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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-12-01

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

Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT)

EPA Science Inventory

High throughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the ...

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

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

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

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

PubMed

Engelmann, Brett W

2017-01-01

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

Analysis of High-Throughput ELISA Microarray Data

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

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

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

High-throughput real-time quantitative reverse transcription PCR.

PubMed

Bookout, Angie L; Cummins, Carolyn L; Mangelsdorf, David J; Pesola, Jean M; Kramer, Martha F

2006-02-01

Extensive detail on the application of the real-time quantitative polymerase chain reaction (QPCR) for the analysis of gene expression is provided in this unit. The protocols are designed for high-throughput, 384-well-format instruments, such as the Applied Biosystems 7900HT, but may be modified to suit any real-time PCR instrument. QPCR primer and probe design and validation are discussed, and three relative quantitation methods are described: the standard curve method, the efficiency-corrected DeltaCt method, and the comparative cycle time, or DeltaDeltaCt method. In addition, a method is provided for absolute quantification of RNA in unknown samples. RNA standards are subjected to RT-PCR in the same manner as the experimental samples, thus accounting for the reaction efficiencies of both procedures. This protocol describes the production and quantitation of synthetic RNA molecules for real-time and non-real-time RT-PCR applications.

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

PubMed

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

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

PubMed Central

Dutta, Sanjib; Koide, Akiko; Koide, Shohei

2008-01-01

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

High content screening of ToxCast compounds using Vala Sciences’ complex cell culturing systems (SOT)

EPA Science Inventory

US EPA’s ToxCast research program evaluates bioactivity for thousands of chemicals utilizing high-throughput screening assays to inform chemical testing decisions. Vala Sciences provides high content, multiplexed assays that utilize quantitative cell-based digital image analysis....

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-06-05

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

A method for quantitative analysis of standard and high-throughput qPCR expression data based on input sample quantity.

PubMed

Adamski, Mateusz G; Gumann, Patryk; Baird, Alison E

2014-01-01

Over the past decade rapid advances have occurred in the understanding of RNA expression and its regulation. Quantitative polymerase chain reactions (qPCR) have become the gold standard for quantifying gene expression. Microfluidic next generation, high throughput qPCR now permits the detection of transcript copy number in thousands of reactions simultaneously, dramatically increasing the sensitivity over standard qPCR. Here we present a gene expression analysis method applicable to both standard polymerase chain reactions (qPCR) and high throughput qPCR. This technique is adjusted to the input sample quantity (e.g., the number of cells) and is independent of control gene expression. It is efficiency-corrected and with the use of a universal reference sample (commercial complementary DNA (cDNA)) permits the normalization of results between different batches and between different instruments--regardless of potential differences in transcript amplification efficiency. Modifications of the input quantity method include (1) the achievement of absolute quantification and (2) a non-efficiency corrected analysis. When compared to other commonly used algorithms the input quantity method proved to be valid. This method is of particular value for clinical studies of whole blood and circulating leukocytes where cell counts are readily available.

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

PubMed

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

2012-12-07

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2012-06-20

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

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

PubMed Central

2010-01-01

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

78 FR 56720 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-13

...-valve replacement in high-risk patients. N Engl J Med. 2011 Jun 9;364(23):2187-98. [PMID 21639811... be activated upon demand to release the therapeutic agent at the desired site. The concurrent release... streamlined for high-throughput analysis. Quantitative molecular diagnostics. Unique microRNAs and/or mRNAs...

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

PubMed

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

2014-06-01

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

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

PubMed Central

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

2017-01-01

Abstract Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure–property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure–property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure–property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials. PMID:28458737

Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

PubMed Central

Bodenmiller, Bernd; Zunder, Eli R.; Finck, Rachel; Chen, Tiffany J.; Savig, Erica S.; Bruggner, Robert V.; Simonds, Erin F.; Bendall, Sean C.; Sachs, Karen; Krutzik, Peter O.; Nolan, Garry P.

2013-01-01

The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors, and revealed off-target effects. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease. PMID:22902532

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2012-01-01

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

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

PubMed Central

Choudhry, Priya

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2002-02-01

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

High-throughput quantitative analysis by desorption electrospray ionization mass spectrometry.

PubMed

Manicke, Nicholas E; Kistler, Thomas; Ifa, Demian R; Cooks, R Graham; Ouyang, Zheng

2009-02-01

A newly developed high-throughput desorption electrospray ionization (DESI) source was characterized in terms of its performance in quantitative analysis. A 96-sample array, containing pharmaceuticals in various matrices, was analyzed in a single run with a total analysis time of 3 min. These solution-phase samples were examined from a hydrophobic PTFE ink printed on glass. The quantitative accuracy, precision, and limit of detection (LOD) were characterized. Chemical background-free samples of propranolol (PRN) with PRN-d(7) as internal standard (IS) and carbamazepine (CBZ) with CBZ-d(10) as IS were examined. So were two other sample sets consisting of PRN/PRN-d(7) at varying concentration in a biological milieu of 10% urine or porcine brain total lipid extract, total lipid concentration 250 ng/microL. The background-free samples, examined in a total analysis time of 1.5 s/sample, showed good quantitative accuracy and precision, with a relative error (RE) and relative standard deviation (RSD) generally less than 3% and 5%, respectively. The samples in urine and the lipid extract required a longer analysis time (2.5 s/sample) and showed RSD values of around 10% for the samples in urine and 4% for the lipid extract samples and RE values of less than 3% for both sets. The LOD for PRN and CBZ when analyzed without chemical background was 10 and 30 fmol, respectively. The LOD of PRN increased to 400 fmol analyzed in 10% urine, and 200 fmol when analyzed in the brain lipid extract.

Large-scale human skin lipidomics by quantitative, high-throughput shotgun mass spectrometry.

PubMed

Sadowski, Tomasz; Klose, Christian; Gerl, Mathias J; Wójcik-Maciejewicz, Anna; Herzog, Ronny; Simons, Kai; Reich, Adam; Surma, Michal A

2017-03-07

The lipid composition of human skin is essential for its function; however the simultaneous quantification of a wide range of stratum corneum (SC) and sebaceous lipids is not trivial. We developed and validated a quantitative high-throughput shotgun mass spectrometry-based platform for lipid analysis of tape-stripped SC skin samples. It features coverage of 16 lipid classes; total quantification to the level of individual lipid molecules; high reproducibility and high-throughput capabilities. With this method we conducted a large lipidomic survey of 268 human SC samples, where we investigated the relationship between sampling depth and lipid composition, lipidome variability in samples from 14 different sampling sites on the human body and finally, we assessed the impact of age and sex on lipidome variability in 104 healthy subjects. We found sebaceous lipids to constitute an abundant component of the SC lipidome as they diffuse into the topmost SC layers forming a gradient. Lipidomic variability with respect to sampling depth, site and subject is considerable, and mainly accredited to sebaceous lipids, while stratum corneum lipids vary less. This stresses the importance of sampling design and the role of sebaceous lipids in skin studies.

Rapid Analysis of Corni fructus Using Paper Spray-Mass Spectrometry.

PubMed

Guo, Yuan; Gu, Zhixin; Liu, Xuemei; Liu, Jingjing; Ma, Ming; Chen, Bo; Wang, Liping

2017-07-01

Paper spray-mass spectrometry (PS-MS) is a kind of ambient MS technique for the rapid analysis of samples. Corni fructus has been widely used in traditional Chinese compound preparations and healthy food. However, a number of counterfeits of Corni fructus, such as Crataegi fructus, Lycii fructus, and grape skin are illegally sold in crude herb markets. Therefore, the development of a rapid and high-throughput quality evaluation method is important for ensuring the effectiveness and safety of the crude materials of Corni fructus. To develop PS-MS chemical profiles and a semi-quantitative method of Corni fructus for quality assessment and control, and species distinction of Corni fructus. Both positive and negative ion PS-MS chemical profiles were constructed for species distinction. The statistical analysis of the chemical profiles was accomplished by principal component analysis (PCA). Rapid semi-quantitative analysis of loganin and morroniside in the extracts of Corni fructus were accomplished by PS-MS. The profiles of the Corni fructus and Crataegi fructus samples were clearly clustered into two categories. The limit of quantification (LOQ) in the semi-quantitative analysis was 6 μg/mL and 5.6 μg/mL for loganin and morroniside, respectively. PS-MS is a simple, rapid, and high-throughput method for the quality control and species distinction of Corni fructus. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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

PubMed

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

2008-04-01

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

High-throughput technology for novel SO2 oxidation catalysts

PubMed Central

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

2011-01-01

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

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

PubMed Central

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

2010-01-01

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

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

PubMed

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

2015-01-01

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

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

PubMed

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

2010-01-01

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

Development of multitissue microfluidic dynamic array for assessing changes in gene expression associated with channel catfish appetite, growth, metabolism, and intestinal health

USDA-ARS?s Scientific Manuscript database

Large-scale, gene expression methods allow for high throughput analysis of physiological pathways at a fraction of the cost of individual gene expression analysis. Systems, such as the Fluidigm quantitative PCR array described here, can provide powerful assessments of the effects of diet, environme...

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

PubMed

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

2012-01-01

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

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

PubMed Central

2012-01-01

Background Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. Method We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. Results We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. Conclusions The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind. PMID:22369037

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform.

PubMed

Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing

2008-02-01

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-08-16

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

77 FR 68773 - FIFRA Scientific Advisory Panel; Notice of Public Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-16

... for physical chemical properties that cannot be easily tested in in vitro systems or stable enough for.... Quantitative structural-activity relationship (QSAR) models and estrogen receptor (ER) expert systems development. High-throughput data generation and analysis (expertise focused on how this methodology can be...

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

PubMed Central

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

2013-01-01

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

Analysis of Ingredient Lists to Quantitatively Characterize Chemicals in Consumer Products

EPA Science Inventory

The EPA’s ExpoCast program is developing high throughput (HT) approaches to generate the needed exposure estimates to compare against HT bioactivity data generated from the US inter-agency Tox21 and the US EPA ToxCast programs. Assessing such exposures for the thousands of...

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

PubMed

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

2018-01-18

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

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

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

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

2008-05-03

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

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

PubMed

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

2018-05-07

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

A differential mobility spectrometry/mass spectrometry platform for the rapid detection and quantitation of DNA adduct dG-ABP.

PubMed

Kafle, Amol; Klaene, Joshua; Hall, Adam B; Glick, James; Coy, Stephen L; Vouros, Paul

2013-07-15

There is continued interest in exploring new analytical technologies for the detection and quantitation of DNA adducts, biomarkers which provide direct evidence of exposure and genetic damage in cells. With the goal of reducing clean-up steps and improving sample throughput, a Differential Mobility Spectrometry/Mass Spectrometry (DMS/MS) platform has been introduced for adduct analysis. A DMS/MS platform has been utilized for the analysis of dG-ABP, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl (4-ABP). After optimization of the DMS parameters, each sample was analyzed in just 30 s following a simple protein precipitation step of the digested DNA. A detection limit of one modification in 10^6 nucleosides has been achieved using only 2 µg of DNA. A brief comparison (quantitative and qualitative) with liquid chromatography/mass spectrometry is also presented highlighting the advantages of using the DMS/MS method as a high-throughput platform. The data presented demonstrate the successful application of a DMS/MS/MS platform for the rapid quantitation of DNA adducts using, as a model analyte, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl. Copyright © 2013 John Wiley & Sons, Ltd.

New High Throughput Methods to Estimate Chemical Exposure

EPA Science Inventory

EPA has made many recent advances in high throughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing an...

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

PubMed

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

2017-12-01

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

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

PubMed

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

2018-04-27

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

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

PubMed

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

2016-07-01

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

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2018-06-01

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

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

PubMed

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

2014-05-28

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

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

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

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

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

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

PubMed

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

2015-01-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2016-01-19

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

Quantitative characterization of conformational-specific protein-DNA binding using a dual-spectral interferometric imaging biosensor.

PubMed

Zhang, Xirui; Daaboul, George G; Spuhler, Philipp S; Dröge, Peter; Ünlü, M Selim

2016-03-14

DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are not fully understood. Recently, it was discovered that DNA-binding proteins recognize specific binding sites to carry out their functions through an indirect readout mechanism by recognizing and capturing DNA conformational flexibility and deformation. High-throughput DNA microarray-based methods that provide large-scale protein-DNA binding information have shown effective and comprehensive analysis of protein-DNA binding affinities, but do not provide information of DNA conformational changes in specific protein-DNA complexes. Building on the high-throughput capability of DNA microarrays, we demonstrate a quantitative approach that simultaneously measures the amount of protein binding to DNA and nanometer-scale DNA conformational change induced by protein binding in a microarray format. Both measurements rely on spectral interferometry on a layered substrate using a single optical instrument in two distinct modalities. In the first modality, we quantitate the amount of binding of protein to surface-immobilized DNA in each DNA spot using a label-free spectral reflectivity technique that accurately measures the surface densities of protein and DNA accumulated on the substrate. In the second modality, for each DNA spot, we simultaneously measure DNA conformational change using a fluorescence vertical sectioning technique that determines average axial height of fluorophores tagged to specific nucleotides of the surface-immobilized DNA. The approach presented in this paper, when combined with current high-throughput DNA microarray-based technologies, has the potential to serve as a rapid and simple method for quantitative and large-scale characterization of conformational specific protein-DNA interactions.

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

PubMed

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

2013-06-21

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

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

Gentry, T.; Schadt, C.; Zhou, J.

Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics

PubMed Central

Röst, Hannes L.; Liu, Yansheng; D’Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C.; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-01-01

Large scale, quantitative proteomic studies have become essential for the analysis of clinical cohorts, large perturbation experiments and systems biology studies. While next-generation mass spectrometric techniques such as SWATH-MS have substantially increased throughput and reproducibility, ensuring consistent quantification of thousands of peptide analytes across multiple LC-MS/MS runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we have developed the TRIC software which utilizes fragment ion data to perform cross-run alignment, consistent peak-picking and quantification for high throughput targeted proteomics. TRIC uses a graph-based alignment strategy based on non-linear retention time correction to integrate peak elution information from all LC-MS/MS runs acquired in a study. When compared to state-of-the-art SWATH-MS data analysis, the algorithm was able to reduce the identification error by more than 3-fold at constant recall, while correcting for highly non-linear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem (iPS) cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups and substantially increased the quantitative completeness and biological information in the data, providing insights into protein dynamics of iPS cells. Overall, this study demonstrates the importance of consistent quantification in highly challenging experimental setups, and proposes an algorithm to automate this task, constituting the last missing piece in a pipeline for automated analysis of massively parallel targeted proteomics datasets. PMID:27479329

Noninvasive characterization of the fission yeast cell cycle by monitoring dry mass with digital holographic microscopy.

PubMed

Rappaz, Benjamin; Cano, Elena; Colomb, Tristan; Kühn, Jonas; Depeursinge, Christian; Simanis, Viesturs; Magistretti, Pierre J; Marquet, Pierre

2009-01-01

Digital holography microscopy (DHM) is an optical technique which provides phase images yielding quantitative information about cell structure and cellular dynamics. Furthermore, the quantitative phase images allow the derivation of other parameters, including dry mass production, density, and spatial distribution. We have applied DHM to study the dry mass production rate and the dry mass surface density in wild-type and mutant fission yeast cells. Our study demonstrates the applicability of DHM as a tool for label-free quantitative analysis of the cell cycle and opens the possibility for its use in high-throughput screening.

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

PubMed

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

2018-05-01

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

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

PubMed

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

2012-12-01

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

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

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

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

EPA Science Inventory

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

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

Shin, Jong; Phelan, Paul J.; Chhum, Panharith

2014-11-15

Progressive Multifocal Leukoencephalopathy (PML) is caused by lytic replication of JC virus (JCV) in specific cells of the central nervous system. Like other polyomaviruses, JCV encodes a large T-antigen helicase needed for replication of the viral DNA. Here, we report the development of a luciferase-based, quantitative and high-throughput assay of JCV DNA replication in C33A cells, which, unlike the glial cell lines Hs 683 and U87, accumulate high levels of nuclear T-ag needed for robust replication. Using this assay, we investigated the requirement for different domains of T-ag, and for specific sequences within and flanking the viral origin, in JCVmore » DNA replication. Beyond providing validation of the assay, these studies revealed an important stimulatory role of the transcription factor NF1 in JCV DNA replication. Finally, we show that the assay can be used for inhibitor testing, highlighting its value for the identification of antiviral drugs targeting JCV DNA replication. - Highlights: • Development of a high-throughput screening assay for JCV DNA replication using C33A cells. • Evidence that T-ag fails to accumulate in the nuclei of established glioma cell lines. • Evidence that NF-1 directly promotes JCV DNA replication in C33A cells. • Proof-of-concept that the HTS assay can be used to identify pharmacological inhibitor of JCV DNA replication.« less

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-08-20

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

Open Port Probe Sampling Interface for the Direct Coupling of Biocompatible Solid-Phase Microextraction to Atmospheric Pressure Ionization Mass Spectrometry.

PubMed

Gómez-Ríos, Germán Augusto; Liu, Chang; Tascon, Marcos; Reyes-Garcés, Nathaly; Arnold, Don W; Covey, Thomas R; Pawliszyn, Janusz

2017-04-04

In recent years, the direct coupling of solid phase microextraction (SPME) and mass spectrometry (MS) has shown its great potential to improve limits of quantitation, accelerate analysis throughput, and diminish potential matrix effects when compared to direct injection to MS. In this study, we introduce the open port probe (OPP) as a robust interface to couple biocompatible SPME (Bio-SPME) fibers to MS systems for direct electrospray ionization. The presented design consisted of minimal alterations to the front-end of the instrument and provided better sensitivity, simplicity, speed, wider compound coverage, and high-throughput in comparison to the LC-MS based approach. Quantitative determination of clenbuterol, fentanyl, and buprenorphine was successfully achieved in human urine. Despite the use of short extraction/desorption times (5 min/5 s), limits of quantitation below the minimum required performance levels (MRPL) set by the world antidoping agency (WADA) were obtained with good accuracy (≥90%) and linearity (R 2 > 0.99) over the range evaluated for all analytes using sample volumes of 300 μL. In-line technologies such as multiple reaction monitoring with multistage fragmentation (MRM 3 ) and differential mobility spectrometry (DMS) were used to enhance the selectivity of the method without compromising analysis speed. On the basis of calculations, once coupled to high throughput, this method can potentially yield preparation times as low as 15 s per sample based on the 96-well plate format. Our results demonstrated that Bio-SPME-OPP-MS efficiently integrates sampling/sample cleanup and atmospheric pressure ionization, making it an advantageous configuration for several bioanalytical applications, including doping in sports, in vivo tissue sampling, and therapeutic drug monitoring.

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

PubMed

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

2006-08-01

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

A Rapid and Quantitative Flow Cytometry Method for the Analysis of Membrane Disruptive Antimicrobial Activity.

PubMed

O'Brien-Simpson, Neil M; Pantarat, Namfon; Attard, Troy J; Walsh, Katrina A; Reynolds, Eric C

2016-01-01

We describe a microbial flow cytometry method that quantifies within 3 hours antimicrobial peptide (AMP) activity, termed Minimum Membrane Disruptive Concentration (MDC). Increasing peptide concentration positively correlates with the extent of bacterial membrane disruption and the calculated MDC is equivalent to its MBC. The activity of AMPs representing three different membranolytic modes of action could be determined for a range of Gram positive and negative bacteria, including the ESKAPE pathogens, E. coli and MRSA. By using the MDC50 concentration of the parent AMP, the method provides high-throughput, quantitative screening of AMP analogues. A unique feature of the MDC assay is that it directly measures peptide/bacteria interactions and lysed cell numbers rather than bacteria survival as with MIC and MBC assays. With the threat of multi-drug resistant bacteria, this high-throughput MDC assay has the potential to aid in the development of novel antimicrobials that target bacteria with improved efficacy.

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

PubMed

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

2017-02-21

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

Structuring intuition with theory: The high-throughput way

NASA Astrophysics Data System (ADS)

Fornari, Marco

2015-03-01

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

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

PubMed

Röst, Hannes L; Liu, Yansheng; D'Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi

2016-09-01

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

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

PubMed Central

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

2012-01-01

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

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

PubMed

Moutsatsos, Ioannis K; Parker, Christian N

2016-01-01

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

Breast cancer diagnosis using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-11-01

The standard practice in histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope to diagnose whether a lesion is benign or malignant. This determination is made based on a manual, qualitative inspection, making it subject to investigator bias and resulting in low throughput. Hence, a quantitative, label-free, and high-throughput diagnosis method is highly desirable. We present here preliminary results showing the potential of quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated phase maps of unstained breast tissue biopsies using spatial light interference microscopy (SLIM). As a first step toward quantitative diagnosis based on SLIM, we carried out a qualitative evaluation of our label-free images. These images were shown to two pathologists who classified each case as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on corresponding H&E stained tissue images and the number of agreements were counted. The agreement between SLIM and H&E based diagnosis was 88% for the first pathologist and 87% for the second. Our results demonstrate the potential and promise of SLIM for quantitative, label-free, and high-throughput diagnosis.

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

PubMed

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

2010-04-15

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

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

PubMed Central

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

2010-01-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

PubMed

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

2015-01-01

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

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

PubMed Central

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

2011-01-01

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

A Microfluidic Platform for High-Throughput Multiplexed Protein Quantitation

PubMed Central

Volpetti, Francesca; Garcia-Cordero, Jose; Maerkl, Sebastian J.

2015-01-01

We present a high-throughput microfluidic platform capable of quantitating up to 384 biomarkers in 4 distinct samples by immunoassay. The microfluidic device contains 384 unit cells, which can be individually programmed with pairs of capture and detection antibody. Samples are quantitated in each unit cell by four independent MITOMI detection areas, allowing four samples to be analyzed in parallel for a total of 1,536 assays per device. We show that the device can be pre-assembled and stored for weeks at elevated temperature and we performed proof-of-concept experiments simultaneously quantitating IL-6, IL-1β, TNF-α, PSA, and GFP. Finally, we show that the platform can be used to identify functional antibody combinations by screening 64 antibody combinations requiring up to 384 unique assays per device. PMID:25680117

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

PubMed Central

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

2015-01-01

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

High-Throughput Analysis and Automation for Glycomics Studies.

PubMed

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

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

AI-augmented time stretch microscopy

NASA Astrophysics Data System (ADS)

Mahjoubfar, Ata; Chen, Claire L.; Lin, Jiahao; Jalali, Bahram

2017-02-01

Cell reagents used in biomedical analysis often change behavior of the cells that they are attached to, inhibiting their native signaling. On the other hand, label-free cell analysis techniques have long been viewed as challenging either due to insufficient accuracy by limited features, or because of low throughput as a sacrifice of improved precision. We present a recently developed artificial-intelligence augmented microscope, which builds upon high-throughput time stretch quantitative phase imaging (TS-QPI) and deep learning to perform label-free cell classification with record high-accuracy. Our system captures quantitative optical phase and intensity images simultaneously by frequency multiplexing, extracts multiple biophysical features of the individual cells from these images fused, and feeds these features into a supervised machine learning model for classification. The enhanced performance of our system compared to other label-free assays is demonstrated by classification of white blood T-cells versus colon cancer cells and lipid accumulating algal strains for biofuel production, which is as much as five-fold reduction in inaccuracy. This system obtains the accuracy required in practical applications such as personalized drug development, while the cells remain intact and the throughput is not sacrificed. Here, we introduce a data acquisition scheme based on quadrature phase demodulation that enables interruptionless storage of TS-QPI cell images. Our proof of principle demonstration is capable of saving 40 TB of cell images in about four hours, i.e. pictures of every single cell in 10 mL of a sample.

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

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

Bhandari, Deepak; Van Berkel, Gary J

2012-01-01

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

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

PubMed

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

2016-07-01

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

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

PubMed

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

2018-06-01

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

Quantitative characterization of conformational-specific protein-DNA binding using a dual-spectral interferometric imaging biosensor

NASA Astrophysics Data System (ADS)

Zhang, Xirui; Daaboul, George G.; Spuhler, Philipp S.; Dröge, Peter; Ünlü, M. Selim

2016-03-01

DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are not fully understood. Recently, it was discovered that DNA-binding proteins recognize specific binding sites to carry out their functions through an indirect readout mechanism by recognizing and capturing DNA conformational flexibility and deformation. High-throughput DNA microarray-based methods that provide large-scale protein-DNA binding information have shown effective and comprehensive analysis of protein-DNA binding affinities, but do not provide information of DNA conformational changes in specific protein-DNA complexes. Building on the high-throughput capability of DNA microarrays, we demonstrate a quantitative approach that simultaneously measures the amount of protein binding to DNA and nanometer-scale DNA conformational change induced by protein binding in a microarray format. Both measurements rely on spectral interferometry on a layered substrate using a single optical instrument in two distinct modalities. In the first modality, we quantitate the amount of binding of protein to surface-immobilized DNA in each DNA spot using a label-free spectral reflectivity technique that accurately measures the surface densities of protein and DNA accumulated on the substrate. In the second modality, for each DNA spot, we simultaneously measure DNA conformational change using a fluorescence vertical sectioning technique that determines average axial height of fluorophores tagged to specific nucleotides of the surface-immobilized DNA. The approach presented in this paper, when combined with current high-throughput DNA microarray-based technologies, has the potential to serve as a rapid and simple method for quantitative and large-scale characterization of conformational specific protein-DNA interactions.DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are not fully understood. Recently, it was discovered that DNA-binding proteins recognize specific binding sites to carry out their functions through an indirect readout mechanism by recognizing and capturing DNA conformational flexibility and deformation. High-throughput DNA microarray-based methods that provide large-scale protein-DNA binding information have shown effective and comprehensive analysis of protein-DNA binding affinities, but do not provide information of DNA conformational changes in specific protein-DNA complexes. Building on the high-throughput capability of DNA microarrays, we demonstrate a quantitative approach that simultaneously measures the amount of protein binding to DNA and nanometer-scale DNA conformational change induced by protein binding in a microarray format. Both measurements rely on spectral interferometry on a layered substrate using a single optical instrument in two distinct modalities. In the first modality, we quantitate the amount of binding of protein to surface-immobilized DNA in each DNA spot using a label-free spectral reflectivity technique that accurately measures the surface densities of protein and DNA accumulated on the substrate. In the second modality, for each DNA spot, we simultaneously measure DNA conformational change using a fluorescence vertical sectioning technique that determines average axial height of fluorophores tagged to specific nucleotides of the surface-immobilized DNA. The approach presented in this paper, when combined with current high-throughput DNA microarray-based technologies, has the potential to serve as a rapid and simple method for quantitative and large-scale characterization of conformational specific protein-DNA interactions. Electronic supplementary information (ESI) available: DNA sequences and nomenclature (Table 1S); SDS-PAGE assay of IHF stock solution (Fig. 1S); determination of the concentration of IHF stock solution by Bradford assay (Fig. 2S); equilibrium binding isotherm fitting results of other DNA sequences (Table 2S); calculation of dissociation constants (Fig. 3S, 4S; Table 2S); geometric model for quantitation of DNA bending angle induced by specific IHF binding (Fig. 4S); customized flow cell assembly (Fig. 5S); real-time measurement of average fluorophore height change by SSFM (Fig. 6S); summary of binding parameters obtained from additive isotherm model fitting (Table 3S); average surface densities of 10 dsDNA spots and bound IHF at equilibrium (Table 4S); effects of surface densities on the binding and bending of dsDNA (Tables 5S, 6S and Fig. 7S-10S). See DOI: 10.1039/c5nr06785e

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2006-10-16

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

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

PubMed Central

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

2014-01-01

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

Optofluidic time-stretch quantitative phase microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Wu, Yi; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Lee, Sangwook; Isozaki, Akihiro; Li, Ming; Jiang, Yiyue; Yasumoto, Atsushi; Di Carlo, Dino; Tanaka, Yo; Yatomi, Yutaka; Ozeki, Yasuyuki; Goda, Keisuke

2018-03-01

Innovations in optical microscopy have opened new windows onto scientific research, industrial quality control, and medical practice over the last few decades. One of such innovations is optofluidic time-stretch quantitative phase microscopy - an emerging method for high-throughput quantitative phase imaging that builds on the interference between temporally stretched signal and reference pulses by using dispersive properties of light in both spatial and temporal domains in an interferometric configuration on a microfluidic platform. It achieves the continuous acquisition of both intensity and phase images with a high throughput of more than 10,000 particles or cells per second by overcoming speed limitations that exist in conventional quantitative phase imaging methods. Applications enabled by such capabilities are versatile and include characterization of cancer cells and microalgal cultures. In this paper, we review the principles and applications of optofluidic time-stretch quantitative phase microscopy and discuss its future perspective. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2013-01-01

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

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

PubMed Central

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

2015-01-01

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

High-Throughput Assessment of Cellular Mechanical Properties.

