology and mass spectrometry method, have been widely applied in solving biological problems, especially in human diseases field. This data driven, large-scale and industrialized research model enables the omnidirectional and multi-level study of human diseases from the perspectives of genomics, transcriptomics and proteomics levels, etc. In this paper, the latest development of the high-throughput technologies that applied in DNA, RNA, epigenomics, metagenomics including proteomics and some applications in translational medicine are reviewed. At genomics level, exome sequencing has been the hot spot of the recent research. However, the predominance of whole genome resequencing in detecting large structural variants within the whole genome level is coming to stand out as the drop of sequencing cost, which also makes it possible for personalized genome based medicine application. At trancriptomics level, e.g., small RNA sequencing can be used to detect known and predict unknown miRNA. Those small RNA could not only be the biomarkers for disease diagnosis and prognosis, but also show the potential of disease treatment. At proteomics level, e.g., target proteomics can be used to detect the possible disease-related protein or peptides, which can be useful index for clinical staging and typing. Furthermore, the application and development of trans-omics study in disease research are briefly introduced. By applying bioinformatics technologies for integrating multi-omics data, the mechanism, diagnosis and therapy of the disease are likely to be systemically explained and realized, so as to provide powerful tools for disease diagnosis and therapies.

High throughput screening method for assessing heterogeneity of microorganisms

NARCIS (Netherlands)

Ingham, C.J.; Sprenkels, A.J.; van Hylckama Vlieg, J.E.T.; Bomer, Johan G.; de Vos, W.M.; van den Berg, Albert

2006-01-01

The invention relates to the field of microbiology. Provided is a method which is particularly powerful for High Throughput Screening (HTS) purposes. More specific a high throughput method for determining heterogeneity or interactions of microorganisms is provided.

Robust Feature Selection from Microarray Data Based on Cooperative Game Theory and Qualitative Mutual Information

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Atiyeh Mortazavi

2016-01-01

Full Text Available High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.

Low Complexity Approach for High Throughput Belief-Propagation based Decoding of LDPC Codes

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BOT, A.

2013-11-01

Full Text Available The paper proposes a low complexity belief propagation (BP based decoding algorithm for LDPC codes. In spite of the iterative nature of the decoding process, the proposed algorithm provides both reduced complexity and increased BER performances as compared with the classic min-sum (MS algorithm, generally used for hardware implementations. Linear approximations of check-nodes update function are used in order to reduce the complexity of the BP algorithm. Considering this decoding approach, an FPGA based hardware architecture is proposed for implementing the decoding algorithm, aiming to increase the decoder throughput. FPGA technology was chosen for the LDPC decoder implementation, due to its parallel computation and reconfiguration capabilities. The obtained results show improvements regarding decoding throughput and BER performances compared with state-of-the-art approaches.

Reverse Phase Protein Arrays for High-throughput Toxicity Screening

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

High-throughput screening is extensively applied for identification of drug targets and drug discovery and recently it found entry into toxicity testing. Reverse phase protein arrays (RPPAs) are used widespread for quantification of protein markers. We reasoned that RPPAs also can be utilized...... beneficially in automated high-throughput toxicity testing. An advantage of using RPPAs is that, in addition to the baseline toxicity readout, they allow testing of multiple markers of toxicity, such as inflammatory responses, which do not necessarily cumulate in cell death. We used transfection of si......RNAs with known killing effects as a model system to demonstrate that RPPA-based protein quantification can serve as substitute readout of cell viability, hereby reliably reflecting toxicity. In terms of automation, cell exposure, protein harvest, serial dilution and sample reformatting were performed using...

High-throughput bioinformatics with the Cyrille2 pipeline system

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de Groot Joost CW

2008-02-01

Full Text Available Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1 a web based, graphical user interface (GUI that enables a pipeline operator to manage the system; 2 the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3 the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

High-throughput fragment screening by affinity LC-MS.

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Duong-Thi, Minh-Dao; Bergström, Maria; Fex, Tomas; Isaksson, Roland; Ohlson, Sten

2013-02-01

Fragment screening, an emerging approach for hit finding in drug discovery, has recently been proven effective by its first approved drug, vemurafenib, for cancer treatment. Techniques such as nuclear magnetic resonance, surface plasmon resonance, and isothemal titration calorimetry, with their own pros and cons, have been employed for screening fragment libraries. As an alternative approach, screening based on high-performance liquid chromatography separation has been developed. In this work, we present weak affinity LC/MS as a method to screen fragments under high-throughput conditions. Affinity-based capillary columns with immobilized thrombin were used to screen a collection of 590 compounds from a fragment library. The collection was divided into 11 mixtures (each containing 35 to 65 fragments) and screened by MS detection. The primary screening was performed in 3500 fragments per day). Thirty hits were defined, which subsequently entered a secondary screening using an active site-blocked thrombin column for confirmation of specificity. One hit showed selective binding to thrombin with an estimated dissociation constant (K (D)) in the 0.1 mM range. This study shows that affinity LC/MS is characterized by high throughput, ease of operation, and low consumption of target and fragments, and therefore it promises to be a valuable method for fragment screening.

Evaluation of chronic lymphocytic leukemia by BAC-based microarray analysis

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McDaniel Lisa D

2011-02-01

Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.

Applications of ambient mass spectrometry in high-throughput screening.

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Li, Li-Ping; Feng, Bao-Sheng; Yang, Jian-Wang; Chang, Cui-Lan; Bai, Yu; Liu, Hu-Wei

2013-06-07

The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

Improved precision and accuracy for microarrays using updated probe set definitions

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Larsson Ola

2007-02-01

Full Text Available Abstract Background Microarrays enable high throughput detection of transcript expression levels. Different investigators have recently introduced updated probe set definitions to more accurately map probes to our current knowledge of genes and transcripts. Results We demonstrate that updated probe set definitions provide both better precision and accuracy in probe set estimates compared to the original Affymetrix definitions. We show that the improved precision mainly depends on the increased number of probes that are integrated into each probe set, but we also demonstrate an improvement when the same number of probes is used. Conclusion Updated probe set definitions does not only offer expression levels that are more accurately associated to genes and transcripts but also improvements in the estimated transcript expression levels. These results give support for the use of updated probe set definitions for analysis and meta-analysis of microarray data.

Functional characterisation of homomeric ionotropic glutamate receptors GluR1-GluR6 in a fluorescence-based high throughput screening assay

DEFF Research Database (Denmark)

Strange, Mette; Bräuner-Osborne, Hans; Jensen, Anders A.

2006-01-01

We have constructed stable HEK293 cell lines expressing the rat ionotropic glutamate receptor subtypes GluR1(i), GluR2Q(i), GluR3(i), GluR4(i), GluR5Q and GluR6Q and characterised the pharmacological profiles of the six homomeric receptors in a fluorescence-based high throughput screening assay...... assay reported to date. We propose that high throughput screening of compound libraries at the six GluR-HEK293 cell lines could be helpful in the search for structurally and pharmacologically novel ligands acting at the receptors....

High-throughput multiplex HLA-typing by ligase detection reaction (LDR) and universal array (UA) approach.

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Consolandi, Clarissa

2009-01-01

One major goal of genetic research is to understand the role of genetic variation in living systems. In humans, by far the most common type of such variation involves differences in single DNA nucleotides, and is thus termed single nucleotide polymorphism (SNP). The need for improvement in throughput and reliability of traditional techniques makes it necessary to develop new technologies. Thus the past few years have witnessed an extraordinary surge of interest in DNA microarray technology. This new technology offers the first great hope for providing a systematic way to explore the genome. It permits a very rapid analysis of thousands genes for the purpose of gene discovery, sequencing, mapping, expression, and polymorphism detection. We generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. In particular, we set up a universal array approach in combination with a PCR-LDR (polymerase chain reaction-ligation detection reaction) strategy for allele identification in the HLA gene.

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

Science.gov (United States)

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

2012-01-01

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

Quantitative description on structure-property relationships of Li-ion battery materials for high-throughput computations

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Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun

2017-12-01

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.

Screening of Chlamydomonas reinhardtii Populations with Single-Cell Resolution by Using a High-Throughput Microscale Sample Preparation for Matrix-Assisted Laser Desorption Ionization Mass Spectrometry.

Science.gov (United States)

Krismer, Jasmin; Sobek, Jens; Steinhoff, Robert F; Fagerer, Stephan R; Pabst, Martin; Zenobi, Renato

2015-08-15

The consequences of cellular heterogeneity, such as biocide persistence, can only be tackled by studying each individual in a cell population. Fluorescent tags provide tools for the high-throughput analysis of genomes, RNA transcripts, or proteins on the single-cell level. However, the analysis of lower-molecular-weight compounds that elude tagging is still a great challenge. Here, we describe a novel high-throughput microscale sample preparation technique for single cells that allows a mass spectrum to be obtained for each individual cell within a microbial population. The approach presented includes spotting Chlamydomonas reinhardtii cells, using a noncontact microarrayer, onto a specialized slide and controlled lysis of cells separated on the slide. Throughout the sample preparation, analytes were traced and individual steps optimized using autofluorescence detection of chlorophyll. The lysates of isolated cells are subjected to a direct, label-free analysis using matrix-assisted laser desorption ionization mass spectrometry. Thus, we were able to differentiate individual cells of two Chlamydomonas reinhardtii strains based on single-cell mass spectra. Furthermore, we showed that only population profiles with real single-cell resolution render a nondistorted picture of the phenotypes contained in a population. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

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Daniel Vasiliu

Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

Development of a Rapid Fluorescence-Based High-Throughput Screening Assay to Identify Novel Kynurenine 3-Monooxygenase Inhibitor Scaffolds.

Science.gov (United States)

Jacobs, K R; Guillemin, G J; Lovejoy, D B

2018-02-01

Kynurenine 3-monooxygenase (KMO) is a well-validated therapeutic target for the treatment of neurodegenerative diseases, including Alzheimer's disease (AD) and Huntington's disease (HD). This work reports a facile fluorescence-based KMO assay optimized for high-throughput screening (HTS) that achieves a throughput approximately 20-fold higher than the fastest KMO assay currently reported. The screen was run with excellent performance (average Z' value of 0.80) from 110,000 compounds across 341 plates and exceeded all statistical parameters used to describe a robust HTS assay. A subset of molecules was selected for validation by ultra-high-performance liquid chromatography, resulting in the confirmation of a novel hit with an IC 50 comparable to that of the well-described KMO inhibitor Ro-61-8048. A medicinal chemistry program is currently underway to further develop our novel KMO inhibitor scaffolds.

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

Science.gov (United States)

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.

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

Science.gov (United States)

Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system

Characterization of Bovine Serum Albumin Blocking Efficiency on Epoxy-Functionalized Substrates for Microarray Applications.

Science.gov (United States)

Sun, Yung-Shin; Zhu, Xiangdong

2016-10-01

Microarrays provide a platform for high-throughput characterization of biomolecular interactions. To increase the sensitivity and specificity of microarrays, surface blocking is required to minimize the nonspecific interactions between analytes and unprinted yet functionalized surfaces. To block amine- or epoxy-functionalized substrates, bovine serum albumin (BSA) is one of the most commonly used blocking reagents because it is cheap and easy to use. Based on standard protocols from microarray manufactories, a BSA concentration of 1% (10 mg/mL or 200 μM) and reaction time of at least 30 min are required to efficiently block epoxy-coated slides. In this paper, we used both fluorescent and label-free methods to characterize the BSA blocking efficiency on epoxy-functionalized substrates. The blocking efficiency of BSA was characterized using a fluorescent scanner and a label-free oblique-incidence reflectivity difference (OI-RD) microscope. We found that (1) a BSA concentration of 0.05% (0.5 mg/mL or 10 μM) could give a blocking efficiency of 98%, and (2) the BSA blocking step took only about 5 min to be complete. Also, from real-time and in situ measurements, we were able to calculate the conformational properties (thickness, mass density, and number density) of BSA molecules deposited on the epoxy surface. © 2015 Society for Laboratory Automation and Screening.

An RNA-Based Fluorescent Biosensor for High-Throughput Analysis of the cGAS-cGAMP-STING Pathway.

Science.gov (United States)

Bose, Debojit; Su, Yichi; Marcus, Assaf; Raulet, David H; Hammond, Ming C

2016-12-22

In mammalian cells, the second messenger (2'-5',3'-5') cyclic guanosine monophosphate-adenosine monophosphate (2',3'-cGAMP), is produced by the cytosolic DNA sensor cGAMP synthase (cGAS), and subsequently bound by the stimulator of interferon genes (STING) to trigger interferon response. Thus, the cGAS-cGAMP-STING pathway plays a critical role in pathogen detection, as well as pathophysiological conditions including cancer and autoimmune disorders. However, studying and targeting this immune signaling pathway has been challenging due to the absence of tools for high-throughput analysis. We have engineered an RNA-based fluorescent biosensor that responds to 2',3'-cGAMP. The resulting "mix-and-go" cGAS activity assay shows excellent statistical reliability as a high-throughput screening (HTS) assay and distinguishes between direct and indirect cGAS inhibitors. Furthermore, the biosensor enables quantitation of 2',3'-cGAMP in mammalian cell lysates. We envision this biosensor-based assay as a resource to study the cGAS-cGAMP-STING pathway in the context of infectious diseases, cancer immunotherapy, and autoimmune diseases. Copyright © 2016 Elsevier Ltd. All rights reserved.

Radioactive cDNA microarray in neurospsychiatry

International Nuclear Information System (INIS)

Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon

2003-01-01

Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

Radioactive cDNA microarray in neurospsychiatry

Energy Technology Data Exchange (ETDEWEB)

Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon [Korea University Medical School, Seoul (Korea, Republic of)

2003-02-01

Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

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

KAUST Repository

Call, Douglas F.; Logan, Bruce E.

2011-01-01

There is great interest in studying exoelectrogenic microorganisms, but existing methods can require expensive electrochemical equipment and specialized reactors. We developed a simple system for conducting high throughput bioelectrochemical

SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing.

Science.gov (United States)

Sato, Yukuto; Kojima, Kaname; Nariai, Naoki; Yamaguchi-Kabata, Yumi; Kawai, Yosuke; Takahashi, Mamoru; Mimori, Takahiro; Nagasaki, Masao

2014-08-08

Next-generation sequencers (NGSs) have become one of the main tools for current biology. To obtain useful insights from the NGS data, it is essential to control low-quality portions of the data affected by technical errors such as air bubbles in sequencing fluidics. We develop a software SUGAR (subtile-based GUI-assisted refiner) which can handle ultra-high-throughput data with user-friendly graphical user interface (GUI) and interactive analysis capability. The SUGAR generates high-resolution quality heatmaps of the flowcell, enabling users to find possible signals of technical errors during the sequencing. The sequencing data generated from the error-affected regions of a flowcell can be selectively removed by automated analysis or GUI-assisted operations implemented in the SUGAR. The automated data-cleaning function based on sequence read quality (Phred) scores was applied to a public whole human genome sequencing data and we proved the overall mapping quality was improved. The detailed data evaluation and cleaning enabled by SUGAR would reduce technical problems in sequence read mapping, improving subsequent variant analysis that require high-quality sequence data and mapping results. Therefore, the software will be especially useful to control the quality of variant calls to the low population cells, e.g., cancers, in a sample with technical errors of sequencing procedures.

Molecular Approaches for High Throughput Detection and Quantification of Genetically Modified Crops: A Review

Directory of Open Access Journals (Sweden)

Ibrahim B. Salisu

2017-10-01

Full Text Available As long as the genetically modified crops are gaining attention globally, their proper approval and commercialization need accurate and reliable diagnostic methods for the transgenic content. These diagnostic techniques are mainly divided into two major groups, i.e., identification of transgenic (1 DNA and (2 proteins from GMOs and their products. Conventional methods such as PCR (polymerase chain reaction and enzyme-linked immunosorbent assay (ELISA were routinely employed for DNA and protein based quantification respectively. Although, these Techniques (PCR and ELISA are considered as significantly convenient and productive, but there is need for more advance technologies that allow for high throughput detection and the quantification of GM event as the production of more complex GMO is increasing day by day. Therefore, recent approaches like microarray, capillary gel electrophoresis, digital PCR and next generation sequencing are more promising due to their accuracy and precise detection of transgenic contents. The present article is a brief comparative study of all such detection techniques on the basis of their advent, feasibility, accuracy, and cost effectiveness. However, these emerging technologies have a lot to do with detection of a specific event, contamination of different events and determination of fusion as well as stacked gene protein are the critical issues to be addressed in future.

