Molecular profiling of single circulating tumor cells from lung cancer patients.

PubMed

Park, Seung-Min; Wong, Dawson J; Ooi, Chin Chun; Kurtz, David M; Vermesh, Ophir; Aalipour, Amin; Suh, Susie; Pian, Kelsey L; Chabon, Jacob J; Lee, Sang Hun; Jamali, Mehran; Say, Carmen; Carter, Justin N; Lee, Luke P; Kuschner, Ware G; Schwartz, Erich J; Shrager, Joseph B; Neal, Joel W; Wakelee, Heather A; Diehn, Maximilian; Nair, Viswam S; Wang, Shan X; Gambhir, Sanjiv S

2016-12-27

Circulating tumor cells (CTCs) are established cancer biomarkers for the "liquid biopsy" of tumors. Molecular analysis of single CTCs, which recapitulate primary and metastatic tumor biology, remains challenging because current platforms have limited throughput, are expensive, and are not easily translatable to the clinic. Here, we report a massively parallel, multigene-profiling nanoplatform to compartmentalize and analyze hundreds of single CTCs. After high-efficiency magnetic collection of CTC from blood, a single-cell nanowell array performs CTC mutation profiling using modular gene panels. Using this approach, we demonstrated multigene expression profiling of individual CTCs from non-small-cell lung cancer (NSCLC) patients with remarkable sensitivity. Thus, we report a high-throughput, multiplexed strategy for single-cell mutation profiling of individual lung cancer CTCs toward minimally invasive cancer therapy prediction and disease monitoring.

20180311 - Differential Gene Expression and Concentration-Response Modeling Workflow for High-Throughput Transcriptomic (HTTr) Data: Results From MCF7 Cells (SOT)

EPA Science Inventory

Increasing efficiency and declining cost of generating whole transcriptome profiles has made high-throughput transcriptomics a practical option for chemical bioactivity screening. The resulting data output provides information on the expression of thousands of genes and is amenab...

Differential Gene Expression and Concentration-Response Modeling Workflow for High-Throughput Transcriptomic (HTTr) Data: Results From MCF7 Cells

EPA Science Inventory

Increasing efficiency and declining cost of generating whole transcriptome profiles has made high-throughput transcriptomics a practical option for chemical bioactivity screening. The resulting data output provides information on the expression of thousands of genes and is amenab...

Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening

EPA Science Inventory

The EPA ToxCast research program uses high throughput screening for bioactivity profiling and predicting the toxicity of large numbers of chemicals. ToxCast Phase‐I tested 309 well‐characterized chemicals in over 500 assays for a wide range of molecular targets and cellular respo...

Selecting the most appropriate time points to profile in high-throughput studies

PubMed Central

Kleyman, Michael; Sefer, Emre; Nicola, Teodora; Espinoza, Celia; Chhabra, Divya; Hagood, James S; Kaminski, Naftali; Ambalavanan, Namasivayam; Bar-Joseph, Ziv

2017-01-01

Biological systems are increasingly being studied by high throughput profiling of molecular data over time. Determining the set of time points to sample in studies that profile several different types of molecular data is still challenging. Here we present the Time Point Selection (TPS) method that solves this combinatorial problem in a principled and practical way. TPS utilizes expression data from a small set of genes sampled at a high rate. As we show by applying TPS to study mouse lung development, the points selected by TPS can be used to reconstruct an accurate representation for the expression values of the non selected points. Further, even though the selection is only based on gene expression, these points are also appropriate for representing a much larger set of protein, miRNA and DNA methylation changes over time. TPS can thus serve as a key design strategy for high throughput time series experiments. Supporting Website: www.sb.cs.cmu.edu/TPS DOI: http://dx.doi.org/10.7554/eLife.18541.001 PMID:28124972

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

EPA Science Inventory

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

High Throughput Prioritization for Integrated Toxicity Testing Based on ToxCast Chemical Profiling

EPA Science Inventory

The rational prioritization of chemicals for integrated toxicity testing is a central goal of the U.S. EPA’s ToxCast™ program (http://epa.gov/ncct/toxcast/). ToxCast includes a wide-ranging battery of over 500 in vitro high-throughput screening assays which in Phase I was used to...

Evaluation of High-throughput Genotoxicity Assays Used in Profiling the US EPA ToxCast Chemicals

EPA Science Inventory

Three high-throughput screening (HTS) genotoxicity assays-GreenScreen HC GADD45a-GFP (Gentronix Ltd.), CellCiphr p53 (Cellumen Inc.) and CellSensor p53RE-bla (Invitrogen Corp.)-were used to analyze the collection of 320 predominantly pesticide active compounds being tested in Pha...

Use of Threshold of Toxicological Concern (TTC) with High Throughput Exposure Predictions as a Risk-Based Screening Approach of Several Thousand Commodity Chemicals (SOT Poster)

EPA Science Inventory

Although progress has been made with HTS (high throughput screening) in profiling biological activity (e.g., EPA’s ToxCast™), challenges arise interpreting HTS results in the context of adversity & converting HTS assay concentrations to equivalent human doses for the broad domain...

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

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.

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

PubMed

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

2007-12-01

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

Computational challenges, tools and resources for analyzing co- and post-transcriptional events in high throughput

PubMed Central

Bahrami-Samani, Emad; Vo, Dat T.; de Araujo, Patricia Rosa; Vogel, Christine; Smith, Andrew D.; Penalva, Luiz O. F.; Uren, Philip J.

2014-01-01

Co- and post-transcriptional regulation of gene expression is complex and multi-faceted, spanning the complete RNA lifecycle from genesis to decay. High-throughput profiling of the constituent events and processes is achieved through a range of technologies that continue to expand and evolve. Fully leveraging the resulting data is non-trivial, and requires the use of computational methods and tools carefully crafted for specific data sources and often intended to probe particular biological processes. Drawing upon databases of information pre-compiled by other researchers can further elevate analyses. Within this review, we describe the major co- and post-transcriptional events in the RNA lifecycle that are amenable to high-throughput profiling. We place specific emphasis on the analysis of the resulting data, in particular the computational tools and resources available, as well as looking towards future challenges that remain to be addressed. PMID:25515586

Comprehensive analysis of the T-cell receptor beta chain gene in rhesus monkey by high throughput sequencing

PubMed Central

Li, Zhoufang; Liu, Guangjie; Tong, Yin; Zhang, Meng; Xu, Ying; Qin, Li; Wang, Zhanhui; Chen, Xiaoping; He, Jiankui

2015-01-01

Profiling immune repertoires by high throughput sequencing enhances our understanding of immune system complexity and immune-related diseases in humans. Previously, cloning and Sanger sequencing identified limited numbers of T cell receptor (TCR) nucleotide sequences in rhesus monkeys, thus their full immune repertoire is unknown. We applied multiplex PCR and Illumina high throughput sequencing to study the TCRβ of rhesus monkeys. We identified 1.26 million TCRβ sequences corresponding to 643,570 unique TCRβ sequences and 270,557 unique complementarity-determining region 3 (CDR3) gene sequences. Precise measurements of CDR3 length distribution, CDR3 amino acid distribution, length distribution of N nucleotide of junctional region, and TCRV and TCRJ gene usage preferences were performed. A comprehensive profile of rhesus monkey immune repertoire might aid human infectious disease studies using rhesus monkeys. PMID:25961410

The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome.

PubMed

Kronewitter, Scott R; An, Hyun Joo; de Leoz, Maria Lorna; Lebrilla, Carlito B; Miyamoto, Suzanne; Leiserowitz, Gary S

2009-06-01

Annotation of the human serum N-linked glycome is a formidable challenge but is necessary for disease marker discovery. A new theoretical glycan library was constructed and proposed to provide all possible glycan compositions in serum. It was developed based on established glycobiology and retrosynthetic state-transition networks. We find that at least 331 compositions are possible in the serum N-linked glycome. By pairing the theoretical glycan mass library with a high mass accuracy and high-resolution MS, human serum glycans were effectively profiled. Correct isotopic envelope deconvolution to monoisotopic masses and the high mass accuracy instruments drastically reduced the amount of false composition assignments. The high throughput capacity enabled by this library permitted the rapid glycan profiling of large control populations. With the use of the library, a human serum glycan mass profile was developed from 46 healthy individuals. This paper presents a theoretical N-linked glycan mass library that was used for accurate high-throughput human serum glycan profiling. Rapid methods for evaluating a patient's glycome are instrumental for studying glycan-based markers.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

PubMed

Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister

2014-05-01

The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

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.

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism.

PubMed

Nemenman, Ilya; Escola, G Sean; Hlavacek, William S; Unkefer, Pat J; Unkefer, Clifford J; Wall, Michael E

2007-12-01

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For benchmarking purposes, we generate synthetic metabolic profiles based on a well-established model for red blood cell metabolism. A variety of data sets are generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We use ARACNE, a mainstream algorithm for reverse engineering of transcriptional regulatory networks from gene expression data, to predict metabolic interactions from these data sets. We find that the performance of ARACNE on metabolic data is comparable to that on gene expression data.

Zebrafish Behavioral Profiling Links Drugs to Biological Targets and Rest/Wake Regulation

PubMed Central

Rihel, Jason; Prober, David A.; Arvanites, Anthony; Lam, Kelvin; Zimmerman, Steven; Jang, Sumin; Haggarty, Stephen J.; Kokel, David; Rubin, Lee L.; Peterson, Randall T.; Schier, Alexander F.

2010-01-01

A major obstacle for the discovery of psychoactive drugs is the inability to predict how small molecules will alter complex behaviors. We report the development and application of a high-throughput, quantitative screen for drugs that alter the behavior of larval zebrafish. We found that the multi-dimensional nature of observed phenotypes enabled the hierarchical clustering of molecules according to shared behaviors. Behavioral profiling revealed conserved functions of psychotropic molecules and predicted the mechanisms of action of poorly characterized compounds. In addition, behavioral profiling implicated new factors such as ether-a-go-go-related gene (ERG) potassium channels and immunomodulators in the control of rest and locomotor activity. These results demonstrate the power of high-throughput behavioral profiling in zebrafish to discover and characterize psychotropic drugs and to dissect the pharmacology of complex behaviors. PMID:20075256

Pathway Profiling and Tissue Modeling of Developmental Toxicity

EPA Science Inventory

High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...

Diffraction efficiency of radially-profiled off-plane reflection gratings

NASA Astrophysics Data System (ADS)

Miles, Drew M.; Tutt, James H.; DeRoo, Casey T.; Marlowe, Hannah; Peterson, Thomas J.; McEntaffer, Randall L.; Menz, Benedikt; Burwitz, Vadim; Hartner, Gisela; Laubis, Christian; Scholze, Frank

2015-09-01

Future X-ray missions will require gratings with high throughput and high spectral resolution. Blazed off-plane reflection gratings are capable of meeting these demands. A blazed grating profile optimizes grating efficiency, providing higher throughput to one side of zero-order on the arc of diffraction. This paper presents efficiency measurements made in the 0.3 - 1.5 keV energy band at the Physikalisch-Technische Bundesanstalt (PTB) BESSY II facility for three holographically-ruled gratings, two of which are blazed. Each blazed grating was tested in both the Littrow configuration and anti-Littrow configuration in order to test the alignment sensitivity of these gratings with regard to throughput. This paper outlines the procedure of the grating experiment performed at BESSY II and discuss the resulting efficiency measurements across various energies. Experimental results are generally consistent with theory and demonstrate that the blaze does increase throughput to one side of zero-order. However, the total efficiency of the non-blazed, sinusoidal grating is greater than that of the blazed gratings, which suggests that the method of manufacturing these blazed profiles fails to produce facets with the desired level of precision. Finally, evidence of a successful blaze implementation from first diffraction results of prototype blazed gratings produce via a new fabrication technique at the University of Iowa are presented.

Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

An enzyme-mediated protein-fragment complementation assay for substrate screening of sortase A.

PubMed

Li, Ning; Yu, Zheng; Ji, Qun; Sun, Jingying; Liu, Xiao; Du, Mingjuan; Zhang, Wei

2017-04-29

Enzyme-mediated protein conjugation has gained great attention recently due to the remarkable site-selectivity and mild reaction condition affected by the nature of enzyme. Among all sorts of enzymes reported, sortase A from Staphylococcus aureus (SaSrtA) is the most popular enzyme due to its selectivity and well-demonstrated applications. Position scanning has been widely applied to understand enzyme substrate specificity, but the low throughput of chemical synthesis of peptide substrates and analytical methods (HPLC, LC-ESI-MS) have been the major hurdle to fully decode enzyme substrate profile. We have developed a simple high-throughput substrate profiling method to reveal novel substrates of SaSrtA 7M, a widely used hyperactive peptide ligase, by modified protein-fragment complementation assay (PCA). A small library targeting the LPATG motif recognized by SaSrtA 7M was generated and screened against proteins carrying N-terminal glycine. Using this method, we have confirmed all currently known substrates of the enzyme, and moreover identified some previously unknown substrates with varying activities. The method provides an easy, fast and highly-sensitive way to determine substrate profile of a peptide ligase in a high-throughput manner. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

Bray, Mark-Anthony; Carpenter, Anne E

2015-11-04

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

Quantitative Assessment of RNA-Protein Interactions with High Throughput Sequencing - RNA Affinity Profiling (HiTS-RAP)

PubMed Central

Ozer, Abdullah; Tome, Jacob M.; Friedman, Robin C.; Gheba, Dan; Schroth, Gary P.; Lis, John T.

2016-01-01

Because RNA-protein interactions play a central role in a wide-array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the High Throughput Sequencing-RNA Affinity Profiling (HiTS-RAP) assay, which couples sequencing on an Illumina GAIIx with the quantitative assessment of one or several proteins’ interactions with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of EGFP and NELF-E proteins with their corresponding canonical and mutant RNA aptamers. Here, we provide a detailed protocol for HiTS-RAP, which can be completed in about a month (8 days hands-on time) including the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, high-throughput sequencing and protein binding with GAIIx, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, RNA-MaP and RBNS. A successful HiTS-RAP experiment provides the sequence and binding curves for approximately 200 million RNAs in a single experiment. PMID:26182240

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.

Species-specific predictive models of developmental toxicity using the ToxCast chemical library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive models that correlate with observed in vivo toxicity. In vitro profiling methods are based on ToxCast data, consisting of over 600 high-throughput screening (HTS) and high-content sc...

ToxCast: Using high throughput screening to identify profiles of biological activity

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Applications of high throughput screening to identify profiles of biological activity

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

Identification of Potential Chemical Carcinogens in Compendia of Gene Expression Profiles

EPA Science Inventory

Chemicals induce cancer through partially characterized adverse outcome pathways (AOPs) that include molecular initiating events (MIEs) and downstream key events (KEs). Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput form...

Microfluidic-SANS: insitu molecular insight into complex fluid processing and high throughput characterisation

NASA Astrophysics Data System (ADS)

Lopez, Carlos; Watanabe, Takaichi; Cabral, Joao; Graham, Peter; Porcar, Lionel; Martel, Anne

2014-03-01

The coupling of microfluidics and small angle neutron scattering (SANS) is successfully demonstrated for the first time. We have developed novel microdevices with suitably low SANS background and high pressure compatibility for the investigation of flow-induced phenomena and high throughput phase mapping of complex fluids. We successfully obtained scattering profiles from 50 micron channels, in 10s - 100s second acquisition times. The microfluidic geometry enables the variation of both flow type and magnitude, beyond traditional rheo-SANS setups, and is exceptionally well-suited for complex fluids due to the commensurability of relevant time and lengthscales. We demonstrate our approach by studying model flow responsive systems, including surfactant/co-surfactant/water mixtures, with well-known equilibrium phase behaviour,: sodium dodecyl sulfate (SDS)/octanol/brine, cetyltrimethyl ammonium chloride (C16TAC)/pentanol/water and a model microemulsion system (C10E4 /decane/ D20), as well as polyelectrolyte solutions. Finally, using an online micromixer we are able to implement a high throughput approach, scanning in excess of 10 scattering profiles/min for a continuous aqueous surfactant dilution over two decades in concentration.

A high-throughput approach to profile RNA structure.

PubMed

Delli Ponti, Riccardo; Marti, Stefanie; Armaos, Alexandros; Tartaglia, Gian Gaetano

2017-03-17

Here we introduce the Computational Recognition of Secondary Structure (CROSS) method to calculate the structural profile of an RNA sequence (single- or double-stranded state) at single-nucleotide resolution and without sequence length restrictions. We trained CROSS using data from high-throughput experiments such as Selective 2΄-Hydroxyl Acylation analyzed by Primer Extension (SHAPE; Mouse and HIV transcriptomes) and Parallel Analysis of RNA Structure (PARS; Human and Yeast transcriptomes) as well as high-quality NMR/X-ray structures (PDB database). The algorithm uses primary structure information alone to predict experimental structural profiles with >80% accuracy, showing high performances on large RNAs such as Xist (17 900 nucleotides; Area Under the ROC Curve AUC of 0.75 on dimethyl sulfate (DMS) experiments). We integrated CROSS in thermodynamics-based methods to predict secondary structure and observed an increase in their predictive power by up to 30%. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Applications of high throughput screening to identify profiles of biological activity relevant to carcinogenesis

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

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

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

Industrializing electrophysiology: HT automated patch clamp on SyncroPatch® 96 using instant frozen cells.

PubMed

Polonchuk, Liudmila

2014-01-01

Patch-clamping is a powerful technique for investigating the ion channel function and regulation. However, its low throughput hampered profiling of large compound series in early drug development. Fortunately, automation has revolutionized the area of experimental electrophysiology over the past decade. Whereas the first automated patch-clamp instruments using the planar patch-clamp technology demonstrated rather a moderate throughput, few second-generation automated platforms recently launched by various companies have significantly increased ability to form a high number of high-resistance seals. Among them is SyncroPatch(®) 96 (Nanion Technologies GmbH, Munich, Germany), a fully automated giga-seal patch-clamp system with the highest throughput on the market. By recording from up to 96 cells simultaneously, the SyncroPatch(®) 96 allows to substantially increase throughput without compromising data quality. This chapter describes features of the innovative automated electrophysiology system and protocols used for a successful transfer of the established hERG assay to this high-throughput automated platform.

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

PubMed

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

2015-08-21

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

High throughput and miniaturised systems for biodegradability assessments.

PubMed

Cregut, Mickael; Jouanneau, Sulivan; Brillet, François; Durand, Marie-José; Sweetlove, Cyril; Chenèble, Jean-Charles; L'Haridon, Jacques; Thouand, Gérald

2014-01-01

The society demands safer products with a better ecological profile. Regulatory criteria have been developed to prevent risks for human health and the environment, for example, within the framework of the European regulation REACH (Regulation (EC) No 1907, 2006). This has driven industry to consider the development of high throughput screening methodologies for assessing chemical biodegradability. These new screening methodologies must be scalable for miniaturisation, reproducible and as reliable as existing procedures for enhanced biodegradability assessment. Here, we evaluate two alternative systems that can be scaled for high throughput screening and conveniently miniaturised to limit costs in comparison with traditional testing. These systems are based on two dyes as follows: an invasive fluorescent dyes that serves as a cellular activity marker (a resazurin-like dye reagent) and a noninvasive fluorescent oxygen optosensor dye (an optical sensor). The advantages and limitations of these platforms for biodegradability assessment are presented. Our results confirm the feasibility of these systems for evaluating and screening chemicals for ready biodegradability. The optosensor is a miniaturised version of a component already used in traditional ready biodegradability testing, whereas the resazurin dye offers an interesting new screening mechanism for chemical concentrations greater than 10 mg/l that are not amenable to traditional closed bottle tests. The use of these approaches allows generalisation of high throughput screening methodologies to meet the need of developing new compounds with a favourable ecological profile and also assessment for regulatory purpose.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets.

PubMed

Filzen, Tracey M; Kutchukian, Peter S; Hermes, Jeffrey D; Li, Jing; Tudor, Matthew

2017-02-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Representing high throughput expression profiles via perturbation barcodes reveals compound targets

PubMed Central

Kutchukian, Peter S.; Li, Jing; Tudor, Matthew

2017-01-01

High throughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound’s high throughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data. PMID:28182661

High throughput 16SrRNA gene sequencing reveals the correlation between Propionibacterium acnes and sarcoidosis.

PubMed

Zhao, Meng-Meng; Du, Shan-Shan; Li, Qiu-Hong; Chen, Tao; Qiu, Hui; Wu, Qin; Chen, Shan-Shan; Zhou, Ying; Zhang, Yuan; Hu, Yang; Su, Yi-Liang; Shen, Li; Zhang, Fen; Weng, Dong; Li, Hui-Ping

2017-02-01

This study aims to use high throughput 16SrRNA gene sequencing to examine the bacterial profile of lymph node biopsy samples of patients with sarcoidosis and to further verify the association between Propionibacterium acnes (P. acnes) and sarcoidosis. A total of 36 mediastinal lymph node biopsy specimens were collected from 17 cases of sarcoidosis, 8 tuberculosis (TB group), and 11 non-infectious lung diseases (control group). The V4 region of the bacterial 16SrRNA gene in the specimens was amplified and sequenced using the high throughput sequencing platform MiSeq, and bacterial profile was established. The data analysis software QIIME and Metastats were used to compare bacterial relative abundance in the three patient groups. Overall, 545 genera were identified; 38 showed significantly lower and 29 had significantly higher relative abundance in the sarcoidosis group than in the TB and control groups (P < 0.01). P. acnes 16SrRNA was exclusively found in all the 17 samples of the sarcoidosis group, whereas was not detected in the TB and control groups. The relative abundance of P. acnes in the sarcoidosis group (0.16% ± 0. 11%) was significantly higher than that in the TB (Metastats analysis: P = 0.0010, q = 0.0044) and control groups (Metastats analysis: P = 0.0010, q = 0.0038). The relative abundance of P. granulosum was only 0.0022% ± 0. 0044% in the sarcoidosis group. P. granulosum 16SrRNA was not detected in the other two groups. High throughput 16SrRNA gene sequencing appears to be a useful tool to investigate the bacterial profile of sarcoidosis specimens. The results suggest that P. acnes may be involved in sarcoidosis development.

VIRTUAL EMBRYO: SYSTEMS MODELING IN DEVELOPMENTAL TOXICITY - Symposium: SOT 2012

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. Chemical profiling in ToxCast covered 965 drugs-chemicals in over 500 diverse assays testing...

A novel assay for monoacylglycerol hydrolysis suitable for high-throughput screening.

PubMed

Brengdahl, Johan; Fowler, Christopher J

2006-12-01

A simple assay for monoacylglycerol hydrolysis suitable for high-throughput screening is described. The assay uses [(3)H]2-oleoylglycerol as substrate, with the tritium label in the glycerol part of the molecule and the use of phenyl sepharose gel to separate the hydrolyzed product ([(3)H]glycerol) from substrate. Using cytosolic fractions derived from rat cerebella as a source of hydrolytic activity, the assay gives the appropriate pH profile and sensitivity to inhibition with compounds known to inhibit hydrolysis of this substrate. The assay could also be adapted to a 96-well plate format, using C6 cells as the source of hydrolytic activity. Thus the assay is simple and appropriate for high-throughput screening of inhibitors of monoacylglycerol hydrolysis.

High-throughput method for the quantitation of metabolites and co-factors from homocysteine-methionine cycle for nutritional status assessment.

PubMed

Da Silva, Laeticia; Collino, Sebastiano; Cominetti, Ornella; Martin, Francois-Pierre; Montoliu, Ivan; Moreno, Sergio Oller; Corthesy, John; Kaput, Jim; Kussmann, Martin; Monteiro, Jacqueline Pontes; Guiraud, Seu Ping

2016-09-01

There is increasing interest in the profiling and quantitation of methionine pathway metabolites for health management research. Currently, several analytical approaches are required to cover metabolites and co-factors. We report the development and the validation of a method for the simultaneous detection and quantitation of 13 metabolites in red blood cells. The method, validated in a cohort of healthy human volunteers, shows a high level of accuracy and reproducibility. This high-throughput protocol provides a robust coverage of central metabolites and co-factors in one single analysis and in a high-throughput fashion. In large-scale clinical settings, the use of such an approach will significantly advance the field of nutritional research in health and disease.

Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

Cancer.gov

The vast datasets generated by next generation gene sequencing and expression profiling have transformed biological and translational research. However, technologies to produce large-scale functional genomics datasets, such as high-throughput detection of protein-protein interactions (PPIs), are still in early development. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform featured with both high sensitivity and robustness in a mammalian cell environment remains to be established.

High-Throughput Microfluidic Labyrinth for the Label-free Isolation of Circulating Tumor Cells.

PubMed

Lin, Eric; Rivera-Báez, Lianette; Fouladdel, Shamileh; Yoon, Hyeun Joong; Guthrie, Stephanie; Wieger, Jacob; Deol, Yadwinder; Keller, Evan; Sahai, Vaibhav; Simeone, Diane M; Burness, Monika L; Azizi, Ebrahim; Wicha, Max S; Nagrath, Sunitha

2017-09-27

We present "Labyrinth," a label-free microfluidic device to isolate circulating tumor cells (CTCs) using the combination of long loops and sharp corners to focus both CTCs and white blood cells (WBCs) at a high throughput of 2.5 mL/min. The high yield (>90%) and purity (600 WBCs/mL) of Labyrinth enabled us to profile gene expression in CTCs. As proof of principle, we used previously established cancer stem cell gene signatures to profile single cells isolated from the blood of breast cancer patients. We observed heterogeneous subpopulations of CTCs expressing genes for stem cells, epithelial cells, mesenchymal cells, and cells transitioning between epithelial and mesenchymal. Labyrinth offers a cell-surface marker-independent single-cell isolation platform to study heterogeneous CTC subpopulations. Copyright © 2017 Elsevier Inc. All rights reserved.

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

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.

Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR library

PubMed Central

Zhu, Shiyou; Li, Wei; Liu, Jingze; Chen, Chen-Hao; Liao, Qi; Xu, Ping; Xu, Han; Xiao, Tengfei; Cao, Zhongzheng; Peng, Jingyu; Yuan, Pengfei; Brown, Myles; Liu, Xiaole Shirley; Wei, Wensheng

2017-01-01

CRISPR/Cas9 screens have been widely adopted to analyse coding gene functions, but high throughput screening of non-coding elements using this method is more challenging, because indels caused by a single cut in non-coding regions are unlikely to produce a functional knockout. A high-throughput method to produce deletions of non-coding DNA is needed. Herein, we report a high throughput genomic deletion strategy to screen for functional long non-coding RNAs (lncRNAs) that is based on a lentiviral paired-guide RNA (pgRNA) library. Applying our screening method, we identified 51 lncRNAs that can positively or negatively regulate human cancer cell growth. We individually validated 9 lncRNAs using CRISPR/Cas9-mediated genomic deletion and functional rescue, CRISPR activation or inhibition, and gene expression profiling. Our high-throughput pgRNA genome deletion method should enable rapid identification of functional mammalian non-coding elements. PMID:27798563

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

PubMed Central

Choudhry, Priya

2016-01-01

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

High-throughput profiling of nanoparticle-protein interactions by fluorescamine labeling.

PubMed

Ashby, Jonathan; Duan, Yaokai; Ligans, Erik; Tamsi, Michael; Zhong, Wenwan

2015-02-17

A rapid, high throughput fluorescence assay was designed to screen interactions between proteins and nanoparticles. The assay employs fluorescamine, a primary-amine specific fluorogenic dye, to label proteins. Because fluorescamine could specifically target the surface amines on proteins, a conformational change of the protein upon interaction with nanoparticles will result in a change in fluorescence. In the present study, the assay was applied to test the interactions between a selection of proteins and nanoparticles made of polystyrene, silica, or iron oxide. The particles were also different in their hydrodynamic diameter, synthesis procedure, or surface modification. Significant labeling differences were detected when the same protein incubated with different particles. Principal component analysis (PCA) on the collected fluorescence profiles revealed clear grouping effects of the particles based on their properties. The results prove that fluorescamine labeling is capable of detecting protein-nanoparticle interactions, and the resulting fluorescence profile is sensitive to differences in nanoparticle's physical properties. The assay can be carried out in a high-throughput manner, and is rapid with low operation cost. Thus, it is well suited for evaluating interactions between a larger number of proteins and nanoparticles. Such assessment can help to improve our understanding on the molecular basis that governs the biological behaviors of nanomaterials. It will also be useful for initial examination of the bioactivity and reproducibility of nanomaterials employed in biomedical fields.

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

PubMed

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

2018-01-01

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

A tunable single-monochromator Raman system based on the supercontinuum laser and tunable filters for resonant Raman profile measurements.

PubMed

Liu, X-L; Liu, H-N; Tan, P-H

2017-08-01

Resonant Raman spectroscopy requires that the wavelength of the laser used is close to that of an electronic transition. A tunable laser source and a triple spectrometer are usually necessary for resonant Raman profile measurements. However, such a system is complex with low signal throughput, which limits its wide application by scientific community. Here, a tunable micro-Raman spectroscopy system based on the supercontinuum laser, transmission grating, tunable filters, and single-stage spectrometer is introduced to measure the resonant Raman profile. The supercontinuum laser in combination with transmission grating makes a tunable excitation source with a bandwidth of sub-nanometer. Such a system exhibits continuous excitation tunability and high signal throughput. Its good performance and flexible tunability are verified by resonant Raman profile measurement of twisted bilayer graphene, which demonstrates its potential application prospect for resonant Raman spectroscopy.

JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles

PubMed Central

Portales-Casamar, Elodie; Thongjuea, Supat; Kwon, Andrew T.; Arenillas, David; Zhao, Xiaobei; Valen, Eivind; Yusuf, Dimas; Lenhard, Boris; Wasserman, Wyeth W.; Sandelin, Albin

2010-01-01

JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIP-chip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches. PMID:19906716

On Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which showmore » concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.« less

High-Throughput Sequencing Reveals Principles of Adeno-Associated Virus Serotype 2 Integration

PubMed Central

Janovitz, Tyler; Klein, Isaac A.; Oliveira, Thiago; Mukherjee, Piali; Nussenzweig, Michel C.; Sadelain, Michel

2013-01-01

Viral integrations are important in human biology, yet genome-wide integration profiles have not been determined for many viruses. Adeno-associated virus (AAV) infects most of the human population and is a prevalent gene therapy vector. AAV integrates into the human genome with preference for a single locus, termed AAVS1. However, the genome-wide integration of AAV has not been defined, and the principles underlying this recombination remain unclear. Using a novel high-throughput approach, integrant capture sequencing, nearly 12 million AAV junctions were recovered from a human cell line, providing five orders of magnitude more data than were previously available. Forty-five percent of integrations occurred near AAVS1, and several thousand novel integration hotspots were identified computationally. Most of these occurred in genes, with dozens of hotspots targeting known oncogenes. Viral replication protein binding sites (RBS) and transcriptional activity were major factors favoring integration. In a first for eukaryotic viruses, the data reveal a unique asymmetric integration profile with distinctive directional orientation of viral genomes. These studies provide a new understanding of AAV integration biology through the use of unbiased high-throughput data acquisition and bioinformatics. PMID:23720718

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

High-throughput STR analysis for DNA database using direct PCR.

PubMed

Sim, Jeong Eun; Park, Su Jeong; Lee, Han Chul; Kim, Se-Yong; Kim, Jong Yeol; Lee, Seung Hwan

2013-07-01

Since the Korean criminal DNA database was launched in 2010, we have focused on establishing an automated DNA database profiling system that analyzes short tandem repeat loci in a high-throughput and cost-effective manner. We established a DNA database profiling system without DNA purification using a direct PCR buffer system. The quality of direct PCR procedures was compared with that of conventional PCR system under their respective optimized conditions. The results revealed not only perfect concordance but also an excellent PCR success rate, good electropherogram quality, and an optimal intra/inter-loci peak height ratio. In particular, the proportion of DNA extraction required due to direct PCR failure could be minimized to <3%. In conclusion, the newly developed direct PCR system can be adopted for automated DNA database profiling systems to replace or supplement conventional PCR system in a time- and cost-saving manner. © 2013 American Academy of Forensic Sciences Published 2013. This article is a U.S. Government work and is in the public domain in the U.S.A.

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

PubMed Central

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

2017-01-01

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

High-throughput full-length single-cell mRNA-seq of rare cells.

PubMed

Ooi, Chin Chun; Mantalas, Gary L; Koh, Winston; Neff, Norma F; Fuchigami, Teruaki; Wong, Dawson J; Wilson, Robert J; Park, Seung-Min; Gambhir, Sanjiv S; Quake, Stephen R; Wang, Shan X

2017-01-01

Single-cell characterization techniques, such as mRNA-seq, have been applied to a diverse range of applications in cancer biology, yielding great insight into mechanisms leading to therapy resistance and tumor clonality. While single-cell techniques can yield a wealth of information, a common bottleneck is the lack of throughput, with many current processing methods being limited to the analysis of small volumes of single cell suspensions with cell densities on the order of 107 per mL. In this work, we present a high-throughput full-length mRNA-seq protocol incorporating a magnetic sifter and magnetic nanoparticle-antibody conjugates for rare cell enrichment, and Smart-seq2 chemistry for sequencing. We evaluate the efficiency and quality of this protocol with a simulated circulating tumor cell system, whereby non-small-cell lung cancer cell lines (NCI-H1650 and NCI-H1975) are spiked into whole blood, before being enriched for single-cell mRNA-seq by EpCAM-functionalized magnetic nanoparticles and the magnetic sifter. We obtain high efficiency (> 90%) capture and release of these simulated rare cells via the magnetic sifter, with reproducible transcriptome data. In addition, while mRNA-seq data is typically only used for gene expression analysis of transcriptomic data, we demonstrate the use of full-length mRNA-seq chemistries like Smart-seq2 to facilitate variant analysis of expressed genes. This enables the use of mRNA-seq data for differentiating cells in a heterogeneous population by both their phenotypic and variant profile. In a simulated heterogeneous mixture of circulating tumor cells in whole blood, we utilize this high-throughput protocol to differentiate these heterogeneous cells by both their phenotype (lung cancer versus white blood cells), and mutational profile (H1650 versus H1975 cells), in a single sequencing run. This high-throughput method can help facilitate single-cell analysis of rare cell populations, such as circulating tumor or endothelial cells, with demonstrably high-quality transcriptomic data.

Steroid Profiling by Gas Chromatography–Mass Spectrometry and High Performance Liquid Chromatography–Mass Spectrometry for Adrenal Diseases

PubMed Central

McDonald, Jeffrey G.; Matthew, Susan

2012-01-01

The ability to measure steroid hormone concentrations in blood and urine specimens is central to the diagnosis and proper treatment of adrenal diseases. The traditional approach has been to assay each steroid hormone, precursor, or metabolite using individual aliquots of serum, each with a separate immunoassay. For complex diseases, such as congenital adrenal hyperplasia and adrenocortical cancer, in which the assay of several steroids is essential for management, this approach is time consuming and costly, in addition to using large amounts of serum. Gas chromatography/mass spectrometry profiling of steroid metabolites in urine has been employed for many years but only in a small number of specialized laboratories and suffers from slow throughput. The advent of commercial high-performance liquid chromatography instruments coupled to tandem mass spectrometers offers the potential for medium- to high-throughput profiling of serum steroids using small quantities of sample. Here, we review the physical principles of mass spectrometry, the instrumentation used for these techniques, the terminology used in this field and applications to steroid analysis. PMID:22170384

Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study

PubMed Central

Yan, Benedict; Hu, Yongli; Ban, Kenneth H.K.; Tiang, Zenia; Ng, Christopher; Lee, Joanne; Tan, Wilson; Chiu, Lily; Tan, Tin Wee; Seah, Elaine; Ng, Chin Hin; Chng, Wee-Joo; Foo, Roger

2017-01-01

Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable. PMID:28454300

On the possibility of using polycrystalline material in the development of structure-based generic assays

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

Allaire, Marc, E-mail: allaire@bnl.gov; Moiseeva, Natalia; Botez, Cristian E.

The correlation coefficients calculated between raw powder diffraction profiles can be used to identify ligand-bound/unbound states of lysozyme. The discovery of ligands that bind specifically to a targeted protein benefits from the development of generic assays for high-throughput screening of a library of chemicals. Protein powder diffraction (PPD) has been proposed as a potential method for use as a structure-based assay for high-throughput screening applications. Building on this effort, powder samples of bound/unbound states of soluble hen-egg white lysozyme precipitated with sodium chloride were compared. The correlation coefficients calculated between the raw diffraction profiles were consistent with the known bindingmore » properties of the ligands and suggested that the PPD approach can be used even prior to a full description using stereochemically restrained Rietveld refinement.« less

High throughput screening and profiling of high-value carotenoids from a wide diversity of bacteria in surface seawater.

PubMed

Asker, Dalal

2018-09-30

Carotenoids are valuable natural colorants that exhibit numerous health promoting properties, and thus are widely used in food, feeds, pharmaceutical and nutraceuticals industries. In this study, we isolated and identified novel microbial sources that produced high-value carotenoids using high throughput screening (HTS). A total of 701 pigmented microbial strains library including marine bacteria and red yeast was constructed. Carotenoids profiling using HPLC-DAD-MS methods showed 88 marine bacterial strains with potential for the production of high-value carotenoids including astaxanthin (28 strains), zeaxanthin (21 strains), lutein (1 strains) and canthaxanthin (2 strains). A comprehensive 16S rRNA gene based phylogenetic analysis revealed that these strains can be classified into 30 species belonging to five bacterial classes (Flavobacteriia, α-Proteobacteria, γ-Proteobacteria, Actinobacteria and Bacilli). Importantly, we discovered novel producers of zeaxanthin and lutein, and a high diversity in both carotenoids and producing microbial strains, which are promising and highly selective biotechnological sources for high-value carotenoids. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

Ethoscopes: An open platform for high-throughput ethomics.

PubMed

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

2017-10-01

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

Ionomic screening of field-grown soybeans identifies mutants with altered seed elemental composition

USDA-ARS?s Scientific Manuscript database

Soybean seeds contain high levels of mineral nutrients essential for human and animal nutrition. High throughput elemental profiling (ionomics) has identified mutants in model plant species grown in controlled environments. Here, we describe a method for identifying potential soybean ionomics mutant...

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...

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.

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

PubMed

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

2016-07-01

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

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

PubMed

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

2017-05-19

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

Quantitative profiling of immune repertoires for minor lymphocyte counts using unique molecular identifiers.

PubMed

Egorov, Evgeny S; Merzlyak, Ekaterina M; Shelenkov, Andrew A; Britanova, Olga V; Sharonov, George V; Staroverov, Dmitriy B; Bolotin, Dmitriy A; Davydov, Alexey N; Barsova, Ekaterina; Lebedev, Yuriy B; Shugay, Mikhail; Chudakov, Dmitriy M

2015-06-15

Emerging high-throughput sequencing methods for the analyses of complex structure of TCR and BCR repertoires give a powerful impulse to adaptive immunity studies. However, there are still essential technical obstacles for performing a truly quantitative analysis. Specifically, it remains challenging to obtain comprehensive information on the clonal composition of small lymphocyte populations, such as Ag-specific, functional, or tissue-resident cell subsets isolated by sorting, microdissection, or fine needle aspirates. In this study, we report a robust approach based on unique molecular identifiers that allows profiling Ag receptors for several hundred to thousand lymphocytes while preserving qualitative and quantitative information on clonal composition of the sample. We also describe several general features regarding the data analysis with unique molecular identifiers that are critical for accurate counting of starting molecules in high-throughput sequencing applications. Copyright © 2015 by The American Association of Immunologists, Inc.

In vitro data and in silico models for computational toxicology (Teratology Society ILSI HESI workshop)

EPA Science Inventory

The challenge of assessing the potential developmental health risks for the tens of thousands of environmental chemicals is beyond the capacity for resource-intensive animal protocols. Large data streams coming from high-throughput (HTS) and high-content (HCS) profiling of biolog...

HIGH-DIMENSIONAL PROFILING OF TRANSCRIPTION FACTOR ACTIVITY DIFFERENTIATES TOXCAST CHEMICAL GROUPS

EPA Science Inventory

The ToxCast™ project at the U.S. EPA uses a diverse battery of high throughput screening assays and informatics models to rapidly characterize the activity of chemicals. A central goal of the project is to provide empirical evidence to aid in the prioritization of chemicals for a...

Simultaneous Profiling of Lysoglycerophospholipids in Rice (Oryza sativa L.) Using Direct Infusion-Tandem Mass Spectrometry with Multiple Reaction Monitoring.

PubMed

Lim, Dong Kyu; Mo, Changyeun; Long, Nguyen Phuoc; Kim, Giyoung; Kwon, Sung Won

2017-03-29

White rice is the final product after the hull and bran layers have been removed during the milling process. Although lysoglycerophospholipids (lysoGPLs) only occupy a small proportion in white rice, they are essential for evaluating rice authenticity and quality. In this study, we developed a high-throughput and targeted lipidomics approach that involved direct infusion-tandem mass spectrometry with multiple reaction monitoring to simultaneously profile lysoGPLs in white rice. The method is capable of characterizing 17 lysoGPLs within 1 min. In addition, unsupervised and supervised analyses exhibited a considerably large diversity of lysoGPL concentrations in white rice from different origins. In particular, a classification model was built using identified lysoGPLs that can differentiate white rice from Korea, China, and Japan. Among the discriminatory lysoGPLs, for the lysoPE(16:0) and lysoPE(18:2) compositions, there were relatively small within-group variations, and they were considerably different among the three countries. In conclusion, our proposed method provides a rapid, high-throughput, and comprehensive format for profiling lysoGPLs in rice samples.

Line-edge quality optimization of electron beam resist for high-throughput character projection exposure utilizing atomic force microscope analysis

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Mita, Yoshio; Asada, Kunihiro

2017-04-01

High-throughput electron-beam lithography (EBL) by character projection (CP) and variable-shaped beam (VSB) methods is a promising technique for low-to-medium volume device fabrication with regularly arranged layouts, such as standard-cell logics and memory arrays. However, non-VLSI applications like MEMS and MOEMS may not fully utilize the benefits of CP method due to their wide variety of layout figures including curved and oblique edges. In addition, the stepwise shapes that appear on such irregular edges by VSB exposure often result in intolerable edge roughness, which may degrade performances of the fabricated devices. In our former study, we proposed a general EBL methodology for such applications utilizing a combination of CP and VSB methods, and demonstrated its capabilities in electron beam (EB) shot reduction and edge-quality improvement by using a leading-edge EB exposure tool, ADVANTEST F7000S-VD02, and high-resolution Hydrogen Silsesquioxane resist. Both scanning electron microscope and atomic force microscope observations were used to analyze quality of the resist edge profiles to determine the influence of the control parameters used in the exposure-data preparation process. In this study, we carried out detailed analysis of the captured edge profiles utilizing Fourier analysis, and successfully distinguish the systematic undulation by the exposed CP character profiles from random roughness components. Such capability of precise edge-roughness analysis is useful to our EBL methodology to maintain both the line-edge quality and the exposure throughput by optimizing the control parameters in the layout data conversion.

Accounting Artifacts in High-Throughput Toxicity Assays.

PubMed

Hsieh, Jui-Hua

2016-01-01

Compound activity identification is the primary goal in high-throughput screening (HTS) assays. However, assay artifacts including both systematic (e.g., compound auto-fluorescence) and nonsystematic (e.g., noise) complicate activity interpretation. In addition, other than the traditional potency parameter, half-maximal effect concentration (EC50), additional activity parameters (e.g., point-of-departure, POD) could be derived from HTS data for activity profiling. A data analysis pipeline has been developed to handle the artifacts and to provide compound activity characterization with either binary or continuous metrics. This chapter outlines the steps in the pipeline using Tox21 glucocorticoid receptor (GR) β-lactamase assays, including the formats to identify either agonists or antagonists, as well as the counter-screen assays for identifying artifacts as examples. The steps can be applied to other lower-throughput assays with concentration-response data.

Novel Acoustic Loading of a Mass Spectrometer: Toward Next-Generation High-Throughput MS Screening.