PubMed

Darling, Eric M; Di Carlo, Dino

2015-01-01

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

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

PubMed

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

2017-08-15

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

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

PubMed

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

2007-03-27

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

High-speed Fourier ptychographic microscopy based on programmable annular illuminations.

PubMed

Sun, Jiasong; Zuo, Chao; Zhang, Jialin; Fan, Yao; Chen, Qian

2018-05-16

High-throughput quantitative phase imaging (QPI) is essential to cellular phenotypes characterization as it allows high-content cell analysis and avoids adverse effects of staining reagents on cellular viability and cell signaling. Among different approaches, Fourier ptychographic microscopy (FPM) is probably the most promising technique to realize high-throughput QPI by synthesizing a wide-field, high-resolution complex image from multiple angle-variably illuminated, low-resolution images. However, the large dataset requirement in conventional FPM significantly limits its imaging speed, resulting in low temporal throughput. Moreover, the underlying theoretical mechanism as well as optimum illumination scheme for high-accuracy phase imaging in FPM remains unclear. Herein, we report a high-speed FPM technique based on programmable annular illuminations (AIFPM). The optical-transfer-function (OTF) analysis of FPM reveals that the low-frequency phase information can only be correctly recovered if the LEDs are precisely located at the edge of the objective numerical aperture (NA) in the frequency space. By using only 4 low-resolution images corresponding to 4 tilted illuminations matching a 10×, 0.4 NA objective, we present the high-speed imaging results of in vitro Hela cells mitosis and apoptosis at a frame rate of 25 Hz with a full-pitch resolution of 655 nm at a wavelength of 525 nm (effective NA = 0.8) across a wide field-of-view (FOV) of 1.77 mm 2 , corresponding to a space-bandwidth-time product of 411 megapixels per second. Our work reveals an important capability of FPM towards high-speed high-throughput imaging of in vitro live cells, achieving video-rate QPI performance across a wide range of scales, both spatial and temporal.

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

PubMed

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

2017-04-11

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

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Fluorescence-based Western blotting for quantitation of protein biomarkers in clinical samples.

PubMed

Zellner, Maria; Babeluk, Rita; Diestinger, Michael; Pirchegger, Petra; Skeledzic, Senada; Oehler, Rudolf

2008-09-01

Since most high throughput techniques used in biomarker discovery are very time and cost intensive, highly specific and quantitative analytical alternative application methods are needed for the routine analysis. Conventional Western blotting allows detection of specific proteins to the level of single isotypes while its quantitative accuracy is rather limited. We report a novel and improved quantitative Western blotting method. The use of fluorescently labelled secondary antibodies strongly extends the dynamic range of the quantitation and improves the correlation with the protein amount (r=0.997). By an additional fluorescent staining of all proteins immediately after their transfer to the blot membrane, it is possible to visualise simultaneously the antibody binding and the total protein profile. This allows for an accurate correction for protein load. Applying this normalisation it could be demonstrated that fluorescence-based Western blotting is able to reproduce a quantitative analysis of two specific proteins in blood platelet samples from 44 subjects with different diseases as initially conducted by 2D-DIGE. These results show that the proposed fluorescence-based Western blotting is an adequate application technique for biomarker quantitation and suggest possibilities of employment that go far beyond.

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

The major-effect quantitative trait locus CsARN6.1 encodes an AAA ATPase domain-containing protein that is associated with waterlogging stress tolerance by promoting adventitious root formation

USDA-ARS?s Scientific Manuscript database

In plants, the formation of hypocotyl-derived adventitious roots (AR) is an important morphological acclimation to waterlogging stress, but its genetic basis is largely unknown. In the present study, with combined use of bulked segregant analysis-based high throughput next-gen whole genome sequencin...

Molecular and Cellular Quantitative Microscopy: theoretical investigations, technological developments and applications to neurobiology

NASA Astrophysics Data System (ADS)

Esposito, Alessandro

2006-05-01

This PhD project aims at the development and evaluation of microscopy techniques for the quantitative detection of molecular interactions and cellular features. The primarily investigated techniques are Fαrster Resonance Energy Transfer imaging and Fluorescence Lifetime Imaging Microscopy. These techniques have the capability to quantitatively probe the biochemical environment of fluorophores. An automated microscope capable of unsupervised operation has been developed that enables the investigation of molecular and cellular properties at high throughput levels and the analysis of cellular heterogeneity. State-of-the-art Förster Resonance Energy Transfer imaging, Fluorescence Lifetime Imaging Microscopy, Confocal Laser Scanning Microscopy and the newly developed tools have been combined with cellular and molecular biology techniques for the investigation of protein-protein interactions, oligomerization and post-translational modifications of α-Synuclein and Tau, two proteins involved in Parkinson’s and Alzheimer’s disease, respectively. The high inter-disciplinarity of this project required the merging of the expertise of both the Molecular Biophysics Group at the Debye Institute - Utrecht University and the Cell Biophysics Group at the European Neuroscience Institute - Gαttingen University. This project was conducted also with the support and the collaboration of the Center for the Molecular Physiology of the Brain (Göttingen), particularly with the groups associated with the Molecular Quantitative Microscopy and Parkinson’s Disease and Aggregopathies areas. This work demonstrates that molecular and cellular quantitative microscopy can be used in combination with high-throughput screening as a powerful tool for the investigation of the molecular mechanisms of complex biological phenomena like those occurring in neurodegenerative diseases.

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

PubMed

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

2018-01-01

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

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

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

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

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

PubMed

Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

2008-01-23

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

Peroxisystem: harnessing systems cell biology to study peroxisomes.

PubMed

Schuldiner, Maya; Zalckvar, Einat

2015-04-01

In recent years, high-throughput experimentation with quantitative analysis and modelling of cells, recently dubbed systems cell biology, has been harnessed to study the organisation and dynamics of simple biological systems. Here, we suggest that the peroxisome, a fascinating dynamic organelle, can be used as a good candidate for studying a complete biological system. We discuss several aspects of peroxisomes that can be studied using high-throughput systematic approaches and be integrated into a predictive model. Such approaches can be used in the future to study and understand how a more complex biological system, like a cell and maybe even ultimately a whole organism, works. © 2015 Société Française des Microscopies and Société de Biologie Cellulaire de France. Published by John Wiley & Sons Ltd.

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

PubMed Central

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

2010-01-01

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

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

PubMed

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

2016-09-12

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

Bibliometrics for Social Validation.

PubMed

Hicks, Daniel J

2016-01-01

This paper introduces a bibliometric, citation network-based method for assessing the social validation of novel research, and applies this method to the development of high-throughput toxicology research at the US Environmental Protection Agency. Social validation refers to the acceptance of novel research methods by a relevant scientific community; it is formally independent of the technical validation of methods, and is frequently studied in history, philosophy, and social studies of science using qualitative methods. The quantitative methods introduced here find that high-throughput toxicology methods are spread throughout a large and well-connected research community, which suggests high social validation. Further assessment of social validation involving mixed qualitative and quantitative methods are discussed in the conclusion.

Bibliometrics for Social Validation

PubMed Central

2016-01-01

This paper introduces a bibliometric, citation network-based method for assessing the social validation of novel research, and applies this method to the development of high-throughput toxicology research at the US Environmental Protection Agency. Social validation refers to the acceptance of novel research methods by a relevant scientific community; it is formally independent of the technical validation of methods, and is frequently studied in history, philosophy, and social studies of science using qualitative methods. The quantitative methods introduced here find that high-throughput toxicology methods are spread throughout a large and well-connected research community, which suggests high social validation. Further assessment of social validation involving mixed qualitative and quantitative methods are discussed in the conclusion. PMID:28005974

Quantitative Analysis for Installation Access Planning at Naval Base San Diego

DTIC Science & Technology

2012-09-01

VPH in one processing lane, then we can assume that if the SECO were to open another sentry processing lane, the total throughput of both lanes would...be 600 VPH . Similarly, if two sentries in tandem can produce a throughput of 500 VPH , then having two lanes with two sentries in tandem each will...produce a total throughput of 1000 VPH . We assume throughout that there is no server idleness and so there is essentially an infinite backlog of

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop plants with large and complex genomes. PMID:29250096

Validation of high-throughput single cell analysis methodology.

PubMed

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

2014-05-01

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

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

PubMed Central

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

2015-01-01

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

QUANTITATIVE MASS SPECTROMETRIC ANALYSIS OF GLYCOPROTEINS COMBINED WITH ENRICHMENT METHODS

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2009-01-01

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

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

PubMed Central

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

2016-01-01

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

Quantitative Developments of Biomolecular Databases, Measurement Methodology, and Comprehensive Transport Models for Bioanalytical Microfluidics

DTIC Science & Technology

2006-10-01

Gibbs, E. M., Fletterick, R. J., Day, Y. S. N., Myszka, D. G., and Rath, V. L. (2002) “Structure-activity analysis of the purine-binding site of human ...Rich, R. L., Day, Y. S. N., Morton, T. A., and Myszka, D. G., (2001) “High- resolution and high-throughput protocols for measuring drug/ human serum...entire text) 1. Attard, P., Images of nanobubbles on hydrophobic surfaces and their interactions. Phys. Rev. Lett., 2001. 87. 2. Ottino, J.M

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments.

PubMed

Martin, Daniel B; Holzman, Ted; May, Damon; Peterson, Amelia; Eastham, Ashley; Eng, Jimmy; McIntosh, Martin

2008-11-01

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

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

PubMed

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

2017-10-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

Jankowsky, Eckhard; Harris, Michael E

2017-04-15

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

Rapid, quantitative analysis of ppm/ppb nicotine using surface-enhanced Raman scattering from polymer-encapsulated Ag nanoparticles (gel-colls).

PubMed

Bell, Steven E J; Sirimuthu, Narayana M S

2004-11-01

Rapid, quantitative SERS analysis of nicotine at ppm/ppb levels has been carried out using stable and inexpensive polymer-encapsulated Ag nanoparticles (gel-colls). The strongest nicotine band (1030 cm(-1)) was measured against d(5)-pyridine internal standard (974 cm(-1)) which was introduced during preparation of the stock gel-colls. Calibration plots of I(nic)/I(pyr) against the concentration of nicotine were non-linear but plotting I(nic)/I(pyr) against [nicotine](x)(x = 0.6-0.75, depending on the exact experimental conditions) gave linear calibrations over the range (0.1-10 ppm) with R(2) typically ca. 0.998. The RMS prediction error was found to be 0.10 ppm when the gel-colls were used for quantitative determination of unknown nicotine samples in 1-5 ppm level. The main advantages of the method are that the gel-colls constitute a highly stable and reproducible SERS medium that allows high throughput (50 sample h(-1)) measurements.

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

PubMed

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

2013-08-06

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

Precise, High-throughput Analysis of Bacterial Growth.

PubMed

Kurokawa, Masaomi; Ying, Bei-Wen

2017-09-19

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

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

PubMed

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

2015-11-01

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

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

PubMed

Ule, Jernej

2009-12-01

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

Metrologies for quantitative nanomechanical testing and quality control in semiconductor manufacturing

NASA Astrophysics Data System (ADS)

Pratt, Jon R.; Kramar, John A.; Newell, David B.; Smith, Douglas T.

2005-05-01

If nanomechanical testing is to evolve into a tool for process and quality control in semiconductor fabrication, great advances in throughput, repeatability, and accuracy of the associated instruments and measurements will be required. A recent grant awarded by the NIST Advanced Technology Program seeks to address the throughput issue by developing a high-speed AFM-based platform for quantitative nanomechanical measurements. The following paper speaks to the issue of quantitative accuracy by presenting an overview of various standards and techniques under development at NIST and other national metrology institutes (NMIs) that can provide a metrological basis for nanomechanical testing. The infrastructure we describe places firm emphasis on traceability to the International System of Units, paving the way for truly quantitative, rather than qualitative, physical property testing.

Universal and specific quantitative detection of botulinum neurotoxin genes

PubMed Central

2010-01-01

Background Clostridium botulinum, an obligate anaerobic spore-forming bacterium, produces seven antigenic variants of botulinum toxin that are distinguished serologically and termed "serotypes". Botulinum toxin blocks the release of acetylcholine at neuromuscular junctions resulting in flaccid paralysis. The potential lethality of the disease warrants a fast and accurate means of diagnosing suspected instances of food contamination or human intoxication. Currently, the Food and Drug Administration (FDA)-accepted assay to detect and type botulinum neurotoxins (BoNTs) is the mouse protection bioassay. While specific and sensitive, this assay requires the use of laboratory animals, may take up to four days to achieve a diagnosis, and is unsuitable for high-throughput analysis. We report here a two-step PCR assay that identifies all toxin types, that achieves the specificity of the mouse bioassay while surpassing it in equivalent sensitivity, that has capability for high-throughput analysis, and that provides quantitative results within hours. The first step of our assay consists of a conventional PCR that detects the presence of C. botulinum regardless of the neurotoxin type. The second step uses quantitative PCR (qPCR) technology to determine the specific serotype of the neurotoxin. Results We assayed purified C. botulinum DNA and crude toxin preparations, as well as food and stool from healthy individuals spiked with purified BoNT DNA, and one stool sample from a case of infant botulism for the presence of the NTNH gene, which is part of the BoNT gene cluster, and for the presence of serotype-specific BoNT genes. The PCR surpassed the mouse bioassay both in specificity and sensitivity, detecting positive signals in BoNT preparations containing well below the 1 LD50 required for detection via the mouse bioassay. These results were type-specific and we were reliably able to quantify as few as 10 genomic copies. Conclusions While other studies have reported conventional or quantitative PCR-based assays for the detection of C. botulinum genes, our procedure's high-throughput capability and its portability allows most laboratories to quickly assess the possible presence of BoNTs either in food processing samples or in suspected cases of botulism. Thus, this assay provides rapid and specific detection of BoNT and toxin complex genes and would enable the targeting of appropriate therapeutics to infected individuals in a timely manner. PMID:20961439

Droplet microfluidics--a tool for single-cell analysis.

PubMed

Joensson, Haakan N; Andersson Svahn, Helene

2012-12-03

Droplet microfluidics allows the isolation of single cells and reagents in monodisperse picoliter liquid capsules and manipulations at a throughput of thousands of droplets per second. These qualities allow many of the challenges in single-cell analysis to be overcome. Monodispersity enables quantitative control of solute concentrations, while encapsulation in droplets provides an isolated compartment for the single cell and its immediate environment. The high throughput allows the processing and analysis of the tens of thousands to millions of cells that must be analyzed to accurately describe a heterogeneous cell population so as to find rare cell types or access sufficient biological space to find hits in a directed evolution experiment. The low volumes of the droplets make very large screens economically viable. This Review gives an overview of the current state of single-cell analysis involving droplet microfluidics and offers examples where droplet microfluidics can further biological understanding. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

Rapid analysis and exploration of fluorescence microscopy images.

PubMed

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

2014-03-19

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

A rapid high-resolution method for resolving DNA topoisomers.

PubMed

Mitchenall, Lesley A; Hipkin, Rachel E; Piperakis, Michael M; Burton, Nicolas P; Maxwell, Anthony

2018-01-16

Agarose gel electrophoresis has been the mainstay technique for the analysis of DNA samples of moderate size. In addition to separating linear DNA molecules, it can also resolve different topological forms of plasmid DNAs, an application useful for the analysis of the reactions of DNA topoisomerases. However, gel electrophoresis is an intrinsically low-throughput technique and suffers from other potential disadvantages. We describe the application of the QIAxcel Advanced System, a high-throughput capillary electrophoresis system, to separate DNA topoisomers, and compare this technique with gel electrophoresis. We prepared a range of topoisomers of plasmids pBR322 and pUC19, and a 339 bp DNA minicircle, and compared their separation by gel electrophoresis and the QIAxcel System. We found superior resolution with the QIAxcel System, and that quantitative analysis of topoisomer distributions was straightforward. We show that the QIAxcel system has advantages in terms of speed, resolution and cost, and can be applied to DNA circles of various sizes. It can readily be adapted for use in compound screening against topoisomerase targets.

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

PubMed

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

2008-01-01

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

Diagnosis of breast cancer biopsies using quantitative phase imaging

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-03-01

The standard practice in the histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope. The pathologist looks at certain morphological features, visible under the stain, to diagnose whether a tumor is benign or malignant. This determination is made based on qualitative inspection making it subject to investigator bias. Furthermore, since this method requires a microscopic examination by the pathologist it suffers from low throughput. A quantitative, label-free and high throughput method for detection of these morphological features from images of tissue biopsies is, hence, highly desirable as it would assist the pathologist in making a quicker and more accurate diagnosis of cancers. We present here preliminary results showing the potential of using quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated optical path length maps of unstained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM). As a first step towards diagnosis based on quantitative phase imaging, we carried out a qualitative evaluation of the imaging resolution and contrast of our label-free phase images. These images were shown to two pathologists who marked the tumors present in tissue as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on H&E stained tissue images and the number of agreements were counted. In our experiment, the agreement between SLIM and H&E based diagnosis was measured to be 88%. Our preliminary results demonstrate the potential and promise of SLIM for a push in the future towards quantitative, label-free and high throughput diagnosis.

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

PubMed

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

2007-02-01

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

An open-source computational and data resource to analyze digital maps of immunopeptidomes

DOE PAGES

Caron, Etienne; Espona, Lucia; Kowalewski, Daniel J.; ...

2015-07-08

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies.

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

PubMed

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

2012-07-26

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

Neutral desorption extractive electrospray ionization mass spectrometry for fast screening sunscreen agents in cream cosmetic products.

PubMed

Zhang, Xinglei; Liu, Yan; Zhang, Jinghua; Hu, Zhong; Hu, Bin; Ding, Liying; Jia, Li; Chen, Huanwen

2011-09-15

High throughput analysis of sunscreen agents present in cream cosmetic has been demonstrated, typically 2 samples per minute, using neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) without sample pretreatment. For the targeted compounds such as 4-Aminobenzoic acid and oxybenzone, ND-EESI-MS method provided linear signal responses in the range of 1-100 ppb. Limits of detection (LOD) of the method were estimated at sub-ppb levels for the analytes tested. Reasonable relative standard deviation (RSD=8.4-16.0%) was obtained as a result of 10 independent measurements for commercial cosmetics samples spiked with each individual sunscreen agents at 1-10 ppb. Acceptable recoveries were achieved in the range of 87-116% for direct analysis of commercial cream cosmetic samples. The experimental data demonstrate that ND-EESI-MS is a useful tool for high throughput screening of sunscreen agents in highly viscous cream cosmetic products, with the capability to obtain quantitative information of the analytes. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-05-15

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

Ultrafast Microfluidic Cellular Imaging by Optical Time-Stretch.

PubMed

Lau, Andy K S; Wong, Terence T W; Shum, Ho Cheung; Wong, Kenneth K Y; Tsia, Kevin K

2016-01-01

There is an unmet need in biomedicine for measuring a multitude of parameters of individual cells (i.e., high content) in a large population efficiently (i.e., high throughput). This is particularly driven by the emerging interest in bringing Big-Data analysis into this arena, encompassing pathology, drug discovery, rare cancer cell detection, emulsion microdroplet assays, to name a few. This momentum is particularly evident in recent advancements in flow cytometry. They include scaling of the number of measurable colors from the labeled cells and incorporation of imaging capability to access the morphological information of the cells. However, an unspoken predicament appears in the current technologies: higher content comes at the expense of lower throughput, and vice versa. For example, accessing additional spatial information of individual cells, imaging flow cytometers only achieve an imaging throughput ~1000 cells/s, orders of magnitude slower than the non-imaging flow cytometers. In this chapter, we introduce an entirely new imaging platform, namely optical time-stretch microscopy, for ultrahigh speed and high contrast label-free single-cell (in a ultrafast microfluidic flow up to 10 m/s) imaging and analysis with an ultra-fast imaging line-scan rate as high as tens of MHz. Based on this technique, not only morphological information of the individual cells can be obtained in an ultrafast manner, quantitative evaluation of cellular information (e.g., cell volume, mass, refractive index, stiffness, membrane tension) at nanometer scale based on the optical phase is also possible. The technology can also be integrated with conventional fluorescence measurements widely adopted in the non-imaging flow cytometers. Therefore, these two combinatorial and complementary measurement capabilities in long run is an attractive platform for addressing the pressing need for expanding the "parameter space" in high-throughput single-cell analysis. This chapter provides the general guidelines of constructing the optical system for time stretch imaging, fabrication and design of the microfluidic chip for ultrafast fluidic flow, as well as the image acquisition and processing.

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

PubMed

Sun, T; Chen, L; Zhang, W

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

Stoltzfus, Caleb; Mikhailov, Alexandr; Rebane, Aleksander

2017-02-01

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

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

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

PubMed

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

2018-05-08

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2017-12-21

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

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

PubMed

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

2017-02-01

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

COMPASS: a suite of pre- and post-search proteomics software tools for OMSSA

PubMed Central

Wenger, Craig D.; Phanstiel, Douglas H.; Lee, M. Violet; Bailey, Derek J.; Coon, Joshua J.

2011-01-01

Here we present the Coon OMSSA Proteomic Analysis Software Suite (COMPASS): a free and open-source software pipeline for high-throughput analysis of proteomics data, designed around the Open Mass Spectrometry Search Algorithm. We detail a synergistic set of tools for protein database generation, spectral reduction, peptide false discovery rate analysis, peptide quantitation via isobaric labeling, protein parsimony and protein false discovery rate analysis, and protein quantitation. We strive for maximum ease of use, utilizing graphical user interfaces and working with data files in the original instrument vendor format. Results are stored in plain text comma-separated values files, which are easy to view and manipulate with a text editor or spreadsheet program. We illustrate the operation and efficacy of COMPASS through the use of two LC–MS/MS datasets. The first is a dataset of a highly annotated mixture of standard proteins and manually validated contaminants that exhibits the identification workflow. The second is a dataset of yeast peptides, labeled with isobaric stable isotope tags and mixed in known ratios, to demonstrate the quantitative workflow. For these two datasets, COMPASS performs equivalently or better than the current de facto standard, the Trans-Proteomic Pipeline. PMID:21298793

Droplet barcoding for single cell transcriptomics applied to embryonic stem cells

PubMed Central

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-01-01

Summary It has long been the dream of biologists to map gene expression at the single cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after LIF withdrawal. The reproducibility of these high-throughput single cell data allowed us to deconstruct cell populations and infer gene expression relationships. PMID:26000487

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Identification of Novel Pro-Migratory, Cancer-Associated Genes Using Quantitative, Microscopy-Based Screening

PubMed Central

Naffar-Abu-Amara, Suha; Shay, Tal; Galun, Meirav; Cohen, Naomi; Isakoff, Steven J.; Kam, Zvi; Geiger, Benjamin

2008-01-01

Background Cell migration is a highly complex process, regulated by multiple genes, signaling pathways and external stimuli. To discover genes or pharmacological agents that can modulate the migratory activity of cells, screening strategies that enable the monitoring of diverse migratory parameters in a large number of samples are necessary. Methodology In the present study, we describe the development of a quantitative, high-throughput cell migration assay, based on a modified phagokinetic tracks (PKT) procedure, and apply it for identifying novel pro-migratory genes in a cancer-related gene library. In brief, cells are seeded on fibronectin-coated 96-well plates, covered with a monolayer of carboxylated latex beads. Motile cells clear the beads, located along their migratory paths, forming tracks that are visualized using an automated, transmitted-light screening microscope. The tracks are then segmented and characterized by multi-parametric, morphometric analysis, resolving a variety of morphological and kinetic features. Conclusions In this screen we identified 4 novel genes derived from breast carcinoma related cDNA library, whose over-expression induces major alteration in the migration of the stationary MCF7 cells. This approach can serve for high throughput screening for novel ways to modulate cellular migration in pathological states such as tumor metastasis and invasion. PMID:18213366

Systems cell biology

PubMed Central

Mast, Fred D.; Ratushny, Alexander V.

2014-01-01

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. PMID:25225336

Composition and Quantitation of Microalgal Lipids by ERETIC 1H NMR Method

PubMed Central

Nuzzo, Genoveffa; Gallo, Carmela; d’Ippolito, Giuliana; Cutignano, Adele; Sardo, Angela; Fontana, Angelo

2013-01-01

Accurate characterization of biomass constituents is a crucial aspect of research in the biotechnological application of natural products. Here we report an efficient, fast and reproducible method for the identification and quantitation of fatty acids and complex lipids (triacylglycerols, glycolipids, phospholipids) in microalgae under investigation for the development of functional health products (probiotics, food ingredients, drugs, etc.) or third generation biofuels. The procedure consists of extraction of the biological matrix by modified Folch method and direct analysis of the resulting material by proton nuclear magnetic resonance (1H NMR). The protocol uses a reference electronic signal as external standard (ERETIC method) and allows assessment of total lipid content, saturation degree and class distribution in both high throughput screening of algal collection and metabolic analysis during genetic or culturing studies. As proof of concept, the methodology was applied to the analysis of three microalgal species (Thalassiosira weissflogii, Cyclotella cryptica and Nannochloropsis salina) which drastically differ for the qualitative and quantitative composition of their fatty acid-based lipids. PMID:24084790

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-08-01

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

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

PubMed

Paiva, Anthony; Shou, Wilson Z

2016-08-01

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

A software suite for the generation and comparison of peptide arrays from sets of data collected by liquid chromatography-mass spectrometry.

PubMed

Li, Xiao-jun; Yi, Eugene C; Kemp, Christopher J; Zhang, Hui; Aebersold, Ruedi

2005-09-01

There is an increasing interest in the quantitative proteomic measurement of the protein contents of substantially similar biological samples, e.g. for the analysis of cellular response to perturbations over time or for the discovery of protein biomarkers from clinical samples. Technical limitations of current proteomic platforms such as limited reproducibility and low throughput make this a challenging task. A new LC-MS-based platform is able to generate complex peptide patterns from the analysis of proteolyzed protein samples at high throughput and represents a promising approach for quantitative proteomics. A crucial component of the LC-MS approach is the accurate evaluation of the abundance of detected peptides over many samples and the identification of peptide features that can stratify samples with respect to their genetic, physiological, or environmental origins. We present here a new software suite, SpecArray, that generates a peptide versus sample array from a set of LC-MS data. A peptide array stores the relative abundance of thousands of peptide features in many samples and is in a format identical to that of a gene expression microarray. A peptide array can be subjected to an unsupervised clustering analysis to stratify samples or to a discriminant analysis to identify discriminatory peptide features. We applied the SpecArray to analyze two sets of LC-MS data: one was from four repeat LC-MS analyses of the same glycopeptide sample, and another was from LC-MS analysis of serum samples of five male and five female mice. We demonstrate through these two study cases that the SpecArray software suite can serve as an effective software platform in the LC-MS approach for quantitative proteomics.

A computational image analysis glossary for biologists.

PubMed

Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

2012-09-01

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

Widely-targeted quantitative lipidomics methodology by supercritical fluid chromatography coupled with fast-scanning triple quadrupole mass spectrometry.