Controlling high-throughput manufacturing at the nano-scale

Science.gov (United States)

Cooper, Khershed P.

2013-09-01

Interest in nano-scale manufacturing research and development is growing. The reason is to accelerate the translation of discoveries and inventions of nanoscience and nanotechnology into products that would benefit industry, economy and society. Ongoing research in nanomanufacturing is focused primarily on developing novel nanofabrication techniques for a variety of applications—materials, energy, electronics, photonics, biomedical, etc. Our goal is to foster the development of high-throughput methods of fabricating nano-enabled products. Large-area parallel processing and highspeed continuous processing are high-throughput means for mass production. An example of large-area processing is step-and-repeat nanoimprinting, by which nanostructures are reproduced again and again over a large area, such as a 12 in wafer. Roll-to-roll processing is an example of continuous processing, by which it is possible to print and imprint multi-level nanostructures and nanodevices on a moving flexible substrate. The big pay-off is high-volume production and low unit cost. However, the anticipated cost benefits can only be realized if the increased production rate is accompanied by high yields of high quality products. To ensure product quality, we need to design and construct manufacturing systems such that the processes can be closely monitored and controlled. One approach is to bring cyber-physical systems (CPS) concepts to nanomanufacturing. CPS involves the control of a physical system such as manufacturing through modeling, computation, communication and control. Such a closely coupled system will involve in-situ metrology and closed-loop control of the physical processes guided by physics-based models and driven by appropriate instrumentation, sensing and actuation. This paper will discuss these ideas in the context of controlling high-throughput manufacturing at the nano-scale.

Variance estimation in the analysis of microarray data

KAUST Repository

Wang, Yuedong

2009-04-01

Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

Microarray-based identification and RT-PCR test screening for epithelial-specific mRNAs in peripheral blood of patients with colon cancer

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Coppola Domenico

2006-10-01

Full Text Available Abstract Background The efficacy of screening for colorectal cancer using a simple blood-based assay for the detection of tumor cells disseminated in the circulation at an early stage of the disease is gaining positive feedback from several lines of research. This method seems able to reduce colorectal cancer mortality and may replace colonoscopy as the most effective means of detecting colonic lesions. Methods In this work, we present a new microarray-based high-throughput screening method to identifying candidate marker mRNAs for the early detection of epithelial cells diluted in peripheral blood cells. This method includes 1. direct comparison of different samples of colonic mucosa and of blood cells to identify consistent epithelial-specific mRNAs from among 20,000 cDNA assayed by microarray slides; 2. identification of candidate marker mRNAs by data analysis, which allowed selection of only 10 putative differentially expressed genes; 3. Selection of some of the most suitable mRNAs (TMEM69, RANBP3 and PRSS22 that were assayed in blood samples from normal subjects and patients with colon cancer as possible markers for the presence of epithelial cells in the blood, using reverse transcription – polymerase chain reaction (RT-PCR. Results Our present results seem to provide an indication, for the first time obtained by genome-scale screening, that a suitable and consistent colon epithelium mRNA marker may be difficult to identify. Conclusion The design of new approaches to identify such markers is warranted.

A versatile, high through-put, bead-based phagocytosis assay for Plasmodium falciparum

DEFF Research Database (Denmark)

Lloyd, Yukie M.; Ngati, Elise P.; Salanti, Ali

2017-01-01

Antibody-mediated phagocytosis is an important immune effector mechanism against Plasmodium falciparum-infected erythrocytes (IE); however, current phagocytosis assays use IE collected from infected individuals or from in vitro cultures of P. falciparum, making them prone to high variation....... A simple, high-throughput flow cytometric assay was developed that uses THP-1 cells and fluorescent beads covalently-coupled with the malarial antigen VAR2CSA. The assay is highly repeatable, provides both the overall percent phagocytosis and semi-quantitates the number of antigen-coupled beads...

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

Science.gov (United States)

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.

High-throughput scoring of seed germination

NARCIS (Netherlands)

Ligterink, Wilco; Hilhorst, Henk W.M.

2017-01-01

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very

Screening for C3 deficiency in newborns using microarrays.

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Magdalena Janzi

Full Text Available BACKGROUND: Dried blood spot samples (DBSS from newborns are widely used in neonatal screening for selected metabolic diseases and diagnostic possibilities for additional disorders are continuously being evaluated. Primary immunodeficiency disorders comprise a group of more than one hundred diseases, several of which are fatal early in life. Yet, a majority of the patients are not diagnosed due to lack of high-throughput screening methods. METHODOLOGY/PRINCIPAL FINDINGS: We have previously developed a system using reverse phase protein microarrays for analysis of IgA levels in serum samples. In this study, we extended the applicability of the method to include determination of complement component C3 levels in eluates from DBSS collected at birth. Normal levels of C3 were readily detected in 269 DBSS from healthy newborns, while no C3 was detected in sera and DBSS from C3 deficient patients. CONCLUSIONS/SIGNIFICANCE: The findings suggest that patients with deficiencies of specific serum proteins can be identified by analysis of DBSS using reverse phase protein microarrays.

Applications of high-throughput clonogenic survival assays in high-LET particle microbeams

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Antonios eGeorgantzoglou

2016-01-01

Full Text Available Charged particle therapy is increasingly becoming a valuable tool in cancer treatment, mainly due to the favorable interaction of particle radiation with matter. Its application is still limited due, in part, to lack of data regarding the radiosensitivity of certain cell lines to this radiation type, especially to high-LET particles. From the earliest days of radiation biology, the clonogenic survival assay has been used to provide radiation response data. This method produces reliable data but it is not optimized for high-throughput microbeam studies with high-LET radiation where high levels of cell killing lead to a very low probability of maintaining cells’ clonogenic potential. A new method, therefore, is proposed in this paper, which could potentially allow these experiments to be conducted in a high-throughput fashion. Cells are seeded in special polypropylene dishes and bright-field illumination provides cell visualization. Digital images are obtained and cell detection is applied based on corner detection, generating individual cell targets as x-y points. These points in the dish are then irradiated individually by a micron field size high-LET microbeam. Post-irradiation, time-lapse imaging follows cells’ response. All irradiated cells are tracked by linking trajectories in all time-frames, based on finding their nearest position. Cell divisions are detected based on cell appearance and individual cell temporary corner density. The number of divisions anticipated is low due to the high probability of cell killing from high-LET irradiation. Survival curves are produced based on cell’s capacity to divide at least 4-5 times. The process is repeated for a range of doses of radiation. Validation shows the efficiency of the proposed cell detection and tracking method in finding cell divisions.

Applications of High-Throughput Clonogenic Survival Assays in High-LET Particle Microbeams.

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Georgantzoglou, Antonios; Merchant, Michael J; Jeynes, Jonathan C G; Mayhead, Natalie; Punia, Natasha; Butler, Rachel E; Jena, Rajesh

2015-01-01

Charged particle therapy is increasingly becoming a valuable tool in cancer treatment, mainly due to the favorable interaction of particle radiation with matter. Its application is still limited due, in part, to lack of data regarding the radiosensitivity of certain cell lines to this radiation type, especially to high-linear energy transfer (LET) particles. From the earliest days of radiation biology, the clonogenic survival assay has been used to provide radiation response data. This method produces reliable data but it is not optimized for high-throughput microbeam studies with high-LET radiation where high levels of cell killing lead to a very low probability of maintaining cells' clonogenic potential. A new method, therefore, is proposed in this paper, which could potentially allow these experiments to be conducted in a high-throughput fashion. Cells are seeded in special polypropylene dishes and bright-field illumination provides cell visualization. Digital images are obtained and cell detection is applied based on corner detection, generating individual cell targets as x-y points. These points in the dish are then irradiated individually by a micron field size high-LET microbeam. Post-irradiation, time-lapse imaging follows cells' response. All irradiated cells are tracked by linking trajectories in all time-frames, based on finding their nearest position. Cell divisions are detected based on cell appearance and individual cell temporary corner density. The number of divisions anticipated is low due to the high probability of cell killing from high-LET irradiation. Survival curves are produced based on cell's capacity to divide at least four to five times. The process is repeated for a range of doses of radiation. Validation shows the efficiency of the proposed cell detection and tracking method in finding cell divisions.

Integration of an In Situ MALDI-Based High-Throughput Screening Process: A Case Study with Receptor Tyrosine Kinase c-MET.

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Beeman, Katrin; Baumgärtner, Jens; Laubenheimer, Manuel; Hergesell, Karlheinz; Hoffmann, Martin; Pehl, Ulrich; Fischer, Frank; Pieck, Jan-Carsten

2017-12-01

Mass spectrometry (MS) is known for its label-free detection of substrates and products from a variety of enzyme reactions. Recent hardware improvements have increased interest in the use of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS for high-throughput drug discovery. Despite interest in this technology, several challenges remain and must be overcome before MALDI-MS can be integrated as an automated "in-line reader" for high-throughput drug discovery. Two such hurdles include in situ sample processing and deposition, as well as integration of MALDI-MS for enzymatic screening assays that usually contain high levels of MS-incompatible components. Here we adapt our c-MET kinase assay to optimize for MALDI-MS compatibility and test its feasibility for compound screening. The pros and cons of the Echo (Labcyte) as a transfer system for in situ MALDI-MS sample preparation are discussed. We demonstrate that this method generates robust data in a 1536-grid format. We use the MALDI-MS to directly measure the ratio of c-MET substrate and phosphorylated product to acquire IC50 curves and demonstrate that the pharmacology is unaffected. The resulting IC50 values correlate well between the common label-based capillary electrophoresis and the label-free MALDI-MS detection method. We predict that label-free MALDI-MS-based high-throughput screening will become increasingly important and more widely used for drug discovery.

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

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Salvo-Chirnside Eliane

2011-12-01

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

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

Science.gov (United States)

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

2011-12-02

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

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

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Riccardo Ludovisi

2017-09-01

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

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

Science.gov (United States)

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

2017-01-01

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

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

Science.gov (United States)

Schönmann, Susan; Loy, Alexander; Wimmersberger, Céline; Sobek, Jens; Aquino, Catharine; Vandamme, Peter; Frey, Beat; Rehrauer, Hubert; Eberl, Leo

2009-04-01

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Management of High-Throughput DNA Sequencing Projects: Alpheus.

Science.gov (United States)

Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F

2008-12-26

High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.

High-throughput Screening for Protein-based Inheritance in S. cerevisiae.

Science.gov (United States)

Byers, James S; Jarosz, Daniel F

2017-08-08

The encoding of biological information that is accessible to future generations is generally achieved via changes to the DNA sequence. Long-lived inheritance encoded in protein conformation (rather than sequence) has long been viewed as paradigm-shifting but rare. The best characterized examples of such epigenetic elements are prions, which possess a self-assembling behavior that can drive the heritable manifestation of new phenotypes. Many archetypal prions display a striking N/Q-rich sequence bias and assemble into an amyloid fold. These unusual features have informed most screening efforts to identify new prion proteins. However, at least three known prions (including the founding prion, PrP Sc ) do not harbor these biochemical characteristics. We therefore developed an alternative method to probe the scope of protein-based inheritance based on a property of mass action: the transient overexpression of prion proteins increases the frequency at which they acquire a self-templating conformation. This paper describes a method for analyzing the capacity of the yeast ORFeome to elicit protein-based inheritance. Using this strategy, we previously found that >1% of yeast proteins could fuel the emergence of biological traits that were long-lived, stable, and arose more frequently than genetic mutation. This approach can be employed in high throughput across entire ORFeomes or as a targeted screening paradigm for specific genetic networks or environmental stimuli. Just as forward genetic screens define numerous developmental and signaling pathways, these techniques provide a methodology to investigate the influence of protein-based inheritance in biological processes.

High-throughput characterization for solar fuels materials discovery

Science.gov (United States)

Mitrovic, Slobodan; Becerra, Natalie; Cornell, Earl; Guevarra, Dan; Haber, Joel; Jin, Jian; Jones, Ryan; Kan, Kevin; Marcin, Martin; Newhouse, Paul; Soedarmadji, Edwin; Suram, Santosh; Xiang, Chengxiang; Gregoire, John; High-Throughput Experimentation Team

2014-03-01

In this talk I will present the status of the High-Throughput Experimentation (HTE) project of the Joint Center for Artificial Photosynthesis (JCAP). JCAP is an Energy Innovation Hub of the U.S. Department of Energy with a mandate to deliver a solar fuel generator based on an integrated photoelectrochemical cell (PEC). However, efficient and commercially viable catalysts or light absorbers for the PEC do not exist. The mission of HTE is to provide the accelerated discovery through combinatorial synthesis and rapid screening of material properties. The HTE pipeline also features high-throughput material characterization using x-ray diffraction and x-ray photoemission spectroscopy (XPS). In this talk I present the currently operating pipeline and focus on our combinatorial XPS efforts to build the largest free database of spectra from mixed-metal oxides, nitrides, sulfides and alloys. This work was performed at Joint Center for Artificial Photosynthesis, a DOE Energy Innovation Hub, supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993.

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

Science.gov (United States)

The EPA ToxCast effort has screened thousands of chemicals across hundreds of high-throughput in vitro screening assays. The project is now leveraging high-throughput transcriptomic (HTTr) technologies to substantially expand its coverage of biological pathways. The first HTTr sc...

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

DEFF Research Database (Denmark)

Bosco, Filippo; Hwu, En-Te; Chen, Ching-Hsiu

2011-01-01

Sensors are crucial in many daily operations including security, environmental control, human diagnostics and patient monitoring. Screening and online monitoring require reliable and high-throughput sensing. We report on the demonstration of a high-throughput label-free sensor platform utilizing...

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

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

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

Protein Array (RPPA)-based readout format integrated into robotic siRNA screening. This technique would allow post-screening high-throughput quantification of protein changes. Recently, breast cancer stem cells (BCSCs) have attracted much attention, as a tumor- and metastasis-driving subpopulation...

A high-throughput pipeline for the design of real-time PCR signatures

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Reifman Jaques

2010-06-01

Full Text Available Abstract Background Pathogen diagnostic assays based on polymerase chain reaction (PCR technology provide high sensitivity and specificity. However, the design of these diagnostic assays is computationally intensive, requiring high-throughput methods to identify unique PCR signatures in the presence of an ever increasing availability of sequenced genomes. Results We present the Tool for PCR Signature Identification (TOPSI, a high-performance computing pipeline for the design of PCR-based pathogen diagnostic assays. The TOPSI pipeline efficiently designs PCR signatures common to multiple bacterial genomes by obtaining the shared regions through pairwise alignments between the input genomes. TOPSI successfully designed PCR signatures common to 18 Staphylococcus aureus genomes in less than 14 hours using 98 cores on a high-performance computing system. Conclusions TOPSI is a computationally efficient, fully integrated tool for high-throughput design of PCR signatures common to multiple bacterial genomes. TOPSI is freely available for download at http://www.bhsai.org/downloads/topsi.tar.gz.

Towards Chip Scale Liquid Chromatography and High Throughput Immunosensing

Energy Technology Data Exchange (ETDEWEB)

Ni, Jing [Iowa State Univ., Ames, IA (United States)

2000-09-21

This work describes several research projects aimed towards developing new instruments and novel methods for high throughput chemical and biological analysis. Approaches are taken in two directions. The first direction takes advantage of well-established semiconductor fabrication techniques and applies them to miniaturize instruments that are workhorses in analytical laboratories. Specifically, the first part of this work focused on the development of micropumps and microvalves for controlled fluid delivery. The mechanism of these micropumps and microvalves relies on the electrochemically-induced surface tension change at a mercury/electrolyte interface. A miniaturized flow injection analysis device was integrated and flow injection analyses were demonstrated. In the second part of this work, microfluidic chips were also designed, fabricated, and tested. Separations of two fluorescent dyes were demonstrated in microfabricated channels, based on an open-tubular liquid chromatography (OT LC) or an electrochemically-modulated liquid chromatography (EMLC) format. A reduction in instrument size can potentially increase analysis speed, and allow exceedingly small amounts of sample to be analyzed under diverse separation conditions. The second direction explores the surface enhanced Raman spectroscopy (SERS) as a signal transduction method for immunoassay analysis. It takes advantage of the improved detection sensitivity as a result of surface enhancement on colloidal gold, the narrow width of Raman band, and the stability of Raman scattering signals to distinguish several different species simultaneously without exploiting spatially-separated addresses on a biochip. By labeling gold nanoparticles with different Raman reporters in conjunction with different detection antibodies, a simultaneous detection of a dual-analyte immunoassay was demonstrated. Using this scheme for quantitative analysis was also studied and preliminary dose-response curves from an immunoassay of a

High resolution light-sheet based high-throughput imaging cytometry system enables visualization of intra-cellular organelles

Science.gov (United States)

Regmi, Raju; Mohan, Kavya; Mondal, Partha Pratim

2014-09-01

Visualization of intracellular organelles is achieved using a newly developed high throughput imaging cytometry system. This system interrogates the microfluidic channel using a sheet of light rather than the existing point-based scanning techniques. The advantages of the developed system are many, including, single-shot scanning of specimens flowing through the microfluidic channel at flow rate ranging from micro- to nano- lit./min. Moreover, this opens-up in-vivo imaging of sub-cellular structures and simultaneous cell counting in an imaging cytometry system. We recorded a maximum count of 2400 cells/min at a flow-rate of 700 nl/min, and simultaneous visualization of fluorescently-labeled mitochondrial network in HeLa cells during flow. The developed imaging cytometry system may find immediate application in biotechnology, fluorescence microscopy and nano-medicine.