PubMed

Sinclair, Ian; Stearns, Rick; Pringle, Steven; Wingfield, Jonathan; Datwani, Sammy; Hall, Eric; Ghislain, Luke; Majlof, Lars; Bachman, Martin

2016-02-01

High-throughput, direct measurement of substrate-to-product conversion by label-free detection, without the need for engineered substrates or secondary assays, could be considered the "holy grail" of drug discovery screening. Mass spectrometry (MS) has the potential to be part of this ultimate screening solution, but is constrained by the limitations of existing MS sample introduction modes that cannot meet the throughput requirements of high-throughput screening (HTS). Here we report data from a prototype system (Echo-MS) that uses acoustic droplet ejection (ADE) to transfer femtoliter-scale droplets in a rapid, precise, and accurate fashion directly into the MS. The acoustic source can load samples into the MS from a microtiter plate at a rate of up to three samples per second. The resulting MS signal displays a very sharp attack profile and ions are detected within 50 ms of activation of the acoustic transducer. Additionally, we show that the system is capable of generating multiply charged ion species from simple peptides and large proteins. The combination of high speed and low sample volume has significant potential within not only drug discovery, but also other areas of the industry. © 2015 Society for Laboratory Automation and Screening.

Method development in high-performance liquid chromatography for high-throughput profiling and metabonomic studies of biofluid samples.

PubMed

Pham-Tuan, Hai; Kaskavelis, Lefteris; Daykin, Clare A; Janssen, Hans-Gerd

2003-06-15

"Metabonomics" has in the past decade demonstrated enormous potential in furthering the understanding of, for example, disease processes, toxicological mechanisms, and biomarker discovery. The same principles can also provide a systematic and comprehensive approach to the study of food ingredient impact on consumer health. However, "metabonomic" methodology requires the development of rapid, advanced analytical tools to comprehensively profile biofluid metabolites within consumers. Until now, NMR spectroscopy has been used for this purpose almost exclusively. Chromatographic techniques and in particular HPLC, have not been exploited accordingly. The main drawbacks of chromatography are the long analysis time, instabilities in the sample fingerprint and the rigorous sample preparation required. This contribution addresses these problems in the quest to develop generic methods for high-throughput profiling using HPLC. After a careful optimization process, stable fingerprints of biofluid samples can be obtained using standard HPLC equipment. A method using a short monolithic column and a rapid gradient with a high flow-rate has been developed that allowed rapid and detailed profiling of larger numbers of urine samples. The method can be easily translated into a slow, shallow-gradient high-resolution method for identification of interesting peaks by LC-MS/NMR. A similar approach has been applied for cell culture media samples. Due to the much higher protein content of such samples non-porous polymer-based small particle columns yielded the best results. The study clearly shows that HPLC can be used in metabonomic fingerprinting studies.

Managing the genomic revolution in cancer diagnostics.

PubMed

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.

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

Ethoscopes: An open platform for high-throughput ethomics

PubMed Central

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

2017-01-01

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

Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles

PubMed Central

Zheng, Yun; Ji, Bo; Song, Renhua; Wang, Shengpeng; Li, Ting; Zhang, Xiaotuo; Chen, Kun; Li, Tianqing; Li, Jinyan

2016-01-01

Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3′-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles. PMID:27229138

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

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

PubMed

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

2016-01-01

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

High throughput screening technologies for ion channels

PubMed Central

Yu, Hai-bo; Li, Min; Wang, Wei-ping; Wang, Xiao-liang

2016-01-01

Ion channels are involved in a variety of fundamental physiological processes, and their malfunction causes numerous human diseases. Therefore, ion channels represent a class of attractive drug targets and a class of important off-targets for in vitro pharmacological profiling. In the past decades, the rapid progress in developing functional assays and instrumentation has enabled high throughput screening (HTS) campaigns on an expanding list of channel types. Chronologically, HTS methods for ion channels include the ligand binding assay, flux-based assay, fluorescence-based assay, and automated electrophysiological assay. In this review we summarize the current HTS technologies for different ion channel classes and their applications. PMID:26657056

Analysis of high-throughput biological data using their rank values.

PubMed

Dembélé, Doulaye

2018-01-01

High-throughput biological technologies are routinely used to generate gene expression profiling or cytogenetics data. To achieve high performance, methods available in the literature become more specialized and often require high computational resources. Here, we propose a new versatile method based on the data-ordering rank values. We use linear algebra, the Perron-Frobenius theorem and also extend a method presented earlier for searching differentially expressed genes for the detection of recurrent copy number aberration. A result derived from the proposed method is a one-sample Student's t-test based on rank values. The proposed method is to our knowledge the only that applies to gene expression profiling and to cytogenetics data sets. This new method is fast, deterministic, and requires a low computational load. Probabilities are associated with genes to allow a statistically significant subset selection in the data set. Stability scores are also introduced as quality parameters. The performance and comparative analyses were carried out using real data sets. The proposed method can be accessed through an R package available from the CRAN (Comprehensive R Archive Network) website: https://cran.r-project.org/web/packages/fcros .

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

Performance of Identifiler Direct and PowerPlex 16 HS on the Applied Biosystems 3730 DNA Analyzer for processing biological samples archived on FTA cards.

PubMed

Laurin, Nancy; DeMoors, Anick; Frégeau, Chantal

2012-09-01

Direct amplification of STR loci from biological samples collected on FTA cards without prior DNA purification was evaluated using Identifiler Direct and PowerPlex 16 HS in conjunction with the use of a high throughput Applied Biosystems 3730 DNA Analyzer. In order to reduce the overall sample processing cost, reduced PCR volumes combined with various FTA disk sizes were tested. Optimized STR profiles were obtained using a 0.53 mm disk size in 10 μL PCR volume for both STR systems. These protocols proved effective in generating high quality profiles on the 3730 DNA Analyzer from both blood and buccal FTA samples. Reproducibility, concordance, robustness, sample stability and profile quality were assessed using a collection of blood and buccal samples on FTA cards from volunteer donors as well as from convicted offenders. The new developed protocols offer enhanced throughput capability and cost effectiveness without compromising the robustness and quality of the STR profiles obtained. These results support the use of these protocols for processing convicted offender samples submitted to the National DNA Data Bank of Canada. Similar protocols could be applied to the processing of casework reference samples or in paternity or family relationship testing. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Identification of Inhibitors in Lignocellulosic Slurries and Determination of Their Effect on Hydrocarbon-Producing Microorganisms

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

Yang, Shihui; Franden, Mary A; Yang, Qing

The aim of this work was to identify inhibitors in pretreated lignocellulosic slurries, evaluate high-throughput screening strategies, and investigate the impact of inhibitors on potential hydrocarbon-producing microorganisms. Compounds present in slurries that could inhibit microbial growth were identified through a detailed analysis of saccharified slurries by applying a combination of approaches of high-performance liquid chromatography, GC-MS, LC-DAD-MS, and ICP-MS. Several high-throughput assays were then evaluated to generate toxicity profiles. Our results demonstrated that Bioscreen C was useful for analyzing bacterial toxicity but not for yeast. AlamarBlue reduction assay can be a useful high-throughput assay for both bacterial and yeast strainsmore » as long as medium components do not interfere with fluorescence measurements. In addition, this work identified two major inhibitors (furfural and ammonium acetate) for three potential hydrocarbon-producing bacterial species that include Escherichia coli, Cupriavidus necator, and Rhodococcus opacus PD630, which are also the primary inhibitors for ethanologens. Here, this study was strived to establish a pipeline to quantify inhibitory compounds in biomass slurries and high-throughput approaches to investigate the effect of inhibitors on microbial biocatalysts, which can be applied for various biomass slurries or hydrolyzates generated through different pretreatment and enzymatic hydrolysis processes or different microbial candidates.« less

Identification of Inhibitors in Lignocellulosic Slurries and Determination of Their Effect on Hydrocarbon-Producing Microorganisms

DOE PAGES

Yang, Shihui; Franden, Mary A; Yang, Qing; ...

2018-04-04

The aim of this work was to identify inhibitors in pretreated lignocellulosic slurries, evaluate high-throughput screening strategies, and investigate the impact of inhibitors on potential hydrocarbon-producing microorganisms. Compounds present in slurries that could inhibit microbial growth were identified through a detailed analysis of saccharified slurries by applying a combination of approaches of high-performance liquid chromatography, GC-MS, LC-DAD-MS, and ICP-MS. Several high-throughput assays were then evaluated to generate toxicity profiles. Our results demonstrated that Bioscreen C was useful for analyzing bacterial toxicity but not for yeast. AlamarBlue reduction assay can be a useful high-throughput assay for both bacterial and yeast strainsmore » as long as medium components do not interfere with fluorescence measurements. In addition, this work identified two major inhibitors (furfural and ammonium acetate) for three potential hydrocarbon-producing bacterial species that include Escherichia coli, Cupriavidus necator, and Rhodococcus opacus PD630, which are also the primary inhibitors for ethanologens. Here, this study was strived to establish a pipeline to quantify inhibitory compounds in biomass slurries and high-throughput approaches to investigate the effect of inhibitors on microbial biocatalysts, which can be applied for various biomass slurries or hydrolyzates generated through different pretreatment and enzymatic hydrolysis processes or different microbial candidates.« less

Use of high-throughput and in vivo data to support read ...

EPA Pesticide Factsheets

Disrupting normal function of mitochondria can culminate in a variety of organ-level toxicities. A number of mechanisms - such as uncoupling of oxidative phosphorylation and inhibition of the electron transport chain - have been implicated in mitochondrial toxicity. The presence of mitochondrial toxicity has led to a number of drugs being withdrawn from the market highlighting the need to identify potential mitochondrial toxicants within the environment. High-throughput screening (HTS) assays provide a means of rapidly gathering toxicity data for a large number of chemicals; however, information as to the associated in vivo effect is typically unknown. The Adverse Outcome Pathway (AOP) concept provides a valuable scaffold onto which mechanistic data from different levels of biological organisation can be arranged.Information pertaining to mitochondrial toxicity from the U.S. EPA’s ToxCast program were integrated with rodent in vivo data from U.S. EPA’s ToxRefDB to connect the high throughput ToxCast assay results with potential adverse outcome data. Previously developed structural alerts were utilized to profile the chemicals with both in vitro mitochondrial toxicity and in vivo rodent data. Structural similarity guided by the toxicity profile as measured in the ToxCast assay battery was then used to group those chemicals which either were not tested in a mitochondrial toxicity assay or were not considered a “hit” and read-across was performed. Subsequen

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

PubMed

Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

2015-08-01

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

High throughput ion-channel pharmacology: planar-array-based voltage clamp.

PubMed

Kiss, Laszlo; Bennett, Paul B; Uebele, Victor N; Koblan, Kenneth S; Kane, Stefanie A; Neagle, Brad; Schroeder, Kirk

2003-02-01

Technological advances often drive major breakthroughs in biology. Examples include PCR, automated DNA sequencing, confocal/single photon microscopy, AFM, and voltage/patch-clamp methods. The patch-clamp method, first described nearly 30 years ago, was a major technical achievement that permitted voltage-clamp analysis (membrane potential control) of ion channels in most cells and revealed a role for channels in unimagined areas. Because of the high information content, voltage clamp is the best way to study ion-channel function; however, throughput is too low for drug screening. Here we describe a novel breakthrough planar-array-based HT patch-clamp technology developed by Essen Instruments capable of voltage-clamping thousands of cells per day. This technology provides greater than two orders of magnitude increase in throughput compared with the traditional voltage-clamp techniques. We have applied this method to study the hERG K(+) channel and to determine the pharmacological profile of QT prolonging drugs.

Elucidation of Adverse Bioactivity Profiles as Predictors of Toxicity Potential

EPA Science Inventory

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

Analysis, annotation, and profiling of the oat seed transcriptome

USDA-ARS?s Scientific Manuscript database

Novel high-throughput next generation sequencing (NGS) technologies are providing opportunities to explore genomes and transcriptomes in a cost-effective manner. To construct a gene expression atlas of developing oat (Avena sativa) seeds, two software packages specifically designed for RNA-seq (Trin...

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...

HIGH-THROUGHPUT CHEMICAL SCREENING USING PROTEIN PROFILING OF FISH PLASMA

EPA Science Inventory

Compounds that affect the hormone system, referred to as "endocrine-disrupting chemicals" (EDCs), cause human and animal health problems. It is necessary to test putative EDC chemicals for such deleterious effects, though current testing methodologies are time/animal intensive an...

High-Throughput In Vivo Genotoxicity Testing: An Automated Readout System for the Somatic Mutation and Recombination Test (SMART)

PubMed Central

Kwak, Jihoon; Genovesio, Auguste; Kang, Myungjoo; Hansen, Michael Adsett Edberg; Han, Sung-Jun

2015-01-01

Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods. PMID:25830368

Cancer biomarker discovery: the entropic hallmark.

PubMed

Berretta, Regina; Moscato, Pablo

2010-08-18

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

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.

Profiling optimization for big data transfer over dedicated channels

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

Yun, D.; Wu, Qishi; Rao, Nageswara S

The transfer of big data is increasingly supported by dedicated channels in high-performance networks, where transport protocols play an important role in maximizing applicationlevel throughput and link utilization. The performance of transport protocols largely depend on their control parameter settings, but it is prohibitively time consuming to conduct an exhaustive search in a large parameter space to find the best set of parameter values. We propose FastProf, a stochastic approximation-based transport profiler, to quickly determine the optimal operational zone of a given data transfer protocol/method over dedicated channels. We implement and test the proposed method using both emulations based onmore » real-life performance measurements and experiments over physical connections with short (2 ms) and long (380 ms) delays. Both the emulation and experimental results show that FastProf significantly reduces the profiling overhead while achieving a comparable level of end-to-end throughput performance with the exhaustive search-based approach.« less

High-throughput optofluidic profiling of Euglena gracilis with morphological and chemical specificity

NASA Astrophysics Data System (ADS)

Guo, Baoshan; Lei, Cheng; Ito, Takuro; Jiang, Yiyue; Ozeki, Yasuyuki; Goda, Keisuke

2016-11-01

The world is faced with environmental problems and the energy crisis due to the combustion and depletion of fossil fuels. 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, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate a high-throughput optofluidic Euglena gracilis profiler which consists of an optical time-stretch microscope and a fluorescence analyzer on top of an inertial-focusing microfluidic device that can detect fluorescence from lipid droplets in their cell body and provide images of E. gracilis cells simultaneously at a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method provides a promise for evaluating the efficiency of lipid-inducing techniques for biofuel production, which is also applicable for identifying biomedical samples such as blood cells and cancer cells.

Profile and Fate of Bacterial Pathogens in Sewage Treatment Plants Revealed by High-Throughput Metagenomic Approach.

PubMed

Li, Bing; Ju, Feng; Cai, Lin; Zhang, Tong

2015-09-01

The broad-spectrum profile of bacterial pathogens and their fate in sewage treatment plants (STPs) were investigated using high-throughput sequencing based metagenomic approach. This novel approach could provide a united platform to standardize bacterial pathogen detection and realize direct comparison among different samples. Totally, 113 bacterial pathogen species were detected in eight samples including influent, effluent, activated sludge (AS), biofilm, and anaerobic digestion sludge with the abundances ranging from 0.000095% to 4.89%. Among these 113 bacterial pathogens, 79 species were reported in STPs for the first time. Specially, compared to AS in bulk mixed liquor, more pathogen species and higher total abundance were detected in upper foaming layer of AS. This suggests that the foaming layer of AS might impose more threat to onsite workers and citizens in the surrounding areas of STPs because pathogens in foaming layer are easily transferred into air and cause possible infections. The high removal efficiency (98.0%) of total bacterial pathogens suggests that AS treatment process is effective to remove most bacterial pathogens. Remarkable similarities of bacterial pathogen compositions between influent and human gut indicated that bacterial pathogen profiles in influents could well reflect the average bacterial pathogen communities of urban resident guts within the STP catchment area.

Modeling limb-bud dysmorphogenesis in a predictive virtual embryo model

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational methods that integrate knowledge of biological systems and in vivo toxicities (www.epa.gov/ncct/toxcast/). Many ToxCast assays assess signaling pathways and c...

A fungal mock community control for amplicon sequencing experiments

USDA-ARS?s Scientific Manuscript database

The field of microbial ecology has been profoundly advanced by the ability to profile the composition of complex microbial communities by means of high throughput amplicon sequencing of marker genes amplified directly from environmental genomic DNA extracts. However, it has become increasingly clear...

Activity profiles of 676 ToxCast Phase II compounds in 231 biochemical high-throughput screening assays

EPA Science Inventory

Understanding potential health risks posed by environmental chemicals is a significant challenge elevated by large numbers of diverse chemicals with generally uncharacterized exposures, mechanisms and toxicities. The present study is a performance evaluation and critical analysis...

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

PubMed

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

2017-07-14

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

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

PubMed

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

2018-04-27

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

20180312 - Application of a Multiplexed High Content Imaging (HCI) Based Cell Viability and Apoptosis Chemical Screening Assay with Results in MCF-7 Cells (SOT)

EPA Science Inventory

The NCCT high throughput transcriptomics (HTTr) screening program uses whole transcriptome profiling assay in human-derived cells to collect concentration-response data for large numbers (100s-1000s) of environmental chemicals. To contextualize HTTr data, chemical effects on cell...

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

PubMed

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

2018-02-27

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

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

PubMed

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

2010-04-05

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

Microscale Laminar Vortices for High-Purity Extraction and Release of Circulating Tumor Cells.

PubMed

Hur, Soojung Claire; Che, James; Di Carlo, Dino

2017-01-01

Circulating tumor cells (CTCs) are disseminated tumor cells that reflect the tumors of origin and can provide a liquid biopsy that would potentially enable noninvasive tumor profiling, treatment monitoring, and identification of targeted treatments. Accurate and rapid purification of CTCs holds great potential to improve cancer care but the task remains technically challenging. Microfluidic isolation of CTCs within microscale vortices enables high-throughput and size-based purification of rare CTCs from bodily fluids. Collected cells are highly pure, viable, and easily accessible, allowing seamless integration with various downstream applications. Here, we describe how to fabricate the High-Throughput Vortex Chip (Vortex-HT) and to process diluted whole blood for CTC collection. Lastly, immunostaining and imaging protocols for CTC classification and corresponding CTC image galleries are reported.

Determination of red blood cell fatty acid profiles: Rapid and high-confident analysis by chemical ionization-gas chromatography-tandem mass spectrometry.

PubMed

Schober, Yvonne; Wahl, Hans Günther; Renz, Harald; Nockher, Wolfgang Andreas

2017-01-01

Cellular fatty acid (FA) profiles have been acknowledged as biomarkers in various human diseases. Nevertheless, common FA analysis by gas chromatography mass spectrometry (GC-MS) requires long analysis time. Hence, there is a need for feasible methods for high throughput analysis in clinical studies. FA was extracted from red blood cells (RBC) and derivatized to fatty acid methyl esters (FAME). A method using gas chromatography tandem mass spectrometry (GC-MS/MS) with ammonia-induced chemical ionization (CI) was developed for the analysis of FA profiles in human RBC. We compared this method with classical single GC-MS using electron impact ionization (EI). The FA profiles of 703 RBC samples were determined by GC-MS/MS. In contrast to EI ammonia-induced CI resulted in adequate amounts of molecular ions for further fragmentation of FAME. Specific fragments for confident quantification and fragmentation were determined for 45 FA. The GC-MS/MS method has a total run time of 9min compared to typical analysis times of up to 60min in conventional GC-MS. Intra and inter assay variations were <10% for all FA analyzed. Analysis of RBC FA composition revealed an age-dependent increase of the omega-3 eicosapentaenoic and docosahexaenoic acid, and a decline of the omega-6 linoleic acid with a corresponding rise of the omega-3 index. The combination of ammonia-induced CI and tandem mass spectrometry after GC separation allows for high-throughput, robust and confident analysis of FA profiles in the clinical laboratory. Copyright © 2016. Published by Elsevier B.V.

Nanomaterial (NM) bioactivity profiling by ToxCast high-throughput screening (HTS)

EPA Science Inventory

Rapidly increasing numbers of new NMs and their uses demand efficient tests of NM bioactivity for safety assessment. The EPA’s ToxCast program uses HTS assays to prioritize for targeted testing, identify biological pathways affected, and aid in linking NM properties and potential...

Transcription profile of boar spermatozoa as revealed by RNA-sequencing

USDA-ARS?s Scientific Manuscript database

High-throughput RNA sequencing (RNA-Seq) overcomes the limitations of the current hybridization-based techniques to detect the actual pool of RNA transcripts in spermatozoa. The application of this technology in livestock can speed the discovery of potential predictors of male fertility. As a first ...

Opportunities for bead-based multiplex assays in veterinary diagnostic laboratories

USDA-ARS?s Scientific Manuscript database

Bead based multiplex assays (BBMA) also referred to as Luminex, MultiAnalyte Profiling or cytometric bead array (CBA) assays, are applicable for high throughput, simultaneous detection of multiple analytes in solution (from several, up to 50-500 analytes within a single, small sample volume). Curren...

Novel Inducers of Fetal Globin Identified through High Throughput Screening (HTS) Are Active In Vivo in Anemic Baboons and Transgenic Mice.

PubMed

Boosalis, Michael S; Sangerman, Jose I; White, Gary L; Wolf, Roman F; Shen, Ling; Dai, Yan; White, Emily; Makala, Levi H; Li, Biaoru; Pace, Betty S; Nouraie, Mehdi; Faller, Douglas V; Perrine, Susan P

2015-01-01

High-level fetal (γ) globin expression ameliorates clinical severity of the beta (β) hemoglobinopathies, and safe, orally-bioavailable γ-globin inducing agents would benefit many patients. We adapted a LCR-γ-globin promoter-GFP reporter assay to a high-throughput robotic system to evaluate five diverse chemical libraries for this activity. Multiple structurally- and functionally-diverse compounds were identified which activate the γ-globin gene promoter at nanomolar concentrations, including some therapeutics approved for other conditions. Three candidates with established safety profiles were further evaluated in erythroid progenitors, anemic baboons and transgenic mice, with significant induction of γ-globin expression observed in vivo. A lead candidate, Benserazide, emerged which demonstrated > 20-fold induction of γ-globin mRNA expression in anemic baboons and increased F-cell proportions by 3.5-fold in transgenic mice. Benserazide has been used chronically to inhibit amino acid decarboxylase to enhance plasma levels of L-dopa. These studies confirm the utility of high-throughput screening and identify previously unrecognized fetal globin inducing candidates which can be developed expediently for treatment of hemoglobinopathies.

Single Cell Profiling using Ionic Liquid Matrix-Enhanced Secondary Ion Mass Spectrometry for Neuronal Cell Type Differentiation

PubMed Central

Do, Thanh D.; Comi, Troy J.; Dunham, Sage J. B.; Rubakhin, Stanislav S.; Sweedler, Jonathan V.

2017-01-01

A high-throughput single cell profiling method has been developed for matrix-enhanced secondary ion mass spectrometry (ME-SIMS) to investigate the lipid profiles of neuronal cells. Populations of cells are dispersed onto the substrate, their locations determined using optical microscopy, and the cell locations used to guide the acquisition of SIMS spectra from the cells. Up to 2,000 cells can be assayed in one experiment at a rate of 6 s per cell. Multiple saturated and unsaturated phosphatidylcholines (PCs) and their fragments are detected and verified with tandem mass spectrometry from individual cells when ionic liquids are employed as a matrix. Optically guided single cell profiling with ME-SIMS is suitable for a range of cell sizes, from Aplysia californica neurons larger than 75 μm to 7-μm rat cerebellar neurons. ME-SIMS analysis followed by t-distributed stochastic neighbor embedding of peaks in the lipid molecular mass range (m/z 700–850) distinguishes several cell types from the rat central nervous system, largely based on the relative proportions of the four dominant lipids, PC(32:0), PC(34:1), PC(36:1), and PC(38:5). Furthermore, subpopulations within each cell type are tentatively classified consistent with their endogenous lipid ratios. The results illustrate the efficacy of a new approach to classify single cell populations and subpopulations using SIMS profiling of lipid and metabolite contents. These methods are broadly applicable for high throughput single cell chemical analyses. PMID:28194949

Combination of automated high throughput platforms, flow cytometry, and hierarchical clustering to detect cell state.

PubMed

Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas

2007-01-01

This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.

High throughput screening of particle conditioning operations: I. System design and method development.

PubMed

Noyes, Aaron; Huffman, Ben; Godavarti, Ranga; Titchener-Hooker, Nigel; Coffman, Jonathan; Sunasara, Khurram; Mukhopadhyay, Tarit

2015-08-01

The biotech industry is under increasing pressure to decrease both time to market and development costs. Simultaneously, regulators are expecting increased process understanding. High throughput process development (HTPD) employs small volumes, parallel processing, and high throughput analytics to reduce development costs and speed the development of novel therapeutics. As such, HTPD is increasingly viewed as integral to improving developmental productivity and deepening process understanding. Particle conditioning steps such as precipitation and flocculation may be used to aid the recovery and purification of biological products. In this first part of two articles, we describe an ultra scale-down system (USD) for high throughput particle conditioning (HTPC) composed of off-the-shelf components. The apparatus is comprised of a temperature-controlled microplate with magnetically driven stirrers and integrated with a Tecan liquid handling robot. With this system, 96 individual reaction conditions can be evaluated in parallel, including downstream centrifugal clarification. A comprehensive suite of high throughput analytics enables measurement of product titer, product quality, impurity clearance, clarification efficiency, and particle characterization. HTPC at the 1 mL scale was evaluated with fermentation broth containing a vaccine polysaccharide. The response profile was compared with the Pilot-scale performance of a non-geometrically similar, 3 L reactor. An engineering characterization of the reactors and scale-up context examines theoretical considerations for comparing this USD system with larger scale stirred reactors. In the second paper, we will explore application of this system to industrially relevant vaccines and test different scale-up heuristics. © 2015 Wiley Periodicals, Inc.

A radial flow microfluidic device for ultra-high-throughput affinity-based isolation of circulating tumor cells.

PubMed

Murlidhar, Vasudha; Zeinali, Mina; Grabauskiene, Svetlana; Ghannad-Rezaie, Mostafa; Wicha, Max S; Simeone, Diane M; Ramnath, Nithya; Reddy, Rishindra M; Nagrath, Sunitha

2014-12-10

Circulating tumor cells (CTCs) are believed to play an important role in metastasis, a process responsible for the majority of cancer-related deaths. But their rarity in the bloodstream makes microfluidic isolation complex and time-consuming. Additionally the low processing speeds can be a hindrance to obtaining higher yields of CTCs, limiting their potential use as biomarkers for early diagnosis. Here, a high throughput microfluidic technology, the OncoBean Chip, is reported. It employs radial flow that introduces a varying shear profile across the device, enabling efficient cell capture by affinity at high flow rates. The recovery from whole blood is validated with cancer cell lines H1650 and MCF7, achieving a mean efficiency >80% at a throughput of 10 mL h(-1) in contrast to a flow rate of 1 mL h(-1) standardly reported with other microfluidic devices. Cells are recovered with a viability rate of 93% at these high speeds, increasing the ability to use captured CTCs for downstream analysis. Broad clinical application is demonstrated using comparable flow rates from blood specimens obtained from breast, pancreatic, and lung cancer patients. Comparable CTC numbers are recovered in all the samples at the two flow rates, demonstrating the ability of the technology to perform at high throughputs. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly Sensitive and High-Throughput Analysis of Plant Hormones Using MS-Probe Modification and Liquid Chromatography–Tandem Mass Spectrometry: An Application for Hormone Profiling in Oryza sativa

PubMed Central

Kojima, Mikiko; Kamada-Nobusada, Tomoe; Komatsu, Hirokazu; Takei, Kentaro; Kuroha, Takeshi; Mizutani, Masaharu; Ashikari, Motoyuki; Ueguchi-Tanaka, Miyako; Matsuoka, Makoto; Suzuki, Koji; Sakakibara, Hitoshi

2009-01-01

We have developed a highly sensitive and high-throughput method for the simultaneous analysis of 43 molecular species of cytokinins, auxins, ABA and gibberellins. This method consists of an automatic liquid handling system for solid phase extraction and ultra-performance liquid chromatography (UPLC) coupled with a tandem quadrupole mass spectrometer (qMS/MS) equipped with an electrospray interface (ESI; UPLC-ESI-qMS/MS). In order to improve the detection limit of negatively charged compounds, such as gibberellins, we chemically derivatized fractions containing auxin, ABA and gibberellins with bromocholine that has a quaternary ammonium functional group. This modification, that we call ‘MS-probe’, makes these hormone derivatives have a positive ion charge and permits all compounds to be measured in the positive ion mode with UPLC-ESI-qMS/MS in a single run. Consequently, quantification limits of gibberellins increased up to 50-fold. Our current method needs <100 mg (FW) of plant tissues to determine phytohormone profiles and enables us to analyze >180 plant samples simultaneously. Application of this method to plant hormone profiling enabled us to draw organ distribution maps of hormone species in rice and also to identify interactions among the four major hormones in the rice gibberellin signaling mutants, gid1-3, gid2-1 and slr1. Combining the results of hormone profiling data with transcriptome data in the gibberellin signaling mutants allows us to analyze relationships between changes in gene expression and hormone metabolism. PMID:19369275

Digital transcriptome profiling using selective hexamer priming for cDNA synthesis.

PubMed

Armour, Christopher D; Castle, John C; Chen, Ronghua; Babak, Tomas; Loerch, Patrick; Jackson, Stuart; Shah, Jyoti K; Dey, John; Rohl, Carol A; Johnson, Jason M; Raymond, Christopher K

2009-09-01

We developed a procedure for the preparation of whole transcriptome cDNA libraries depleted of ribosomal RNA from only 1 microg of total RNA. The method relies on a collection of short, computationally selected oligonucleotides, called 'not-so-random' (NSR) primers, to obtain full-length, strand-specific representation of nonribosomal RNA transcripts. In this study we validated the technique by profiling human whole brain and universal human reference RNA using ultra-high-throughput sequencing.

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.

Predictive models of prenatal developmental toxicity from ToxCast high-throughput screening data

EPA Science Inventory

EPA's ToxCast™ project is profiling the in vitro bioactivity of chemicals to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesized that developmental toxicity in guideline animal studies captured in the ToxRefDB database wou...

Real-Time Growth Kinetics Measuring Hormone Mimicry for ToxCast Chemicals in T‑47D Human Ductal Carcinoma Cells

EPA Science Inventory

High-throughput screening (HTS) assays capable of profiling thousands of environmentally relevant chemicals for in vitro biological activity provide useful information on the potential for disrupting endocrine pathways. Disruption of the estrogen signaling pathway has been implic...

Comparison of L1000 and Affymetrix Microarray for In Vitro Concentration-Response Gene Expression Profiling (SOT)

EPA Science Inventory

Advances in high-throughput screening technologies and in vitro systems have opened doors for cost-efficient evaluation of chemical effects on a diversity of biological endpoints. However, toxicogenomics platforms remain too costly to evaluate large libraries of chemicals in conc...

Optimization Of A High-Throughput Transcriptomic (HTTr) Bioactivity Screen In MCF7 Cells Using Targeted RNA-Seq (SOT)

EPA Science Inventory

Recent advances in targeted RNA-Seq technology allow researchers to efficiently and cost-effectively obtain whole transcriptome profiles using picograms of mRNA from human cell lysates. Low mRNA input requirements and sample multiplexing capabilities has made time- and concentrat...

Identification of vascular disruptor compounds by analysis in zebrafish embryos and mouse embryonic endothelial cells

EPA Science Inventory

The large number of diverse chemicals in production or in the environment has motivated medium to high throughput in vitro or small animal approaches to efficiently profile chemical-biological interactions and to utilize this information to assess risks of chemical exposures on h...

NCCT ToxCast Program for Nanomaterial Prioritization: High-Throughput Screening, Consideration of Exposure, and Bioactivity Profiling/Modeling

EPA Science Inventory

Find relationships between bioactivities and NM characteristics or testing conditions. Recommend a dose metric for NMs in vitro studies. Establish associations to in vivo toxicity or pathways identified from testing of conventional chemicals with ToxCast HTS methods. May be abl...

Effects of dietary plant-derived phytonutrients on the genome-wide profiles and coccidiosis resistance in the broiler chickens

USDA-ARS?s Scientific Manuscript database

The present study was conducted to investigate the effects of dietary plant-derived phytonutrients, carvacrol, cinnamaldehyde and Capsicum oleoresin, on the translational regulation of genes associated with immunology, physiology and metabolism using high-throughput microarray analysis and in vivo d...

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...

Biological profiling and dose-response modeling tools, characterizing uncertainty

EPA Science Inventory

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

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...

A Comparison of Machine Learning Algorithms for Chemical Toxicity Classification Using a Simulated Multi-Scale Data Model

EPA Science Inventory

Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in hig...

Predictive Signatures of Developmental Toxicity Modeled with HTS Data from ToxCast™ Bioactivity Profiles

EPA Science Inventory

The EPA ToxCast™ research program uses a high-throughput screening (HTS) approach for predicting the toxicity of large numbers of chemicals. Phase-I contains 309 well-characterized chemicals which are mostly pesticides tested in over 600 assays of different molecular targets, cel...

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.

High-Throughput Quantitative Lipidomics Analysis of Nonesterified Fatty Acids in Plasma by LC-MS.

PubMed

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

2017-01-01

Nonesterified fatty acids are important biological molecules which have multiple functions such as energy storage, gene regulation, or cell signaling. Comprehensive profiling of nonesterified fatty acids in biofluids can facilitate studying and understanding their roles in biological systems. For these reasons, we have developed and validated a high-throughput, nontargeted lipidomics method coupling liquid chromatography to high-resolution mass spectrometry for quantitative analysis of nonesterified fatty acids. Sufficient chromatographic separation is achieved to separate positional isomers such as polyunsaturated and branched-chain species and quantify a wide range of nonesterified fatty acids in human plasma samples. However, this method is not limited only to these fatty acid species and offers the possibility to perform untargeted screening of additional nonesterified fatty acid species.

Experiments and Analyses of Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang; Sen, Satyabrata

Dedicated wide-area network connections are increasingly employed in high-performance computing and big data scenarios. One might expect the performance and dynamics of data transfers over such connections to be easy to analyze due to the lack of competing traffic. However, non-linear transport dynamics and end-system complexities (e.g., multi-core hosts and distributed filesystems) can in fact make analysis surprisingly challenging. We present extensive measurements of memory-to-memory and disk-to-disk file transfers over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory-to-memory transfers, profiles of both TCP and UDT throughput as a function of RTT show concavemore » and convex regions; large buffer sizes and more parallel flows lead to wider concave regions, which are highly desirable. TCP and UDT both also display complex throughput dynamics, as indicated by their Poincare maps and Lyapunov exponents. For disk-to-disk transfers, we determine that high throughput can be achieved via a combination of parallel I/O threads, parallel network threads, and direct I/O mode. Our measurements also show that Lustre filesystems can be mounted over long-haul connections using LNet routers, although challenges remain in jointly optimizing file I/O and transport method parameters to achieve peak throughput.« less

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.

High-resolution phylogenetic microbial community profiling

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

Singer, Esther; Bushnell, Brian; Coleman-Derr, Devin

Over the past decade, high-throughput short-read 16S rRNA gene amplicon sequencing has eclipsed clone-dependent long-read Sanger sequencing for microbial community profiling. The transition to new technologies has provided more quantitative information at the expense of taxonomic resolution with implications for inferring metabolic traits in various ecosystems. We applied single-molecule real-time sequencing for microbial community profiling, generating full-length 16S rRNA gene sequences at high throughput, which we propose to name PhyloTags. We benchmarked and validated this approach using a defined microbial community. When further applied to samples from the water column of meromictic Sakinaw Lake, we show that while community structuresmore » at the phylum level are comparable between PhyloTags and Illumina V4 16S rRNA gene sequences (iTags), variance increases with community complexity at greater water depths. PhyloTags moreover allowed less ambiguous classification. Last, a platform-independent comparison of PhyloTags and in silico generated partial 16S rRNA gene sequences demonstrated significant differences in community structure and phylogenetic resolution across multiple taxonomic levels, including a severe underestimation in the abundance of specific microbial genera involved in nitrogen and methane cycling across the Lake's water column. Thus, PhyloTags provide a reliable adjunct or alternative to cost-effective iTags, enabling more accurate phylogenetic resolution of microbial communities and predictions on their metabolic potential.« less

High-resolution phylogenetic microbial community profiling

DOE PAGES

Singer, Esther; Bushnell, Brian; Coleman-Derr, Devin; ...

2016-02-09

Over the past decade, high-throughput short-read 16S rRNA gene amplicon sequencing has eclipsed clone-dependent long-read Sanger sequencing for microbial community profiling. The transition to new technologies has provided more quantitative information at the expense of taxonomic resolution with implications for inferring metabolic traits in various ecosystems. We applied single-molecule real-time sequencing for microbial community profiling, generating full-length 16S rRNA gene sequences at high throughput, which we propose to name PhyloTags. We benchmarked and validated this approach using a defined microbial community. When further applied to samples from the water column of meromictic Sakinaw Lake, we show that while community structuresmore » at the phylum level are comparable between PhyloTags and Illumina V4 16S rRNA gene sequences (iTags), variance increases with community complexity at greater water depths. PhyloTags moreover allowed less ambiguous classification. Last, a platform-independent comparison of PhyloTags and in silico generated partial 16S rRNA gene sequences demonstrated significant differences in community structure and phylogenetic resolution across multiple taxonomic levels, including a severe underestimation in the abundance of specific microbial genera involved in nitrogen and methane cycling across the Lake's water column. Thus, PhyloTags provide a reliable adjunct or alternative to cost-effective iTags, enabling more accurate phylogenetic resolution of microbial communities and predictions on their metabolic potential.« less

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

PubMed Central

Giacomotto, Jean; Ségalat, Laurent

2010-01-01

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

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.

Chemical genomic profiling via barcode sequencing to predict compound mode of action

PubMed Central

Piotrowski, Jeff S.; Simpkins, Scott W.; Li, Sheena C.; Deshpande, Raamesh; McIlwain, Sean; Ong, Irene; Myers, Chad L.; Boone, Charlie; Andersen, Raymond J.

2015-01-01

Summary Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds. PMID:25618354

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

PubMed Central

Shockley, Keith R.

2014-01-01

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

Effects of Perfluorooctanoic Acid on Metabolic Profiles in Brain and Liver of Mouse Revealed by a High-throughput Targeted Metabolomics Approach

NASA Astrophysics Data System (ADS)

Yu, Nanyang; Wei, Si; Li, Meiying; Yang, Jingping; Li, Kan; Jin, Ling; Xie, Yuwei; Giesy, John P.; Zhang, Xiaowei; Yu, Hongxia

2016-04-01

Perfluorooctanoic acid (PFOA), a perfluoroalkyl acid, can result in hepatotoxicity and neurobehavioral effects in animals. The metabolome, which serves as a connection among transcriptome, proteome and toxic effects, provides pathway-based insights into effects of PFOA. Since understanding of changes in the metabolic profile during hepatotoxicity and neurotoxicity were still incomplete, a high-throughput targeted metabolomics approach (278 metabolites) was used to investigate effects of exposure to PFOA for 28 d on brain and liver of male Balb/c mice. Results of multivariate statistical analysis indicated that PFOA caused alterations in metabolic pathways in exposed individuals. Pathway analysis suggested that PFOA affected metabolism of amino acids, lipids, carbohydrates and energetics. Ten and 18 metabolites were identified as potential unique biomarkers of exposure to PFOA in brain and liver, respectively. In brain, PFOA affected concentrations of neurotransmitters, including serotonin, dopamine, norepinephrine, and glutamate in brain, which provides novel insights into mechanisms of PFOA-induced neurobehavioral effects. In liver, profiles of lipids revealed involvement of β-oxidation and biosynthesis of saturated and unsaturated fatty acids in PFOA-induced hepatotoxicity, while alterations in metabolism of arachidonic acid suggesting potential of PFOA to cause inflammation response in liver. These results provide insight into the mechanism and biomarkers for PFOA-induced effects.

Ozone Mapping and Profiler Suite: using mission performance data to refine predictive contamination modeling

NASA Astrophysics Data System (ADS)

Devaud, Genevieve; Jaross, Glen

2014-09-01

On October 28, 2011, the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched at Vandenberg Air Force base aboard a United Launch Alliance Delta II rocket. Included among the five instruments was the Ozone Mapping and Profiler Suite (OMPS), an advanced suite of three hyperspectral instruments built by Ball Aerospace and Technologies Corporation (BATC) for the NASA Goddard Space Flight Center. Molecular transport modeling is used to predict optical throughput changes due to contaminant accumulation to ensure performance margin to End Of Life. The OMPS Nadir Profiler, operating at the lowest wavelengths of 250 - 310 nm, is most sensitive to contaminant accumulation. Geometry, thermal profile and material properties must be accurately modeled in order to have confidence in the results, yet it is well known that the complex chemistry and process dependent variability of aerospace materials presents a substantial challenge to the modeler. Assumptions about the absorption coefficients, desorption and diffusion kinetics of outgassing species from polymeric materials dramatically affect the model predictions, yet it is rare indeed that on-mission data is analyzed at a later date as a means to compare with modeling results. Optical throughput measurements for the Ozone and Mapping Profiler Suite on the Suomi NPP Satellite indicate that optical throughput degradation between day 145 and day 858 is less than 0.5%. We will show how assumptions about outgassing rates and desorption energies, in particular, dramatically affect the modeled optical throughput and what assumptions represent the on-orbit data.

Transfer of a Mycobacterium tuberculosis genotyping method, Spoligotyping, from a reverse line-blot hybridization, membrane-based assay to the Luminex multianalyte profiling system.

PubMed

Cowan, Lauren S; Diem, Lois; Brake, Mary Catherine; Crawford, Jack T

2004-01-01

Spoligotyping using Luminex technology was shown to be a highly reproducible method suitable for high-throughput analysis. Spoligotyping of 48 isolates using the traditional membrane-based assay and the Luminex assay yielded concordant results for all isolates. The Luminex platform provides greater flexibility and cost effectiveness than the membrane-based assay.

Metabolite Profiles and the Risk of Developing Diabetes

PubMed Central

Wang, Thomas J.; Larson, Martin G.; Vasan, Ramachandran S.; Cheng, Susan; Rhee, Eugene P.; McCabe, Elizabeth; Lewis, Gregory D.; Fox, Caroline S.; Jacques, Paul F.; Fernandez, Céline; O’Donnell, Christopher J.; Carr, Stephen A.; Mootha, Vamsi K.; Florez, Jose C.; Souza, Amanda; Melander, Olle; Clish, Clary B.; Gerszten, Robert E.

2011-01-01

Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines, and other polar metabolites were profiled in baseline specimens using liquid chromatography-tandem mass spectrometry. Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly-significant associations with future diabetes: isoleucine, leucine, valine, tyrosine, and phenylalanine. A combination of three amino acids predicted future diabetes (>5-fold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential importance of amino acid metabolism early in the pathogenesis of diabetes, and suggest that amino acid profiles could aid in diabetes risk assessment. PMID:21423183

Metabolite profiles and the risk of developing diabetes.

PubMed

Wang, Thomas J; Larson, Martin G; Vasan, Ramachandran S; Cheng, Susan; Rhee, Eugene P; McCabe, Elizabeth; Lewis, Gregory D; Fox, Caroline S; Jacques, Paul F; Fernandez, Céline; O'Donnell, Christopher J; Carr, Stephen A; Mootha, Vamsi K; Florez, Jose C; Souza, Amanda; Melander, Olle; Clish, Clary B; Gerszten, Robert E

2011-04-01

Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography-tandem mass spectrometry (LC-MS). Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly significant associations with future diabetes: isoleucine, leucine, valine, tyrosine and phenylalanine. A combination of three amino acids predicted future diabetes (with a more than fivefold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment.

Comparison of diverse nanomaterial bioactivity profiles based on high-throughput screening (HTS) in ToxCast™ (FutureToxII)

EPA Science Inventory

Most nanomaterials (NMs) in commerce lack hazard data. Efficient NM testing requires suitable toxicity tests for prioritization of NMs to be tested. The EPA’s ToxCast program is screening NM bioactivities and ranking NMs by their bioactivities to inform targeted testing planning....