PubMed

Takeda, Hiroaki; Izumi, Yoshihiro; Takahashi, Masatomo; Paxton, Thanai; Tamura, Shohei; Koike, Tomonari; Yu, Ying; Kato, Noriko; Nagase, Katsutoshi; Shiomi, Masashi; Bamba, Takeshi

2018-05-03

Lipidomics, the mass spectrometry-based comprehensive analysis of lipids, has attracted attention as an analytical approach to provide novel insight into lipid metabolism and to search for biomarkers. However, an ideal method for both comprehensive and quantitative analysis of lipids has not been fully developed. Herein, we have proposed a practical methodology for widely-targeted quantitative lipidome analysis using supercritical fluid chromatography fast-scanning triple-quadrupole mass spectrometry (SFC/QqQMS) and theoretically calculated a comprehensive lipid multiple reaction monitoring (MRM) library. Lipid classes can be separated by SFC with a normal phase diethylamine-bonded silica column with high-resolution, high-throughput, and good repeatability. Structural isomers of phospholipids can be monitored by mass spectrometric separation with fatty acyl-based MRM transitions. SFC/QqQMS analysis with an internal standard-dilution method offers quantitative information for both lipid class and individual lipid molecular species in the same lipid class. Additionally, data acquired using this method has advantages including reduction of misidentification and acceleration of data analysis. Using the SFC/QqQMS system, alteration of plasma lipid levels in myocardial infarction-prone rabbits to the supplementation of eicosapentaenoic acid was first observed. Our developed SFC/QqQMS method represents a potentially useful tool for in-depth studies focused on complex lipid metabolism and biomarker discovery. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

Noninvasive High-Throughput Single-Cell Analysis of HIV Protease Activity Using Ratiometric Flow Cytometry

PubMed Central

Gaber, Rok; Majerle, Andreja; Jerala, Roman; Benčina, Mojca

2013-01-01

To effectively fight against the human immunodeficiency virus infection/acquired immunodeficiency syndrome (HIV/AIDS) epidemic, ongoing development of novel HIV protease inhibitors is required. Inexpensive high-throughput screening assays are needed to quickly scan large sets of chemicals for potential inhibitors. We have developed a Förster resonance energy transfer (FRET)-based, HIV protease-sensitive sensor using a combination of a fluorescent protein pair, namely mCerulean and mCitrine. Through extensive in vitro characterization, we show that the FRET-HIV sensor can be used in HIV protease screening assays. Furthermore, we have used the FRET-HIV sensor for intracellular quantitative detection of HIV protease activity in living cells, which more closely resembles an actual viral infection than an in vitro assay. We have developed a high-throughput method that employs a ratiometric flow cytometry for analyzing large populations of cells that express the FRET-HIV sensor. The method enables FRET measurement of single cells with high sensitivity and speed and should be used when subpopulation-specific intracellular activity of HIV protease needs to be estimated. In addition, we have used a confocal microscopy sensitized emission FRET technique to evaluate the usefulness of the FRET-HIV sensor for spatiotemporal detection of intracellular HIV protease activity. PMID:24287545

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

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

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

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

Framework for a Quantitative Systemic Toxicity Model (FutureToxII)

EPA Science Inventory

EPA’s ToxCast program profiles the bioactivity of chemicals in a diverse set of ~700 high throughput screening (HTS) assays. In collaboration with L’Oreal, a quantitative model of systemic toxicity was developed using no effect levels (NEL) from ToxRefDB for 633 chemicals with HT...

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

PubMed Central

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

2012-01-01

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

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

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

Guo, Xuejiang; Tang, Keqi

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers wouldmore » ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode, also known as multiple reaction monitoring (MRM), is capable of quantitatively measuring hundreds of candidate protein biomarkers from a relevant clinical sample in a single analysis. The specificity, reproducibility and sensitivity could be as good as ELISA. Furthermore, SRM MS can also quantify protein isoforms and post-translational modifications, for which traditional antibody-based immunoassays often don’t exist.« less

Quantitative analysis of drug distribution by ambient mass spectrometry imaging method with signal extinction normalization strategy and inkjet-printing technology.

PubMed

Luo, Zhigang; He, Jingjing; He, Jiuming; Huang, Lan; Song, Xiaowei; Li, Xin; Abliz, Zeper

2018-03-01

Quantitative mass spectrometry imaging (MSI) is a robust approach that provides both quantitative and spatial information for drug candidates' research. However, because of complicated signal suppression and interference, acquiring accurate quantitative information from MSI data remains a challenge, especially for whole-body tissue sample. Ambient MSI techniques using spray-based ionization appear to be ideal for pharmaceutical quantitative MSI analysis. However, it is more challenging, as it involves almost no sample preparation and is more susceptible to ion suppression/enhancement. Herein, based on our developed air flow-assisted desorption electrospray ionization (AFADESI)-MSI technology, an ambient quantitative MSI method was introduced by integrating inkjet-printing technology with normalization of the signal extinction coefficient (SEC) using the target compound itself. The method utilized a single calibration curve to quantify multiple tissue types. Basic blue 7 and an antitumor drug candidate (S-(+)-deoxytylophorinidine, CAT) were chosen to initially validate the feasibility and reliability of the quantitative MSI method. Rat tissue sections (heart, kidney, and brain) administered with CAT was then analyzed. The quantitative MSI analysis results were cross-validated by LC-MS/MS analysis data of the same tissues. The consistency suggests that the approach is able to fast obtain the quantitative MSI data without introducing interference into the in-situ environment of the tissue sample, and is potential to provide a high-throughput, economical and reliable approach for drug discovery and development. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-02-15

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

High-throughput label-free screening of euglena gracilis with optofluidic time-stretch quantitative phase microscopy

NASA Astrophysics Data System (ADS)

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

2017-02-01

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis - an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

Systems cell biology.

PubMed

Mast, Fred D; Ratushny, Alexander V; Aitchison, John D

2014-09-15

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. © 2014 Mast et al.

High-throughput analysis of spatio-temporal dynamics in Dictyostelium

PubMed Central

Sawai, Satoshi; Guan, Xiao-Juan; Kuspa, Adam; Cox, Edward C

2007-01-01

We demonstrate a time-lapse video approach that allows rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations. Quantitative information was gathered by sampling life histories of more than 2,000 mutant clones from a large mutagenesis collection. Approximately 4% of the clonal lines showed a mutant phenotype at one stage. Many of these could be ordered by clustering into functional groups. The dataset allows one to search and retrieve movies on a gene-by-gene and phenotype-by-phenotype basis. PMID:17659086

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

PubMed Central

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

2007-01-01

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

High-throughput sequencing in acute lymphoblastic leukemia: Follow-up of minimal residual disease and emergence of new clones.

PubMed

Salson, Mikaël; Giraud, Mathieu; Caillault, Aurélie; Grardel, Nathalie; Duployez, Nicolas; Ferret, Yann; Duez, Marc; Herbert, Ryan; Rocher, Tatiana; Sebda, Shéhérazade; Quief, Sabine; Villenet, Céline; Figeac, Martin; Preudhomme, Claude

2017-02-01

Minimal residual disease (MRD) is known to be an independent prognostic factor in patients with acute lymphoblastic leukemia (ALL). High-throughput sequencing (HTS) is currently used in routine practice for the diagnosis and follow-up of patients with hematological neoplasms. In this retrospective study, we examined the role of immunoglobulin/T-cell receptor-based MRD in patients with ALL by HTS analysis of immunoglobulin H and/or T-cell receptor gamma chain loci in bone marrow samples from 11 patients with ALL, at diagnosis and during follow-up. We assessed the clinical feasibility of using combined HTS and bioinformatics analysis with interactive visualization using Vidjil software. We discuss the advantages and drawbacks of HTS for monitoring MRD. HTS gives a more complete insight of the leukemic population than conventional real-time quantitative PCR (qPCR), and allows identification of new emerging clones at each time point of the monitoring. Thus, HTS monitoring of Ig/TR based MRD is expected to improve the management of patients with ALL. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of adenosine triphosphate affinity probe and scheduled multiple-reaction monitoring analysis for profiling global kinome in human cells in response to arsenite treatment.

PubMed

Guo, Lei; Xiao, Yongsheng; Wang, Yinsheng

2014-11-04

Phosphorylation of cellular components catalyzed by kinases plays important roles in cell signaling and proliferation. Quantitative assessment of perturbation in global kinome may provide crucial knowledge for elucidating the mechanisms underlying the cytotoxic effects of environmental toxicants. Here, we utilized an adenosine triphosphate (ATP) affinity probe coupled with stable isotope labeling by amino acids in cell culture (SILAC) to assess quantitatively the arsenite-induced alteration of global kinome in human cells. We constructed a SILAC-compatible kinome library for scheduled multiple-reaction monitoring (MRM) analysis and adopted on-the-fly recalibration of retention time shift, which provided better throughput of the analytical method and enabled the simultaneous quantification of the expression of ∼300 kinases in two LC-MRM runs. With this improved analytical method, we conducted an in-depth quantitative analysis of the perturbation of kinome of GM00637 human skin fibroblast cells induced by arsenite exposure. Several kinases involved in cell cycle progression, including cyclin-dependent kinases (CDK1 and CDK4) and Aurora kinases A, B, and C, were found to be hyperactivated, and the altered expression of CDK1 was further validated by Western analysis. In addition, treatment with a CDK inhibitor, flavopiridol, partially restored the arsenite-induced growth inhibition of human skin fibroblast cells. Thus, sodium arsenite may confer its cytotoxic effect partly through the aberrant activation of CDKs and the resultant perturbation of cell cycle progression. Together, we developed a high-throughput, SILAC-compatible, and MRM-based kinome profiling method and demonstrated that the method is powerful in deciphering the molecular modes of action of a widespread environmental toxicant. The method should be generally applicable for uncovering the cellular pathways triggered by other extracellular stimuli.

Application of Adenosine Triphosphate Affinity Probe and Scheduled Multiple-Reaction Monitoring Analysis for Profiling Global Kinome in Human Cells in Response to Arsenite Treatment

PubMed Central

2015-01-01

Phosphorylation of cellular components catalyzed by kinases plays important roles in cell signaling and proliferation. Quantitative assessment of perturbation in global kinome may provide crucial knowledge for elucidating the mechanisms underlying the cytotoxic effects of environmental toxicants. Here, we utilized an adenosine triphosphate (ATP) affinity probe coupled with stable isotope labeling by amino acids in cell culture (SILAC) to assess quantitatively the arsenite-induced alteration of global kinome in human cells. We constructed a SILAC-compatible kinome library for scheduled multiple-reaction monitoring (MRM) analysis and adopted on-the-fly recalibration of retention time shift, which provided better throughput of the analytical method and enabled the simultaneous quantification of the expression of ∼300 kinases in two LC-MRM runs. With this improved analytical method, we conducted an in-depth quantitative analysis of the perturbation of kinome of GM00637 human skin fibroblast cells induced by arsenite exposure. Several kinases involved in cell cycle progression, including cyclin-dependent kinases (CDK1 and CDK4) and Aurora kinases A, B, and C, were found to be hyperactivated, and the altered expression of CDK1 was further validated by Western analysis. In addition, treatment with a CDK inhibitor, flavopiridol, partially restored the arsenite-induced growth inhibition of human skin fibroblast cells. Thus, sodium arsenite may confer its cytotoxic effect partly through the aberrant activation of CDKs and the resultant perturbation of cell cycle progression. Together, we developed a high-throughput, SILAC-compatible, and MRM-based kinome profiling method and demonstrated that the method is powerful in deciphering the molecular modes of action of a widespread environmental toxicant. The method should be generally applicable for uncovering the cellular pathways triggered by other extracellular stimuli. PMID:25301106

Lipid Informed Quantitation and Identification

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

Kevin Crowell, PNNL

2014-07-21

LIQUID (Lipid Informed Quantitation and Identification) is a software program that has been developed to enable users to conduct both informed and high-throughput global liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based lipidomics analysis. This newly designed desktop application can quickly identify and quantify lipids from LC-MS/MS datasets while providing a friendly graphical user interface for users to fully explore the data. Informed data analysis simply involves the user specifying an electrospray ionization mode, lipid common name (i.e. PE(16:0/18:2)), and associated charge carrier. A stemplot of the isotopic profile and a line plot of the extracted ion chromatogram are also provided to showmore » the MS-level evidence of the identified lipid. In addition to plots, other information such as intensity, mass measurement error, and elution time are also provided. Typically, a global analysis for 15,000 lipid targets« less

Quantitative Model of Systemic Toxicity Using ToxCast and ToxRefDB (SOT)

EPA Science Inventory

EPA’s ToxCast program profiles the bioactivity of chemicals in a diverse set of ~700 high throughput screening (HTS) assays. In collaboration with L’Oreal, a quantitative model of systemic toxicity was developed using no effect levels (NEL) from ToxRefDB for 633 chemicals with HT...

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

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

2006-06-15

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

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

PubMed

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

2016-02-01

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

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

PubMed Central

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Fast quantitation of opioid isomers in human plasma by differential mobility spectrometry/mass spectrometry via SPME/open-port probe sampling interface.

PubMed

Liu, Chang; Gómez-Ríos, Germán Augusto; Schneider, Bradley B; Le Blanc, J C Yves; Reyes-Garcés, Nathaly; Arnold, Don W; Covey, Thomas R; Pawliszyn, Janusz

2017-10-23

Mass spectrometry (MS) based quantitative approaches typically require a thorough sample clean-up and a decent chromatographic step in order to achieve needed figures of merit. However, in most cases, such processes are not optimal for urgent assessments and high-throughput determinations. The direct coupling of solid phase microextraction (SPME) to MS has shown great potential to shorten the total sample analysis time of complex matrices, as well as to diminish potential matrix effects and instrument contamination. In this study, we demonstrate the use of the open-port probe (OPP) as a direct and robust sampling interface to couple biocompatible-SPME (Bio-SPME) fibres to MS for the rapid quantitation of opioid isomers (i.e. codeine and hydrocodone) in human plasma. In place of chromatography, a differential mobility spectrometry (DMS) device was implemented to provide the essential selectivity required to quantify these constitutional isomers. Taking advantage of the simplified sample preparation process based on Bio-SPME and the fast separation with DMS-MS coupling via OPP, a high-throughput assay (10-15 s per sample) with limits of detection in the sub-ng/mL range was developed. Succinctly, we demonstrated that by tuning adequate ion mobility separation conditions, SPME-OPP-MS can be employed to quantify non-resolved compounds or those otherwise hindered by co-extracted isobaric interferences without further need of coupling to other separation platforms. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep Learning in Label-free Cell Classification

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

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

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

PubMed Central

Sulyok, Michael; Liu, Xingzhong; Rao, Mingyong

2016-01-01

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

Single-Cell Based Quantitative Assay of Chromosome Transmission Fidelity

PubMed Central

Zhu, Jin; Heinecke, Dominic; Mulla, Wahid A.; Bradford, William D.; Rubinstein, Boris; Box, Andrew; Haug, Jeffrey S.; Li, Rong

2015-01-01

Errors in mitosis are a primary cause of chromosome instability (CIN), generating aneuploid progeny cells. Whereas a variety of factors can influence CIN, under most conditions mitotic errors are rare events that have been difficult to measure accurately. Here we report a green fluorescent protein−based quantitative chromosome transmission fidelity (qCTF) assay in budding yeast that allows sensitive and quantitative detection of CIN and can be easily adapted to high-throughput analysis. Using the qCTF assay, we performed genome-wide quantitative profiling of genes that affect CIN in a dosage-dependent manner and identified genes that elevate CIN when either increased (icCIN) or decreased in copy number (dcCIN). Unexpectedly, qCTF screening also revealed genes whose change in copy number quantitatively suppress CIN, suggesting that the basal error rate of the wild-type genome is not minimized, but rather, may have evolved toward an optimal level that balances both stability and low-level karyotype variation for evolutionary adaptation. PMID:25823586

Single-Cell Based Quantitative Assay of Chromosome Transmission Fidelity.

PubMed

Zhu, Jin; Heinecke, Dominic; Mulla, Wahid A; Bradford, William D; Rubinstein, Boris; Box, Andrew; Haug, Jeffrey S; Li, Rong

2015-03-30

Errors in mitosis are a primary cause of chromosome instability (CIN), generating aneuploid progeny cells. Whereas a variety of factors can influence CIN, under most conditions mitotic errors are rare events that have been difficult to measure accurately. Here we report a green fluorescent protein-based quantitative chromosome transmission fidelity (qCTF) assay in budding yeast that allows sensitive and quantitative detection of CIN and can be easily adapted to high-throughput analysis. Using the qCTF assay, we performed genome-wide quantitative profiling of genes that affect CIN in a dosage-dependent manner and identified genes that elevate CIN when either increased (icCIN) or decreased in copy number (dcCIN). Unexpectedly, qCTF screening also revealed genes whose change in copy number quantitatively suppress CIN, suggesting that the basal error rate of the wild-type genome is not minimized, but rather, may have evolved toward an optimal level that balances both stability and low-level karyotype variation for evolutionary adaptation. Copyright © 2015 Zhu et al.

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

PubMed Central

2015-01-01

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

Quantitative High-Throughput Luciferase Screening in Identifying CAR Modulators.

PubMed

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

2016-01-01

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

Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

2016-09-01

We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

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

PubMed

Erickson, Heidi S

2012-09-28

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

Development of high-throughput and high sensitivity capillary gel electrophoresis platform method for Western, Eastern, and Venezuelan equine encephalitis (WEVEE) virus like particles (VLPs) purity determination and characterization.

PubMed

Gollapudi, Deepika; Wycuff, Diane L; Schwartz, Richard M; Cooper, Jonathan W; Cheng, K C

2017-10-01

In this paper, we describe development of a high-throughput, highly sensitive method based on Lab Chip CGE-SDS platform for purity determination and characterization of virus-like particle (VLP) vaccines. A capillary gel electrophoresis approach requiring about 41 s per sample for analysis and demonstrating sensitivity to protein initial concentrations as low as 20 μg/mL, this method has been used previously to evaluate monoclonal antibodies, but this application for lot release assay of VLPs using this platform is unique. The method was qualified and shown to be accurate for the quantitation of VLP purity. Assay repeatability was confirmed to be less than 2% relative standard deviation of the mean (% RSD) with interday precision less than 2% RSD. The assay can evaluate purified VLPs in a concentration range of 20-249 μg/mL for VEE and 20-250 μg/mL for EEE and WEE VLPs. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2009-08-25

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

Subunit mass analysis for monitoring antibody oxidation.

PubMed

Sokolowska, Izabela; Mo, Jingjie; Dong, Jia; Lewis, Michael J; Hu, Ping

2017-04-01

Methionine oxidation is a common posttranslational modification (PTM) of monoclonal antibodies (mAbs). Oxidation can reduce the in-vivo half-life, efficacy and stability of the product. Peptide mapping is commonly used to monitor the levels of oxidation, but this is a relatively time-consuming method. A high-throughput, automated subunit mass analysis method was developed to monitor antibody methionine oxidation. In this method, samples were treated with IdeS, EndoS and dithiothreitol to generate three individual IgG subunits (light chain, Fd' and single chain Fc). These subunits were analyzed by reversed phase-ultra performance liquid chromatography coupled with an online quadrupole time-of-flight mass spectrometer and the levels of oxidation on each subunit were quantitated based on the deconvoluted mass spectra using the UNIFI software. The oxidation results obtained by subunit mass analysis correlated well with the results obtained by peptide mapping. Method qualification demonstrated that this subunit method had excellent repeatability and intermediate precision. In addition, UNIFI software used in this application allows automated data acquisition and processing, which makes this method suitable for high-throughput process monitoring and product characterization. Finally, subunit mass analysis revealed the different patterns of Fc methionine oxidation induced by chemical and photo stress, which makes it attractive for investigating the root cause of oxidation.

Automated sample preparation using membrane microtiter extraction for bioanalytical mass spectrometry.

PubMed

Janiszewski, J; Schneider, P; Hoffmaster, K; Swyden, M; Wells, D; Fouda, H

1997-01-01

The development and application of membrane solid phase extraction (SPE) in 96-well microtiter plate format is described for the automated analysis of drugs in biological fluids. The small bed volume of the membrane allows elution of the analyte in a very small solvent volume, permitting direct HPLC injection and negating the need for the time consuming solvent evaporation step. A programmable liquid handling station (Quadra 96) was modified to automate all SPE steps. To avoid drying of the SPE bed and to enhance the analytical precision a novel protocol for performing the condition, load and wash steps in rapid succession was utilized. A block of 96 samples can now be extracted in 10 min., about 30 times faster than manual solvent extraction or single cartridge SPE methods. This processing speed complements the high-throughput speed of contemporary high performance liquid chromatography mass spectrometry (HPLC/MS) analysis. The quantitative analysis of a test analyte (Ziprasidone) in plasma demonstrates the utility and throughput of membrane SPE in combination with HPLC/MS. The results obtained with the current automated procedure compare favorably with those obtained using solvent and traditional solid phase extraction methods. The method has been used for the analysis of numerous drug prototypes in biological fluids to support drug discovery efforts.

Continuous flow real-time PCR device using multi-channel fluorescence excitation and detection.

PubMed

Hatch, Andrew C; Ray, Tathagata; Lintecum, Kelly; Youngbull, Cody

2014-02-07

High throughput automation is greatly enhanced using techniques that employ conveyor belt strategies with un-interrupted streams of flow. We have developed a 'conveyor belt' analog for high throughput real-time quantitative Polymerase Chain Reaction (qPCR) using droplet emulsion technology. We developed a low power, portable device that employs LED and fiber optic fluorescence excitation in conjunction with a continuous flow thermal cycler to achieve multi-channel fluorescence detection for real-time fluorescence measurements. Continuously streaming fluid plugs or droplets pass through tubing wrapped around a two-temperature zone thermal block with each wrap of tubing fluorescently coupled to a 64-channel multi-anode PMT. This work demonstrates real-time qPCR of 0.1-10 μL droplets or fluid plugs over a range of 7 orders of magnitude concentration from 1 × 10(1) to 1 × 10(7). The real-time qPCR analysis allows dynamic range quantification as high as 1 × 10(7) copies per 10 μL reaction, with PCR efficiencies within the range of 90-110% based on serial dilution assays and a limit of detection of 10 copies per rxn. The combined functionality of continuous flow, low power thermal cycling, high throughput sample processing, and real-time qPCR improves the rates at which biological or environmental samples can be continuously sampled and analyzed.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

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

2017-05-15

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

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

PubMed Central

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

2013-01-01

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

Quantifying Golgi structure using EM: combining volume-SEM and stereology for higher throughput.

PubMed

Ferguson, Sophie; Steyer, Anna M; Mayhew, Terry M; Schwab, Yannick; Lucocq, John Milton

2017-06-01

Investigating organelles such as the Golgi complex depends increasingly on high-throughput quantitative morphological analyses from multiple experimental or genetic conditions. Light microscopy (LM) has been an effective tool for screening but fails to reveal fine details of Golgi structures such as vesicles, tubules and cisternae. Electron microscopy (EM) has sufficient resolution but traditional transmission EM (TEM) methods are slow and inefficient. Newer volume scanning EM (volume-SEM) methods now have the potential to speed up 3D analysis by automated sectioning and imaging. However, they produce large arrays of sections and/or images, which require labour-intensive 3D reconstruction for quantitation on limited cell numbers. Here, we show that the information storage, digital waste and workload involved in using volume-SEM can be reduced substantially using sampling-based stereology. Using the Golgi as an example, we describe how Golgi populations can be sensed quantitatively using single random slices and how accurate quantitative structural data on Golgi organelles of individual cells can be obtained using only 5-10 sections/images taken from a volume-SEM series (thereby sensing population parameters and cell-cell variability). The approach will be useful in techniques such as correlative LM and EM (CLEM) where small samples of cells are treated and where there may be variable responses. For Golgi study, we outline a series of stereological estimators that are suited to these analyses and suggest workflows, which have the potential to enhance the speed and relevance of data acquisition in volume-SEM.

Temporal Data Set Reduction Based on D-Optimality for Quantitative FLIM-FRET Imaging.

PubMed

Omer, Travis; Intes, Xavier; Hahn, Juergen

2015-01-01

Fluorescence lifetime imaging (FLIM) when paired with Förster resonance energy transfer (FLIM-FRET) enables the monitoring of nanoscale interactions in living biological samples. FLIM-FRET model-based estimation methods allow the quantitative retrieval of parameters such as the quenched (interacting) and unquenched (non-interacting) fractional populations of the donor fluorophore and/or the distance of the interactions. The quantitative accuracy of such model-based approaches is dependent on multiple factors such as signal-to-noise ratio and number of temporal points acquired when sampling the fluorescence decays. For high-throughput or in vivo applications of FLIM-FRET, it is desirable to acquire a limited number of temporal points for fast acquisition times. Yet, it is critical to acquire temporal data sets with sufficient information content to allow for accurate FLIM-FRET parameter estimation. Herein, an optimal experimental design approach based upon sensitivity analysis is presented in order to identify the time points that provide the best quantitative estimates of the parameters for a determined number of temporal sampling points. More specifically, the D-optimality criterion is employed to identify, within a sparse temporal data set, the set of time points leading to optimal estimations of the quenched fractional population of the donor fluorophore. Overall, a reduced set of 10 time points (compared to a typical complete set of 90 time points) was identified to have minimal impact on parameter estimation accuracy (≈5%), with in silico and in vivo experiment validations. This reduction of the number of needed time points by almost an order of magnitude allows the use of FLIM-FRET for certain high-throughput applications which would be infeasible if the entire number of time sampling points were used.

A High Throughput Method for Measuring Polycyclic Aromatic Hydrocarbons in Seafood Using QuEChERS Extraction and SBSE.

PubMed

Pfannkoch, Edward A; Stuff, John R; Whitecavage, Jacqueline A; Blevins, John M; Seely, Kathryn A; Moran, Jeffery H

2015-01-01

National Oceanic and Atmospheric Administration (NOAA) Method NMFS-NWFSC-59 2004 is currently used to quantitatively analyze seafood for polycyclic aromatic hydrocarbon (PAH) contamination, especially following events such as the Deepwater Horizon oil rig explosion that released millions of barrels of crude oil into the Gulf of Mexico. This method has limited throughput capacity; hence, alternative methods are necessary to meet analytical demands after such events. Stir bar sorptive extraction (SBSE) is an effective technique to extract trace PAHs in water and the quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction strategy effectively extracts PAHs from complex food matrices. This study uses SBSE to concentrate PAHs and eliminate matrix interference from QuEChERS extracts of seafood, specifically oysters, fish, and shrimp. This method provides acceptable recovery (65-138%) linear calibrations and is sensitive (LOD = 0.02 ppb, LOQ = 0.06 ppb) while providing higher throughput and maintaining equivalency between NOAA 2004 as determined by analysis of NIST SRM 1974b mussel tissue.

Quantitative secondary electron imaging for work function extraction at atomic level and layer identification of graphene

PubMed Central

Zhou, Yangbo; Fox, Daniel S; Maguire, Pierce; O’Connell, Robert; Masters, Robert; Rodenburg, Cornelia; Wu, Hanchun; Dapor, Maurizio; Chen, Ying; Zhang, Hongzhou

2016-01-01

Two-dimensional (2D) materials usually have a layer-dependent work function, which require fast and accurate detection for the evaluation of their device performance. A detection technique with high throughput and high spatial resolution has not yet been explored. Using a scanning electron microscope, we have developed and implemented a quantitative analytical technique which allows effective extraction of the work function of graphene. This technique uses the secondary electron contrast and has nanometre-resolved layer information. The measurement of few-layer graphene flakes shows the variation of work function between graphene layers with a precision of less than 10 meV. It is expected that this technique will prove extremely useful for researchers in a broad range of fields due to its revolutionary throughput and accuracy. PMID:26878907

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.

PubMed

Klein, Allon M; Mazutis, Linas; Akartuna, Ilke; Tallapragada, Naren; Veres, Adrian; Li, Victor; Peshkin, Leonid; Weitz, David A; Kirschner, Marc W

2015-05-21

It has long been the dream of biologists to map gene expression at the single-cell level. With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways. Recently, RNA sequencing has achieved single-cell resolution. What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing. We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing. The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays. We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal. The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships. VIDEO ABSTRACT. Copyright © 2015 Elsevier Inc. All rights reserved.