High-throughput sequence alignment using Graphics Processing Units

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Trapnell Cole

2007-12-01

Full Text Available Abstract Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

High throughput imaging cytometer with acoustic focussing.

Science.gov (United States)

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

2015-10-31

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

Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

Science.gov (United States)

High-throughput screening (HTS) generates in vitro data for characterizing potential chemical hazard. TK models are needed to allow in vitro to in vivo extrapolation (IVIVE) to real world situations. The U.S. EPA has created a public tool (R package “httk” for high throughput tox...

High throughput nonparametric probability density estimation.

Science.gov (United States)

Farmer, Jenny; Jacobs, Donald

2018-01-01

In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

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

Science.gov (United States)

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

2016-01-01

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

Roche genome sequencer FLX based high-throughput sequencing of ancient DNA

DEFF Research Database (Denmark)

Alquezar-Planas, David E; Fordyce, Sarah Louise

2012-01-01

Since the development of so-called "next generation" high-throughput sequencing in 2005, this technology has been applied to a variety of fields. Such applications include disease studies, evolutionary investigations, and ancient DNA. Each application requires a specialized protocol to ensure...... that the data produced is optimal. Although much of the procedure can be followed directly from the manufacturer's protocols, the key differences lie in the library preparation steps. This chapter presents an optimized protocol for the sequencing of fossil remains and museum specimens, commonly referred...

High-throughput screening of Erwinia chrysanthemi pectin methylesterase variants using carbohydrate microarrays

DEFF Research Database (Denmark)

Øbro, Jens; Sørensen, Iben; Derkx, Patrick

2009-01-01

the activity of a series of variant enzymes based on the PME from the important pathogen Erwinia chrysanthemi. A library of 99 E. chrysanthemi PME mutants was created in which seven amino acids were altered by various different substitutions. Each mutant PME was incubated with a highly methyl esterified lime...

Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

Energy Technology Data Exchange (ETDEWEB)

Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon [College of Medicine, Univ. of Korea, Seoul (Korea, Republic of)

2003-07-01

Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology.

Radioactive cDNA microarray (II): Gene expression profiling of antidepressant treatment by human cDNA microarray

International Nuclear Information System (INIS)

Lee, Ji Hye; Kang, Rhee Hun; Ham, Byung Joo; Lee, Min Su; Shin, Kyung Ho; Choe, Jae Gol; Kim, Meyoung Kon

2003-01-01

Major depressive disorder is a prevalent psychiatric disorder in primary care, associated with impaired patient functioning and well-being. Fluoxetine is a selective serotonin-reuptake inhibitors (SSRIs) and is a commonly prescribed antidepressant compound. Its action is primarily attributed to selective inhibition of the reuptake of serotonin (5-hydroxytryptamine) in the central nervous system. Objectives ; the aims of this study were two-fold: (1) to determine the usefulness for investigation of the transcription profiles in depression patients, and (2) to assess the differences in gene expression profiles between positive response group and negative response groups by fluoxetine treatment. This study included 53 patients with major depression (26 in positive response group with antidepressant treatment, 27 in negative response group with antidepressant treatment), and 53 healthy controls. To examine the difference of gene expression profile in depression patients, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 genes in total. Using 33p-labeled probes, this method provided highly sensitive gene expression profiles including brain receptors, drug metabolism, and cellular signaling. Gene transcription profiles were classified into several categories in accordance with the antidepressant gene-regulation. The gene profiles were significantly up-(22 genes) and down-(16 genes) regulated in the positive response group when compared to the control group. Also, in the negative response group, 35 genes were up-regulated and 8 genes were down-regulated when compared to the control group. Consequently, we demonstrated that radioactive human cDNA microarray is highly likely to be an efficient technology for evaluating the gene regulation of antidepressants, such as selective serotonin-reuptake inhibitors (SSRIs), by using high-throughput biotechnology

poolHiTS: A Shifted Transversal Design based pooling strategy for high-throughput drug screening

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Woolf Peter J

2008-05-01

Full Text Available Abstract Background A key goal of drug discovery is to increase the throughput of small molecule screens without sacrificing screening accuracy. High-throughput screening (HTS in drug discovery involves testing a large number of compounds in a biological assay to identify active compounds. Normally, molecules from a large compound library are tested individually to identify the activity of each molecule. Usually a small number of compounds are found to be active, however the presence of false positive and negative testing errors suggests that this one-drug one-assay screening strategy can be significantly improved. Pooling designs are testing schemes that test mixtures of compounds in each assay, thereby generating a screen of the whole compound library in fewer tests. By repeatedly testing compounds in different combinations, pooling designs also allow for error-correction. These pooled designs, for specific experiment parameters, can be simply and efficiently created using the Shifted Transversal Design (STD pooling algorithm. However, drug screening contains a number of key constraints that require specific modifications if this pooling approach is to be useful for practical screen designs. Results In this paper, we introduce a pooling strategy called poolHiTS (Pooled High-Throughput Screening which is based on the STD algorithm. In poolHiTS, we implement a limit on the number of compounds that can be mixed in a single assay. In addition, we show that the STD-based pooling strategy is limited in the error-correction that it can achieve. Due to the mixing constraint, we show that it is more efficient to split a large library into smaller blocks of compounds, which are then tested using an optimized strategy repeated for each block. We package the optimal block selection algorithm into poolHiTS. The MATLAB codes for the poolHiTS algorithm and the corresponding decoding strategy are also provided. Conclusion We have produced a practical version

High-throughput Microarray Detection of Vomeronasal Receptor Gene Expression in Rodents

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Xiaohong Zhang

2010-11-01

Full Text Available We performed comprehensive data mining to explore the vomeronasal receptor (V1R & V2R repertoires in mouse and rat using the mm5 and rn3 genome, respectively. This bioinformatic analysis was followed by investigation of gene expression using a custom designed high-density oligonucleotide array containing all of these receptors and other selected genes of interest. This array enabled us to detect the specific expression of V1R and V2Rs which were previously identified solely based on computational prediction from gene sequence data, thereby establishing that these genes are indeed part of the vomeronasal system, especially the V2Rs. 168 V1Rs and 98 V2Rs were detected to be highly enriched in mouse vomeronasal organ (VNO, and 108 V1Rs and 87 V2Rs in rat VNO. We monitored the expression profile of mouse VR genes in other non-VNO tissues with the result that some VR genes were re-designated as VR-like genes based on their non-olfactory expression pattern. Temporal expression profiles for mouse VR genes were characterized and their patterns were classified, revealing the developmental dynamics of these so-called pheromone receptors. We found numerous patterns of temporal expression which indicate possible behavior-related functions. The uneven composition of VR genes in certain patterns suggests a functional differentiation between the two types of VR genes. We found the coherence between VR genes and transcription factors in terms of their temporal expression patterns. In situ hybridization experiments were performed to evaluate the cell number change over time for selected receptor genes.

Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

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Jouventin Pierre

2010-05-01

Full Text Available Abstract Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.

High-Throughput Screening of Heterogeneous Catalysts for the Conversion of Furfural to Bio-Based Fuel Components

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Roberto Pizzi

2015-12-01

Full Text Available The one-pot catalytic reductive etherification of furfural to 2-methoxymethylfuran (furfuryl methyl ether, FME, a valuable bio-based chemical or fuel, is reported. A large number of commercially available hydrogenation heterogeneous catalysts based on nickel, copper, cobalt, iridium, palladium and platinum catalysts on various support were evaluated by a high-throughput screening approach. The reaction was carried out in liquid phase with a 10% w/w furfural in methanol solution at 50 bar of hydrogen. Among all the samples tested, carbon-supported noble metal catalysts were found to be the most promising in terms of productivity and selectivity. In particular, palladium on charcoal catalysts show high selectivity (up to 77% to FME. Significant amounts of furfuryl alcohol (FA and 2-methylfuran (2-MF are observed as the major by-products.

Simultaneous measurements of auto-immune and infectious disease specific antibodies using a high throughput multiplexing tool.

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Atul Asati

Full Text Available Considering importance of ganglioside antibodies as biomarkers in various immune-mediated neuropathies and neurological disorders, we developed a high throughput multiplexing tool for the assessment of gangliosides-specific antibodies based on Biolpex/Luminex platform. In this report, we demonstrate that the ganglioside high throughput multiplexing tool is robust, highly specific and demonstrating ∼100-fold higher concentration sensitivity for IgG detection than ELISA. In addition to the ganglioside-coated array, the high throughput multiplexing tool contains beads coated with influenza hemagglutinins derived from H1N1 A/Brisbane/59/07 and H1N1 A/California/07/09 strains. Influenza beads provided an added advantage of simultaneous detection of ganglioside- and influenza-specific antibodies, a capacity important for the assay of both infectious antigen-specific and autoimmune antibodies following vaccination or disease. Taken together, these results support the potential adoption of the ganglioside high throughput multiplexing tool for measuring ganglioside antibodies in various neuropathic and neurological disorders.

High-throughput measurement of polymer film thickness using optical dyes

Science.gov (United States)

Grunlan, Jaime C.; Mehrabi, Ali R.; Ly, Tien

2005-01-01

Optical dyes were added to polymer solutions in an effort to create a technique for high-throughput screening of dry polymer film thickness. Arrays of polystyrene films, cast from a toluene solution, containing methyl red or solvent green were used to demonstrate the feasibility of this technique. Measurements of the peak visible absorbance of each film were converted to thickness using the Beer-Lambert relationship. These absorbance-based thickness calculations agreed within 10% of thickness measured using a micrometer for polystyrene films that were 10-50 µm. At these thicknesses it is believed that the absorbance values are actually more accurate. At least for this solvent-based system, thickness was shown to be accurately measured in a high-throughput manner that could potentially be applied to other equivalent systems. Similar water-based films made with poly(sodium 4-styrenesulfonate) dyed with malachite green oxalate or congo red did not show the same level of agreement with the micrometer measurements. Extensive phase separation between polymer and dye resulted in inflated absorbance values and calculated thickness that was often more than 25% greater than that measured with the micrometer. Only at thicknesses below 15 µm could reasonable accuracy be achieved for the water-based films.

High-throughput optical system for HDES hyperspectral imager

Science.gov (United States)

Václavík, Jan; Melich, Radek; Pintr, Pavel; Pleštil, Jan

2015-01-01

Affordable, long-wave infrared hyperspectral imaging calls for use of an uncooled FPA with high-throughput optics. This paper describes the design of the optical part of a stationary hyperspectral imager in a spectral range of 7-14 um with a field of view of 20°×10°. The imager employs a push-broom method made by a scanning mirror. High throughput and a demand for simplicity and rigidity led to a fully refractive design with highly aspheric surfaces and off-axis positioning of the detector array. The design was optimized to exploit the machinability of infrared materials by the SPDT method and a simple assemblage.

Subnuclear foci quantification using high-throughput 3D image cytometry

Science.gov (United States)

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.

Assessment of a direct hybridization microarray strategy for comprehensive monitoring of genetically modified organisms (GMOs).

Science.gov (United States)

Turkec, Aydin; Lucas, Stuart J; Karacanli, Burçin; Baykut, Aykut; Yuksel, Hakki

2016-03-01

Detection of GMO material in crop and food samples is the primary step in GMO monitoring and regulation, with the increasing number of GM events in the world market requiring detection solutions with high multiplexing capacity. In this study, we test the suitability of a high-density oligonucleotide microarray platform for direct, quantitative detection of GMOs found in the Turkish feed market. We tested 1830 different 60nt probes designed to cover the GM cassettes from 12 different GM cultivars (3 soya, 9 maize), as well as plant species-specific and contamination controls, and developed a data analysis method aiming to provide maximum throughput and sensitivity. The system was able specifically to identify each cultivar, and in 10/12 cases was sensitive enough to detect GMO DNA at concentrations of ⩽1%. These GMOs could also be quantified using the microarray, as their fluorescence signals increased linearly with GMO concentration. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of a novel multiplex DNA microarray for Fusarium graminearum and analysis of azole fungicide responses

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Deising Holger B

2011-01-01

Full Text Available Abstract Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024 groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide

Patterning cell using Si-stencil for high-throughput assay

KAUST Repository

Wu, Jinbo

2011-01-01

In this communication, we report a newly developed cell pattering methodology by a silicon-based stencil, which exhibited advantages such as easy handling, reusability, hydrophilic surface and mature fabrication technologies. Cell arrays obtained by this method were used to investigate cell growth under a temperature gradient, which demonstrated the possibility of studying cell behavior in a high-throughput assay. This journal is © The Royal Society of Chemistry 2011.

Label-Free and Multiplex Detection of Antibiotic Residues in Milk Using Imaging Surface Plasmon Resonance-Based Immunosensor

NARCIS (Netherlands)

Raz, Sabina Rebe; Bremer, Maria G. E. G.; Haasnoot, Willem; Norde, Willem

2009-01-01

Monitoring of antimicrobial drug residues in foods relies greatly on the availability of adequate analytical techniques. Currently, there is a need for a high-throughput screening method with a broad-spectrum detection range. This paper describes the development of a microarray biosensor, based on

Label-Free and Multiplex Detection of Antibiotic Residues in Milk Using Imaging surface Plasmon Resonance-Based immunosensor

NARCIS (Netherlands)

Rebe, S.; Bremer, M.G.E.G.; Haasnoot, W.; Norde, W.

2009-01-01

Monitoring of antimicrobial drug residues in foods relies greatly on the availability of adequate analytical techniques. Currently, there is a need for a high-throughput screening method with a broad-spectrum detection range. This paper describes the development of a microarray biosensor, based on

High Performance Computing Modernization Program Kerberos Throughput Test Report

Science.gov (United States)

2017-10-26

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5524--17-9751 High Performance Computing Modernization Program Kerberos Throughput Test ...NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 2. REPORT TYPE1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING...PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT High Performance Computing Modernization Program Kerberos Throughput Test Report Daniel G. Gdula* and

Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

International Nuclear Information System (INIS)

Karaçali, Bilge; Tözeren, Aydin

2007-01-01

Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest

High throughput Screening to Identify Natural Human Monoamine Oxidase B Inhibitors

Science.gov (United States)

Mazzio, E; Deiab, S; Park, K; Soliman, KFA

2012-01-01

Age-related increase in monoamine oxidase B (MAO-B) may contribute to CNS neurodegenerative diseases. Moreover, MAO-B inhibitors are used in the treatment of idiopathic Parkinson disease as preliminary monotherapy or adjunct therapy with L-dopa. To date, meager natural sources of MAO-B inhibitors have been identified, and the relative strength, potency and rank of many plants relative to standard drugs such as Selegiline (L-deprenyl, Eldepryl) are not known. In this work, we developed and utilized a high throughput enzyme microarray format to screen and evaluate 905 natural product extracts (0.025–.7 mg/ml) to inhibit human MAO-B derived from BTI-TN-5B1-4 cells infected with recombinant baculovirus. The protein sequence of purified enzyme was confirmed using 1D gel electrophoresis-matrix assisted laser desorption ionization-time-of-flight-tandem mass spectroscopy, and enzyme activity was confirmed by [1] substrate conversion (3-mM benzylamine) to H202 and [2] benzaldehyde. Of the 905 natural extracts tested, the lowest IC50s [Comfrey, Bringraj, Skullcap, Kava-kava, Wild Indigo, Gentian and Green Tea. In conclusion, the data reflect relative potency information by rank of commonly used herbs and plants that contain human MAO-B inhibitory properties in their natural form. PMID:22887993

High-density polymer microarrays: identifying synthetic polymers that control human embryonic stem cell growth.