Analysis of Chemical Bioactivity through In Vitro Profiling using ToxCast and Tox21 High-Throughput Screening (China tox. conf. TATT)

EPA Science Inventory

Safety assessment of drugs and environmental chemicals relies extensively on animal testing. However, the quantity of chemicals needing assessment and challenges of species extrapolation drive the development of alternative approaches. The EPA’s ToxCast and the multiagency Tox21 ...

Identifying Functionally Linked Gene Modules Within Biological Pathways Assessed by ToxCast In Vitro Assays

EPA Science Inventory

The US EPA ToxCast program is using in vitro high-throughput screening assays to profile the bioactivity of environmental chemicals, with the ultimate goal of predicting in vivo toxicity. We hypothesize that in modeling toxicity it will be more constructive to understand the pert...

Using the ToxMiner Database for Identifying Disease-Gene Associations in the ToxCast Dataset

EPA Science Inventory

The US EPA ToxCast program is using in vitro, high-throughput screening (HTS) to profile and model the bioactivity of environmental chemicals. The main goal of the ToxCast program is to generate predictive signatures of toxicity that ultimately provide rapid and cost-effective me...

Application of the ToxMiner Database: Network Analysis Linking the ToxCast Chemicals to Known Disease-Gene Associations

EPA Science Inventory

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effecti...

Endocrine Profiling and Prioritization of Environmental Chemicals Using ToxCast Data

EPA Science Inventory

The prioritization of chemicals for toxicity testing is a primary goal of the U.S. EPA’s ToxCast™ program. Phase I of ToxCast utilized a battery of 467 in vitro, high-throughput screening assays to assess 309 environmental chemicals. One important mode of action leading to toxici...

Transcriptome profiling to identify ATRA-responsive genes in human iPSC-derived endoderm for high-throughput point of departure analysis (SOT Annual Meeting)

EPA Science Inventory

Toxicological tipping points occur at chemical concentrations that overwhelm a cell’s adaptive response leading to permanent effects. We focused on retinoid signaling in differentiating endoderm to identify developmental pathways for tipping point analysis. Human induced pluripot...

Analysis of petunia hybrida in response to salt stress using high throughput RNA sequencing

USDA-ARS?s Scientific Manuscript database

Salt and drought are among the greatest challenges to crop and native plants in meeting their yield and reproductive potentials. DNA sequencing-enabled transcriptome profiling provides a means of assessing what genes are responding to salt or drought stress so as to better understand the molecular ...

A multi-analyte profile of serum proteins to screen for toxicological effects of anticholinesterase insecticides in the rat

EPA Science Inventory

The development of high throughput biochemical screens could be useful to assess the broad spectrum of physiological effects of environmental toxicants. To explore the prospect of using a screen in an in vivo exposure scenario, we applied a commercially available multianalyte pro...

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...

Strategies for integrating transcriptional profiling into high throughput toxicity testing (SOT Symposium Workshop presentation)

EPA Science Inventory

Presentation Description: The release of the National Research Council’s Report “Toxicity Testing in the 21st Century: A Vision and a Strategy” in 2007 initiated a broad-based movement in the toxicology community to re-think how toxicity testing and risk assessment are performed....

Profiling Environmental Chemicals for Activity in the Antioxidant Response Element Signaling Pathway Using a High-Throughput Screening Approach

EPA Science Inventory

1 ABSTRACT 2 3 BACKGROUND: Oxidative stress has been implicated in the pathogenesis of a variety 4 of diseases ranging from cancer to neurodegeneration, highlighti.ng the need to identify 5 chemicals that can induce this effect. The antioxidant response element (ARE)...

Reducing the critical particle diameter in (highly) asymmetric sieve-based lateral displacement devices.

PubMed

Dijkshoorn, J P; Schutyser, M A I; Sebris, M; Boom, R M; Wagterveld, R M

2017-10-26

Deterministic lateral displacement technology was originally developed in the realm of microfluidics, but has potential for larger scale separation as well. In our previous studies, we proposed a sieve-based lateral displacement device inspired on the principle of deterministic lateral displacement. The advantages of this new device is that it gives a lower pressure drop, lower risk of particle accumulation, higher throughput and is simpler to manufacture. However, until now this device has only been investigated for its separation of large particles of around 785 µm diameter. To separate smaller particles, we investigate several design parameters for their influence on the critical particle diameter. In a dimensionless evaluation, device designs with different geometry and dimensions were compared. It was found that sieve-based lateral displacement devices are able to displace particles due to the crucial role of the flow profile, despite of their unusual and asymmetric design. These results demonstrate the possibility to actively steer the velocity profile in order to reduce the critical diameter in deterministic lateral displacement devices, which makes this separation principle more accessible for large-scale, high throughput applications.

Editor's Highlight: High-Throughput Functional Genomics Identifies Modulators of TCE Metabolite Genotoxicity and Candidate Susceptibility Genes.

PubMed

De La Rosa, Vanessa Y; Asfaha, Jonathan; Fasullo, Michael; Loguinov, Alex; Li, Peng; Moore, Lee E; Rothman, Nathaniel; Nakamura, Jun; Swenberg, James A; Scelo, Ghislaine; Zhang, Luoping; Smith, Martyn T; Vulpe, Chris D

2017-11-01

Trichloroethylene (TCE), an industrial chemical and environmental contaminant, is a human carcinogen. Reactive metabolites are implicated in renal carcinogenesis associated with TCE exposure, yet the toxicity mechanisms of these metabolites and their contribution to cancer and other adverse effects remain unclear. We employed an integrated functional genomics approach that combined functional profiling studies in yeast and avian DT40 cell models to provide new insights into the specific mechanisms contributing to toxicity associated with TCE metabolites. Genome-wide profiling studies in yeast identified the error-prone translesion synthesis (TLS) pathway as an import mechanism in response to TCE metabolites. The role of TLS DNA repair was further confirmed by functional profiling in DT40 avian cell lines, but also revealed that TLS and homologous recombination DNA repair likely play competing roles in cellular susceptibility to TCE metabolites in higher eukaryotes. These DNA repair pathways are highly conserved between yeast, DT40, and humans. We propose that in humans, mutagenic TLS is favored over homologous recombination repair in response to TCE metabolites. The results of these studies contribute to the body of evidence supporting a mutagenic mode of action for TCE-induced renal carcinogenesis mediated by reactive metabolites in humans. Our approach illustrates the potential for high-throughput in vitro functional profiling in yeast to elucidate toxicity pathways (molecular initiating events, key events) and candidate susceptibility genes for focused study. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Rapid identification and validation of novel targeted approaches for Glioblastoma: A combined ex vivo-in vivo pharmaco-omic model.

PubMed

Daher, Ahmad; de Groot, John

2018-01-01

Tumor heterogeneity is a major factor in glioblastoma's poor response to therapy and seemingly inevitable recurrence. Only two glioblastoma drugs have received Food and Drug Administration approval since 1998, highlighting the urgent need for new therapies. Profiling "omics" analyses have helped characterize glioblastoma molecularly and have thus identified multiple molecular targets for precision medicine. These molecular targets have influenced clinical trial design; many "actionable" mutation-focused trials are underway, but because they have not yet led to therapeutic breakthroughs, new strategies for treating glioblastoma, especially those with a pharmacological functional component, remain in high demand. In that regard, high-throughput screening that allows for expedited preclinical drug testing and the use of GBM models that represent tumor heterogeneity more accurately than traditional cancer cell lines is necessary to maximize the successful translation of agents into the clinic. High-throughput screening has been successfully used in the testing, discovery, and validation of potential therapeutics in various cancer models, but it has not been extensively utilized in glioblastoma models. In this report, we describe the basic aspects of high-throughput screening and propose a modified high-throughput screening model in which ex vivo and in vivo drug testing is complemented by post-screening pharmacological, pan-omic analysis to expedite anti-glioma drugs' preclinical testing and develop predictive biomarker datasets that can aid in personalizing glioblastoma therapy and inform clinical trial design. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel Inducers of Fetal Globin Identified through High Throughput Screening (HTS) Are Active In Vivo in Anemic Baboons and Transgenic Mice

PubMed Central

Boosalis, Michael S.; Sangerman, Jose I.; White, Gary L.; Wolf, Roman F.; Shen, Ling; Dai, Yan; White, Emily; Makala, Levi H.; Li, Biaoru; Pace, Betty S.; Nouraie, Mehdi; Faller, Douglas V.; Perrine, Susan P.

2015-01-01

High-level fetal (γ) globin expression ameliorates clinical severity of the beta (β) hemoglobinopathies, and safe, orally-bioavailable γ-globin inducing agents would benefit many patients. We adapted a LCR-γ-globin promoter-GFP reporter assay to a high-throughput robotic system to evaluate five diverse chemical libraries for this activity. Multiple structurally- and functionally-diverse compounds were identified which activate the γ-globin gene promoter at nanomolar concentrations, including some therapeutics approved for other conditions. Three candidates with established safety profiles were further evaluated in erythroid progenitors, anemic baboons and transgenic mice, with significant induction of γ-globin expression observed in vivo. A lead candidate, Benserazide, emerged which demonstrated > 20-fold induction of γ-globin mRNA expression in anemic baboons and increased F-cell proportions by 3.5-fold in transgenic mice. Benserazide has been used chronically to inhibit amino acid decarboxylase to enhance plasma levels of L-dopa. These studies confirm the utility of high-throughput screening and identify previously unrecognized fetal globin inducing candidates which can be developed expediently for treatment of hemoglobinopathies. PMID:26713848

Transfer of a Mycobacterium tuberculosis Genotyping Method, Spoligotyping, from a Reverse Line-Blot Hybridization, Membrane-Based Assay to the Luminex Multianalyte Profiling System

PubMed Central

Cowan, Lauren S.; Diem, Lois; Brake, Mary Catherine; Crawford, Jack T.

2004-01-01

Spoligotyping using Luminex technology was shown to be a highly reproducible method suitable for high-throughput analysis. Spoligotyping of 48 isolates using the traditional membrane-based assay and the Luminex assay yielded concordant results for all isolates. The Luminex platform provides greater flexibility and cost effectiveness than the membrane-based assay. PMID:14715809

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.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

Application of the ToxMiner Database: Network Analysis of Linkage between ToxCast Phase I Chemicals and Thyroid Related Disease Outcomes

EPA Science Inventory

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effecti...

Gene Expression Analysis of Copper Tolerance and Wood Decay in the Brown Rot Fungus Fibroporia radiculosa

Treesearch

J. D. Tang; L. A. Parker; A. D. Perkins; T. S. Sonstegard; S. G. Schroeder; D. D. Nicholas; S. V. Diehl

2013-01-01

High-throughput transcriptomics was used to identify Fibroporia radiculosa genes that were differentially regulated during colonization of wood treated with a copper-based preservative. The transcriptome was profiled at two time points while the fungus was growing on wood treated with micronized copper quat (MCQ). A total of 917 transcripts were...

Biological profiling of the ToxCast Phase II Chemical Library in Primary Human Cell Co-Culture Systems

EPA Science Inventory

The U.S. EPA’s ToxCast research project was developed to address the need for high-throughput testing of chemicals and a pathway-based approach to hazard screening. Phase I of ToxCast tested over 300 unique compounds (mostly pesticides and antimicrobials). With the addition of Ph...

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

PubMed Central

2014-01-01

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

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

PubMed

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

2014-03-05

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

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

New Era of Studying RNA Secondary Structure and Its Influence on Gene Regulation in Plants.

PubMed

Yang, Xiaofei; Yang, Minglei; Deng, Hongjing; Ding, Yiliang

2018-01-01

The dynamic structure of RNA plays a central role in post-transcriptional regulation of gene expression such as RNA maturation, degradation, and translation. With the rise of next-generation sequencing, the study of RNA structure has been transformed from in vitro low-throughput RNA structure probing methods to in vivo high-throughput RNA structure profiling. The development of these methods enables incremental studies on the function of RNA structure to be performed, revealing new insights of novel regulatory mechanisms of RNA structure in plants. Genome-wide scale RNA structure profiling allows us to investigate general RNA structural features over 10s of 1000s of mRNAs and to compare RNA structuromes between plant species. Here, we provide a comprehensive and up-to-date overview of: (i) RNA structure probing methods; (ii) the biological functions of RNA structure; (iii) genome-wide RNA structural features corresponding to their regulatory mechanisms; and (iv) RNA structurome evolution in plants.

High-throughput screening of PLGA thin films utilizing hydrophobic fluorescent dyes for hydrophobic drug compounds.

PubMed

Steele, Terry W J; Huang, Charlotte L; Kumar, Saranya; Widjaja, Effendi; Chiang Boey, Freddy Yin; Loo, Joachim S C; Venkatraman, Subbu S

2011-10-01

Hydrophobic, antirestenotic drugs such as paclitaxel (PCTX) and rapamycin are often incorporated into thin film coatings for local delivery using implantable medical devices and polymers such as drug-eluting stents and balloons. Selecting the optimum coating formulation through screening the release profile of these drugs in thin films is time consuming and labor intensive. We describe here a high-throughput assay utilizing three model hydrophobic fluorescent compounds: fluorescein diacetate (FDAc), coumarin-6, and rhodamine 6G that were incorporated into poly(d,l-lactide-co-glycolide) (PLGA) and PLGA-polyethylene glycol films. Raman microscopy determined the hydrophobic fluorescent dye distribution within the PLGA thin films in comparison with that of PCTX. Their subsequent release was screened in a high-throughput assay and directly compared with HPLC quantification of PCTX release. It was observed that PCTX controlled-release kinetics could be mimicked by a hydrophobic dye that had similar octanol-water partition coefficient values and homogeneous dissolution in a PLGA matrix as the drug. In particular, FDAc was found to be the optimal hydrophobic dye at modeling the burst release as well as the total amount of PCTX released over a period of 30 days. Copyright © 2011 Wiley-Liss, Inc.

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

PubMed

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

2015-12-01

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

Multicapillary SDS-gel electrophoresis for the analysis of fluorescently labeled mAb preparations: a high throughput quality control process for the production of QuantiPlasma and PlasmaScan mAb libraries.

PubMed

Székely, Andrea; Szekrényes, Akos; Kerékgyártó, Márta; Balogh, Attila; Kádas, János; Lázár, József; Guttman, András; Kurucz, István; Takács, László

2014-08-01

Molecular heterogeneity of mAb preparations is the result of various co- and post-translational modifications and to contaminants related to the production process. Changes in molecular composition results in alterations of functional performance, therefore quality control and validation of therapeutic or diagnostic protein products is essential. A special case is the consistent production of mAb libraries (QuantiPlasma™ and PlasmaScan™) for proteome profiling, quality control of which represents a challenge because of high number of mAbs (>1000). Here, we devise a generally applicable multicapillary SDS-gel electrophoresis process for the analysis of fluorescently labeled mAb preparations for the high throughput quality control of mAbs of the QuantiPlasma™ and PlasmaScan™ libraries. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Qgui: A high-throughput interface for automated setup and analysis of free energy calculations and empirical valence bond simulations in biological systems.

PubMed

Isaksen, Geir Villy; Andberg, Tor Arne Heim; Åqvist, Johan; Brandsdal, Bjørn Olav

2015-07-01

Structural information and activity data has increased rapidly for many protein targets during the last decades. In this paper, we present a high-throughput interface (Qgui) for automated free energy and empirical valence bond (EVB) calculations that use molecular dynamics (MD) simulations for conformational sampling. Applications to ligand binding using both the linear interaction energy (LIE) method and the free energy perturbation (FEP) technique are given using the estrogen receptor (ERα) as a model system. Examples of free energy profiles obtained using the EVB method for the rate-limiting step of the enzymatic reaction catalyzed by trypsin are also shown. In addition, we present calculation of high-precision Arrhenius plots to obtain the thermodynamic activation enthalpy and entropy with Qgui from running a large number of EVB simulations. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Multiplexing a high-throughput liability assay to leverage efficiencies.

PubMed

Herbst, John; Anthony, Monique; Stewart, Jeremy; Connors, David; Chen, Taosheng; Banks, Martyn; Petrillo, Edward W; Agler, Michele

2009-06-01

In order to identify potential cytochrome P-450 3A4 (drug-metabolizing enzyme) inducers at an early stage of the drug discovery process, a cell-based transactivation high-throughput luciferase reporter assay for the human pregnane X receptor (PXR) in HepG2 cells has been implemented and multiplexed with a viability end point for data interpretation, as part of a Lead Profiling portfolio of assays. As a routine part of Lead Profiling operations, assays are periodically evaluated for utility as well as for potential improvements in technology or process. We used a recent evaluation of our PXR-transactivation assay as a model for the application of Lean Thinking-based process analysis to lab-bench assay optimization and automation. This resulted in the development of a 384-well multiplexed homogeneous assay simultaneously detecting PXR transactivation and HepG2 cell cytotoxicity. In order to multiplex fluorescent and luminescent read-outs, modifications to each assay were necessary, which included optimization of multiple assay parameters such as cell density, plate type, and reagent concentrations. Subsequently, a set of compounds including known cytotoxic compounds and PXR inducers were used to validate the multiplexed assay. Results from the multiplexed assay correlate well with those from the singleplexed assay formats measuring PXR transactivation and viability separately. Implementation of the multiplexed assay for routine compound profiling provides improved data quality, sample conservation, cost savings, and resource efficiencies.

Hit to lead account of the discovery of bisbenzamide and related ureidobenzamide inhibitors of Rho kinase.

PubMed

Morwick, Tina; Büttner, Frank H; Cywin, Charles L; Dahmann, Georg; Hickey, Eugene; Jakes, Scott; Kaplita, Paul; Kashem, Mohammed A; Kerr, Steven; Kugler, Stanley; Mao, Wang; Marshall, Daniel; Paw, Zofia; Shih, Cheng-Kon; Wu, Frank; Young, Erick

2010-01-28

A highly selective series of bisbenzamide inhibitors of Rho-associated coiled-coil forming protein kinase (ROCK) and a related ureidobenzamide series, both identified by high throughput screening (HTS), are described. Details of the hit validation and lead generation process, including structure-activity relationship (SAR) studies, a selectivity assessment, target-independent profiling (TIP) results, and an analysis of functional activity using a rat aortic ring assay are discussed.

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

PubMed

Chiaravalli, Jeanne; Glickman, J Fraser

2017-08-01

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

Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome.

PubMed

Chetwynd, Andrew J; David, Arthur; Hill, Elizabeth M; Abdul-Sada, Alaa

2014-10-01

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra-high-pressure liquid chromatography-nanoelectrospray ionization-time-of-flight MS (nUHPLC-nESI-TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC-ESI-TOFMS, nUHPLC-nESI-TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000-fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC-nESI-TOFMS, supporting implementation of this platform as a novel approach for high-throughput (xeno)metabolomics. Copyright © 2014 John Wiley & Sons, Ltd.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

Should we treat the ionome as a combination of individual elements, or should we be deriving novel combined traits?

USDA-ARS?s Scientific Manuscript database

It has been more than 10 years since the concept of the ionome, all of the mineral nutrients in a cell tissue or organism, was introduced. In the intervening years, ionomics, high throughput elemental profiling, has been used to analyze over 400,000 samples from at least 7 different organisms. There...

Computation Modeling of Limb-bud Dysmorphogenesis: Predicting Cellular Dynamics and Key Events in Developmental Toxicity with a Multicellular Systems Model (FutureToxII)

EPA Science Inventory

Congenital limb malformations are among the most frequent malformation occurs in humans, with a frequency of about 1 in 500 to 1 in 1000 human live births. ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput (HTS) and computational methods that...

Extending the Derek-Meteor Workflow to Predict Chemical-Toxicity Space Impacted by Metabolism: Application to ToxCast and Tox21 Chemical Inventories

EPA Science Inventory

A central aim of EPA’s ToxCast project is to use in vitro high-throughput screening (HTS) profiles to build predictive models of in vivo toxicity. Where assays lack metabolic capability, such efforts may need to anticipate the role of metabolic activation (or deactivation). A wo...

Using the ToxMiner Database for a Network Analysis of Linkage between ToxCast Phase I Chemicals and Thyroid Related Disease Outcomes

EPA Science Inventory

The US EPA ToxCast program is using in vitro, high-throughput screening (HTS) to profile and model the bioactivity of environmental chemicals. The main goal of the ToxCast program is to generate predictive signatures of toxicity that ultimately provide rapid and cost-effective me...

Identification of novel IP receptor agonists using historical ligand biased chemical arrays.

PubMed

McKeown, Stephen C; Charlton, Steven J; Cox, Brian; Fitch, Helen; Howson, Christopher D; Leblanc, Catherine; Meyer, Arndt; Rosethorne, Elizabeth M; Stanley, Emily

2014-05-15

By considering published structural information we have designed high throughput biaryl lipophilic acid arrays leveraging facile chemistry to expedite their synthesis. We rapidly identified multiple hits which were of suitable IP agonist potency. These relatively simple and strategically undecorated molecules present an ideal opportunity for optimization towards our target candidate profile. Copyright © 2014 Elsevier Ltd. All rights reserved.

EPA's ToxCast Project: Lessons learned and future directions for use of HTS in predicting in vivo toxicology -- A Chemical Perspective

EPA Science Inventory

U.S. EPA’s ToxCast and the related Tox21 projects are employing high-throughput screening (HTS) technologies to profile thousands of chemicals, which in turn serve as probes of a wide diversity of targets, pathways and mechanisms related to toxicity. Initial models relating ToxCa...

In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing

PubMed Central

Aguilar, Carlos A.; Shcherbina, Anna; Ricke, Darrell O.; Pop, Ramona; Carrigan, Christopher T.; Gifford, Casey A.; Urso, Maria L.; Kottke, Melissa A.; Meissner, Alexander

2015-01-01

Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual’s muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing. PMID:26381351

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen

PubMed Central

Plouffe, David; Brinker, Achim; McNamara, Case; Henson, Kerstin; Kato, Nobutaka; Kuhen, Kelli; Nagle, Advait; Adrián, Francisco; Matzen, Jason T.; Anderson, Paul; Nam, Tae-gyu; Gray, Nathanael S.; Chatterjee, Arnab; Janes, Jeff; Yan, S. Frank; Trager, Richard; Caldwell, Jeremy S.; Schultz, Peter G.; Zhou, Yingyao; Winzeler, Elizabeth A.

2008-01-01

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of ≈1.7 million compounds, we identified a diverse collection of ≈6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 μM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities. PMID:18579783

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.

Translational bioinformatics in the cloud: an affordable alternative

PubMed Central

2010-01-01

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

The Role of Mass Spectrometry-Based Metabolomics in Medical Countermeasures Against Radiation

PubMed Central

Patterson, Andrew D.; Lanz, Christian; Gonzalez, Frank J.; Idle, Jeffrey R.

2013-01-01

Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry (CMCR) was established to develop field-deployable biodosimeters based, in principle, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter. PMID:19890938

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

PubMed

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

2015-12-15

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

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.

ChiMS: Open-source instrument control software platform on LabVIEW for imaging/depth profiling mass spectrometers.

PubMed

Cui, Yang; Hanley, Luke

2015-06-01

ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science.

ChiMS: Open-source instrument control software platform on LabVIEW for imaging/depth profiling mass spectrometers

PubMed Central

Cui, Yang; Hanley, Luke

2015-01-01

ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science. PMID:26133872

ChiMS: Open-source instrument control software platform on LabVIEW for imaging/depth profiling mass spectrometers

NASA Astrophysics Data System (ADS)

Cui, Yang; Hanley, Luke

2015-06-01

ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science.

Mechanisms of Abnormal Growth Regulation in Prostatic Adenocarcinoma Using Abi1/Hssh3bp1 Conditional Knockout Mouse Model

DTIC Science & Technology

2009-06-01

density lipoprotein uptake and cholesterol accumulation by macrophages differentiated from human monocytes with macrophage-colony-stimulating factor (M...model will likely have high impact on the prostate cancer research field including development of novel potential drug therapies. Our model will...Shin, and B.J. Mayer. 2007. High -throughput phosphotyrosine profiling using SH2 domains. Mol Cell. 26:899-915. Macoska, J.A., J. Xu, D. Ziemnicka, T.S

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.

Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells.

PubMed

Gatto, Sole; Puri, Pier Lorenzo; Malecova, Barbora

2017-01-01

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

Plastic straw: future of high-speed signaling

NASA Astrophysics Data System (ADS)

Song, Ha Il; Jin, Huxian; Bae, Hyeon-Min

2015-11-01

The ever-increasing demand for bandwidth triggered by mobile and video Internet traffic requires advanced interconnect solutions satisfying functional and economic constraints. A new interconnect called E-TUBE is proposed as a cost-and-power-effective all-electrical-domain wideband waveguide solution for high-speed high-volume short-reach communication links. The E-TUBE achieves an unprecedented level of performance in terms of bandwidth-per-carrier frequency, power, and density without requiring a precision manufacturing process unlike conventional optical/waveguide solutions. The E-TUBE exhibits a frequency-independent loss-profile of 4 dB/m and has nearly 20-GHz bandwidth over the V band. A single-sideband signal transmission enabled by the inherent frequency response of the E-TUBE renders two-times data throughput without any physical overhead compared to conventional radio frequency communication technologies. This new interconnect scheme would be attractive to parties interested in high throughput links, including but not limited to, 100/400 Gbps chip-to-chip communications.

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

PubMed Central

Bray, Mark-Anthony; Singh, Shantanu; Han, Han; Davis, Chadwick T.; Borgeson, Blake; Hartland, Cathy; Kost-Alimova, Maria; Gustafsdottir, Sigrun M.; Gibson, Christopher C.; Carpenter, Anne E.

2016-01-01

In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, a morphological profiling assay multiplexing six fluorescent dyes imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multi-well plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Then, automated image analysis software identifies individual cells and measures ~1,500 morphological features (various measures of size, shape, texture, intensity, etc.) to produce a rich profile suitable for detecting subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes two weeks; feature extraction and data analysis take an additional 1-2 weeks. PMID:27560178

Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

PubMed Central

Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

2012-01-01

Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

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

PubMed Central

Georgiou, Georgios

2016-01-01

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

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

Fully Automated Sample Preparation for Ultrafast N-Glycosylation Analysis of Antibody Therapeutics.

PubMed

Szigeti, Marton; Lew, Clarence; Roby, Keith; Guttman, Andras

2016-04-01

There is a growing demand in the biopharmaceutical industry for high-throughput, large-scale N-glycosylation profiling of therapeutic antibodies in all phases of product development, but especially during clone selection when hundreds of samples should be analyzed in a short period of time to assure their glycosylation-based biological activity. Our group has recently developed a magnetic bead-based protocol for N-glycosylation analysis of glycoproteins to alleviate the hard-to-automate centrifugation and vacuum-centrifugation steps of the currently used protocols. Glycan release, fluorophore labeling, and cleanup were all optimized, resulting in a <4 h magnetic bead-based process with excellent yield and good repeatability. This article demonstrates the next level of this work by automating all steps of the optimized magnetic bead-based protocol from endoglycosidase digestion, through fluorophore labeling and cleanup with high-throughput sample processing in 96-well plate format, using an automated laboratory workstation. Capillary electrophoresis analysis of the fluorophore-labeled glycans was also optimized for rapid (<3 min) separation to accommodate the high-throughput processing of the automated sample preparation workflow. Ultrafast N-glycosylation analyses of several commercially relevant antibody therapeutics are also shown and compared to their biosimilar counterparts, addressing the biological significance of the differences. © 2015 Society for Laboratory Automation and Screening.

Treatment Algorithms Based on Tumor Molecular Profiling: The Essence of Precision Medicine Trials.

PubMed

Le Tourneau, Christophe; Kamal, Maud; Tsimberidou, Apostolia-Maria; Bedard, Philippe; Pierron, Gaëlle; Callens, Céline; Rouleau, Etienne; Vincent-Salomon, Anne; Servant, Nicolas; Alt, Marie; Rouzier, Roman; Paoletti, Xavier; Delattre, Olivier; Bièche, Ivan

2016-04-01

With the advent of high-throughput molecular technologies, several precision medicine (PM) studies are currently ongoing that include molecular screening programs and PM clinical trials. Molecular profiling programs establish the molecular profile of patients' tumors with the aim to guide therapy based on identified molecular alterations. The aim of prospective PM clinical trials is to assess the clinical utility of tumor molecular profiling and to determine whether treatment selection based on molecular alterations produces superior outcomes compared with unselected treatment. These trials use treatment algorithms to assign patients to specific targeted therapies based on tumor molecular alterations. These algorithms should be governed by fixed rules to ensure standardization and reproducibility. Here, we summarize key molecular, biological, and technical criteria that, in our view, should be addressed when establishing treatment algorithms based on tumor molecular profiling for PM trials. © The Author 2015. Published by Oxford University Press.

MALDI-TOF MS Profiling-Advances in Species Identification of Pests, Parasites, and Vectors.

PubMed

Murugaiyan, Jayaseelan; Roesler, Uwe

2017-01-01

Invertebrate pests and parasites of humans, animals, and plants continue to cause serious diseases and remain as a high treat to agricultural productivity and storage. The rapid and accurate species identification of the pests and parasites are needed for understanding epidemiology, monitoring outbreaks, and designing control measures. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as a rapid, cost effective, and high throughput technique of microbial species identification in modern diagnostic laboratories. The development of soft ionization techniques and the release of commercial pattern matching software platforms has resulted in the exponential growth of applications in higher organisms including parasitology. The present review discusses the proof-of-principle experiments and various methods of MALDI MS profiling in rapid species identification of both laboratory and field isolates of pests, parasites and vectors.

MALDI-TOF MS Profiling-Advances in Species Identification of Pests, Parasites, and Vectors

PubMed Central

Murugaiyan, Jayaseelan; Roesler, Uwe

2017-01-01

Invertebrate pests and parasites of humans, animals, and plants continue to cause serious diseases and remain as a high treat to agricultural productivity and storage. The rapid and accurate species identification of the pests and parasites are needed for understanding epidemiology, monitoring outbreaks, and designing control measures. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling has emerged as a rapid, cost effective, and high throughput technique of microbial species identification in modern diagnostic laboratories. The development of soft ionization techniques and the release of commercial pattern matching software platforms has resulted in the exponential growth of applications in higher organisms including parasitology. The present review discusses the proof-of-principle experiments and various methods of MALDI MS profiling in rapid species identification of both laboratory and field isolates of pests, parasites and vectors. PMID:28555175

Functional annotation of chemical libraries across diverse biological processes.

PubMed

Piotrowski, Jeff S; Li, Sheena C; Deshpande, Raamesh; Simpkins, Scott W; Nelson, Justin; Yashiroda, Yoko; Barber, Jacqueline M; Safizadeh, Hamid; Wilson, Erin; Okada, Hiroki; Gebre, Abraham A; Kubo, Karen; Torres, Nikko P; LeBlanc, Marissa A; Andrusiak, Kerry; Okamoto, Reika; Yoshimura, Mami; DeRango-Adem, Eva; van Leeuwen, Jolanda; Shirahige, Katsuhiko; Baryshnikova, Anastasia; Brown, Grant W; Hirano, Hiroyuki; Costanzo, Michael; Andrews, Brenda; Ohya, Yoshikazu; Osada, Hiroyuki; Yoshida, Minoru; Myers, Chad L; Boone, Charles

2017-09-01

Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

Schizosaccharomyces pombe Polysome Profile Analysis and RNA Purification.

PubMed

Wolf, Dieter A; Bähler, Jürg; Wise, Jo Ann

2017-04-03

Polysome profile analysis is widely used by investigators studying the mechanism and regulation of translation. The method described here uses high-velocity centrifugation of whole cell extracts on linear sucrose gradients to separate 40S and 60S ribosomal subunits from 80S monosomes and polysomes. Cycloheximide is included in the lysis buffer to "freeze" polysomes by blocking translation. After centrifugation, the gradient is fractionated and RNA (and/or protein) is prepared from each fraction for subsequent analysis of individual species using northern or western blots. The entire RNA population in each fraction can be analyzed by hybridization to microarrays or by high-throughput RNA sequencing, and the proteins present can be identified by mass spectrometry analysis. © 2017 Cold Spring Harbor Laboratory Press.

A Near-Infrared Spectrometer to Measure Zodiacal Light Absorption Spectrum

NASA Technical Reports Server (NTRS)

Kutyrev, A. S.; Arendt, R.; Dwek, E.; Kimble, R.; Moseley, S. H.; Rapchun, D.; Silverberg, R. F.

2010-01-01

We have developed a high throughput infrared spectrometer for zodiacal light fraunhofer lines measurements. The instrument is based on a cryogenic dual silicon Fabry-Perot etalon which is designed to achieve high signal to noise Fraunhofer line profile measurements. Very large aperture silicon Fabry-Perot etalons and fast camera optics make these measurements possible. The results of the absorption line profile measurements will provide a model free measure of the zodiacal Light intensity in the near infrared. The knowledge of the zodiacal light brightness is crucial for accurate subtraction of zodiacal light foreground for accurate measure of the extragalactic background light after the subtraction of zodiacal light foreground. We present the final design of the instrument and the first results of its performance.

High-Throughput Screening Using a Whole-Cell Virus Replication Reporter Gene Assay to Identify Inhibitory Compounds against Rift Valley Fever Virus Infection.

PubMed

Islam, Md Koushikul; Baudin, Maria; Eriksson, Jonas; Öberg, Christopher; Habjan, Matthias; Weber, Friedemann; Överby, Anna K; Ahlm, Clas; Evander, Magnus

2016-04-01

Rift Valley fever virus (RVFV) is an emerging virus that causes serious illness in humans and livestock. There are no approved vaccines or treatments for humans. The purpose of the study was to identify inhibitory compounds of RVFV infection without any preconceived idea of the mechanism of action. A whole-cell-based high-throughput drug screening assay was developed to screen 28,437 small chemical compounds targeting RVFV infection. To accomplish both speed and robustness, a replication-competent NSs-deleted RVFV expressing a fluorescent reporter gene was developed. Inhibition of fluorescence intensity was quantified by spectrophotometry and related to virus infection in human lung epithelial cells (A549). Cell toxicity was assessed by the Resazurin cell viability assay. After primary screening, 641 compounds were identified that inhibited RVFV infection by ≥80%, with ≥50% cell viability at 50 µM concentration. These compounds were subjected to a second screening regarding dose-response profiles, and 63 compounds with ≥60% inhibition of RVFV infection at 3.12 µM compound concentration and ≥50% cell viability at 25 µM were considered hits. Of these, six compounds with high inhibitory activity were identified. In conclusion, the high-throughput assay could efficiently and safely identify several promising compounds that inhibited RVFV infection. © 2016 Society for Laboratory Automation and Screening.

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR.

PubMed

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch.

GETPrime: a gene- or transcript-specific primer database for quantitative real-time PCR

PubMed Central

Gubelmann, Carine; Gattiker, Alexandre; Massouras, Andreas; Hens, Korneel; David, Fabrice; Decouttere, Frederik; Rougemont, Jacques; Deplancke, Bart

2011-01-01

The vast majority of genes in humans and other organisms undergo alternative splicing, yet the biological function of splice variants is still very poorly understood in large part because of the lack of simple tools that can map the expression profiles and patterns of these variants with high sensitivity. High-throughput quantitative real-time polymerase chain reaction (qPCR) is an ideal technique to accurately quantify nucleic acid sequences including splice variants. However, currently available primer design programs do not distinguish between splice variants and also differ substantially in overall quality, functionality or throughput mode. Here, we present GETPrime, a primer database supported by a novel platform that uniquely combines and automates several features critical for optimal qPCR primer design. These include the consideration of all gene splice variants to enable either gene-specific (covering the majority of splice variants) or transcript-specific (covering one splice variant) expression profiling, primer specificity validation, automated best primer pair selection according to strict criteria and graphical visualization of the latter primer pairs within their genomic context. GETPrime primers have been extensively validated experimentally, demonstrating high transcript specificity in complex samples. Thus, the free-access, user-friendly GETPrime database allows fast primer retrieval and visualization for genes or groups of genes of most common model organisms, and is available at http://updepla1srv1.epfl.ch/getprime/. Database URL: http://deplanckelab.epfl.ch. PMID:21917859

Ionomics: The functional genomics of elements.

PubMed

Baxter, Ivan

2010-03-01

Ionomics is the study of elemental accumulation in living systems using high-throughput elemental profiling. This approach has been applied extensively in plants for forward and reverse genetics, screening diversity panels, and modeling of physiological states. In this review, I will discuss some of the advantages and limitations of the ionomics approach as well as the important parameters to consider when designing ionomics experiments, and how to evaluate ionomics data.

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

DOE PAGES

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

2016-09-01

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

Use of High Throughput Screening Data in IARC Monograph ...

EPA Pesticide Factsheets

Purpose: Evaluation of carcinogenic mechanisms serves a critical role in IARC monograph evaluations, and can lead to “upgrade” or “downgrade” of the carcinogenicity conclusions based on human and animal evidence alone. Three recent IARC monograph Working Groups (110, 112, and 113) pioneered analysis of high throughput in vitro screening data from the U.S. Environmental Protection Agency’s ToxCast program in evaluations of carcinogenic mechanisms. Methods: For monograph 110, ToxCast assay data across multiple nuclear receptors were used to test the hypothesis that PFOA acts exclusively through the PPAR family of receptors, with activity profiles compared to several prototypical nuclear receptor-activating compounds. For monographs 112 and 113, ToxCast assays were systematically evaluated and used as an additional data stream in the overall evaluation of the mechanistic evidence. Specifically, ToxCast assays were mapped to 10 “key characteristics of carcinogens” recently identified by an IARC expert group, and chemicals’ bioactivity profiles were evaluated both in absolute terms (number of relevant assays positive for bioactivity) and relative terms (ranking with respect to other compounds evaluated by IARC, using the ToxPi methodology). Results: PFOA activates multiple nuclear receptors in addition to the PPAR family in the ToxCast assays. ToxCast assays offered substantial coverage for 5 of the 10 “key characteristics,” with the greates

Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods

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

Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.

Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less

High-content profiling of cell responsiveness to graded substrates based on combinyatorially variant polymers.

PubMed

Liu, Er; Treiser, Matthew D; Patel, Hiral; Sung, Hak-Joon; Roskov, Kristen E; Kohn, Joachim; Becker, Matthew L; Moghe, Prabhas V

2009-08-01

We have developed a novel approach combining high information and high throughput analysis to characterize cell adhesive responses to biomaterial substrates possessing gradients in surface topography. These gradients were fabricated by subjecting thin film blends of tyrosine-derived polycarbonates, i.e. poly(DTE carbonate) and poly(DTO carbonate) to a gradient temperature annealing protocol. Saos-2 cells engineered with a green fluorescent protein (GFP) reporter for farnesylation (GFP-f) were cultured on the gradient substrates to assess the effects of nanoscale surface topology and roughness that arise during the phase separation process on cell attachment and adhesion strength. The high throughput imaging approach allowed us to rapidly identify the "global" and "high content" structure-property relationships between cell adhesion and biomaterial properties such as polymer chemistry and topography. This study found that cell attachment and spreading increased monotonically with DTE content and were significantly elevated at the position with intermediate regions corresponding to the highest "gradient" of surface roughness, while GFP-f farnesylation intensity descriptors were sensitively altered by surface roughness, even in cells with comparable levels of spreading.

Ancient pathogen DNA in archaeological samples detected with a Microbial Detection Array.

PubMed

Devault, Alison M; McLoughlin, Kevin; Jaing, Crystal; Gardner, Shea; Porter, Teresita M; Enk, Jacob M; Thissen, James; Allen, Jonathan; Borucki, Monica; DeWitte, Sharon N; Dhody, Anna N; Poinar, Hendrik N

2014-03-06

Ancient human remains of paleopathological interest typically contain highly degraded DNA in which pathogenic taxa are often minority components, making sequence-based metagenomic characterization costly. Microarrays may hold a potential solution to these challenges, offering a rapid, affordable, and highly informative snapshot of microbial diversity in complex samples without the lengthy analysis and/or high cost associated with high-throughput sequencing. Their versatility is well established for modern clinical specimens, but they have yet to be applied to ancient remains. Here we report bacterial profiles of archaeological and historical human remains using the Lawrence Livermore Microbial Detection Array (LLMDA). The array successfully identified previously-verified bacterial human pathogens, including Vibrio cholerae (cholera) in a 19th century intestinal specimen and Yersinia pestis ("Black Death" plague) in a medieval tooth, which represented only minute fractions (0.03% and 0.08% alignable high-throughput shotgun sequencing reads) of their respective DNA content. This demonstrates that the LLMDA can identify primary and/or co-infecting bacterial pathogens in ancient samples, thereby serving as a rapid and inexpensive paleopathological screening tool to study health across both space and time.

Plasma Doping—Enabling Technology for High Dose Logic and Memory Applications

NASA Astrophysics Data System (ADS)

Miller, T.; Godet, L.; Papasouliotis, G. D.; Singh, V.

2008-11-01

As logic and memory device dimensions shrink with each generation, there are more high dose implants at lower energies. Examples include dual poly gate (also referred to as counter-doped poly), elevated source drain and contact plug implants. Plasma Doping technology throughput and dopant profile benefits at these ultra high dose and lower energy conditions have been well established [1,2,3]. For the first time a production-worthy plasma doping implanter, the VIISta PLAD tool, has been developed with unique architecture suited for precise and repeatable dopant placement. Critical elements of the architecture include pulsed DC wafer bias, closed-loop dosimetry and a uniform low energy, high density plasma source. In this paper key performance metrics such as dose uniformity, dose repeatability and dopant profile control will be presented that demonstrate the production-worthiness of the VIISta PLAD tool for several high dose applications.

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

PubMed Central

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

2014-01-01

Molecular profiling of tumor tissue to detect alterations, such as oncogenic mutations, plays a vital role in determining treatment options in oncology. Hence, there is an increasing need for a robust and high-throughput technology to detect oncogenic hotspot mutations. Although commercial assays are available to detect genetic alterations in single genes, only a limited amount of tissue is often available from patients, requiring multiplexing to allow for simultaneous detection of mutations in many genes using low DNA input. Even though next-generation sequencing (NGS) platforms provide powerful tools for this purpose, they face challenges such as high cost, large DNA input requirement, complex data analysis, and long turnaround times, limiting their use in clinical settings. We report the development of the next generation mutation multi-analyte panel (MUT-MAP), a high-throughput microfluidic, panel for detecting 120 somatic mutations across eleven genes of therapeutic interest (AKT1, BRAF, EGFR, FGFR3, FLT3, HRAS, KIT, KRAS, MET, NRAS, and PIK3CA) using allele-specific PCR (AS-PCR) and Taqman technology. This mutation panel requires as little as 2 ng of high quality DNA from fresh frozen or 100 ng of DNA from formalin-fixed paraffin-embedded (FFPE) tissues. Mutation calls, including an automated data analysis process, have been implemented to run 88 samples per day. Validation of this platform using plasmids showed robust signal and low cross-reactivity in all of the newly added assays and mutation calls in cell line samples were found to be consistent with the Catalogue of Somatic Mutations in Cancer (COSMIC) database allowing for direct comparison of our platform to Sanger sequencing. High correlation with NGS when compared to the SuraSeq500 panel run on the Ion Torrent platform in a FFPE dilution experiment showed assay sensitivity down to 0.45%. This multiplexed mutation panel is a valuable tool for high-throughput biomarker discovery in personalized medicine and cancer drug development. PMID:24658394

Real-time investigation of human topoisomerase I reaction kinetics using an optical sensor: a fast method for drug screening and determination of active enzyme concentrations

NASA Astrophysics Data System (ADS)

Kristoffersen, Emil L.; Jørgensen, Line A.; Franch, Oskar; Etzerodt, Michael; Frøhlich, Rikke; Bjergbæk, Lotte; Stougaard, Magnus; Ho, Yi-Ping; Knudsen, Birgitta R.