Customized Molecular Phenotyping by Quantitative Gene Expression and Pattern Recognition Analysis

PubMed Central

Akilesh, Shreeram; Shaffer, Daniel J.; Roopenian, Derry

2003-01-01

Description of the molecular phenotypes of pathobiological processes in vivo is a pressing need in genomic biology. We have implemented a high-throughput real-time PCR strategy to establish quantitative expression profiles of a customized set of target genes. It enables rapid, reproducible data acquisition from limited quantities of RNA, permitting serial sampling of mouse blood during disease progression. We developed an easy to use statistical algorithm—Global Pattern Recognition—to readily identify genes whose expression has changed significantly from healthy baseline profiles. This approach provides unique molecular signatures for rheumatoid arthritis, systemic lupus erythematosus, and graft versus host disease, and can also be applied to defining the molecular phenotype of a variety of other normal and pathological processes. PMID:12840047

An open-source computational and data resource to analyze digital maps of immunopeptidomes

PubMed Central

Caron, Etienne; Espona, Lucia; Kowalewski, Daniel J; Schuster, Heiko; Ternette, Nicola; Alpízar, Adán; Schittenhelm, Ralf B; Ramarathinam, Sri H; Lindestam Arlehamn, Cecilia S; Chiek Koh, Ching; Gillet, Ludovic C; Rabsteyn, Armin; Navarro, Pedro; Kim, Sangtae; Lam, Henry; Sturm, Theo; Marcilla, Miguel; Sette, Alessandro; Campbell, David S; Deutsch, Eric W; Moritz, Robert L; Purcell, Anthony W; Rammensee, Hans-Georg; Stevanovic, Stefan; Aebersold, Ruedi

2015-01-01

We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the design of efficient immunotherapies. DOI: http://dx.doi.org/10.7554/eLife.07661.001 PMID:26154972

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

PubMed

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

2012-12-01

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

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

PubMed

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

2013-04-09

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

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

PubMed

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

2017-05-01

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

Use of Ambient Ionization High-Resolution Mass Spectrometry for the Kinetic Analysis of Organic Surface Reactions.

PubMed

Sen, Rickdeb; Escorihuela, Jorge; Smulders, Maarten M J; Zuilhof, Han

2016-04-12

In contrast to homogeneous systems, studying the kinetics of organic reactions on solid surfaces remains a difficult task due to the limited availability of appropriate analysis techniques that are general, high-throughput, and capable of offering quantitative, structural surface information. Here, we demonstrate how direct analysis in real time mass spectrometry (DART-MS) complies with above considerations and can be used for determining interfacial kinetic parameters. The presented approach is based on the use of a MS tag that--in principle--allows application to other reactions. To show the potential of DART-MS, we selected the widely applied strain-promoted alkyne-azide cycloaddition (SPAAC) as a model reaction to elucidate the effects of the nanoenvironment on the interfacial reaction rate.

Direct Analysis in Real Time-Mass Spectrometry for the Rapid Detection of Metabolites of Aconite Alkaloids in Intestinal Bacteria

NASA Astrophysics Data System (ADS)

Li, Xue; Hou, Guangyue; Xing, Junpeng; Song, Fengrui; Liu, Zhiqiang; Liu, Shuying

2014-12-01

In the present work, direct analysis of real time ionization combined with multi-stage tandem mass spectrometry (DART-MSn) was used to investigate the metabolic profile of aconite alkaloids in rat intestinal bacteria. A total of 36 metabolites from three aconite alkaloids were identified by using DART-MSn, and the feasibility of quantitative analysis of these analytes was examined. Key parameters of the DART ion source, such as helium gas temperature and pressure, the source-to-MS distance, and the speed of the autosampler, were optimized to achieve high sensitivity, enhance reproducibility, and reduce the occurrence of fragmentation. The instrument analysis time for one sample can be less than 10 s for this method. Compared with ESI-MS and UPLC-MS, the DART-MS is more efficient for directly detecting metabolic samples, and has the advantage of being a simple, high-speed, high-throughput method.

Direct analysis in real time-mass spectrometry for the rapid detection of metabolites of aconite alkaloids in intestinal bacteria.

PubMed

Li, Xue; Hou, Guangyue; Xing, Junpeng; Song, Fengrui; Liu, Zhiqiang; Liu, Shuying

2014-12-01

In the present work, direct analysis of real time ionization combined with multi-stage tandem mass spectrometry (DART-MS(n)) was used to investigate the metabolic profile of aconite alkaloids in rat intestinal bacteria. A total of 36 metabolites from three aconite alkaloids were identified by using DART-MS(n), and the feasibility of quantitative analysis of these analytes was examined. Key parameters of the DART ion source, such as helium gas temperature and pressure, the source-to-MS distance, and the speed of the autosampler, were optimized to achieve high sensitivity, enhance reproducibility, and reduce the occurrence of fragmentation. The instrument analysis time for one sample can be less than 10 s for this method. Compared with ESI-MS and UPLC-MS, the DART-MS is more efficient for directly detecting metabolic samples, and has the advantage of being a simple, high-speed, high-throughput method.

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

PubMed Central

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

2015-01-01

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

Sugar and acid content of Citrus prediction modeling using FT-IR fingerprinting in combination with multivariate statistical analysis.

PubMed

Song, Seung Yeob; Lee, Young Koung; Kim, In-Jung

2016-01-01

A high-throughput screening system for Citrus lines were established with higher sugar and acid contents using Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. FT-IR spectra confirmed typical spectral differences between the frequency regions of 950-1100 cm(-1), 1300-1500 cm(-1), and 1500-1700 cm(-1). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate five Citrus lines into three separate clusters corresponding to their taxonomic relationships. The quantitative predictive modeling of sugar and acid contents from Citrus fruits was established using partial least square regression algorithms from FT-IR spectra. The regression coefficients (R(2)) between predicted values and estimated sugar and acid content values were 0.99. These results demonstrate that by using FT-IR spectra and applying quantitative prediction modeling to Citrus sugar and acid contents, excellent Citrus lines can be early detected with greater accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fragman: an R package for fragment analysis.

PubMed

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

2016-04-21

Determination of microsatellite lengths or other DNA fragment types is an important initial component of many genetic studies such as mutation detection, linkage and quantitative trait loci (QTL) mapping, genetic diversity, pedigree analysis, and detection of heterozygosity. A handful of commercial and freely available software programs exist for fragment analysis; however, most of them are platform dependent and lack high-throughput applicability. We present the R package Fragman to serve as a freely available and platform independent resource for automatic scoring of DNA fragment lengths diversity panels and biparental populations. The program analyzes DNA fragment lengths generated in Applied Biosystems® (ABI) either manually or automatically by providing panels or bins. The package contains additional tools for converting the allele calls to GenAlEx, JoinMap® and OneMap software formats mainly used for genetic diversity and generating linkage maps in plant and animal populations. Easy plotting functions and multiplexing friendly capabilities are some of the strengths of this R package. Fragment analysis using a unique set of cranberry (Vaccinium macrocarpon) genotypes based on microsatellite markers is used to highlight the capabilities of Fragman. Fragman is a valuable new tool for genetic analysis. The package produces equivalent results to other popular software for fragment analysis while possessing unique advantages and the possibility of automation for high-throughput experiments by exploiting the power of R.

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

PubMed

Subhash, Santhilal; Kanduri, Chandrasekhar

2016-09-13

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

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

PubMed

Putt, Karson S; Pugh, Randall B

2013-01-01

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

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

PubMed Central

Putt, Karson S.; Pugh, Randall B.

2013-01-01

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

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

EPA Pesticide Factsheets

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

Evaluation of a solid-phase extraction method for benzoylecgonine urine analysis in a high-throughput forensic urine drug-testing laboratory.

PubMed

Stout, Peter R; Gehlhausen, Jay M; Horn, Carl K; Klette, Kevin L

2002-10-01

A novel extraction and derivatization procedure for the cocaine metabolite benzoylecgonine (BZE) was developed and evaluated for use in a high-volume forensic urine analysis laboratory. Extractions utilized a Speedisk 48 positive pressure extraction manifold and polymer-based cation-exchange extraction columns. Samples were derivatized by the addition of pentafluoropropionic anhydride and pentafluoropropanol. All analyses were performed in selected ion monitoring mode; ions included m/z 421, 300, 272, 429, and 303 with m/z 421 to 429 ratio used for quantitation. The average extraction efficiency was 80%. Seventy-five common over-the-counter products, including prescription drugs, drug metabolites, and other drugs of abuse, demonstrated no significant interference with respect to chromatography or quantitation. The limit of detection and limit of quantitation were calculated at 12.5 ng/mL, and the assay was linear from 12.5 to 20,000 ng/mL with an r2 of 0.99932. A series of 20 precision samples (100 ng/mL) produced an average response of 97.8 ng/mL and a percent coefficient of variation of 4.1%. A set of 79 archived human urine samples that had previously been found to contain BZE were analyzed by 3 separate laboratories. The results did not differ significantly from prior quantitation or between laboratories. The Speedisk has proven viable for a high-volume production facility reducing overall cost of analysis by decreasing analysis time and minimizing waste production while meeting strict forensic requirements.

Experimental design and quantitative analysis of microbial community multiomics.

PubMed

Mallick, Himel; Ma, Siyuan; Franzosa, Eric A; Vatanen, Tommi; Morgan, Xochitl C; Huttenhower, Curtis

2017-11-30

Studies of the microbiome have become increasingly sophisticated, and multiple sequence-based, molecular methods as well as culture-based methods exist for population-scale microbiome profiles. To link the resulting host and microbial data types to human health, several experimental design considerations, data analysis challenges, and statistical epidemiological approaches must be addressed. Here, we survey current best practices for experimental design in microbiome molecular epidemiology, including technologies for generating, analyzing, and integrating microbiome multiomics data. We highlight studies that have identified molecular bioactives that influence human health, and we suggest steps for scaling translational microbiome research to high-throughput target discovery across large populations.

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

PubMed

Ollion, Jean; Cochennec, Julien; Loll, François; Escudé, Christophe; Boudier, Thomas

2013-07-15

The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. thomas.boudier@snv.jussieu.fr Supplementary data are available at Bioinformatics online.

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

PubMed

Ulitsky, Igor; Shamir, Ron

2007-01-26

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

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

PubMed Central

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

2016-01-01

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

Quantitative Image Restoration in Bright Field Optical Microscopy.

PubMed

Gutiérrez-Medina, Braulio; Sánchez Miranda, Manuel de Jesús

2017-11-07

Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2017-03-01

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

Accelerating evaluation of converged lattice thermal conductivity

NASA Astrophysics Data System (ADS)

Qin, Guangzhao; Hu, Ming

2018-01-01

High-throughput computational materials design is an emerging area in materials science, which is based on the fast evaluation of physical-related properties. The lattice thermal conductivity (κ) is a key property of materials for enormous implications. However, the high-throughput evaluation of κ remains a challenge due to the large resources costs and time-consuming procedures. In this paper, we propose a concise strategy to efficiently accelerate the evaluation process of obtaining accurate and converged κ. The strategy is in the framework of phonon Boltzmann transport equation (BTE) coupled with first-principles calculations. Based on the analysis of harmonic interatomic force constants (IFCs), the large enough cutoff radius (rcutoff), a critical parameter involved in calculating the anharmonic IFCs, can be directly determined to get satisfactory results. Moreover, we find a simple way to largely ( 10 times) accelerate the computations by fast reconstructing the anharmonic IFCs in the convergence test of κ with respect to the rcutof, which finally confirms the chosen rcutoff is appropriate. Two-dimensional graphene and phosphorene along with bulk SnSe are presented to validate our approach, and the long-debate divergence problem of thermal conductivity in low-dimensional systems is studied. The quantitative strategy proposed herein can be a good candidate for fast evaluating the reliable κ and thus provides useful tool for high-throughput materials screening and design with targeted thermal transport properties.

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

PubMed Central

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

2011-01-01

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

Clinical value of protein expression of kallikrein-related peptidase 7 (KLK7) in ovarian cancer.

PubMed

Dorn, Julia; Gkazepis, Apostolos; Kotzsch, Matthias; Kremer, Marcus; Propping, Corinna; Mayer, Katharina; Mengele, Karin; Diamandis, Eleftherios P; Kiechle, Marion; Magdolen, Viktor; Schmitt, Manfred

2014-01-01

Expression of the kallikrein-related peptidase 7 (KLK7) is dysregulated in ovarian cancer. We assessed KLK7 expression by ELISA and quantitative immunohistochemistry and analyzed its association with clinicopathological parameters and patients' outcome. KLK7 antigen concentrations were determined in tumor tissue extracts of 98 ovarian cancer patients by ELISA. For analysis of KLK7 immunoexpression in ovarian cancer tissue microarrays, a manual quantitative scoring system as well as a software tool for quantitative high-throughput automated image analysis was used. In immunohistochemical analyses, expression levels of KLK7 were not associated with patients' outcome. However, in multivariate analyses, KLK7 antigen levels in tumor tissue extracts were significantly associated with both overall and progression-free survival: ovarian cancer patients with high KLK7 levels had a significantly, 2-fold lower risk of death [hazard ratio (HR)=0.51, 95% confidence interval (CI)=0.29-0.90, p=0.019] or relapse [HR=0.47, 95% CI=0.25-0.91, p=0.024), as compared with patients who displayed low KLK7 levels. Our results indicate that - in contrast to earlier findings - high KLK7 antigen levels in tumor tissue extracts may be associated with a better prognosis of ovarian cancer patients.

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

PubMed

Kavlock, Robert; Dix, David

2010-02-01

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

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

PubMed

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

2017-06-20

The selective perturbation of complex microbial ecosystems to predictably influence outcomes in engineered and industrial environments remains a grand challenge for geomicrobiology. In some industrial ecosystems, such as oil reservoirs, sulfate reducing microorganisms (SRM) produce hydrogen sulfide which is toxic, explosive, and corrosive. Despite the economic cost of sulfidogenesis, there has been minimal exploration of the chemical space of possible inhibitory compounds, and very little work has quantitatively assessed the selectivity of putative souring treatments. We have developed a high-throughput screening strategy to identify potent and selective inhibitors of SRM, quantitatively ranked the selectivity and potency of hundreds of compounds and identified previously unrecognized SRM selective inhibitors and synergistic interactions between inhibitors. Zinc pyrithione is the most potent inhibitor of sulfidogenesis that we identified, and is several orders of magnitude more potent than commonly used industrial biocides. Both zinc and copper pyrithione are also moderately selective against SRM. The high-throughput (HT) approach we present can be readily adapted to target SRM in diverse environments and similar strategies could be used to quantify the potency and selectivity of inhibitors of a variety of microbial metabolisms. Our findings and approach are relevant to efforts to engineer environmental ecosystems and also to understand the role of natural gradients in shaping microbial niche space.

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

PubMed Central

Bokulich, Nicholas A.

2013-01-01

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

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

PubMed

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

2018-02-21

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

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

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

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

2016-09-22

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

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

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

Hakala, Jacqueline Alexandra

2016-11-22

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

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

PubMed Central

Wang, Li; Carnegie, Graeme K.

2013-01-01

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

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

PubMed

Wang, Li; Carnegie, Graeme K

2013-08-15

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

Thin-Film Material Science and Processing | Materials Science | NREL

Science.gov Websites

, a prime example of this research is thin-film photovoltaics (PV). Thin films are important because have developed a quantitative high-throughput technique that can measure many barriers in parallel with

Quantitative High-throughput Luciferase Screening in Identifying CAR Modulators

PubMed Central

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

2017-01-01

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

A Review of Imaging Techniques for Plant Phenotyping

PubMed Central

Li, Lei; Zhang, Qin; Huang, Danfeng

2014-01-01

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

1-Million droplet array with wide-field fluorescence imaging for digital PCR.

PubMed

Hatch, Andrew C; Fisher, Jeffrey S; Tovar, Armando R; Hsieh, Albert T; Lin, Robert; Pentoney, Stephen L; Yang, David L; Lee, Abraham P

2011-11-21

Digital droplet reactors are useful as chemical and biological containers to discretize reagents into picolitre or nanolitre volumes for analysis of single cells, organisms, or molecules. However, most DNA based assays require processing of samples on the order of tens of microlitres and contain as few as one to as many as millions of fragments to be detected. Presented in this work is a droplet microfluidic platform and fluorescence imaging setup designed to better meet the needs of the high-throughput and high-dynamic-range by integrating multiple high-throughput droplet processing schemes on the chip. The design is capable of generating over 1-million, monodisperse, 50 picolitre droplets in 2-7 minutes that then self-assemble into high density 3-dimensional sphere packing configurations in a large viewing chamber for visualization and analysis. This device then undergoes on-chip polymerase chain reaction (PCR) amplification and fluorescence detection to digitally quantify the sample's nucleic acid contents. Wide-field fluorescence images are captured using a low cost 21-megapixel digital camera and macro-lens with an 8-12 cm(2) field-of-view at 1× to 0.85× magnification, respectively. We demonstrate both end-point and real-time imaging ability to perform on-chip quantitative digital PCR analysis of the entire droplet array. Compared to previous work, this highly integrated design yields a 100-fold increase in the number of on-chip digitized reactors with simultaneous fluorescence imaging for digital PCR based assays.

Stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization.

PubMed

Veeraraghavan, Rengasayee; Gourdie, Robert G

2016-11-07

The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200-300 nm of each other in the xy-plane and within 500-700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy-based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins. © 2016 Veeraraghavan and Gourdie. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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

PubMed Central

Schaufele, Fred

2013-01-01

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

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

PubMed Central

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Mirsky, Vladimir M.

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

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

PubMed

Keegan, Alissa; Plath, Kathrin; Damoiseaux, Robert

2018-01-01

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

BEAMS Lab: Novel approaches to finding a balance between throughput and sensitivity

NASA Astrophysics Data System (ADS)

Liberman, Rosa G.; Skipper, Paul L.; Prakash, Chandra; Shaffer, Christopher L.; Flarakos, Jimmy; Tannenbaum, Steven R.

2007-06-01

Development of 14C AMS has long pursued the twin goals of maximizing both sensitivity and precision in the interest, among others, of optimizing radiocarbon dating. Application of AMS to biomedical research is less constrained with respect to sensitivity requirements, but more demanding of high throughput. This work presents some technical and conceptual developments in sample processing and analytical instrumentation designed to streamline the process of extracting quantitative data from the various types of samples encountered in analytical biochemistry.

Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome

PubMed Central

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

2011-01-01

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

Rapid Analysis of Bisphenol A and Its Analogues in Food Packaging Products by Paper Spray Ionization Mass Spectrometry.

PubMed

Chen, Shuo; Chang, Quanying; Yin, Kai; He, Qunying; Deng, Yongxiu; Chen, Bo; Liu, Chengbin; Wang, Ying; Wang, Liping

2017-06-14

In this study, a paper spray ionization mass spectrometric (PS-MS) method was developed for the rapid in situ screening and simultaneous quantitative analysis of bisphenol A and its analogues, i.e., bisphenol S, bisphenol F, and bisphenol AF, in food packaging products. At the optimal PS-MS conditions, the calibration curves of bisphenols in the range of 1-100 μg/mL were linear. The correlation coefficients were higher than 0.998, and the LODs of the target compounds were 0.1-0.3 μg/mL. After a simple treatment by dichloromethane on the surface, the samples were analyzed by PS-MS in situ for rapid screening without a traditional sample pretreatment procedure, such as powdering, extraction, and enrichment steps. The analytical time of the PS-MS method was less than 1 min. In comparison with conventional HPLC-MS/MS, it was demonstrated that PS-MS was a more effective high-throughput screening and quantitative analysis method.

Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline.

PubMed

Loh, K B; Ramli, N; Tan, L K; Roziah, M; Rahmat, K; Ariffin, H

2012-07-01

The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.

Time-Domain Microfluidic Fluorescence Lifetime Flow Cytometry for High-Throughput Förster Resonance Energy Transfer Screening

PubMed Central

Nedbal, Jakub; Visitkul, Viput; Ortiz-Zapater, Elena; Weitsman, Gregory; Chana, Prabhjoat; Matthews, Daniel R; Ng, Tony; Ameer-Beg, Simon M

2015-01-01

Sensing ion or ligand concentrations, physico-chemical conditions, and molecular dimerization or conformation change is possible by assays involving fluorescent lifetime imaging. The inherent low throughput of imaging impedes rigorous statistical data analysis on large cell numbers. We address this limitation by developing a fluorescence lifetime-measuring flow cytometer for fast fluorescence lifetime quantification in living or fixed cell populations. The instrument combines a time-correlated single photon counting epifluorescent microscope with microfluidics cell-handling system. The associated computer software performs burst integrated fluorescence lifetime analysis to assign fluorescence lifetime, intensity, and burst duration to each passing cell. The maximum safe throughput of the instrument reaches 3,000 particles per minute. Living cells expressing spectroscopic rulers of varying peptide lengths were distinguishable by Förster resonant energy transfer measured by donor fluorescence lifetime. An epidermal growth factor (EGF)-stimulation assay demonstrated the technique's capacity to selectively quantify EGF receptor phosphorylation in cells, which was impossible by measuring sensitized emission on a standard flow cytometer. Dual-color fluorescence lifetime detection and cell-specific chemical environment sensing were exemplified using di-4-ANEPPDHQ, a lipophilic environmentally sensitive dye that exhibits changes in its fluorescence lifetime as a function of membrane lipid order. To our knowledge, this instrument opens new applications in flow cytometry which were unavailable due to technological limitations of previously reported fluorescent lifetime flow cytometers. The presented technique is sensitive to lifetimes of most popular fluorophores in the 0.5–5 ns range including fluorescent proteins and is capable of detecting multi-exponential fluorescence lifetime decays. This instrument vastly enhances the throughput of experiments involving fluorescence lifetime measurements, thereby providing statistically significant quantitative data for analysis of large cell populations. © 2014 International Society for Advancement of Cytometry PMID:25523156

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

PubMed

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

2018-05-21

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

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

PubMed

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

2017-03-01

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

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

PubMed Central

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

2017-01-01

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

Wake Vortex Systems Cost/Benefits Analysis

NASA Technical Reports Server (NTRS)

Crisp, Vicki K.

1997-01-01

The goals of cost/benefit assessments are to provide quantitative and qualitative data to aid in the decision-making process. Benefits derived from increased throughput (or decreased delays) used to balance life-cycle costs. Packaging technologies together may provide greater gains (demonstrate higher return on investment).

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

EPA Science Inventory

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

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

PubMed

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

2002-07-31

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

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

PubMed

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

2014-11-21

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

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays

USGS Publications Warehouse

Hahn, Cassidy M.; Iwanowicz, Luke R.; Cornman, Robert S.; Mazik, Patricia M.; Blazer, Vicki S.

2016-01-01

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest.

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

DOE PAGES

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

2015-01-07

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

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

DOE PAGES

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

2016-09-23

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

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth.

PubMed

Sankar, Martial; Nieminen, Kaisa; Ragni, Laura; Xenarios, Ioannis; Hardtke, Christian S

2014-02-11

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth

PubMed Central

Sankar, Martial; Nieminen, Kaisa; Ragni, Laura; Xenarios, Ioannis; Hardtke, Christian S

2014-01-01

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001 PMID:24520159

Development of a 63K SNP array for Gossypium and high-density mapping of intra- and inter-specific populations of cotton (G. hirsutum L.)

USDA-ARS?s Scientific Manuscript database

High-throughput genotyping arrays provide a standardized resource for crop research communities that are useful for a breadth of applications including high-density genetic mapping, genome-wide association studies (GWAS), genomic selection (GS), candidate marker and quantitative trait loci (QTL) ide...

Paper Capillary Enables Effective Sampling for Microfluidic Paper Analytical Devices.

PubMed

Shangguan, Jin-Wen; Liu, Yu; Wang, Sha; Hou, Yun-Xuan; Xu, Bi-Yi; Xu, Jing-Juan; Chen, Hong-Yuan

2018-06-06

Paper capillary is introduced to enable effective sampling on microfluidic paper analytical devices. By coupling mac-roscale capillary force of paper capillary and microscale capillary forces of native paper, fluid transport can be flexibly tailored with proper design. Subsequently, a hybrid-fluid-mode paper capillary device was proposed, which enables fast and reliable sampling in an arrayed form, with less surface adsorption and bias for different components. The resulting device thus well supports high throughput, quantitative, and repeatable assays all by hands operation. With all these merits, multiplex analysis of ions, proteins, and microbe have all been realized on this platform, which has paved the way to level-up analysis on μPADs.

A simple and widely applicable hit validation strategy for protein-protein interaction inhibitors based on a quantitative ligand displacement assay.

PubMed

Sameshima, Tomoya; Miyahisa, Ikuo; Homma, Misaki; Aikawa, Katsuji; Hixon, Mark S; Matsui, Junji

2014-12-15

Identification of inhibitors for protein-protein interactions (PPIs) from high-throughput screening (HTS) is challenging due to the weak affinity of primary hits. We present a hit validation strategy of PPI inhibitors using quantitative ligand displacement assay. From an HTS for Bcl-xL/Mcl-1 inhibitors, we obtained a hit candidate, I1, which potentially forms a reactive Michael acceptor, I2, inhibiting Bcl-xL/Mcl-1 through covalent modification. We confirmed rapid reversible and competitive binding of I1 with a probe peptide, suggesting non-covalent binding. The advantages of our approach over biophysical assays include; simplicity, higher throughput, low protein consumption and universal application to PPIs including insoluble membrane proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ex Priori: Exposure-based Prioritization across Chemical Space

EPA Science Inventory

EPA's Exposure Prioritization (Ex Priori) is a simplified, quantitative visual dashboard that makes use of data from various inputs to provide rank-ordered internalized dose metric. This complements other high throughput screening by viewing exposures within all chemical space si...

Quantitative High-Throughput Screening and Orthogonal Assays to Identify Modulators of the Vitamin D Receptor (SETAC)

EPA Science Inventory

The Vitamin D nuclear receptor (VDR) is a selective, ligand-inducible transcription factor involved in numerous biological processes such as cell proliferation, differentiation, detoxification, calcium homeostasis, neurodevelopment, immune system regulation, cardiovascular functi...

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

PubMed

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

2017-01-01

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

Digital histologic analysis reveals morphometric patterns of age-related involution in breast epithelium and stroma.

PubMed

Sandhu, Rupninder; Chollet-Hinton, Lynn; Kirk, Erin L; Midkiff, Bentley; Troester, Melissa A

2016-02-01

Complete age-related regression of mammary epithelium, often termed postmenopausal involution, is associated with decreased breast cancer risk. However, most studies have qualitatively assessed involution. We quantitatively analyzed epithelium, stroma, and adipose tissue from histologically normal breast tissue of 454 patients in the Normal Breast Study. High-resolution digital images of normal breast hematoxylin and eosin-stained slides were partitioned into epithelium, adipose tissue, and nonfatty stroma. Percentage area and nuclei per unit area (nuclear density) were calculated for each component. Quantitative data were evaluated in association with age using linear regression and cubic spline models. Stromal area decreased (P = 0.0002), and adipose tissue area increased (P < 0.0001), with an approximate 0.7% change in area for each component, until age 55 years when these area measures reached a steady state. Although epithelial area did not show linear changes with age, epithelial nuclear density decreased linearly beginning in the third decade of life. No significant age-related trends were observed for stromal or adipose nuclear density. Digital image analysis offers a high-throughput method for quantitatively measuring tissue morphometry and for objectively assessing age-related changes in adipose tissue, stroma, and epithelium. Epithelial nuclear density is a quantitative measure of age-related breast involution that begins to decline in the early premenopausal period. Copyright © 2015 Elsevier Inc. All rights reserved.