Science.gov (United States)

Hansen, Anne; Mjoseng, Heidi K; Zhang, Rong; Kalloudis, Michail; Koutsos, Vasileios; de Sousa, Paul A; Bradley, Mark

2014-06-01

The fabrication of high-density polymer microarray is described, allowing the simultaneous and efficient evaluation of more than 7000 different polymers in a single-cellular-based screen. These high-density polymer arrays are applied in the search for synthetic substrates for hESCs culture. Up-scaling of the identified hit polymers enables long-term cellular cultivation and promoted successful stem-cell maintenance. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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Theodoros Kelesidis

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

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

DEFF Research Database (Denmark)

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H

2017-01-01

To target bacterial pathogens that invade and proliferate inside host cells, it is necessary to design intervention strategies directed against bacterial attachment, cellular invasion and intracellular proliferation. We present an automated microscopy-based, fast, high-throughput method for analy...

Elimination of heparin interference during microarray processing of fresh and biobank-archived blood samples.

Science.gov (United States)

Hebels, Dennie G A J; van Herwijnen, Marcel H M; Brauers, Karen J J; de Kok, Theo M C M; Chalkiadaki, Georgia; Kyrtopoulos, Soterios A; Kleinjans, Jos C S

2014-07-01

In the context of environmental health research, biobank blood samples have recently been identified as suitable for high-throughput omics analyses enabling the identification of new biomarkers of exposure and disease. However, blood samples containing the anti-coagulant heparin could complicate transcriptomic analysis because heparin may inhibit RNA polymerase causing inefficient cRNA synthesis and fluorophore labelling. We investigated the inhibitory effect of heparin and the influence of storage conditions (0 or 3 hr bench times, storage at room temperature or -80°C) on fluorophore labelling in heparinized fresh human buffy coat and whole blood biobank samples during the mRNA work-up protocol for microarray analysis. Subsequently, we removed heparin by lithium chloride (LiCl) treatment and performed a quality control analysis of LiCl-treated biobank sample microarrays to prove their suitability for downstream data analysis. Both fresh and biobank samples experienced varying degrees of heparin-induced inhibition of fluorophore labelling, making most samples unusable for microarray analysis. RNA derived from EDTA and citrate blood was not inhibited. No effect of bench time was observed but room temperature storage gave slightly better results. Strong correlations were observed between original blood sample RNA yield and the amount of synthesized cRNA. LiCl treatment restored sample quality to normal standards in both fresh and biobank samples and the previously identified correlations disappeared. Microarrays hybridized with LiCl-treated biobank samples were of excellent quality with no identifiable influence of heparin. We conclude that, to obtain high quality results, in most cases heparin removal is essential in blood-derived RNA samples intended for microarray analysis. Copyright © 2014 Wiley Periodicals, Inc.

Establishment and Application of a Visual DNA Microarray for the Detection of Food-borne Pathogens.

Science.gov (United States)

Li, Yongjin

2016-01-01

The accurate detection and identification of food-borne pathogenic microorganisms is critical for food safety nowadays. In the present work, a visual DNA microarray was established and applied to detect pathogens commonly found in food, including Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in food samples. Multiplex PCR (mPCR) was employed to simultaneously amplify specific gene fragments, fimY for Salmonella, ipaH for Shigella, iap for L. monocytogenes and ECs2841 for E. coli O157:H7, respectively. Biotinylated PCR amplicons annealed to the microarray probes were then reacted with a streptavidin-alkaline phosphatase conjugate and nitro blue tetrazolium/5-bromo-4-chloro-3'-indolylphosphate, p-toluidine salt (NBT/BCIP); the positive results were easily visualized as blue dots formatted on the microarray surface. The performance of a DNA microarray was tested against 14 representative collection strains and mock-contamination food samples. The combination of mPCR and a visual micro-plate chip specifically and sensitively detected Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in standard strains and food matrices with a sensitivity of ∼10(2) CFU/mL of bacterial culture. Thus, the developed method is advantageous because of its high throughput, cost-effectiveness and ease of use.

Development and validation of a quantitative, high-throughput, fluorescent-based bioassay to detect schistosoma viability.

Directory of Open Access Journals (Sweden)

Emily Peak

2010-07-01

Full Text Available Schistosomiasis, caused by infection with the blood fluke Schistosoma, is responsible for greater than 200,000 human deaths per annum. Objective high-throughput screens for detecting novel anti-schistosomal targets will drive 'genome to drug' lead translational science at an unprecedented rate. Current methods for detecting schistosome viability rely on qualitative microscopic criteria, which require an understanding of parasite morphology, and most importantly, must be subjectively interpreted. These limitations, in the current state of the art, have significantly impeded progress into whole schistosome screening for next generation chemotherapies.We present here a microtiter plate-based method for reproducibly detecting schistosomula viability that takes advantage of the differential uptake of fluorophores (propidium iodide and fluorescein diacetate by living organisms. We validate this high-throughput system in detecting schistosomula viability using auranofin (a known inhibitor of thioredoxin glutathione reductase, praziquantel and a range of small compounds with previously-described (gambogic acid, sodium salinomycin, ethinyl estradiol, fluoxetidine hydrochloride, miconazole nitrate, chlorpromazine hydrochloride, amphotericin b, niclosamide or suggested (bepridil, ciclopirox, rescinnamine, flucytosine, vinblastine and carbidopa anti-schistosomal activities. This developed method is sensitive (200 schistosomula/well can be assayed, relevant to industrial (384-well microtiter plate compatibility and academic (96-well microtiter plate compatibility settings, translatable to functional genomics screens and drug assays, does not require a priori knowledge of schistosome biology and is quantitative.The wide-scale application of this fluorescence-based bioassay will greatly accelerate the objective identification of novel therapeutic lead targets/compounds to combat schistosomiasis. Adapting this bioassay for use with other parasitic worm species

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

Science.gov (United States)

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.

High-throughput antibody development and retrospective epitope mapping

DEFF Research Database (Denmark)

Rydahl, Maja Gro

the binding profile - in more or less high resolution - of two small molecular probes, 11 carbohydrate binding modules and 24 monoclonal antibodies. This was made possible by combining the HTP multiplexing capacity of carbohydrate microarrays with diverse glycomic tools, to downstream characterize...

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

Directory of Open Access Journals (Sweden)

Albert-Baskar Arul

2013-06-01

Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

High-throughput theoretical design of lithium battery materials

International Nuclear Information System (INIS)

Ling Shi-Gang; Gao Jian; Xiao Rui-Juan; Chen Li-Quan

2016-01-01

The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is reviewed, including high-capacity cathodes, low-strain cathodes, anodes, solid state electrolytes, and electrolyte additives. With the development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new materials. With the help of automatic simulation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve performance, and some representative criteria are: higher energy density, better safety, and faster charge/discharge speed. (topical review)

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

Science.gov (United States)

Najafov, Jamil; Najafov, Ayaz

2017-07-19

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

Virulence Characterization of Salmonella enterica by a New Microarray: Detection and Evaluation of the Cytolethal Distending Toxin Gene Activity in the Unusual Host S. Typhimurium.

Directory of Open Access Journals (Sweden)

Rui Figueiredo

Full Text Available Salmonella enterica is a zoonotic foodborne pathogen that causes acute gastroenteritis in humans. We assessed the virulence potential of one-hundred and six Salmonella strains isolated from food animals and products. A high through-put virulence genes microarray demonstrated Salmonella Pathogenicity Islands (SPI and adherence genes were highly conserved, while prophages and virulence plasmid genes were variably present. Isolates were grouped by serotype, and virulence plasmids separated S. Typhimurium in two clusters. Atypical microarray results lead to whole genome sequencing (WGS of S. Infantis Sal147, which identified deletion of thirty-eight SPI-1 genes. Sal147 was unable to invade HeLa cells and showed reduced mortality in Galleria mellonella infection model, in comparison to a SPI-1 harbouring S. Infantis. Microarray and WGS of S. Typhimurium Sal199, established for the first time in S. Typhimurium presence of cdtB and other Typhi-related genes. Characterization of Sal199 showed cdtB genes were upstream of transposase IS911, and co-expressed with other Typhi-related genes. Cell cycle arrest, cytoplasmic distension, and nuclear enlargement were detected in HeLa cells infected by Sal199, but not with S. Typhimurium LT2. Increased mortality of Galleria was detected on infection with Sal199 compared to LT2. Thus, Salmonella isolates were rapidly characterized using a high through-put microarray; helping to identify unusual virulence features which were corroborated by further characterisation. This work demonstrates that the use of suitable screening methods for Salmonella virulence can help assess the potential risk associated with certain Salmonella to humans. Incorporation of such methodology into surveillance could help reduce the risk of emergence of epidemic Salmonella strains.

Screening for Antifibrotic Compounds Using High Throughput System Based on Fluorescence Polarization

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Branko Stefanovic

2014-04-01

Full Text Available Fibroproliferative diseases are one of the leading causes of death worldwide. They are characterized by reactive fibrosis caused by uncontrolled synthesis of type I collagen. There is no cure for fibrosis and development of therapeutics that can inhibit collagen synthesis is urgently needed. Collagen α1(I mRNA and α2(I mRNA encode for type I collagen and they have a unique 5' stem-loop structure in their 5' untranslated regions (5'SL. Collagen 5'SL binds protein LARP6 with high affinity and specificity. The interaction between LARP6 and the 5'SL is critical for biosynthesis of type I collagen and development of fibrosis in vivo. Therefore, this interaction represents is an ideal target to develop antifibrotic drugs. A high throughput system to screen for chemical compounds that can dissociate LARP6 from 5'SL has been developed. It is based on fluorescence polarization and can be adapted to screen for inhibitors of other protein-RNA interactions. Screening of 50,000 chemical compounds yielded a lead compound that can inhibit type I collagen synthesis at nanomolar concentrations. The development, characteristics, and critical appraisal of this assay are presented.

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

Directory of Open Access Journals (Sweden)

Ankush Prashar

Full Text Available The rapid development of genomic technology has made high throughput genotyping widely accessible but the associated high throughput phenotyping is now the major limiting factor in genetic analysis of traits. This paper evaluates the use of thermal imaging for the high throughput field phenotyping of Solanum tuberosum for differences in stomatal behaviour. A large multi-replicated trial of a potato mapping population was used to investigate the consistency in genotypic rankings across different trials and across measurements made at different times of day and on different days. The results confirmed a high degree of consistency between the genotypic rankings based on relative canopy temperature on different occasions. Genotype discrimination was enhanced both through normalising data by expressing genotype temperatures as differences from image means and through the enhanced replication obtained by using overlapping images. A Monte Carlo simulation approach was used to confirm the magnitude of genotypic differences that it is possible to discriminate. The results showed a clear negative association between canopy temperature and final tuber yield for this population, when grown under ample moisture supply. We have therefore established infrared thermography as an easy, rapid and non-destructive screening method for evaluating large population trials for genetic analysis. We also envisage this approach as having great potential for evaluating plant response to stress under field conditions.

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

Science.gov (United States)

Coolbaugh, M J; Shakalli Tang, M J; Wood, D W

2017-01-01

High throughput methods for recombinant protein production using E. coli typically involve the use of affinity tags for simple purification of the protein of interest. One drawback of these techniques is the occasional need for tag removal before study, which can be hard to predict. In this work, we demonstrate two high throughput purification methods for untagged protein targets based on simple and cost-effective self-cleaving intein tags. Two model proteins, E. coli beta-galactosidase (βGal) and superfolder green fluorescent protein (sfGFP), were purified using self-cleaving versions of the conventional chitin-binding domain (CBD) affinity tag and the nonchromatographic elastin-like-polypeptide (ELP) precipitation tag in a 96-well filter plate format. Initial tests with shake flask cultures confirmed that the intein purification scheme could be scaled down, with >90% pure product generated in a single step using both methods. The scheme was then validated in a high throughput expression platform using 24-well plate cultures followed by purification in 96-well plates. For both tags and with both target proteins, the purified product was consistently obtained in a single-step, with low well-to-well and plate-to-plate variability. This simple method thus allows the reproducible production of highly pure untagged recombinant proteins in a convenient microtiter plate format. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiplex Detection and Genotyping of Point Mutations Involved in Charcot-Marie-Tooth Disease Using a Hairpin Microarray-Based Assay

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Yasser Baaj

2009-01-01

Full Text Available We previously developed a highly specific method for detecting SNPs with a microarray-based system using stem-loop probes. In this paper we demonstrate that coupling a multiplexing procedure with our microarray method is possible for the simultaneous detection and genotyping of four point mutations, in three different genes, involved in Charcot-Marie-Tooth disease. DNA from healthy individuals and patients was amplified, labeled with Cy3 by multiplex PCR; and hybridized to microarrays. Spot signal intensities were 18 to 74 times greater for perfect matches than for mismatched target sequences differing by a single nucleotide (discrimination ratio for “homozygous” DNA from healthy individuals. “Heterozygous” mutant DNA samples gave signal intensity ratios close to 1 at the positions of the mutations as expected. Genotyping by this method was therefore reliable. This system now combines the principle of highly specific genotyping based on stem-loop structure probes with the advantages of multiplex analysis.

Targeted deposition of antibodies on a multiplex CMOS microarray and optimization of a sensitive immunoassay using electrochemical detection.

Directory of Open Access Journals (Sweden)

John Cooper

2010-03-01

Full Text Available The CombiMatrix ElectraSense microarray is a highly multiplex, complementary metal oxide semiconductor with 12,544 electrodes that are individually addressable. This platform is commercially available as a custom DNA microarray; and, in this configuration, it has also been used to tether antibodies (Abs specifically on electrodes using complementary DNA sequences conjugated to the Abs.An empirical method is described for developing and optimizing immunoassays on the CombiMatrix ElectraSense microarray based upon targeted deposition of polypyrrole (Ppy and capture Ab. This process was automated using instrumentation that can selectively apply a potential or current to individual electrodes and also measure current generated at the electrodes by an enzyme-enhanced electrochemical (ECD reaction. By designating groups of electrodes on the array for different Ppy deposition conditions, we determined that the sensitivity and specificity of a sandwich immunoassay for staphylococcal enterotoxin B (SEB is influenced by the application of different voltages or currents and the application time. The sandwich immunoassay used a capture Ab adsorbed to the Ppy and a reporter Ab labeled for fluorescence detection or ECD, and results from these methods of detection were different.Using Ppy deposition conditions for optimum results, the lower limit of detection for SEB using the ECD assay was between 0.003 and 0.01 pg/ml, which represents an order of magnitude improvement over a conventional enzyme-linked immunosorbant assay. In the absence of understanding the variables and complexities that affect assay performance, this highly multiplexed electrode array provided a rapid, high throughput, and empirical approach for developing a sensitive immunoassay.

High-Throughput Block Optical DNA Sequence Identification.

Science.gov (United States)

Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

2018-01-01

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

Science.gov (United States)

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

2015-10-06

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

High Throughput Plasma Water Treatment

Science.gov (United States)

Mujovic, Selman; Foster, John

2016-10-01

The troublesome emergence of new classes of micro-pollutants, such as pharmaceuticals and endocrine disruptors, poses challenges for conventional water treatment systems. In an effort to address these contaminants and to support water reuse in drought stricken regions, new technologies must be introduced. The interaction of water with plasma rapidly mineralizes organics by inducing advanced oxidation in addition to other chemical, physical and radiative processes. The primary barrier to the implementation of plasma-based water treatment is process volume scale up. In this work, we investigate a potentially scalable, high throughput plasma water reactor that utilizes a packed bed dielectric barrier-like geometry to maximize the plasma-water interface. Here, the water serves as the dielectric medium. High-speed imaging and emission spectroscopy are used to characterize the reactor discharges. Changes in methylene blue concentration and basic water parameters are mapped as a function of plasma treatment time. Experimental results are compared to electrostatic and plasma chemistry computations, which will provide insight into the reactor's operation so that efficiency can be assessed. Supported by NSF (CBET 1336375).

Microarray Dot Electrodes Utilizing Dielectrophoresis for Cell Characterization

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Fatimah Ibrahim

2013-07-01

Full Text Available During the last three decades; dielectrophoresis (DEP has become a vital tool for cell manipulation and characterization due to its non-invasiveness. It is very useful in the trend towards point-of-care systems. Currently, most efforts are focused on using DEP in biomedical applications, such as the spatial manipulation of cells, the selective separation or enrichment of target cells, high-throughput molecular screening, biosensors and immunoassays. A significant amount of research on DEP has produced a wide range of microelectrode configurations. In this paper; we describe the microarray dot electrode, a promising electrode geometry to characterize and manipulate cells via DEP. The advantages offered by this type of microelectrode are also reviewed. The protocol for fabricating planar microelectrodes using photolithography is documented to demonstrate the fast and cost-effective fabrication process. Additionally; different state-of-the-art Lab-on-a-Chip (LOC devices that have been proposed for DEP applications in the literature are reviewed. We also present our recently designed LOC device, which uses an improved microarray dot electrode configuration to address the challenges facing other devices. This type of LOC system has the capability to boost the implementation of DEP technology in practical settings such as clinical cell sorting, infection diagnosis, and enrichment of particle populations for drug development.

Integrative missing value estimation for microarray data.

Science.gov (United States)

Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine

2006-10-12

Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

High throughput salt separation from uranium deposits

Energy Technology Data Exchange (ETDEWEB)

Kwon, S.W.; Park, K.M.; Kim, J.G.; Kim, I.T.; Park, S.B., E-mail: swkwon@kaeri.re.kr [Korea Atomic Energy Research Inst. (Korea, Republic of)

2014-07-01

It is very important to increase the throughput of the salt separation system owing to the high uranium content of spent nuclear fuel and high salt fraction of uranium dendrites in pyroprocessing. Multilayer porous crucible system was proposed to increase a throughput of the salt distiller in this study. An integrated sieve-crucible assembly was also investigated for the practical use of the porous crucible system. The salt evaporation behaviors were compared between the conventional nonporous crucible and the porous crucible. Two step weight reductions took place in the porous crucible, whereas the salt weight reduced only at high temperature by distillation in a nonporous crucible. The first weight reduction in the porous crucible was caused by the liquid salt penetrated out through the perforated crucible during the temperature elevation until the distillation temperature. Multilayer porous crucibles have a benefit to expand the evaporation surface area. (author)

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

International Nuclear Information System (INIS)

Tani, Hidenori; Akimitsu, Nobuyoshi; Fujita, Osamu; Matsuda, Yasuyoshi; Miyata, Ryo; Tsuneda, Satoshi; Igarashi, Masayuki; Sekiguchi, Yuji; Noda, Naohiro

2009-01-01

We have developed a novel high-throughput screening assay of hepatitis C virus (HCV) nonstructural protein 3 (NS3) helicase inhibitors using the fluorescence-quenching phenomenon via photoinduced electron transfer between fluorescent dyes and guanine bases. We prepared double-stranded DNA (dsDNA) with a 5'-fluorescent-dye (BODIPY FL)-labeled strand hybridized with a complementary strand, the 3'-end of which has guanine bases. When dsDNA is unwound by helicase, the dye emits fluorescence owing to its release from the guanine bases. Our results demonstrate that this assay is suitable for quantitative assay of HCV NS3 helicase activity and useful for high-throughput screening for inhibitors. Furthermore, we applied this assay to the screening for NS3 helicase inhibitors from cell extracts of microorganisms, and found several cell extracts containing potential inhibitors.

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

DEFF Research Database (Denmark)

Tiendrebeogo, Regis W; Adu, Bright; Singh, Susheel K

2014-01-01

BACKGROUND: Unbiased flow cytometry-based methods have become the technique of choice in many laboratories for high-throughput, accurate assessments of malaria parasites in bioassays. A method to quantify live parasites based on mitotracker red CMXRos was recently described but consistent...... distinction of early ring stages of Plasmodium falciparum from uninfected red blood cells (uRBC) remains a challenge. METHODS: Here, a high-throughput, three-parameter (tri-colour) flow cytometry technique based on mitotracker red dye, the nucleic acid dye coriphosphine O (CPO) and the leucocyte marker CD45...... for enumerating live parasites in bioassays was developed. The technique was applied to estimate the specific growth inhibition index (SGI) in the antibody-dependent cellular inhibition (ADCI) assay and compared to parasite quantification by microscopy and mitotracker red staining. The Bland-Altman analysis...

High-throughput microfluidics automated cytogenetic processing for effectively lowering biological process time and aid triage during radiation accidents

International Nuclear Information System (INIS)

Ramakumar, Adarsh

2016-01-01

Nuclear or radiation mass casualties require individual, rapid, and accurate dose-based triage of exposed subjects for cytokine therapy and supportive care, to save life. Radiation mass casualties will demand high-throughput individual diagnostic dose assessment for medical management of exposed subjects. Cytogenetic techniques are widely used for triage and definitive radiation biodosimetry. Prototype platform to demonstrate high-throughput microfluidic micro incubation to support the logistics of sample in miniaturized incubators from the site of accident to analytical labs has been developed. Efforts have been made, both at the level of developing concepts and advanced system for higher throughput in processing the samples and also implementing better and efficient methods of logistics leading to performance of lab-on-chip analyses. Automated high-throughput platform with automated feature extraction, storage, cross platform data linkage, cross platform validation and inclusion of multi-parametric biomarker approaches will provide the first generation high-throughput platform systems for effective medical management, particularly during radiation mass casualty events

Crystal Symmetry Algorithms in a High-Throughput Framework for Materials

Science.gov (United States)

Taylor, Richard

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

Development of Control Applications for High-Throughput Protein Crystallography Experiments

International Nuclear Information System (INIS)

Gaponov, Yurii A.; Matsugaki, Naohiro; Honda, Nobuo; Sasajima, Kumiko; Igarashi, Noriyuki; Hiraki, Masahiko; Yamada, Yusuke; Wakatsuki, Soichi

2007-01-01

An integrated client-server control system (PCCS) with a unified relational database (PCDB) has been developed for high-throughput protein crystallography experiments on synchrotron beamlines. The major steps in protein crystallographic experiments (purification, crystallization, crystal harvesting, data collection, and data processing) are integrated into the software. All information necessary for performing protein crystallography experiments is stored in the PCDB database (except raw X-ray diffraction data, which is stored in the Network File Server). To allow all members of a protein crystallography group to participate in experiments, the system was developed as a multi-user system with secure network access based on TCP/IP secure UNIX sockets. Secure remote access to the system is possible from any operating system with X-terminal and SSH/X11 (Secure Shell with graphical user interface) support. Currently, the system covers the high-throughput X-ray data collection stages and is being commissioned at BL5A and NW12A (PF, PF-AR, KEK, Tsukuba, Japan)

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

NARCIS (Netherlands)

Nas, R.J.M.; Berkel, van C.H.

2010-01-01

This paper presents a hardware design for a scalable, high throughput, configurable LFSR. High throughput is achieved by producing L consecutive outputs per clock cycle with a clock cycle period that, for practical cases, increases only logarithmically with the block size L and the length of the

High-throughput epitope identification for snakebite antivenom

DEFF Research Database (Denmark)

Engmark, Mikael; De Masi, Federico; Laustsen, Andreas Hougaard

Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individua...... toxins from pit vipers (Crotalidae) using the ICP Crotalidae antivenom. Due to an abundance of snake venom metalloproteinases and phospholipase A2s in the venoms used for production of the investigated antivenom, this study focuses on these toxin families.......Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individual...

eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

Science.gov (United States)

Liu, Robin H.; Longiaru, Mathew

2009-05-01

DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

DESIGN OF LOW EPI AND HIGH THROUGHPUT CORDIC CELL TO IMPROVE THE PERFORMANCE OF MOBILE ROBOT

Directory of Open Access Journals (Sweden)

P. VELRAJKUMAR

2014-04-01

Full Text Available This paper mainly focuses on pass logic based design, which gives an low Energy Per Instruction (EPI and high throughput COrdinate Rotation Digital Computer (CORDIC cell for application of robotic exploration. The basic components of CORDIC cell namely register, multiplexer and proposed adder is designed using pass transistor logic (PTL design. The proposed adder is implemented in bit-parallel iterative CORDIC circuit whereas designed using DSCH2 VLSI CAD tool and their layouts are generated by Microwind 3 VLSI CAD tool. The propagation delay, area and power dissipation are calculated from the simulated results for proposed adder based CORDIC cell. The EPI, throughput and effect of temperature are calculated from generated layout. The output parameter of generated layout is analysed using BSIM4 advanced analyzer. The simulated result of the proposed adder based CORDIC circuit is compared with other adder based CORDIC circuits. From the analysis of these simulated results, it was found that the proposed adder based CORDIC circuit dissipates low power, gives faster response, low EPI and high throughput.

O arranjo em matriz de amostras teciduais (tissue microarray: larga escala e baixo custo ao alcance do patologista Tissue microarrays: high throughput and low cost avaiable for pathologists

Directory of Open Access Journals (Sweden)

Victor Piana de Andrade

2007-02-01

Full Text Available O arranjo em matriz de amostras teciduais, ou tissue microarray (TMA, é uma técnica descrita em 1998 por Kononen et al. com ampla aceitação pela literatura mundial. Com um conceito extremamente simples, trata-se de agrupar um grande número de amostras teciduais em um único bloco de parafina, permitindo o estudo de expressão de marcadores moleculares em larga escala com grande aproveitamento do material arquivado, do tempo e dos custos. Discutimos as vantagens e limitações do método, as estratégias e técnica de construção, as aplicações e dificuldades encontradas para a patologia investigativa nos últimos cinco anos de uso no Hospital do Câncer A. C. Camargo.Tissue microarrays (TMA is a worldwide well accepted technique described in 1998 by Kononen et al. It uses an extremely simple concept of ordering hundreds of samples in just one paraffin block to evaluate protein expression in large cohorts with great advantages on costs, time and sample saving. We discuss the technique, its advantages and limitations, strategies to construct the receptor block, its usefulness and difficulties experienced in the last five years at Hospital do Cancer A.C. Camargo.

Chromatographic Monoliths for High-Throughput Immunoaffinity Isolation of Transferrin from Human Plasma

Directory of Open Access Journals (Sweden)

Irena Trbojević-Akmačić

2016-06-01

Full Text Available Changes in protein glycosylation are related to different diseases and have a potential as diagnostic and prognostic disease biomarkers. Transferrin (Tf glycosylation changes are common marker for congenital disorders of glycosylation. However, biological interindividual variability of Tf N-glycosylation and genes involved in glycosylation regulation are not known. Therefore, high-throughput Tf isolation method and large scale glycosylation studies are needed in order to address these questions. Due to their unique chromatographic properties, the use of chromatographic monoliths enables very fast analysis cycle, thus significantly increasing sample preparation throughput. Here, we are describing characterization of novel immunoaffinity-based monolithic columns in a 96-well plate format for specific high-throughput purification of human Tf from blood plasma. We optimized the isolation and glycan preparation procedure for subsequent ultra performance liquid chromatography (UPLC analysis of Tf N-glycosylation and managed to increase the sensitivity for approximately three times compared to initial experimental conditions, with very good reproducibility. This work is licensed under a Creative Commons Attribution 4.0 International License.

High-throughput selection for cellulase catalysts using chemical complementation.

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T; Lin, Hening; Tao, Haiyan; Cornish, Virginia W

2008-12-24

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases, however, is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Because of the large number of enzyme variants that selections can now test as compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity.

Correction of Microplate Data from High-Throughput Screening.

Science.gov (United States)

Wang, Yuhong; Huang, Ruili

2016-01-01

High-throughput screening (HTS) makes it possible to collect cellular response data from a large number of cell lines and small molecules in a timely and cost-effective manner. The errors and noises in the microplate-formatted data from HTS have unique characteristics, and they can be generally grouped into three categories: run-wise (temporal, multiple plates), plate-wise (background pattern, single plate), and well-wise (single well). In this chapter, we describe a systematic solution for identifying and correcting such errors and noises, mainly basing on pattern recognition and digital signal processing technologies.

Filter Paper-based Nucleic Acid Storage in High-throughput Solid Tumor Genotyping.

Science.gov (United States)

Stachler, Matthew; Jia, Yonghui; Sharaf, Nematullah; Wade, Jacqueline; Longtine, Janina; Garcia, Elizabeth; Sholl, Lynette M

2015-01-01

Molecular testing of tumors from formalin-fixed paraffin-embedded (FFPE) tissue blocks is central to clinical practice; however, it requires histology support and increases test turnaround time. Prospective fresh frozen tissue collection requires special handling, additional storage space, and may not be feasible for small specimens. Filter paper-based collection of tumor DNA reduces the need for histology support, requires little storage space, and preserves high-quality nucleic acid. We investigated the performance of tumor smears on filter paper in solid tumor genotyping, as compared with paired FFPE samples. Whatman FTA Micro Card (FTA preps) smears were prepared from 21 fresh tumor samples. A corresponding cytology smear was used to assess tumor cellularity and necrosis. DNA was isolated from FTA preps and FFPE core samples using automated methods and quantified using SYBR green dsDNA detection. Samples were genotyped for 471 mutations on a mass spectrophotometry-based platform (Sequenom). DNA concentrations from FTA preps and FFPE correlated for untreated carcinomas but not for mesenchymal tumors (Spearman σ=0.39 and σ=-0.1, respectively). Average DNA concentrations were lower from FTA preps as compared with FFPE, but DNA quality was higher with less fragmentation. Seventy-six percent of FTA preps and 86% of FFPE samples generated adequate DNA for genotyping. FTA preps tended to perform poorly for collection of DNA from pretreated carcinomas and mesenchymal neoplasms. Of the 16 paired DNA samples that were genotyped, 15 (94%) gave entirely concordant results. Filter paper-based sample preservation is a feasible alternative to FFPE for use in automated, high-throughput genotyping of carcinomas.

Toward reliable and repeatable automated STEM-EDS metrology with high throughput

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Zhong, Zhenxin; Donald, Jason; Dutrow, Gavin; Roller, Justin; Ugurlu, Ozan; Verheijen, Martin; Bidiuk, Oleksii

2018-03-01

New materials and designs in complex 3D architectures in logic and memory devices have raised complexity in S/TEM metrology. In this paper, we report about a newly developed, automated, scanning transmission electron microscopy (STEM) based, energy dispersive X-ray spectroscopy (STEM-EDS) metrology method that addresses these challenges. Different methodologies toward repeatable and efficient, automated STEM-EDS metrology with high throughput are presented: we introduce the best known auto-EDS acquisition and quantification methods for robust and reliable metrology and present how electron exposure dose impacts the EDS metrology reproducibility, either due to poor signalto-noise ratio (SNR) at low dose or due to sample modifications at high dose conditions. Finally, we discuss the limitations of the STEM-EDS metrology technique and propose strategies to optimize the process both in terms of throughput and metrology reliability.

Combination of Small Molecule Microarray and Confocal Microscopy Techniques for Live Cell Staining Fluorescent Dye Discovery

Directory of Open Access Journals (Sweden)

Attila Bokros

2013-08-01

Full Text Available Discovering new fluorochromes is significantly advanced by high-throughput screening (HTS methods. In the present study a combination of small molecule microarray (SMM prescreening and confocal laser scanning microscopy (CLSM was developed in order to discover novel cell staining fluorescent dyes. Compounds with high native fluorescence were selected from a 14,585-member library and further tested on living cells under the microscope. Eleven compartment-specific, cell-permeable (or plasma membrane-targeted fluorochromes were identified. Their cytotoxicity was tested and found that between 1–10 micromolar range, they were non-toxic even during long-term incubations.

Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

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Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

2014-01-01

The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

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

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Resendis-Antonio Osbaldo

2011-07-01

Full Text Available Abstract Background Bacterial nitrogen fixation is the biological process by which atmospheric nitrogen is uptaken by bacteroids located in plant root nodules and converted into ammonium through the enzymatic activity of nitrogenase. In practice, this biological process serves as a natural form of fertilization and its optimization has significant implications in sustainable agricultural programs. Currently, the advent of high-throughput technology supplies with valuable data that contribute to understanding the metabolic activity during bacterial nitrogen fixation. This undertaking is not trivial, and the development of computational methods useful in accomplishing an integrative, descriptive and predictive framework is a crucial issue to decoding the principles that regulated the metabolic activity of this biological process. Results In this work we present a systems biology description of the metabolic activity in bacterial nitrogen fixation. This was accomplished by an integrative analysis involving high-throughput data and constraint-based modeling to characterize the metabolic activity in Rhizobium etli bacteroids located at the root nodules of Phaseolus vulgaris (bean plant. Proteome and transcriptome technologies led us to identify 415 proteins and 689 up-regulated genes that orchestrate this biological process. Taking into account these data, we: 1 extended the metabolic reconstruction reported for R. etli; 2 simulated the metabolic activity during symbiotic nitrogen fixation; and 3 evaluated the in silico results in terms of bacteria phenotype. Notably, constraint-based modeling simulated nitrogen fixation activity in such a way that 76.83% of the enzymes and 69.48% of the genes were experimentally justified. Finally, to further assess the predictive scope of the computational model, gene deletion analysis was carried out on nine metabolic enzymes. Our model concluded that an altered metabolic activity on these enzymes induced

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

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Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

2008-01-23

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

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

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Gurard-Levin, Zachary A; Scholle, Michael D; Eisenberg, Adam H; Mrksich, Milan

2011-07-11

High-throughput screening is a common strategy used to identify compounds that modulate biochemical activities, but many approaches depend on cumbersome fluorescent reporters or antibodies and often produce false-positive hits. The development of "label-free" assays addresses many of these limitations, but current approaches still lack the throughput needed for applications in drug discovery. This paper describes a high-throughput, label-free assay that combines self-assembled monolayers with mass spectrometry, in a technique called SAMDI, as a tool for screening libraries of 100,000 compounds in one day. This method is fast, has high discrimination, and is amenable to a broad range of chemical and biological applications.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

High-throughput Transcriptome analysis, CAGE and beyond

KAUST Repository

Kodzius, Rimantas

2008-11-25

1. Current research - PhD work on discovery of new allergens - Postdoctoral work on Transcriptional Start Sites a) Tag based technologies allow higher throughput b) CAGE technology to define promoters c) CAGE data analysis to understand Transcription - Wo

High-throughput Transcriptome analysis, CAGE and beyond

KAUST Repository

Kodzius, Rimantas

2008-01-01

1. Current research - PhD work on discovery of new allergens - Postdoctoral work on Transcriptional Start Sites a) Tag based technologies allow higher throughput b) CAGE technology to define promoters c) CAGE data analysis to understand Transcription - Wo

Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens

International Nuclear Information System (INIS)

Stempfer, René; Weinhäusel, Andreas; Syed, Parvez; Vierlinger, Klemens; Pichler, Rudolf; Meese, Eckart; Leidinger, Petra; Ludwig, Nicole; Kriegner, Albert; Nöhammer, Christa

2010-01-01

The simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate. Candidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients. Methods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly. Protein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto

Generation and analyses of human synthetic antibody libraries and their application for protein microarrays.

Science.gov (United States)

Säll, Anna; Walle, Maria; Wingren, Christer; Müller, Susanne; Nyman, Tomas; Vala, Andrea; Ohlin, Mats; Borrebaeck, Carl A K; Persson, Helena

2016-10-01

Antibody-based proteomics offers distinct advantages in the analysis of complex samples for discovery and validation of biomarkers associated with disease. However, its large-scale implementation requires tools and technologies that allow development of suitable antibody or antibody fragments in a high-throughput manner. To address this we designed and constructed two human synthetic antibody fragment (scFv) libraries denoted HelL-11 and HelL-13. By the use of phage display technology, in total 466 unique scFv antibodies specific for 114 different antigens were generated. The specificities of these antibodies were analyzed in a variety of immunochemical assays and a subset was further evaluated for functionality in protein microarray applications. This high-throughput approach demonstrates the ability to rapidly generate a wealth of reagents not only for proteome research, but potentially also for diagnostics and therapeutics. In addition, this work provides a great example on how a synthetic approach can be used to optimize library designs. By having precise control of the diversity introduced into the antigen-binding sites, synthetic libraries offer increased understanding of how different diversity contributes to antibody binding reactivity and stability, thereby providing the key to future library optimization. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The JCSG high-throughput structural biology pipeline

International Nuclear Information System (INIS)

Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wooley, John; Wüthrich, Kurt; Wilson, Ian A.

2010-01-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years and has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe. The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications

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

Science.gov (United States)

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

2017-02-21

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

Profiling Humoral Immune Responses to Clostridium difficile-Specific Antigens by Protein Microarray Analysis.

Science.gov (United States)

Negm, Ola H; Hamed, Mohamed R; Dilnot, Elizabeth M; Shone, Clifford C; Marszalowska, Izabela; Lynch, Mark; Loscher, Christine E; Edwards, Laura J; Tighe, Patrick J; Wilcox, Mark H; Monaghan, Tanya M

2015-09-01

Clostridium difficile is an anaerobic, Gram-positive, and spore-forming bacterium that is the leading worldwide infective cause of hospital-acquired and antibiotic-associated diarrhea. Several studies have reported associations between humoral immunity and the clinical course of C. difficile infection (CDI). Host humoral immune responses are determined using conventional enzyme-linked immunosorbent assay (ELISA) techniques. Herein, we report the first use of a novel protein microarray assay to determine systemic IgG antibody responses against a panel of highly purified C. difficile-specific antigens, including native toxins A and B (TcdA and TcdB, respectively), recombinant fragments of toxins A and B (TxA4 and TxB4, respectively), ribotype-specific surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). Microarrays were probed with sera from a total of 327 individuals with CDI, cystic fibrosis without diarrhea, and healthy controls. For all antigens, precision profiles demonstrated ELISA in the quantification of antitoxin A and antitoxin B IgG. These results indicate that microarray is a suitable assay for defining humoral immune responses to C. difficile protein antigens and may have potential advantages in throughput, convenience, and cost. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Development and validation of a 48-target analytical method for high-throughput monitoring of genetically modified organisms.

Science.gov (United States)

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-05

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection.

Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

Directory of Open Access Journals (Sweden)

Gravelat Fabrice

2010-09-01

Full Text Available Abstract Background Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. Results First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality can be used to study a complex environment efficiently. Conclusions We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments

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

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Guangbo Liu

Full Text Available Saccharomyces cerevisiae (budding yeast is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids or genome mutation (e.g., gene mutation, deletion, epitope tagging is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

Current Knowledge on Microarray Technology - An Overview

African Journals Online (AJOL)

Erah

This paper reviews basics and updates of each microarray technology and serves to .... through protein microarrays. Protein microarrays also known as protein chips are nothing but grids that ... conditioned media, patient sera, plasma and urine. Clontech ... based antibody arrays) is similar to membrane-based antibody ...

Comparing microarrays and next-generation sequencing technologies for microbial ecology research.

Science.gov (United States)

Roh, Seong Woon; Abell, Guy C J; Kim, Kyoung-Ho; Nam, Young-Do; Bae, Jin-Woo

2010-06-01

Recent advances in molecular biology have resulted in the application of DNA microarrays and next-generation sequencing (NGS) technologies to the field of microbial ecology. This review aims to examine the strengths and weaknesses of each of the methodologies, including depth and ease of analysis, throughput and cost-effectiveness. It also intends to highlight the optimal application of each of the individual technologies toward the study of a particular environment and identify potential synergies between the two main technologies, whereby both sample number and coverage can be maximized. We suggest that the efficient use of microarray and NGS technologies will allow researchers to advance the field of microbial ecology, and importantly, improve our understanding of the role of microorganisms in their various environments.

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

Science.gov (United States)

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.

Integrative missing value estimation for microarray data

Directory of Open Access Journals (Sweden)

Zhou Xianghong

2006-10-01

Full Text Available Abstract Background Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. Results We present the integrative Missing Value Estimation method (iMISS by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS imputation algorithm by up to 15% improvement in our benchmark tests. Conclusion We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

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

Science.gov (United States)

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

2014-01-01

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

3D material cytometry (3DMaC): a very high-replicate, high-throughput analytical method using microfabricated, shape-specific, cell-material niches.

Science.gov (United States)

Parratt, Kirsten; Jeong, Jenny; Qiu, Peng; Roy, Krishnendu

2017-08-08

Studying cell behavior within 3D material niches is key to understanding cell biology in health and diseases, and developing biomaterials for regenerative medicine applications. Current approaches to studying these cell-material niches have low throughput and can only analyze a few replicates per experiment resulting in reduced measurement assurance and analytical power. Here, we report 3D material cytometry (3DMaC), a novel high-throughput method based on microfabricated, shape-specific 3D cell-material niches and imaging cytometry. 3DMaC achieves rapid and highly multiplexed analyses of very high replicate numbers ("n" of 10 4 -10 6 ) of 3D biomaterial constructs. 3DMaC overcomes current limitations of low "n", low-throughput, and "noisy" assays, to provide rapid and simultaneous analyses of potentially hundreds of parameters in 3D biomaterial cultures. The method is demonstrated here for a set of 85 000 events containing twelve distinct cell-biomaterial micro-niches along with robust, customized computational methods for high-throughput analytics with potentially unprecedented statistical power.

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

Science.gov (United States)

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

2018-01-01

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

Development and operation of a high-throughput accurate-wavelength lens-based spectrometer

Energy Technology Data Exchange (ETDEWEB)

Bell, Ronald E., E-mail: rbell@pppl.gov [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States)

2014-11-15

A high-throughput spectrometer for the 400–820 nm wavelength range has been developed for charge exchange recombination spectroscopy or general spectroscopy. A large 2160 mm{sup −1} grating is matched with fast f/1.8 200 mm lenses, which provide stigmatic imaging. A precision optical encoder measures the grating angle with an accuracy ≤0.075 arc sec. A high quantum efficiency low-etaloning CCD detector allows operation at longer wavelengths. A patch panel allows input fibers to interface with interchangeable fiber holders that attach to a kinematic mount at the entrance slit. Computer-controlled hardware allows automated control of wavelength, timing, f-number, automated data collection, and wavelength calibration.

Genomotyping of Pseudomonas putida strains using P. putida KT2440-based high-density DNA microarrays: Implications for transcriptomics studies

NARCIS (Netherlands)

Ballerstedt, H.; Volkers, R.J.M.; Mars, A.E.; Hallsworth, J.E.; Santos, V.A.M.D.; Puchalka, J.; Duuren, J. van; Eggink, G.; Timmis, K.N.; Bont, J.A.M. de; Wery, J.

2007-01-01

Pseudomonas putida KT2440 is the only fully sequenced P. putida strain. Thus, for transcriptomics and proteomics studies with other P. putida strains, the P. putida KT2440 genomic database serves as standard reference. The utility of KT2440 whole-genome, high-density oligonucleotide microarrays for

Incorporation of gene-specific variability improves expression analysis using high-density DNA microarrays

Directory of Open Access Journals (Sweden)

Spitznagel Edward

2003-11-01

Full Text Available Abstract Background The assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed. Results We used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates. Conclusion The strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http://www.sadovsky.wustl.edu/tscore.html.

High-Throughput Next-Generation Sequencing of Polioviruses

Science.gov (United States)

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

2016-01-01

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

An algorithm for finding biologically significant features in microarray data based on a priori manifold learning.

Directory of Open Access Journals (Sweden)

Zena M Hira

Full Text Available Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap.

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

National Research Council Canada - National Science Library

Boger, Dale L

2005-01-01

.... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

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

National Research Council Canada - National Science Library

Boger, Dale

2004-01-01

.... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

Creation of a small high-throughput screening facility.

Science.gov (United States)

Flak, Tod

2009-01-01

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

A CRISPR CASe for High-Throughput Silencing

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Jacob eHeintze

2013-10-01

Full Text Available Manipulation of gene expression on a genome-wide level is one of the most important systematic tools in the post-genome era. Such manipulations have largely been enabled by expression cloning approaches using sequence-verified cDNA libraries, large-scale RNA interference libraries (shRNA or siRNA and zinc finger nuclease technologies. More recently, the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated (Cas9-mediated gene editing technology has been described that holds great promise for future use of this technology in genomic manipulation. It was suggested that the CRISPR system has the potential to be used in high-throughput, large-scale loss of function screening. Here we discuss some of the challenges in engineering of CRISPR/Cas genomic libraries and some of the aspects that need to be addressed in order to use this technology on a high-throughput scale.

High throughput route selection in multi-rate wireless mesh networks

Institute of Scientific and Technical Information of China (English)

WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

2008-01-01

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

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

Science.gov (United States)

Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays DE DeGroot, RS Thomas, and SO SimmonsNational Center for Computational Toxicology, US EPA, Research Triangle Park, NC USAThe EPA’s ToxCast program utilizes a wide variety of high-throughput s...

Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

Directory of Open Access Journals (Sweden)

Jianping Hua

2004-01-01

Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

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

Science.gov (United States)

Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

2012-05-01

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-12-10

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

Detection of genomic variation by selection of a 9 mb DNA region and high throughput sequencing.

Directory of Open Access Journals (Sweden)

Sergey I Nikolaev

Full Text Available Detection of the rare polymorphisms and causative mutations of genetic diseases in a targeted genomic area has become a major goal in order to understand genomic and phenotypic variability. We have interrogated repeat-masked regions of 8.9 Mb on human chromosomes 21 (7.8 Mb and 7 (1.1 Mb from an individual from the International HapMap Project (NA12872. We have optimized a method of genomic selection for high throughput sequencing. Microarray-based selection and sequencing resulted in 260-fold enrichment, with 41% of reads mapping to the target region. 83% of SNPs in the targeted region had at least 4-fold sequence coverage and 54% at least 15-fold. When assaying HapMap SNPs in NA12872, our sequence genotypes are 91.3% concordant in regions with coverage > or = 4-fold, and 97.9% concordant in regions with coverage > or = 15-fold. About 81% of the SNPs recovered with both thresholds are listed in dbSNP. We observed that regions with low sequence coverage occur in close proximity to low-complexity DNA. Validation experiments using Sanger sequencing were performed for 46 SNPs with 15-20 fold coverage, with a confirmation rate of 96%, suggesting that DNA selection provides an accurate and cost-effective method for identifying rare genomic variants.

HTTK: R Package for High-Throughput Toxicokinetics

Science.gov (United States)

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

A High-Throughput SU-8Microfluidic Magnetic Bead Separator

DEFF Research Database (Denmark)

Bu, Minqiang; Christensen, T. B.; Smistrup, Kristian

2007-01-01

We present a novel microfluidic magnetic bead separator based on SU-8 fabrication technique for high through-put applications. The experimental results show that magnetic beads can be captured at an efficiency of 91 % and 54 % at flow rates of 1 mL/min and 4 mL/min, respectively. Integration...... of soft magnetic elements in the chip leads to a slightly higher capturing efficiency and a more uniform distribution of captured beads over the separation chamber than the system without soft magnetic elements....

High-throughput genotyping of single nucleotide polymorphisms with rolling circle amplification

Directory of Open Access Journals (Sweden)

Sun Zhenyu

2001-08-01

Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs are the foundation of powerful complex trait and pharmacogenomic analyses. The availability of large SNP databases, however, has emphasized a need for inexpensive SNP genotyping methods of commensurate simplicity, robustness, and scalability. We describe a solution-based, microtiter plate method for SNP genotyping of human genomic DNA. The method is based upon allele discrimination by ligation of open circle probes followed by rolling circle amplification of the signal using fluorescent primers. Only the probe with a 3' base complementary to the SNP is circularized by ligation. Results SNP scoring by ligation was optimized to a 100,000 fold discrimination against probe mismatched to the SNP. The assay was used to genotype 10 SNPs from a set of 192 genomic DNA samples in a high-throughput format. Assay directly from genomic DNA eliminates the need to preamplify the target as done for many other genotyping methods. The sensitivity of the assay was demonstrated by genotyping from 1 ng of genomic DNA. We demonstrate that the assay can detect a single molecule of the circularized probe. Conclusions Compatibility with homogeneous formats and the ability to assay small amounts of genomic DNA meets the exacting requirements of automated, high-throughput SNP scoring.

Galaxy Workflows for Web-based Bioinformatics Analysis of Aptamer High-throughput Sequencing Data

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William H Thiel

2016-01-01

Full Text Available Development of RNA and DNA aptamers for diagnostic and therapeutic applications is a rapidly growing field. Aptamers are identified through iterative rounds of selection in a process termed SELEX (Systematic Evolution of Ligands by EXponential enrichment. High-throughput sequencing (HTS revolutionized the modern SELEX process by identifying millions of aptamer sequences across multiple rounds of aptamer selection. However, these vast aptamer HTS datasets necessitated bioinformatics techniques. Herein, we describe a semiautomated approach to analyze aptamer HTS datasets using the Galaxy Project, a web-based open source collection of bioinformatics tools that were originally developed to analyze genome, exome, and transcriptome HTS data. Using a series of Workflows created in the Galaxy webserver, we demonstrate efficient processing of aptamer HTS data and compilation of a database of unique aptamer sequences. Additional Workflows were created to characterize the abundance and persistence of aptamer sequences within a selection and to filter sequences based on these parameters. A key advantage of this approach is that the online nature of the Galaxy webserver and its graphical interface allow for the analysis of HTS data without the need to compile code or install multiple programs.

High-Throughput Network Communication with NetIO

CERN Document Server

Schumacher, J\\"orn; The ATLAS collaboration; Vandelli, Wainer

2016-01-01

HPC network technologies like Infiniband, TrueScale or OmniPath provide low-latency and high-throughput communication between hosts, which makes them attractive options for data-acquisition systems in large-scale high-energy physics experiments. Like HPC networks, DAQ networks are local and include a well specified number of systems. Unfortunately traditional network communication APIs for HPC clusters like MPI or PGAS target exclusively the HPC community and are not suited well for DAQ applications. It is possible to build distributed DAQ applications using low-level system APIs like Infiniband Verbs (and this has been done), but it requires a non negligible effort and expert knowledge. On the other hand, message services like 0MQ have gained popularity in the HEP community. Such APIs allow to build distributed applications with a high-level approach and provide good performance. Unfortunately their usage usually limits developers to TCP/IP-based networks. While it is possible to operate a TCP/IP stack on to...

High-throughput cell-based screening reveals a role for ZNF131 as a repressor of ERalpha signaling

Directory of Open Access Journals (Sweden)

Du Peige

2008-10-01

Full Text Available Abstract Background Estrogen receptor α (ERα is a transcription factor whose activity is affected by multiple regulatory cofactors. In an effort to identify the human genes involved in the regulation of ERα, we constructed a high-throughput, cell-based, functional screening platform by linking a response element (ERE with a reporter gene. This allowed the cellular activity of ERα, in cells cotransfected with the candidate gene, to be quantified in the presence or absence of its cognate ligand E2. Results From a library of 570 human cDNA clones, we identified zinc finger protein 131 (ZNF131 as a repressor of ERα mediated transactivation. ZNF131 is a typical member of the BTB/POZ family of transcription factors, and shows both ubiquitous expression and a high degree of sequence conservation. The luciferase reporter gene assay revealed that ZNF131 inhibits ligand-dependent transactivation by ERα in a dose-dependent manner. Electrophoretic mobility shift assay clearly demonstrated that the interaction between ZNF131 and ERα interrupts or prevents ERα binding to the estrogen response element (ERE. In addition, ZNF131 was able to suppress the expression of pS2, an ERα target gene. Conclusion We suggest that the functional screening platform we constructed can be applied for high-throughput genomic screening candidate ERα-related genes. This in turn may provide new insights into the underlying molecular mechanisms of ERα regulation in mammalian cells.

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

Directory of Open Access Journals (Sweden)

Gavin C. Bowick

2011-05-01

Full Text Available The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

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

NARCIS (Netherlands)

Gego, A.; Silvie, O.; Franetich, J.F.; Farhati, K.; Hannoun, L.; Luty, A.J.F.; Sauerwein, R.W.; Boucheix, C.; Rubinstein, E.; Mazier, D.

2006-01-01

Plasmodium liver stages represent potential targets for antimalarial prophylactic drugs. Nevertheless, there is a lack of molecules active on these stages. We have now developed a new approach for the high-throughput screening of drug activity on Plasmodium liver stages in vitro, based on an

Autoregressive-model-based missing value estimation for DNA microarray time series data.

Science.gov (United States)

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Design of a High-Throughput Biological Crystallography Beamline for Superconducting Wiggler

International Nuclear Information System (INIS)

Tseng, P.C.; Chang, C.H.; Fung, H.S.; Ma, C.I.; Huang, L.J.; Jean, Y.C.; Song, Y.F.; Huang, Y.S.; Tsang, K.L.; Chen, C.T.

2004-01-01

We are constructing a high-throughput biological crystallography beamline BL13B, which utilizes the radiation generated from a 3.2 Tesla, 32-pole superconducting multipole wiggler, for multi-wavelength anomalous diffraction (MAD), single-wavelength anomalous diffraction (SAD), and other related experiments. This beamline is a standard double crystal monochromator (DCM) x-ray beamline equipped with a collimating mirror (CM) and a focusing mirror (FM). Both the CM and FM are one meter long and made of Si substrate, and the CM is side-cooled by water. Based on detailed thermal analysis, liquid nitrogen (LN2) cooling for both crystals of the DCM has been adopted to optimize the energy resolution and photon beam throughput. This beamline will deliver, through a 100 μm diameter pinhole, photon flux of greater than 1011 photons/sec in the energy range from 6.5 keV to 19 keV, which is comparable to existing protein crystallography beamlines from bending magnet source at high energy storage rings

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

Directory of Open Access Journals (Sweden)

Viti Federica

2008-04-01

Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

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

CERN Document Server

Lapington, J S; Miller, G M; Ashton, T J R; Jarron, P; Despeisse, M; Powolny, F; Howorth, J; Milnes, J

2009-01-01

High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchanne...

The development of a high-throughput measurement method of octanol/water distribution coefficient based on hollow fiber membrane solvent microextraction technique.

Science.gov (United States)

Bao, James J; Liu, Xiaojing; Zhang, Yong; Li, Youxin

2014-09-15

This paper describes the development of a novel high-throughput hollow fiber membrane solvent microextraction technique for the simultaneous measurement of the octanol/water distribution coefficient (logD) for organic compounds such as drugs. The method is based on a designed system, which consists of a 96-well plate modified with 96 hollow fiber membrane tubes and a matching lid with 96 center holes and 96 side holes distributing in 96 grids. Each center hole was glued with a sealed on one end hollow fiber membrane tube, which is used to separate the aqueous phase from the octanol phase. A needle, such as microsyringe or automatic sampler, can be directly inserted into the membrane tube to deposit octanol as the accepted phase or take out the mixture of the octanol and the drug. Each side hole is filled with aqueous phase and could freely take in/out solvent as the donor phase from the outside of the hollow fiber membranes. The logD can be calculated by measuring the drug concentration in each phase after extraction equilibrium. After a comprehensive comparison, the polytetrafluoroethylene hollow fiber with the thickness of 210 μm, an extraction time of 300 min, a temperature of 25 °C and atmospheric pressure without stirring are selected for the high throughput measurement. The correlation coefficient of the linear fit of the logD values of five drugs determined by our system to reference values is 0.9954, showed a nice accurate. The -8.9% intra-day and -4.4% inter-day precision of logD for metronidazole indicates a good precision. In addition, the logD values of eight drugs were simultaneously and successfully measured, which indicated that the 96 throughput measure method of logD value was accurate, precise, reliable and useful for high throughput screening. Copyright © 2014 Elsevier B.V. All rights reserved.

New miRNA labeling method for bead-based quantification

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Lanfranchi Gerolamo

2010-06-01

Full Text Available Abstract Background microRNAs (miRNAs are small single-stranded non-coding RNAs that act as crucial regulators of gene expression. Different methods have been developed for miRNA expression profiling in order to better understand gene regulation in normal and pathological conditions. miRNAs expression values obtained from large scale methodologies such as microarrays still need a validation step with alternative technologies. Results Here we have applied with an innovative approach, the Luminex® xMAP™ technology validate expression data of differentially expressed miRNAs obtained from high throughput arrays. We have developed a novel labeling system of small RNA molecules (below 200 nt, optimizing the sensitive cloning method for miRNAs, termed miRNA amplification profiling (mRAP. The Luminex expression patterns of three miRNAs (miR-23a, miR-27a and miR-199a in seven different cell lines have been validated by TaqMan miRNA assay. In all cases, bead-based meas were confirmed by the data obtained by TaqMan and microarray technologies. Conclusions We demonstrate that the measure of individual miRNA by the bead-based method is feasible, high speed, sensitive and low cost. The Luminex® xMAP™ technology also provides flexibility, since the central reaction can be scaled up with additional miRNA capturing beads, allowing validation of many differentially expressed miRNAs obtained from microarrays in a single experiment. We propose this technology as an alternative method to qRT-PCR for validating miRNAs expression data obtained with high-throughput technologies.

A texture based pattern recognition approach to distinguish melanoma from non-melanoma cells in histopathological tissue microarray sections.

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Elton Rexhepaj

Full Text Available AIMS: Immunohistochemistry is a routine practice in clinical cancer diagnostics and also an established technology for tissue-based research regarding biomarker discovery efforts. Tedious manual assessment of immunohistochemically stained tissue needs to be fully automated to take full advantage of the potential for high throughput analyses enabled by tissue microarrays and digital pathology. Such automated tools also need to be reproducible for different experimental conditions and biomarker targets. In this study we present a novel supervised melanoma specific pattern recognition approach that is fully automated and quantitative. METHODS AND RESULTS: Melanoma samples were immunostained for the melanocyte specific target, Melan-A. Images representing immunostained melanoma tissue were then digitally processed to segment regions of interest, highlighting Melan-A positive and negative areas. Color deconvolution was applied to each region of interest to separate the channel containing the immunohistochemistry signal from the hematoxylin counterstaining channel. A support vector machine melanoma classification model was learned from a discovery melanoma patient cohort (n = 264 and subsequently validated on an independent cohort of melanoma patient tissue sample images (n = 157. CONCLUSION: Here we propose a novel method that takes advantage of utilizing an immuhistochemical marker highlighting melanocytes to fully automate the learning of a general melanoma cell classification model. The presented method can be applied on any protein of interest and thus provides a tool for quantification of immunohistochemistry-based protein expression in melanoma.

A High-throughput Selection for Cellulase Catalysts Using Chemical Complementation

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T.; Lin, Hening; Tao, Haiyan; Cornish, Virginia W.

2010-01-01

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases however is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Due to the large number of enzyme variants selections can test compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity. PMID:19053460

High-throughput fabrication of anti-counterfeiting colloid-based photoluminescent microtags using electrical nanoimprint lithography

International Nuclear Information System (INIS)

Diaz, R; Palleau, E; Poirot, D; Sangeetha, N M; Ressier, L

2014-01-01

This work demonstrates the excellent capability of the recently developed electrical nanoimprint lithography (e-NIL) technique for quick, high-throughput production of well-defined colloid assemblies on surfaces. This is shown by fabricating micron-sized photoluminescent quick response (QR) codes based on the electrostatic directed trapping (so called nanoxerography process) of 28 nm colloidal lanthanide-doped upconverting NaYF 4 nanocrystals. Influencing experimental parameters have been optimized and the contribution of triboelectrification in e-NIL was evidenced. Under the chosen conditions, more than 300 000 nanocrystal-based QR codes were fabricated on a 4 inch silicon wafer, in less than 15 min. These microtags were then transferred to transparent flexible films, to be easily integrated onto desired products. Invisible to the naked eye, they can be decoded and authenticated using an optical microscopy image of their specific photoluminescence mapping. Beyond this very promising application for product tracking and the anti-counterfeiting strategies, e-NIL nanoxerography, potentially applicable to any types of charged and/or polarizable colloids and pattern geometries opens up tremendous opportunities for industrial scale production of various other kinds of colloid-based devices and sensors. (paper)

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

OpenAIRE

Fan, Beiyuan; Li, Xiufeng; Chen, Deyong; Peng, Hongshang; Wang, Junbo; Chen, Jian

2016-01-01

This article reviews recent developments in microfluidic systems enabling high-throughput characterization of single-cell proteins. Four key perspectives of microfluidic platforms are included in this review: (1) microfluidic fluorescent flow cytometry; (2) droplet based microfluidic flow cytometry; (3) large-array micro wells (microengraving); and (4) large-array micro chambers (barcode microchips). We examine the advantages and limitations of each technique and discuss future research oppor...

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

Science.gov (United States)

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

High-throughput screening to identify inhibitors of lysine demethylases.

Science.gov (United States)

Gale, Molly; Yan, Qin

2015-01-01

Lysine demethylases (KDMs) are epigenetic regulators whose dysfunction is implicated in the pathology of many human diseases including various types of cancer, inflammation and X-linked intellectual disability. Particular demethylases have been identified as promising therapeutic targets, and tremendous efforts are being devoted toward developing suitable small-molecule inhibitors for clinical and research use. Several High-throughput screening strategies have been developed to screen for small-molecule inhibitors of KDMs, each with advantages and disadvantages in terms of time, cost, effort, reliability and sensitivity. In this Special Report, we review and evaluate the High-throughput screening methods utilized for discovery of novel small-molecule KDM inhibitors.

High throughput protein production screening

Science.gov (United States)

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

2009-09-08

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

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

International Nuclear Information System (INIS)

Mercier, Kelly A.; Powers, Robert

2005-01-01

High-throughput screening (HTS) using NMR spectroscopy has become a common component of the drug discovery effort and is widely used throughout the pharmaceutical industry. NMR provides additional information about the nature of small molecule-protein interactions compared to traditional HTS methods. In order to achieve comparable efficiency, small molecules are often screened as mixtures in NMR-based assays. Nevertheless, an analysis of the efficiency of mixtures and a corresponding determination of the optimum mixture size (OMS) that minimizes the amount of material and instrumentation time required for an NMR screen has been lacking. A model for calculating OMS based on the application of the hypergeometric distribution function to determine the probability of a 'hit' for various mixture sizes and hit rates is presented. An alternative method for the deconvolution of large screening mixtures is also discussed. These methods have been applied in a high-throughput NMR screening assay using a small, directed library

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

Science.gov (United States)

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

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

Science.gov (United States)

Zheng, Guokuo

In this work, a simple and efficient needleless high throughput electrospinning process using an aluminum disk spinneret with 24 holes is described. Electrospun mats produced by this setup consisted of fine fibers (nano-sized) of the highest quality while the productivity (yield) was many times that obtained from conventional single-needle electrospinning. The goal was to produce scaled-up amounts of the same or better quality nanofibers under variable concentration, voltage, and the working distance than those produced with the single needle lab setting. The fiber mats produced were either polymer or ceramic (such as molybdenum trioxide nanofibers). Through experimentation the optimum process conditions were defined to be: 24 kilovolt, a distance to collector of 15cm. More diluted solutions resulted in smaller diameter fibers. Comparing the morphologies of the nanofibers of MoO3 produced by both the traditional and the high throughput set up it was found that they were very similar. Moreover, the nanofibers production rate is nearly 10 times than that of traditional needle electrospinning. Thus, the high throughput process has the potential to become an industrial nanomanufacturing process and the materials processed by it may be used as filtration devices, in tissue engineering, and as sensors.

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

Directory of Open Access Journals (Sweden)

Urard Pascal

2006-01-01

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

TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays

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Neuvial Pierre

2010-05-01

Full Text Available Abstract Background High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, including total copy number and loss of heterozygosity (LOH analyses. Even after state of the art preprocessing methods, allelic signal estimates from genotyping arrays still suffer from systematic effects that make them difficult to use effectively for such downstream analyses. Results We propose a method, TumorBoost, for normalizing allelic estimates of one tumor sample based on estimates from a single matched normal. The method applies to any paired tumor-normal estimates from any microarray-based technology, combined with any preprocessing method. We demonstrate that it increases the signal-to-noise ratio of allelic signals, making it significantly easier to detect allelic imbalances. Conclusions TumorBoost increases the power to detect somatic copy-number events (including copy-neutral LOH in the tumor from allelic signals of Affymetrix or Illumina origin. We also conclude that high-precision allelic estimates can be obtained from a single pair of tumor-normal hybridizations, if TumorBoost is combined with single-array preprocessing methods such as (allele-specific CRMA v2 for Affymetrix or BeadStudio's (proprietary XY-normalization method for Illumina. A bounded-memory implementation is available in the open-source and cross-platform R package aroma.cn, which is part of the Aroma Project (http://www.aroma-project.org/.

ELISA-BASE: an integrated bioinformatics tool for analyzing and tracking ELISA microarray data

OpenAIRE

White, Amanda M.; Collett, James R.; Seurynck-Servoss, Shannon L.; Daly, Don S.; Zangar, Richard C.

2009-01-01

Summary:ELISA-BASE is an open source database for capturing, organizing and analyzing enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Software Environment (BASE) database system.

Solion ion source for high-efficiency, high-throughput solar cell manufacturing

Energy Technology Data Exchange (ETDEWEB)

Koo, John, E-mail: john-koo@amat.com; Binns, Brant; Miller, Timothy; Krause, Stephen; Skinner, Wesley; Mullin, James [Applied Materials, Inc., Varian Semiconductor Equipment Business Unit, 35 Dory Road, Gloucester, Massachusetts 01930 (United States)

2014-02-15

In this paper, we introduce the Solion ion source for high-throughput solar cell doping. As the source power is increased to enable higher throughput, negative effects degrade the lifetime of the plasma chamber and the extraction electrodes. In order to improve efficiency, we have explored a wide range of electron energies and determined the conditions which best suit production. To extend the lifetime of the source we have developed an in situ cleaning method using only existing hardware. With these combinations, source life-times of >200 h for phosphorous and >100 h for boron ion beams have been achieved while maintaining 1100 cell-per-hour production.

GEPAS, a web-based tool for microarray data analysis and interpretation

Science.gov (United States)

Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín

2008-01-01

Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806

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

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Mariusz Butkiewicz

2013-01-01

Full Text Available With the rapidly increasing availability of High-Throughput Screening (HTS data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR models are built using Artificial Neural Networks (ANNs, Support Vector Machines (SVMs, Decision Trees (DTs, and Kohonen networks (KNs. Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.

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

Science.gov (United States)

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

2016-01-01

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

High-throughput spectrometer designs in a compact form-factor: principles and applications

Science.gov (United States)

Norton, S. M.

2013-05-01

Many compact, portable Raman spectrometers have entered the market in the past few years with applications in narcotics and hazardous material identification, as well as verification applications in pharmaceuticals and security screening. Often, the required compact form-factor has forced designers to sacrifice throughput and sensitivity for portability and low-cost. We will show that a volume phase holographic (VPH)-based spectrometer design can achieve superior throughput and thus sensitivity over conventional Czerny-Turner reflective designs. We will look in depth at the factors influencing throughput and sensitivity and illustrate specific VPH-based spectrometer examples that highlight these design principles.

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

Directory of Open Access Journals (Sweden)

Patil Ashwini

2005-04-01

Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.

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

Science.gov (United States)

Baumann, Pascal; Hahn, Tobias; Hubbuch, Jürgen

2015-10-01

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

A ground-up approach to High Throughput Cloud Computing in High-Energy Physics

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00245123; Ganis, Gerardo; Bagnasco, Stefano

The thesis explores various practical approaches in making existing High Throughput computing applications common in High Energy Physics work on cloud-provided resources, as well as opening the possibility for running new applications. The work is divided into two parts: firstly we describe the work done at the computing facility hosted by INFN Torino to entirely convert former Grid resources into cloud ones, eventually running Grid use cases on top along with many others in a more flexible way. Integration and conversion problems are duly described. The second part covers the development of solutions for automatizing the orchestration of cloud workers based on the load of a batch queue and the development of HEP applications based on ROOT's PROOF that can adapt at runtime to a changing number of workers.

Statistical removal of background signals from high-throughput 1H NMR line-broadening ligand-affinity screens

International Nuclear Information System (INIS)

Worley, Bradley; Sisco, Nicholas J.; Powers, Robert

2015-01-01

NMR ligand-affinity screens are vital to drug discovery, are routinely used to screen fragment-based libraries, and used to verify chemical leads from high-throughput assays and virtual screens. NMR ligand-affinity screens are also a highly informative first step towards identifying functional epitopes of unknown proteins, as well as elucidating the biochemical functions of protein–ligand interaction at their binding interfaces. While simple one-dimensional 1 H NMR experiments are capable of indicating binding through a change in ligand line shape, they are plagued by broad, ill-defined background signals from protein 1 H resonances. We present an uncomplicated method for subtraction of protein background in high-throughput ligand-based affinity screens, and show that its performance is maximized when phase-scatter correction is applied prior to subtraction

High-Dimensional Additive Hazards Regression for Oral Squamous Cell Carcinoma Using Microarray Data: A Comparative Study

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Omid Hamidi

2014-01-01

Full Text Available Microarray technology results in high-dimensional and low-sample size data sets. Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified. A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present. The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest. The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves. The selected genes by all methods were highly significant (P<0.001. The Lasso showed maximum median of area under ROC curve over time (0.95 and smoothly clipped absolute deviation showed the lowest prediction error (0.105. It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features. So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.

A Primer on High-Throughput Computing for Genomic Selection

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Xiao-Lin eWu

2011-02-01

Full Text Available High-throughput computing (HTC uses computer clusters to solve advanced computational problems, with the goal of accomplishing high throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general purpose computation on a graphics processing unit (GPU provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin – Madison, which can be leveraged for genomic selection, in terms of central processing unit (CPU capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

Science.gov (United States)

Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Statistical Methods for Comparative Phenomics Using High-Throughput Phenotype Microarrays

KAUST Repository

Sturino, Joseph; Zorych, Ivan; Mallick, Bani; Pokusaeva, Karina; Chang, Ying-Ying; Carroll, Raymond J; Bliznuyk, Nikolay

2010-01-01

develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second

High-throughput miRNA profiling of human melanoma blood samples

Directory of Open Access Journals (Sweden)

Rass Knuth

2010-06-01

Full Text Available Abstract Background MicroRNA (miRNA signatures are not only found in cancer tissue but also in blood of cancer patients. Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool. Methods Using a microarray based approach we screened almost 900 human miRNAs to detect miRNAs that are deregulated in their expression in blood cells of melanoma patients. We analyzed 55 blood samples, including 20 samples of healthy individuals, 24 samples of melanoma patients as test set, and 11 samples of melanoma patients as independent validation set. Results A hypothesis test based approch detected 51 differentially regulated miRNAs, including 21 miRNAs that were downregulated in blood cells of melanoma patients and 30 miRNAs that were upregulated in blood cells of melanoma patients as compared to blood cells of healthy controls. The tets set and the independent validation set of the melanoma samples showed a high correlation of fold changes (0.81. Applying hierarchical clustering and principal component analysis we found that blood samples of melanoma patients and healthy individuals can be well differentiated from each other based on miRNA expression analysis. Using a subset of 16 significant deregulated miRNAs, we were able to reach a classification accuracy of 97.4%, a specificity of 95% and a sensitivity of 98.9% by supervised analysis. MiRNA microarray data were validated by qRT-PCR. Conclusions Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.

Microarray-based genotyping of Salmonella: Inter-laboratory evaluation of reproducibility and standardization potential

DEFF Research Database (Denmark)

Grønlund, Hugo Ahlm; Riber, Leise; Vigre, Håkan

2011-01-01

Bacterial food-borne infections in humans caused by Salmonella spp. are considered a crucial food safety issue. Therefore, it is important for the risk assessments of Salmonella to consider the genomic variationamong different isolates in order to control pathogen-induced infections. Microarray...... critical methodology parameters that differed between the two labs were identified. These related to printing facilities, choice of hybridization buffer,wash buffers used following the hybridization and choice of procedure for purifying genomic DNA. Critical parameters were randomized in a four......DNA and different wash buffers. However, less agreement (Kappa=0.2–0.6) between microarray results were observed when using different hybridization buffers, indicating this parameter as being highly criticalwhen transferring a standard microarray assay between laboratories. In conclusion, this study indicates...

Deciphering cellular morphology and biocompatibility using polymer microarrays

International Nuclear Information System (INIS)

Pernagallo, Salvatore; Unciti-Broceta, Asier; DIaz-Mochon, Juan Jose; Bradley, Mark

2008-01-01

A quantitative and qualitative analysis of cellular adhesion, morphology and viability is essential in understanding and designing biomaterials such as those involved in implant surfaces or as tissue-engineering scaffolds. As a means to simultaneously perform these studies in a high-throughput (HT) manner, we report a normalized protocol which allows the rapid analysis of a large number of potential cell binding substrates using polymer microarrays and high-content fluorescence microscopy. The method was successfully applied to the discovery of optimal polymer substrates from a 214-member polyurethane library with mouse fibroblast cells (L929), as well as simultaneous evaluation of cell viability and cellular morphology. Analysis demonstrated high biocompatibility of the binding polymers and permitted the identification of several different cellular morphologies, showing that specific polymer interactions may provoke changes in cell shape. In addition, SAR studies showed a clear correspondence between cellular adhesion and polymer structure. The approach can be utilized to perform multiple experiments (up to 1024 single experiments per slide) in a highly reproducible manner, leading to the generation of vast amounts of data in a short time period (48-72 h) while reducing dramatically the quantities of polymers, reagents and cells used

High-throughput screening of monoclonal antibodies against plant cell wall glycans by hierarchical clustering of their carbohydrate microarray binding profiles

DEFF Research Database (Denmark)

Moller, Isabel Eva; Marcus, Susan E.; Haeger, Ash

2008-01-01

Antibody-producing hybridoma cell lines were created following immunisation with a crude extract of cell wall polymers from the plant Arabidopsis thaliana. In order to rapidly screen the specificities of individual monoclonal antibodies (mAbs), their binding to microarrays containing 50 cell wall...... investigated using subsequent immunochemical and biochemical analyses and two novel mAbs are described in detail. mAb LM13 binds to an arabinanase-sensitive pectic epitope and mAb LM14, binds to an epitope occurring on arabinogalactan-proteins. Both mAbs display novel patterns of recognition of cell walls...

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

Science.gov (United States)

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

2017-09-29

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

Target gene expression levels and competition between transfected and endogenous microRNAs are strong confounding factors in microRNA high-throughput experiments

Science.gov (United States)

2012-01-01

Background MicroRNA (miRNA) target genes tend to have relatively long and conserved 3' untranslated regions (UTRs), but to what degree these characteristics contribute to miRNA targeting is poorly understood. Different high-throughput experiments have, for example, shown that miRNAs preferentially regulate genes with both short and long 3' UTRs and that target site conservation is both important and irrelevant for miRNA targeting. Results We have analyzed several gene context-dependent features, including 3' UTR length, 3' UTR conservation, and messenger RNA (mRNA) expression levels, reported to have conflicting influence on miRNA regulation. By taking into account confounding factors such as technology-dependent experimental bias and competition between transfected and endogenous miRNAs, we show that two factors - target gene expression and competition - could explain most of the previously reported experimental differences. Moreover, we find that these and other target site-independent features explain about the same amount of variation in target gene expression as the target site-dependent features included in the TargetScan model. Conclusions Our results show that it is important to consider confounding factors when interpreting miRNA high throughput experiments and urge special caution when using microarray data to compare average regulatory effects between groups of genes that have different average gene expression levels. PMID:22325809

High-Throughput Analysis and Automation for Glycomics Studies

NARCIS (Netherlands)

Shubhakar, A.; Reiding, K.R.; Gardner, R.A.; Spencer, D.I.R.; Fernandes, D.L.; Wuhrer, M.

2015-01-01

This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing

Throughput, latency and cost comparisons of microcontroller-based implementations of wireless sensor network (WSN) in high jump sports

Science.gov (United States)

Ahmad, Afandi; Roslan, Muhammad Faris; Amira, Abbes

2017-09-01

In high jump sports, approach take-off speed and force during the take-off are two (2) main important parts to gain maximum jump. To measure both parameters, wireless sensor network (WSN) that contains microcontroller and sensor are needed to describe the results of speed and force for jumpers. Most of the microcontroller exhibit transmission issues in terms of throughput, latency and cost. Thus, this study presents the comparison of wireless microcontrollers in terms of throughput, latency and cost, and the microcontroller that have best performances and cost will be implemented in high jump wearable device. In the experiments, three (3) parts have been integrated - input, process and output. Force (for ankle) and global positioning system (GPS) sensor (for body waist) acts as an input for data transmission. These data were then being processed by both microcontrollers, ESP8266 and Arduino Yun Mini to transmit the data from sensors to the server (host-PC) via message queuing telemetry transport (MQTT) protocol. The server acts as receiver and the results was calculated from the MQTT log files. At the end, results obtained have shown ESP8266 microcontroller had been chosen since it achieved high throughput, low latency and 11 times cheaper in term of prices compared to Arduino Yun Mini microcontroller.

Association Mapping of Total Carotenoids in Diverse Soybean Genotypes Based on Leaf Extracts and High-Throughput Canopy Spectral Reflectance Measurements.

Directory of Open Access Journals (Sweden)

Arun Prabhu Dhanapal

Full Text Available Carotenoids are organic pigments that are produced predominantly by photosynthetic organisms and provide antioxidant activity to a wide variety of plants, animals, bacteria, and fungi. The carotenoid biosynthetic pathway is highly conserved in plants and occurs mostly in chromoplasts and chloroplasts. Leaf carotenoids play important photoprotective roles and targeted selection for leaf carotenoids may offer avenues to improve abiotic stress tolerance. A collection of 332 soybean [Glycine max (L. Merr.] genotypes was grown in two years and total leaf carotenoid content was determined using three different methods. The first method was based on extraction and spectrophotometric determination of carotenoid content (eCaro in leaf tissue, whereas the other two methods were derived from high-throughput canopy spectral reflectance measurements using wavelet transformed reflectance spectra (tCaro and a spectral reflectance index (iCaro. An association mapping approach was employed using 31,253 single nucleotide polymorphisms (SNPs to identify SNPs associated with total carotenoid content using a mixed linear model based on data from two growing seasons. A total of 28 SNPs showed a significant association with total carotenoid content in at least one of the three approaches. These 28 SNPs likely tagged 14 putative loci for carotenoid content. Six putative loci were identified using eCaro, five loci with tCaro, and nine loci with iCaro. Three of these putative loci were detected by all three carotenoid determination methods. All but four putative loci were located near a known carotenoid-related gene. These results showed that carotenoid markers can be identified in soybean using extract-based as well as by high-throughput canopy spectral reflectance-based approaches, demonstrating the utility of field-based canopy spectral reflectance phenotypes for association mapping.

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

Science.gov (United States)

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

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

KAUST Repository

Wu, Jinbo

2012-11-20

Microdroplets offer unique compartments for accommodating a large number of chemical and biological reactions in tiny volume with precise control. A major concern in droplet-based microfluidics is the difficulty to address droplets individually and achieve high throughput at the same time. Here, we have combined an improved cartridge sampling technique with a microfluidic chip to perform droplet screenings and aggressive reaction with minimal (nanoliter-scale) reagent consumption. The droplet composition, distance, volume (nanoliter to subnanoliter scale), number, and sequence could be precisely and digitally programmed through the improved sampling technique, while sample evaporation and cross-contamination are effectively eliminated. Our combined device provides a simple model to utilize multiple droplets for various reactions with low reagent consumption and high throughput. © 2012 American Chemical Society.

Identification of listeria species isolated in Tunisia by Microarray based assay : results of a preliminary study

International Nuclear Information System (INIS)

Hmaied, Fatma; Helel, Salma; Barkallah, Insaf; Leberre, V.; Francois, J.M.; Kechrid, A.

2008-01-01

Microarray-based assay is a new molecular approach for genetic screening and identification of microorganisms. We have developed a rapid microarray-based assay for the reliable detection and discrimination of Listeria spp. in food and clinical isolates from Tunisia. The method used in the present study is based on the PCR amplification of a virulence factor gene (iap gene). the PCR mixture contained cyanine Cy5labeled dCTP. Therefore, The PCR products were fluorescently labeled. The presence of multiple species-specific sequences within the iap gene enabled us to design different oligoprobes per species. The species-specific sequences of the iap gene used in this study were obtained from genBank and then aligned for phylogenetic analysis in order to identify and retrieve the sequences of homologues of the amplified iap gene analysed. 20 probes were used for detection and identification of 22 food isolates and clinical isolates of Listeria spp (L. monocytogenes, L. ivanovi), L. welshimeri, L. seeligeri, and L. grayi). Each bacterial gene was identified by hybridization to oligoprobes specific for each Listeria species and immobilized on a glass surface. The microarray analysis showed that 5 clinical isolates and 2 food isolates were identified listeria monocytogenes. Concerning the remaining 15 food isolates; 13 were identified listeria innocua and 2 isolates could not be identified by microarray based assay. Further phylogenetic and molecular analysis are required to design more species-specific probes for the identification of Listeria spp. Microarray-based assay is a simple and rapid method used for Listeria species discrimination

High throughput materials research and development for lithium ion batteries