2015-05-01

Human DNA topoisomerase I (hTopI) is a nuclear enzyme that catalyzes relaxation of super helical tension that arises in the genome during essential DNA metabolic processes. This is accomplished through a common reaction mechanism shared among the type IB topoisomerase enzymes, including eukaryotic and poxvirus topoisomerase I. The mechanism of hTopI is specifically targeted in cancer treatment using camptothecin derivatives. These drugs convert the hTopI activity into a cellular poison, and hence the cytotoxic effects of camptothecin derivatives correlate with the hTopI activity. Therefore, fast and reliable techniques for high throughput measurements of hTopI activity are of high clinical interest. Here we demonstrate potential applications of a fluorophore-quencher based DNA sensor designed for measurement of hTopI cleavage-ligation activities, which are the catalytic steps affected by camptothecin. The kinetic analysis of the hTopI reaction with the DNA sensor exhibits a characteristic burst profile. This is the result of a two-step ping-pong reaction mechanism, where a fast first reaction, the one creating the signal, is followed by a slower second reaction necessary for completion of the catalytic cycle. Hence, the burst profile holds information about two reactions in the enzymatic mechanism. Moreover, it allows the amount of active enzyme in the reaction to be determined. The presented results pave the way for future high throughput drug screening and the potential of measuring active hTopI concentrations in clinical samples for individualized treatment.Human DNA topoisomerase I (hTopI) is a nuclear enzyme that catalyzes relaxation of super helical tension that arises in the genome during essential DNA metabolic processes. This is accomplished through a common reaction mechanism shared among the type IB topoisomerase enzymes, including eukaryotic and poxvirus topoisomerase I. The mechanism of hTopI is specifically targeted in cancer treatment using camptothecin derivatives. These drugs convert the hTopI activity into a cellular poison, and hence the cytotoxic effects of camptothecin derivatives correlate with the hTopI activity. Therefore, fast and reliable techniques for high throughput measurements of hTopI activity are of high clinical interest. Here we demonstrate potential applications of a fluorophore-quencher based DNA sensor designed for measurement of hTopI cleavage-ligation activities, which are the catalytic steps affected by camptothecin. The kinetic analysis of the hTopI reaction with the DNA sensor exhibits a characteristic burst profile. This is the result of a two-step ping-pong reaction mechanism, where a fast first reaction, the one creating the signal, is followed by a slower second reaction necessary for completion of the catalytic cycle. Hence, the burst profile holds information about two reactions in the enzymatic mechanism. Moreover, it allows the amount of active enzyme in the reaction to be determined. The presented results pave the way for future high throughput drug screening and the potential of measuring active hTopI concentrations in clinical samples for individualized treatment. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr01474c

iPSC-derived neurons as a higher-throughput readout for autism: Promises and pitfalls

PubMed Central

Prilutsky, Daria; Palmer, Nathan P.; Smedemark-Margulies, Niklas; Schlaeger, Thorsten M.; Margulies, David M.; Kohane, Isaac S.

2014-01-01

The elucidation of disease etiologies and establishment of robust, scalable, high-throughput screening assays for autism spectrum disorders (ASDs) have been impeded by both inaccessibility of disease-relevant neuronal tissue and the genetic heterogeneity of the disorder. Neuronal cells derived from induced pluripotent stem cells (iPSCs) from autism patients may circumvent these obstacles and serve as relevant cell models. To date, derived cells are characterized and screened by assessing their neuronal phenotypes. These characterizations are often etiology-specific or lack reproducibility and stability. In this manuscript, we present an overview of efforts to study iPSC-derived neurons as a model for autism, and we explore the plausibility of gene expression profiling as a reproducible and stable disease marker. PMID:24374161

Genome wide transcriptional profiling of Herbaspirillum seropedicae SmR1 grown in the presence of naringenin.

PubMed

Tadra-Sfeir, Michelle Z; Faoro, Helisson; Camilios-Neto, Doumit; Brusamarello-Santos, Liziane; Balsanelli, Eduardo; Weiss, Vinicius; Baura, Valter A; Wassem, Roseli; Cruz, Leonardo M; De Oliveira Pedrosa, Fábio; Souza, Emanuel M; Monteiro, Rose A

2015-01-01

Herbaspirillum seropedicae is a diazotrophic bacterium which associates endophytically with economically important gramineae. Flavonoids such as naringenin have been shown to have an effect on the interaction between H. seropedicae and its host plants. We used a high-throughput sequencing based method (RNA-Seq) to access the influence of naringenin on the whole transcriptome profile of H. seropedicae. Three hundred and four genes were downregulated and seventy seven were upregulated by naringenin. Data analysis revealed that genes related to bacterial flagella biosynthesis, chemotaxis and biosynthesis of peptidoglycan were repressed by naringenin. Moreover, genes involved in aromatic metabolism and multidrug transport efllux were actived.

Technical variables in high-throughput miRNA expression profiling: much work remains to be done.

PubMed

Nelson, Peter T; Wang, Wang-Xia; Wilfred, Bernard R; Tang, Guiliang

2008-11-01

MicroRNA (miRNA) gene expression profiling has provided important insights into plant and animal biology. However, there has not been ample published work about pitfalls associated with technical parameters in miRNA gene expression profiling. One source of pertinent information about technical variables in gene expression profiling is the separate and more well-established literature regarding mRNA expression profiling. However, many aspects of miRNA biochemistry are unique. For example, the cellular processing and compartmentation of miRNAs, the differential stability of specific miRNAs, and aspects of global miRNA expression regulation require specific consideration. Additional possible sources of systematic bias in miRNA expression studies include the differential impact of pre-analytical variables, substrate specificity of nucleic acid processing enzymes used in labeling and amplification, and issues regarding new miRNA discovery and annotation. We conclude that greater focus on technical parameters is required to bolster the validity, reliability, and cultural credibility of miRNA gene expression profiling studies.

Near infrared spectroscopy for high-throughput characterization of Shea tree (Vitellaria paradoxa) nut fat profiles.

PubMed

Davrieux, Fabrice; Allal, François; Piombo, Georges; Kelly, Bokary; Okulo, John B; Thiam, Massamba; Diallo, Ousmane B; Bouvet, Jean-Marc

2010-07-14

The Shea tree (Vitellaria paradoxa) is a major tree species in African agroforestry systems. Butter extracted from its nuts offers an opportunity for sustainable development in Sudanian countries and an attractive potential for the food and cosmetics industries. The purpose of this study was to develop near-infrared spectroscopy (NIRS) calibrations to characterize Shea nut fat profiles. Powders prepared from nuts collected from 624 trees in five African countries (Senegal, Mali, Burkina Faso, Ghana and Uganda) were analyzed for moisture content, fat content using solvent extraction, and fatty acid profiles using gas chromatography. Results confirmed the differences between East and West African Shea nut fat composition: eastern nuts had significantly higher fat and oleic acid contents. Near infrared reflectance spectra were recorded for each sample. Ten percent of the samples were randomly selected for validation and the remaining samples used for calibration. For each constituent, calibration equations were developed using modified partial least squares (MPLS) regression. The equation performances were evaluated using the ratio performance to deviation (RPD(p)) and R(p)(2) parameters, obtained by comparison of the validation set NIR predictions and corresponding laboratory values. Moisture (RPD(p) = 4.45; R(p)(2) = 0.95) and fat (RPD(p) = 5.6; R(p)(2) = 0.97) calibrations enabled accurate determination of these traits. NIR models for stearic (RPD(p) = 6.26; R(p)(2) = 0.98) and oleic (RPD(p) = 7.91; R(p)(2) = 0.99) acids were highly efficient and enabled sharp characterization of these two major Shea butter fatty acids. This study demonstrated the ability of near-infrared spectroscopy for high-throughput phenotyping of Shea nuts.

CGDM: collaborative genomic data model for molecular profiling data using NoSQL.

PubMed

Wang, Shicai; Mares, Mihaela A; Guo, Yi-Ke

2016-12-01

High-throughput molecular profiling has greatly improved patient stratification and mechanistic understanding of diseases. With the increasing amount of data used in translational medicine studies in recent years, there is a need to improve the performance of data warehouses in terms of data retrieval and statistical processing. Both relational and Key Value models have been used for managing molecular profiling data. Key Value models such as SeqWare have been shown to be particularly advantageous in terms of query processing speed for large datasets. However, more improvement can be achieved, particularly through better indexing techniques of the Key Value models, taking advantage of the types of queries which are specific for the high-throughput molecular profiling data. In this article, we introduce a Collaborative Genomic Data Model (CGDM), aimed at significantly increasing the query processing speed for the main classes of queries on genomic databases. CGDM creates three Collaborative Global Clustering Index Tables (CGCITs) to solve the velocity and variety issues at the cost of limited extra volume. Several benchmarking experiments were carried out, comparing CGDM implemented on HBase to the traditional SQL data model (TDM) implemented on both HBase and MySQL Cluster, using large publicly available molecular profiling datasets taken from NCBI and HapMap. In the microarray case, CGDM on HBase performed up to 246 times faster than TDM on HBase and 7 times faster than TDM on MySQL Cluster. In single nucleotide polymorphism case, CGDM on HBase outperformed TDM on HBase by up to 351 times and TDM on MySQL Cluster by up to 9 times. The CGDM source code is available at https://github.com/evanswang/CGDM. y.guo@imperial.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pharmacological profiling of the TRPV3 channel in recombinant and native assays.

PubMed

Grubisha, Olivera; Mogg, Adrian J; Sorge, Jessica L; Ball, Laura-Jayne; Sanger, Helen; Ruble, Cara L A; Folly, Elizabeth A; Ursu, Daniel; Broad, Lisa M

2014-05-01

Transient receptor potential vanilloid subtype 3 (TRPV3) is implicated in nociception and certain skin conditions. As such, it is an attractive target for pharmaceutical research. Understanding of endogenous TRPV3 function and pharmacology remains elusive as selective compounds and native preparations utilizing higher throughput methodologies are lacking. In this study, we developed medium-throughput recombinant and native cellular assays to assess the detailed pharmacological profile of human, rat and mouse TRPV3 channels. Medium-throughput cellular assays were developed using a Ca(2+) -sensitive dye and a fluorescent imaging plate reader. Human and rat TRPV3 pharmacology was examined in recombinant cell lines, while the mouse 308 keratinocyte cell line was used to assess endogenous TRPV3 activity. A recombinant rat TRPV3 cellular assay was successfully developed after solving a discrepancy in the published rat TRPV3 protein sequence. A medium-throughput, native, mouse TRPV3 keratinocyte assay was also developed and confirmed using genetic approaches. Whereas the recombinant human and rat TRPV3 assays exhibited similar agonist and antagonist profiles, the native mouse assay showed important differences, namely, TRPV3 activity was detected only in the presence of potentiator or during agonist synergy. Furthermore, the native assay was more sensitive to block by some antagonists. Our findings demonstrate similarities but also notable differences in TRPV3 pharmacology between recombinant and native systems. These findings offer insights into TRPV3 function and these assays should aid further research towards developing TRPV3 therapies. © 2013 The British Pharmacological Society.

Engineering the on-axis intensity of Bessel beam by a feedback tuning loop

NASA Astrophysics Data System (ADS)

Li, Runze; Yu, Xianghua; Yang, Yanlong; Peng, Tong; Yao, Baoli; Zhang, Chunmin; Ye, Tong

2018-02-01

The Bessel beam belongs to a typical class of non-diffractive optical fields that are characterized by their invariant focal profiles along the propagation direction. However, ideal Bessel beams only rigorously exist in theory; Bessel beams generated in the lab are quasi-Bessel beams with finite focal extensions and varying intensity profiles along the propagation axis. The ability to engineer the on-axis intensity profile to the desired shape is essential for many applications. Here we demonstrate an iterative optimization-based approach to engineering the on-axis intensity of Bessel beams. The genetic algorithm is used to demonstrate this approach. Starting with a traditional axicon phase mask, in the design process, the computed on-axis beam profile is fed into a feedback tuning loop of an iterative optimization process, which searches for an optimal radial phase distribution that can generate a generalized Bessel beam with the desired onaxis intensity profile. The experimental implementation involves a fine-tuning process that adjusts the originally targeted profile so that the optimization process can optimize the phase mask to yield an improved on-axis profile. Our proposed method has been demonstrated in engineering several zeroth-order Bessel beams with customized on-axis profiles. High accuracy and high energy throughput merit its use in many applications.

Robo-Lector - a novel platform for automated high-throughput cultivations in microtiter plates with high information content.

PubMed

Huber, Robert; Ritter, Daniel; Hering, Till; Hillmer, Anne-Kathrin; Kensy, Frank; Müller, Carsten; Wang, Le; Büchs, Jochen

2009-08-01

In industry and academic research, there is an increasing demand for flexible automated microfermentation platforms with advanced sensing technology. However, up to now, conventional platforms cannot generate continuous data in high-throughput cultivations, in particular for monitoring biomass and fluorescent proteins. Furthermore, microfermentation platforms are needed that can easily combine cost-effective, disposable microbioreactors with downstream processing and analytical assays. To meet this demand, a novel automated microfermentation platform consisting of a BioLector and a liquid-handling robot (Robo-Lector) was sucessfully built and tested. The BioLector provides a cultivation system that is able to permanently monitor microbial growth and the fluorescence of reporter proteins under defined conditions in microtiter plates. Three examplary methods were programed on the Robo-Lector platform to study in detail high-throughput cultivation processes and especially recombinant protein expression. The host/vector system E. coli BL21(DE3) pRhotHi-2-EcFbFP, expressing the fluorescence protein EcFbFP, was hereby investigated. With the method 'induction profiling' it was possible to conduct 96 different induction experiments (varying inducer concentrations from 0 to 1.5 mM IPTG at 8 different induction times) simultaneously in an automated way. The method 'biomass-specific induction' allowed to automatically induce cultures with different growth kinetics in a microtiter plate at the same biomass concentration, which resulted in a relative standard deviation of the EcFbFP production of only +/- 7%. The third method 'biomass-specific replication' enabled to generate equal initial biomass concentrations in main cultures from precultures with different growth kinetics. This was realized by automatically transferring an appropiate inoculum volume from the different preculture microtiter wells to respective wells of the main culture plate, where subsequently similar growth kinetics could be obtained. The Robo-Lector generates extensive kinetic data in high-throughput cultivations, particularly for biomass and fluorescence protein formation. Based on the non-invasive on-line-monitoring signals, actions of the liquid-handling robot can easily be triggered. This interaction between the robot and the BioLector (Robo-Lector) combines high-content data generation with systematic high-throughput experimentation in an automated fashion, offering new possibilities to study biological production systems. The presented platform uses a standard liquid-handling workstation with widespread automation possibilities. Thus, high-throughput cultivations can now be combined with small-scale downstream processing techniques and analytical assays. Ultimately, this novel versatile platform can accelerate and intensify research and development in the field of systems biology as well as modelling and bioprocess optimization.

Multi-Omics Analysis Reveals a Correlation between the Host Phylogeny, Gut Microbiota and Metabolite Profiles in Cyprinid Fishes

PubMed Central

Li, Tongtong; Long, Meng; Li, Huan; Gatesoupe, François-Joël; Zhang, Xujie; Zhang, Qianqian; Feng, Dongyue; Li, Aihua

2017-01-01

Gut microbiota play key roles in host nutrition and metabolism. However, little is known about the relationship between host genetics, gut microbiota and metabolic profiles. Here, we used high-throughput sequencing and gas chromatography/mass spectrometry approaches to characterize the microbiota composition and the metabolite profiles in the gut of five cyprinid fish species with three different feeding habits raised under identical husbandry conditions. Our results showed that host species and feeding habits significantly affect not only gut microbiota composition but also metabolite profiles (ANOSIM, p ≤ 0.05). Mantel test demonstrated that host phylogeny, gut microbiota, and metabolite profiles were significantly related to each other (p ≤ 0.05). Additionally, the carps with the same feeding habits had more similarity in gut microbiota composition and metabolite profiles. Various metabolites were correlated positively with bacterial taxa involved in food degradation. Our results shed new light on the microbiome and metabolite profiles in the gut content of cyprinid fishes, and highlighted the correlations between host genotype, fish gut microbiome and putative functions, and gut metabolite profiles. PMID:28367147

High-throughput assessment of oxidative respiration in fish embryos: Advancing adverse outcome pathways for mitochondrial dysfunction.

PubMed

Souders, Christopher L; Liang, Xuefang; Wang, Xiaohong; Ector, Naomi; Zhao, Yuan H; Martyniuk, Christopher J

2018-06-01

Mitochondrial dysfunction is a prevalent molecular event that can result in multiple adverse outcomes. Recently, a novel high throughput method to assess metabolic capacity in fish embryos following exposure to chemicals has been adapted for environmental toxicology. Assessments of oxygen consumption rates using the Seahorse XF(e) 24/96 Extracellular Flux Analyzer (Agilent Technologies) can be used to garner insight into toxicant effects at early stages of development. Here we synthesize the current state of the science using high throughput metabolic profiling in zebrafish embryos, and present considerations for those wishing to adopt high throughput methods for mitochondrial bioenergetics into their research. Chemicals that have been investigated in zebrafish using this metabolic platform include herbicides (e.g. paraquat, diquat), industrial compounds (e.g. benzo-[a]-pyrene, tributyltin), natural products (e.g. quercetin), and anti-bacterial chemicals (i.e. triclosan). Some of these chemicals inhibit mitochondrial endpoints in the μM-mM range, and reduce basal respiration, maximum respiration, and spare capacity. We present a theoretical framework for how one can use mitochondrial performance data in zebrafish to categorize chemicals of concern and prioritize mitochondrial toxicants. Noteworthy is that our studies demonstrate that there can be considerable variation in basal respiration of untreated zebrafish embryos due to clutch-specific effects as well as individual variability, and basal oxygen consumption rates (OCR) can vary on average between 100 and 300 pmol/min/embryo. We also compare OCR between chorionated and dechorionated embryos, as both models are employed to test chemicals. After 24 h, dechorionated embryos remain responsive to mitochondrial toxicants, although they show a blunted response to the uncoupling agent carbonylcyanide-4-trifluoromethoxyphenylhydrazone (FCCP); dechorionated embryos are therefore a viable option for investigations into mitochondrial bioenergetics. We present an adverse outcome pathway framework that incorporates endpoints related to mitochondrial bioenergetics. High throughput bioenergetics assays conducted using whole embryos are expected to support adverse outcome pathways for mitochondrial dysfunction. Copyright © 2018 Elsevier B.V. All rights reserved.

Challenges in profiling and lead optimization of drug discovery for methyltransferases.

PubMed

Horiuchi, Kurumi Y

2015-11-01

The importance of epigenetics in the initiation and progression of disease has attracted many investigators to incorporate this novel and exciting field in drug development. Protein methyltransferases are one of the target classes which have gained attention as potential therapeutic targets after promising results of inhibitors for EZH2 and DOT1L in clinical trials. There are many technologies developed in order to find small molecule inhibitors for protein methyltransferases. However, in contrast to high throughput screening, profiling against different methyltransferases is challenging since each enzyme has a different substrate preference so that it is hard to profile in one assay format. Here, different technologies for methyltransferase assays will be overviewed, and the advantages and disadvantages of each will be discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

PubMed

Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

2016-05-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

Building Structure Feature-based Models for Predicting Isoform-specific Human Cytochrome P-450 (hCYP 3A4, 2D6 and 2C9) Inhibition Assay Results in ToxCast

EPA Science Inventory

EPA’s ToxCast project is using high-throughput screening (HTS) to profile and prioritize chemicals for further testing. ToxCast Phase I evaluated 309 unique chemicals, the majority pesticide actives, in over 500 HTS assays. These included 3 human cytochrome P450 (hCYP3A4, hCYP2...

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology.

PubMed

Aretz, Ina; Meierhofer, David

2016-04-27

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

PubMed Central

Aretz, Ina; Meierhofer, David

2016-01-01

Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology. PMID:27128910

Comprehensive protein profiling by multiplexed capillary zone electrophoresis using cross-linked polyacrylamide coated capillaries.

PubMed

Liu, Shaorong; Gao, Lin; Pu, Qiaosheng; Lu, Joann J; Wang, Xingjia

2006-02-01

We have recently developed a new process to create cross-linked polyacrylamide (CPA) coatings on capillary walls to suppress protein-wall interactions. Here, we demonstrate CPA-coated capillaries for high-efficiency (>2 x 10(6) plates per meter) protein separations by capillary zone electrophoresis (CZE). Because CPA virtually eliminates electroosmotic flow, positive and negative proteins cannot be analyzed in a single run. A "one-sample-two-separation" approach is developed to achieve a comprehensive protein analysis. High throughput is achieved through a multiplexed CZE system.

Fluorophore Absorption Size Exclusion Chromatography (FA-SEC): An Alternative Method for High-Throughput Detergent Screening of Membrane Proteins.

PubMed

Lin, Sung-Yao; Sun, Xing-Han; Hsiao, Yu-Hsuan; Chang, Shao-En; Li, Guan-Syun; Hu, Nien-Jen

2016-01-01

Membrane proteins play key roles in many fundamental functions in cells including ATP synthesis, ion and molecule transporter, cell signalling and enzymatic reactions, accounting for ~30% genes of whole genomes. However, the hydrophobic nature of membrane proteins frequently hampers the progress of structure determination. Detergent screening is the critical step in obtaining stable detergent-solubilized membrane proteins and well-diffracting protein crystals. Fluorescence Detection Size Exclusion Chromatography (FSEC) has been developed to monitor the extraction efficiency and monodispersity of membrane proteins in detergent micelles. By tracing the FSEC profiles of GFP-fused membrane proteins, this method significantly enhances the throughput of detergent screening. However, current methods to acquire FSEC profiles require either an in-line fluorescence detector with the SEC equipment or an off-line spectrofluorometer microplate reader. Here, we introduce an alternative method detecting the absorption of GFP (FA-SEC) at 485 nm, thus making this methodology possible on conventional SEC equipment through the in-line absorbance spectrometer. The results demonstrate that absorption is in great correlation with fluorescence of GFP. The comparably weaker absorption signal can be improved by using a longer path-length flow cell. The FA-SEC profiles were congruent with the ones plotted by FSEC, suggesting FA-SEC could be a comparable and economical setup for detergent screening of membrane proteins.

Temperature control in a 30 stage, 5-cm Centrifugal Contactor Pilot Plant

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

Jack D. Law; Troy G. Garn; David H. Meikrantz

2009-09-01

Temperature profile testing was performed using a 30 stage 5-cm centrifugal contactor pilot plant. These tests were performed to evaluate the ability to control process temperature by adjusting feed solution temperatures. This would eliminate the need for complex jacketed heat exchanger installation on the centrifugal contactors. Thermocouples were installed on the inlet and outlets of each stage, as well as directly in the mixing zone of several of the contactor stages. Lamp oil, a commercially available alkane mixture of C14 to C18 chains, and tap water adjusted to pH 2 with nitric acid were the solution feeds for the temperaturemore » profile testing. Temperature data profiles for an array of total throughputs and contactor rpm values for both single-phase and two-phase systems were collected with selected profiles. The total throughput ranged from 0.5-1.4 L/min with rotor speeds from 3500-4000 rpm. Inlet solution temperatures ranging from ambient up to 50 °C were tested. Results of the two-phase temperature profile testing are detailed« less

Diffraction Efficiency Testing of Sinusoidal and Blazed Off-Plane Reflection Gratings

NASA Astrophysics Data System (ADS)

Tutt, James H.; McEntaffer, Randall L.; Marlowe, Hannah; Miles, Drew M.; Peterson, Thomas J.; Deroo, Casey T.; Scholze, Frank; Laubis, Christian

2016-09-01

Reflection gratings in the off-plane mount have the potential to enhance the performance of future high resolution soft X-ray spectrometers. Diffraction efficiency can be optimized through the use of blazed grating facets, achieving high-throughput on one side of zero-order. This paper presents the results from a comparison between a grating with a sinusoidally grooved profile and two gratings that have been blazed. The results show that the blaze does increase throughput to one side of zero-order; however, the total throughput of the sinusoidal gratings is greater than the blazed gratings, suggesting the method of manufacturing the blazed gratings does not produce precise facets. The blazed gratings were also tested in their Littrow and anti-Littrow configurations to quantify diffraction efficiency sensitivity to rotations about the grating normal. Only a small difference in the energy at which efficiency is maximized between the Littrow and anti-Littrow configurations is seen with a small shift in peak efficiency towards higher energies in the anti-Littrow case. This is due to a decrease in the effective blaze angle in the anti-Littrow mounting. This is supported by PCGrate-SX V6.1 modeling carried out for each blazed grating which predicts similar response trends in the Littrow and anti-Littrow orientations.

High-Throughput Screening Platform for the Discovery of New Immunomodulator Molecules from Natural Product Extract Libraries.

PubMed

Pérez Del Palacio, José; Díaz, Caridad; de la Cruz, Mercedes; Annang, Frederick; Martín, Jesús; Pérez-Victoria, Ignacio; González-Menéndez, Víctor; de Pedro, Nuria; Tormo, José R; Algieri, Francesca; Rodriguez-Nogales, Alba; Rodríguez-Cabezas, M Elena; Reyes, Fernando; Genilloud, Olga; Vicente, Francisca; Gálvez, Julio

2016-07-01

It is widely accepted that central nervous system inflammation and systemic inflammation play a significant role in the progression of chronic neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, neurotropic viral infections, stroke, paraneoplastic disorders, traumatic brain injury, and multiple sclerosis. Therefore, it seems reasonable to propose that the use of anti-inflammatory drugs might diminish the cumulative effects of inflammation. Indeed, some epidemiological studies suggest that sustained use of anti-inflammatory drugs may prevent or slow down the progression of neurodegenerative diseases. However, the anti-inflammatory drugs and biologics used clinically have the disadvantage of causing side effects and a high cost of treatment. Alternatively, natural products offer great potential for the identification and development of bioactive lead compounds into drugs for treating inflammatory diseases with an improved safety profile. In this work, we present a validated high-throughput screening approach in 96-well plate format for the discovery of new molecules with anti-inflammatory/immunomodulatory activity. The in vitro models are based on the quantitation of nitrite levels in RAW264.7 murine macrophages and interleukin-8 in Caco-2 cells. We have used this platform in a pilot project to screen a subset of 5976 noncytotoxic crude microbial extracts from the MEDINA microbial natural product collection. To our knowledge, this is the first report on an high-throughput screening of microbial natural product extracts for the discovery of immunomodulators. © 2016 Society for Laboratory Automation and Screening.

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

PubMed

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

2007-03-01

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

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

Geometric screening of core/shell hydrogel microcapsules using a tapered microchannel with interdigitated electrodes.

PubMed

Niu, Ye; Qi, Lin; Zhang, Fen; Zhao, Yi

2018-07-30

Core/shell hydrogel microcapsules attract increasing research attention due to their potentials in tissue engineering, food engineering, and drug delivery. Current approaches for generating core/shell hydrogel microcapsules suffer from large geometric variations. Geometrically defective core/shell microcapsules need to be removed before further use. High-throughput geometric characterization of such core/shell microcapsules is therefore necessary. In this work, a continuous-flow device was developed to measure the geometric properties of microcapsules with a hydrogel shell and an aqueous core. The microcapsules were pumped through a tapered microchannel patterned with an array of interdigitated microelectrodes. The geometric parameters (the shell thickness and the diameter) were derived from the displacement profiles of the microcapsules. The results show that this approach can successfully distinguish all unencapsulated microparticles. The geometric properties of core/shell microcapsules can be determined with high accuracy. The efficacy of this method was demonstrated through a drug releasing experiment where the optimization of the electrospray process based on geometric screening can lead to controlled and extended drug releasing profiles. This method does not require high-speed optical systems, simplifying the system configuration and making it an indeed miniaturized device. The throughput of up to 584 microcapsules per minute was achieved. This study provides a powerful tool for screening core/shell hydrogel microcapsules and is expected to facilitate the applications of these microcapsules in various fields. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.

PubMed

Himmelreich, Uwe; Sorrell, Tania C; Daniel, Heide-Marie

2017-01-01

Rapid and robust high-throughput identification of environmental, industrial, or clinical yeast isolates is important whenever relatively large numbers of samples need to be processed in a cost-efficient way. Nuclear magnetic resonance (NMR) spectroscopy generates complex data based on metabolite profiles, chemical composition and possibly on medium consumption, which can not only be used for the assessment of metabolic pathways but also for accurate identification of yeast down to the subspecies level. Initial results on NMR based yeast identification where comparable with conventional and DNA-based identification. Potential advantages of NMR spectroscopy in mycological laboratories include not only accurate identification but also the potential of automated sample delivery, automated analysis using computer-based methods, rapid turnaround time, high throughput, and low running costs.We describe here the sample preparation, data acquisition and analysis for NMR-based yeast identification. In addition, a roadmap for the development of classification strategies is given that will result in the acquisition of a database and analysis algorithms for yeast identification in different environments.

MicroRNA-21 promotes proliferation of rat hepatocyte BRL-3A by targeting FASLG.

PubMed

Li, J J; Chan, W H; Leung, W Y; Wang, Y; Xu, C S

2015-04-27

Rat liver regeneration (RLR) induced by partial hepatectomy involves cell proliferation regulated by numerous factors, including microRNAs (miRNAs). miRNA high-throughput sequencing has been established and used to analyze miRNA expression profiles. This study showed that 39 miRNAs were related to RLR through the analysis of miRNA high-throughput sequencing. Their role toward rat normal hepatocyte line BRL-3A was studied by gain- and loss-of-function analyses, and one of them, microRNA-21 (miR-21), obviously upregulated and promoted BRL-3A cell proliferation. Using bioinformatics to search for miR-21 targets revealed that Fas ligand (FASLG) is one of miR-21's target genes. A dual-luciferase report assay and Western blot assay showed that miR-21 directly targeted the 3'-untranslated region of FASLG and inhibited the expression of FASLG, which suggests that miR-21 promoted BRL-3A cell proliferation by reducing FASLG expression.

NMRbot: Python scripts enable high-throughput data collection on current Bruker BioSpin NMR spectrometers.

PubMed

Clos, Lawrence J; Jofre, M Fransisca; Ellinger, James J; Westler, William M; Markley, John L

2013-06-01

To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on recent advances in Bruker BioSpin NMR spectrometer hardware and software. Given the daunting challenge for non-NMR experts to collect quality spectra, our goal was to increase user accessibility, provide customized functionality, and improve the consistency and reliability of resultant data. This methodology, NMRbot, is encoded in a set of scripts written in the Python programming language accessible within the Bruker BioSpin TopSpin ™ software. NMRbot improves automated data acquisition and offers novel tools for use in optimizing experimental parameters on the fly. This automated procedure has been successfully implemented for investigations in metabolomics, small-molecule library profiling, and protein-ligand titrations on four Bruker BioSpin NMR spectrometers at the National Magnetic Resonance Facility at Madison. The investigators reported benefits from ease of setup, improved spectral quality, convenient customizations, and overall time savings.

Metabolome progression during early gut microbial colonization of gnotobiotic mice

PubMed Central

Marcobal, Angela; Yusufaly, Tahir; Higginbottom, Steven; Snyder, Michael; Sonnenburg, Justin L.; Mias, George I.

2015-01-01

The microbiome has been implicated directly in host health, especially host metabolic processes and development of immune responses. These are particularly important in infants where the gut first begins being colonized, and such processes may be modeled in mice. In this investigation we follow longitudinally the urine metabolome of ex-germ-free mice, which are colonized with two bacterial species, Bacteroides thetaiotaomicron and Bifidobacterium longum. High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series analysis to urine metabolomics data. Results demonstrate both gradual and punctuated changes in metabolite production and that early colonization events profoundly impact the nature of small molecules circulating in the host. The identified small molecules are implicated in amino acid and carbohydrate metabolic processes, and offer insights into the dynamic changes occurring during the colonization process, using high-throughput longitudinal methodology. PMID:26118551

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.

High-Throughput Characterization of Porous Materials Using Graphics Processing Units

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

Kim, Jihan; Martin, Richard L.; Rübel, Oliver

We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CHmore » $$_{4}$$ and CO$$_{2}$$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.« less

Quantifying domain-ligand affinities and specificities by high-throughput holdup assay

PubMed Central

Vincentelli, Renaud; Luck, Katja; Poirson, Juline; Polanowska, Jolanta; Abdat, Julie; Blémont, Marilyne; Turchetto, Jeremy; Iv, François; Ricquier, Kevin; Straub, Marie-Laure; Forster, Anne; Cassonnet, Patricia; Borg, Jean-Paul; Jacob, Yves; Masson, Murielle; Nominé, Yves; Reboul, Jérôme; Wolff, Nicolas; Charbonnier, Sebastian; Travé, Gilles

2015-01-01

Many protein interactions are mediated by small linear motifs interacting specifically with defined families of globular domains. Quantifying the specificity of a motif requires measuring and comparing its binding affinities to all its putative target domains. To this aim, we developed the high-throughput holdup assay, a chromatographic approach that can measure up to a thousand domain-motif equilibrium binding affinities per day. Extracts of overexpressed domains are incubated with peptide-coated resins and subjected to filtration. Binding affinities are deduced from microfluidic capillary electrophoresis of flow-throughs. After benchmarking the approach on 210 PDZ-peptide pairs with known affinities, we determined the affinities of two viral PDZ-binding motifs derived from Human Papillomavirus E6 oncoproteins for 209 PDZ domains covering 79% of the human PDZome. We obtained exquisite sequence-dependent binding profiles, describing quantitatively the PDZome recognition specificity of each motif. This approach, applicable to many categories of domain-ligand interactions, has a wide potential for quantifying the specificities of interactomes. PMID:26053890

High-throughput and sensitive analysis of 3-monochloropropane-1,2-diol fatty acid esters in edible oils by supercritical fluid chromatography/tandem mass spectrometry.

PubMed

Hori, Katsuhito; Matsubara, Atsuki; Uchikata, Takato; Tsumura, Kazunobu; Fukusaki, Eiichiro; Bamba, Takeshi

2012-08-10

We have established a high-throughput and sensitive analytical method based on supercritical fluid chromatography (SFC) coupled with triple quadrupole mass spectrometry (QqQ MS) for 3-monochloropropane-1,2-diol (3-MCPD) fatty acid esters in edible oils. All analytes were successfully separated within 9 min without sample purification. The system was precise and sensitive, with a limit of detection less than 0.063 mg/kg. The recovery rate of 3-MCPD fatty acid esters spiked into oil samples was in the range of 62.68-115.23%. Furthermore, several edible oils were tested for analyzing 3-MCPD fatty acid ester profiles. This is the first report on the analysis of 3-MCPD fatty acid esters by SFC/QqQ MS. The developed method will be a powerful tool for investigating 3-MCPD fatty acid esters in edible oils. Copyright © 2012 Elsevier B.V. All rights reserved.

A Systematic Approach to Time-series Metabolite Profiling and RNA-seq Analysis of Chinese Hamster Ovary Cell Culture.

PubMed

Hsu, Han-Hsiu; Araki, Michihiro; Mochizuki, Masao; Hori, Yoshimi; Murata, Masahiro; Kahar, Prihardi; Yoshida, Takanobu; Hasunuma, Tomohisa; Kondo, Akihiko

2017-03-02

Chinese hamster ovary (CHO) cells are the primary host used for biopharmaceutical protein production. The engineering of CHO cells to produce higher amounts of biopharmaceuticals has been highly dependent on empirical approaches, but recent high-throughput "omics" methods are changing the situation in a rational manner. Omics data analyses using gene expression or metabolite profiling make it possible to identify key genes and metabolites in antibody production. Systematic omics approaches using different types of time-series data are expected to further enhance understanding of cellular behaviours and molecular networks for rational design of CHO cells. This study developed a systematic method for obtaining and analysing time-dependent intracellular and extracellular metabolite profiles, RNA-seq data (enzymatic mRNA levels) and cell counts from CHO cell cultures to capture an overall view of the CHO central metabolic pathway (CMP). We then calculated correlation coefficients among all the profiles and visualised the whole CMP by heatmap analysis and metabolic pathway mapping, to classify genes and metabolites together. This approach provides an efficient platform to identify key genes and metabolites in CHO cell culture.

Bioactive Potential of Marine Macroalgae from the Central Red Sea (Saudi Arabia) Assessed by High-Throughput Imaging-Based Phenotypic Profiling

PubMed Central

Kremb, Stephan; Müller, Constanze; Schmitt-Kopplin, Philippe; Voolstra, Christian R.

2017-01-01

Marine algae represent an important source of novel natural products. While their bioactive potential has been studied to some extent, limited information is available on marine algae from the Red Sea. This study aimed at the broad discovery of new bioactivities from a collection of twelve macroalgal species from the Central Red Sea. We used imaging-based High-Content Screening (HCS) with a diverse spectrum of cellular markers for detailed cytological profiling of fractionated algal extracts. The cytological profiles for 3 out of 60 algal fractions clustered closely to reference inhibitors and showed strong inhibitory activities on the HIV-1 reverse transcriptase in a single-enzyme biochemical assay, validating the suggested biological target. Subsequent chemical profiling of the active fractions of two brown algal species by ultra-high resolution mass spectrometry (FT-ICR-MS) revealed possible candidate molecules. A database query of these molecules led us to groups of compounds with structural similarities, which are suggested to be responsible for the observed activity. Our work demonstrates the versatility and power of cytological profiling for the bioprospecting of unknown biological resources and highlights Red Sea algae as a source of bioactives that may serve as a starting point for further studies. PMID:28335513

Bioactive Potential of Marine Macroalgae from the Central Red Sea (Saudi Arabia) Assessed by High-Throughput Imaging-Based Phenotypic Profiling.

PubMed

Kremb, Stephan; Müller, Constanze; Schmitt-Kopplin, Philippe; Voolstra, Christian R

2017-03-20

Marine algae represent an important source of novel natural products. While their bioactive potential has been studied to some extent, limited information is available on marine algae from the Red Sea. This study aimed at the broad discovery of new bioactivities from a collection of twelve macroalgal species from the Central Red Sea. We used imaging-based High-Content Screening (HCS) with a diverse spectrum of cellular markers for detailed cytological profiling of fractionated algal extracts. The cytological profiles for 3 out of 60 algal fractions clustered closely to reference inhibitors and showed strong inhibitory activities on the HIV-1 reverse transcriptase in a single-enzyme biochemical assay, validating the suggested biological target. Subsequent chemical profiling of the active fractions of two brown algal species by ultra-high resolution mass spectrometry (FT-ICR-MS) revealed possible candidate molecules. A database query of these molecules led us to groups of compounds with structural similarities, which are suggested to be responsible for the observed activity. Our work demonstrates the versatility and power of cytological profiling for the bioprospecting of unknown biological resources and highlights Red Sea algae as a source of bioactives that may serve as a starting point for further studies.

Isolation of Biologically Active Exosomes from Plasma of Patients with Cancer.

PubMed

Hong, Chang-Sook; Funk, Sonja; Whiteside, Theresa L

2017-01-01

A method for exosome isolation from human plasma was developed for rapid, high-throughput processing of plasma specimens obtained from patients with cancer. This method removes the bulk of plasma proteins associated with exosomes and can be used for comparative examinations of exosomes and their content in serial specimens of patients' plasma, allowing for monitoring changes in exosome numbers, profiles, and functions in the course of cancer progression or during therapy. The plasma-derived exosomes can be recovered in quantities sufficient for the characterization of their morphology by transmission electron microscopy (TEM), size and concentration by qNano, protein/lipid ratios, nucleic acid extraction, molecular profiling by Western blots or immune arrays, and functional assays.

Genome wide transcriptional profiling of Herbaspirillum seropedicae SmR1 grown in the presence of naringenin

PubMed Central

Tadra-Sfeir, Michelle Z.; Faoro, Helisson; Camilios-Neto, Doumit; Brusamarello-Santos, Liziane; Balsanelli, Eduardo; Weiss, Vinicius; Baura, Valter A.; Wassem, Roseli; Cruz, Leonardo M.; De Oliveira Pedrosa, Fábio; Souza, Emanuel M.; Monteiro, Rose A.

2015-01-01

Herbaspirillum seropedicae is a diazotrophic bacterium which associates endophytically with economically important gramineae. Flavonoids such as naringenin have been shown to have an effect on the interaction between H. seropedicae and its host plants. We used a high-throughput sequencing based method (RNA-Seq) to access the influence of naringenin on the whole transcriptome profile of H. seropedicae. Three hundred and four genes were downregulated and seventy seven were upregulated by naringenin. Data analysis revealed that genes related to bacterial flagella biosynthesis, chemotaxis and biosynthesis of peptidoglycan were repressed by naringenin. Moreover, genes involved in aromatic metabolism and multidrug transport efllux were actived. PMID:26052319

Applying Zeeman Doppler imaging to solar spectra

NASA Astrophysics Data System (ADS)

Hussain, G. A. J.; Saar, S. H.; Collier Cameron, A.

2004-03-01

A new generation of spectro-polarimeters with high throughput (e.g. CFHT/ESPADONS and LBT/PEPSI) is becoming available. This opportunity can be exploited using Zeeman Doppler imaging (ZDI), a technique that inverts time-series of Stokes V spectra to map stellar surface magnetic fields (Semel 1989). ZDI is assisted by ``Least squares deconvolution'' (LSD), which sums up the signal from 1000's of photospheric lines to produce a mean deconvolved profile with higher S:N (Donati & Collier Cameron 1997).

Discovery of 1,5-Disubstituted Pyridones: A New Class of Positive Allosteric Modulators of the Metabotropic Glutamate 2 Receptor

PubMed Central

2010-01-01

A series of 1,5-disubstituted pyridones was identified as positive allosteric modulators (PAMs) of the metabotropic glutamate receptor 2 (mGluR2) via high throughput screening (HTS). Subsequent SAR exploration led to the identification of several compounds with improved in vitro activity. Lead compound 8 was further profiled and found to attenuate the increase in PCP induced locomotor activity in mice. PMID:22778815

Analysis of plant germline development by high-throughput RNA profiling: technical advances and new insights.

PubMed

Schmidt, Anja; Schmid, Marc W; Grossniklaus, Ueli

2012-04-01

Reproduction is a crucial step in the life cycle of plants. The male and female germline lineages develop in the reproductive organs of the flower, which in higher plants are the anthers and ovules, respectively. Development of the germline lineage initiates from a dedicated sporophytic cell that undergoes meiosis to form spores that subsequently give rise to the gametophytes through mitotic cell divisions. The mature male and female gametophytes harbour the male (sperm cells) and female gametes (egg and central cell), respectively. Those unite during double fertilization to initiate embryo and endosperm development in sexually reproducing higher plants. While cytological changes involved in development of the germline lineages have been well characterized in a number of species, investigation of the transcriptional basis underlying their development and the specification of the gametes proved challenging. This is largely due to the inaccessibility of the cells constituting the germline lineages, which are enclosed by sporophytic tissues. Only recently, these technical limitations could be overcome by combining new methods to isolate the relevant cells with powerful transcriptional profiling methods, such as microarrays or high-throughput sequencing of RNA. This review focuses on these technical advances and the new insights gained from them concerning the transcriptional basis and molecular mechanisms underlying germline development. © 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.

Protein comparability assessments and potential applicability of high throughput biophysical methods and data visualization tools to compare physical stability profiles

PubMed Central

Alsenaidy, Mohammad A.; Jain, Nishant K.; Kim, Jae H.; Middaugh, C. Russell; Volkin, David B.

2014-01-01

In this review, some of the challenges and opportunities encountered during protein comparability assessments are summarized with an emphasis on developing new analytical approaches to better monitor higher-order protein structures. Several case studies are presented using high throughput biophysical methods to collect protein physical stability data as function of temperature, agitation, ionic strength and/or solution pH. These large data sets were then used to construct empirical phase diagrams (EPDs), radar charts, and comparative signature diagrams (CSDs) for data visualization and structural comparisons between the different proteins. Protein samples with different sizes, post-translational modifications, and inherent stability are presented: acidic fibroblast growth factor (FGF-1) mutants, different glycoforms of an IgG1 mAb prepared by deglycosylation, as well as comparisons of different formulations of an IgG1 mAb and granulocyte colony stimulating factor (GCSF). Using this approach, differences in structural integrity and conformational stability profiles were detected under stress conditions that could not be resolved by using the same techniques under ambient conditions (i.e., no stress). Thus, an evaluation of conformational stability differences may serve as an effective surrogate to monitor differences in higher-order structure between protein samples. These case studies are discussed in the context of potential utility in protein comparability studies. PMID:24659968

An exposure:activity profiling method for interpreting high-throughput screening data for estrogenic activity--proof of concept.