Computer-based fluorescence quantification: a novel approach to study nucleolar biology

PubMed Central

2011-01-01

Background Nucleoli are composed of possibly several thousand different proteins and represent the most conspicuous compartments in the nucleus; they play a crucial role in the proper execution of many cellular processes. As such, nucleoli carry out ribosome biogenesis and sequester or associate with key molecules that regulate cell cycle progression, tumorigenesis, apoptosis and the stress response. Nucleoli are dynamic compartments that are characterized by a constant flux of macromolecules. Given the complex and dynamic composition of the nucleolar proteome, it is challenging to link modifications in nucleolar composition to downstream effects. Results In this contribution, we present quantitative immunofluorescence methods that rely on computer-based image analysis. We demonstrate the effectiveness of these techniques by monitoring the dynamic association of proteins and RNA with nucleoli under different physiological conditions. Thus, the protocols described by us were employed to study stress-dependent changes in the nucleolar concentration of endogenous and GFP-tagged proteins. Furthermore, our methods were applied to measure de novo RNA synthesis that is associated with nucleoli. We show that the techniques described here can be easily combined with automated high throughput screening (HTS) platforms, making it possible to obtain large data sets and analyze many of the biological processes that are located in nucleoli. Conclusions Our protocols set the stage to analyze in a quantitative fashion the kinetics of shuttling nucleolar proteins, both at the single cell level as well as for a large number of cells. Moreover, the procedures described here are compatible with high throughput image acquisition and analysis using HTS automated platforms, thereby providing the basis to quantify nucleolar components and activities for numerous samples and experimental conditions. Together with the growing amount of information obtained for the nucleolar proteome, improvements in quantitative microscopy as they are described here can be expected to produce new insights into the complex biological functions that are orchestrated by the nucleolus. PMID:21639891

High-throughput spectral and lifetime-based FRET screening in living cells to identify small-molecule effectors of SERCA

PubMed Central

Schaaf, Tory M.; Peterson, Kurt C.; Grant, Benjamin D.; Bawaskar, Prachi; Yuen, Samantha; Li, Ji; Muretta, Joseph M.; Gillispie, Gregory D.; Thomas, David D.

2017-01-01

A robust high-throughput screening (HTS) strategy has been developed to discover small-molecule effectors targeting the sarco/endoplasmic reticulum calcium ATPase (SERCA), based on a fluorescence microplate reader that records both the nanosecond decay waveform (lifetime mode) and the complete emission spectrum (spectral mode), with high precision and speed. This spectral unmixing plate reader (SUPR) was used to screen libraries of small molecules with a fluorescence resonance energy transfer (FRET) biosensor expressed in living cells. Ligand binding was detected by FRET associated with structural rearrangements of green (GFP, donor) and red (RFP, acceptor) fluorescent proteins fused to the cardiac-specific SERCA2a isoform. The results demonstrate accurate quantitation of FRET along with high precision of hit identification. Fluorescence lifetime analysis resolved SERCA’s distinct structural states, providing a method to classify small-molecule chemotypes on the basis of their structural effect on the target. The spectral analysis was also applied to flag interference by fluorescent compounds. FRET hits were further evaluated for functional effects on SERCA’s ATPase activity via both a coupled-enzyme assay and a FRET-based calcium sensor. Concentration-response curves indicated excellent correlation between FRET and function. These complementary spectral and lifetime FRET detection methods offer an attractive combination of precision, speed, and resolution for HTS. PMID:27899691

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

DOT National Transportation Integrated Search

2013-10-01

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

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

2014-01-01

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

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

PubMed Central

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

2009-01-01

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

Identifying haplotypes for flowering and QTLs for fruit quality in the RosBREED Michigan and Oregon strawberry (Fragaria ×ananassa) breeding sets using pedigree-based analysis [abstract

USDA-ARS?s Scientific Manuscript database

Strawberry (Fragaria ×ananassa) is consumed for its flavor and health benefits. Over the last two decades, several quantitative trait loci (QTL) analysis studies for consumer traits were conducted using low-density genetic maps. The previous studies utilized low-throughput genotyping methodologies. ...

Quantitative analysis of amygdalin and prunasin in Prunus serotina Ehrh. using (1) H-NMR spectroscopy.

PubMed

Santos Pimenta, Lúcia P; Schilthuizen, Menno; Verpoorte, Robert; Choi, Young Hae

2014-01-01

Prunus serotina is native to North America but has been invasively introduced in Europe since the seventeenth century. This plant contains cyanogenic glycosides that are believed to be related to its success as an invasive plant. For these compounds, chromatographic- or spectrometric-based (targeting on HCN hydrolysis) methods of analysis have been employed so far. However, the conventional methods require tedious preparation steps and a long measuring time. To develop a fast and simple method to quantify the cyanogenic glycosides, amygdalin and prunasin in dried Prunus serotina leaves without any pre-purification steps using (1) H-NMR spectroscopy. Extracts of Prunus serotina leaves using CH3 OH-d4 and KH2 PO4 buffer in D2 O (1:1) were quantitatively analysed for amygdalin and prunasin using (1) H-NMR spectroscopy. Different internal standards were evaluated for accuracy and stability. The purity of quantitated (1) H-NMR signals was evaluated using several two-dimensional NMR experiments. Trimethylsilylpropionic acid sodium salt-d4 proved most suitable as the internal standard for quantitative (1) H-NMR analysis. Two-dimensional J-resolved NMR was shown to be a useful tool to confirm the structures and to check for possible signal overlapping with the target signals for the quantitation. Twenty-two samples of P. serotina were subsequently quantitatively analysed for the cyanogenic glycosides prunasin and amygdalin. The NMR method offers a fast, high-throughput analysis of cyanogenic glycosides in dried leaves permitting simultaneous quantification and identification of prunasin and amygdalin in Prunus serotina. Copyright © 2013 John Wiley & Sons, Ltd.

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

PubMed

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

2016-07-05

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

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

PubMed

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

2017-11-01

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

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

PubMed Central

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

2009-01-01

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

Molecular beacons for DNA binding proteins: an emerging technology for detection of DNA binding proteins and their ligands.

PubMed

Dummitt, Benjamin; Chang, Yie-Hwa

2006-06-01

Quantitation of the level or activity of specific proteins is one of the most commonly performed experiments in biomedical research. Protein detection has historically been difficult to adapt to high throughput platforms because of heavy reliance upon antibodies for protein detection. Molecular beacons for DNA binding proteins is a recently developed technology that attempts to overcome such limitations. Protein detection is accomplished using inexpensive, easy-to-synthesize oligonucleotides, accompanied by a fluorescence readout. Importantly, detection of the protein and reporting of the signal occur simultaneously, allowing for one-step protocols and increased potential for use in high throughput analysis. While the initial iteration of the technology allowed only for the detection of sequence-specific DNA binding proteins, more recent adaptations allow for the possibility of development of beacons for any protein, independent of native DNA binding activity. Here, we discuss the development of the technology, the mechanism of the reaction, and recent improvements and modifications made to improve the assay in terms of sensitivity, potential for multiplexing, and broad applicability.

Recent Advances in Clinical Glycoproteomics of Immunoglobulins (Igs).

PubMed

Plomp, Rosina; Bondt, Albert; de Haan, Noortje; Rombouts, Yoann; Wuhrer, Manfred

2016-07-01

Antibody glycosylation analysis has seen methodological progress resulting in new findings with regard to antibody glycan structure and function in recent years. For example, antigen-specific IgG glycosylation analysis is now applicable for clinical samples because of the increased sensitivity of measurements, and this has led to new insights in the relationship between IgG glycosylation and various diseases. Furthermore, many new methods have been developed for the purification and analysis of IgG Fc glycopeptides, notably multiple reaction monitoring for high-throughput quantitative glycosylation analysis. In addition, new protocols for IgG Fab glycosylation analysis were established revealing autoimmune disease-associated changes. Functional analysis has shown that glycosylation of IgA and IgE is involved in transport across the intestinal epithelium and receptor binding, respectively. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed

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

2014-12-01

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

A novel quantitative high-throughput screen identifies drugs that both activate SUMO conjugation via the inhibition of microRNAs 182 and 183 and facilitate neuroprotection in a model of oxygen and glucose deprivation

PubMed Central

Bernstock, Joshua D; Lee, Yang-ja; Peruzzotti-Jametti, Luca; Southall, Noel; Johnson, Kory R; Maric, Dragan; Volpe, Giulio; Kouznetsova, Jennifer; Zheng, Wei; Pluchino, Stefano

2015-01-01

The conjugation/de-conjugation of Small Ubiquitin-like Modifier (SUMO) has been shown to be associated with a diverse set of physiologic/pathologic conditions. The clinical significance and ostensible therapeutic utility offered via the selective control of the global SUMOylation process has become readily apparent in ischemic pathophysiology. Herein, we describe the development of a novel quantitative high-throughput screening (qHTS) system designed to identify small molecules capable of increasing SUMOylation via the regulation/inhibition of members of the microRNA (miRNA)-182 family. This assay employs a SHSY5Y human neuroblastoma cell line stably transfected with a dual firefly-Renilla luciferase reporter system for identification of specific inhibitors of either miR-182 or miR-183. In this study, we have identified small molecules capable of inducing increased global conjugation of SUMO in both SHSY5Y cells and rat E18-derived primary cortical neurons. The protective effects of a number of the identified compounds were confirmed via an in vitro ischemic model (oxygen/glucose deprivation). Of note, this assay can be easily repurposed to allow high-throughput analyses of the potential drugability of other relevant miRNA(s) in ischemic pathobiology. PMID:26661196

solGS: a web-based tool for genomic selection

USDA-ARS?s Scientific Manuscript database

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

Digital PCR for detection of citrus pathogens

USDA-ARS?s Scientific Manuscript database

Citrus trees are often infected with multiple pathogens of economic importance, especially those with insect or mite vectors. Real-time/quantitative PCR (qPCR) has been used for high-throughput detection and relative quantification of pathogens; however, target reference or standards are required. I...

20180312 - Mechanistic Modeling of Developmental Defects through Computational Embryology (SOT)

EPA Science Inventory

Significant advances in the genome sciences, in automated high-throughput screening (HTS), and in alternative methods for testing enable rapid profiling of chemical libraries for quantitative effects on diverse cellular activities. While a surfeit of HTS data and information is n...

Exploiting induced variation to dissect quantitative traits in barley.

PubMed

Druka, Arnis; Franckowiak, Jerome; Lundqvist, Udda; Bonar, Nicola; Alexander, Jill; Guzy-Wrobelska, Justyna; Ramsay, Luke; Druka, Ilze; Grant, Iain; Macaulay, Malcolm; Vendramin, Vera; Shahinnia, Fahimeh; Radovic, Slobodanka; Houston, Kelly; Harrap, David; Cardle, Linda; Marshall, David; Morgante, Michele; Stein, Nils; Waugh, Robbie

2010-04-01

The identification of genes underlying complex quantitative traits such as grain yield by means of conventional genetic analysis (positional cloning) requires the development of several large mapping populations. However, it is possible that phenotypically related, but more extreme, allelic variants generated by mutational studies could provide a means for more efficient cloning of QTLs (quantitative trait loci). In barley (Hordeum vulgare), with the development of high-throughput genome analysis tools, efficient genome-wide identification of genetic loci harbouring mutant alleles has recently become possible. Genotypic data from NILs (near-isogenic lines) that carry induced or natural variants of genes that control aspects of plant development can be compared with the location of QTLs to potentially identify candidate genes for development--related traits such as grain yield. As yield itself can be divided into a number of allometric component traits such as tillers per plant, kernels per spike and kernel size, mutant alleles that both affect these traits and are located within the confidence intervals for major yield QTLs may represent extreme variants of the underlying genes. In addition, the development of detailed comparative genomic models based on the alignment of a high-density barley gene map with the rice and sorghum physical maps, has enabled an informed prioritization of 'known function' genes as candidates for both QTLs and induced mutant genes.

Rapid analysis of Aurantii Fructus Immaturus (Zhishi) using paper spray ionization mass spectrometry.

PubMed

Liu, Xuemei; Gu, Zhixin; Guo, Yuan; Liu, Jingjing; Ma, Ming; Chen, Bo; Wang, Liping

2017-04-15

Paper spray-mass spectrometry (PS-MS) is a rapid, solvent-efficient, and high-throughput analytical method for analyzing complex samples. In this study, a PS-MS method was developed to obtain MS profiles of Aurantii Fructus Immaturus (aka Zhishi in Chinese) in positive and negative ion modes. In combination with multivariate analyses, including principal component analysis and cluster analysis, the PS-MS profiles of 25 batches of Zhishi were discriminated in 25 batches of Citri Reticulatae Pericarpium Viride (aka Qingpi in Chinese; an adulterant of Zhishi). Moreover, a rapid quantitative analysis of synephrine, a prescriptive quality control component of Zhishi listed in the Chinese Pharmacopoeia, was conducted with PS-MS using synephrine-d2 as an internal standard (IS). The linearity range was 1.68-16.8μg/mL (R 2 =0.9985), the limit of quantitation was 0.5μg/mL. Relative standard deviations in the intra- and inter-day precision of the MS were 4.87 and 4.90%, respectively. Compared with HPLC results, there was no significant difference in the quantitation of synephrine. This study demonstrated that the PS-MS method is useful for the rapid discrimination and quality control of Zhishi samples. Copyright © 2017 Elsevier B.V. All rights reserved.

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

ScienceCinema

Athavale, Ajay

2018-01-04

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

OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

PubMed

Röst, Hannes L; Sachsenberg, Timo; Aiche, Stephan; Bielow, Chris; Weisser, Hendrik; Aicheler, Fabian; Andreotti, Sandro; Ehrlich, Hans-Christian; Gutenbrunner, Petra; Kenar, Erhan; Liang, Xiao; Nahnsen, Sven; Nilse, Lars; Pfeuffer, Julianus; Rosenberger, George; Rurik, Marc; Schmitt, Uwe; Veit, Johannes; Walzer, Mathias; Wojnar, David; Wolski, Witold E; Schilling, Oliver; Choudhary, Jyoti S; Malmström, Lars; Aebersold, Ruedi; Reinert, Knut; Kohlbacher, Oliver

2016-08-30

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease.

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

PubMed

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

2017-02-01

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

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

PubMed

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

2013-01-01

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

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

PubMed

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

2011-02-01

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

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

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

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

2014-07-01

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

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

PubMed Central

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

2004-01-01

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

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

PubMed

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

2018-03-02

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

Ranking the in vivo toxicity of nanomaterials in Drosophila melanogaster

NASA Astrophysics Data System (ADS)

Vecchio, G.; Galeone, A.; Malvindi, M. A.; Cingolani, R.; Pompa, P. P.

2013-09-01

In this work, we propose a quantitative assessment of nanoparticles toxicity in vivo. We show a quantitative ranking of several types of nanoparticles (AuNPs, AgNPs, cadmium-based QDs, cadmium-free QDs, and iron oxide NPs, with different coating and/or surface chemistries), providing a categorization of their toxicity outcomes. This strategy may offer an innovative high-throughput screening tool of nanomaterials, of potential and broad interest to the nanoscience community.

Using In Vitro High-Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards.

PubMed

Burgoon, Lyle D; Druwe, Ingrid L; Painter, Kyle; Yost, Erin E

2017-02-01

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high-throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline-based meta-regression can be used to integrate data across multiple assay replicates to generate a concentration-response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk-specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta-regression, may allow risk assessors to identify points of departure and risk-specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods. © 2016 Society for Risk Analysis.

Testing quantitative adverse outcome pathway predictions using aromatase inhibitors in female fathead minnows

EPA Science Inventory

To become more efficient and cost effective regulatory toxicology is increasingly averting from whole animal testing toward collecting data at lower levels of biological organization, through such means as in vitro high throughput screening (HTS) assays. When anchored to relevant...

An Upper Bound for Population Exposure Variability (SOT)

EPA Science Inventory

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

Comprehensive circular RNA expression profile in radiation-treated HeLa cells and analysis of radioresistance-related circRNAs.

PubMed

Yu, Duo; Li, Yunfeng; Ming, Zhihui; Wang, Hongyong; Dong, Zhuo; Qiu, Ling; Wang, Tiejun

2018-01-01

Cervical cancer is one of the most common cancers in women worldwide. Malignant tumors develop resistance mechanisms and are less sensitive to or do not respond to irradiation. With the development of high-throughput sequencing technologies, circular RNA (circRNA) has been identified in an increasing number of diseases, especially cancers. It has been reported that circRNA can compete with microRNAs (miRNAs) to change the stability or translation of target RNAs, thus regulating gene expression at the transcriptional level. However, the role of circRNAs in cervical cancer and the radioresistance mechanisms of HeLa cells are unknown. The objective of this study is to investigate the role of circRNAs in radioresistance in HeLa cells. High-throughput sequencing and bioinformatics analysis of irradiated and sham-irradiated HeLa cells. The reliability of high-throughput RNA sequencing was validated using quantitative real-time polymerase chain reaction. The most significant circRNA functions and pathways were selected by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A circRNA-miRNA-target gene interaction network was used to find circRNAs associated with radioresistance. Moreover, a protein-protein interaction network was constructed to identify radioresistance-related hub proteins. High-throughput sequencing allowed the identification of 16,893 circRNAs involved in the response of HeLa cells to radiation. Compared with the control group, there were 153 differentially expressed circRNAs, of which 76 were up-regulated and 77 were down-regulated. GO covered three domains: biological process (BP), cellular component (CC) and molecular function (MF). The terms assigned to the BP domain were peptidyl-tyrosine dephosphorylation and regulation of cell migration. The identified CC terms were cell-cell adherens junction, nucleoplasm and cytosol, and the identified MF terms were protein binding and protein tyrosine phosphatase activity. The top five KEGG pathways were MAPK signaling pathway, endocytosis, axon guidance, neurotrophin signaling pathway, and SNARE interactions in vesicular transport. The protein-protein interaction analysis indicated that 19 proteins might be hub proteins. CircRNAs may play a major role in the response to radiation. These findings may improve our understanding of the role of circRNAs in radioresistance in HeLa cells and allow the development of novel therapeutic approaches.

Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

PubMed

Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

2015-12-01

We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

Identification of susceptibility genes and genetic modifiers of human diseases

NASA Astrophysics Data System (ADS)

Abel, Kenneth; Kammerer, Stefan; Hoyal, Carolyn; Reneland, Rikard; Marnellos, George; Nelson, Matthew R.; Braun, Andreas

2005-03-01

The completion of the human genome sequence enables the discovery of genes involved in common human disorders. The successful identification of these genes is dependent on the availability of informative sample sets, validated marker panels, a high-throughput scoring technology, and a strategy for combining these resources. We have developed a universal platform technology based on mass spectrometry (MassARRAY) for analyzing nucleic acids with high precision and accuracy. To fuel this technology, we generated more than 100,000 validated assays for single nucleotide polymorphisms (SNPs) covering virtually all known and predicted human genes. We also established a large DNA sample bank comprised of more than 50,000 consented healthy and diseased individuals. This combination of reagents and technology allows the execution of large-scale genome-wide association studies. Taking advantage of MassARRAY"s capability for quantitative analysis of nucleic acids, allele frequencies are estimated in sample pools containing large numbers of individual DNAs. To compare pools as a first-pass "filtering" step is a tremendous advantage in throughput and cost over individual genotyping. We employed this approach in numerous genome-wide, hypothesis-free searches to identify genes associated with common complex diseases, such as breast cancer, osteoporosis, and osteoarthritis, and genes involved in quantitative traits like high density lipoproteins cholesterol (HDL-c) levels and central fat. Access to additional well-characterized patient samples through collaborations allows us to conduct replication studies that validate true disease genes. These discoveries will expand our understanding of genetic disease predisposition, and our ability for early diagnosis and determination of specific disease subtype or progression stage.

Automation of fluorescent differential display with digital readout.

PubMed

Meade, Jonathan D; Cho, Yong-Jig; Fisher, Jeffrey S; Walden, Jamie C; Guo, Zhen; Liang, Peng

2006-01-01

Since its invention in 1992, differential display (DD) has become the most commonly used technique for identifying differentially expressed genes because of its many advantages over competing technologies such as DNA microarray, serial analysis of gene expression (SAGE), and subtractive hybridization. Despite the great impact of the method on biomedical research, there has been a lack of automation of DD technology to increase its throughput and accuracy for systematic gene expression analysis. Most of previous DD work has taken a "shot-gun" approach of identifying one gene at a time, with a limited number of polymerase chain reaction (PCR) reactions set up manually, giving DD a low-tech and low-throughput image. We have optimized the DD process with a new platform that incorporates fluorescent digital readout, automated liquid handling, and large-format gels capable of running entire 96-well plates. The resulting streamlined fluorescent DD (FDD) technology offers an unprecedented accuracy, sensitivity, and throughput in comprehensive and quantitative analysis of gene expression. These major improvements will allow researchers to find differentially expressed genes of interest, both known and novel, quickly and easily.

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

PubMed

Shou, Wilson Z; Zhang, Jun

2012-05-01

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

Exploring the diversity of Listeria monocytogenes biofilm architecture by high-throughput confocal laser scanning microscopy and the predominance of the honeycomb-like morphotype.

PubMed

Guilbaud, Morgan; Piveteau, Pascal; Desvaux, Mickaël; Brisse, Sylvain; Briandet, Romain

2015-03-01

Listeria monocytogenes is involved in food-borne illness with a high mortality rate. The persistence of the pathogen along the food chain can be associated with its ability to form biofilms on inert surfaces. While most of the phenotypes associated with biofilms are related to their spatial organization, most published data comparing biofilm formation by L. monocytogenes isolates are based on the quantitative crystal violet assay, which does not give access to structural information. Using a high-throughput confocal-imaging approach, the aim of this work was to decipher the structural diversity of biofilms formed by 96 L. monocytogenes strains isolated from various environments. Prior to large-scale analysis, an experimental design was created to improve L. monocytogenes biofilm formation in microscopic-grade microplates, with special emphasis on the growth medium composition. Microscopic analysis of biofilms formed under the selected conditions by the 96 isolates revealed only weak correlation between the genetic lineages of the isolates and the structural properties of the biofilms. However, a gradient in their geometric descriptors (biovolume, mean thickness, and roughness), ranging from flat multilayers to complex honeycomb-like structures, was shown. The dominant honeycomb-like morphotype was characterized by hollow voids hosting free-swimming cells and localized pockets containing mixtures of dead cells and extracellular DNA (eDNA). Copyright © 2015, American Society for Microbiology. All Rights Reserved.

High throughput quantification of N-glycans using one-pot sialic acid modification and matrix assisted laser desorption ionization time of flight mass spectrometry

PubMed Central

Gil, Geun-Cheol; Iliff, Bryce; Cerny, Ron; Velander, William H.; Van Cott, Kevin E.

2010-01-01

Appropriate glycosylation of recombinant therapeutic glycoproteins has been emphasized in biopharmaceutical industries because the carbohydrate component can affect safety, efficacy, and consistency of the glycoproteins. Reliable quantification methods are essential to ensure consistency of their products with respect to glycosylation, particularly sialylation. Mass spectrometry (MS) has become a popular tool to analyze glycan profiles and structures, showing high resolution and sensitivity with structure identification ability. However, quantification of sialylated glycans using MS is not as reliable because of the different ionization efficiency between neutral and acidic glycans. We report here that amidation in mild acidic conditions can be used to neutralize acidic N-glycans still attached to the protein. The resulting amidated N-glycans can then released from the protein using PNGase F, and labeled with permanent charges on the reducing end to avoid any modification and the formation of metal adducts during MS analysis. The N-glycan modification, digestion, and desalting steps were performed using a single-pot method that can be done in microcentrifuge tubes or 96-well microfilter plates, enabling high throughput glycan analysis. Using this method we were able to perform quantitative MALDI-TOF MS of a recombinant human glycoprotein to determine changes in fucosylation and changes in sialylation that were in very good agreement with a normal phase HPLC oligosaccharide mapping method. PMID:20586471

A fully integrated standalone portable cavity ringdown breath acetone analyzer.

PubMed

Sun, Meixiu; Jiang, Chenyu; Gong, Zhiyong; Zhao, Xiaomeng; Chen, Zhuying; Wang, Zhennan; Kang, Meiling; Li, Yingxin; Wang, Chuji

2015-09-01

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

A fully integrated standalone portable cavity ringdown breath acetone analyzer

NASA Astrophysics Data System (ADS)

Sun, Meixiu; Jiang, Chenyu; Gong, Zhiyong; Zhao, Xiaomeng; Chen, Zhuying; Wang, Zhennan; Kang, Meiling; Li, Yingxin; Wang, Chuji

2015-09-01

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-08-09

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-07-01

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

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

PubMed Central

2015-01-01

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

Adapting the γ-H2AX assay for automated processing in human lymphocytes. 1. Technological aspects.

PubMed

Turner, Helen C; Brenner, David J; Chen, Youhua; Bertucci, Antonella; Zhang, Jian; Wang, Hongliang; Lyulko, Oleksandra V; Xu, Yanping; Shuryak, Igor; Schaefer, Julia; Simaan, Nabil; Randers-Pehrson, Gerhard; Yao, Y Lawrence; Amundson, Sally A; Garty, Guy

2011-03-01

The immunofluorescence-based detection of γ-H2AX is a reliable and sensitive method for quantitatively measuring DNA double-strand breaks (DSBs) in irradiated samples. Since H2AX phosphorylation is highly linear with radiation dose, this well-established biomarker is in current use in radiation biodosimetry. At the Center for High-Throughput Minimally Invasive Radiation Biodosimetry, we have developed a fully automated high-throughput system, the RABIT (Rapid Automated Biodosimetry Tool), that can be used to measure γ-H2AX yields from fingerstick-derived samples of blood. The RABIT workstation has been designed to fully automate the γ-H2AX immunocytochemical protocol, from the isolation of human blood lymphocytes in heparin-coated PVC capillaries to the immunolabeling of γ-H2AX protein and image acquisition to determine fluorescence yield. High throughput is achieved through the use of purpose-built robotics, lymphocyte handling in 96-well filter-bottomed plates, and high-speed imaging. The goal of the present study was to optimize and validate the performance of the RABIT system for the reproducible and quantitative detection of γ-H2AX total fluorescence in lymphocytes in a multiwell format. Validation of our biodosimetry platform was achieved by the linear detection of a dose-dependent increase in γ-H2AX fluorescence in peripheral blood samples irradiated ex vivo with γ rays over the range 0 to 8 Gy. This study demonstrates for the first time the optimization and use of our robotically based biodosimetry workstation to successfully quantify γ-H2AX total fluorescence in irradiated peripheral lymphocytes.

Bioanalytical high-throughput selected reaction monitoring-LC/MS determination of selected estrogen receptor modulators in human plasma: 2000 samples/day.

PubMed

Zweigenbaum, J; Henion, J

2000-06-01

The high-throughput determination of small molecules in biological matrixes has become an important part of drug discovery. This work shows that increased throughput LC/MS/MS techniques can be used for the analysis of selected estrogen receptor modulators in human plasma where more than 2000 samples may be analyzed in a 24-h period. The compounds used to demonstrate the high-throughput methodology include tamoxifen, raloxifene, 4-hydroxytamoxifen, nafoxidine, and idoxifene. Tamoxifen and raloxifene are used in both breast cancer therapy and osteoporosis and have shown prophylactic potential for the reduction of the risk of breast cancer. The described strategy provides LC/MS/MS separation and quantitation for each of the five test articles in control human plasma. The method includes sample preparation employing liquid-liquid extraction in the 96-well format, an LC separation of the five compounds in less than 30 s, and selected reaction monitoring detection from low nano- to microgram per milliter levels. Precision and accuracy are determined where each 96-well plate is considered a typical "tray" having calibration standards and quality control (QC) samples dispersed through each plate. A concept is introduced where 24 96-well plates analyzed in 1 day is considered a "grand tray", and the method is cross-validated with standards placed only at the beginning of the first plate and the end of the last plate. Using idoxifene-d5 as an internal standard, the results obtained for idoxifene and tamoxifen satisfy current bioanalytical method validation criteria on two separate days where 2112 and 2304 samples were run, respectively. Method validation included 24-h autosampler stability and one freeze-thaw cycle stability for the extracts. Idoxifene showed acceptable results with accuracy ranging from 0.3% for the high quality control (QC) to 15.4% for the low QC and precision of 3.6%-13.9% relative standard deviation. Tamoxifen showed accuracy ranging from 1.6% to 13.8% and precision from 7.8% to 15.2%. The linear dynamic range for these compounds was 3 orders of magnitude. The limit of quantification was 5 and 50 ng/ mL for tamoxifen and idoxifene, respectively. The other compounds in this study in general satisfy the more relaxed bioanalytical acceptance criteria for modern drug discovery. It is suggested that the quantification levels reported in this high-throughput analysis example are adequate for many drug discovery and related early pharmaceutical studies.

QUANTITATIVE IN VITRO MEASUREMENT OF CELLULAR PROCESSES CRITICAL TO THE DEVELOPMENT OF NEURAL CONNECTIVITY USING HCA.

EPA Science Inventory

New methods are needed to screen thousands of environmental chemicals for toxicity, including developmental neurotoxicity. In vitro, cell-based assays that model key cellular events have been proposed for high throughput screening of chemicals for developmental neurotoxicity. Whi...

High Throughput Heuristics for Prioritizing Human Exposure to Environmental Chemicals

EPA Science Inventory

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the potential hazard presented by the chemical, and the possibility of being exposed. Without the capacity to make quantitative, albeit uncertain, f...

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

PubMed

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

2013-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Harnessing cell-to-cell variations to probe bacterial structure and biophysics

NASA Astrophysics Data System (ADS)

Cass, Julie A.

Advances in microscopy and biotechnology have given us novel insights into cellular biology and physics. While bacteria were long considered to be relatively unstructured, the development of fluorescence microscopy techniques, and spatially and temporally resolved high-throughput quantitative studies, have uncovered that the bacterial cell is highly organized, and its structure rigorously maintained. In this thesis I will describe our gateTool software, designed to harness cell-to-cell variations to probe bacterial structure, and discuss two exciting aspects of structure that we have employed gateTool to investigate: (i) chromosome organization and the cellular mechanisms for controlling DNA dynamics, and (ii) the study of cell wall synthesis, and how the genes in the synthesis pathway impact cellular shape. In the first project, we develop a spatial and temporal mapping of cell-cycle-dependent chromosomal organization, and use this quantitative map to discover that chromosomal loci segregate from midcell with universal dynamics. In the second project, I describe preliminary time- lapse and snapshot imaging analysis suggesting phentoypical coherence across peptidoglycan synthesis pathways.

Quantitative maps of genetic interactions in yeast - comparative evaluation and integrative analysis.

PubMed

Lindén, Rolf O; Eronen, Ville-Pekka; Aittokallio, Tero

2011-03-24

High-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms. Using large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies. We have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

Web-based visual analysis for high-throughput genomics

PubMed Central

2013-01-01

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

High Throughput Sequence Analysis for Disease Resistance in Maize

USDA-ARS?s Scientific Manuscript database

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

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

EPA Science Inventory

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

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

PubMed Central

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

2016-01-01

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

Novel Quantitative Autophagy Analysis by Organelle Flow Cytometry after Cell Sonication

PubMed Central

Degtyarev, Michael; Reichelt, Mike; Lin, Kui

2014-01-01

Autophagy is a dynamic process of bulk degradation of cellular proteins and organelles in lysosomes. Current methods of autophagy measurement include microscopy-based counting of autophagic vacuoles (AVs) in cells. We have developed a novel method to quantitatively analyze individual AVs using flow cytometry. This method, OFACS (organelle flow after cell sonication), takes advantage of efficient cell disruption with a brief sonication, generating cell homogenates with fluorescently labeled AVs that retain their integrity as confirmed with light and electron microscopy analysis. These AVs could be detected directly in the sonicated cell homogenates on a flow cytometer as a distinct population of expected organelle size on a cytometry plot. Treatment of cells with inhibitors of autophagic flux, such as chloroquine or lysosomal protease inhibitors, increased the number of particles in this population under autophagy inducing conditions, while inhibition of autophagy induction with 3-methyladenine or knockdown of ATG proteins prevented this accumulation. This assay can be easily performed in a high-throughput format and opens up previously unexplored avenues for autophagy analysis. PMID:24489953

Applications of Microfluidics in Quantitative Biology.

PubMed

Bai, Yang; Gao, Meng; Wen, Lingling; He, Caiyun; Chen, Yuan; Liu, Chenli; Fu, Xiongfei; Huang, Shuqiang

2018-05-01

Quantitative biology is dedicated to taking advantage of quantitative reasoning and advanced engineering technologies to make biology more predictable. Microfluidics, as an emerging technique, provides new approaches to precisely control fluidic conditions on small scales and collect data in high-throughput and quantitative manners. In this review, the authors present the relevant applications of microfluidics to quantitative biology based on two major categories (channel-based microfluidics and droplet-based microfluidics), and their typical features. We also envision some other microfluidic techniques that may not be employed in quantitative biology right now, but have great potential in the near future. © 2017 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. Biotechnology Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

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

PubMed

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

1994-01-01

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

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

NASA Astrophysics Data System (ADS)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Robust and Sensitive Analysis of Mouse Knockout Phenotypes

PubMed Central

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

2012-01-01

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

Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Cancer.gov

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq.

PubMed

Wang, Jun; Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq

PubMed Central

Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet. PMID:28644843

High-speed spectral nanocytology for early cancer screening

PubMed Central

Subramanian, Hariharan; Maneval, Charles D.; White, Craig A.; Levenson, Richard M.; Backman, Vadim

2013-01-01

Abstract. High-throughput partial wave spectroscopy (HTPWS) is introduced as a high-speed spectral nanocytology technique that utilizes the field effect of carcinogenesis to perform minimally invasive cancer screening on at-risk populations. HTPWS uses fully automated hardware and an acousto-optic tunable filter to scan slides at low magnification, to select cells, and to rapidly acquire spectra at each spatial pixel in a cell between 450 and 700 nm, completing measurements of 30 cells in 40 min. Statistical quantitative analysis on the size and density of intracellular nanostructures extracted from the spectra at each pixel in a cell yields the diagnostic biomarker, disorder strength (Ld). Linear correlation between Ld and the length scale of nanostructures was measured in phantoms with R2=0.93. Diagnostic sensitivity was demonstrated by measuring significantly higher Ld from a human colon cancer cell line (HT29 control vector) than a less aggressive variant (epidermal growth factor receptor knockdown). Clinical diagnostic performance for lung cancer screening was tested on 23 patients, yielding a significant difference in Ld between smokers and cancer patients, p=0.02 and effect size=1.00. The high-throughput performance, nanoscale sensitivity, and diagnostic sensitivity make HTPWS a potentially clinically relevant modality for risk stratification of the large populations at risk of developing cancer. PMID:24193949

Microwave assisted saponification (MAS) followed by on-line liquid chromatography (LC)-gas chromatography (GC) for high-throughput and high-sensitivity determination of mineral oil in different cereal-based foodstuffs.

PubMed

Moret, Sabrina; Scolaro, Marianna; Barp, Laura; Purcaro, Giorgia; Conte, Lanfranco S

2016-04-01

A high throughput, high-sensitivity procedure, involving simultaneous microwave-assisted extraction (MAS) and unsaponifiable extraction, followed by on-line liquid chromatography (LC)-gas chromatography (GC), has been optimised for rapid and efficient extraction and analytical determination of mineral oil saturated hydrocarbons (MOSH) and mineral oil aromatic hydrocarbons (MOAH) in cereal-based products of different composition. MAS has the advantage of eliminating fat before LC-GC analysis, allowing an increase in the amount of sample extract injected, and hence in sensitivity. The proposed method gave practically quantitative recoveries and good repeatability. Among the different cereal-based products analysed (dry semolina and egg pasta, bread, biscuits, and cakes), egg pasta packed in direct contact with recycled paperboard had on average the highest total MOSH level (15.9 mg kg(-1)), followed by cakes (10.4 mg kg(-1)) and bread (7.5 mg kg(-1)). About 50% of the pasta and bread samples and 20% of the biscuits and cake samples had detectable MOAH amounts. The highest concentrations were found in an egg pasta in direct contact with recycled paperboard (3.6 mg kg(-1)) and in a milk bread (3.6 mg kg(-1)). Copyright © 2015 Elsevier Ltd. All rights reserved.

Glycoprotein Disease Markers and Single Protein-omics*

PubMed Central

Chandler, Kevin; Goldman, Radoslav

2013-01-01

Glycoproteins are well represented among biomarkers for inflammatory and cancer diseases. Secreted and membrane-associated glycoproteins make excellent targets for noninvasive detection. In this review, we discuss clinically applicable markers of cancer diseases and methods for their analysis. High throughput discovery continues to supply marker candidates with unusual glycan structures, altered glycoprotein abundance, or distribution of site-specific glycoforms. Improved analytical methods are needed to unlock the potential of these discoveries in validated clinical assays. A new generation of targeted quantitative assays is expected to advance the use of glycoproteins in early detection of diseases, molecular disease classification, and monitoring of therapeutic interventions. PMID:23399550

Transcriptome discovery in non-model wild fish species for the development of quantitative transcript abundance assays.

PubMed

Hahn, Cassidy M; Iwanowicz, Luke R; Cornman, Robert S; Mazik, Patricia M; Blazer, Vicki S

2016-12-01

Environmental studies increasingly identify the presence of both contaminants of emerging concern (CECs) and legacy contaminants in aquatic environments; however, the biological effects of these compounds on resident fishes remain largely unknown. High throughput methodologies were employed to establish partial transcriptomes for three wild-caught, non-model fish species; smallmouth bass (Micropterus dolomieu), white sucker (Catostomus commersonii) and brown bullhead (Ameiurus nebulosus). Sequences from these transcriptome databases were utilized in the development of a custom nCounter CodeSet that allowed for direct multiplexed measurement of 50 transcript abundance endpoints in liver tissue. Sequence information was also utilized in the development of quantitative real-time PCR (qPCR) primers. Cross-species hybridization allowed the smallmouth bass nCounter CodeSet to be used for quantitative transcript abundance analysis of an additional non-model species, largemouth bass (Micropterus salmoides). We validated the nCounter analysis data system with qPCR for a subset of genes and confirmed concordant results. Changes in transcript abundance biomarkers between sexes and seasons were evaluated to provide baseline data on transcript modulation for each species of interest. Published by Elsevier Inc.

Sensitive and quantitative measurement of gene expression directly from a small amount of whole blood.

PubMed

Zheng, Zhi; Luo, Yuling; McMaster, Gary K

2006-07-01

Accurate and precise quantification of mRNA in whole blood is made difficult by gene expression changes during blood processing, and by variations and biases introduced by sample preparations. We sought to develop a quantitative whole-blood mRNA assay that eliminates blood purification, RNA isolation, reverse transcription, and target amplification while providing high-quality data in an easy assay format. We performed single- and multiplex gene expression analysis with multiple hybridization probes to capture mRNA directly from blood lysate and used branched DNA to amplify the signal. The 96-well plate singleplex assay uses chemiluminescence detection, and the multiplex assay combines Luminex-encoded beads with fluorescent detection. The single- and multiplex assays could quantitatively measure as few as 6000 and 24,000 mRNA target molecules (0.01 and 0.04 amoles), respectively, in up to 25 microL of whole blood. Both formats had CVs < 10% and dynamic ranges of 3-4 logs. Assay sensitivities allowed quantitative measurement of gene expression in the minority of cells in whole blood. The signals from whole-blood lysate correlated well with signals from purified RNA of the same sample, and absolute mRNA quantification results from the assay were similar to those obtained by quantitative reverse transcription-PCR. Both single- and multiplex assay formats were compatible with common anticoagulants and PAXgene-treated samples; however, PAXgene preparations induced expression of known antiapoptotic genes in whole blood. Both the singleplex and the multiplex branched DNA assays can quantitatively measure mRNA expression directly from small volumes of whole blood. The assay offers an alternative to current technologies that depend on RNA isolation and is amenable to high-throughput gene expression analysis of whole blood.

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

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

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

2009-07-20

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

Native denaturation differential scanning fluorimetry: Determining the effect of urea using a quantitative real-time thermocycler.

PubMed

Childers, Christine L; Green, Stuart R; Dawson, Neal J; Storey, Kenneth B

2016-09-01

The effect of protein stability on kinetic function is monitored with many techniques that often require large amounts of expensive substrates and specialized equipment not universally available. We present differential scanning fluorimetry (DSF), a simple high-throughput assay performed in real-time thermocyclers, as a technique for analysis of protein unfolding. Furthermore, we demonstrate a correlation between the half-maximal rate of protein unfolding (Knd), and protein unfolding by urea (I50). This demonstrates that DSF methods can determine the structural stability of an enzyme's active site and can compare the relative structural stability of homologous enzymes with a high degree of sequence similarity. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

Virtual Liver: Quantitative Dose-Response Using Systems Biology

EPA Science Inventory

The U.S. EPA’s ToxCast™ program uses hundreds of high-throughput, in vitro assays to screen chemicals in order to rapidly identify signatures of toxicity. These assays measure the in vitro concentrations at which cellular pathways are perturbed by chemicals. The U.S. EPA’s Virtu...

SPECIES-SPECIFIC DETECTION OF THREE HUMAN-PATHOGENIC MICROSPORIDIAL SPECIES FROM THE GENUS ENCEPHALITOZOON VIA FLUOROGENIC 5' NUCLEASE PCR ASSAYS

EPA Science Inventory

This describes fluorogenic 5' nuclease PCR assays suitable for rapid, sensitive, quantitative, high-throughput detection of the human-pathogenic microsporidial species Encephalitozoon hellem, E. cunicli and E. intestinalis. The assays utilize species-specific primer sets and a g...

Quantitative High-Throughput Screening and Confirmation Studies for Identification of Compounds that Activate the Aryl Hydrocarbon Receptor Pathway (SETAC)

EPA Science Inventory

The aryl hydrocarbon receptor (AhR) is a transcription factor that mediates adaptive responses to known environmental pollutants, such as aromatic hydrocarbons, through regulation of Phase I and II xenobiotic metabolizing enzymes as well as important growth and differentiation pa...

A Call for Nominations of Quantitative High-Throughput Screening Assays from Relevant Human Toxicity Pathways

EPA Science Inventory

The National Research Council of the United States National Academies of Science has recently released a document outlining a long-range vision and strategy for transforming toxicity testing from largely whole animal-based testing to one based on in vitro assays. “Toxicity Testin...

Profiling Environmental Chemicals in the Antioxidant Response Element Pathway using Quantitative High Throughput Screening (qHTS)

EPA Science Inventory

The antioxidant response element (ARE) signaling pathway plays an important role in the amelioration of oxidative stress, which can contribute to a number of diseases, including cancer. We screened 1408 NTP-provided substances in 1536-well qHTS format at concentrations ranging fr...

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

EPA Science Inventory

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

Analysis of CERN computing infrastructure and monitoring data

NASA Astrophysics Data System (ADS)

Nieke, C.; Lassnig, M.; Menichetti, L.; Motesnitsalis, E.; Duellmann, D.

2015-12-01

Optimizing a computing infrastructure on the scale of LHC requires a quantitative understanding of a complex network of many different resources and services. For this purpose the CERN IT department and the LHC experiments are collecting a large multitude of logs and performance probes, which are already successfully used for short-term analysis (e.g. operational dashboards) within each group. The IT analytics working group has been created with the goal to bring data sources from different services and on different abstraction levels together and to implement a suitable infrastructure for mid- to long-term statistical analysis. It further provides a forum for joint optimization across single service boundaries and the exchange of analysis methods and tools. To simplify access to the collected data, we implemented an automated repository for cleaned and aggregated data sources based on the Hadoop ecosystem. This contribution describes some of the challenges encountered, such as dealing with heterogeneous data formats, selecting an efficient storage format for map reduce and external access, and will describe the repository user interface. Using this infrastructure we were able to quantitatively analyze the relationship between CPU/wall fraction, latency/throughput constraints of network and disk and the effective job throughput. In this contribution we will first describe the design of the shared analysis infrastructure and then present a summary of first analysis results from the combined data sources.

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

PubMed Central

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

2007-01-01

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

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

PubMed

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

2016-01-15

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

Automated High-Throughput Quantification of Mitotic Spindle Positioning from DIC Movies of Caenorhabditis Embryos

PubMed Central

Cluet, David; Spichty, Martin; Delattre, Marie

2014-01-01

The mitotic spindle is a microtubule-based structure that elongates to accurately segregate chromosomes during anaphase. Its position within the cell also dictates the future cell cleavage plan, thereby determining daughter cell orientation within a tissue or cell fate adoption for polarized cells. Therefore, the mitotic spindle ensures at the same time proper cell division and developmental precision. Consequently, spindle dynamics is the matter of intensive research. Among the different cellular models that have been explored, the one-cell stage C. elegans embryo has been an essential and powerful system to dissect the molecular and biophysical basis of spindle elongation and positioning. Indeed, in this large and transparent cell, spindle poles (or centrosomes) can be easily detected from simple DIC microscopy by human eyes. To perform quantitative and high-throughput analysis of spindle motion, we developed a computer program ACT for Automated-Centrosome-Tracking from DIC movies of C. elegans embryos. We therefore offer an alternative to the image acquisition and processing of transgenic lines expressing fluorescent spindle markers. Consequently, experiments on large sets of cells can be performed with a simple setup using inexpensive microscopes. Moreover, analysis of any mutant or wild-type backgrounds is accessible because laborious rounds of crosses with transgenic lines become unnecessary. Last, our program allows spindle detection in other nematode species, offering the same quality of DIC images but for which techniques of transgenesis are not accessible. Thus, our program also opens the way towards a quantitative evolutionary approach of spindle dynamics. Overall, our computer program is a unique macro for the image- and movie-processing platform ImageJ. It is user-friendly and freely available under an open-source licence. ACT allows batch-wise analysis of large sets of mitosis events. Within 2 minutes, a single movie is processed and the accuracy of the automated tracking matches the precision of the human eye. PMID:24763198

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

EPA Science Inventory

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

Multistrip Western blotting: a tool for comparative quantitative analysis of multiple proteins.

PubMed

Aksamitiene, Edita; Hoek, Jan B; Kiyatkin, Anatoly

2015-01-01

The qualitative and quantitative measurements of protein abundance and modification states are essential in understanding their functions in diverse cellular processes. Typical Western blotting, though sensitive, is prone to produce substantial errors and is not readily adapted to high-throughput technologies. Multistrip Western blotting is a modified immunoblotting procedure based on simultaneous electrophoretic transfer of proteins from multiple strips of polyacrylamide gels to a single membrane sheet. In comparison with the conventional technique, Multistrip Western blotting increases data output per single blotting cycle up to tenfold; allows concurrent measurement of up to nine different total and/or posttranslationally modified protein expression obtained from the same loading of the sample; and substantially improves the data accuracy by reducing immunoblotting-derived signal errors. This approach enables statistically reliable comparison of different or repeated sets of data and therefore is advantageous to apply in biomedical diagnostics, systems biology, and cell signaling research.

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

PubMed

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

2012-03-01

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

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

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

Luo, Wei; Shabbir, Faizan; Gong, Chao

2015-04-13

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

A high-throughput label-free nanoparticle analyser.

PubMed

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

2011-05-01

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

Populational analysis of suspended microtissues for high-throughput, multiplexed 3D tissue engineering

PubMed Central

Chen, Alice A.; Underhill, Gregory H.; Bhatia, Sangeeta N.

2014-01-01

Three-dimensional (3D) tissue models have significantly improved our understanding of structure/function relationships and promise to lead to new advances in regenerative medicine. However, despite the expanding diversity of 3D tissue fabrication methods, approaches for functional assessment have been relatively limited. Here, we describe the fabrication of microtissue (μ-tissue) suspensions and their quantitative evaluation with techniques capable of analyzing large sample numbers and performing multiplexed parallel analysis. We applied this platform to 3D μ-tissues representing multiple stages of liver development and disease including: embryonic stem cells, bipotential hepatic progenitors, mature hepatocytes, and hepatoma cells photoencapsulated in polyethylene glycol hydrogels. Multiparametric μ-tissue cytometry enabled quantitation of fluorescent reporter expression within populations of intact μ-tissues (n≥102-103) and sorting-based enrichment of subsets for subsequent studies. Further, 3D μ-tissues could be implanted in vivo, respond to systemic stimuli, retrieved and quantitatively assessed. In order to facilitate multiplexed ‘pooled’ experimentation, fluorescent labeling strategies were developed and utilized to investigate the impact of μ-tissue composition and exposure to soluble factors. In particular, examination of drug/gene interactions on collections of 3D hepatoma μ-tissues indicated synergistic influence of doxorubicin and knockdown of the anti-apoptotic gene BCL-XL. Collectively, these studies highlight the broad utility of μ-tissue suspensions as an enabling approach for high n, populational analysis of 3D tissue biology in vitro and in vivo. PMID:20820630

Evaluation of laser diode thermal desorption-tandem mass spectrometry (LDTD-MS-MS) in forensic toxicology.

PubMed

Bynum, Nichole D; Moore, Katherine N; Grabenauer, Megan

2014-10-01

Many forensic laboratories experience backlogs due to increased drug-related cases. Laser diode thermal desorption (LDTD) has demonstrated its applicability in other scientific areas by providing data comparable with instrumentation, such as liquid chromatography-tandem mass spectrometry, in less time. LDTD-MS-MS was used to validate 48 compounds in drug-free human urine and blood for screening or quantitative analysis. Carryover, interference, limit of detection, limit of quantitation, matrix effect, linearity, precision and accuracy and stability were evaluated. Quantitative analysis indicated that LDTD-MS-MS produced precise and accurate results with the average overall within-run precision in urine and blood represented by a %CV <14.0 and <7.0, respectively. The accuracy for all drugs in urine ranged from 88.9 to 104.5% and 91.9 to 107.1% in blood. Overall, LDTD has the potential for use in forensic toxicology but before it can be successfully implemented that there are some challenges that must be addressed. Although the advantages of the LDTD system include minimal maintenance and rapid analysis (∼10 s per sample) which makes it ideal for high-throughput forensic laboratories, a major disadvantage is its inability or difficulty analyzing isomers and isobars due to the lack of chromatography without the use of high-resolution MS; therefore, it would be best implemented as a screening technique. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

MIPHENO: Data normalization for high throughput metabolic analysis.

EPA Science Inventory

High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...

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

ScienceCinema

Gore, Brooklin

2018-02-01

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

Novel approaches to analysis of 3-chloropropane-1,2-diol esters in vegetable oils.

PubMed

Moravcova, Eliska; Vaclavik, Lukas; Lacina, Ondrej; Hrbek, Vojtech; Riddellova, Katerina; Hajslova, Jana

2012-03-01

A sensitive and accurate method utilizing ultrahigh performance liquid chromatography (U-HPLC) coupled to high resolution mass spectrometry based on orbitrap technology (orbitrapMS) for the analysis of nine 3-chloropropane-1,2-diol (3-MCPD) diesters in vegetable oils was developed. To remove the interfering triacylglycerols that induce strong matrix effects, a clean-up step on silica gel column was used. The quantitative analysis was performed with the use of deuterium-labeled internal standards. The lowest calibration levels estimated for the respective analytes ranged from 2 to 5 μg kg(-1). Good recovery values (89-120%) and repeatability (RSD 5-9%) was obtained at spiking levels of 2 and 10 mg kg(-1). As an alternative, a novel ambient desorption ionization technique, direct analysis in real time (DART), hyphenated with orbitrapMS, was employed for no separation, high-throughput, semi-quantitative screening of 3-MCPD diesters in samples obtained by chromatographic fractionation. Additionally, the levels of 3-MCPD diesters measured in reallife vegetable oil samples (palm oil, sunflower oil, rapeseed oil) using both methods are reported. Relatively good agreement of the data generated by U-HPLC-orbitrapMS and DART-orbitrapMS were observed. With regard to a low ionization yield achieved for 3-MCPD monoesters, the methods presented in this paper were not yet applicable for the analysis of these contaminants at the naturally occurring levels.

Molecular Rotors for Universal Quantitation of Nanoscale Hydrophobic Interfaces in Microplate Format.

PubMed

Bisso, Paul W; Tai, Michelle; Katepalli, Hari; Bertrand, Nicolas; Blankschtein, Daniel; Langer, Robert

2018-01-10

Hydrophobic self-assembly pairs diverse chemical precursors and simple formulation processes to access a vast array of functional colloids. Exploration of this design space, however, is stymied by lack of broadly general, high-throughput colloid characterization tools. Here, we show that a narrow structural subset of fluorescent, zwitterionic molecular rotors, dialkylaminostilbazolium sulfonates [DASS] with intermediate-length alkyl tails, fills this major analytical void by quantitatively sensing hydrophobic interfaces in microplate format. DASS dyes supersede existing interfacial probes by avoiding off-target fluorogenic interactions and dye aggregation while preserving hydrophobic partitioning strength. To illustrate the generality of this approach, we demonstrate (i) a microplate-based technique for measuring mass concentration of small (20-200 nm), dilute (submicrogram sensitivity) drug delivery nanoparticles; (ii) elimination of particle size, surfactant chemistry, and throughput constraints on quantifying the complex surfactant/metal oxide adsorption isotherms critical for environmental remediation and enhanced oil recovery; and (iii) more reliable self-assembly onset quantitation for chemically and structurally distinct amphiphiles. These methods could streamline the development of nanotechnologies for a broad range of applications.

One step screening of retroviral producer clones by real time quantitative PCR.

PubMed

Towers, G J; Stockholm, D; Labrousse-Najburg, V; Carlier, F; Danos, O; Pagès, J C

1999-01-01

Recombinant retroviruses are obtained from either stably or transiently transfected retrovirus producer cells. In the case of stably producing lines, a large number of clones must be screened in order to select the one with the highest titre. The multi-step selection of high titre producing clones is time consuming and expensive. We have taken advantage of retroviral endogenous reverse transcription to develop a quantitative PCR assay on crude supernatant from producing clones. We used Taqman PCR technology, which, by using fluorescence measurement at each cycle of amplification, allows PCR product quantification. Fluorescence results from specific degradation of a probe oligonucleotide by the Taq polymerase 3'-5' exonuclease activity. Primers and probe sequences were chosen to anneal to the viral strong stop species, which is the first DNA molecule synthesised during reverse transcription. The protocol consists of a single real time PCR, using as template filtered viral supernatant without any other pre-treatment. We show that the primers and probe described allow quantitation of serially diluted plasmid to as few as 15 plasmid molecules. We then test 200 GFP-expressing retroviral-producing clones either by FACS analysis of infected cells or by using the quantitative PCR. We confirm that the Taqman protocol allows the detection of virus in supernatant and selection of high titre clones. Furthermore, we can determine infectious titre by quantitative PCR on genomic DNA from infected cells, using an additional set of primers and probe to albumin to normalise for the genomic copy number. We demonstrate that real time quantitative PCR can be used as a powerful and reliable single step, high throughput screen for high titre retroviral producer clones.

High-throughput nanoparticle sizing using lensfree holographic microscopy and liquid nanolenses (Conference Presentation)

NASA Astrophysics Data System (ADS)

McLeod, Euan

2016-03-01

The sizing of individual nanoparticles and the recovery of the distributions of sizes from populations of nanoparticles provide valuable information in virology, exosome analysis, air and water quality monitoring, and nanomaterials synthesis. Conventional approaches for nanoparticle sizing include those based on costly or low-throughput laboratory-scale equipment such as transmission electron microscopy or nanoparticle tracking analysis, as well as those approaches that only provide population-averaged quantities, such as dynamic light scattering. Some of these limitations can be overcome using a new family of alternative approaches based on quantitative phase imaging that combines lensfree holographic on-chip microscopy with self-assembled liquid nanolenses. In these approaches, the particles of interest are deposited onto a glass coverslip and the sample is coated with either pure liquid polyethylene glycol (PEG) or aqueous solutions of PEG. Due to surface tension, the PEG self-assembles into nano-scale lenses around the particles of interest. These nanolenses enhance the scattering signatures of the embedded particles such that individual nanoparticles as small as 40 nm are clearly visible in phase images reconstructed from captured holograms. The magnitude of the phase quantitatively corresponds to particle size with an accuracy of +/-11 nm. This family of approaches can individually size more than 10^5 particles in parallel, can handle a large dynamic range of particle sizes (40 nm - 100s of microns), and can accurately size multi-modal distributions of particles. Furthermore, the entire approach has been implemented in a compact and cost-effective device suitable for use in the field or in low-resource settings.

Proteomics: from hypothesis to quantitative assay on a single platform. Guidelines for developing MRM assays using ion trap mass spectrometers.

PubMed

Han, Bomie; Higgs, Richard E

2008-09-01

High-throughput HPLC-mass spectrometry (HPLC-MS) is routinely used to profile biological samples for potential protein markers of disease, drug efficacy and toxicity. The discovery technology has advanced to the point where translating hypotheses from proteomic profiling studies into clinical use is the bottleneck to realizing the full potential of these approaches. The first step in this translation is the development and analytical validation of a higher throughput assay with improved sensitivity and selectivity relative to typical profiling assays. Multiple reaction monitoring (MRM) assays are an attractive approach for this stage of biomarker development given their improved sensitivity and specificity, the speed at which the assays can be developed and the quantitative nature of the assay. While the profiling assays are performed with ion trap mass spectrometers, MRM assays are traditionally developed in quadrupole-based mass spectrometers. Development of MRM assays from the same instrument used in the profiling analysis enables a seamless and rapid transition from hypothesis generation to validation. This report provides guidelines for rapidly developing an MRM assay using the same mass spectrometry platform used for profiling experiments (typically ion traps) and reviews methodological and analytical validation considerations. The analytical validation guidelines presented are drawn from existing practices on immunological assays and are applicable to any mass spectrometry platform technology.

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

PubMed

Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

PubMed

Gough, Albert; Stern, Andrew M; Maier, John; Lezon, Timothy; Shun, Tong-Ying; Chennubhotla, Chakra; Schurdak, Mark E; Haney, Steven A; Taylor, D Lansing

2017-03-01

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

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

PubMed

Sallon, C; Soulet, D; Tremblay, Y

2017-12-01

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

A novel high-throughput method for supported liquid extraction of retinol and alpha-tocopherol from human serum and simultaneous quantitation by liquid chromatography tandem mass spectrometry.

PubMed

Hinchliffe, Edward; Rudge, James; Reed, Paul

2016-07-01

Measurement of vitamin A (retinol) and E (alpha-tocopherol) in UK clinical laboratories is currently performed exclusively by high-performance liquid chromatography with ultraviolet detection. We investigated whether retinol and alpha-tocopherol could be measured simultaneously by liquid chromatography tandem mass spectrometry. Serum samples (100 μL) were extracted using Isolute + Supported Liquid Extraction plates. Chromatography was performed on a Phenomenex Kinetex Biphenyl 2.6 μm, 50 × 2.1 mm column, and liquid chromatography tandem mass spectrometry on a Waters Acquity TQD. Injection-to-injection time was 4.3 min. The assay was validated according to published guidelines. Patient samples were used to compare liquid chromatography tandem mass spectrometry and high-performance liquid chromatography with ultraviolet detection methods. For retinol and alpha-tocopherol, respectively, the assay was linear up to 6.0 and 80.0 μmol/L, and lower limit of quantification was 0.07 and 0.26 μmol/L. Intra and interassay imprecision were within desirable analytical specifications. Analysis of quality control material aligned to NIST SRM 968e, and relative spiked recovery from human serum, both yielded results within 15% of target values. Method comparison with high-performance liquid chromatography with ultraviolet detection methodology demonstrated a negative bias for retinol and alpha-tocopherol by the liquid chromatography tandem mass spectrometry method. Analysis of United Kingdom National External Quality Assurance Scheme samples yielded mean bias from the target value of +3.0% for retinol and -11.2% for alpha-tocopherol. We have developed a novel, high-throughput method for extraction of retinol and alpha-tocopherol from human serum followed by simultaneous quantitation by liquid chromatography tandem mass spectrometry. The method offers a rapid, sensitive, specific and cost-effective alternative to high-performance liquid chromatography with ultraviolet detection methodology, and is suitable for routine clinical monitoring of patients predisposed to fat-soluble vitamin malabsorption. © The Author(s) 2015.

Label-Free, LC-MS-Based Assays to Quantitate Small-Molecule Antagonist Binding to the Mammalian BLT1 Receptor.

PubMed

Chen, Xun; Stout, Steven; Mueller, Uwe; Boykow, George; Visconti, Richard; Siliphaivanh, Phieng; Spencer, Kerrie; Presland, Jeremy; Kavana, Michael; Basso, Andrea D; McLaren, David G; Myers, Robert W

2017-08-01

We have developed and validated label-free, liquid chromatography-mass spectrometry (LC-MS)-based equilibrium direct and competition binding assays to quantitate small-molecule antagonist binding to recombinant human and mouse BLT1 receptors expressed in HEK 293 cell membranes. Procedurally, these binding assays involve (1) equilibration of the BLT1 receptor and probe ligand, with or without a competitor; (2) vacuum filtration through cationic glass fiber filters to separate receptor-bound from free probe ligand; and (3) LC-MS analysis in selected reaction monitoring mode for bound probe ligand quantitation. Two novel, optimized probe ligands, compounds 1 and 2, were identified by screening 20 unlabeled BLT1 antagonists for direct binding. Saturation direct binding studies confirmed the high affinity, and dissociation studies established the rapid binding kinetics of probe ligands 1 and 2. Competition binding assays were established using both probe ligands, and the affinities of structurally diverse BLT1 antagonists were measured. Both binding assay formats can be executed with high specificity and sensitivity and moderate throughput (96-well plate format) using these approaches. This highly versatile, label-free method for studying ligand binding to membrane-associated receptors should find broad application as an alternative to traditional methods using labeled ligands.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

PubMed

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

Monitoring the synthesis of biomolecules using mass spectrometry.

PubMed

Miyagi, Masaru; Kasumov, Takhar

2016-10-28

The controlled and selective synthesis/clearance of biomolecules is critical for most cellular processes. In most high-throughput 'omics' studies, we measure the static quantities of only one class of biomolecules (e.g. DNA, mRNA, proteins or metabolites). It is, however, important to recognize that biological systems are highly dynamic in which biomolecules are continuously renewed and different classes of biomolecules interact and affect each other's production/clearance. Therefore, it is necessary to measure the turnover of diverse classes of biomolecules to understand the dynamic nature of biological systems. Herein, we explain why the kinetic analysis of a diverse range of biomolecules is important and how such an analysis can be done. We argue that heavy water ((2)H2O) could be a universal tracer for monitoring the synthesis of biomolecules on a global scale.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

Monitoring the synthesis of biomolecules using mass spectrometry

PubMed Central

2016-01-01

The controlled and selective synthesis/clearance of biomolecules is critical for most cellular processes. In most high-throughput ‘omics’ studies, we measure the static quantities of only one class of biomolecules (e.g. DNA, mRNA, proteins or metabolites). It is, however, important to recognize that biological systems are highly dynamic in which biomolecules are continuously renewed and different classes of biomolecules interact and affect each other's production/clearance. Therefore, it is necessary to measure the turnover of diverse classes of biomolecules to understand the dynamic nature of biological systems. Herein, we explain why the kinetic analysis of a diverse range of biomolecules is important and how such an analysis can be done. We argue that heavy water (2H2O) could be a universal tracer for monitoring the synthesis of biomolecules on a global scale. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644976

High-throughput deep screening and identification of four peripheral leucocyte microRNAs as novel potential combination biomarkers for preeclampsia

PubMed Central

Wang, Yonghong; Yang, Xukui; Yang, Yuanyuan; Wang, Wenjun; Zhao, Meiling; Liu, Huiqiang; Li, Dongyan; Hao, Min

2016-01-01

Objective: To identify the specific microRNA (miRNA) biomarkers of preeclampsia (PE), the miRNA profiles analysis were performed. Study Design: The blood samples were obtained from five PE patients and five normal healthy pregnant women. The small RNA profiles were analyzed to identify miRNA expression levels and find out miRNAs that may associate with PE. The quantitative reverse transcriptase–PCR (qRT-PCR) assay was used to validate differentially expressed peripheral leucocyte miRNAs in a new cohort. Result: The data analysis showed that 10 peripheral leucocyte miRNAs were significantly differently expressed in severe PE patients. Four differently expressed miRNAs were successfully validated using qRT-PCR method. Conclusion: We successfully constructed a model with high accuracy to predict PE. A combination of four peripheral leucocyte miRNAs has great potential to serve as diagnostic biomarkers of PE. PMID:26675000

Snapshot Hyperspectral Volumetric Microscopy

NASA Astrophysics Data System (ADS)

Wu, Jiamin; Xiong, Bo; Lin, Xing; He, Jijun; Suo, Jinli; Dai, Qionghai

2016-04-01

The comprehensive analysis of biological specimens brings about the demand for capturing the spatial, temporal and spectral dimensions of visual information together. However, such high-dimensional video acquisition faces major challenges in developing large data throughput and effective multiplexing techniques. Here, we report the snapshot hyperspectral volumetric microscopy that computationally reconstructs hyperspectral profiles for high-resolution volumes of ~1000 μm × 1000 μm × 500 μm at video rate by a novel four-dimensional (4D) deconvolution algorithm. We validated the proposed approach with both numerical simulations for quantitative evaluation and various real experimental results on the prototype system. Different applications such as biological component analysis in bright field and spectral unmixing of multiple fluorescence are demonstrated. The experiments on moving fluorescent beads and GFP labelled drosophila larvae indicate the great potential of our method for observing multiple fluorescent markers in dynamic specimens.

High Resolution Separations and Improved Ion Production and Transmission in Metabolomics

PubMed Central

Metz, Thomas O.; Page, Jason S.; Baker, Erin S.; Tang, Keqi; Ding, Jie; Shen, Yufeng; Smith, Richard D.

2008-01-01

The goal of metabolomics analyses is the detection and quantitation of as many sample components as reasonably possible in order to identify compounds or “features” that can be used to characterize the samples under study. When utilizing electrospray ionization to produce ions for analysis by mass spectrometry (MS), it is important that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize ionization suppression and thereby extend the dynamic range of the measurement, as well as the coverage of the metabolome. Similarly, optimization of the MS inlet and interface can lead to increased measurement sensitivity. This perspective review will focus on the role of high resolution liquid chromatography (LC) separations in conjunction with improved ion production and transmission for LC-MS-based metabolomics. Additional emphasis will be placed on the compromise between metabolome coverage and sample analysis throughput. PMID:19255623

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

PubMed

Najafov, Jamil; Najafov, Ayaz

2017-07-19

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

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

PubMed

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

2016-06-18

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

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

PubMed

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

2016-01-01

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

Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays

EPA Science Inventory

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

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

USDA-ARS?s Scientific Manuscript database

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

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

DTIC Science & Technology

2016-06-01

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

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

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

USDA-ARS?s Scientific Manuscript database

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

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

EPA Science Inventory

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

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

PubMed

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

2015-11-01

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

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

PubMed

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

2006-08-01

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

Development of a high-throughput method to evaluate the impact of inhibitory compounds from lignocellulosic hydrolysates on the growth of Zymomonas mobilis.

PubMed

Franden, Mary Ann; Pienkos, Philip T; Zhang, Min

2009-12-01

Overcoming the effects of hydrolysate toxicity towards ethanologens is a key technical barrier in the biochemical conversion process for biomass feedstocks to ethanol. Despite its importance, the complexity of the hydrolysate toxicity phenomena and the lack of systematic studies, analysis and tools surrounding this issue have blocked a full understanding of relationships involving toxic compounds in hydrolysates and their effects on ethanologen growth and fermentation. In this study, we developed a quantitative, high-throughput biological growth assay using an automated turbidometer to obtain detailed inhibitory kinetics for individual compounds present in lignocellulosic biomass hydrolysate. Information about prolonged lag time and final cell densities can also be obtained. The effects of furfural, hydroxymethylfurfural (HMF), acetate and ethanol on growth rate and final cell densities of Zymomonas mobilis 8b on glucose are presented. This method was also shown to be of value in toxicity studies of hydrolysate itself, despite the highly colored nature of this material. Using this approach, we can generate comprehensive inhibitory profiles with many individual compounds and develop models that predict and examine toxic effects in the complex mixture of hydrolysates, leading to the development of improved pretreatment and conditioning processes as well as fermentation organisms.

Enhanced model-based design of a high-throughput three dimensional micromixer driven by alternating-current electrothermal flow.

PubMed

Wu, Yupan; Ren, Yukun; Jiang, Hongyuan

2017-01-01

We propose a 3D microfluidic mixer based on the alternating current electrothermal (ACET) flow. The ACET vortex is produced by 3D electrodes embedded in the sidewall of the microchannel and is used to stir the fluidic sample throughout the entire channel depth. An optimized geometrical structure of the proposed 3D micromixer device is obtained based on the enhanced theoretical model of ACET flow and natural convection. We quantitatively analyze the flow field driven by the ACET, and a pattern of electrothermal microvortex is visualized by the micro-particle imaging velocimetry. Then, the mixing experiment is conducted using dye solutions with varying solution conductivities. Mixing efficiency can exceed 90% for electrolytes with 0.2 S/m (1 S/m) when the flow rate is 0.364 μL/min (0.728 μL/min) and the imposed peak-to-peak voltage is 52.5 V (35 V). A critical analysis of our micromixer in comparison with different mixer designs using a comparative mixing index is also performed. The ACET micromixer embedded with sidewall 3D electrodes can achieve a highly effective mixing performance and can generate high throughput in the continuous-flow condition. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Microfluidic system for high throughput characterisation of echogenic particles.

PubMed

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

2015-01-21

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

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

PubMed Central

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

2013-01-01

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

ACCELERATED SOLVENT EXTRACTION COMBINED WITH ...

EPA Pesticide Factsheets

A research project was initiated to address a recurring problem of elevated detection limits above required risk-based concentrations for the determination of semivolatile organic compounds in high moisture content solid samples. This project was initiated, in cooperation with the EPA Region 1 Laboratory, under the Regional Methods Program administered through the ORD Office of Science Policy. The aim of the project was to develop an approach for the rapid removal of water in high moisture content solids (e.g., wetland sediments) in preparation for analysis via Method 8270. Alternative methods for water removal have been investigated to enhance compound solid concentrations and improve extraction efficiency, with the use of pressure filtration providing a high-throughput alternative for removal of the majority of free water in sediments and sludges. In order to eliminate problems with phase separation during extraction of solids using Accelerated Solvent Extraction, a variation of a water-isopropanol extraction method developed at the USGS National Water Quality Laboratory in Denver, CO is being employed. The concentrations of target compounds in water-isopropanol extraction fluids are subsequently analyzed using an automated Solid Phase Extraction (SPE)-GC/MS method developed in our laboratory. The coupled approaches for dewatering, extraction, and target compound identification-quantitation provide a useful alternative to enhance sample throughput for Me

Global Profiling of Reactive Oxygen and Nitrogen Species in Biological Systems

PubMed Central

Zielonka, Jacek; Zielonka, Monika; Sikora, Adam; Adamus, Jan; Joseph, Joy; Hardy, Micael; Ouari, Olivier; Dranka, Brian P.; Kalyanaraman, Balaraman

2012-01-01

Herein we describe a high-throughput fluorescence and HPLC-based methodology for global profiling of reactive oxygen and nitrogen species (ROS/RNS) in biological systems. The combined use of HPLC and fluorescence detection is key to successful implementation and validation of this methodology. Included here are methods to specifically detect and quantitate the products formed from interaction between the ROS/RNS species and the fluorogenic probes, as follows: superoxide using hydroethidine, peroxynitrite using boronate-based probes, nitric oxide-derived nitrosating species with 4,5-diaminofluorescein, and hydrogen peroxide and other oxidants using 10-acetyl-3,7-dihydroxyphenoxazine (Amplex® Red) with and without horseradish peroxidase, respectively. In this study, we demonstrate real-time monitoring of ROS/RNS in activated macrophages using high-throughput fluorescence and HPLC methods. This global profiling approach, simultaneous detection of multiple ROS/RNS products of fluorescent probes, developed in this study will be useful in unraveling the complex role of ROS/RNS in redox regulation, cell signaling, and cellular oxidative processes and in high-throughput screening of anti-inflammatory antioxidants. PMID:22139901

Epigenetics and Epigenomics of Plants.

PubMed

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

2018-01-23

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

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

PubMed

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

2018-06-04

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

A Novel Two-Step Hierarchial Quantitative Structure-Activity Relationship Modeling Workflow for Predicting Acute Toxicity of Chemicals in Rodents

EPA Science Inventory

Background: Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Methods and results: A database co...

Use of in Vitro HTS-Derived Concentration-Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity

EPA Science Inventory

Background: Quantitative high-throughput screening (qHTS) assays are increasingly being employed to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in co...

Identifying Environmental Chemicals as Agonists of the Androgen Receptor by Applying a Quantitative High-throughput Screening Platform

EPA Science Inventory

Background: The androgen receptor (AR, NR3C4) is a nuclear receptor whose main function is acting as a transcription factor regulating gene expression for male sexual development and maintaining accessory sexual organ function. It is also a necessary component of female fertility...

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

PubMed

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

2017-07-01

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

Optimization of a resazurin-based microplate assay for large-scale compound screenings against Klebsiella pneumoniae.

PubMed

Kim, Hyung Jun; Jang, Soojin

2018-01-01

A new resazurin-based assay was evaluated and optimized using a microplate (384-well) format for high-throughput screening of antibacterial molecules against Klebsiella pneumoniae . Growth of the bacteria in 384-well plates was more effectively measured and had a > sixfold higher signal-to-background ratio using the resazurin-based assay compared with absorbance measurements at 600 nm. Determination of minimum inhibitory concentrations of the antibiotics revealed that the optimized assay quantitatively measured antibacterial activity of various antibiotics. An edge effect observed in the initial assay was significantly reduced using a 1-h incubation of the bacteria-containing plates at room temperature. There was an approximately 10% decrease in signal variability between the edge and the middle wells along with improvement in the assay robustness ( Z ' = 0.99). This optimized resazurin-based assay is an efficient, inexpensive, and robust assay that can quantitatively measure antibacterial activity using a high-throughput screening system to assess a large number of compounds for discovery of new antibiotics against K. pneumoniae .

A survey of microparasites present in adult migrating Chinook salmon (Oncorhynchus tshawytscha) in south-western British Columbia determined by high-throughput quantitative polymerase chain reaction.

PubMed

Bass, A L; Hinch, S G; Teffer, A K; Patterson, D A; Miller, K M

2017-04-01

Microparasites play an important role in the demography, ecology and evolution of Pacific salmonids. As salmon stocks continue to decline and the impacts of global climate change on fish populations become apparent, a greater understanding of microparasites in wild salmon populations is warranted. We used high-throughput, quantitative PCR (HT-qRT-PCR) to rapidly screen 82 adult Chinook salmon from five geographically or genetically distinct groups (mostly returning to tributaries of the Fraser River) for 45 microparasite taxa. We detected 20 microparasite species, four of which have not previously been documented in Chinook salmon, and four of which have not been previously detected in any salmonids in the Fraser River. Comparisons of microparasite load to blood plasma variables revealed some positive associations between Flavobacterium psychrophilum, Cryptobia salmositica and Ceratonova shasta and physiological indices suggestive of morbidity. We include a comparison of our findings for each microparasite taxa with previous knowledge of its distribution in British Columbia. © 2017 John Wiley & Sons Ltd.

Radiomics: Extracting more information from medical images using advanced feature analysis

PubMed Central

Lambin, Philippe; Rios-Velazquez, Emmanuel; Leijenaar, Ralph; Carvalho, Sara; van Stiphout, Ruud G.P.M.; Granton, Patrick; Zegers, Catharina M.L.; Gillies, Robert; Boellard, Ronald; Dekker, André; Aerts, Hugo J.W.L.

2015-01-01

Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics – the high-throughput extraction of large amounts of image features from radiographic images – addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory. PMID:22257792

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

DOE PAGES

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

2016-09-23

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

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

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

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

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

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

PubMed

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

2016-11-14

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

Development of combinatorial chemistry methods for coatings: high-throughput adhesion evaluation and scale-up of combinatorial leads.

PubMed

Potyrailo, Radislav A; Chisholm, Bret J; Morris, William G; Cawse, James N; Flanagan, William P; Hassib, Lamyaa; Molaison, Chris A; Ezbiansky, Karin; Medford, George; Reitz, Hariklia

2003-01-01

Coupling of combinatorial chemistry methods with high-throughput (HT) performance testing and measurements of resulting properties has provided a powerful set of tools for the 10-fold accelerated discovery of new high-performance coating materials for automotive applications. Our approach replaces labor-intensive steps with automated systems for evaluation of adhesion of 8 x 6 arrays of coating elements that are discretely deposited on a single 9 x 12 cm plastic substrate. Performance of coatings is evaluated with respect to their resistance to adhesion loss, because this parameter is one of the primary considerations in end-use automotive applications. Our HT adhesion evaluation provides previously unavailable capabilities of high speed and reproducibility of testing by using a robotic automation, an expanded range of types of tested coatings by using the coating tagging strategy, and an improved quantitation by using high signal-to-noise automatic imaging. Upon testing, the coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Using our HT methodology, we have developed several coatings leads. These HT screening results for the best coating compositions have been validated on the traditional scales of coating formulation and adhesion loss testing. These validation results have confirmed the superb performance of combinatorially developed coatings over conventional coatings on the traditional scale.

High-throughput metabolic stability studies in drug discovery by orthogonal acceleration time-of-flight (OATOF) with analogue-to-digital signal capture (ADC).

PubMed

Temesi, David G; Martin, Scott; Smith, Robin; Jones, Christopher; Middleton, Brian

2010-06-30

Screening assays capable of performing quantitative analysis on hundreds of compounds per week are used to measure metabolic stability during early drug discovery. Modern orthogonal acceleration time-of-flight (OATOF) mass spectrometers equipped with analogue-to-digital signal capture (ADC) now offer performance levels suitable for many applications normally supported by triple quadruple instruments operated in multiple reaction monitoring (MRM) mode. Herein the merits of MRM and OATOF with ADC detection are compared for more than 1000 compounds screened in rat and/or cryopreserved human hepatocytes over a period of 3 months. Statistical comparison of a structurally diverse subset indicated good agreement for the two detection methods. The overall success rate was higher using OATOF detection and data acquisition time was reduced by around 20%. Targeted metabolites of diazepam were detected in samples from a CLint determination performed at 1 microM. Data acquisition by positive and negative ion mode switching can be achieved on high-performance liquid chromatography (HPLC) peak widths as narrow as 0.2 min (at base), thus enabling a more comprehensive first pass analysis with fast HPLC gradients. Unfortunately, most existing OATOF instruments lack the software tools necessary to rapidly convert the huge amounts of raw data into quantified results. Software with functionality similar to open access triple quadrupole systems is needed for OATOF to truly compete in a high-throughput screening environment. Copyright 2010 John Wiley & Sons, Ltd.

A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

PubMed Central

Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

2013-01-01

Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

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

ScienceCinema

Jordan, Scott

2018-01-24

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

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

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

PubMed

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

2013-03-01

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

Monitoring the dynamics of syntrophic β-oxidizing bacteria during anaerobic degradation of oleic acid by quantitative PCR.

PubMed

Ziels, Ryan M; Beck, David A C; Martí, Magalí; Gough, Heidi L; Stensel, H David; Svensson, Bo H

2015-04-01

The ecophysiology of long-chain fatty acid-degrading syntrophic β-oxidizing bacteria has been poorly understood due to a lack of quantitative abundance data. Here, TaqMan quantitative PCR (qPCR) assays targeting the 16S rRNA gene of the known mesophilic syntrophic β-oxidizing bacterial genera Syntrophomonas and Syntrophus were developed and validated. Microbial community dynamics were followed using qPCR and Illumina-based high-throughput amplicon sequencing in triplicate methanogenic bioreactors subjected to five consecutive batch feedings of oleic acid. With repeated oleic acid feeding, the initial specific methane production rate significantly increased along with the relative abundances of Syntrophomonas and methanogenic archaea in the bioreactor communities. The novel qPCR assays showed that Syntrophomonas increased from 7 to 31% of the bacterial community 16S rRNA gene concentration, whereas that of Syntrophus decreased from 0.02 to less than 0.005%. High-throughput amplicon sequencing also revealed that Syntrophomonas became the dominant genus within the bioreactor microbiomes. These results suggest that increased specific mineralization rates of oleic acid were attributed to quantitative shifts within the microbial communities toward higher abundances of syntrophic β-oxidizing bacteria and methanogenic archaea. The novel qPCR assays targeting syntrophic β-oxidizing bacteria may thus serve as monitoring tools to indicate the fatty acid β-oxidization potential of anaerobic digester communities. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Analysis of Inorganic Nanoparticles by Single-particle Inductively Coupled Plasma Time-of-Flight Mass Spectrometry.

PubMed

Hendriks, Lyndsey; Gundlach-Graham, Alexander; Günther, Detlef

2018-04-25

Due to the rapid development of nanotechnologies, engineered nanomaterials (ENMs) and nanoparticles (ENPs) are becoming a part of everyday life: nanotechnologies are quickly migrating from laboratory benches to store shelves and industrial processes. As the use of ENPs continues to expand, their release into the environment is unavoidable; however, understanding the mechanisms and degree of ENP release is only possible through direct detection of these nanospecies in relevant matrices and at realistic concentrations. Key analytical requirements for quantitative detection of ENPs include high sensitivity to detect small particles at low total mass concentrations and the need to separate signals of ENPs from a background of dissolved elemental species and natural nanoparticles (NNPs). To this end, an emerging method called single-particle inductively coupled plasma mass spectrometry (sp-ICPMS) has demonstrated great potential for the characterization of inorganic nanoparticles (NPs) at environmentally relevant concentrations. Here, we comment on the capabilities of modern sp-ICPMS analysis with particular focus on the measurement possibilities offered by ICP-time-of-flight mass spectrometry (ICP-TOFMS). ICP-TOFMS delivers complete elemental mass spectra for individual NPs, which allows for high-throughput, untargeted quantitative analysis of dispersed NPs in natural matrices. Moreover, the multi-element detection capabilities of ICP-TOFMS enable new NP-analysis strategies, including online calibration via microdroplets for accurate NP mass quantification and matrix compensation.

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

PubMed Central

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

2015-01-01

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

Courtney E. Payne | NREL

Science.gov Websites

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

A Novel Method for Tracking Individuals of Fruit Fly Swarms Flying in a Laboratory Flight Arena.

PubMed

Cheng, Xi En; Qian, Zhi-Ming; Wang, Shuo Hong; Jiang, Nan; Guo, Aike; Chen, Yan Qiu

2015-01-01

The growing interest in studying social behaviours of swarming fruit flies, Drosophila melanogaster, has heightened the need for developing tools that provide quantitative motion data. To achieve such a goal, multi-camera three-dimensional tracking technology is the key experimental gateway. We have developed a novel tracking system for tracking hundreds of fruit flies flying in a confined cubic flight arena. In addition to the proposed tracking algorithm, this work offers additional contributions in three aspects: body detection, orientation estimation, and data validation. To demonstrate the opportunities that the proposed system offers for generating high-throughput quantitative motion data, we conducted experiments on five experimental configurations. We also performed quantitative analysis on the kinematics and the spatial structure and the motion patterns of fruit fly swarms. We found that there exists an asymptotic distance between fruit flies in swarms as the population density increases. Further, we discovered the evidence for repulsive response when the distance between fruit flies approached the asymptotic distance. Overall, the proposed tracking system presents a powerful method for studying flight behaviours of fruit flies in a three-dimensional environment.

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2016-04-01

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

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

PubMed Central

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

2010-01-01

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

A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy.

PubMed

Farr, Ryan J; Januszewski, Andrzej S; Joglekar, Mugdha V; Liang, Helena; McAulley, Annie K; Hewitt, Alex W; Thomas, Helen E; Loudovaris, Tom; Kay, Thomas W H; Jenkins, Alicia; Hardikar, Anandwardhan A

2015-06-02

MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA using a standard 96-well platform, a high-content microfluidics platform and two ultra-high content platforms. We used extensive analytical tools to compute inter- and intra-run variability and concordance measured using fidelity scoring, coefficient of variation and cluster analysis. We carried out unprejudiced next generation sequencing to identify a microRNA signature for Diabetic Retinopathy (DR) and systematically assessed the validation of this signature on clinical samples using each of the above four qPCR platforms. The results indicate that sensitivity to measure low copy number microRNAs is inversely related to qPCR reaction volume and that the choice of platform for microRNA biomarker validation should be made based on the abundance of miRNAs of interest.

Method development aspects for the quantitation of pharmaceutical compounds in human plasma with a matrix-assisted laser desorption/ionization source in the multiple reaction monitoring mode.

PubMed

Kovarik, Peter; Grivet, Chantal; Bourgogne, Emmanuel; Hopfgartner, Gérard

2007-01-01

The present work investigates various method development aspects for the quantitative analysis of pharmaceutical compounds in human plasma using matrix-assisted laser desorption/ionization and multiple reaction monitoring (MALDI-MRM). Talinolol was selected as a model analyte. Liquid-liquid extraction (LLE) and protein precipitation were evaluated regarding sensitivity and throughput for the MALDI-MRM technique and its applicability without and with chromatographic separation. Compared to classical electrospray liquid chromatography/mass spectrometry (LC/ESI-MS) method development, with MALDI-MRM the tuning of the analyte in single MS mode is more challenging due to interfering matrix background ions. An approach is proposed using background subtraction. With LLE and using a 200 microL human plasma aliquot acceptable precision and accuracy could be obtained in the range of 1 to 1000 ng/mL without any LC separation. Approximately 3 s were required for one analysis. A full calibration curve and its quality control samples (20 samples) can be analyzed within 1 min. Combining LC with the MALDI analysis allowed improving the linearity down to 50 pg/mL, while reducing the throughput potential only by two-fold. Matrix effects are still a significant issue with MALDI but can be monitored in a similar way to that used for LC/ESI-MS analysis.

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

PubMed

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

2011-01-01

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

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

PubMed

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

2014-07-08

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

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

PubMed

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

2010-02-01

The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell biology has advanced rapidly with increasing availability of new data and powerful simulation techniques, a quantitative orientation is still lacking in life sciences education to make efficient use of these new tools to implement the new toxicity testing paradigm. A revamped undergraduate curriculum in the biological sciences including compulsory courses in mathematics and analysis of dynamical systems is required to address this gap. In parallel, dissemination of computational systems biology techniques and other analytical tools among practicing toxicologists and risk assessment professionals will help accelerate implementation of the new toxicity testing vision.

Resource for the Development of Biomedical Accelerator Mass Spectrometry (AMS)

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

Tuerteltaub, K. W.; Bench, G.; Buchholz, B. A.

The NIH Research Resource for Biomedical AMS was originally funded at Lawrence Livermore National Laboratory in 1999 to develop and apply the technology of accelerator mass spectrometry (AMS) in broad- based biomedical research. The Resource’s niche is to fill needs for ultra high sensitivity quantitation when isotope-labeled agents are used. The Research Resource’s Technology Research and Development (TR&D) efforts will focus on the needs of the biomedical research community in the context of seven Driving Biomedical Projects (DBPs) that will drive the Center’s technical capabilities through three core TR&Ds. We will expand our present capabilities by developing a fully integratedmore » HPLC AMS to increase our capabilities for metabolic measurements, we will develop methods to understand cellular processes and we will develop and validate methods for the application of AMS in human studies, which is a growing area of demand by collaborators and service users. In addition, we will continue to support new and ongoing collaborative and service projects that require the capabilities of the Resource. The Center will continue to train researchers in the use of the AMS capabilities being developed, and the results of all efforts will be widely disseminated to advance progress in biomedical research. Towards these goals, our specific aims are to:1.) Increase the value and information content of AMS measurements by combining molecular speciation with quantitation of defined macromolecular isolates. Specifically, develop and validate methods for macromolecule labeling, characterization and quantitation.2.) Develop and validate methods and strategies to enable AMS to become more broadly used in human studies. Specifically, demonstrate robust methods for conducting pharmacokinetic/pharmacodynamics studies in humans and model systems.3.) Increase the accessibility of AMS to the Biomedical research community and the throughput of AMS through direct coupling to separatory instruments.4.) Provide high throughput 14C BioAMS analysis for collaborative and service clients.« less

Resource for the Development of Biomedical Accelerator Mass Spectrometry (AMS)

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

Turteltaub, K. W.; Bench, G.; Buchholz, B. A.

2016-04-08

The NIH Research Resource for Biomedical AMS was originally funded at Lawrence Livermore National Laboratory in 1999 to develop and apply the technology of accelerator mass spectrometry (AMS) in broad- based biomedical research. The Resource’s niche is to fill needs for ultra high sensitivity quantitation when isotope-labeled agents are used. The Research Resource’s Technology Research and Development (TR&D) efforts will focus on the needs of the biomedical research community in the context of seven Driving Biomedical Projects (DBPs) that will drive the Center’s technical capabilities through three core TR&Ds. We will expand our present capabilities by developing a fully integratedmore » HPLC AMS to increase our capabilities for metabolic measurements, we will develop methods to understand cellular processes and we will develop and validate methods for the application of AMS in human studies, which is a growing area of demand by collaborators and service users. In addition, we will continue to support new and ongoing collaborative and service projects that require the capabilities of the Resource. The Center will continue to train researchers in the use of the AMS capabilities being developed, and the results of all efforts will be widely disseminated to advance progress in biomedical research. Towards these goals, our specific aims are to:1.) Increase the value and information content of AMS measurements by combining molecular speciation with quantitation of defined macromolecular isolates. Specifically, develop and validate methods for macromolecule labeling, characterization and quantitation.2.) Develop and validate methods and strategies to enable AMS to become more broadly used in human studies. Specifically, demonstrate robust methods for conducting pharmacokinetic/pharmacodynamics studies in humans and model systems.3.) Increase the accessibility of AMS to the Biomedical research community and the throughput of AMS through direct coupling to separatory instruments.4.) Provide high throughput 14C BioAMS analysis for collaborative and service clients.« less

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

USDA-ARS?s Scientific Manuscript database

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

MBTH: A novel approach to rapid, spectrophotometric quantitation of total algal carbohydrates

DOE PAGES

Van Wychen, Stefanie; Long, William; Black, Stuart K.; ...

2016-11-24

A high-throughput and robust application of the 3-methyl-2-benzothiazolinone hydrazone (MBTH) method was developed for carbohydrate determination in microalgae. The traditional phenol-sulfuric acid method to quantify carbohydrates is strongly affected by algal biochemical components and exhibits a highly variable response to microalgal monosaccharides. We present a novel use of the MBTH method to accurately quantify carbohydrates in hydrolyzate after acid hydrolysis of algal biomass, without a need for neutralization. As a result, the MBTH method demonstrated consistent and sensitive quantitation of algae-specific monosaccharides down to 5 ug mL -1 without interference from other algae acidic hydrolyzate components.

MBTH: A novel approach to rapid, spectrophotometric quantitation of total algal carbohydrates

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

Van Wychen, Stefanie; Long, William; Black, Stuart K.

A high-throughput and robust application of the 3-methyl-2-benzothiazolinone hydrazone (MBTH) method was developed for carbohydrate determination in microalgae. The traditional phenol-sulfuric acid method to quantify carbohydrates is strongly affected by algal biochemical components and exhibits a highly variable response to microalgal monosaccharides. We present a novel use of the MBTH method to accurately quantify carbohydrates in hydrolyzate after acid hydrolysis of algal biomass, without a need for neutralization. As a result, the MBTH method demonstrated consistent and sensitive quantitation of algae-specific monosaccharides down to 5 ug mL -1 without interference from other algae acidic hydrolyzate components.

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

PubMed

Pelz, Oliver; Gilsdorf, Moritz; Boutros, Michael

2010-04-12

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

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

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

Xu, Zhe; Wu, Chaochao; Xie, Fang

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective andmore » robust analytical platform for comprehensive analyses of tissue peptidomes, and which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Additionally, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. In conclusion, peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.« less

Stereoselective Degradation and Molecular Ecological Mechanism of Chiral Pesticides Beta-Cypermethrin in Soils with Different pH Values.

PubMed

Yang, Zhong-Hua; Ji, Guo-Dong

2015-12-15

For decades, pesticides have been widely used for agricultural activities around the world, and the environmental problems caused by these compounds have raised widespread concern. However, the different enantioselective behaviors of chiral pesticide enantiomers are often ignored. Here, the selective degradation patterns and mechanisms of chiral pesticide enantiomers were successfully investigated for the first time in the soils of three cultivation areas with different pH values. Beta-cypermethrin was chosen as the target analyte. We found that the degradation rates of the four isomers of beta-cypermethrin were different. We used stepwise regression equations between degradation rates and functional genes to quantitatively study their relationships. Quantitative response analysis revealed that different isomers have different equations even under identical conditions. The results of path analysis showed that a single functional gene can make different direct and indirect contributions to the degradation of different isomers. Finally, the high-throughput technology was used to analysis the genome of the three tested soils and then compared the main microbial communities in them. We have successfully devised a method to investigate the molecular biological mechanisms of the selective degradation behavior of chiral compounds, thus enabling us to better understand these mechanisms.

Data processing has major impact on the outcome of quantitative label-free LC-MS analysis.

PubMed

Chawade, Aakash; Sandin, Marianne; Teleman, Johan; Malmström, Johan; Levander, Fredrik

2015-02-06

High-throughput multiplexed protein quantification using mass spectrometry is steadily increasing in popularity, with the two major techniques being data-dependent acquisition (DDA) and targeted acquisition using selected reaction monitoring (SRM). However, both techniques involve extensive data processing, which can be performed by a multitude of different software solutions. Analysis of quantitative LC-MS/MS data is mainly performed in three major steps: processing of raw data, normalization, and statistical analysis. To evaluate the impact of data processing steps, we developed two new benchmark data sets, one each for DDA and SRM, with samples consisting of a long-range dilution series of synthetic peptides spiked in a total cell protein digest. The generated data were processed by eight different software workflows and three postprocessing steps. The results show that the choice of the raw data processing software and the postprocessing steps play an important role in the final outcome. Also, the linear dynamic range of the DDA data could be extended by an order of magnitude through feature alignment and a charge state merging algorithm proposed here. Furthermore, the benchmark data sets are made publicly available for further benchmarking and software developments.

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

DOE PAGES

Xu, Zhe; Wu, Chaochao; Xie, Fang; ...

2014-10-28

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective andmore » robust analytical platform for comprehensive analyses of tissue peptidomes, and which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Additionally, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. In conclusion, peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.« less

PeptideDepot: flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information.

PubMed

Yu, Kebing; Salomon, Arthur R

2009-12-01

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post-acquisition analysis of proteomic data.

A Robotic Platform for Quantitative High-Throughput Screening

PubMed Central

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

2008-01-01

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

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

PubMed

Liu, Yun; Grossman, Jeffrey C

2014-12-10

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

Pediatric Glioblastoma Therapies Based on Patient-Derived Stem Cell Resources

DTIC Science & Technology

2014-11-01

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

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

PubMed

Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Overcoming bias and systematic errors in next generation sequencing data.

PubMed

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

2010-12-10

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

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

PubMed

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

2017-10-01

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

High Throughput Screen to Identify Novel Drugs that Inhibit Prostate Cancer Metastasis

DTIC Science & Technology

2005-10-01

mutants of the SSeCKS α promoter fused to luciferase reporter cassettes (left) were transiently expressed along with pRL-TK- renilla in either P69 or...DU145 cells, and the resulting luciferase activity was normalized to that of renilla activity. Figure 3. Semi quantitative RT-PCR of SSeCKS (either

Toxcast and the Use of Human Relevant In Vitro Exposures: Incorporating High-Throughput Exposure and Toxicity Testing Data for 21st Century Risk Assessments (British Toxicological Society Annual Congress)

EPA Science Inventory

The path for incorporating new approach methods and technologies into quantitative chemical risk assessment poses a diverse set of scientific challenges. These challenges include sufficient coverage of toxicological mechanisms to meaningfully interpret negative test results, dev...

QuASAR-MPRA: accurate allele-specific analysis for massively parallel reporter assays.

PubMed

Kalita, Cynthia A; Moyerbrailean, Gregory A; Brown, Christopher; Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

2018-03-01

The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRAs), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets. We have further developed our method for allele-specific analysis QuASAR (quantitative allele-specific analysis of reads) to analyze allele-specific signals in barcoded read counts data from MPRA. Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. The provided allelic skew estimate and its standard error also simplifies meta-analysis of replicate experiments. Additionally, we show that a beta-binomial distribution better models the variability present in the allelic imbalance of these synthetic reporters and results in a test that is statistically well calibrated under the null. Applying this approach to the MPRA data, we found 602 SNPs with significant (false discovery rate 10%) allele-specific regulatory function in LCLs. We also show that we can combine MPRA with QuASAR estimates to validate existing experimental and computational annotations of regulatory variants. Our study shows that with appropriate data analysis tools, we can improve the power to detect allelic effects in high-throughput reporter assays. http://github.com/piquelab/QuASAR/tree/master/mpra. fluca@wayne.edu or rpique@wayne.edu. Supplementary data are available online at Bioinformatics. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

PubMed Central

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

2016-01-01

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

Methods, Tools and Current Perspectives in Proteogenomics *

PubMed Central

Ruggles, Kelly V.; Krug, Karsten; Wang, Xiaojing; Clauser, Karl R.; Wang, Jing; Payne, Samuel H.; Fenyö, David; Zhang, Bing; Mani, D. R.

2017-01-01

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications. PMID:28456751

Ultrasensitive Single Fluorescence-Labeled Probe-Mediated Single Universal Primer-Multiplex-Droplet Digital Polymerase Chain Reaction for High-Throughput Genetically Modified Organism Screening.

PubMed

Niu, Chenqi; Xu, Yuancong; Zhang, Chao; Zhu, Pengyu; Huang, Kunlun; Luo, Yunbo; Xu, Wentao

2018-05-01

As genetically modified (GM) technology develops and genetically modified organisms (GMOs) become more available, GMOs face increasing regulations and pressure to adhere to strict labeling guidelines. A singleplex detection method cannot perform the high-throughput analysis necessary for optimal GMO detection. Combining the advantages of multiplex detection and droplet digital polymerase chain reaction (ddPCR), a single universal primer-multiplex-ddPCR (SUP-M-ddPCR) strategy was proposed for accurate broad-spectrum screening and quantification. The SUP increases efficiency of the primers in PCR and plays an important role in establishing a high-throughput, multiplex detection method. Emerging ddPCR technology has been used for accurate quantification of nucleic acid molecules without a standard curve. Using maize as a reference point, four heterologous sequences ( 35S, NOS, NPTII, and PAT) were selected to evaluate the feasibility and applicability of this strategy. Surprisingly, these four genes cover more than 93% of the transgenic maize lines and serve as preliminary screening sequences. All screening probes were labeled with FAM fluorescence, which allows the signals from the samples with GMO content and those without to be easily differentiated. This fiveplex screening method is a new development in GMO screening. Utilizing an optimal amplification assay, the specificity, limit of detection (LOD), and limit of quantitation (LOQ) were validated. The LOD and LOQ of this GMO screening method were 0.1% and 0.01%, respectively, with a relative standard deviation (RSD) < 25%. This method could serve as an important tool for the detection of GM maize from different processed, commercially available products. Further, this screening method could be applied to other fields that require reliable and sensitive detection of DNA targets.

Phenotypic approaches to drought in cassava: review

PubMed Central

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

2012-01-01

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

A high-throughput microfluidic dental plaque biofilm system to visualize and quantify the effect of antimicrobials

PubMed Central

Nance, William C.; Dowd, Scot E.; Samarian, Derek; Chludzinski, Jeffrey; Delli, Joseph; Battista, John; Rickard, Alexander H.

2013-01-01

Objectives Few model systems are amenable to developing multi-species biofilms in parallel under environmentally germane conditions. This is a problem when evaluating the potential real-world effectiveness of antimicrobials in the laboratory. One such antimicrobial is cetylpyridinium chloride (CPC), which is used in numerous over-the-counter oral healthcare products. The aim of this work was to develop a high-throughput microfluidic system that is combined with a confocal laser scanning microscope (CLSM) to quantitatively evaluate the effectiveness of CPC against oral multi-species biofilms grown in human saliva. Methods Twenty-four-channel BioFlux microfluidic plates were inoculated with pooled human saliva and fed filter-sterilized saliva for 20 h at 37°C. The bacterial diversity of the biofilms was evaluated by bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). The antimicrobial/anti-biofilm effect of CPC (0.5%–0.001% w/v) was examined using Live/Dead stain, CLSM and 3D imaging software. Results The analysis of biofilms by bTEFAP demonstrated that they contained genera typically found in human dental plaque. These included Aggregatibacter, Fusobacterium, Neisseria, Porphyromonas, Streptococcus and Veillonella. Using Live/Dead stain, clear gradations in killing were observed when the biofilms were treated with CPC between 0.5% and 0.001% w/v. At 0.5% (w/v) CPC, 90% of the total signal was from dead/damaged cells. Below this concentration range, less killing was observed. In the 0.5%–0.05% (w/v) range CPC penetration/killing was greatest and biofilm thickness was significantly reduced. Conclusions This work demonstrates the utility of a high-throughput microfluidic–CLSM system to grow multi-species oral biofilms, which are compositionally similar to naturally occurring biofilms, to assess the effectiveness of antimicrobials. PMID:23800904

High throughput, cell type-specific analysis of key proteins in human endometrial biopsies of women from fertile and infertile couples

PubMed Central

Leach, Richard E.; Jessmon, Philip; Coutifaris, Christos; Kruger, Michael; Myers, Evan R.; Ali-Fehmi, Rouba; Carson, Sandra A.; Legro, Richard S.; Schlaff, William D.; Carr, Bruce R.; Steinkampf, Michael P.; Silva, Susan; Leppert, Phyllis C.; Giudice, Linda; Diamond, Michael P.; Armant, D. Randall

2012-01-01

BACKGROUND Although histological dating of endometrial biopsies provides little help for prediction or diagnosis of infertility, analysis of individual endometrial proteins, proteomic profiling and transcriptome analysis have suggested several biomarkers with altered expression arising from intrinsic abnormalities, inadequate stimulation by or in response to gonadal steroids or altered function due to systemic disorders. The objective of this study was to delineate the developmental dynamics of potentially important proteins in the secretory phase of the menstrual cycle, utilizing a collection of endometrial biopsies from women of fertile (n = 89) and infertile (n = 89) couples. METHODS AND RESULTS Progesterone receptor-B (PGR-B), leukemia inhibitory factor, glycodelin/progestagen-associated endometrial protein (PAEP), homeobox A10, heparin-binding EGF-like growth factor, calcitonin and chemokine ligand 14 (CXCL14) were measured using a high-throughput, quantitative immunohistochemical method. Significant cyclic and tissue-specific regulation was documented for each protein, as well as their dysregulation in women of infertile couples. Infertile patients demonstrated a delay early in the secretory phase in the decline of PGR-B (P < 0.05) and premature mid-secretory increases in PAEP (P < 0.05) and CXCL14 (P < 0.05), suggesting that the implantation interval could be closing early. Correlation analysis identified potential interactions among certain proteins that were disrupted by infertility. CONCLUSIONS This approach overcomes the limitations of a small sample number. Protein expression and localization provided important insights into the potential roles of these proteins in normal and pathological development of the endometrium that is not attainable from transcriptome analysis, establishing a basis for biomarker, diagnostic and targeted drug development for women with infertility. PMID:22215622

Immediate drop on demand technology (I-DOT) coupled with mass spectrometry via an open port sampling interface.

PubMed

Van Berkel, Gary J; Kertesz, Vilmos; Boeltz, Harry

2017-11-01

The aim of this work was to demonstrate and evaluate the analytical performance of coupling the immediate drop on demand technology to a mass spectrometer via the recently introduced open port sampling interface and ESI. Methodology & results: A maximum sample analysis throughput of 5 s per sample was demonstrated. Signal reproducibility was 10% or better as demonstrated by the quantitative analysis of propranolol and its stable isotope-labeled internal standard propranolol-d7. The ability of the system to multiply charge and analyze macromolecules was demonstrated using the protein cytochrome c. This immediate drop on demand technology/open port sampling interface/ESI-MS combination allowed for the quantitative analysis of relatively small mass analytes and was used for the identification of macromolecules like proteins.

A rapid quantitative analysis of bile acids, lysophosphatidylcholines and polyunsaturated fatty acids in biofluids based on ultraperformance liquid chromatography coupled with triple quadrupole tandem massspectrometry.

PubMed

Peng, Zhangxiao; Zhang, Qian; Mao, Ziming; Wang, Jie; Liu, Chunying; Lin, Xuejing; Li, Xin; Ji, Weidan; Fan, Jianhui; Wang, Maorong; Su, Changqing

2017-11-15

Much evidence suggested that quantitative analysis of bile acids (BAs), lysophosphatidylcholines (LPCs), and polyunsaturated fatty acids (PUFAs) in biofluids may be very useful for diagnosis and prevention of hepatobiliary disease with a non-invasive manner. However, simultaneously fast analysis of these metabolites has been challenging for their huge differences of physicochemical properties and concentration levels in biofluids. In this study, we present a liquid chromatography-mass spectrometry method with a high throughput analytical cycle (10min) to fast and accurately quantify fifteen potential biomarkers (eight BAs, four LPCs and three PUFAs) of hepatobiliary disease. The accuracy for the fifteen analytes in plasma and urine matrices was 80.45%-118.99% and 84.55%-112.66%, respectively. The intra- and inter- precisions for the fifteen analytes in plasma and urine matrices were all less than 20% and the lower limit of quantification (LLOQ) of analytes is up to 0.0283-8.2172nmol/L. Therefore, this method is fast, sensitive and accurate for the quantitative analysis of BAs, LPCs and PUFAs in biofluids. Moreover, the stability and concentration differences of the analytes in plasma and serum were evaluated, and the results demonstrated that LPCs is stable, but PUFAs is very unstable in freeze and thaw cycles, and the concentrations of the analytes in serum were slightly higher than those in plasma. We suggested plasma may be a kind of better bio-sample than serum using for quantitative analysis of metabolites in blood, due to the characteristics of plasma are more close to blood than those of serum. Copyright © 2017 Elsevier B.V. All rights reserved.

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

USDA-ARS?s Scientific Manuscript database

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

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

Cancer.gov

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

The application of multiple reaction monitoring and multi-analyte profiling to HDL proteins

PubMed Central

2014-01-01

Background HDL carries a rich protein cargo and examining HDL protein composition promises to improve our understanding of its functions. Conventional mass spectrometry methods can be lengthy and difficult to extend to large populations. In addition, without prior enrichment of the sample, the ability of these methods to detect low abundance proteins is limited. Our objective was to develop a high-throughput approach to examine HDL protein composition applicable to diabetes and cardiovascular disease (CVD). Methods We optimized two multiplexed assays to examine HDL proteins using a quantitative immunoassay (Multi-Analyte Profiling- MAP) and mass spectrometric-based quantitative proteomics (Multiple Reaction Monitoring-MRM). We screened HDL proteins using human xMAP (90 protein panel) and MRM (56 protein panel). We extended the application of these two methods to HDL isolated from a group of participants with diabetes and prior cardiovascular events and a group of non-diabetic controls. Results We were able to quantitate 69 HDL proteins using MAP and 32 proteins using MRM. For several common proteins, the use of MRM and MAP was highly correlated (p < 0.01). Using MAP, several low abundance proteins implicated in atherosclerosis and inflammation were found on HDL. On the other hand, MRM allowed the examination of several HDL proteins not available by MAP. Conclusions MAP and MRM offer a sensitive and high-throughput approach to examine changes in HDL proteins in diabetes and CVD. This approach can be used to measure the presented HDL proteins in large clinical studies. PMID:24397693

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

PubMed Central

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

2014-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Qualitative and quantitative measurement of cannabinoids in cannabis using modified HPLC/DAD method.

PubMed

Patel, Bhupendra; Wene, Daniel; Fan, Zhihua Tina

2017-11-30

This study presents an accurate and high throughput method for the quantitative determination of various cannabinoids in cannabis plant material using high pressure liquid chromatography (HPLC) with a diode array detector (DAD). Sample extraction and chromatographic analysis conditions for the measurement of cannabinoids in the complex cannabis plant material matrix were optimized. The Agilent Poroshell 120 SB-C18 column provided high resolution for all target analytes with a short run time (10minutes) given the core shell technology. The aqueous buffer mobile phase was optimized with ammonium acetate at pH 4.75. The change in the mobile phase and the new column ensured a separation between cannabidiol (CBD and cannabigerol (CBG) along with cannabigerol and tetrahydrocannabinolic acid (THCA), which were not well separated by previous publications, improved buffering capacity, and provided analytical performance stability. Moreover, baseline drifting was significantly minimized by the use of a low concentration buffer solution (25mM ammonium acetate). In addition, evaporation and reconstitution of the sample residue with a methanol-organic pure (OP) water solution (65:35) significantly reduced the matrix interference. The modified extraction produced good recoveries (>91%) for each of the eight cannabinoids. The optimized method was validated for specificity, linearity, sensitivity, precision, accuracy, and stability. The combined relative standard deviation (%RSD) for intra-day and inter-day precision for all eight analytes varied from 2.5% to 5.2% and 0.28% to 5.5%, respectively. The %RSD for the repeatability study varied from 1.1% to 5.5%. The recoveries from spiked cannabis matrix samples were greater than 90% for all analytes, except delta-8-tetrahydrocannabinol (Δ 8 -THC), which was 80%. The recoveries varied from 81% to 107% with a precision of 0.7-8.1%RSD. Delta-9-tetrahydrocannabinol (Δ 9 -THC) in all of the cannabis samples (n=635) was less than 10%, which is in compliance with the NJ Medicinal Marijuana regulation. Analysis of samples from two cultivars, which included ten individual samples, four composite samples, seven calibration standards, and four quality control standards, can be performed within 24hours by this high throughput method. Published by Elsevier B.V.

Serial analysis of gene expression identifies connective tissue growth factor expression as a prognostic biomarker in gallbladder cancer.

PubMed

Alvarez, Hector; Corvalan, Alejandro; Roa, Juan C; Argani, Pedram; Murillo, Francisco; Edwards, Jennifer; Beaty, Robert; Feldmann, Georg; Hong, Seung-Mo; Mullendore, Michael; Roa, Ivan; Ibañez, Luis; Pimentel, Fernando; Diaz, Alfonso; Riggins, Gregory J; Maitra, Anirban

2008-05-01

Gallbladder cancer (GBC) is an uncommon neoplasm in the United States, but one with high mortality rates. This malignancy remains largely understudied at the molecular level such that few targeted therapies or predictive biomarkers exist. We built the first series of serial analysis of gene expression (SAGE) libraries from GBC and nonneoplastic gallbladder mucosa, composed of 21-bp long-SAGE tags. SAGE libraries were generated from three stage-matched GBC patients (representing Hispanic/Latino, Native American, and Caucasian ethnicities, respectively) and one histologically alithiasic gallbladder. Real-time quantitative PCR was done on microdissected epithelium from five matched GBC and corresponding nonneoplastic gallbladder mucosa. Immunohistochemical analysis was done on a panel of 182 archival GBC in high-throughput tissue microarray format. SAGE tags corresponding to connective tissue growth factor (CTGF) transcripts were identified as differentially overexpressed in all pairwise comparisons of GBC (P < 0.001). Real-time quantitative PCR confirmed significant overexpression of CTGF transcripts in microdissected primary GBC (P < 0.05), but not in metastatic GBC, compared with nonneoplastic gallbladder epithelium. By immunohistochemistry, 66 of 182 (36%) GBC had high CTGF antigen labeling, which was significantly associated with better survival on univariate analysis (P = 0.0069, log-rank test). An unbiased analysis of the GBC transcriptome by SAGE has identified CTGF expression as a predictive biomarker of favorable prognosis in this malignancy. The SAGE libraries from GBC and nonneoplastic gallbladder mucosa are publicly available at the Cancer Genome Anatomy Project web site and should facilitate much needed research into this lethal neoplasm.

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

PubMed

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

2017-08-01

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

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

PubMed Central

JR, Luft; EH, Snell; GT, DeTitta

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Zhu, Chenggang; Fei, Yiyan; Zhu, Xiangdong

2017-02-01

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