PubMed

Becker, Richard A; Friedman, Katie Paul; Simon, Ted W; Marty, M Sue; Patlewicz, Grace; Rowlands, J Craig

2015-04-01

Rapid high throughput in vitro screening (HTS) assays are now available for characterizing dose-responses in assays that have been selected for their sensitivity in detecting estrogen-related endpoints. For example, EPA's ToxCast™ program recently released endocrine assay results for more than 1800 substances and the interagency Tox21 consortium is in the process of releasing data for approximately 10,000 chemicals. But such activity measurements alone fall short for the purposes of priority setting or screening because the relevant exposure context is not considered. Here, we extend the method of exposure:activity profiling by calculating the exposure:activity ratios (EARs) using human exposure estimates and AC50 values for a range of chemicals tested in a suite of seven estrogenic assays in ToxCast™ and Tox21. To provide additional context, relative estrogenic exposure:activity quotients (REEAQ) were derived by comparing chemical-specific EARs to the EAR of the ubiquitous dietary phytoestrogen, genistein (GEN). Although the activity of a substance in HTS-endocrine assays is not a measure of health hazard or risk, understanding how such a dose compares to human exposures provides a valuable additional metric that can be used in decision-making; substances with small EARs and REEAQs would indicate low priority for further endocrine screening or testing. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Denoising DNA deep sequencing data—high-throughput sequencing errors and their correction

PubMed Central

Laehnemann, David; Borkhardt, Arndt

2016-01-01

Characterizing the errors generated by common high-throughput sequencing platforms and telling true genetic variation from technical artefacts are two interdependent steps, essential to many analyses such as single nucleotide variant calling, haplotype inference, sequence assembly and evolutionary studies. Both random and systematic errors can show a specific occurrence profile for each of the six prominent sequencing platforms surveyed here: 454 pyrosequencing, Complete Genomics DNA nanoball sequencing, Illumina sequencing by synthesis, Ion Torrent semiconductor sequencing, Pacific Biosciences single-molecule real-time sequencing and Oxford Nanopore sequencing. There is a large variety of programs available for error removal in sequencing read data, which differ in the error models and statistical techniques they use, the features of the data they analyse, the parameters they determine from them and the data structures and algorithms they use. We highlight the assumptions they make and for which data types these hold, providing guidance which tools to consider for benchmarking with regard to the data properties. While no benchmarking results are included here, such specific benchmarks would greatly inform tool choices and future software development. The development of stand-alone error correctors, as well as single nucleotide variant and haplotype callers, could also benefit from using more of the knowledge about error profiles and from (re)combining ideas from the existing approaches presented here. PMID:26026159

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.

Protein comparability assessments and potential applicability of high throughput biophysical methods and data visualization tools to compare physical stability profiles.

PubMed

Alsenaidy, Mohammad A; Jain, Nishant K; Kim, Jae H; Middaugh, C Russell; Volkin, David B

2014-01-01

In this review, some of the challenges and opportunities encountered during protein comparability assessments are summarized with an emphasis on developing new analytical approaches to better monitor higher-order protein structures. Several case studies are presented using high throughput biophysical methods to collect protein physical stability data as function of temperature, agitation, ionic strength and/or solution pH. These large data sets were then used to construct empirical phase diagrams (EPDs), radar charts, and comparative signature diagrams (CSDs) for data visualization and structural comparisons between the different proteins. Protein samples with different sizes, post-translational modifications, and inherent stability are presented: acidic fibroblast growth factor (FGF-1) mutants, different glycoforms of an IgG1 mAb prepared by deglycosylation, as well as comparisons of different formulations of an IgG1 mAb and granulocyte colony stimulating factor (GCSF). Using this approach, differences in structural integrity and conformational stability profiles were detected under stress conditions that could not be resolved by using the same techniques under ambient conditions (i.e., no stress). Thus, an evaluation of conformational stability differences may serve as an effective surrogate to monitor differences in higher-order structure between protein samples. These case studies are discussed in the context of potential utility in protein comparability studies.

Development of a sub-cm high resolution ion Doppler tomography diagnostics for fine structure measurement of guide field reconnection in TS-U

NASA Astrophysics Data System (ADS)

Tanabe, Hiroshi; Koike, Hideya; Hatano, Hironori; Hayashi, Takumi; Cao, Qinghong; Himeno, Shunichi; Kaneda, Taishi; Akimitsu, Moe; Sawada, Asuka; Ono, Yasushi

2017-10-01

A new type of high-throughput/high-resolution 96CH ion Doppler tomography diagnostics has been developed using ``multi-slit'' spectroscopy technique for detailed investigation of fine structure formation during high guide field magnetic reconnection. In the last three years, high field merging experiment in MAST pioneered new frontiers of reconnection heating: formation of highly peaked structure around X-point in high guide field condition (Bt > 0.3 T), outflow dissipation under the influence of better plasma confinement to form high temperature ring structure which aligns with closed flux surface of toroidal plasma, and interaction between ion and electron temperature profile during transport/confinement phase to form triple peak structure (τeiE 4 ms). To investigate more detailed mechanism with in-situ magnetic measurement, the university of Tokyo starts the upgrade of plasma parameters and spatial resolution of optical diagnostics as in MAST. Now, a new type of high-throughput/high-resolution 96CH ion Doppler tomography diagnostics system construction has been completed and it successfully resolved fine structure of ion heating downstream, aligned with closed flux surface formed by reconnected field. This work was supported by JSPS KAKENHI Grant Numbers 15H05750, 15K14279 and 17H04863.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding.

PubMed

Shahi, Payam; Kim, Samuel C; Haliburton, John R; Gartner, Zev J; Abate, Adam R

2017-03-14

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

NASA Astrophysics Data System (ADS)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

PubMed Central

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-01-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing. PMID:28290550

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

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

PubMed

Huang, Yuhong; Willats, William G; Lange, Lene; Jin, Yanling; Fang, Yang; Salmeán, Armando A; Pedersen, Henriette L; Busk, Peter Kamp; Zhao, Hai

2016-01-01

Viscosity reduction has a great impact on the efficiency of ethanol production when using roots and tubers as feedstock. Plant cell wall-degrading enzymes have been successfully applied to overcome the challenges posed by high viscosity. However, the changes in cell wall polymers during the viscosity-reducing process are poorly characterized. Comprehensive microarray polymer profiling, which is a high-throughput microarray, was used for the first time to map changes in the cell wall polymers of sweet potato (Ipomoea batatas), cassava (Manihot esculenta), and Canna edulis Ker. over the entire viscosity-reducing process. The results indicated that the composition of cell wall polymers among these three roots and tubers was markedly different. The gel-like matrix and glycoprotein network in the C. edulis Ker. cell wall caused difficulty in viscosity reduction. The obvious viscosity reduction of the sweet potato and the cassava was attributed to the degradation of homogalacturonan and the released 1,4-β-d-galactan and 1,5-α-l-arabinan. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Strategic and Operational Plan for Integrating Transcriptomics ...

EPA Pesticide Factsheets

Plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT; the details are in the attached slide presentation presentation on plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT, given at the OECD meeting on June 23, 2016

High-Throughput Experimental Approach Capabilities | Materials Science |

Science.gov Websites

NREL High-Throughput Experimental Approach Capabilities High-Throughput Experimental Approach by yellow and is for materials in the upper right sector. NREL's high-throughput experimental ,Te) and oxysulfide sputtering Combi-5: Nitrides and oxynitride sputtering We also have several non

Robo-Lector – a novel platform for automated high-throughput cultivations in microtiter plates with high information content

PubMed Central

Huber, Robert; Ritter, Daniel; Hering, Till; Hillmer, Anne-Kathrin; Kensy, Frank; Müller, Carsten; Wang, Le; Büchs, Jochen

2009-01-01

Background In industry and academic research, there is an increasing demand for flexible automated microfermentation platforms with advanced sensing technology. However, up to now, conventional platforms cannot generate continuous data in high-throughput cultivations, in particular for monitoring biomass and fluorescent proteins. Furthermore, microfermentation platforms are needed that can easily combine cost-effective, disposable microbioreactors with downstream processing and analytical assays. Results To meet this demand, a novel automated microfermentation platform consisting of a BioLector and a liquid-handling robot (Robo-Lector) was sucessfully built and tested. The BioLector provides a cultivation system that is able to permanently monitor microbial growth and the fluorescence of reporter proteins under defined conditions in microtiter plates. Three examplary methods were programed on the Robo-Lector platform to study in detail high-throughput cultivation processes and especially recombinant protein expression. The host/vector system E. coli BL21(DE3) pRhotHi-2-EcFbFP, expressing the fluorescence protein EcFbFP, was hereby investigated. With the method 'induction profiling' it was possible to conduct 96 different induction experiments (varying inducer concentrations from 0 to 1.5 mM IPTG at 8 different induction times) simultaneously in an automated way. The method 'biomass-specific induction' allowed to automatically induce cultures with different growth kinetics in a microtiter plate at the same biomass concentration, which resulted in a relative standard deviation of the EcFbFP production of only ± 7%. The third method 'biomass-specific replication' enabled to generate equal initial biomass concentrations in main cultures from precultures with different growth kinetics. This was realized by automatically transferring an appropiate inoculum volume from the different preculture microtiter wells to respective wells of the main culture plate, where subsequently similar growth kinetics could be obtained. Conclusion The Robo-Lector generates extensive kinetic data in high-throughput cultivations, particularly for biomass and fluorescence protein formation. Based on the non-invasive on-line-monitoring signals, actions of the liquid-handling robot can easily be triggered. This interaction between the robot and the BioLector (Robo-Lector) combines high-content data generation with systematic high-throughput experimentation in an automated fashion, offering new possibilities to study biological production systems. The presented platform uses a standard liquid-handling workstation with widespread automation possibilities. Thus, high-throughput cultivations can now be combined with small-scale downstream processing techniques and analytical assays. Ultimately, this novel versatile platform can accelerate and intensify research and development in the field of systems biology as well as modelling and bioprocess optimization. PMID:19646274

Integrated Magneto-Electrochemical Sensor for Exosome Analysis.

PubMed

Jeong, Sangmoo; Park, Jongmin; Pathania, Divya; Castro, Cesar M; Weissleder, Ralph; Lee, Hakho

2016-02-23

Extracellular vesicles, including exosomes, are nanoscale membrane particles that carry molecular information on parental cells. They are being pursued as biomarkers of cancers that are difficult to detect or serially follow. Here we present a compact sensor technology for rapid, on-site exosome screening. The sensor is based on an integrated magneto-electrochemical assay: exosomes are immunomagnetically captured from patient samples and profiled through electrochemical reaction. By combining magnetic enrichment and enzymatic amplification, the approach enables (i) highly sensitive, cell-specific exosome detection and (ii) sensor miniaturization and scale-up for high-throughput measurements. As a proof-of-concept, we implemented a portable, eight-channel device and applied it to screen extracellular vesicles in plasma samples from ovarian cancer patients. The sensor allowed for the simultaneous profiling of multiple protein markers within an hour, outperforming conventional methods in assay sensitivity and speed.

Integrated Magneto-Electrochemical Sensor for Exosome Analysis

PubMed Central

Jeong, Sangmoo; Park, Jongmin; Pathania, Divya; Castro, Cesar M.; Weissleder, Ralph; Lee, Hakho

2016-01-01

Extracellular vesicles, including exosomes, are nanoscale vesicles that carry molecular information of parental cells. They are being pursued as biomarkers of cancers that are difficult to detect or serially follow. Here we present a compact sensor technology for rapid, on-site exosome screening. The sensor is based on an integrated magnetic-electrochemical assay: exosomes are immunomagnetically captured from patient samples, and profiled through electrochemical reaction. By combining magnetic enrichment and enzymatic amplification, the approach enables i) highly sensitive, cell-specific exosome detection, and ii) sensor miniaturization and scale-up for high throughput measurements. As a proof-of-concept, we implemented a portable, eight-channel device, and applied it to screen extracellular vesicles in plasma samples from ovarian cancer patients. The sensor allowed for the profiling of multiple protein markers simultaneously within an hour, outperforming conventional methods in assay sensitivity and speed. PMID:26808216

Metabolic profiles are principally different between cancers of the liver, pancreas and breast.

PubMed

Budhu, Anuradha; Terunuma, Atsushi; Zhang, Geng; Hussain, S Perwez; Ambs, Stefan; Wang, Xin Wei

2014-01-01

Molecular profiling of primary tumors may facilitate the classification of patients with cancer into more homogenous biological groups to aid clinical management. Metabolomic profiling has been shown to be a powerful tool in characterizing the biological mechanisms underlying a disease but has not been evaluated for its ability to classify cancers by their tissue of origin. Thus, we assessed metabolomic profiling as a novel tool for multiclass cancer characterization. Global metabolic profiling was employed to identify metabolites in paired tumor and non-tumor liver (n=60), breast (n=130) and pancreatic (n=76) tissue specimens. Unsupervised principal component analysis showed that metabolites are principally unique to each tissue and cancer type. Such a difference can also be observed even among early stage cancers, suggesting a significant and unique alteration of global metabolic pathways associated with each cancer type. Our global high-throughput metabolomic profiling study shows that specific biochemical alterations distinguish liver, pancreatic and breast cancer and could be applied as cancer classification tools to differentiate tumors based on tissue of origin.

An Accelerated Analytical Process for the Development of STR Profiles for Casework Samples.

PubMed

Laurin, Nancy; Frégeau, Chantal J

2015-07-01

Significant efforts are being devoted to the development of methods enabling rapid generation of short tandem repeat (STR) profiles in order to reduce turnaround times for the delivery of human identification results from biological evidence. Some of the proposed solutions are still costly and low throughput. This study describes the optimization of an analytical process enabling the generation of complete STR profiles (single-source or mixed profiles) for human identification in approximately 5 h. This accelerated process uses currently available reagents and standard laboratory equipment. It includes a 30-min lysis step, a 27-min DNA extraction using the Promega Maxwell(®) 16 System, DNA quantification in <1 h using the Qiagen Investigator(®) Quantiplex HYres kit, fast amplification (<26 min) of the loci included in AmpFℓSTR(®) Identifiler(®), and analysis of the profiles on the 3500-series Genetic Analyzer. This combination of fast individual steps produces high-quality profiling results and offers a cost-effective alternative approach to rapid DNA analysis. © 2015 American Academy of Forensic Sciences.

g:Profiler-a web server for functional interpretation of gene lists (2016 update).

PubMed

Reimand, Jüri; Arak, Tambet; Adler, Priit; Kolberg, Liis; Reisberg, Sulev; Peterson, Hedi; Vilo, Jaak

2016-07-08

Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and ranked gene lists and finds statistically significant Gene Ontology terms, pathways and other gene function related terms. Translation of hundreds of gene identifiers is another core feature of g:Profiler. Since its first publication in 2007, our web server has become a popular tool of choice among basic and translational researchers. Timeliness is a major advantage of g:Profiler as genome and pathway information is synchronized with the Ensembl database in quarterly updates. g:Profiler supports 213 species including mammals and other vertebrates, plants, insects and fungi. The 2016 update of g:Profiler introduces several novel features. We have added further functional datasets to interpret gene lists, including transcription factor binding site predictions, Mendelian disease annotations, information about protein expression and complexes and gene mappings of human genetic polymorphisms. Besides the interactive web interface, g:Profiler can be accessed in computational pipelines using our R package, Python interface and BioJS component. g:Profiler is freely available at http://biit.cs.ut.ee/gprofiler/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

PubMed

Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

2018-01-01

The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for further refinement towards addressing a large clinical need.

High-Throughput Multi-Analyte Luminex Profiling Implicates Eotaxin-1 in Ulcerative Colitis

PubMed Central

Coburn, Lori A.; Horst, Sara N.; Chaturvedi, Rupesh; Brown, Caroline T.; Allaman, Margaret M.; Scull, Brooks P.; Singh, Kshipra; Piazuelo, M. Blanca; Chitnavis, Maithili V.; Hodges, Mallary E.; Rosen, Michael J.; Williams, Christopher S.; Slaughter, James C.; Beaulieu, Dawn B.; Schwartz, David A.; Wilson, Keith T.

2013-01-01

Accurate and high-throughput technologies are needed for identification of new therapeutic targets and for optimizing therapy in inflammatory bowel disease. Our aim was to assess multi-analyte protein-based assays of cytokines/chemokines using Luminex technology. We have reported that Luminex-based profiling was useful in assessing response to L-arginine therapy in the mouse model of dextran sulfate sodium colitis. Therefore, we studied prospectively collected samples from ulcerative colitis (UC) patients and control subjects. Serum, colon biopsies, and clinical information were obtained from subjects undergoing colonoscopy for evaluation of UC or for non-UC indications. In total, 38 normal controls and 137 UC cases completed the study. Histologic disease severity and the Mayo Disease Activity Index (DAI) were assessed. Serum and colonic tissue cytokine/chemokine profiles were measured by Luminex-based multiplex testing of 42 analytes. Only eotaxin-1 and G-CSF were increased in serum of patients with histologically active UC vs. controls. While 13 cytokines/chemokines were increased in active UC vs. controls in tissues, only eotaxin-1 was increased in all levels of active disease in both serum and tissue. In tissues, eotaxin-1 correlated with the DAI and with eosinophil counts. Increased eotaxin-1 levels were confirmed by real-time PCR. Tissue eotaxin-1 levels were also increased in experimental murine colitis induced by dextran sulfate sodium, oxazolone, or Citrobacter rodentium, but not in murine Helicobacter pylori infection. Our data implicate eotaxin-1 as an etiologic factor and therapeutic target in UC, and indicate that Luminex-based assays may be useful to assess IBD pathogenesis and to select patients for anti-cytokine/chemokine therapies. PMID:24367513

Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

PubMed Central

Siepel, Adam; Lis, John T.

2012-01-01

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity. PMID:22479205

Molecular-genetic profiling and high-throughput in vitro drug screening in NUT midline carcinoma—an aggressive and fatal disease

PubMed Central

Stirnweiss, Anja; Oommen, Joyce; Kotecha, Rishi S.; Kees, Ursula R.; Beesley, Alex H.

2017-01-01

NUT midline carcinoma (NMC) is a rare and aggressive cancer, with survival typically less than seven months, that can arise in people of any age. Genetically, NMC is defined by the chromosomal fusion of NUTM1 with a chromatin-binding partner, typically the bromodomain-containing protein BRD4. However, little is known about other genetic aberrations in this disease. In this study, we used a unique panel of cell lines to describe the molecular-genetic features of NMC. Next-generation sequencing identified a recurring high-impact mutation in the DNA-helicase gene RECQL5 in 75% of lines studied, and biological signals from mutation-signature and network analyses consistent with a general failure in DNA-repair. A high-throughput drug screen confirmed that microtubule inhibitors, topoisomerase inhibitors and anthracyclines are highly cytotoxic in the majority of NMC lines, and that cell lines expressing the BRD4-NUTM1 (exon11:exon2) variant are an order of magnitude more responsive to bromodomain inhibitors (iBETs) on average than those with other BRD4-NUTM1 translocation variants. We also identified a highly significant correlation between iBET and aurora kinase inhibitor efficacy in this study. Integration of exome sequencing, transcriptome, and drug sensitivity profiles suggested that aberrant activity of the nuclear receptor co-activator NCOA3 may correlate with poor response to iBETs. In conclusion, our data emphasize the heterogeneity of NMC and highlights genetic aberrations that could be explored to improve therapeutic strategies. The novel finding of a recurring RECQL5 mutation, together with recent reports of chromoplexy in this disease, suggests that DNA-repair pathways are likely to play a central role in NMC tumorigenesis. PMID:29348827

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing

PubMed Central

Morgan, Horatio H.; du Toit, Maret; Setati, Mathabatha E.

2017-01-01

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity. PMID:28553266

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity.

PubMed

Seamon, Kyle J; Light, Yooli K; Saada, Edwin A; Schoeniger, Joseph S; Harmon, Brooke

2018-06-05

The RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate its utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity

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

Seamon, Kyle Jeffrey; Light, Yooli Kim; Saada, Edwin A.

Here, the RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate itsmore » utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.« less

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity

DOE PAGES

Seamon, Kyle Jeffrey; Light, Yooli Kim; Saada, Edwin A.; ...

2018-05-14

Here, the RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate itsmore » utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.« less

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing.

PubMed

Morgan, Horatio H; du Toit, Maret; Setati, Mathabatha E

2017-01-01

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity.

A novel informatics concept for high-throughput shotgun lipidomics based on the molecular fragmentation query language

PubMed Central

2011-01-01

Shotgun lipidome profiling relies on direct mass spectrometric analysis of total lipid extracts from cells, tissues or organisms and is a powerful tool to elucidate the molecular composition of lipidomes. We present a novel informatics concept of the molecular fragmentation query language implemented within the LipidXplorer open source software kit that supports accurate quantification of individual species of any ionizable lipid class in shotgun spectra acquired on any mass spectrometry platform. PMID:21247462

Transcriptome complexity in cardiac development and diseases--an expanding universe between genome and phenome.

PubMed

Gao, Chen; Wang, Yibin

2014-01-01

With the advancement of transcriptome profiling by micro-arrays and high-throughput RNA-sequencing, transcriptome complexity and its dynamics are revealed at different levels in cardiovascular development and diseases. In this review, we will highlight the recent progress in our knowledge of cardiovascular transcriptome complexity contributed by RNA splicing, RNA editing and noncoding RNAs. The emerging importance of many of these previously under-explored aspects of gene regulation in cardiovascular development and pathology will be discussed.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.

PubMed

Gierahn, Todd M; Wadsworth, Marc H; Hughes, Travis K; Bryson, Bryan D; Butler, Andrew; Satija, Rahul; Fortune, Sarah; Love, J Christopher; Shalek, Alex K

2017-04-01

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.

Potentials and capabilities of the Extracellular Vesicle (EV) Array.

PubMed

Jørgensen, Malene Møller; Bæk, Rikke; Varming, Kim

2015-01-01

Extracellular vesicles (EVs) and exosomes are difficult to enrich or purify from biofluids, hence quantification and phenotyping of these are tedious and inaccurate. The multiplexed, highly sensitive and high-throughput platform of the EV Array presented by Jørgensen et al., (J Extracell Vesicles, 2013; 2: 10) has been refined regarding the capabilities of the method for characterization and molecular profiling of EV surface markers. Here, we present an extended microarray platform to detect and phenotype plasma-derived EVs (optimized for exosomes) for up to 60 antigens without any enrichment or purification prior to analysis.

MMP Inhibitors: Past, present and future.

PubMed

Cathcart, Jillian M; Cao, Jian

2015-06-01

  Development of inhibitors of matrix metalloproteinases (MMPs) has been fraught with challenges. Early compounds largely failed due to poor selectivity and bioavailability. Dose-limiting side effects, off-target interactions, and improperly designed clinical trials significantly impeded clinical success. As information becomes available and technology evolves, tools to combat these obstacles have been developed. Improved methods for high throughput screening and drug design have led to identification of compounds exhibiting high potency, binding affinity, and favorable pharmacokinetic profiles. Current research into MMP inhibitors employs innovative approaches for drug delivery methods and allosteric inhibitors. Such innovation is key for development of clinically successful compounds.

Identification of quinazoline based inhibitors of IRAK4 for the treatment of inflammation

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

Smith, Graham F.; Altman, Michael D.; Andresen, Brian

Interleukin-1 receptor associated kinase 4 (IRAK4) has been implicated in IL-1R and TLR based signaling. Therefore selective inhibition of the kinase activity of this protein represents an attractive target for the treatment of inflammatory diseases. Medicinal chemistry optimization of high throughput screening (HTS) hits with the help of structure based drug design led to the identification of orally-bioavailable quinazoline based IRAK4 inhibitors with excellent pharmacokinetic profile and kinase selectivity. These highly selective IRAK4 compounds show activity in vivo via oral dosing in a TLR7 driven model of inflammation.

Pharmacological profiling of the TRPV3 channel in recombinant and native assays

PubMed Central

Grubisha, Olivera; Mogg, Adrian J; Sorge, Jessica L; Ball, Laura-Jayne; Sanger, Helen; Ruble, Cara L A; Folly, Elizabeth A; Ursu, Daniel; Broad, Lisa M

2014-01-01

Background and Purpose Transient receptor potential vanilloid subtype 3 (TRPV3) is implicated in nociception and certain skin conditions. As such, it is an attractive target for pharmaceutical research. Understanding of endogenous TRPV3 function and pharmacology remains elusive as selective compounds and native preparations utilizing higher throughput methodologies are lacking. In this study, we developed medium-throughput recombinant and native cellular assays to assess the detailed pharmacological profile of human, rat and mouse TRPV3 channels. Experimental Approach Medium-throughput cellular assays were developed using a Ca2+-sensitive dye and a fluorescent imaging plate reader. Human and rat TRPV3 pharmacology was examined in recombinant cell lines, while the mouse 308 keratinocyte cell line was used to assess endogenous TRPV3 activity. Key Results A recombinant rat TRPV3 cellular assay was successfully developed after solving a discrepancy in the published rat TRPV3 protein sequence. A medium-throughput, native, mouse TRPV3 keratinocyte assay was also developed and confirmed using genetic approaches. Whereas the recombinant human and rat TRPV3 assays exhibited similar agonist and antagonist profiles, the native mouse assay showed important differences, namely, TRPV3 activity was detected only in the presence of potentiator or during agonist synergy. Furthermore, the native assay was more sensitive to block by some antagonists. Conclusions and Implications Our findings demonstrate similarities but also notable differences in TRPV3 pharmacology between recombinant and native systems. These findings offer insights into TRPV3 function and these assays should aid further research towards developing TRPV3 therapies. Linked Articles This article is part of a themed section on the pharmacology of TRP channels. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014.171.issue-10 PMID:23848361

Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival.

PubMed

Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar

2011-04-26

High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.

CA resist with high sensitivity and sub-100-nm resolution for advanced mask making

NASA Astrophysics Data System (ADS)

Huang, Wu-Song; Kwong, Ranee W.; Hartley, John G.; Moreau, Wayne M.; Angelopoulos, Marie; Magg, Christopher; Lawliss, Mark

2000-07-01

Recently, there is significant interest in using CA resist for electron beam (E-beam) applications including mask making, direct write, and projection printing. CA resists provide superior lithographic performance in comparison to traditional non-CA E-beam resist in particular high contrast, resolution, and sensitivity. However, most of the commercially available CA resist have the concern of airborne base contaminants and sensitivity to PAB and/or PEB temperatures. In this presentation, we will discuss a new improved ketal resists system referred to as KRS-XE which exhibits excellent lithography, is robust toward airborne base, compatible with 0.263N TMAH aqueous developer and exhibits excellent lithography, is robust toward airborne base, compatible with 0.263N TMAH aqueous developer and exhibits a large PAB/PEB latitude. With the combination of a high performance mask making E-beam exposure tool, high kV shaped beam system EL4+ and the KRS-XE resist, we have printed 75nm lines/space feature with excellent profile control at a dose of 13(mu) C/cm2 at 75kV. The shaped beam vector scan system used here provides a unique property in resolving small features in lithography and throughput. Overhead in EL4+$ limits the systems ability to fully exploit the sensitivity of the new resist for throughput. The EL5 system has sufficiently low overhead that it is projected to print a 4X, 16G DRAM mask with OPC in under 3 hours with the CA resist. We will discuss the throughput advantages of the next generation EL5 system over the existing EL4+.

ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis

PubMed Central

2011-01-01

Background Chromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of Drosophila melanogaster. Results Both technologies produce highly reproducible profiles within each platform, ChIP-seq generally produces profiles with a better signal-to-noise ratio, and allows detection of more peaks and narrower peaks. The set of peaks identified by the two technologies can be significantly different, but the extent to which they differ varies depending on the factor and the analysis algorithm. Importantly, we found that there is a significant variation among multiple sequencing profiles of input DNA libraries and that this variation most likely arises from both differences in experimental condition and sequencing depth. We further show that using an inappropriate input DNA profile can impact the average signal profiles around genomic features and peak calling results, highlighting the importance of having high quality input DNA data for normalization in ChIP-seq analysis. Conclusions Our findings highlight the biases present in each of the platforms, show the variability that can arise from both technology and analysis methods, and emphasize the importance of obtaining high quality and deeply sequenced input DNA libraries for ChIP-seq analysis. PMID:21356108

In silico gene expression profiling in Cannabis sativa.

PubMed

Massimino, Luca

2017-01-01

The cannabis plant and its active ingredients (i.e., cannabinoids and terpenoids) have been socially stigmatized for half a century. Luckily, with more than 430,000 published scientific papers and about 600 ongoing and completed clinical trials, nowadays cannabis is employed for the treatment of many different medical conditions. Nevertheless, even if a large amount of high-throughput functional genomic data exists, most researchers feature a strong background in molecular biology but lack advanced bioinformatics skills. In this work, publicly available gene expression datasets have been analyzed giving rise to a total of 40,224 gene expression profiles taken from cannabis plant tissue at different developmental stages. The resource presented here will provide researchers with a starting point for future investigations with Cannabis sativa .

Unsupervised Outlier Profile Analysis

PubMed Central

Ghosh, Debashis; Li, Song

2014-01-01

In much of the analysis of high-throughput genomic data, “interesting” genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use for the outlier expression problem, in particular with continuous data, is problematic but nevertheless motivates new statistics that give an unsupervised analog to previously developed outlier profile analysis approaches. Some simulation studies are used to evaluate the proposal. A bivariate extension is described that can accommodate data from two platforms on matched samples. The proposed methods are applied to data from a prostate cancer study. PMID:25452686

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

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

PubMed Central

Wright, Imogen A.; Travers, Simon A.

2014-01-01

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

The Human Cell Atlas.

PubMed

Regev, Aviv; Teichmann, Sarah A; Lander, Eric S; Amit, Ido; Benoist, Christophe; Birney, Ewan; Bodenmiller, Bernd; Campbell, Peter; Carninci, Piero; Clatworthy, Menna; Clevers, Hans; Deplancke, Bart; Dunham, Ian; Eberwine, James; Eils, Roland; Enard, Wolfgang; Farmer, Andrew; Fugger, Lars; Göttgens, Berthold; Hacohen, Nir; Haniffa, Muzlifah; Hemberg, Martin; Kim, Seung; Klenerman, Paul; Kriegstein, Arnold; Lein, Ed; Linnarsson, Sten; Lundberg, Emma; Lundeberg, Joakim; Majumder, Partha; Marioni, John C; Merad, Miriam; Mhlanga, Musa; Nawijn, Martijn; Netea, Mihai; Nolan, Garry; Pe'er, Dana; Phillipakis, Anthony; Ponting, Chris P; Quake, Stephen; Reik, Wolf; Rozenblatt-Rosen, Orit; Sanes, Joshua; Satija, Rahul; Schumacher, Ton N; Shalek, Alex; Shapiro, Ehud; Sharma, Padmanee; Shin, Jay W; Stegle, Oliver; Stratton, Michael; Stubbington, Michael J T; Theis, Fabian J; Uhlen, Matthias; van Oudenaarden, Alexander; Wagner, Allon; Watt, Fiona; Weissman, Jonathan; Wold, Barbara; Xavier, Ramnik; Yosef, Nir

2017-12-05

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Transcriptomic and phenotypic profiling in developing zebrafish exposed to thyroid hormone receptor agonists

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

Haggard, Derik E.; Noyes, Pamela D.; Waters, Katrina M.

There is a need to develop novel, high-throughput screening and prioritization methods to identify chemicals with adverse estrogen, androgen, and thyroid activity to protect human health and the environment and is of interest to the Endocrine Disruptor Screening Program. The current aim is to explore the utility of zebrafish as a testing paradigm to classify endocrine activity using phenotypically anchored transcriptome profiling. Transcriptome analysis was conducted on embryos exposed to 25 estrogen-, androgen-, or thyroid-active chemicals at a concentration that elicited adverse malformations or mortality at 120 hours post-fertilization in 80% of the animals exposed. Analysis of the top 1000more » significant differentially expressed transcripts across all treatments identified a unique transcriptional and phenotypic profile for thyroid hormone receptor agonists, which can be used as a biomarker screen for potential thyroid hormone agonists.« less

Network-assisted target identification for haploinsufficiency and homozygous profiling screens

PubMed Central

Wang, Sheng

2017-01-01

Chemical genomic screens have recently emerged as a systematic approach to drug discovery on a genome-wide scale. Drug target identification and elucidation of the mechanism of action (MoA) of hits from these noisy high-throughput screens remain difficult. Here, we present GIT (Genetic Interaction Network-Assisted Target Identification), a network analysis method for drug target identification in haploinsufficiency profiling (HIP) and homozygous profiling (HOP) screens. With the drug-induced phenotypic fitness defect of the deletion of a gene, GIT also incorporates the fitness defects of the gene’s neighbors in the genetic interaction network. On three genome-scale yeast chemical genomic screens, GIT substantially outperforms previous scoring methods on target identification on HIP and HOP assays, respectively. Finally, we showed that by combining HIP and HOP assays, GIT further boosts target identification and reveals potential drug’s mechanism of action. PMID:28574983

Informing the Selection of Screening Hit Series with in Silico Absorption, Distribution, Metabolism, Excretion, and Toxicity Profiles.

PubMed

Sanders, John M; Beshore, Douglas C; Culberson, J Christopher; Fells, James I; Imbriglio, Jason E; Gunaydin, Hakan; Haidle, Andrew M; Labroli, Marc; Mattioni, Brian E; Sciammetta, Nunzio; Shipe, William D; Sheridan, Robert P; Suen, Linda M; Verras, Andreas; Walji, Abbas; Joshi, Elizabeth M; Bueters, Tjerk

2017-08-24

High-throughput screening (HTS) has enabled millions of compounds to be assessed for biological activity, but challenges remain in the prioritization of hit series. While biological, absorption, distribution, metabolism, excretion, and toxicity (ADMET), purity, and structural data are routinely used to select chemical matter for further follow-up, the scarcity of historical ADMET data for screening hits limits our understanding of early hit compounds. Herein, we describe a process that utilizes a battery of in-house quantitative structure-activity relationship (QSAR) models to generate in silico ADMET profiles for hit series to enable more complete characterizations of HTS chemical matter. These profiles allow teams to quickly assess hit series for desirable ADMET properties or suspected liabilities that may require significant optimization. Accordingly, these in silico data can direct ADMET experimentation and profoundly impact the progression of hit series. Several prospective examples are presented to substantiate the value of this approach.

The Human Cell Atlas

PubMed Central

Amit, Ido; Benoist, Christophe; Birney, Ewan; Bodenmiller, Bernd; Campbell, Peter; Carninci, Piero; Clatworthy, Menna; Clevers, Hans; Deplancke, Bart; Dunham, Ian; Eberwine, James; Eils, Roland; Enard, Wolfgang; Farmer, Andrew; Fugger, Lars; Göttgens, Berthold; Hacohen, Nir; Haniffa, Muzlifah; Hemberg, Martin; Kim, Seung; Klenerman, Paul; Kriegstein, Arnold; Lein, Ed; Linnarsson, Sten; Lundberg, Emma; Lundeberg, Joakim; Majumder, Partha; Marioni, John C; Merad, Miriam; Mhlanga, Musa; Nawijn, Martijn; Netea, Mihai; Nolan, Garry; Pe'er, Dana; Phillipakis, Anthony; Ponting, Chris P; Quake, Stephen; Reik, Wolf; Rozenblatt-Rosen, Orit; Sanes, Joshua; Satija, Rahul; Schumacher, Ton N; Shalek, Alex; Shapiro, Ehud; Sharma, Padmanee; Shin, Jay W; Stegle, Oliver; Stratton, Michael; Stubbington, Michael J T; Theis, Fabian J; Uhlen, Matthias; van Oudenaarden, Alexander; Wagner, Allon; Watt, Fiona; Weissman, Jonathan; Wold, Barbara; Xavier, Ramnik; Yosef, Nir

2017-01-01

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community. PMID:29206104

Arrays of High-Aspect Ratio Microchannels for High-Throughput Isolation of Circulating Tumor Cells (CTCs).

PubMed

Hupert, Mateusz L; Jackson, Joshua M; Wang, Hong; Witek, Małgorzata A; Kamande, Joyce; Milowsky, Matthew I; Whang, Young E; Soper, Steven A

2014-10-01

Microsystem-based technologies are providing new opportunities in the area of in vitro diagnostics due to their ability to provide process automation enabling point-of-care operation. As an example, microsystems used for the isolation and analysis of circulating tumor cells (CTCs) from complex, heterogeneous samples in an automated fashion with improved recoveries and selectivity are providing new opportunities for this important biomarker. Unfortunately, many of the existing microfluidic systems lack the throughput capabilities and/or are too expensive to manufacture to warrant their widespread use in clinical testing scenarios. Here, we describe a disposable, all-polymer, microfluidic system for the high-throughput (HT) isolation of CTCs directly from whole blood inputs. The device employs an array of high aspect ratio (HAR), parallel, sinusoidal microchannels (25 µm × 150 µm; W × D; AR = 6.0) with walls covalently decorated with anti-EpCAM antibodies to provide affinity-based isolation of CTCs. Channel width, which is similar to an average CTC diameter (12-25 µm), plays a critical role in maximizing the probability of cell/wall interactions and allows for achieving high CTC recovery. The extended channel depth allows for increased throughput at the optimized flow velocity (2 mm/s in a microchannel); maximizes cell recovery, and prevents clogging of the microfluidic channels during blood processing. Fluidic addressing of the microchannel array with a minimal device footprint is provided by large cross-sectional area feed and exit channels poised orthogonal to the network of the sinusoidal capillary channels (so-called Z-geometry). Computational modeling was used to confirm uniform addressing of the channels in the isolation bed. Devices with various numbers of parallel microchannels ranging from 50 to 320 have been successfully constructed. Cyclic olefin copolymer (COC) was chosen as the substrate material due to its superior properties during UV-activation of the HAR microchannels surfaces prior to antibody attachment. Operation of the HT-CTC device has been validated by isolation of CTCs directly from blood secured from patients with metastatic prostate cancer. High CTC sample purities (low number of contaminating white blood cells, WBCs) allowed for direct lysis and molecular profiling of isolated CTCs.

Potential of dynamically harmonized Fourier transform ion cyclotron resonance cell for high-throughput metabolomics fingerprinting: control of data quality.

PubMed

Habchi, Baninia; Alves, Sandra; Jouan-Rimbaud Bouveresse, Delphine; Appenzeller, Brice; Paris, Alain; Rutledge, Douglas N; Rathahao-Paris, Estelle

2018-01-01

Due to the presence of pollutants in the environment and food, the assessment of human exposure is required. This necessitates high-throughput approaches enabling large-scale analysis and, as a consequence, the use of high-performance analytical instruments to obtain highly informative metabolomic profiles. In this study, direct introduction mass spectrometry (DIMS) was performed using a Fourier transform ion cyclotron resonance (FT-ICR) instrument equipped with a dynamically harmonized cell. Data quality was evaluated based on mass resolving power (RP), mass measurement accuracy, and ion intensity drifts from the repeated injections of quality control sample (QC) along the analytical process. The large DIMS data size entails the use of bioinformatic tools for the automatic selection of common ions found in all QC injections and for robustness assessment and correction of eventual technical drifts. RP values greater than 10 6 and mass measurement accuracy of lower than 1 ppm were obtained using broadband mode resulting in the detection of isotopic fine structure. Hence, a very accurate relative isotopic mass defect (RΔm) value was calculated. This reduces significantly the number of elemental composition (EC) candidates and greatly improves compound annotation. A very satisfactory estimate of repeatability of both peak intensity and mass measurement was demonstrated. Although, a non negligible ion intensity drift was observed for negative ion mode data, a normalization procedure was easily applied to correct this phenomenon. This study illustrates the performance and robustness of the dynamically harmonized FT-ICR cell to perform large-scale high-throughput metabolomic analyses in routine conditions. Graphical abstract Analytical performance of FT-ICR instrument equipped with a dynamically harmonized cell.

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

PubMed

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

2010-01-01

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

Enhanced High Resolution RBS System

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

Pollock, Thomas J.; Hass, James A.; Klody, George M.

2011-06-01

Improvements in full spectrum resolution with the second NEC high resolution RBS system are summarized. Results for 50 A ring TiN/HfO films on Si yielding energy resolution on the order of 1 keV are also presented. Detector enhancements include improved pulse processing electronics, upgraded shielding for the MCP/RAE detector, and reduced noise generated from pumping. Energy resolution measurements on spectra front edge coupled with calculations using 0.4mStr solid angle show that beam energy spread at 400 KeV from the Pelletron registered accelerator is less than 100 eV. To improve user throughput, magnet control has been added to the automatic datamore » collection. Depth profiles derived from experimental data are discussed. For the thin films profiled, depth resolutions were on the Angstrom level with the non-linear energy/channel conversions ranging from 100 to 200 eV.« less

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

Logic gate scanner focus control in high-volume manufacturing using scatterometry

NASA Astrophysics Data System (ADS)

Dare, Richard J.; Swain, Bryan; Laughery, Michael

2004-05-01

Tool matching and optimal process control are critical requirements for success in semiconductor manufacturing. It is imperative that a tool"s operating conditions are understood and controlled in order to create a process that is repeatable and produces devices within specifications. Likewise, it is important where possible to match multiple systems using some methodology, so that regardless of which tool is used the process remains in control. Agere Systems is currently using Timbre Technologies" Optical Digital Profilometry (ODP) scatterometry for controlling Nikon scanner focus at the most critical lithography layer; logic gate. By adjusting focus settings and verifying the resultant changes in resist profile shape using ODP, it becomes possible to actively control scanner focus to achieve a desired resist profile. Since many critical lithography processes are designed to produce slightly re-entrant resist profiles, this type of focus control is not possible via Critical Dimension Scanning Electron Microscopy (CDSEM) where reentrant profiles cannot be accurately determined. Additionally, the high throughput and non-destructive nature of this measurement technique saves both cycle time and wafer costs compared to cross-section SEM. By implementing an ODP daily process check and after any maintenance on a scanner, Agere successfully enabled focus drift control, i.e. making necessary focus or equipment changes in order to maintain a desired resist profile.

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

[Expression profiles of the exosomal miRNAs in the chronic hepatitis B patients with persistently normal ALT].

PubMed

Li, Ronghua; Fu, Xiaoyu; Tang, Yujing; Fu, Lei; Tan, Deming; Ouyang, Yi; Peng, Shifang

2018-05-28

To investigate expression profiles of the plasma exosomal miRNAs of the chronic hepatitis B (CHB) patients with persistently normal alamine aminotransferase (PNALT) for the first time and try to find exosomal miRNAs which could reflect liver inflammation better. 
 Methods: Five CHB patients with liver tissue inflammation grade ≥A2 of PNALT and 5 CHB patients with liver tissue inflammation grade

Defining RNA-Small Molecule Affinity Landscapes Enables Design of a Small Molecule Inhibitor of an Oncogenic Noncoding RNA.

PubMed

Velagapudi, Sai Pradeep; Luo, Yiling; Tran, Tuan; Haniff, Hafeez S; Nakai, Yoshio; Fallahi, Mohammad; Martinez, Gustavo J; Childs-Disney, Jessica L; Disney, Matthew D

2017-03-22

RNA drug targets are pervasive in cells, but methods to design small molecules that target them are sparse. Herein, we report a general approach to score the affinity and selectivity of RNA motif-small molecule interactions identified via selection. Named High Throughput Structure-Activity Relationships Through Sequencing (HiT-StARTS), HiT-StARTS is statistical in nature and compares input nucleic acid sequences to selected library members that bind a ligand via high throughput sequencing. The approach allowed facile definition of the fitness landscape of hundreds of thousands of RNA motif-small molecule binding partners. These results were mined against folded RNAs in the human transcriptome and identified an avid interaction between a small molecule and the Dicer nuclease-processing site in the oncogenic microRNA (miR)-18a hairpin precursor, which is a member of the miR-17-92 cluster. Application of the small molecule, Targapremir-18a, to prostate cancer cells inhibited production of miR-18a from the cluster, de-repressed serine/threonine protein kinase 4 protein (STK4), and triggered apoptosis. Profiling the cellular targets of Targapremir-18a via Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP), a covalent small molecule-RNA cellular profiling approach, and other studies showed specific binding of the compound to the miR-18a precursor, revealing broadly applicable factors that govern small molecule drugging of noncoding RNAs.

Defining RNA–Small Molecule Affinity Landscapes Enables Design of a Small Molecule Inhibitor of an Oncogenic Noncoding RNA

PubMed Central

2017-01-01

RNA drug targets are pervasive in cells, but methods to design small molecules that target them are sparse. Herein, we report a general approach to score the affinity and selectivity of RNA motif–small molecule interactions identified via selection. Named High Throughput Structure–Activity Relationships Through Sequencing (HiT-StARTS), HiT-StARTS is statistical in nature and compares input nucleic acid sequences to selected library members that bind a ligand via high throughput sequencing. The approach allowed facile definition of the fitness landscape of hundreds of thousands of RNA motif–small molecule binding partners. These results were mined against folded RNAs in the human transcriptome and identified an avid interaction between a small molecule and the Dicer nuclease-processing site in the oncogenic microRNA (miR)-18a hairpin precursor, which is a member of the miR-17-92 cluster. Application of the small molecule, Targapremir-18a, to prostate cancer cells inhibited production of miR-18a from the cluster, de-repressed serine/threonine protein kinase 4 protein (STK4), and triggered apoptosis. Profiling the cellular targets of Targapremir-18a via Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP), a covalent small molecule–RNA cellular profiling approach, and other studies showed specific binding of the compound to the miR-18a precursor, revealing broadly applicable factors that govern small molecule drugging of noncoding RNAs. PMID:28386598

High-throughput metabolic profiling of diverse green Coffea arabica beans identified tryptophan as a universal discrimination factor for immature beans.

PubMed

Setoyama, Daiki; Iwasa, Keiko; Seta, Harumichi; Shimizu, Hiroaki; Fujimura, Yoshinori; Miura, Daisuke; Wariishi, Hiroyuki; Nagai, Chifumi; Nakahara, Koichi

2013-01-01

The maturity of green coffee beans is the most influential determinant of the quality and flavor of the resultant coffee beverage. However, the chemical compounds that can be used to discriminate the maturity of the beans remain uncharacterized. We herein analyzed four distinct stages of maturity (immature, semi-mature, mature and overripe) of nine different varieties of green Coffea arabica beans hand-harvested from a single experimental field in Hawaii. After developing a high-throughput experimental system for sample preparation and liquid chromatography-mass spectrometry (LC-MS) measurement, we applied metabolic profiling, integrated with chemometric techniques, to explore the relationship between the metabolome and maturity of the sample in a non-biased way. For the multivariate statistical analyses, a partial least square (PLS) regression model was successfully created, which allowed us to accurately predict the maturity of the beans based on the metabolomic information. As a result, tryptophan was identified to be the best contributor to the regression model; the relative MS intensity of tryptophan was higher in immature beans than in those after the semi-mature stages in all arabica varieties investigated, demonstrating a universal discrimination factor for diverse arabica beans. Therefore, typtophan, either alone or together with other metabolites, may be utilized for traders as an assessment standard when purchasing qualified trading green arabica bean products. Furthermore, our results suggest that the tryptophan metabolism may be tightly linked to the development of coffee cherries and/or beans.

Multipurpose HTS Coagulation Analysis: Assay Development and Assessment of Coagulopathic Snake Venoms

PubMed Central

Still, Kristina B. M.; Nandlal, Randjana S. S.; Slagboom, Julien; Somsen, Govert W.; Kool, Jeroen

2017-01-01

Coagulation assays currently employed are often low throughput, require specialized equipment and/or require large blood/plasma samples. This study describes the development, optimization and early application of a generic low-volume and high-throughput screening (HTS) assay for coagulation activity. The assay is a time-course spectrophotometric measurement which kinetically measures the clotting profile of bovine or human plasma incubated with Ca2+ and a test compound. The HTS assay can be a valuable new tool for coagulation diagnostics in hospitals, for research in coagulation disorders, for drug discovery and for venom research. A major effect following envenomation by many venomous snakes is perturbation of blood coagulation caused by haemotoxic compounds present in the venom. These compounds, such as anticoagulants, are potential leads in drug discovery for cardiovascular diseases. The assay was implemented in an integrated analytical approach consisting of reversed-phase liquid chromatography (LC) for separation of crude venom components in combination with parallel post-column coagulation screening and mass spectrometry (MS). The approach was applied for the rapid assessment and identification of profiles of haemotoxic compounds in snake venoms. Procoagulant and anticoagulant activities were correlated with accurate masses from the parallel MS measurements, facilitating the detection of peptides showing strong anticoagulant activity. PMID:29186818

HT-COMET: a novel automated approach for high throughput assessment of human sperm chromatin quality.

PubMed

Albert, Océane; Reintsch, Wolfgang E; Chan, Peter; Robaire, Bernard

2016-05-01

Can we make the comet assay (single-cell gel electrophoresis) for human sperm a more accurate and informative high throughput assay? We developed a standardized automated high throughput comet (HT-COMET) assay for human sperm that improves its accuracy and efficiency, and could be of prognostic value to patients in the fertility clinic. The comet assay involves the collection of data on sperm DNA damage at the level of the single cell, allowing the use of samples from severe oligozoospermic patients. However, this makes comet scoring a low throughput procedure that renders large cohort analyses tedious. Furthermore, the comet assay comes with an inherent vulnerability to variability. Our objective is to develop an automated high throughput comet assay for human sperm that will increase both its accuracy and efficiency. The study comprised two distinct components: a HT-COMET technical optimization section based on control versus DNAse treatment analyses ( ITALIC! n = 3-5), and a cross-sectional study on 123 men presenting to a reproductive center with sperm concentrations categorized as severe oligozoospermia, oligozoospermia or normozoospermia. Sperm chromatin quality was measured using the comet assay: on classic 2-well slides for software comparison; on 96-well slides for HT-COMET optimization; after exposure to various concentrations of a damage-inducing agent, DNAse, using HT-COMET; on 123 subjects with different sperm concentrations using HT-COMET. Data from the 123 subjects were correlated to classic semen quality parameters and plotted as single-cell data in individual DNA damage profiles. We have developed a standard automated HT-COMET procedure for human sperm. It includes automated scoring of comets by a fully integrated high content screening setup that compares well with the most commonly used semi-manual analysis software. Using this method, a cross-sectional study on 123 men showed no significant correlation between sperm concentration and sperm DNA damage, confirming the existence of hidden chromatin damage in men with apparently normal semen characteristics, and a significant correlation between percentage DNA in the tail and percentage of progressively motile spermatozoa. Finally, the use of DNA damage profiles helped to distinguish subjects between and within sperm concentration categories, and allowed a determination of the proportion of highly damaged cells. The main limitations of the HT-COMET are the high, yet indispensable, investment in an automated liquid handling system and heating block to ensure accuracy, and the availability of an automated plate reading microscope and analysis software. This standardized HT-COMET assay offers many advantages, including higher accuracy and evenness due to automation of sensitive steps, a 14.4-fold increase in sample analysis capacity, and an imaging and scoring time of 1 min/well. Overall, HT-COMET offers a decrease in total experimental time of more than 90%. Hence, this assay constitutes a more efficient option to assess sperm chromatin quality, paves the way to using this assay to screen large cohorts, and holds prognostic value for infertile patients. Funded by the CIHR Institute of Human Development, Child and Youth Health (IHDCYH; RHF 100625). O.A. is a fellow supported by the Fonds de la Recherche du Québec - Santé (FRQS) and the CIHR Training Program in Reproduction, Early Development, and the Impact on Health (REDIH). B.R. is a James McGill Professor. The authors declare no conflicts of interest. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparative Transcriptomes and EVO-DEVO Studies Depending on Next Generation Sequencing.

PubMed

Liu, Tiancheng; Yu, Lin; Liu, Lei; Li, Hong; Li, Yixue

2015-01-01

High throughput technology has prompted the progressive omics studies, including genomics and transcriptomics. We have reviewed the improvement of comparative omic studies, which are attributed to the high throughput measurement of next generation sequencing technology. Comparative genomics have been successfully applied to evolution analysis while comparative transcriptomics are adopted in comparison of expression profile from two subjects by differential expression or differential coexpression, which enables their application in evolutionary developmental biology (EVO-DEVO) studies. EVO-DEVO studies focus on the evolutionary pressure affecting the morphogenesis of development and previous works have been conducted to illustrate the most conserved stages during embryonic development. Old measurements of these studies are based on the morphological similarity from macro view and new technology enables the micro detection of similarity in molecular mechanism. Evolutionary model of embryo development, which includes the "funnel-like" model and the "hourglass" model, has been evaluated by combination of these new comparative transcriptomic methods with prior comparative genomic information. Although the technology has promoted the EVO-DEVO studies into a new era, technological and material limitation still exist and further investigations require more subtle study design and procedure.

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.

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.

HTS techniques for patch clamp-based ion channel screening - advances and economy.

PubMed

Farre, Cecilia; Fertig, Niels

2012-06-01

Ten years ago, the first publication appeared showing patch clamp recordings performed on a planar glass chip instead of using a conventional patch clamp pipette. "Going planar" proved to revolutionize ion channel drug screening as we know it, by allowing high quality measurements of ion channels and their effectors at a higher throughput and at the same time de-skilling the highly laborious technique. Over the years, platforms evolved in response to user requirements regarding experimental features, data handling plus storage, and suitable target diversity. This article gives a snapshot image of patch clamp-based ion channel screening with focus on platforms developed to meet requirements of high-throughput screening environments. The commercially available platforms are described, along with their benefits and drawbacks in ion channel drug screening. Automated patch clamp (APC) platforms allow faster investigation of a larger number of ion channel active compounds or cell clones than previously possible. Since patch clamp is the only method allowing direct, real-time measurements of ion channel activity, APC holds the promise of picking up high quality leads, where they otherwise would have been overseen using indirect methods. In addition, drug candidate safety profiling can be performed earlier in the drug discovery process, avoiding late-phase compound withdrawal due to safety liability issues, which is highly costly and inefficient.

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

EPA Pesticide Factsheets

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

Loss of heterozygosity assay for molecular detection of cancer using energy-transfer primers and capillary array electrophoresis.

PubMed

Medintz, I L; Lee, C C; Wong, W W; Pirkola, K; Sidransky, D; Mathies, R A

2000-08-01

Microsatellite DNA loci are useful markers for the detection of loss of heterozygosity (LOH) and microsatellite instability (MI) associated with primary cancers. To carry out large-scale studies of LOH and MI in cancer progression, high-throughput instrumentation and assays with high accuracy and sensitivity need to be validated. DNA was extracted from 26 renal tumor and paired lymphocyte samples and amplified with two-color energy-transfer (ET) fluorescent primers specific for loci associated with cancer-induced chromosomal changes. PCR amplicons were separated on the MegaBACE-1000 96 capillary array electrophoresis (CAE) instrument and analyzed with MegaBACE Genetic Profiler v.1.0 software. Ninety-six separations were achieved in parallel in 75 minutes. Loss of heterozygosity was easily detected in tumor samples as was the gain/loss of microsatellite core repeats. Allelic ratios were determined with a precision of +/- 10% or better. Prior analysis of these samples with slab gel electrophoresis and radioisotope labeling had not detected these changes with as much sensitivity or precision. This study establishes the validity of this assay and the MegaBACE instrument for large-scale, high-throughput studies of the molecular genetic changes associated with cancer.

Systematic Cell-Based Phenotyping of Missense Alleles Empowers Rare Variant Association Studies: A Case for LDLR and Myocardial Infarction

PubMed Central

Schuberth, Christian; Won, Hong-Hee; Blattmann, Peter; Joggerst-Thomalla, Brigitte; Theiss, Susanne; Asselta, Rosanna; Duga, Stefano; Merlini, Pier Angelica; Ardissino, Diego; Lander, Eric S.; Gabriel, Stacey; Rader, Daniel J.; Peloso, Gina M.; Kathiresan, Sekar; Runz, Heiko

2015-01-01

A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude. PMID:25647241

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Terminator oligo blocking efficiently eliminates rRNA from Drosophila small RNA sequencing libraries.

PubMed

Wickersheim, Michelle L; Blumenstiel, Justin P

2013-11-01

A large number of methods are available to deplete ribosomal RNA reads from high-throughput RNA sequencing experiments. Such methods are critical for sequencing Drosophila small RNAs between 20 and 30 nucleotides because size selection is not typically sufficient to exclude the highly abundant class of 30 nucleotide 2S rRNA. Here we demonstrate that pre-annealing terminator oligos complimentary to Drosophila 2S rRNA prior to 5' adapter ligation and reverse transcription efficiently depletes 2S rRNA sequences from the sequencing reaction in a simple and inexpensive way. This depletion is highly specific and is achieved with minimal perturbation of miRNA and piRNA profiles.

Low-Cost High-Precision PIAA Optics for High Contrast Imaging with Exo-Planet Coronagraphs

NASA Technical Reports Server (NTRS)

Balasubramanian, Kunjithapatham; Shaklan, Stuart B.; Pueyo, Laurent; Wilson, Daniel W.; Guyon, Olivier

2010-01-01

PIAA optics for high contrast imaging present challenges in manufacturing and testing due to their large surface departures from aspheric profiles at the aperture edges. With smaller form factors and consequent smaller surface deformations (<50 microns), fabrication of these mirrors with diamond turning followed by electron beam lithographic techniques becomes feasible. Though such a design reduces the system throughput to approx.50%, it still provides good performance down to 2 lambda/D inner working angle. With new achromatic focal plane mask designs, the system performance can be further improved. We report on the design, expected performance, fabrication challenges, and initial assessment of such novel PIAA optics.

Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

PubMed

Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

2015-01-01

There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

Structure-Based Optimization of Arylamides as Inhibitors of Soluble Epoxide Hydrolase

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

Eldrup, Anne B.; Soleymanzadeh, Fariba; Taylor, Steven J.

2009-11-04

Inhibition of soluble epoxide hydrolase (sEH) is hypothesized to lead to an increase in circulating levels of epoxyeicosatrienoic acids, resulting in the potentiation of their in vivo pharmacological properties. As part of an effort to identify inhibitors of sEH with high and sustained plasma exposure, we recently performed a high throughput screen of our compound collection. The screen identified N-(3,3-diphenyl-propyl)-nicotinamide as a potent inhibitor of sEH. Further profiling of this lead revealed short metabolic half-lives in microsomes and rapid clearance in the rat. Consistent with these observations, the determination of the in vitro metabolic profile of N-(3,3-diphenyl-propyl)-nicotinamide in rat livermore » microsomes revealed extensive oxidative metabolism and a propensity for metabolite switching. Lead optimization, guided by the analysis of the solid-state costructure of N-(3,3-diphenyl-propyl)-nicotinamide bound to human sEH, led to the identification of a class of potent and selective inhibitors. An inhibitor from this class displayed an attractive in vitro metabolic profile and high and sustained plasma exposure in the rat after oral administration.« less

Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

PubMed

Lee, Jia-Ying Joey; Miller, James Alastair; Basu, Sreetama; Kee, Ting-Zhen Vanessa; Loo, Lit-Hsin

2018-06-01

Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity. This approach is called "High-throughput In vitro Phenotypic Profiling for Toxicity Prediction" (HIPPTox). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks and/or activation of the DNA-damage response (DDR) pathway. Therefore, HIPPTox helps us to uncover these common modes-of-action of pulmonotoxic chemicals. HIPPTox may also be applied to other cell types or models, and accelerate the development of predictive in vitro assays for other cell-type- or organ-specific toxicities.

Unravelling the complexity of microRNA-mediated gene regulation in black pepper (Piper nigrum L.) using high-throughput small RNA profiling.

PubMed

Asha, Srinivasan; Sreekumar, Sweda; Soniya, E V

2016-01-01

Analysis of high-throughput small RNA deep sequencing data, in combination with black pepper transcriptome sequences revealed microRNA-mediated gene regulation in black pepper ( Piper nigrum L.). Black pepper is an important spice crop and its berries are used worldwide as a natural food additive that contributes unique flavour to foods. In the present study to characterize microRNAs from black pepper, we generated a small RNA library from black pepper leaf and sequenced it by Illumina high-throughput sequencing technology. MicroRNAs belonging to a total of 303 conserved miRNA families were identified from the sRNAome data. Subsequent analysis from recently sequenced black pepper transcriptome confirmed precursor sequences of 50 conserved miRNAs and four potential novel miRNA candidates. Stem-loop qRT-PCR experiments demonstrated differential expression of eight conserved miRNAs in black pepper. Computational analysis of targets of the miRNAs showed 223 potential black pepper unigene targets that encode diverse transcription factors and enzymes involved in plant development, disease resistance, metabolic and signalling pathways. RLM-RACE experiments further mapped miRNA-mediated cleavage at five of the mRNA targets. In addition, miRNA isoforms corresponding to 18 miRNA families were also identified from black pepper. This study presents the first large-scale identification of microRNAs from black pepper and provides the foundation for the future studies of miRNA-mediated gene regulation of stress responses and diverse metabolic processes in black pepper.

High-throughput multiple-mouse imaging with micro-PET/CT for whole-skeleton assessment.

PubMed

Yagi, Masashi; Arentsen, Luke; Shanley, Ryan M; Hui, Susanta K

2014-11-01

Recent studies have proven that skeleton-wide functional assessment is essential to comprehensively understand physiological aspects of the skeletal system. Therefore, in contrast to regional imaging studies utilizing a multiple-animal holder (mouse hotel), we attempted to develop and characterize a multiple-mouse imaging system with micro-PET/CT for high-throughput whole-skeleton assessment. Using items found in a laboratory, a simple mouse hotel that houses four mice linked with gas anesthesia was constructed. A mouse-simulating phantom was used to measure uniformity in a cross sectional area and flatness (Amax/Amin*100) along the axial, radial and tangential directions, where Amax and Amin are maximum and minimum activity concentration in the profile, respectively. Fourteen mice were used for single- or multiple-micro-PET/CT scans. NaF uptake was measured at eight skeletal sites (skull to tibia). Skeletal (18)F activities measured with mice in the mouse hotel were within 1.6 ± 4% (mean ± standard deviation) of those measured with mice in the single-mouse holder. Single-holder scanning yields slightly better uniformity and flatness over the hotel. Compared to use of the single-mouse holder, scanning with the mouse hotel reduced study time (by 65%), decreased the number of scans (four-fold), reduced cost, required less computer storage space (40%), and maximized (18)F usage. The mouse hotel allows high-throughput, quantitatively equivalent scanning compared to the single-mouse holder for micro-PET/CT imaging for whole-skeleton assessment of mice. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Application of ToxCast High-Throughput Screening and ...

EPA Pesticide Factsheets

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

Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

PubMed Central

Liu, Zhi-Ping

2015-01-01

Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

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

PubMed Central

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

2008-01-01

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

High-Throughput Screening of Chemical Effects on Steroidogenesis Using H295R Human Adrenocortical Carcinoma Cells.

PubMed

Karmaus, Agnes L; Toole, Colleen M; Filer, Dayne L; Lewis, Kenneth C; Martin, Matthew T

2016-04-01

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ≥ 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

Tiered High-Throughput Screening Approach to Identify Thyroperoxidase Inhibitors Within the ToxCast Phase I and II Chemical Libraries

PubMed Central

Watt, Eric D.; Hornung, Michael W.; Hedge, Joan M.; Judson, Richard S.; Crofton, Kevin M.; Houck, Keith A.; Simmons, Steven O.

2016-01-01

High-throughput screening for potential thyroid-disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the U.S. Environmental Protection Agency ToxCast screening assay portfolio. To fill 1 critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast phase I and II chemical libraries, comprised of 1074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single-concentration screen were retested in concentration-response. Due to high false-positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed 2 additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using guaiacol as a substrate to confirm the activity profiles of putative TPO inhibitors. This effort represents the most extensive TPO inhibition screening campaign to date and illustrates a tiered screening approach that focuses resources, maximizes assay throughput, and reduces animal use. PMID:26884060

CA resist with high sensitivity and sub-100-nm resolution for advanced mask and device making

NASA Astrophysics Data System (ADS)

Kwong, Ranee W.; Huang, Wu-Song; Hartley, John G.; Moreau, Wayne M.; Robinson, Christopher F.; Angelopoulos, Marie; Magg, Christopher; Lawliss, Mark

2000-07-01

Recently, there is significant interest in using CA resists for electron beam (E-Beam) applications including mask making, direct write, and projection printing. CA resists provide superior lithographic performance in comparison to traditional non CA E-beam resists in particular high contrast, resolution, and sensitivity. However, most of the commercially available CA resists have the concern of airborne base contaminants and sensitivity to PAB and/or PEB temperatures. In this presentation, we will discuss a new improved ketal resist system referred to as KRS-XE which exhibits excellent lithography, is robust toward airborne base, compatible with 0.263 N TMAH aqueous developer and exhibits a large PAB/PEB latitude. With the combination of a high performance mask making E-beam exposure tool, high kV (75 kV) shaped beam system EL4+ and the KRS-XE resist, we have printed 75 nm lines/space features with excellent profile control at a dose of 13 (mu) C/cm2 at 75 kV. The shaped beam vector scan system used here provides an unique property in resolving small features in lithography and throughput. Overhead in EL4+ limits the systems ability to fully exploit the sensitivity of the new resist for throughput. The EL5 system, currently in the build phase, has sufficiently low overhead that it is projected to print a 4X, 16G, DRAM mask with OPC in under 3 hours with the CA resist. We will discuss the throughput advantages of the next generation EL5 system over the existing EL4+. In addition we will show the resolution of KRS-XE down to 70 nm using the PREVAIL projection printing system.

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

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

High-Throughput Screening of Chemical Effects on Steroidogenesis Using H295R Human Adrenocortical Carcinoma Cells

PubMed Central

Toole, Colleen M.; Filer, Dayne L.; Lewis, Kenneth C.; Martin, Matthew T.

2016-01-01

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ≥ 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. PMID:26781511

High Throughput Screening For Hazard and Risk of Environmental Contaminants

EPA Science Inventory

High throughput toxicity testing provides detailed mechanistic information on the concentration response of environmental contaminants in numerous potential toxicity pathways. High throughput screening (HTS) has several key advantages: (1) expense orders of magnitude less than an...

Processing MALDI mass spectra to improve mass spectral direct tissue analysis

NASA Astrophysics Data System (ADS)

Norris, Jeremy L.; Cornett, Dale S.; Mobley, James A.; Andersson, Malin; Seeley, Erin H.; Chaurand, Pierre; Caprioli, Richard M.

2007-02-01

Profiling and imaging biological specimens using MALDI mass spectrometry has significant potential to contribute to our understanding and diagnosis of disease. The technique is efficient and high-throughput providing a wealth of data about the biological state of the sample from a very simple and direct experiment. However, in order for these techniques to be put to use for clinical purposes, the approaches used to process and analyze the data must improve. This study examines some of the existing tools to baseline subtract, normalize, align, and remove spectral noise for MALDI data, comparing the advantages of each. A preferred workflow is presented that can be easily implemented for data in ASCII format. The advantages of using such an approach are discussed for both molecular profiling and imaging mass spectrometry.

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

PubMed

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

2016-01-01

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

Identification and Characterization of Influenza Virus Entry Inhibitors through Dual Myxovirus High-Throughput Screening.

PubMed

Weisshaar, Marco; Cox, Robert; Morehouse, Zachary; Kumar Kyasa, Shiva; Yan, Dan; Oberacker, Phil; Mao, Shuli; Golden, Jennifer E; Lowen, Anice C; Natchus, Michael G; Plemper, Richard K

2016-08-15

Influenza A virus (IAV) infections cause major morbidity and mortality, generating an urgent need for novel antiviral therapeutics. We recently established a dual myxovirus high-throughput screening protocol that combines a fully replication-competent IAV-WSN strain and a respiratory syncytial virus reporter strain for the simultaneous identification of IAV-specific, paramyxovirus-specific, and broad-spectrum inhibitors. In the present study, this protocol was applied to a screening campaign to assess a diverse chemical library with over 142,000 entries. Focusing on IAV-specific hits, we obtained a hit rate of 0.03% after cytotoxicity testing and counterscreening. Three chemically distinct hit classes with nanomolar potency and favorable cytotoxicity profiles were selected. Time-of-addition, minigenome, and viral entry studies demonstrated that these classes block hemagglutinin (HA)-mediated membrane fusion. Antiviral activity extends to an isolate from the 2009 pandemic and, in one case, another group 1 subtype. Target identification through biolayer interferometry confirmed binding of all hit compounds to HA. Resistance profiling revealed two distinct escape mechanisms: primary resistance, associated with reduced compound binding, and secondary resistance, associated with unaltered binding. Secondary resistance was mediated, unusually, through two different pairs of cooperative mutations, each combining a mutation eliminating the membrane-proximal stalk N-glycan with a membrane-distal change in HA1 or HA2. Chemical synthesis of an analog library combined with in silico docking extracted a docking pose for the hit classes. Chemical interrogation spotlights IAV HA as a major druggable target for small-molecule inhibition. Our study identifies novel chemical scaffolds with high developmental potential, outlines diverse routes of IAV escape from entry inhibition, and establishes a path toward structure-aided lead development. This study is one of the first to apply a fully replication-competent third-generation IAV reporter strain to a large-scale high-throughput screen (HTS) drug discovery campaign, allowing multicycle infection and screening in physiologically relevant human respiratory cells. A large number of potential druggable targets was thus chemically interrogated, but mechanistic characterization, positive target identification, and resistance profiling demonstrated that three chemically promising and structurally distinct hit classes selected for further analysis all block HA-mediated membrane fusion. Viral escape from inhibition could be achieved through primary and secondary resistance mechanisms. In silico docking predicted compound binding to a microdomain located at the membrane-distal site of the prefusion HA stalk that was also previously suggested as a target site for chemically unrelated HA inhibitors. This study identifies an unexpected chemodominance of the HA stalk microdomain for small-molecule inhibitors in IAV inhibitor screening campaigns and highlights a novel mechanism of cooperative resistance to IAV entry blockers. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Identification and Characterization of Influenza Virus Entry Inhibitors through Dual Myxovirus High-Throughput Screening

PubMed Central

Weisshaar, Marco; Cox, Robert; Morehouse, Zachary; Kumar Kyasa, Shiva; Yan, Dan; Oberacker, Phil; Mao, Shuli; Lowen, Anice C.; Natchus, Michael G.

2016-01-01

ABSTRACT Influenza A virus (IAV) infections cause major morbidity and mortality, generating an urgent need for novel antiviral therapeutics. We recently established a dual myxovirus high-throughput screening protocol that combines a fully replication-competent IAV-WSN strain and a respiratory syncytial virus reporter strain for the simultaneous identification of IAV-specific, paramyxovirus-specific, and broad-spectrum inhibitors. In the present study, this protocol was applied to a screening campaign to assess a diverse chemical library with over 142,000 entries. Focusing on IAV-specific hits, we obtained a hit rate of 0.03% after cytotoxicity testing and counterscreening. Three chemically distinct hit classes with nanomolar potency and favorable cytotoxicity profiles were selected. Time-of-addition, minigenome, and viral entry studies demonstrated that these classes block hemagglutinin (HA)-mediated membrane fusion. Antiviral activity extends to an isolate from the 2009 pandemic and, in one case, another group 1 subtype. Target identification through biolayer interferometry confirmed binding of all hit compounds to HA. Resistance profiling revealed two distinct escape mechanisms: primary resistance, associated with reduced compound binding, and secondary resistance, associated with unaltered binding. Secondary resistance was mediated, unusually, through two different pairs of cooperative mutations, each combining a mutation eliminating the membrane-proximal stalk N-glycan with a membrane-distal change in HA1 or HA2. Chemical synthesis of an analog library combined with in silico docking extracted a docking pose for the hit classes. Chemical interrogation spotlights IAV HA as a major druggable target for small-molecule inhibition. Our study identifies novel chemical scaffolds with high developmental potential, outlines diverse routes of IAV escape from entry inhibition, and establishes a path toward structure-aided lead development. IMPORTANCE This study is one of the first to apply a fully replication-competent third-generation IAV reporter strain to a large-scale high-throughput screen (HTS) drug discovery campaign, allowing multicycle infection and screening in physiologically relevant human respiratory cells. A large number of potential druggable targets was thus chemically interrogated, but mechanistic characterization, positive target identification, and resistance profiling demonstrated that three chemically promising and structurally distinct hit classes selected for further analysis all block HA-mediated membrane fusion. Viral escape from inhibition could be achieved through primary and secondary resistance mechanisms. In silico docking predicted compound binding to a microdomain located at the membrane-distal site of the prefusion HA stalk that was also previously suggested as a target site for chemically unrelated HA inhibitors. This study identifies an unexpected chemodominance of the HA stalk microdomain for small-molecule inhibitors in IAV inhibitor screening campaigns and highlights a novel mechanism of cooperative resistance to IAV entry blockers. PMID:27252534

Soil DNA metabarcoding and high-throughput sequencing as a forensic tool: considerations, potential limitations and recommendations.

PubMed

Young, J M; Austin, J J; Weyrich, L S

2017-02-01

Analysis of physical evidence is typically a deciding factor in forensic casework by establishing what transpired at a scene or who was involved. Forensic geoscience is an emerging multi-disciplinary science that can offer significant benefits to forensic investigations. Soil is a powerful, nearly 'ideal' contact trace evidence, as it is highly individualistic, easy to characterise, has a high transfer and retention probability, and is often overlooked in attempts to conceal evidence. However, many real-life cases encounter close proximity soil samples or soils with low inorganic content, which cannot be easily discriminated based on current physical and chemical analysis techniques. The capability to improve forensic soil discrimination, and identify key indicator taxa from soil using the organic fraction is currently lacking. The development of new DNA sequencing technologies offers the ability to generate detailed genetic profiles from soils and enhance current forensic soil analyses. Here, we discuss the use of DNA metabarcoding combined with high-throughput sequencing (HTS) technology to distinguish between soils from different locations in a forensic context. Specifically, we provide recommendations for best practice, outline the potential limitations encountered in a forensic context and describe the future directions required to integrate soil DNA analysis into casework. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Mapping of MPEG-4 decoding on a flexible architecture platform

NASA Astrophysics Data System (ADS)

van der Tol, Erik B.; Jaspers, Egbert G.

2001-12-01

In the field of consumer electronics, the advent of new features such as Internet, games, video conferencing, and mobile communication has triggered the convergence of television and computers technologies. This requires a generic media-processing platform that enables simultaneous execution of very diverse tasks such as high-throughput stream-oriented data processing and highly data-dependent irregular processing with complex control flows. As a representative application, this paper presents the mapping of a Main Visual profile MPEG-4 for High-Definition (HD) video onto a flexible architecture platform. A stepwise approach is taken, going from the decoder application toward an implementation proposal. First, the application is decomposed into separate tasks with self-contained functionality, clear interfaces, and distinct characteristics. Next, a hardware-software partitioning is derived by analyzing the characteristics of each task such as the amount of inherent parallelism, the throughput requirements, the complexity of control processing, and the reuse potential over different applications and different systems. Finally, a feasible implementation is proposed that includes amongst others a very-long-instruction-word (VLIW) media processor, one or more RISC processors, and some dedicated processors. The mapping study of the MPEG-4 decoder proves the flexibility and extensibility of the media-processing platform. This platform enables an effective HW/SW co-design yielding a high performance density.

High Throughput Transcriptomics: From screening to pathways

EPA Science Inventory

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

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.

High Throughput Experimental Materials Database

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

Zakutayev, Andriy; Perkins, John; Schwarting, Marcus

The mission of the High Throughput Experimental Materials Database (HTEM DB) is to enable discovery of new materials with useful properties by releasing large amounts of high-quality experimental data to public. The HTEM DB contains information about materials obtained from high-throughput experiments at the National Renewable Energy Laboratory (NREL).

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.

Novel approach of fragment-based lead discovery applied to renin inhibitors.

PubMed

Tawada, Michiko; Suzuki, Shinkichi; Imaeda, Yasuhiro; Oki, Hideyuki; Snell, Gyorgy; Behnke, Craig A; Kondo, Mitsuyo; Tarui, Naoki; Tanaka, Toshimasa; Kuroita, Takanobu; Tomimoto, Masaki

2016-11-15

A novel approach was conducted for fragment-based lead discovery and applied to renin inhibitors. The biochemical screening of a fragment library against renin provided the hit fragment which showed a characteristic interaction pattern with the target protein. The hit fragment bound only to the S1, S3, and S3 SP (S3 subpocket) sites without any interactions with the catalytic aspartate residues (Asp32 and Asp215 (pepsin numbering)). Prior to making chemical modifications to the hit fragment, we first identified its essential binding sites by utilizing the hit fragment's substructures. Second, we created a new and smaller scaffold, which better occupied the identified essential S3 and S3 SP sites, by utilizing library synthesis with high-throughput chemistry. We then revisited the S1 site and efficiently explored a good building block attaching to the scaffold with library synthesis. In the library syntheses, the binding modes of each pivotal compound were determined and confirmed by X-ray crystallography and the library was strategically designed by structure-based computational approach not only to obtain a more active compound but also to obtain informative Structure Activity Relationship (SAR). As a result, we obtained a lead compound offering synthetic accessibility as well as the improved in vitro ADMET profiles. The fragments and compounds possessing a characteristic interaction pattern provided new structural insights into renin's active site and the potential to create a new generation of renin inhibitors. In addition, we demonstrated our FBDD strategy integrating highly sensitive biochemical assay, X-ray crystallography, and high-throughput synthesis and in silico library design aimed at fragment morphing at the initial stage was effective to elucidate a pocket profile and a promising lead compound. Copyright © 2016 Elsevier Ltd. All rights reserved.

A translatable predictor of human radiation exposure.

PubMed

Lucas, Joseph; Dressman, Holly K; Suchindran, Sunil; Nakamura, Mai; Chao, Nelson J; Himburg, Heather; Minor, Kerry; Phillips, Gary; Ross, Joel; Abedi, Majid; Terbrueggen, Robert; Chute, John P

2014-01-01

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

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

EPA Science Inventory

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

Evaluation of Sequencing Approaches for High-Throughput Transcriptomics - (BOSC)

EPA Science Inventory

Whole-genome in vitro transcriptomics has shown the capability to identify mechanisms of action and estimates of potency for chemical-mediated effects in a toxicological framework, but with limited throughput and high cost. The generation of high-throughput global gene expression...

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

PubMed

Wright, Imogen A; Travers, Simon A

2014-07-01

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

High Throughput Determination of Critical Human Dosing Parameters (SOT)

EPA Science Inventory

High throughput toxicokinetics (HTTK) is a rapid approach that uses in vitro data to estimate TK for hundreds of environmental chemicals. Reverse dosimetry (i.e., reverse toxicokinetics or RTK) based on HTTK data converts high throughput in vitro toxicity screening (HTS) data int...

High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

EPA Science Inventory

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

Optimization of high-throughput nanomaterial developmental toxicity testing in zebrafish embryos

EPA Science Inventory

Nanomaterial (NM) developmental toxicities are largely unknown. With an extensive variety of NMs available, high-throughput screening methods may be of value for initial characterization of potential hazard. We optimized a zebrafish embryo test as an in vivo high-throughput assay...

High-Throughput Sequencing of microRNAs in Glucocorticoid Sensitive Paediatric Inflammatory Bowel Disease Patients.

PubMed

De Iudicibus, Sara; Lucafò, Marianna; Vitulo, Nicola; Martelossi, Stefano; Zimbello, Rosanna; De Pascale, Fabio; Forcato, Claudio; Naviglio, Samuele; Di Silvestre, Alessia; Gerdol, Marco; Stocco, Gabriele; Valle, Giorgio; Ventura, Alessandro; Bramuzzo, Matteo; Decorti, Giuliana

2018-05-08

The aim of this research was the identification of novel pharmacogenomic biomarkers for better understanding the complex gene regulation mechanisms underpinning glucocorticoid (GC) action in paediatric inflammatory bowel disease (IBD). This goal was achieved by evaluating high-throughput microRNA (miRNA) profiles during GC treatment, integrated with the assessment of expression changes in GC receptor (GR) heterocomplex genes. Furthermore, we tested the hypothesis that differentially expressed miRNAs could be directly regulated by GCs through investigating the presence of GC responsive elements (GREs) in their gene promoters. Ten IBD paediatric patients responding to GCs were enrolled. Peripheral blood was obtained at diagnosis (T0) and after four weeks of steroid treatment (T4). MicroRNA profiles were analyzed using next generation sequencing, and selected significantly differentially expressed miRNAs were validated by quantitative reverse transcription-polymerase chain reaction. In detail, 18 miRNAs were differentially expressed from T0 to T4, 16 of which were upregulated and 2 of which were downregulated. Out of these, three miRNAs (miR-144, miR-142, and miR-96) could putatively recognize the 3’UTR of the GR gene and three miRNAs (miR-363, miR-96, miR-142) contained GREs sequences, thereby potentially enabling direct regulation by the GR. In conclusion, we identified miRNAs differently expressed during GC treatment and miRNAs which could be directly regulated by GCs in blood cells of young IBD patients. These results could represent a first step towards their translation as pharmacogenomic biomarkers.

Simultaneous virtual prediction of anti-Escherichia coli activities and ADMET profiles: A chemoinformatic complementary approach for high-throughput screening.

PubMed

Speck-Planche, Alejandro; Cordeiro, M N D S

2014-02-10

Escherichia coli remains one of the principal pathogens that cause nosocomial infections, medical conditions that are increasingly common in healthcare facilities. E. coli is intrinsically resistant to many antibiotics, and multidrug-resistant strains have emerged recently. Chemoinformatics has been a great ally of experimental methodologies such as high-throughput screening, playing an important role in the discovery of effective antibacterial agents. However, there is no approach that can design safer anti-E. coli agents, because of the multifactorial nature and complexity of bacterial diseases and the lack of desirable ADMET (absorption, distribution, metabolism, elimination, and toxicity) profiles as a major cause of disapproval of drugs. In this work, we introduce the first multitasking model based on quantitative-structure biological effect relationships (mtk-QSBER) for simultaneous virtual prediction of anti-E. coli activities and ADMET properties of drugs and/or chemicals under many experimental conditions. The mtk-QSBER model was developed from a large and heterogeneous data set of more than 37800 cases, exhibiting overall accuracies of >95% in both training and prediction (validation) sets. The utility of our mtk-QSBER model was demonstrated by performing virtual prediction of properties for the investigational drug avarofloxacin (AVX) under 260 different experimental conditions. Results converged with the experimental evidence, confirming the remarkable anti-E. coli activities and safety of AVX. Predictions also showed that our mtk-QSBER model can be a promising computational tool for virtual screening of desirable anti-E. coli agents, and this chemoinformatic approach could be extended to the search for safer drugs with defined pharmacological activities.

Automated profiling of individual cell-cell interactions from high-throughput time-lapse imaging microscopy in nanowell grids (TIMING).

PubMed

Merouane, Amine; Rey-Villamizar, Nicolas; Lu, Yanbin; Liadi, Ivan; Romain, Gabrielle; Lu, Jennifer; Singh, Harjeet; Cooper, Laurence J N; Varadarajan, Navin; Roysam, Badrinath

2015-10-01

There is a need for effective automated methods for profiling dynamic cell-cell interactions with single-cell resolution from high-throughput time-lapse imaging data, especially, the interactions between immune effector cells and tumor cells in adoptive immunotherapy. Fluorescently labeled human T cells, natural killer cells (NK), and various target cells (NALM6, K562, EL4) were co-incubated on polydimethylsiloxane arrays of sub-nanoliter wells (nanowells), and imaged using multi-channel time-lapse microscopy. The proposed cell segmentation and tracking algorithms account for cell variability and exploit the nanowell confinement property to increase the yield of correctly analyzed nanowells from 45% (existing algorithms) to 98% for wells containing one effector and a single target, enabling automated quantification of cell locations, morphologies, movements, interactions, and deaths without the need for manual proofreading. Automated analysis of recordings from 12 different experiments demonstrated automated nanowell delineation accuracy >99%, automated cell segmentation accuracy >95%, and automated cell tracking accuracy of 90%, with default parameters, despite variations in illumination, staining, imaging noise, cell morphology, and cell clustering. An example analysis revealed that NK cells efficiently discriminate between live and dead targets by altering the duration of conjugation. The data also demonstrated that cytotoxic cells display higher motility than non-killers, both before and during contact. broysam@central.uh.edu or nvaradar@central.uh.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

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

Distinct seasonal infectious agent profiles in life-history variants of juvenile Fraser River Chinook salmon: An application of high-throughput genomic screening.

PubMed

Tucker, Strahan; Li, Shaorong; Kaukinen, Karia H; Patterson, David A; Miller, Kristina M

2018-01-01

Disease-causing infectious agents are natural components of ecosystems and considered a major selective force driving the evolution of host species. However, knowledge of the presence and abundance of suites of infectious agents in wild populations has been constrained by our ability to easily screen for them. Using salmon as a model, we contrasted seasonal pathogenic infectious agents in life history variants of juvenile Chinook salmon from the Fraser River system (N = 655), British Columbia (BC), through the application of a novel high-throughput quantitative PCR monitoring platform. This included freshwater hatchery origin fish and samples taken at sea between ocean entry in spring and over-winter residence in coastal waters. These variants currently display opposite trends in productivity, with yearling stocks generally in decline and sub-yearling stocks doing comparatively well. We detected the presence of 32 agents, 21 of which were at >1% prevalence. Variants carried a different infectious agent profile in terms of (1) diversity, (2) origin or transmission environment of infectious agents, and (3) prevalence and abundance of individual agents. Differences in profiles tended to reflect differential timing and residence patterns through freshwater, estuarine and marine habitats. Over all seasons, individual salmon carried an average of 3.7 agents. Diversity changed significantly, increasing upon saltwater entrance, increasing through the fall and decreasing slightly in winter. Diversity varied between life history types with yearling individuals carrying 1.3-times more agents on average. Shifts in prevalence and load over time were examined to identify agents with the greatest potential for impact at the stock level; those displaying concurrent decrease in prevalence and load truncation with time. Of those six that had similar patterns in both variants, five reached higher prevalence in yearling fish while only one reached higher prevalence in sub-yearling fish; this pattern was present for an additional five agents in yearling fish only.

Gene expression profiling reveals underlying molecular mechanisms of the early stages of tamoxifen-induced rat hepatocarcinogenesis

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

Pogribny, Igor P.; Bagnyukova, Tetyana V.; Tryndyak, Volodymyr P.

2007-11-15

Tamoxifen is a widely used anti-estrogenic drug for chemotherapy and, more recently, for the chemoprevention of breast cancer. Despite the indisputable benefits of tamoxifen in preventing the occurrence and re-occurrence of breast cancer, the use of tamoxifen has been shown to induce non-alcoholic steatohepatitis, which is a life-threatening fatty liver disease with a risk of progression to cirrhosis and hepatocellular carcinoma. In recent years, the high-throughput microarray technology for large-scale analysis of gene expression has become a powerful tool for increasing the understanding of the molecular mechanisms of carcinogenesis and for identifying new biomarkers with diagnostic and predictive values. Inmore » the present study, we used the high-throughput microarray technology to determine the gene expression profiles in the liver during early stages of tamoxifen-induced rat hepatocarcinogenesis. Female Fisher 344 rats were fed a 420 ppm tamoxifen containing diet for 12 or 24 weeks, and gene expression profiles were determined in liver of control and tamoxifen-exposed rats. The results indicate that early stages of tamoxifen-induced liver carcinogenesis are characterized by alterations in several major cellular pathways, specifically those involved in the tamoxifen metabolism, lipid metabolism, cell cycle signaling, and apoptosis/cell proliferation control. One of the most prominent changes during early stages of tamoxifen-induced hepatocarcinogenesis is dysregulation of signaling pathways in cell cycle progression from the G{sub 1} to S phase, evidenced by the progressive and sustained increase in expression of the Pdgfc, Calb3, Ets1, and Ccnd1 genes accompanied by the elevated level of the PI3K, p-PI3K, Akt1/2, Akt3, and cyclin B, D1, and D3 proteins. The early appearance of these alterations suggests their importance in the mechanism of neoplastic cell transformation induced by tamoxifen.« less

High-throughput informative single nucleotide polymorphism-based typing of Neisseria gonorrhoeae using the Sequenom MassARRAY iPLEX platform.

PubMed

Trembizki, Ella; Smith, Helen; Lahra, Monica M; Chen, Marcus; Donovan, Basil; Fairley, Christopher K; Guy, Rebecca; Kaldor, John; Regan, David; Ward, James; Nissen, Michael D; Sloots, Theo P; Whiley, David M

2014-06-01

Neisseria gonorrhoeae antimicrobial resistance (AMR) is a global problem heightened by emerging resistance to ceftriaxone. Appropriate molecular typing methods are important for understanding the emergence and spread of N. gonorrhoeae AMR. We report on the development, validation and testing of a Sequenom MassARRAY iPLEX method for multilocus sequence typing (MLST)-style genotyping of N. gonorrhoeae isolates. An iPLEX MassARRAY method (iPLEX14SNP) was developed targeting 14 informative gonococcal single nucleotide polymorphisms (SNPs) previously shown to predict MLST types. The method was initially validated using 24 N. gonorrhoeae control isolates and was then applied to 397 test isolates collected throughout Queensland, Australia in the first half of 2012. The iPLEX14SNP method provided 100% accuracy for the control isolates, correctly identifying all 14 SNPs for all 24 isolates (336/336). For the 397 test isolates, the iPLEX14SNP assigned results for 5461 of the possible 5558 SNPs (SNP call rate 98.25%), with complete 14 SNP profiles obtained for 364 isolates. Based on the complete SNP profile data, there were 49 different sequence types identified in Queensland, with 11 of the 49 SNP profiles accounting for the majority (n = 280; 77%) of isolates. AMR was dominated by several geographically clustered sequence types. Using the iPLEX14SNP method, up to 384 isolates could be tested within 1 working day for less than Aus$10 per isolate. The iPLEX14SNP offers an accurate and high-throughput method for the MLST-style genotyping of N. gonorrhoeae and may prove particularly useful for large-scale studies investigating the emergence and spread of gonococcal AMR. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High-Throughput Data of Circular RNA Profiles in Human Temporal Cortex Tissue Reveals Novel Insights into Temporal Lobe Epilepsy.

PubMed

Li, Jiaxin; Lin, Haijun; Sun, Zhenrong; Kong, Guanyi; Yan, Xu; Wang, Yujiao; Wang, Xiaoxuan; Wen, Yanhua; Liu, Xiang; Zheng, Hongkun; Jia, Mei; Shi, Zhongfang; Xu, Rong; Yang, Shaohua; Yuan, Fang

2018-01-01

Circular RNAs (circRNAs) are a class of long noncoding RNAs with a closed loop structure that regulate gene expression as microRNA sponges. CircRNAs are more enriched in brain tissue, but knowledge of the role of circRNAs in temporal lobe epilepsy (TLE) has remained limited. This study is the first to identify the global expression profiles and characteristics of circRNAs in human temporal cortex tissue from TLE patients. Temporal cortices were collected from 17 TLE patients and 17 non-TLE patients. Total RNA was isolated, and high-throughput sequencing was used to profile the transcriptome of dysregulated circRNAs. Quantitative PCR was performed for the validation of changed circRNAs. In total, 78983 circRNAs, including 15.29% known and 84.71% novel circRNAs, were detected in this study. Intriguingly, 442 circRNAs were differentially expressed between the TLE and non-TLE groups (fold change≥2.0 and FDR≤0.05). Of these circRNAs, 188 were up-regulated, and 254 were down-regulated in the TLE patient group. Eight circRNAs were validated by real-time PCR. Remarkably, circ-EFCAB2 was intensely up-regulated, while circ-DROSHA expression was significantly lower in the TLE group than in the non-TLE group (P<0.05). Bioinformatic analysis revealed that circ-EFCAB2 binds to miR-485-5p to increase the expression level of the ion channel CLCN6, while circ-DROSHA interacts with miR-1252-5p to decrease the expression level of ATP1A2. The dysregulations of circRNAs may reflect the pathogenesis of TLE and circ-EFCAB2 and circ-DROSHA might be potential therapeutic targets and biomarkers in TLE patients. © 2018 The Author(s). Published by S. Karger AG, Basel.

Metabolite Profiling and Cardiovascular Event Risk: A Prospective Study of Three Population-Based Cohorts

PubMed Central

Würtz, Peter; Havulinna, Aki S; Soininen, Pasi; Tynkkynen, Tuulia; Prieto-Merino, David; Tillin, Therese; Ghorbani, Anahita; Artati, Anna; Wang, Qin; Tiainen, Mika; Kangas, Antti J; Kettunen, Johannes; Kaikkonen, Jari; Mikkilä, Vera; Jula, Antti; Kähönen, Mika; Lehtimäki, Terho; Lawlor, Debbie A; Gaunt, Tom R; Hughes, Alun D; Sattar, Naveed; Illig, Thomas; Adamski, Jerzy; Wang, Thomas J; Perola, Markus; Ripatti, Samuli; Vasan, Ramachandran S; Raitakari, Olli T; Gerszten, Robert E; Casas, Juan-Pablo; Chaturvedi, Nish; Ala-Korpela, Mika; Salomaa, Veikko

2015-01-01

Background High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors. Methods and Results We applied quantitative NMR metabolomics to identify biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the SABRE study (n=2622; 573 events) and British Women’s Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes and medication. When further adjusting for routine lipids, four metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation: 1.18 [95%CI 1.12–1.24]; P=4×10−10) and monounsaturated fatty acid levels (1.17 [1.11–1.24]; P=1×10−8) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89 [0.84–0.94]; P=6×10−5) and docosahexaenoic acid levels (0.90 [0.86–0.95]; P=5×10−5) were associated with lower risk. A risk score incorporating these four biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the two validation cohorts (relative integrated discrimination improvement 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5–10% risk range (net reclassification 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289). Conclusions Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment. PMID:25573147

Distinct seasonal infectious agent profiles in life-history variants of juvenile Fraser River Chinook salmon: An application of high-throughput genomic screening

PubMed Central

Li, Shaorong; Kaukinen, Karia H.; Patterson, David A.; Miller, Kristina M.

2018-01-01

Disease-causing infectious agents are natural components of ecosystems and considered a major selective force driving the evolution of host species. However, knowledge of the presence and abundance of suites of infectious agents in wild populations has been constrained by our ability to easily screen for them. Using salmon as a model, we contrasted seasonal pathogenic infectious agents in life history variants of juvenile Chinook salmon from the Fraser River system (N = 655), British Columbia (BC), through the application of a novel high-throughput quantitative PCR monitoring platform. This included freshwater hatchery origin fish and samples taken at sea between ocean entry in spring and over-winter residence in coastal waters. These variants currently display opposite trends in productivity, with yearling stocks generally in decline and sub-yearling stocks doing comparatively well. We detected the presence of 32 agents, 21 of which were at >1% prevalence. Variants carried a different infectious agent profile in terms of (1) diversity, (2) origin or transmission environment of infectious agents, and (3) prevalence and abundance of individual agents. Differences in profiles tended to reflect differential timing and residence patterns through freshwater, estuarine and marine habitats. Over all seasons, individual salmon carried an average of 3.7 agents. Diversity changed significantly, increasing upon saltwater entrance, increasing through the fall and decreasing slightly in winter. Diversity varied between life history types with yearling individuals carrying 1.3-times more agents on average. Shifts in prevalence and load over time were examined to identify agents with the greatest potential for impact at the stock level; those displaying concurrent decrease in prevalence and load truncation with time. Of those six that had similar patterns in both variants, five reached higher prevalence in yearling fish while only one reached higher prevalence in sub-yearling fish; this pattern was present for an additional five agents in yearling fish only. PMID:29672620

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

EPA Pesticide Factsheets

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

Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

EPA Science Inventory

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

High-throughput RAD-SNP genotyping for characterization of sugar beet genotypes

USDA-ARS?s Scientific Manuscript database

High-throughput SNP genotyping provides a rapid way of developing resourceful set of markers for delineating the genetic architecture and for effective species discrimination. In the presented research, we demonstrate a set of 192 SNPs for effective genotyping in sugar beet using high-throughput mar...

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

EPA Science Inventory

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

Plant-RRBS, a bisulfite and next-generation sequencing-based methylome profiling method enriching for coverage of cytosine positions.

PubMed

Schmidt, Martin; Van Bel, Michiel; Woloszynska, Magdalena; Slabbinck, Bram; Martens, Cindy; De Block, Marc; Coppens, Frederik; Van Lijsebettens, Mieke

2017-07-06

Cytosine methylation in plant genomes is important for the regulation of gene transcription and transposon activity. Genome-wide methylomes are studied upon mutation of the DNA methyltransferases, adaptation to environmental stresses or during development. However, from basic biology to breeding programs, there is a need to monitor multiple samples to determine transgenerational methylation inheritance or differential cytosine methylation. Methylome data obtained by sodium hydrogen sulfite (bisulfite)-conversion and next-generation sequencing (NGS) provide genome-wide information on cytosine methylation. However, a profiling method that detects cytosine methylation state dispersed over the genome would allow high-throughput analysis of multiple plant samples with distinct epigenetic signatures. We use specific restriction endonucleases to enrich for cytosine coverage in a bisulfite and NGS-based profiling method, which was compared to whole-genome bisulfite sequencing of the same plant material. We established an effective methylome profiling method in plants, termed plant-reduced representation bisulfite sequencing (plant-RRBS), using optimized double restriction endonuclease digestion, fragment end repair, adapter ligation, followed by bisulfite conversion, PCR amplification and NGS. We report a performant laboratory protocol and a straightforward bioinformatics data analysis pipeline for plant-RRBS, applicable for any reference-sequenced plant species. As a proof of concept, methylome profiling was performed using an Oryza sativa ssp. indica pure breeding line and a derived epigenetically altered line (epiline). Plant-RRBS detects methylation levels at tens of millions of cytosine positions deduced from bisulfite conversion in multiple samples. To evaluate the method, the coverage of cytosine positions, the intra-line similarity and the differential cytosine methylation levels between the pure breeding line and the epiline were determined. Plant-RRBS reproducibly covers commonly up to one fourth of the cytosine positions in the rice genome when using MspI-DpnII within a group of five biological replicates of a line. The method predominantly detects cytosine methylation in putative promoter regions and not-annotated regions in rice. Plant-RRBS offers high-throughput and broad, genome-dispersed methylation detection by effective read number generation obtained from reproducibly covered genome fractions using optimized endonuclease combinations, facilitating comparative analyses of multi-sample studies for cytosine methylation and transgenerational stability in experimental material and plant breeding populations.

A quantitative literature-curated gold standard for kinase-substrate pairs

PubMed Central

2011-01-01

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future. PMID:21492431

High-Throughput Industrial Coatings Research at The Dow Chemical Company.

PubMed

Kuo, Tzu-Chi; Malvadkar, Niranjan A; Drumright, Ray; Cesaretti, Richard; Bishop, Matthew T

2016-09-12

At The Dow Chemical Company, high-throughput research is an active area for developing new industrial coatings products. Using the principles of automation (i.e., using robotic instruments), parallel processing (i.e., prepare, process, and evaluate samples in parallel), and miniaturization (i.e., reduce sample size), high-throughput tools for synthesizing, formulating, and applying coating compositions have been developed at Dow. In addition, high-throughput workflows for measuring various coating properties, such as cure speed, hardness development, scratch resistance, impact toughness, resin compatibility, pot-life, surface defects, among others have also been developed in-house. These workflows correlate well with the traditional coatings tests, but they do not necessarily mimic those tests. The use of such high-throughput workflows in combination with smart experimental designs allows accelerated discovery and commercialization.

Outlook for Development of High-throughput Cryopreservation for Small-bodied Biomedical Model Fishes★

PubMed Central

Tiersch, Terrence R.; Yang, Huiping; Hu, E.

2011-01-01

With the development of genomic research technologies, comparative genome studies among vertebrate species are becoming commonplace for human biomedical research. Fish offer unlimited versatility for biomedical research. Extensive studies are done using these fish models, yielding tens of thousands of specific strains and lines, and the number is increasing every day. Thus, high-throughput sperm cryopreservation is urgently needed to preserve these genetic resources. Although high-throughput processing has been widely applied for sperm cryopreservation in livestock for decades, application in biomedical model fishes is still in the concept-development stage because of the limited sample volumes and the biological characteristics of fish sperm. High-throughput processing in livestock was developed based on advances made in the laboratory and was scaled up for increased processing speed, capability for mass production, and uniformity and quality assurance. Cryopreserved germplasm combined with high-throughput processing constitutes an independent industry encompassing animal breeding, preservation of genetic diversity, and medical research. Currently, there is no specifically engineered system available for high-throughput of cryopreserved germplasm for aquatic species. This review is to discuss the concepts and needs for high-throughput technology for model fishes, propose approaches for technical development, and overview future directions of this approach. PMID:21440666

High-Throughput Analysis of Sucrose Fatty Acid Esters by Supercritical Fluid Chromatography/Tandem Mass Spectrometry

PubMed Central

Hori, Katsuhito; Tsumura, Kazunobu; Fukusaki, Eiichiro; Bamba, Takeshi

2014-01-01

Supercritical fluid chromatography (SFC) coupled with triple quadrupole mass spectrometry was applied to the profiling of sucrose fatty acid esters (SEs). The SFC conditions (column and modifier gradient) were optimized for the effective separation of SEs. In the column test, a silica gel reversed-phase column was selected. Then, the method was used for the detailed characterization of commercial SEs and the successful analysis of SEs containing different fatty acids. The present method allowed for fast and high-resolution separation of monoesters to tetra-esters within a shorter time (15 min) as compared to the conventional high-performance liquid chromatography. The applicability of our method for the analysis of SEs was thus demonstrated. PMID:26819875

Analysis of translation using polysome profiling

PubMed Central

Chassé, Héloïse; Boulben, Sandrine; Costache, Vlad; Cormier, Patrick

2017-01-01

Abstract During the past decade, there has been growing interest in the role of translational regulation of gene expression in many organisms. Polysome profiling has been developed to infer the translational status of a specific mRNA species or to analyze the translatome, i.e. the subset of mRNAs actively translated in a cell. Polysome profiling is especially suitable for emergent model organisms for which genomic data are limited. In this paper, we describe an optimized protocol for the purification of sea urchin polysomes and highlight the critical steps involved in polysome purification. We applied this protocol to obtain experimental results on translational regulation of mRNAs following fertilization. Our protocol should prove useful for integrating the study of the role of translational regulation in gene regulatory networks in any biological model. In addition, we demonstrate how to carry out high-throughput processing of polysome gradient fractions, for the simultaneous screening of multiple biological conditions and large-scale preparation of samples for next-generation sequencing. PMID:28180329

Ribosome A and P sites revealed by length analysis of ribosome profiling data

PubMed Central

Martens, Andrew T.; Taylor, James; Hilser, Vincent J.

2015-01-01

The high-throughput sequencing of nuclease-protected mRNA fragments bound to ribosomes, a technique known as ribosome profiling, quantifies the relative frequencies with which different regions of transcripts are translated. This technique has revealed novel translation initiation sites with unprecedented scope and has furthered investigations into the connections between codon biases and translation rates. Yet the location of the codon being decoded in ribosome footprints is still unknown, and has been complicated by the recent observation of footprints with non-canonical lengths. Here we show how taking into account the variations in ribosome footprint lengths can reveal the ribosome aminoacyl (A) and peptidyl (P) site locations. These location assignments are in agreement with the proposed mechanisms for various ribosome pauses and further enhance the resolution of the profiling data. We also show that GC-rich motifs at the 5′ ends of footprints are found in yeast, calling into question the anti-Shine-Dalgarno effect's role in ribosome pausing. PMID:25805170

Antitrypanosomal lead discovery: Identification of a ligand-efficient inhibitor of Trypanosoma cruzi CYP51 and parasite growth

PubMed Central

Andriani, Grasiella; Amata, Emanuele; Beatty, Joel; Clements, Zeke; Coffey, Brian J.; Courtemanche, Gilles; Devine, William; Erath, Jessey; Juda, Cristin E.; Wawrzak, Zdzislaw; Wood, JodiAnne T.; Lepesheva, Galina I.; Rodriguez, Ana; Pollastri, Michael P.

2013-01-01

Chagas disease is caused by the intracellular protozoan parasite Trypanosomal cruzi, and current drugs are lacking in terms of desired safety and efficacy profiles. Following on a recently reported high-throughput screening campaign, we have explored initial structure-activity relationships around a class of imidazole-based compounds. This profiling has uncovered compounds 4c (NEU321) and 4j (NEU704), which are potent against in vitro cultures of T. cruzi and are greater than 160-fold selective over host cells. We report in vitro drug metabolism and properties profiling of 4c and show that this chemotype inhibits the T cruzi CYP51 enzyme, an observation confirmed by X-ray crystallographic analysis. We compare the binding orientation of 4c to that of other, previously reported inhibitors. We show that 4c displays a significantly better ligand efficiency and a shorter synthetic route over previously disclosed CYP51 inhibitors, and should therefore be considered a promising lead compound for further optimization. PMID:23448316

Expression profiling of peroxisome proliferator-activated receptor-delta (PPAR-delta) in mouse tissues using tissue microarray.

PubMed

Higashiyama, Hiroyuki; Billin, Andrew N; Okamoto, Yuji; Kinoshita, Mine; Asano, Satoshi

2007-05-01

Peroxisome proliferator-activated receptor-delta (PPAR-delta) is known as a transcription factor involved in the regulation of fatty acid oxidation and mitochondrial biogenesis in several tissues, such as skeletal muscle, liver and adipose tissues. In this study, to elucidate systemic physiological functions of PPAR-delta, we examined the tissue distribution and localization of PPAR-delta in adult mouse tissues using tissue microarray (TMA)-based immunohistochemistry. PPAR-delta positive signals were observed on variety of tissues/cells in multiple systems including cardiovascular, urinary, respiratory, digestive, endocrine, nervous, hematopoietic, immune, musculoskeletal, sensory and reproductive organ systems. In these organs, PPAR-delta immunoreactivity was generally localized on the nucleus, although cytoplasmic localization was observed on several cell types including neurons in the nervous system and cells of the islet of Langerhans. These expression profiling data implicate various physiological roles of PPAR-delta in multiple organ systems. TMA-based immunohistochemistry enables to profile comprehensive protein localization and distribution in a high-throughput manner.

Uniform, optimal signal processing of mapped deep-sequencing data.

PubMed

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

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

PubMed

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

2017-07-01

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

High-throughput measurements of biochemical responses using the plate::vision multimode 96 minilens array reader.

PubMed

Huang, Kuo-Sen; Mark, David; Gandenberger, Frank Ulrich

2006-01-01

The plate::vision is a high-throughput multimode reader capable of reading absorbance, fluorescence, fluorescence polarization, time-resolved fluorescence, and luminescence. Its performance has been shown to be quite comparable with other readers. When the reader is integrated into the plate::explorer, an ultrahigh-throughput screening system with event-driven software and parallel plate-handling devices, it becomes possible to run complicated assays with kinetic readouts in high-density microtiter plate formats for high-throughput screening. For the past 5 years, we have used the plate::vision and the plate::explorer to run screens and have generated more than 30 million data points. Their throughput, performance, and robustness have speeded up our drug discovery process greatly.

Application of high-throughput mini-bioreactor system for systematic scale-down modeling, process characterization, and control strategy development.

PubMed

Janakiraman, Vijay; Kwiatkowski, Chris; Kshirsagar, Rashmi; Ryll, Thomas; Huang, Yao-Ming

2015-01-01

High-throughput systems and processes have typically been targeted for process development and optimization in the bioprocessing industry. For process characterization, bench scale bioreactors have been the system of choice. Due to the need for performing different process conditions for multiple process parameters, the process characterization studies typically span several months and are considered time and resource intensive. In this study, we have shown the application of a high-throughput mini-bioreactor system viz. the Advanced Microscale Bioreactor (ambr15(TM) ), to perform process characterization in less than a month and develop an input control strategy. As a pre-requisite to process characterization, a scale-down model was first developed in the ambr system (15 mL) using statistical multivariate analysis techniques that showed comparability with both manufacturing scale (15,000 L) and bench scale (5 L). Volumetric sparge rates were matched between ambr and manufacturing scale, and the ambr process matched the pCO2 profiles as well as several other process and product quality parameters. The scale-down model was used to perform the process characterization DoE study and product quality results were generated. Upon comparison with DoE data from the bench scale bioreactors, similar effects of process parameters on process yield and product quality were identified between the two systems. We used the ambr data for setting action limits for the critical controlled parameters (CCPs), which were comparable to those from bench scale bioreactor data. In other words, the current work shows that the ambr15(TM) system is capable of replacing the bench scale bioreactor system for routine process development and process characterization. © 2015 American Institute of Chemical Engineers.

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

High-throughput profiling of antibiotic resistance genes in drinking water treatment plants and distribution systems.

PubMed

Xu, Like; Ouyang, Weiying; Qian, Yanyun; Su, Chao; Su, Jianqiang; Chen, Hong

2016-06-01

Antibiotic resistance genes (ARGs) are present in surface water and often cannot be completely eliminated by drinking water treatment plants (DWTPs). Improper elimination of the ARG-harboring microorganisms contaminates the water supply and would lead to animal and human disease. Therefore, it is of utmost importance to determine the most effective ways by which DWTPs can eliminate ARGs. Here, we tested water samples from two DWTPs and distribution systems and detected the presence of 285 ARGs, 8 transposases, and intI-1 by utilizing high-throughput qPCR. The prevalence of ARGs differed in the two DWTPs, one of which employed conventional water treatments while the other had advanced treatment processes. The relative abundance of ARGs increased significantly after the treatment with biological activated carbon (BAC), raising the number of detected ARGs from 76 to 150. Furthermore, the final chlorination step enhanced the relative abundance of ARGs in the finished water generated from both DWTPs. The total enrichment of ARGs varied from 6.4-to 109.2-fold in tap water compared to finished water, among which beta-lactam resistance genes displayed the highest enrichment. Six transposase genes were detected in tap water samples, with the transposase gene TnpA-04 showing the greatest enrichment (up to 124.9-fold). We observed significant positive correlations between ARGs and mobile genetic elements (MGEs) during the distribution systems, indicating that transposases and intI-1 may contribute to antibiotic resistance in drinking water. To our knowledge, this is the first study to investigate the diversity and abundance of ARGs in drinking water treatment systems utilizing high-throughput qPCR techniques in China. Copyright © 2016 Elsevier Ltd. All rights reserved.

Air Traffic Management Technology Demonstration-1 Concept of Operations (ATD-1 ConOps)

NASA Technical Reports Server (NTRS)

Baxley, Brian T.; Johnson, William C.; Swenson, Harry; Robinson, John E.; Prevot, Thomas; Callantine, Todd; Scardina, John; Greene, Michael

2012-01-01

The operational goal of the ATD-1 ConOps is to enable aircraft, using their onboard FMS capabilities, to fly Optimized Profile Descents (OPDs) from cruise to the runway threshold at a high-density airport, at a high throughput rate, using primarily speed control to maintain in-trail separation and the arrival schedule. The three technologies in the ATD-1 ConOps achieve this by calculating a precise arrival schedule, using controller decision support tools to provide terminal controllers with speeds for aircraft to fly to meet times at a particular meter points, and onboard software providing flight crews with speeds for the aircraft to fly to achieve a particular spacing behind preceding aircraft.

The technology and biology of single-cell RNA sequencing.

PubMed

Kolodziejczyk, Aleksandra A; Kim, Jong Kyoung; Svensson, Valentine; Marioni, John C; Teichmann, Sarah A

2015-05-21

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Next Generation Sequencing Technology and Genomewide Data Analysis: Perspectives for Retinal Research

PubMed Central

Chaitankar, Vijender; Karakülah, Gökhan; Ratnapriya, Rinki; Giuste, Felipe O.; Brooks, Matthew J.; Swaroop, Anand

2016-01-01

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well. PMID:27297499

Differentially expressed circulating microRNAs in the development of acute diabetic Charcot foot.

PubMed

Pasquier, Jennifer; Ramachandran, Vimal; Abu-Qaoud, Moh'd Rasheed; Thomas, Binitha; Benurwar, Manasi J; Chidiac, Omar; Hoarau-Véchot, Jessica; Robay, Amal; Fakhro, Khalid; Menzies, Robert A; Jayyousi, Amin; Zirie, Mahmoud; Al Suwaidi, Jassim; Malik, Rayaz A; Talal, Talal K; Najafi-Shoushtari, Seyed Hani; Rafii, Arash; Abi Khalil, Charbel

2018-06-05

Charcot foot (CF) is a rare complication of Type 2 diabetes (T2D). We assessed circulating miRNAs in 17 patients with T2D and acute CF (G1), 17 patients with T2D (G2) and equivalent neuropathy and 17 patients with T2D without neuropathy (G3) using the high-throughput miRNA expression profiling. 51 significantly deregulated miRNAs were identified in G1 versus G2, 37 in G1 versus G3 and 64 in G2 versus G3. Furthermore, we demonstrated that 16 miRNAs differentially expressed between G1 versus G2 could be involved in osteoclastic differentiation. Among them, eight are key factors involved in CF pathophysiology. Our data reveal that CF patients exhibit an altered expression profile of circulating miRNAs.

Primary Characterization of Small RNAs in Symbiotic Nitrogen-Fixing Bacteria.

PubMed

Robledo, Marta; García-Tomsig, Natalia I; Jiménez-Zurdo, José I

2018-01-01

High-throughput transcriptome profiling (RNAseq) has uncovered large and heterogeneous populations of small noncoding RNA species (sRNAs) with potential regulatory roles in bacteria. A large fraction of sRNAs are differentially regulated and rely on protein-assisted antisense interactions to trans-encoded target mRNAs to fine-tune posttranscriptional reprogramming of gene expression in response to external cues. However, annotation and function of sRNAs are still largely overlooked in nonmodel bacteria with complex lifestyles. Here, we describe experimental protocols successfully applied for the accurate annotation, expression profiling and target mRNA identification of trans-acting sRNAs in the nitrogen-fixing α-rhizobium Sinorhizobium meliloti. The protocols presented here can be similarly applied for the characterization of trans-sRNAs in genetically tractable α-proteobacteria of agronomical or clinical relevance interacting with eukaryotic hosts.

High-throughput shock investigation of thin film thermites and thermites in fluoropolymer binder

NASA Astrophysics Data System (ADS)

Matveev, Sergey; Basset, Will; Dlott, Dana; Lee, Evyn; Maria, Jon-Paul; University of Illinois at Urbana-Champaign Collaboration; North Carolina State University Collaboration

2017-06-01

Investigation of nanofabricated thermite systems with respect to their energy release is presented. The knowledge obtained by utilization of a high-throughput tabletop shock-system provides essential information that can be used to tune properties of reactive materials towards a desired application. Our shock system launches 0.25-0.75 mm flyer plates, which can reach velocities of 0.5-6 km s-1 and shock durations of 4 - 16 ns. In current studies, emission was detected by a home-built pyrometer. Various reactive materials with differing composition (Al/CuO and Zr/CuO nanolaminates; Al/CuO/PVDF); Al, Zr, CuO standards) and varying interfacial area, were impacted at velocities spanning the available range to ascertain reaction thresholds. Our results show that reaction-impact threshold for the thermite systems under consideration is <1 km/s and that reaction starts at a time as short as 20 ns. Utilization of graybody approximation provides temperature profiles along the reaction time. In future, our goal is to expand detection capabilities utilizing infrared absorption to analyze formation of the products after the shock. The work is supported by the U.S. Army Research Office under Award W911NF-16-1-0406.

Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies.

PubMed

Kakourou, Alexia; Vach, Werner; Nicolardi, Simone; van der Burgt, Yuri; Mertens, Bart

2016-10-01

Mass spectrometry based clinical proteomics has emerged as a powerful tool for high-throughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry technology have boosted the potential of proteomic studies in biomedical research. However, the complexity of the proteomic expression introduces new statistical challenges in summarizing and analyzing the acquired data. Statistical methods for optimally processing proteomic data are currently a growing field of research. In this paper we present simple, yet appropriate methods to preprocess, summarize and analyze high-throughput MALDI-FTICR mass spectrometry data, collected in a case-control fashion, while dealing with the statistical challenges that accompany such data. The known statistical properties of the isotopic distribution of the peptide molecules are used to preprocess the spectra and translate the proteomic expression into a condensed data set. Information on either the intensity level or the shape of the identified isotopic clusters is used to derive summary measures on which diagnostic rules for disease status allocation will be based. Results indicate that both the shape of the identified isotopic clusters and the overall intensity level carry information on the class outcome and can be used to predict the presence or absence of the disease.

NCBI GEO: archive for functional genomics data sets--10 years on.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Evangelista, Carlos; Kim, Irene F; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Holko, Michelle; Ayanbule, Oluwabukunmi; Yefanov, Andrey; Soboleva, Alexandra

2011-01-01

A decade ago, the Gene Expression Omnibus (GEO) database was established at the National Center for Biotechnology Information (NCBI). The original objective of GEO was to serve as a public repository for high-throughput gene expression data generated mostly by microarray technology. However, the research community quickly applied microarrays to non-gene-expression studies, including examination of genome copy number variation and genome-wide profiling of DNA-binding proteins. Because the GEO database was designed with a flexible structure, it was possible to quickly adapt the repository to store these data types. More recently, as the microarray community switches to next-generation sequencing technologies, GEO has again adapted to host these data sets. Today, GEO stores over 20,000 microarray- and sequence-based functional genomics studies, and continues to handle the majority of direct high-throughput data submissions from the research community. Multiple mechanisms are provided to help users effectively search, browse, download and visualize the data at the level of individual genes or entire studies. This paper describes recent database enhancements, including new search and data representation tools, as well as a brief review of how the community uses GEO data. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

A Pipeline for High-Throughput Concentration Response Modeling of Gene Expression for Toxicogenomics

PubMed Central

House, John S.; Grimm, Fabian A.; Jima, Dereje D.; Zhou, Yi-Hui; Rusyn, Ivan; Wright, Fred A.

2017-01-01

Cell-based assays are an attractive option to measure gene expression response to exposure, but the cost of whole-transcriptome RNA sequencing has been a barrier to the use of gene expression profiling for in vitro toxicity screening. In addition, standard RNA sequencing adds variability due to variable transcript length and amplification. Targeted probe-sequencing technologies such as TempO-Seq, with transcriptomic representation that can vary from hundreds of genes to the entire transcriptome, may reduce some components of variation. Analyses of high-throughput toxicogenomics data require renewed attention to read-calling algorithms and simplified dose–response modeling for datasets with relatively few samples. Using data from induced pluripotent stem cell-derived cardiomyocytes treated with chemicals at varying concentrations, we describe here and make available a pipeline for handling expression data generated by TempO-Seq to align reads, clean and normalize raw count data, identify differentially expressed genes, and calculate transcriptomic concentration–response points of departure. The methods are extensible to other forms of concentration–response gene-expression data, and we discuss the utility of the methods for assessing variation in susceptibility and the diseased cellular state. PMID:29163636

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

New Toxico-Cheminformatics & Computational Toxicology ...

EPA Pesticide Factsheets

EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining, and data read-across. The DSSTox Structure-Browser provides structure searchability across all published DSSTox toxicity-related inventory, and is enabling linkages between previously isolated toxicity data resources. As of early March 2008, the public DSSTox inventory has been integrated into PubChem, allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. The most recent DSSTox version of the Carcinogenic Potency Database file (CPDBAS) illustrates ways in which various summary definitions of carcinogenic activity can be employed in modeling and data mining. Phase I of the ToxCastTM project is generating high-throughput screening data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives, with rich toxicology profiles. Incorporating and expanding traditional SAR concepts into this new high-throughput and data-rich world pose conceptual and practical challenges, but also holds great promise for improving predictive capabilities.

Ultra-high frequency ultrasound biomicroscopy and high throughput cardiovascular phenotyping in a large scale mouse mutagenesis screen

NASA Astrophysics Data System (ADS)

Liu, Xiaoqin; Francis, Richard; Tobita, Kimimasa; Kim, Andy; Leatherbury, Linda; Lo, Cecilia W.

2013-02-01

Ultrasound biomicroscopy (UBM) is ideally suited for phenotyping fetal mice for congenital heart disease (CHD), as imaging can be carried out noninvasively to provide both hemodynamic and structural information essential for CHD diagnosis. Using the UBM (Vevo 2100; 40Hz) in conjunction with the clinical ultrasound system (Acuson Sequioa C512; 15Hz), we developed a two-step screening protocol to scan thousands fetuses derived from ENU mutagenized pedigrees. A wide spectrum of CHD was detected by the UBM, which were subsequently confirmed with follow-up necropsy and histopathology examination with episcopic fluorescence image capture. CHD observed included outflow anomalies, left/right heart obstructive lesions, septal/valvular defects and cardiac situs anomalies. Meanwhile, various extracardiac defects were found, such as polydactyly, craniofacial defects, exencephaly, omphalocele-cleft palate, most of which were associated with cardiac defects. Our analyses showed the UBM was better at assessing cardiac structure and blood flow profiles, while conventional ultrasound allowed higher throughput low-resolution screening. Our study showed the integration of conventional clinical ultrasound imaging with the UBM for fetal mouse cardiovascular phenotyping can maximize the detection and recovery of CHD mutants.

Introducing Bayesian thinking to high-throughput screening for false-negative rate estimation.

PubMed

Wei, Xin; Gao, Lin; Zhang, Xiaolei; Qian, Hong; Rowan, Karen; Mark, David; Peng, Zhengwei; Huang, Kuo-Sen

2013-10-01

High-throughput screening (HTS) has been widely used to identify active compounds (hits) that bind to biological targets. Because of cost concerns, the comprehensive screening of millions of compounds is typically conducted without replication. Real hits that fail to exhibit measurable activity in the primary screen due to random experimental errors will be lost as false-negatives. Conceivably, the projected false-negative rate is a parameter that reflects screening quality. Furthermore, it can be used to guide the selection of optimal numbers of compounds for hit confirmation. Therefore, a method that predicts false-negative rates from the primary screening data is extremely valuable. In this article, we describe the implementation of a pilot screen on a representative fraction (1%) of the screening library in order to obtain information about assay variability as well as a preliminary hit activity distribution profile. Using this training data set, we then developed an algorithm based on Bayesian logic and Monte Carlo simulation to estimate the number of true active compounds and potential missed hits from the full library screen. We have applied this strategy to five screening projects. The results demonstrate that this method produces useful predictions on the numbers of false negatives.

Adenylylation of small RNA sequencing adapters using the TS2126 RNA ligase I.

PubMed

Lama, Lodoe; Ryan, Kevin

2016-01-01

Many high-throughput small RNA next-generation sequencing protocols use 5' preadenylylated DNA oligonucleotide adapters during cDNA library preparation. Preadenylylation of the DNA adapter's 5' end frees from ATP-dependence the ligation of the adapter to RNA collections, thereby avoiding ATP-dependent side reactions. However, preadenylylation of the DNA adapters can be costly and difficult. The currently available method for chemical adenylylation of DNA adapters is inefficient and uses techniques not typically practiced in laboratories profiling cellular RNA expression. An alternative enzymatic method using a commercial RNA ligase was recently introduced, but this enzyme works best as a stoichiometric adenylylating reagent rather than a catalyst and can therefore prove costly when several variant adapters are needed or during scale-up or high-throughput adenylylation procedures. Here, we describe a simple, scalable, and highly efficient method for the 5' adenylylation of DNA oligonucleotides using the thermostable RNA ligase 1 from bacteriophage TS2126. Adapters with 3' blocking groups are adenylylated at >95% yield at catalytic enzyme-to-adapter ratios and need not be gel purified before ligation to RNA acceptors. Experimental conditions are also reported that enable DNA adapters with free 3' ends to be 5' adenylylated at >90% efficiency. © 2015 Lama and Ryan; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Use of the Zebrafish Larvae as a Model to Study Cigarette Smoke Condensate Toxicity

PubMed Central

Ellis, Lee D.; Soo, Evelyn C.; Achenbach, John C.; Morash, Michael G.; Soanes, Kelly H.

2014-01-01

The smoking of tobacco continues to be the leading cause of premature death worldwide and is linked to the development of a number of serious illnesses including heart disease, respiratory diseases, stroke and cancer. Currently, cell line based toxicity assays are typically used to gain information on the general toxicity of cigarettes and other tobacco products. However, they provide little information regarding the complex disease-related changes that have been linked to smoking. The ethical concerns and high cost associated with mammalian studies have limited their widespread use for in vivo toxicological studies of tobacco. The zebrafish has emerged as a low-cost, high-throughput, in vivo model in the study of toxicology. In this study, smoke condensates from 2 reference cigarettes and 6 Canadian brands of cigarettes with different design features were assessed for acute, developmental, cardiac, and behavioural toxicity (neurotoxicity) in zebrafish larvae. By making use of this multifaceted approach we have developed an in vivo model with which to compare the toxicity profiles of smoke condensates from cigarettes with different design features. This model system may provide insights into the development of smoking related disease and could provide a cost-effective, high-throughput platform for the future evaluation of tobacco products. PMID:25526262

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.

High-throughput literature mining to support read-across ...

EPA Pesticide Factsheets

Building scientific confidence in the development and evaluation of read-across remains an ongoing challenge. Approaches include establishing systematic frameworks to identify sources of uncertainty and ways to address them. One source of uncertainty is related to characterizing biological similarity. Many research efforts are underway such as structuring mechanistic data in adverse outcome pathways and investigating the utility of high throughput (HT)/high content (HC) screening data. A largely untapped resource for read-across to date is the biomedical literature. This information has the potential to support read-across by facilitating the identification of valid source analogues with similar biological and toxicological profiles as well as providing the mechanistic understanding for any prediction made. A key challenge in using biomedical literature is to convert and translate its unstructured form into a computable format that can be linked to chemical structure. We developed a novel text-mining strategy to represent literature information for read across. Keywords were used to organize literature into toxicity signatures at the chemical level. These signatures were integrated with HT in vitro data and curated chemical structures. A rule-based algorithm assessed the strength of the literature relationship, providing a mechanism to rank and visualize the signature as literature ToxPIs (LitToxPIs). LitToxPIs were developed for over 6,000 chemicals for a varie

Electron-beam lithography with character projection technique for high-throughput exposure with line-edge quality control

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Maruyama, Satoshi; Mita, Yoshio; Ikeda, Makoto; Asada, Kunihiro

2016-07-01

The high throughput of character projection (CP) electron-beam (EB) lithography makes it a promising technique for low-to-medium volume device fabrication with regularly arranged layouts, such as for standard-cell logics and memory arrays. However, non-VLSI applications such as MEMS and MOEMS may not be able to fully utilize the benefits of the CP method due to the wide variety of layout figures including curved and oblique edges. In addition, the stepwise shapes that appear because of the EB exposure process often result in intolerable edge roughness, which degrades device performances. In this study, we propose a general EB lithography methodology for such applications utilizing a combination of the CP and variable-shaped beam methods. In the process of layout data conversion with CP character instantiation, several control parameters were optimized to minimize the shot count, improve the edge quality, and enhance the overall device performance. We have demonstrated EB shot reduction and edge-quality improvement with our methodology by using a leading-edge EB exposure tool, ADVANTEST F7000S-VD02, and a high-resolution hydrogen silsesquioxane resist. Atomic force microscope observations were used to analyze the resist edge profiles' quality to determine the influence of the control parameters used in the data conversion process.

Use of the zebrafish larvae as a model to study cigarette smoke condensate toxicity.

PubMed

Ellis, Lee D; Soo, Evelyn C; Achenbach, John C; Morash, Michael G; Soanes, Kelly H

2014-01-01

The smoking of tobacco continues to be the leading cause of premature death worldwide and is linked to the development of a number of serious illnesses including heart disease, respiratory diseases, stroke and cancer. Currently, cell line based toxicity assays are typically used to gain information on the general toxicity of cigarettes and other tobacco products. However, they provide little information regarding the complex disease-related changes that have been linked to smoking. The ethical concerns and high cost associated with mammalian studies have limited their widespread use for in vivo toxicological studies of tobacco. The zebrafish has emerged as a low-cost, high-throughput, in vivo model in the study of toxicology. In this study, smoke condensates from 2 reference cigarettes and 6 Canadian brands of cigarettes with different design features were assessed for acute, developmental, cardiac, and behavioural toxicity (neurotoxicity) in zebrafish larvae. By making use of this multifaceted approach we have developed an in vivo model with which to compare the toxicity profiles of smoke condensates from cigarettes with different design features. This model system may provide insights into the development of smoking related disease and could provide a cost-effective, high-throughput platform for the future evaluation of tobacco products.

High-throughput optimization by statistical designs: example with rat liver slices cryopreservation.

PubMed

Martin, H; Bournique, B; Blanchi, B; Lerche-Langrand, C

2003-08-01

The purpose of this study was to optimize cryopreservation conditions of rat liver slices in a high-throughput format, with focus on reproducibility. A statistical design of 32 experiments was performed and intracellular lactate dehydrogenase (LDHi) activity and antipyrine (AP) metabolism were evaluated as biomarkers. At freezing, modified University of Wisconsin solution was better than Williams'E medium, and pure dimethyl sulfoxide was better than a cryoprotectant mixture. The best cryoprotectant concentrations were 10% for LDHi and 20% for AP metabolism. Fetal calf serum could be used at 50 or 80%, and incubation of slices with the cryoprotectant could last 10 or 20 min. At thawing, 42 degrees C was better than 22 degrees C. After thawing, 1h was better than 3h of preculture. Cryopreservation increased the interslice variability of the biomarkers. After cryopreservation, LDHi and AP metabolism levels were up to 84 and 80% of fresh values. However, these high levels were not reproducibly achieved. Two factors involved in the day-to-day variability of LDHi were identified: the incubation time with the cryoprotectant and the preculture time. In conclusion, the statistical design was very efficient to quickly determine optimized conditions by simultaneously measuring the role of numerous factors. The cryopreservation procedure developed appears suitable for qualitative metabolic profiling studies.

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

PubMed

Hutz, Janna E; Nelson, Thomas; Wu, Hua; McAllister, Gregory; Moutsatsos, Ioannis; Jaeger, Savina A; Bandyopadhyay, Somnath; Nigsch, Florian; Cornett, Ben; Jenkins, Jeremy L; Selinger, Douglas W

2013-04-01

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

Integrative prescreening in analysis of multiple cancer genomic studies

PubMed Central

2012-01-01

Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431

Enhancing high throughput toxicology - development of putative adverse outcome pathways linking US EPA ToxCast screening targets to relevant apical hazards.

EPA Science Inventory

High throughput toxicology programs, such as ToxCast and Tox21, have provided biological effects data for thousands of chemicals at multiple concentrations. Compared to traditional, whole-organism approaches, high throughput assays are rapid and cost-effective, yet they generall...

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 ...

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.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

PubMed

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available. Copyright © 2016 Du et al.

[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.

Recovering galaxy cluster gas density profiles with XMM-Newton and Chandra

NASA Astrophysics Data System (ADS)

Bartalucci, I.; Arnaud, M.; Pratt, G. W.; Vikhlinin, A.; Pointecouteau, E.; Forman, W. R.; Jones, C.; Mazzotta, P.; Andrade-Santos, F.

2017-12-01

We examined the reconstruction of galaxy cluster radial density profiles obtained from Chandra and XMM-Newton X-ray observations, using high quality data for a sample of twelve objects covering a range of morphologies and redshifts. By comparing the results obtained from the two observatories and by varying key aspects of the analysis procedure, we examined the impact of instrumental effects and of differences in the methodology used in the recovery of the density profiles. We find that the final density profile shape is particularly robust. We adapted the photon weighting vignetting correction method developed for XMM-Newton for use with Chandra data, and confirm that the resulting Chandra profiles are consistent with those corrected a posteriori for vignetting effects. Profiles obtained from direct deprojection and those derived using parametric models are consistent at the 1% level. At radii larger than 6″, the agreement between Chandra and XMM-Newton is better than 1%, confirming an excellent understanding of the XMM-Newton PSF. Furthermore, we find no significant energy dependence. The impact of the well-known offset between Chandra and XMM-Newton gas temperature determinations on the density profiles is found to be negligible. However, we find an overall normalisation offset in density profiles of the order of 2.5%, which is linked to absolute flux cross-calibration issues. As a final result, the weighted ratios of Chandra to XMM-Newton gas masses computed at R2500 and R500 are r = 1.03 ± 0.01 and r = 1.03 ± 0.03, respectively. Our study confirms that the radial density profiles are robustly recovered, and that any differences between Chandra and XMM-Newton can be constrained to the 2.5% level, regardless of the exact data analysis details. These encouraging results open the way for the true combination of X-ray observations of galaxy clusters, fully leveraging the high resolution of Chandra and the high throughput of XMM-Newton.

Integrated Microfluidic Lectin Barcode Platform for High-Performance Focused Glycomic Profiling

NASA Astrophysics Data System (ADS)

Shang, Yuqin; Zeng, Yun; Zeng, Yong

2016-02-01

Protein glycosylation is one of the key processes that play essential roles in biological functions and dysfunctions. However, progress in glycomics has considerably lagged behind genomics and proteomics, due in part to the enormous challenges in analysis of glycans. Here we present a new integrated and automated microfluidic lectin barcode platform to substantially improve the performance of lectin array for focused glycomic profiling. The chip design and flow control were optimized to promote the lectin-glycan binding kinetics and speed of lectin microarray. Moreover, we established an on-chip lectin assay which employs a very simple blocking method to effectively suppress the undesired background due to lectin binding of antibodies. Using this technology, we demonstrated focused differential profiling of tissue-specific glycosylation changes of a biomarker, CA125 protein purified from ovarian cancer cell line and different tissues from ovarian cancer patients in a fast, reproducible, and high-throughput fashion. Highly sensitive CA125 detection was also demonstrated with a detection limit much lower than the clinical cutoff value for cancer diagnosis. This microfluidic platform holds the potential to integrate with sample preparation functions to construct a fully integrated “sample-to-answer” microsystem for focused differential glycomic analysis. Thus, our technology should present a powerful tool in support of rapid advance in glycobiology and glyco-biomarker development.

Integrated Microfluidic Lectin Barcode Platform for High-Performance Focused Glycomic Profiling

PubMed Central

Shang, Yuqin; Zeng, Yun; Zeng, Yong

2016-01-01

Protein glycosylation is one of the key processes that play essential roles in biological functions and dysfunctions. However, progress in glycomics has considerably lagged behind genomics and proteomics, due in part to the enormous challenges in analysis of glycans. Here we present a new integrated and automated microfluidic lectin barcode platform to substantially improve the performance of lectin array for focused glycomic profiling. The chip design and flow control were optimized to promote the lectin-glycan binding kinetics and speed of lectin microarray. Moreover, we established an on-chip lectin assay which employs a very simple blocking method to effectively suppress the undesired background due to lectin binding of antibodies. Using this technology, we demonstrated focused differential profiling of tissue-specific glycosylation changes of a biomarker, CA125 protein purified from ovarian cancer cell line and different tissues from ovarian cancer patients in a fast, reproducible, and high-throughput fashion. Highly sensitive CA125 detection was also demonstrated with a detection limit much lower than the clinical cutoff value for cancer diagnosis. This microfluidic platform holds the potential to integrate with sample preparation functions to construct a fully integrated “sample-to-answer” microsystem for focused differential glycomic analysis. Thus, our technology should present a powerful tool in support of rapid advance in glycobiology and glyco-biomarker development. PMID:26831207

A high-throughput assay for the comprehensive profiling of DNA ligase fidelity

PubMed Central

Lohman, Gregory J. S.; Bauer, Robert J.; Nichols, Nicole M.; Mazzola, Laurie; Bybee, Joanna; Rivizzigno, Danielle; Cantin, Elizabeth; Evans, Thomas C.

2016-01-01

DNA ligases have broad application in molecular biology, from traditional cloning methods to modern synthetic biology and molecular diagnostics protocols. Ligation-based detection of polynucleotide sequences can be achieved by the ligation of probe oligonucleotides when annealed to a complementary target sequence. In order to achieve a high sensitivity and low background, the ligase must efficiently join correctly base-paired substrates, while discriminating against the ligation of substrates containing even one mismatched base pair. In the current study, we report the use of capillary electrophoresis to rapidly generate mismatch fidelity profiles that interrogate all 256 possible base-pair combinations at a ligation junction in a single experiment. Rapid screening of ligase fidelity in a 96-well plate format has allowed the study of ligase fidelity in unprecedented depth. As an example of this new method, herein we report the ligation fidelity of Thermus thermophilus DNA ligase at a range of temperatures, buffer pH and monovalent cation strength. This screen allows the selection of reaction conditions that maximize fidelity without sacrificing activity, while generating a profile of specific mismatches that ligate detectably under each set of conditions. PMID:26365241

A high-throughput assay for the comprehensive profiling of DNA ligase fidelity.

PubMed

Lohman, Gregory J S; Bauer, Robert J; Nichols, Nicole M; Mazzola, Laurie; Bybee, Joanna; Rivizzigno, Danielle; Cantin, Elizabeth; Evans, Thomas C

2016-01-29

DNA ligases have broad application in molecular biology, from traditional cloning methods to modern synthetic biology and molecular diagnostics protocols. Ligation-based detection of polynucleotide sequences can be achieved by the ligation of probe oligonucleotides when annealed to a complementary target sequence. In order to achieve a high sensitivity and low background, the ligase must efficiently join correctly base-paired substrates, while discriminating against the ligation of substrates containing even one mismatched base pair. In the current study, we report the use of capillary electrophoresis to rapidly generate mismatch fidelity profiles that interrogate all 256 possible base-pair combinations at a ligation junction in a single experiment. Rapid screening of ligase fidelity in a 96-well plate format has allowed the study of ligase fidelity in unprecedented depth. As an example of this new method, herein we report the ligation fidelity of Thermus thermophilus DNA ligase at a range of temperatures, buffer pH and monovalent cation strength. This screen allows the selection of reaction conditions that maximize fidelity without sacrificing activity, while generating a profile of specific mismatches that ligate detectably under each set of conditions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The NCI Genomic Data Commons as an engine for precision medicine.

PubMed

Jensen, Mark A; Ferretti, Vincent; Grossman, Robert L; Staudt, Louis M

2017-07-27

The National Cancer Institute Genomic Data Commons (GDC) is an information system for storing, analyzing, and sharing genomic and clinical data from patients with cancer. The recent high-throughput sequencing of cancer genomes and transcriptomes has produced a big data problem that precludes many cancer biologists and oncologists from gleaning knowledge from these data regarding the nature of malignant processes and the relationship between tumor genomic profiles and treatment response. The GDC aims to democratize access to cancer genomic data and to foster the sharing of these data to promote precision medicine approaches to the diagnosis and treatment of cancer.

Discovery and structure-activity relationships of piperidinone- and piperidine-constrained phenethylamines as novel, potent, and selective dipeptidyl peptidase IV inhibitors.

PubMed

Pei, Zhonghua; Li, Xiaofeng; von Geldern, Thomas W; Longenecker, Kenton; Pireh, Daisy; Stewart, Kent D; Backes, Bradley J; Lai, Chunqiu; Lubben, Thomas H; Ballaron, Stephen J; Beno, David W A; Kempf-Grote, Anita J; Sham, Hing L; Trevillyan, James M

2007-04-19

Dipeptidyl peptidase IV (DPP4) inhibitors are emerging as a new class of therapeutic agents for the treatment of type 2 diabetes. They exert their beneficial effects by increasing the levels of active glucagon-like peptide-1 and glucose-dependent insulinotropic peptide, which are two important incretins for glucose homeostasis. Starting from a high-throughput screening hit, we were able to identify a series of piperidinone- and piperidine-constrained phenethylamines as novel DPP4 inhibitors. Optimized compounds are potent, selective, and have good pharmacokinetic profiles.

Development of an Intracellular Screen for New Compounds Able To Inhibit Mycobacterium tuberculosis Growth in Human Macrophages.

PubMed

Sorrentino, Flavia; Gonzalez del Rio, Ruben; Zheng, Xingji; Presa Matilla, Jesus; Torres Gomez, Pedro; Martinez Hoyos, Maria; Perez Herran, Maria Esther; Mendoza Losana, Alfonso; Av-Gay, Yossef

2016-01-01

Here we describe the development and validation of an intracellular high-throughput screening assay for finding new antituberculosis compounds active in human macrophages. The assay consists of a luciferase-based primary identification assay, followed by a green fluorescent protein-based secondary profiling assay. Standard tuberculosis drugs and 158 previously recognized active antimycobacterial compounds were used to evaluate assay robustness. Data show that the assay developed is a short and valuable tool for the discovery of new antimycobacterial compounds. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Omics Profiling in Precision Oncology*

PubMed Central

Yu, Kun-Hsing; Snyder, Michael

2016-01-01

Cancer causes significant morbidity and mortality worldwide, and is the area most targeted in precision medicine. Recent development of high-throughput methods enables detailed omics analysis of the molecular mechanisms underpinning tumor biology. These studies have identified clinically actionable mutations, gene and protein expression patterns associated with prognosis, and provided further insights into the molecular mechanisms indicative of cancer biology and new therapeutics strategies such as immunotherapy. In this review, we summarize the techniques used for tumor omics analysis, recapitulate the key findings in cancer omics studies, and point to areas requiring further research on precision oncology. PMID:27099341

Mass Conservation and Inference of Metabolic Networks from High-Throughput Mass Spectrometry Data

PubMed Central

Bandaru, Pradeep; Bansal, Mukesh

2011-01-01

Abstract We present a step towards the metabolome-wide computational inference of cellular metabolic reaction networks from metabolic profiling data, such as mass spectrometry. The reconstruction is based on identification of irreducible statistical interactions among the metabolite activities using the ARACNE reverse-engineering algorithm and on constraining possible metabolic transformations to satisfy the conservation of mass. The resulting algorithms are validated on synthetic data from an abridged computational model of Escherichia coli metabolism. Precision rates upwards of 50% are routinely observed for identification of full metabolic reactions, and recalls upwards of 20% are also seen. PMID:21314454

Precision medicine in the age of big data: The present and future role of large-scale unbiased sequencing in drug discovery and development.

PubMed

Vicini, P; Fields, O; Lai, E; Litwack, E D; Martin, A-M; Morgan, T M; Pacanowski, M A; Papaluca, M; Perez, O D; Ringel, M S; Robson, M; Sakul, H; Vockley, J; Zaks, T; Dolsten, M; Søgaard, M

2016-02-01

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice. © 2015 American Society for Clinical Pharmacology and Therapeutics.

Profiling of drought-responsive microRNA and mRNA in tomato using high-throughput sequencing.

PubMed

Liu, Minmin; Yu, Huiyang; Zhao, Gangjun; Huang, Qiufeng; Lu, Yongen; Ouyang, Bo

2017-06-26

Abiotic stresses cause severe loss of crop production. Among them, drought is one of the most frequent environmental stresses, which limits crop growth, development and productivity. Plant drought tolerance is fine-tuned by a complex gene regulatory network. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success to improve plant yield and quality. Recent studies have demonstrated that microRNAs play critical roles in plant drought tolerance. However, little is known about the microRNA in drought response of the model plant tomato. Here, we described the profiling of drought-responsive microRNA and mRNA in tomato using high-throughput next-generation sequencing. Drought stress was applied on the seedlings of M82, a drought-sensitive cultivated tomato genotype, and IL9-1, a drought-tolerant introgression line derived from the stress-resistant wild species Solanum pennellii LA0716 and M82. Under drought, IL9-1 performed superior than M82 regarding survival rate, H 2 O 2 elimination and leaf turgor maintenance. A total of four small RNA and eight mRNA libraries were constructed and sequenced using Illumina sequencing technology. 105 conserved and 179 novel microRNAs were identified, among them, 54 and 98 were differentially expressed upon drought stress, respectively. The majority of the differentially-expressed conserved microRNAs was up-regulated in IL9-1 whereas down-regulated in M82. Under drought stress, 2714 and 1161 genes were found to be differentially expressed in M82 and IL9-1, respectively, and many of their homologues are involved in plant stress, such as genes encoding transcription factor and protein kinase. Various pathways involved in abiotic stress were revealed by Gene Ontology and pathway analysis. The mRNA sequencing results indicated that most of the target genes were regulated by their corresponding microRNAs, which suggested that microRNAs may play essential roles in the drought tolerance of tomato. In this study, numerous microRNAs and mRNAs involved in the drought response of tomato were identified using high-throughput sequencing, which will provide new insights into the complex regulatory network of plant adaption to drought stress. This work will also help to exploit new players functioning in plant drought-stress tolerance.

Identification of candidate miRNAs and expression profile of yak oocytes before and after in vitro maturation by high-throughput sequencing.

PubMed

Xiong, X R; Lan, D L; Li, J; Zi, X D; Li, M Y

2016-12-01

Small RNA represents several unique non-coding RNA classes that have important function in a wide range of biological processes including development of germ cells and early embryonic, cell differentiation, cell proliferation and apoptosis in diverse organisms. However, little is known about their expression profiles and effects in yak oocytes maturation and early development. To investigate the function of small RNAs in the maturation process of yak oocyte and early development, two small RNA libraries of oocytes were constructed from germinal vesicle stage (GV) and maturation in vitro to metaphase II-arrested stage (M II) and then sequenced using small RNA high-throughput sequencing technology. A total of 9,742,592 and 12,168,523 clean reads were obtained from GV and M II oocytes, respectively. In total, 801 and 1,018 known miRNAs were acquired from GV and M II oocytes, and 75 miRNAs were found to be significantly differentially expressed: 47 miRNAs were upregulated and 28 miRNAs were downregulated in the M II oocytes compared to the GV stage. Among the upregulated miRNAs, miR-342 has the largest fold change (9.25-fold). Six highly expressed miRNAs (let-7i, miR-10b, miR-10c, miR-143, miR-146b and miR-148) were validated by real-time quantitative PCR (RT-qPCR) and consistent with the sequencing results. Furthermore, the expression patterns of two miRNAs and their potential targets were analysed in different developmental stages of oocytes and early embryos. This study provides the first miRNA profile in the mature process of yak oocyte. Seventy-five miRNAs are expressed differentially in GV and M II oocytes as well as among different development stages of early embryos, suggesting miRNAs involved in regulating oocyte maturation and early development of yak. These results showed specific miRNAs in yak oocytes had dynamic changes during meiosis. Further functional and mechanistic studies on the miRNAs during meiosis may beneficial to understanding the role of miRNAs on meiotic division. © 2016 Blackwell Verlag GmbH.

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.

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.

(Poly)phenolic fingerprint and chemometric analysis of white (Morus alba L.) and black (Morus nigra L.) mulberry leaves by using a non-targeted UHPLC-MS approach.

PubMed

Sánchez-Salcedo, Eva M; Tassotti, Michele; Del Rio, Daniele; Hernández, Francisca; Martínez, Juan José; Mena, Pedro

2016-12-01

This study reports the (poly)phenolic fingerprinting and chemometric discrimination of leaves of eight mulberry clones from Morus alba and Morus nigra cultivated in Spain. UHPLC-MS(n) (Ultra High Performance Liquid Chromatography-Mass Spectrometry) high-throughput analysis allowed the tentative identification of a total of 31 compounds. The phenolic profile of mulberry leaf was characterized by the presence of a high number of flavonol derivatives, mainly glycosylated forms of quercetin and kaempferol. Caffeoylquinic acids, simple phenolic acids, and some organic acids were also detected. Seven compounds were identified for the first time in mulberry leaves. The chemometric analysis (cluster analysis and principal component analysis) of the chromatographic data allowed the characterization of the different mulberry clones and served to explain the great intraspecific variability in mulberry secondary metabolism. This screening of the complete phenolic profile of mulberry leaves can assist the increasing interest for purposes related to quality control, germplasm screening, and bioactivity evaluation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

PubMed

Kebschull, Moritz; Papapanou, Panos N

2017-01-01

Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional patterns, beyond the mere identification of lists of features that differ between groups.Here, we demonstrate the utility of (1) supervised classification algorithms in class validation, and (2) unsupervised clustering in class discovery. We use data from our previous work that described the transcriptional profiles of gingival tissue samples obtained from subjects suffering from chronic or aggressive periodontitis (1) to test whether the two diagnostic entities were also characterized by differences on the molecular level, and (2) to search for a novel, alternative classification of periodontitis based on the tissue transcriptomes.Using machine learning technology, we provide evidence for diagnostic imprecision in the currently accepted classification of periodontitis, and demonstrate that a novel, alternative classification based on differences in gingival tissue transcriptomes is feasible. The outlined procedures allow for the unbiased interrogation of high-dimensional datasets for characteristic underlying classes, and are applicable to a broad range of -omics data.

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

Development of a phenotyping platform for high throughput screening of nodal root angle in sorghum.

PubMed

Joshi, Dinesh C; Singh, Vijaya; Hunt, Colleen; Mace, Emma; van Oosterom, Erik; Sulman, Richard; Jordan, David; Hammer, Graeme

2017-01-01

In sorghum, the growth angle of nodal roots is a major component of root system architecture. It strongly influences the spatial distribution of roots of mature plants in the soil profile, which can impact drought adaptation. However, selection for nodal root angle in sorghum breeding programs has been restricted by the absence of a suitable high throughput phenotyping platform. The aim of this study was to develop a phenotyping platform for the rapid, non-destructive and digital measurement of nodal root angle of sorghum at the seedling stage. The phenotyping platform comprises of 500 soil filled root chambers (50 × 45 × 0.3 cm in size), made of transparent perspex sheets that were placed in metal tubs and covered with polycarbonate sheets. Around 3 weeks after sowing, once the first flush of nodal roots was visible, roots were imaged in situ using an imaging box that included two digital cameras that were remotely controlled by two android tablets. Free software ( openGelPhoto.tcl ) allowed precise measurement of nodal root angle from the digital images. The reliability and efficiency of the platform was evaluated by screening a large nested association mapping population of sorghum and a set of hybrids in six independent experimental runs that included up to 500 plants each. The platform revealed extensive genetic variation and high heritability (repeatability) for nodal root angle. High genetic correlations and consistent ranking of genotypes across experimental runs confirmed the reproducibility of the platform. This low cost, high throughput root phenotyping platform requires no sophisticated equipment, is adaptable to most glasshouse environments and is well suited to dissect the genetic control of nodal root angle of sorghum. The platform is suitable for use in sorghum breeding programs aiming to improve drought adaptation through root system architecture manipulation.

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.

High-throughput sequencing of small RNAs and analysis of differentially expressed microRNAs associated with pistil development in Japanese apricot

PubMed Central

2012-01-01

Background MicroRNAs (miRNAs) are a class of endogenous, small, non-coding RNAs that regulate gene expression by mediating gene silencing at transcriptional and post-transcriptional levels in high plants. However, the diversity of miRNAs and their roles in floral development in Japanese apricot (Prunus mume Sieb. et Zucc) remains largely unexplored. Imperfect flowers with pistil abortion seriously decrease production yields. To understand the role of miRNAs in pistil development, pistil development-related miRNAs were identified by Solexa sequencing in Japanese apricot. Results Solexa sequencing was used to identify and quantitatively profile small RNAs from perfect and imperfect flower buds of Japanese apricot. A total of 22,561,972 and 24,952,690 reads were sequenced from two small RNA libraries constructed from perfect and imperfect flower buds, respectively. Sixty-one known miRNAs, belonging to 24 families, were identified. Comparative profiling revealed that seven known miRNAs exhibited significant differential expression between perfect and imperfect flower buds. A total of 61 potentially novel miRNAs/new members of known miRNA families were also identified by the presence of mature miRNAs and corresponding miRNA*s in the sRNA libraries. Comparative analysis showed that six potentially novel miRNAs were differentially expressed between perfect and imperfect flower buds. Target predictions of the 13 differentially expressed miRNAs resulted in 212 target genes. Gene ontology (GO) annotation revealed that high-ranking miRNA target genes are those implicated in the developmental process, the regulation of transcription and response to stress. Conclusions This study represents the first comparative identification of miRNAomes between perfect and imperfect Japanese apricot flowers. Seven known miRNAs and six potentially novel miRNAs associated with pistil development were identified, using high-throughput sequencing of small RNAs. The findings, both computationally and experimentally, provide valuable information for further functional characterisation of miRNAs associated with pistil development in plants. PMID:22863067

40 CFR Table 9 to Subpart Eeee of... - Continuous Compliance With Operating Limits-High Throughput Transfer Racks

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 12 2010-07-01 2010-07-01 true Continuous Compliance With Operating Limits-High Throughput Transfer Racks 9 Table 9 to Subpart EEEE of Part 63 Protection of Environment...—Continuous Compliance With Operating Limits—High Throughput Transfer Racks As stated in §§ 63.2378(a) and (b...

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.

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

PubMed

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

2017-01-01

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

Analysis of the Effects of Five Factors Relevant to In Vitro Chondrogenesis of Human Mesenchymal Stem Cells Using Factorial Design and High Throughput mRNA-Profiling

PubMed Central

Jakobsen, Rune B.; Østrup, Esben; Zhang, Xiaolan; Mikkelsen, Tarjei S.; Brinchmann, Jan E.

2014-01-01

The in vitro process of chondrogenic differentiation of mesenchymal stem cells for tissue engineering has been shown to require three-dimensional culture along with the addition of differentiation factors to the culture medium. In general, this leads to a phenotype lacking some of the cardinal features of native articular chondrocytes and their extracellular matrix. The factors used vary, but regularly include members of the transforming growth factor β superfamily and dexamethasone, sometimes in conjunction with fibroblast growth factor 2 and insulin-like growth factor 1, however the use of soluble factors to induce chondrogenesis has largely been studied on a single factor basis. In the present study we combined a factorial quality-by-design experiment with high-throughput mRNA profiling of a customized chondrogenesis related gene set as a tool to study in vitro chondrogenesis of human bone marrow derived mesenchymal stem cells in alginate. 48 different conditions of transforming growth factor β 1, 2 and 3, bone morphogenetic protein 2, 4 and 6, dexamethasone, insulin-like growth factor 1, fibroblast growth factor 2 and cell seeding density were included in the experiment. The analysis revealed that the best of the tested differentiation cocktails included transforming growth factor β 1 and dexamethasone. Dexamethasone acted in synergy with transforming growth factor β 1 by increasing many chondrogenic markers while directly downregulating expression of the pro-osteogenic gene osteocalcin. However, all factors beneficial to the expression of desirable hyaline cartilage markers also induced undesirable molecules, indicating that perfect chondrogenic differentiation is not achievable with the current differentiation protocols. PMID:24816923

A high-throughput quantitative expression analysis of cancer-related genes in human HepG2 cells in response to limonene, a potential anticancer agent.

PubMed

Hafidh, Rand R; Hussein, Saba Z; MalAllah, Mohammed Q; Abdulamir, Ahmed S; Abu Bakar, Fatimah

2017-11-14

Citrus bioactive compounds, as active anticancer agent, have been under focus by several studies worldwide. However, the underlying genes responsible for the anticancer potential have not been sufficiently highlighted. The current study investigated the gene expression profile of hepatocellular carcinoma, HepG2, cells after treatment with Limonene. The concentration that killed 50% of HepG2 cells was used to elucidate the genetic mechanisms of limonene anticancer activity. The apoptotic induction was detected by flow cytometry and confocal fluorescence microscope. Two of pro-apoptotic events, caspase-3 activation and phosphatidylserine translocation were manifested by confocal fluorescence microscopy. High-throughput real-time PCR was used to profile 1023 cancer-related genes in 16 different gene families related to the cancer development. In comparison to untreated cells, limonene increased the percentage of apoptotic cells up to 89.61%, by flow cytometry, and 48.2% by fluorescence microscopy. There was a significant limonene-driven differential gene expression of HepG2 cells in 15 different gene families. Limonene was shown to significantly (>2log) up-regulate and down-regulate 14 and 59 genes, respectively. The affected gene families, from most to least affected, were apoptosis induction, signal transduction, cancer genes augmentation, alteration in kinases expression, inflammation, DNA damage repair, and cell cycle proteins. The current study reveals that limonene could be a promising, cheap, and effective anticancer compound. The broad spectrum of limonene anticancer activity is interesting for anticancer drug development. Further research is needed to confirm the current findings and to examine the anticancer potential of limonene along with underlying mechanisms on different cell lines. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Streamlining plant sample preparation: the use of high-throughput robotics to process echinacea samples for biomarker profiling by MALDI-TOF mass spectrometry.

PubMed

Greene, Leasa A; Isaac, Issa; Gray, Dean E; Schwartz, Sarah A

2007-09-01

Several species in the genus Echinacea are beneficial herbs popularly used for many ailments. The most popular Echinacea species for cultivation, wild collection, and herbal products include E. purpurea (L.) Moench, E. pallida (Nutt.) Nutt., and E. angustifolia (DC). Product adulteration is a key concern for the natural products industry, where botanical misidentification and introduction of other botanical and nonbotanical contaminants exist throughout the formulation and production process. Therefore, rapid and cost-effective methods that can be used to monitor these materials for complex product purity and consistency are of benefit to consumers and producers. The objective of this continuing research was to develop automated, high-throughput processing methods that, teamed with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, differentiate Echinacea species by their mass profiles. Small molecules, peptide, and proteins from aerial parts (leaf/stem/flowers), seeds, and roots from E. purpurea and E. angustifolia; seeds and roots from E. pallida; and off-the-shelf Echinacea supplements were extracted and analyzed by MS using methods developed on the ProPrep liquid handling system (Genomic Solutions). Analysis of these samples highlighted key MS signal patterns from both small molecules and proteins that characterized the individual Echinacea materials analyzed. Based on analysis of pure Echinacea samples, off-the-shelf products containing Echinacea could then be evaluated in a streamlined process. Corresponding analysis of dietary supplements was used to monitor for product composition, including Echinacea species and plant materials used. These results highlight the potential for streamlined, automated approaches for agricultural species differentiation and botanical product evaluation.

Internal validation of the GlobalFiler™ Express PCR Amplification Kit for the direct amplification of reference DNA samples on a high-throughput automated workflow.

PubMed

Flores, Shahida; Sun, Jie; King, Jonathan; Budowle, Bruce

2014-05-01

The GlobalFiler™ Express PCR Amplification Kit uses 6-dye fluorescent chemistry to enable multiplexing of 21 autosomal STRs, 1 Y-STR, 1 Y-indel and the sex-determining marker amelogenin. The kit is specifically designed for processing reference DNA samples in a high throughput manner. Validation studies were conducted to assess the performance and define the limitations of this direct amplification kit for typing blood and buccal reference DNA samples on various punchable collection media. Studies included thermal cycling sensitivity, reproducibility, precision, sensitivity of detection, minimum detection threshold, system contamination, stochastic threshold and concordance. Results showed that optimal amplification and injection parameters for a 1.2mm punch from blood and buccal samples were 27 and 28 cycles, respectively, combined with a 12s injection on an ABI 3500xL Genetic Analyzer. Minimum detection thresholds were set at 100 and 120RFUs for 27 and 28 cycles, respectively, and it was suggested that data from positive amplification controls provided a better threshold representation. Stochastic thresholds were set at 250 and 400RFUs for 27 and 28 cycles, respectively, as stochastic effects increased with cycle number. The minimum amount of input DNA resulting in a full profile was 0.5ng, however, the optimum range determined was 2.5-10ng. Profile quality from the GlobalFiler™ Express Kit and the previously validated AmpFlSTR(®) Identifiler(®) Direct Kit was comparable. The validation data support that reliable DNA typing results from reference DNA samples can be obtained using the GlobalFiler™ Express PCR Amplification Kit. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Circulating and synovial antibody profiling of juvenile arthritis patients by nucleic acid programmable protein arrays

PubMed Central

2012-01-01

Introduction Juvenile idiopathic arthritis (JIA) is a heterogeneous disease characterized by chronic joint inflammation of unknown cause in children. JIA is an autoimmune disease and small numbers of autoantibodies have been reported in JIA patients. The identification of antibody markers could improve the existing clinical management of patients. Methods A pilot study was performed on the application of a high-throughput platform, the nucleic acid programmable protein array (NAPPA), to assess the levels of antibodies present in the systemic circulation and synovial joint of a small cohort of juvenile arthritis patients. Plasma and synovial fluid from 10 JIA patients was screened for antibodies against 768 proteins on NAPPAs. Results Quantitative reproducibility of NAPPAs was demonstrated with > 0.95 intra-array and inter-array correlations. A strong correlation was also observed for the levels of antibodies between plasma and synovial fluid across the study cohort (r = 0.96). Differences in the levels of 18 antibodies were revealed between sample types across all patients. Patients were segregated into two clinical subtypes with distinct antibody signatures by unsupervised hierarchical cluster analysis. Conclusion The NAPPAs provide a high-throughput quantitatively reproducible platform to screen for disease-specific autoantibodies at the proteome level on a microscope slide. The strong correlation between the circulating antibody levels and those of the inflamed joint represents a novel finding and provides confidence to use plasma for discovery of autoantibodies in JIA, thus circumventing the challenges associated with joint aspiration. We expect that autoantibody profiling of JIA patients on NAPPAs could yield antibody markers that can act as criteria to stratify patients, predict outcomes and understand disease etiology at the molecular level. PMID:22510425

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

PubMed

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

2016-09-06

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

High-Throughput Sequencing Reveals Differential Expression of miRNAs in Intestine from Sea Cucumber during Aestivation

PubMed Central

Chen, Muyan; Zhang, Xiumei; Liu, Jianning; Storey, Kenneth B.

2013-01-01

The regulatory role of miRNA in gene expression is an emerging hot new topic in the control of hypometabolism. Sea cucumber aestivation is a complicated physiological process that includes obvious hypometabolism as evidenced by a decrease in the rates of oxygen consumption and ammonia nitrogen excretion, as well as a serious degeneration of the intestine into a very tiny filament. To determine whether miRNAs play regulatory roles in this process, the present study analyzed profiles of miRNA expression in the intestine of the sea cucumber (Apostichopus japonicus), using Solexa deep sequencing technology. We identified 308 sea cucumber miRNAs, including 18 novel miRNAs specific to sea cucumber. Animals sampled during deep aestivation (DA) after at least 15 days of continuous torpor, were compared with animals from a non-aestivation (NA) state (animals that had passed through aestivation and returned to the active state). We identified 42 differentially expressed miRNAs [RPM (reads per million) >10, |FC| (|fold change|) ≥1, FDR (false discovery rate) <0.01] during aestivation, which were validated by two other miRNA profiling methods: miRNA microarray and real-time PCR. Among the most prominent miRNA species, miR-200-3p, miR-2004, miR-2010, miR-22, miR-252a, miR-252a-3p and miR-92 were significantly over-expressed during deep aestivation compared with non-aestivation animals. Preliminary analyses of their putative target genes and GO analysis suggest that these miRNAs could play important roles in global transcriptional depression and cell differentiation during aestivation. High-throughput sequencing data and microarray data have been submitted to GEO database. PMID:24143179

Simultaneous Measurements of Auto-Immune and Infectious Disease Specific Antibodies Using a High Throughput Multiplexing Tool

PubMed Central

Asati, Atul; Kachurina, Olga; Kachurin, Anatoly

2012-01-01

Considering importance of ganglioside antibodies as biomarkers in various immune-mediated neuropathies and neurological disorders, we developed a high throughput multiplexing tool for the assessment of gangliosides-specific antibodies based on Biolpex/Luminex platform. In this report, we demonstrate that the ganglioside high throughput multiplexing tool is robust, highly specific and demonstrating ∼100-fold higher concentration sensitivity for IgG detection than ELISA. In addition to the ganglioside-coated array, the high throughput multiplexing tool contains beads coated with influenza hemagglutinins derived from H1N1 A/Brisbane/59/07 and H1N1 A/California/07/09 strains. Influenza beads provided an added advantage of simultaneous detection of ganglioside- and influenza-specific antibodies, a capacity important for the assay of both infectious antigen-specific and autoimmune antibodies following vaccination or disease. Taken together, these results support the potential adoption of the ganglioside high throughput multiplexing tool for measuring ganglioside antibodies in various neuropathic and neurological disorders. PMID:22952605

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

HT-COMET: a novel automated approach for high throughput assessment of human sperm chromatin quality

PubMed Central

Albert, Océane; Reintsch, Wolfgang E.; Chan, Peter; Robaire, Bernard

2016-01-01

STUDY QUESTION Can we make the comet assay (single-cell gel electrophoresis) for human sperm a more accurate and informative high throughput assay? SUMMARY ANSWER We developed a standardized automated high throughput comet (HT-COMET) assay for human sperm that improves its accuracy and efficiency, and could be of prognostic value to patients in the fertility clinic. WHAT IS KNOWN ALREADY The comet assay involves the collection of data on sperm DNA damage at the level of the single cell, allowing the use of samples from severe oligozoospermic patients. However, this makes comet scoring a low throughput procedure that renders large cohort analyses tedious. Furthermore, the comet assay comes with an inherent vulnerability to variability. Our objective is to develop an automated high throughput comet assay for human sperm that will increase both its accuracy and efficiency. STUDY DESIGN, SIZE, DURATION The study comprised two distinct components: a HT-COMET technical optimization section based on control versus DNAse treatment analyses (n = 3–5), and a cross-sectional study on 123 men presenting to a reproductive center with sperm concentrations categorized as severe oligozoospermia, oligozoospermia or normozoospermia. PARTICIPANTS/MATERIALS, SETTING, METHODS Sperm chromatin quality was measured using the comet assay: on classic 2-well slides for software comparison; on 96-well slides for HT-COMET optimization; after exposure to various concentrations of a damage-inducing agent, DNAse, using HT-COMET; on 123 subjects with different sperm concentrations using HT-COMET. Data from the 123 subjects were correlated to classic semen quality parameters and plotted as single-cell data in individual DNA damage profiles. MAIN RESULTS AND THE ROLE OF CHANCE We have developed a standard automated HT-COMET procedure for human sperm. It includes automated scoring of comets by a fully integrated high content screening setup that compares well with the most commonly used semi-manual analysis software. Using this method, a cross-sectional study on 123 men showed no significant correlation between sperm concentration and sperm DNA damage, confirming the existence of hidden chromatin damage in men with apparently normal semen characteristics, and a significant correlation between percentage DNA in the tail and percentage of progressively motile spermatozoa. Finally, the use of DNA damage profiles helped to distinguish subjects between and within sperm concentration categories, and allowed a determination of the proportion of highly damaged cells. LIMITATIONS, REASONS FOR CAUTION The main limitations of the HT-COMET are the high, yet indispensable, investment in an automated liquid handling system and heating block to ensure accuracy, and the availability of an automated plate reading microscope and analysis software. WIDER IMPLICATIONS OF THE FINDINGS This standardized HT-COMET assay offers many advantages, including higher accuracy and evenness due to automation of sensitive steps, a 14.4-fold increase in sample analysis capacity, and an imaging and scoring time of 1 min/well. Overall, HT-COMET offers a decrease in total experimental time of more than 90%. Hence, this assay constitutes a more efficient option to assess sperm chromatin quality, paves the way to using this assay to screen large cohorts, and holds prognostic value for infertile patients. STUDY FUNDING/COMPETING INTEREST(S) Funded by the CIHR Institute of Human Development, Child and Youth Health (IHDCYH; RHF 100625). O.A. is a fellow supported by the Fonds de la Recherche du Québec - Santé (FRQS) and the CIHR Training Program in Reproduction, Early Development, and the Impact on Health (REDIH). B.R. is a James McGill Professor. The authors declare no conflicts of interest. PMID:26975326

Internal Structure and Morphology Profile in Optimizing Filter Membrane Performance

NASA Astrophysics Data System (ADS)

Sanaei, Pejman; Cummings, Linda J.

Membrane filters are in widespread use, and manufacturers have considerable interest in improving their performance, in terms of particle retention properties, and total throughput over the filter lifetime. A good question to ask is therefore: what is the optimal configuration of filter membranes, in terms of internal morphology (pore size and shape), to achieve the most efficient filtration? To answer this question, we must first propose a robust measure of filtration performance. As filtration occurs the membrane becomes blocked, or fouled, by the impurities in the feed solution, and any performance measure must take account of this. For example, one performance measure might be the total throughput (the volume of filtered feed solution) at the end of the filtration process, when the membrane is so badly blocked that it is deemed no longer functional. Here we present a simplified mathematical model, which (i) characterizes membrane internal pore structure via pore or permeability profiles in the depth of the membrane; (ii) accounts for various membrane fouling mechanisms (adsorption, blocking and cake formation); and (iv) predicts the optimum pore profile for our chosen performance measure. NSF DMS-1261596 and NSF DMS-1615719.

Direct Growth of Bacteria in Headspace Vials Allows for Screening of Volatiles by Gas Chromatography Mass Spectrometry.

PubMed

Timm, Collin M; Lloyd, Evan P; Egan, Amanda; Mariner, Ray; Karig, David

2018-01-01

Bacterially produced volatile organic compounds (VOCs) can modify growth patterns of eukaryotic hosts and competing/cohabiting microbes. These compounds have been implicated in skin disorders and attraction of biting pests. Current methods to detect and characterize VOCs from microbial cultures can be laborious and low-throughput, making it difficult to understand the behavior of microbial populations. In this work we present an efficient method employing gas chromatography/mass spectrometry with autosampling to characterize VOC profiles from solid-phase bacterial cultures. We compare this method to complementary plate-based assays and measure the effects of growth media and incubation temperature on the VOC profiles from a well-studied Pseudomonas aeruginosa PAO1 system. We observe that P. aeruginosa produces longer chain VOCs, such as 2-undecanone and 2-undecanol in higher amounts at 37°C than 30°C. We demonstrate the throughput of this method by studying VOC profiles from a representative collection of skin bacterial isolates under three parallel growth conditions. We observe differential production of various aldehydes and ketones depending on bacterial strain. This generalizable method will support screening of bacterial populations in a variety of research areas.

Direct Growth of Bacteria in Headspace Vials Allows for Screening of Volatiles by Gas Chromatography Mass Spectrometry

PubMed Central

Timm, Collin M.; Lloyd, Evan P.; Egan, Amanda; Mariner, Ray; Karig, David

2018-01-01

Bacterially produced volatile organic compounds (VOCs) can modify growth patterns of eukaryotic hosts and competing/cohabiting microbes. These compounds have been implicated in skin disorders and attraction of biting pests. Current methods to detect and characterize VOCs from microbial cultures can be laborious and low-throughput, making it difficult to understand the behavior of microbial populations. In this work we present an efficient method employing gas chromatography/mass spectrometry with autosampling to characterize VOC profiles from solid-phase bacterial cultures. We compare this method to complementary plate-based assays and measure the effects of growth media and incubation temperature on the VOC profiles from a well-studied Pseudomonas aeruginosa PAO1 system. We observe that P. aeruginosa produces longer chain VOCs, such as 2-undecanone and 2-undecanol in higher amounts at 37°C than 30°C. We demonstrate the throughput of this method by studying VOC profiles from a representative collection of skin bacterial isolates under three parallel growth conditions. We observe differential production of various aldehydes and ketones depending on bacterial strain. This generalizable method will support screening of bacterial populations in a variety of research areas. PMID:29662472

LC-MS/MS profiling-based secondary metabolite screening of Myxococcus xanthus.

PubMed

Kim, Jiyoung; Choi, Jung Nam; Kim, Pil; Sok, Dai-Eun; Nam, Soo-Wan; Lee, Choong Hwan

2009-01-01

Myxobacteria, Gram-negative soil bacteria, are a well-known producer of bioactive secondary metabolites. Therefore, this study presents a methodological approach for the high-throughput screening of secondary metabolites from 4 wild-type Myxococcus xanthus strains. First, electrospray ionization mass spectrometry (ESI-MS) was performed using extracellular crude extracts. As a result, 22 metabolite peaks were detected, and the metabolite profiling was then conducted using the m/z value, retention time, and MS/MS fragmentation pattern analyses. Among the peaks, one unknown compound peak was identified as analogous to the myxalamid A, B, and C series. An analysis of the tandem mass spectrometric fragmentation patterns and HR-MS identified myxalamid K as a new compound derived from M. xanthus. In conclusion, LC-MS/MS-based chemical screening of diverse secondary metabolites would appear to be an effective approach for discovering unknown microbial secondary metabolites.

Absolute quantification of microbial taxon abundances.

PubMed

Props, Ruben; Kerckhof, Frederiek-Maarten; Rubbens, Peter; De Vrieze, Jo; Hernandez Sanabria, Emma; Waegeman, Willem; Monsieurs, Pieter; Hammes, Frederik; Boon, Nico

2017-02-01

High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.

Protein Interaction Profile Sequencing (PIP-seq).

PubMed

Foley, Shawn W; Gregory, Brian D

2016-10-10

Every eukaryotic RNA transcript undergoes extensive post-transcriptional processing from the moment of transcription up through degradation. This regulation is performed by a distinct cohort of RNA-binding proteins which recognize their target transcript by both its primary sequence and secondary structure. Here, we describe protein interaction profile sequencing (PIP-seq), a technique that uses ribonuclease-based footprinting followed by high-throughput sequencing to globally assess both protein-bound RNA sequences and RNA secondary structure. PIP-seq utilizes single- and double-stranded RNA-specific nucleases in the absence of proteins to infer RNA secondary structure. These libraries are also compared to samples that undergo nuclease digestion in the presence of proteins in order to find enriched protein-bound sequences. Combined, these four libraries provide a comprehensive, transcriptome-wide view of RNA secondary structure and RNA protein interaction sites from a single experimental technique. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Data Reduction Approaches for Dissecting Transcriptional Effects on Metabolism

PubMed Central

Schwahn, Kevin; Nikoloski, Zoran

2018-01-01

The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coli, Saccharomycies cerevisiae, and Arabidopsis thaliana. PMID:29731765

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

PubMed Central

Fan, Limin; Song, Chao; Meng, Shunlong; Qiu, Liping; Zheng, Yao; Wu, Wei; Qu, Jianhong; Li, Dandan; Zhang, Cong; Hu, Gengdong; Chen, Jiazhang

2016-01-01

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats. PMID:27966673

Development of Engineered Bacteriophages for Escherichia coli Detection and High-Throughput Antibiotic Resistance Determination.

PubMed

Chen, Juhong; Alcaine, Samuel D; Jackson, Angelyca A; Rotello, Vincent M; Nugen, Sam R

2017-04-28

T7 bacteriophages (phages) have been genetically engineered to carry the lacZ operon, enabling the overexpression of beta-galactosidase (β-gal) during phage infection and allowing for the enhanced colorimetric detection of Escherichia coli (E. coli). Following the phage infection of E. coli, the enzymatic activity of the released β-gal was monitored using a colorimetric substrate. Compared with a control T7 phage, our T7 lacZ phage generated significantly higher levels of β-gal expression following phage infection, enabling a lower limit of detection for E. coli cells. Using this engineered T7 lacZ phage, we were able to detect E. coli cells at 10 CFU·mL -1 within 7 h. Furthermore, we demonstrated the potential for phage-based sensing of bacteria antibiotic resistance profiling using our T7 lacZ phage, and subsequent β-gal expression to detect antibiotic resistant profile of E. coli strains.

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

NASA Astrophysics Data System (ADS)

Fan, Limin; Song, Chao; Meng, Shunlong; Qiu, Liping; Zheng, Yao; Wu, Wei; Qu, Jianhong; Li, Dandan; Zhang, Cong; Hu, Gengdong; Chen, Jiazhang

2016-12-01

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats.