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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

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

2017-06-01

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

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

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

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

2014-07-01

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

A Proteomic Workflow Using High-Throughput De Novo Sequencing Towards Complementation of Genome Information for Improved Comparative Crop Science.

PubMed

Turetschek, Reinhard; Lyon, David; Desalegn, Getinet; Kaul, Hans-Peter; Wienkoop, Stefanie

2016-01-01

The proteomic study of non-model organisms, such as many crop plants, is challenging due to the lack of comprehensive genome information. Changing environmental conditions require the study and selection of adapted cultivars. Mutations, inherent to cultivars, hamper protein identification and thus considerably complicate the qualitative and quantitative comparison in large-scale systems biology approaches. With this workflow, cultivar-specific mutations are detected from high-throughput comparative MS analyses, by extracting sequence polymorphisms with de novo sequencing. Stringent criteria are suggested to filter for confidential mutations. Subsequently, these polymorphisms complement the initially used database, which is ready to use with any preferred database search algorithm. In our example, we thereby identified 26 specific mutations in two cultivars of Pisum sativum and achieved an increased number (17 %) of peptide spectrum matches.

BiQ Analyzer HT: locus-specific analysis of DNA methylation by high-throughput bisulfite sequencing

PubMed Central

Lutsik, Pavlo; Feuerbach, Lars; Arand, Julia; Lengauer, Thomas; Walter, Jörn; Bock, Christoph

2011-01-01

Bisulfite sequencing is a widely used method for measuring DNA methylation in eukaryotic genomes. The assay provides single-base pair resolution and, given sufficient sequencing depth, its quantitative accuracy is excellent. High-throughput sequencing of bisulfite-converted DNA can be applied either genome wide or targeted to a defined set of genomic loci (e.g. using locus-specific PCR primers or DNA capture probes). Here, we describe BiQ Analyzer HT (http://biq-analyzer-ht.bioinf.mpi-inf.mpg.de/), a user-friendly software tool that supports locus-specific analysis and visualization of high-throughput bisulfite sequencing data. The software facilitates the shift from time-consuming clonal bisulfite sequencing to the more quantitative and cost-efficient use of high-throughput sequencing for studying locus-specific DNA methylation patterns. In addition, it is useful for locus-specific visualization of genome-wide bisulfite sequencing data. PMID:21565797

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

PubMed Central

2015-01-01

A hybrid microchip/capillary electrophoresis (CE) system was developed to allow unbiased and lossless sample loading and high-throughput repeated injections. This new hybrid CE system consists of a poly(dimethylsiloxane) (PDMS) microchip sample injector featuring a pneumatic microvalve that separates a sample introduction channel from a short sample loading channel, and a fused-silica capillary separation column that connects seamlessly to the sample loading channel. The sample introduction channel is pressurized such that when the pneumatic microvalve opens briefly, a variable-volume sample plug is introduced into the loading channel. A high voltage for CE separation is continuously applied across the loading channel and the fused-silica capillary separation column. Analytes are rapidly separated in the fused-silica capillary, and following separation, high-sensitivity MS detection is accomplished via a sheathless CE/ESI-MS interface. The performance evaluation of the complete CE/ESI-MS platform demonstrated that reproducible sample injection with well controlled sample plug volumes could be achieved by using the PDMS microchip injector. The absence of band broadening from microchip to capillary indicated a minimum dead volume at the junction. The capabilities of the new CE/ESI-MS platform in performing high-throughput and quantitative sample analyses were demonstrated by the repeated sample injection without interrupting an ongoing separation and a linear dependence of the total analyte ion abundance on the sample plug volume using a mixture of peptide standards. The separation efficiency of the new platform was also evaluated systematically at different sample injection times, flow rates, and CE separation voltages. PMID:24865952

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.

New High Throughput Methods to Estimate Chemical Exposure

EPA Science Inventory

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

High-throughput sensing and noninvasive imaging of protein nuclear transport by using reconstitution of split Renilla luciferase.

PubMed

Kim, Sung Bae; Ozawa, Takeaki; Watanabe, Shigeaki; Umezawa, Yoshio

2004-08-10

Nucleocytoplasmic trafficking of functional proteins plays a key role in regulating gene expressions in response to extracellular signals. We developed a genetically encoded bioluminescent indicator for monitoring the nuclear trafficking of target proteins in vitro and in vivo. The principle is based on reconstitution of split fragments of Renilla reniformis (Rluc) by protein splicing with a DnaE intein (a catalytic subunit of DNA polymerase III). A target cytosolic protein fused to the N-terminal half of Rluc is expressed in mammalian cells. If the protein translocates into the nucleus, the Rluc moiety meets the C-terminal half of Rluc, and full-length Rluc is reconstituted by protein splicing. We demonstrated quantitative cell-based in vitro sensing of ligand-induced translocation of androgen receptor, which allowed high-throughput screening of exo- and endogenous agonists and antagonists. Furthermore, the indicator enabled noninvasive in vivo imaging of the androgen receptor translocation in the brains of living mice with a charge-coupled device imaging system. These rapid and quantitative analyses in vitro and in vivo provide a wide variety of applications for screening pharmacological or toxicological compounds and testing them in living animals.

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

PubMed

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

2018-05-01

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

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

EPA Science Inventory

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

A high-throughput label-free nanoparticle analyser.

PubMed

Fraikin, Jean-Luc; Teesalu, Tambet; McKenney, Christopher M; Ruoslahti, Erkki; Cleland, Andrew N

2011-05-01

Synthetic nanoparticles and genetically modified viruses are used in a range of applications, but high-throughput analytical tools for the physical characterization of these objects are needed. Here we present a microfluidic analyser that detects individual nanoparticles and characterizes complex, unlabelled nanoparticle suspensions. We demonstrate the detection, concentration analysis and sizing of individual synthetic nanoparticles in a multicomponent mixture with sufficient throughput to analyse 500,000 particles per second. We also report the rapid size and titre analysis of unlabelled bacteriophage T7 in both salt solution and mouse blood plasma, using just ~1 × 10⁻⁶ l of analyte. Unexpectedly, in the native blood plasma we discover a large background of naturally occurring nanoparticles with a power-law size distribution. The high-throughput detection capability, scalable fabrication and simple electronics of this instrument make it well suited for diverse applications.

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

PubMed Central

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

2014-01-01

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

Breast cancer diagnosis using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

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

EPA Science Inventory

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

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

EPA Science Inventory

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

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

PubMed

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

2014-01-01

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

A Microfluidic Platform for High-Throughput Multiplexed Protein Quantitation

PubMed Central

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

2015-01-01

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

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

PubMed

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

2018-06-01

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

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

PubMed Central

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

2015-01-01

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

High-purity circular RNA isolation method (RPAD) reveals vast collection of intronic circRNAs.

PubMed

Panda, Amaresh C; De, Supriyo; Grammatikakis, Ioannis; Munk, Rachel; Yang, Xiaoling; Piao, Yulan; Dudekula, Dawood B; Abdelmohsen, Kotb; Gorospe, Myriam

2017-07-07

High-throughput RNA sequencing methods coupled with specialized bioinformatic analyses have recently uncovered tens of thousands of unique circular (circ)RNAs, but their complete sequences, genes of origin and functions are largely unknown. Given that circRNAs lack free ends and are thus relatively stable, their association with microRNAs (miRNAs) and RNA-binding proteins (RBPs) can influence gene expression programs. While exoribonuclease treatment is widely used to degrade linear RNAs and enrich circRNAs in RNA samples, it does not efficiently eliminate all linear RNAs. Here, we describe a novel method for the isolation of highly pure circRNA populations involving RNase R treatment followed by Polyadenylation and poly(A)+ RNA Depletion (RPAD), which removes linear RNA to near completion. High-throughput sequencing of RNA prepared using RPAD from human cervical carcinoma HeLa cells and mouse C2C12 myoblasts led to two surprising discoveries: (i) many exonic circRNA (EcircRNA) isoforms share an identical backsplice sequence but have different body sizes and sequences, and (ii) thousands of novel intronic circular RNAs (IcircRNAs) are expressed in cells. In sum, isolating high-purity circRNAs using the RPAD method can enable quantitative and qualitative analyses of circRNA types and sequence composition, paving the way for the elucidation of circRNA functions. Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

High-purity circular RNA isolation method (RPAD) reveals vast collection of intronic circRNAs

PubMed Central

De, Supriyo; Grammatikakis, Ioannis; Munk, Rachel; Yang, Xiaoling; Piao, Yulan; Dudekula, Dawood B.; Gorospe, Myriam

2017-01-01

Abstract High-throughput RNA sequencing methods coupled with specialized bioinformatic analyses have recently uncovered tens of thousands of unique circular (circ)RNAs, but their complete sequences, genes of origin and functions are largely unknown. Given that circRNAs lack free ends and are thus relatively stable, their association with microRNAs (miRNAs) and RNA-binding proteins (RBPs) can influence gene expression programs. While exoribonuclease treatment is widely used to degrade linear RNAs and enrich circRNAs in RNA samples, it does not efficiently eliminate all linear RNAs. Here, we describe a novel method for the isolation of highly pure circRNA populations involving RNase R treatment followed by Polyadenylation and poly(A)+ RNA Depletion (RPAD), which removes linear RNA to near completion. High-throughput sequencing of RNA prepared using RPAD from human cervical carcinoma HeLa cells and mouse C2C12 myoblasts led to two surprising discoveries: (i) many exonic circRNA (EcircRNA) isoforms share an identical backsplice sequence but have different body sizes and sequences, and (ii) thousands of novel intronic circular RNAs (IcircRNAs) are expressed in cells. In sum, isolating high-purity circRNAs using the RPAD method can enable quantitative and qualitative analyses of circRNA types and sequence composition, paving the way for the elucidation of circRNA functions. PMID:28444238

Optofluidic time-stretch quantitative phase microscopy.

PubMed

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

2018-03-01

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

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

PubMed Central

Bittker, Joshua A.

2012-01-01

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

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

PubMed

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

2007-03-27

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

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.

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

PubMed

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

2016-07-01

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

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

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

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

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

PubMed Central

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

2010-01-01

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

Bibliometrics for Social Validation.

PubMed

Hicks, Daniel J

2016-01-01

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

Bibliometrics for Social Validation

PubMed Central

2016-01-01

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

High-throughput real-time quantitative reverse transcription PCR.

PubMed

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

2006-02-01

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

Application of a label-free, gel-free quantitative proteomics method for ecotoxicological studies of small fish species

EPA Science Inventory

Although two-dimensional electrophoresis (2D-GE) remains the basis for many ecotoxicoproteomic analyses, new, non gel-based methods are beginning to be applied to overcome throughput and coverage limitations of 2D-GE. The overall objective of our research was to apply a comprehe...

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

Treesearch

William R. Kenealy; Thomas W. Jeffries

2003-01-01

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

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

PubMed Central

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

2009-01-01

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

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.

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

PubMed

Moutsatsos, Ioannis K; Parker, Christian N

2016-01-01

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

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

PubMed

Ule, Jernej

2009-12-01

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

Metrologies for quantitative nanomechanical testing and quality control in semiconductor manufacturing

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

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

PubMed

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

2015-02-09

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

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

PubMed

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

2008-01-01

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

Trends in mass spectrometry instrumentation for proteomics

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

Smith, Richard D.

2002-12-01

Mass spectrometry has become a primary tool for proteomics due to its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the needs for increased capabilities for proteome measurements are immense and are now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements, and promise more than order of magnitude improvements in sensitivity, dynamic range, and throughput for proteomic analyses in themore » near future.« less

Diagnosis of breast cancer biopsies using quantitative phase imaging

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

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

PubMed

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

2013-08-06

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2017-02-01

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

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.

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

PubMed Central

Dutta, Sanjib; Koide, Akiko; Koide, Shohei

2008-01-01

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

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

PubMed

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

PubMed Central

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

2016-01-01

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

Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis

PubMed Central

Paintdakhi, Ahmad; Parry, Bradley; Campos, Manuel; Irnov, Irnov; Elf, Johan; Surovtsev, Ivan; Jacobs-Wagner, Christine

2016-01-01

Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today’s single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals, and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis, and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills. PMID:26538279

Final technical report

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

Edward DeLong

2011-10-07

Our overarching goals in this project were to: Develop and improve high-throughput sequencing methods and analytical approaches for quantitative analyses of microbial gene expression at the Hawaii Ocean Time Series Station and the Bermuda Atlantic Time Series Station; Conduct field analyses following gene expression patterns in picoplankton microbial communities in general, and Prochlorococcus flow sorted from that community, as they respond to different environmental variables (light, macronutrients, dissolved organic carbon), that are predicted to influence activity, productivity, and carbon cycling; Use the expression analyses of flow sorted Prochlorococcus to identify horizontally transferred genes and gene products, in particular those thatmore » are located in genomic islands and likely to confer habitat-specific fitness advantages; Use the microbial community gene expression data that we generate to gain insights, and test hypotheses, about the variability, genomic context, activity and function of as yet uncharacterized gene products, that appear highly expressed in the environment. We achieved the above goals, and even more over the course of the project. This includes a number of novel methodological developments, as well as the standardization of microbial community gene expression analyses in both field surveys, and experimental modalities. The availability of these methods, tools and approaches is changing current practice in microbial community analyses.« less

Application of the accurate mass and time tag approach in studies of the human blood lipidome

PubMed Central

Ding, Jie; Sorensen, Christina M.; Jaitly, Navdeep; Jiang, Hongliang; Orton, Daniel J.; Monroe, Matthew E.; Moore, Ronald J.; Smith, Richard D.; Metz, Thomas O.

2008-01-01

We report a preliminary demonstration of the accurate mass and time (AMT) tag approach for lipidomics. Initial data-dependent LC-MS/MS analyses of human plasma, erythrocyte, and lymphocyte lipids were performed in order to identify lipid molecular species in conjunction with complementary accurate mass and isotopic distribution information. Identified lipids were used to populate initial lipid AMT tag databases containing 250 and 45 entries for those species detected in positive and negative electrospray ionization (ESI) modes, respectively. The positive ESI database was then utilized to identify human plasma, erythrocyte, and lymphocyte lipids in high-throughput LC-MS analyses based on the AMT tag approach. We were able to define the lipid profiles of human plasma, erythrocytes, and lymphocytes based on qualitative and quantitative differences in lipid abundance. PMID:18502191

Quantitative evaluation of refolding conditions for a disulfide-bond-containing protein using a concise 18O-labeling technique

PubMed Central

Uchimura, Hiromasa; Kim, Yusam; Mizuguchi, Takaaki; Kiso, Yoshiaki; Saito, Kazuki

2011-01-01

A concise method was developed for quantifying native disulfide-bond formation in proteins using isotopically labeled internal standards, which were easily prepared with proteolytic 18O-labeling. As the method has much higher throughput to estimate the amounts of fragments possessing native disulfide arrangements by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) than the conventional high performance liquid chromatography (HPLC) analyses, it allows many different experimental conditions to be assessed in a short time. The method was applied to refolding experiments of a recombinant neuregulin 1-β1 EGF-like motif (NRG1-β1), and the optimum conditions for preparing native NRG1-β1 were obtained by quantitative comparisons. Protein disulfide isomerase (PDI) was most effective at the reduced/oxidized glutathione ratio of 2:1 for refolding the denatured sample NRG1-β1 with the native disulfide bonds. PMID:21500299

Discovery of viruses and virus-like pathogens in pistachio using high-throughput sequencing

USDA-ARS?s Scientific Manuscript database

Pistachio (Pistacia vera L.) trees from the National Clonal Germplasm Repository (NCGR) and orchards in California were surveyed for viruses and virus-like agents by high-throughput sequencing (HTS). Analyses of 60 trees including clonal UCB-1 hybrid rootstock (P. atlantica × P. integerrima) identif...

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...

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

PubMed

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

2017-03-07

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

Microwave assisted saponification (MAS) followed by on-line liquid chromatography (LC)-gas chromatography (GC) for high-throughput and high-sensitivity determination of mineral oil in different cereal-based foodstuffs.

PubMed

Moret, Sabrina; Scolaro, Marianna; Barp, Laura; Purcaro, Giorgia; Conte, Lanfranco S

2016-04-01

A high throughput, high-sensitivity procedure, involving simultaneous microwave-assisted extraction (MAS) and unsaponifiable extraction, followed by on-line liquid chromatography (LC)-gas chromatography (GC), has been optimised for rapid and efficient extraction and analytical determination of mineral oil saturated hydrocarbons (MOSH) and mineral oil aromatic hydrocarbons (MOAH) in cereal-based products of different composition. MAS has the advantage of eliminating fat before LC-GC analysis, allowing an increase in the amount of sample extract injected, and hence in sensitivity. The proposed method gave practically quantitative recoveries and good repeatability. Among the different cereal-based products analysed (dry semolina and egg pasta, bread, biscuits, and cakes), egg pasta packed in direct contact with recycled paperboard had on average the highest total MOSH level (15.9 mg kg(-1)), followed by cakes (10.4 mg kg(-1)) and bread (7.5 mg kg(-1)). About 50% of the pasta and bread samples and 20% of the biscuits and cake samples had detectable MOAH amounts. The highest concentrations were found in an egg pasta in direct contact with recycled paperboard (3.6 mg kg(-1)) and in a milk bread (3.6 mg kg(-1)). Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

A Framework for Linking High-Throughput Modeling and Measurement Efforts to Advance 21st Century Exposure Science

EPA Science Inventory

The past five years have witnessed a rapid shift in the exposure science and toxicology communities towards high-throughput (HT) analyses of chemicals as potential stressors of human and ecological health. Modeling efforts have largely led the charge in the exposure science field...

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.

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

PubMed Central

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

2012-01-01

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

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

PubMed Central

Choudhry, Priya

2016-01-01

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

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...

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

PubMed

Engelmann, Brett W

2017-01-01

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

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

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

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

2016-05-01

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

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

PubMed

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

2014-06-01

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

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

EPA Science Inventory

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-06-05

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

Quantitative High-Throughput Luciferase Screening in Identifying CAR Modulators.

PubMed

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

2016-01-01

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

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

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Opportunistic data locality for end user data analysis

NASA Astrophysics Data System (ADS)

Fischer, M.; Heidecker, C.; Kuehn, E.; Quast, G.; Giffels, M.; Schnepf, M.; Heiss, A.; Petzold, A.

2017-10-01

With the increasing data volume of LHC Run2, user analyses are evolving towards increasing data throughput. This evolution translates to higher requirements for efficiency and scalability of the underlying analysis infrastructure. We approach this issue with a new middleware to optimise data access: a layer of coordinated caches transparently provides data locality for high-throughput analyses. We demonstrated the feasibility of this approach with a prototype used for analyses of the CMS working groups at KIT. In this paper, we present our experience both with the approach in general, and our prototype in specific.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2012-07-26

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

Flow cytometry and real-time quantitative PCR as tools for assessing plasmid persistence.

PubMed

Loftie-Eaton, Wesley; Tucker, Allison; Norton, Ann; Top, Eva M

2014-09-01

The maintenance of a plasmid in the absence of selection for plasmid-borne genes is not guaranteed. However, plasmid persistence can evolve under selective conditions. Studying the molecular mechanisms behind the evolution of plasmid persistence is key to understanding how plasmids are maintained under nonselective conditions. Given the current crisis of rapid antibiotic resistance spread by multidrug resistance plasmids, this insight is of high medical relevance. The conventional method for monitoring plasmid persistence (i.e., the fraction of plasmid-containing cells in a population over time) is based on cultivation and involves differentiating colonies of plasmid-containing and plasmid-free cells on agar plates. However, this technique is time-consuming and does not easily lend itself to high-throughput applications. Here, we present flow cytometry (FCM) and real-time quantitative PCR (qPCR) as alternative tools for monitoring plasmid persistence. For this, we measured the persistence of a model plasmid, pB10::gfp, in three Pseudomonas hosts and in known mixtures of plasmid-containing and -free cells. We also compared three performance criteria: dynamic range, resolution, and variance. Although not without exceptions, both techniques generated estimates of overall plasmid loss rates that were rather similar to those generated by the conventional plate count (PC) method. They also were able to resolve differences in loss rates between artificial plasmid persistence assays. Finally, we briefly discuss the advantages and disadvantages for each technique and conclude that, overall, both FCM and real-time qPCR are suitable alternatives to cultivation-based methods for routine measurement of plasmid persistence, thereby opening avenues for high-throughput analyses. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

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

PubMed

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

2016-03-14

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

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

PubMed

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

2017-05-01

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

Increasing ecological inference from high throughput sequencing of fungi in the environment through a tagging approach

Treesearch

D. Lee Taylor; Michael G. Booth; Jack W. McFarland; Ian C. Herriott; Niall J. Lennon; Chad Nusbaum; Thomas G. Marr

2008-01-01

High throughput sequencing methods are widely used in analyses of microbial diversity but are generally applied to small numbers of samples, which precludes charaterization of patterns of microbial diversity across space and time. We have designed a primer-tagging approach that allows pooling and subsequent sorting of numerous samples, which is directed to...

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

PubMed Central

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

2015-01-01

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

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

PubMed

Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

2017-08-01

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

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

PubMed

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

2010-01-01

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

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

PubMed

Putt, Karson S; Pugh, Randall B

2013-01-01

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

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

PubMed Central

Putt, Karson S.; Pugh, Randall B.

2013-01-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-08-16

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

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

EPA Pesticide Factsheets

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

A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements

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

Orton, Daniel J.; Tfaily, Malak M.; Moore, Ronald J.

To better understand disease conditions and environmental perturbations, multi-omic studies (i.e. proteomic, lipidomic, metabolomic, etc. analyses) are vastly increasing in popularity. In a multi-omic study, a single sample is typically extracted in multiple ways and numerous analyses are performed using different instruments. Thus, one sample becomes many analyses, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injection. While some FIA systems have been created to address these challenges, many have limitations such as high consumable costs, lowmore » pressure capabilities, limited pressure monitoring and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at diverse flow rates (~50 nL/min to 500 µL/min) to accommodate low- and high-flow instrument sources. This system can also operate at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system. The results from these studies showed a highly robust platform, providing consistent performance over many days without carryover as long as washing buffers specific to each molecular analysis were utilized.« less

Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome

PubMed Central

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

2011-01-01

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

A novel 3D imaging system for strawberry phenotyping.

PubMed

He, Joe Q; Harrison, Richard J; Li, Bo

2017-01-01

Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. A low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique.

Bacterial diversity in typical Italian salami at different ripening stages as revealed by high-throughput sequencing of 16S rRNA amplicons.

PubMed

Połka, Justyna; Rebecchi, Annalisa; Pisacane, Vincenza; Morelli, Lorenzo; Puglisi, Edoardo

2015-04-01

The bacterial diversity involved in food fermentations is one of the most important factors shaping the final characteristics of traditional foods. Knowledge about this diversity can be greatly improved by the application of high-throughput sequencing technologies (HTS) coupled to the PCR amplification of the 16S rRNA subunit. Here we investigated the bacterial diversity in batches of Salame Piacentino PDO (Protected Designation of Origin), a dry fermented sausage that is typical of a regional area of Northern Italy. Salami samples from 6 different local factories were analysed at 0, 21, 49 and 63 days of ripening; raw meat at time 0 and casing samples at 21 days of ripening where also analysed, and the effect of starter addition was included in the experimental set-up. Culture-based microbiological analyses and PCR-DGGE were carried out in order to be compared with HTS results. A total of 722,196 high quality sequences were obtained after trimming, paired-reads assembly and quality screening of raw reads obtained by Illumina MiSeq sequencing of the two bacterial 16S hypervariable regions V3 and V4; manual curation of 16S database allowed a correct taxonomical classification at the species for 99.5% of these reads. Results confirmed the presence of main bacterial species involved in the fermentation of salami as assessed by PCR-DGGE, but with a greater extent of resolution and quantitative assessments that are not possible by the mere analyses of gel banding patterns. Thirty-two different Staphylococcus and 33 Lactobacillus species where identified in the salami from different producers, while the whole data set obtained accounted for 13 main families and 98 rare ones, 23 of which were present in at least 10% of the investigated samples, with casings being the major sources of the observed diversity. Multivariate analyses also showed that batches from 6 local producers tend to cluster altogether after 21 days of ripening, thus indicating that HTS has the potential for fine scale differentiation of local fermented foods. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2005-09-01

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

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

PubMed

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

2017-06-20

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

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

PubMed Central

Bokulich, Nicholas A.

2013-01-01

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

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

PubMed

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

2014-01-01

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

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

PubMed

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

2018-02-21

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

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

Science.gov Websites

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

Quantitative High-throughput Luciferase Screening in Identifying CAR Modulators

PubMed Central

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

2017-01-01

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

A Review of Imaging Techniques for Plant Phenotyping

PubMed Central

Li, Lei; Zhang, Qin; Huang, Danfeng

2014-01-01

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

Two Algorithms for High-throughput and Multi-parametric Quantification of Drosophila Neuromuscular Junction Morphology.

PubMed

Castells-Nobau, Anna; Nijhof, Bonnie; Eidhof, Ilse; Wolf, Louis; Scheffer-de Gooyert, Jolanda M; Monedero, Ignacio; Torroja, Laura; van der Laak, Jeroen A W M; Schenck, Annette

2017-05-03

Synaptic morphology is tightly related to synaptic efficacy, and in many cases morphological synapse defects ultimately lead to synaptic malfunction. The Drosophila larval neuromuscular junction (NMJ), a well-established model for glutamatergic synapses, has been extensively studied for decades. Identification of mutations causing NMJ morphological defects revealed a repertoire of genes that regulate synapse development and function. Many of these were identified in large-scale studies that focused on qualitative approaches to detect morphological abnormalities of the Drosophila NMJ. A drawback of qualitative analyses is that many subtle players contributing to NMJ morphology likely remain unnoticed. Whereas quantitative analyses are required to detect the subtler morphological differences, such analyses are not yet commonly performed because they are laborious. This protocol describes in detail two image analysis algorithms "Drosophila NMJ Morphometrics" and "Drosophila NMJ Bouton Morphometrics", available as Fiji-compatible macros, for quantitative, accurate and objective morphometric analysis of the Drosophila NMJ. This methodology is developed to analyze NMJ terminals immunolabeled with the commonly used markers Dlg-1 and Brp. Additionally, its wider application to other markers such as Hrp, Csp and Syt is presented in this protocol. The macros are able to assess nine morphological NMJ features: NMJ area, NMJ perimeter, number of boutons, NMJ length, NMJ longest branch length, number of islands, number of branches, number of branching points and number of active zones in the NMJ terminal.

Global phenotypic characterisation of human platelet lysate expanded MSCs by high-throughput flow cytometry.

PubMed

Reis, Monica; McDonald, David; Nicholson, Lindsay; Godthardt, Kathrin; Knobel, Sebastian; Dickinson, Anne M; Filby, Andrew; Wang, Xiao-Nong

2018-03-02

Mesenchymal stromal cells (MSCs) are a promising cell source to develop cell therapy for many diseases. Human platelet lysate (PLT) is increasingly used as an alternative to foetal calf serum (FCS) for clinical-scale MSC production. To date, the global surface protein expression of PLT-expended MSCs (MSC-PLT) is not known. To investigate this, paired MSC-PLT and MSC-FCS were analysed in parallel using high-throughput flow cytometry for the expression of 356 cell surface proteins. MSC-PLT showed differential surface protein expression compared to their MSC-FCS counterpart. Higher percentage of positive cells was observed in MSC-PLT for 48 surface proteins, of which 13 were significantly enriched on MSC-PLT. This finding was validated using multiparameter flow cytometry and further confirmed by quantitative staining intensity analysis. The enriched surface proteins are relevant to increased proliferation and migration capacity, as well as enhanced chondrogenic and osteogenic differentiation properties. In silico network analysis revealed that these enriched surface proteins are involved in three distinct networks that are associated with inflammatory responses, carbohydrate metabolism and cellular motility. This is the first study reporting differential cell surface protein expression between MSC-PLT and MSC-FSC. Further studies are required to uncover the impact of those enriched proteins on biological functions of MSC-PLT.

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

NASA Astrophysics Data System (ADS)

Potyrailo, Radislav A.; Mirsky, Vladimir M.

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

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

PubMed

Keegan, Alissa; Plath, Kathrin; Damoiseaux, Robert

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

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

PubMed

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

2017-01-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-13

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

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

PubMed Central

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

2010-01-01

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2015-01-01

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

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

PubMed

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

2018-05-21

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

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

PubMed

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

2017-01-01

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

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

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

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

2014-11-15

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-03-01

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

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

PubMed Central

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

2017-01-01

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

Lessons we learned from high-throughput and top-down systems biology analyses about glioma stem cells.

PubMed

Mock, Andreas; Chiblak, Sara; Herold-Mende, Christel

2014-01-01

A growing body of evidence suggests that glioma stem cells (GSCs) account for tumor initiation, therapy resistance, and the subsequent regrowth of gliomas. Thus, continuous efforts have been undertaken to further characterize this subpopulation of less differentiated tumor cells. Although we are able to enrich GSCs, we still lack a comprehensive understanding of GSC phenotypes and behavior. The advent of high-throughput technologies raised hope that incorporation of these newly developed platforms would help to tackle such questions. Since then a couple of comparative genome-, transcriptome- and proteome-wide studies on GSCs have been conducted giving new insights in GSC biology. However, lessons had to be learned in designing high-throughput experiments and some of the resulting conclusions fell short of expectations because they were performed on only a few GSC lines or at one molecular level instead of an integrative poly-omics approach. Despite these shortcomings, our knowledge of GSC biology has markedly expanded due to a number of survival-associated biomarkers as well as glioma-relevant signaling pathways and therapeutic targets being identified. In this article we review recent findings obtained by comparative high-throughput analyses of GSCs. We further summarize fundamental concepts of systems biology as well as its applications for glioma stem cell research.

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

PubMed

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

2002-07-31

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

DPubChem: a web tool for QSAR modeling and high-throughput virtual screening.

PubMed

Soufan, Othman; Ba-Alawi, Wail; Magana-Mora, Arturo; Essack, Magbubah; Bajic, Vladimir B

2018-06-14

High-throughput screening (HTS) performs the experimental testing of a large number of chemical compounds aiming to identify those active in the considered assay. Alternatively, faster and cheaper methods of large-scale virtual screening are performed computationally through quantitative structure-activity relationship (QSAR) models. However, the vast amount of available HTS heterogeneous data and the imbalanced ratio of active to inactive compounds in an assay make this a challenging problem. Although different QSAR models have been proposed, they have certain limitations, e.g., high false positive rates, complicated user interface, and limited utilization options. Therefore, we developed DPubChem, a novel web tool for deriving QSAR models that implement the state-of-the-art machine-learning techniques to enhance the precision of the models and enable efficient analyses of experiments from PubChem BioAssay database. DPubChem also has a simple interface that provides various options to users. DPubChem predicted active compounds for 300 datasets with an average geometric mean and F 1 score of 76.68% and 76.53%, respectively. Furthermore, DPubChem builds interaction networks that highlight novel predicted links between chemical compounds and biological assays. Using such a network, DPubChem successfully suggested a novel drug for the Niemann-Pick type C disease. DPubChem is freely available at www.cbrc.kaust.edu.sa/dpubchem .

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

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

2017-08-20

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

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

PubMed

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

2014-11-21

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

Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

PubMed

Wolen, Aaron R; Miles, Michael F

2012-01-01

For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-09-01

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

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

PubMed

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

2016-08-30

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

High Resolution Separations and Improved Ion Production and Transmission in Metabolomics

PubMed Central

Metz, Thomas O.; Page, Jason S.; Baker, Erin S.; Tang, Keqi; Ding, Jie; Shen, Yufeng; Smith, Richard D.

2008-01-01

The goal of metabolomics analyses is the detection and quantitation of as many sample components as reasonably possible in order to identify compounds or “features” that can be used to characterize the samples under study. When utilizing electrospray ionization to produce ions for analysis by mass spectrometry (MS), it is important that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize ionization suppression and thereby extend the dynamic range of the measurement, as well as the coverage of the metabolome. Similarly, optimization of the MS inlet and interface can lead to increased measurement sensitivity. This perspective review will focus on the role of high resolution liquid chromatography (LC) separations in conjunction with improved ion production and transmission for LC-MS-based metabolomics. Additional emphasis will be placed on the compromise between metabolome coverage and sample analysis throughput. PMID:19255623

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2014-12-15

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

Ex Priori: Exposure-based Prioritization across Chemical Space

EPA Science Inventory

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

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

EPA Science Inventory

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

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

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

2014-01-01

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

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

Analysis of High-Throughput ELISA Microarray Data

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

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

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

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

PubMed

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

2002-10-01

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

solGS: a web-based tool for genomic selection

USDA-ARS?s Scientific Manuscript database

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

Digital PCR for detection of citrus pathogens

USDA-ARS?s Scientific Manuscript database

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

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

EPA Science Inventory

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

Overcoming bias and systematic errors in next generation sequencing data.

PubMed

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

2010-12-10

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

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

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

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

DOE PAGES

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

2015-12-09

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

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.

A novel mesh processing based technique for 3D plant analysis

PubMed Central

2012-01-01

Background In recent years, imaging based, automated, non-invasive, and non-destructive high-throughput plant phenotyping platforms have become popular tools for plant biology, underpinning the field of plant phenomics. Such platforms acquire and record large amounts of raw data that must be accurately and robustly calibrated, reconstructed, and analysed, requiring the development of sophisticated image understanding and quantification algorithms. The raw data can be processed in different ways, and the past few years have seen the emergence of two main approaches: 2D image processing and 3D mesh processing algorithms. Direct image quantification methods (usually 2D) dominate the current literature due to comparative simplicity. However, 3D mesh analysis provides the tremendous potential to accurately estimate specific morphological features cross-sectionally and monitor them over-time. Result In this paper, we present a novel 3D mesh based technique developed for temporal high-throughput plant phenomics and perform initial tests for the analysis of Gossypium hirsutum vegetative growth. Based on plant meshes previously reconstructed from multi-view images, the methodology involves several stages, including morphological mesh segmentation, phenotypic parameters estimation, and plant organs tracking over time. The initial study focuses on presenting and validating the accuracy of the methodology on dicotyledons such as cotton but we believe the approach will be more broadly applicable. This study involved applying our technique to a set of six Gossypium hirsutum (cotton) plants studied over four time-points. Manual measurements, performed for each plant at every time-point, were used to assess the accuracy of our pipeline and quantify the error on the morphological parameters estimated. Conclusion By directly comparing our automated mesh based quantitative data with manual measurements of individual stem height, leaf width and leaf length, we obtained the mean absolute errors of 9.34%, 5.75%, 8.78%, and correlation coefficients 0.88, 0.96, and 0.95 respectively. The temporal matching of leaves was accurate in 95% of the cases and the average execution time required to analyse a plant over four time-points was 4.9 minutes. The mesh processing based methodology is thus considered suitable for quantitative 4D monitoring of plant phenotypic features. PMID:22553969

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

PubMed

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

2017-02-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2011-02-01

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

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

PubMed

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

2013-07-15

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

Rapid quantitative determination of maltose and total sugars in sweet potato (Ipomoea batatas L. [Lam.]) varieties using HPTLC.

PubMed

Lebot, Vincent

2017-03-01

When a raw sweet potato root is analysed, only sucrose, glucose and fructose are present but during cooking, starch is hydrolysed into maltose giving the sweet flavour to cooked roots. This study aimed at developing an HPTLC protocol for the rapid quantitative determination of maltose and total sugars in four commercial varieties and to compare them to 243 hybrids grouped by flesh colour (white, orange, purple). In commercial varieties, mean maltose content varied from 10.26 to 15.60% and total sugars from 17.83 to 27.77% on fresh weight basis. Hybrids showed significant variation in maltose content within each group, with means ranging from 7.65% for white-fleshed, to 8.53% in orange- and 11.98% in purple-fleshed. Total mean sugars content was 20.24, 22.11 and 26.84% respectively for white, orange and purple flesh hybrids. No significant correlations were detected between individual sugars but maltose and total sugars content were highly correlated. Compared to the best commercial variety ( Baby ), 25 hybrids (10.3%) presented a higher maltose content and 40 (16.5%) showed a higher total sugars content. HPTLC was observed as an attractive, cost efficient, high-throughput technique for quantitating maltose and total sugars in sweet potatoes. Perspectives for improving sweet potato quality for consumers' requirements are also discussed.

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

Ranking the in vivo toxicity of nanomaterials in Drosophila melanogaster

NASA Astrophysics Data System (ADS)

Vecchio, G.; Galeone, A.; Malvindi, M. A.; Cingolani, R.; Pompa, P. P.

2013-09-01

In this work, we propose a quantitative assessment of nanoparticles toxicity in vivo. We show a quantitative ranking of several types of nanoparticles (AuNPs, AgNPs, cadmium-based QDs, cadmium-free QDs, and iron oxide NPs, with different coating and/or surface chemistries), providing a categorization of their toxicity outcomes. This strategy may offer an innovative high-throughput screening tool of nanomaterials, of potential and broad interest to the nanoscience community.

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

PubMed Central

2010-01-01

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

Testing quantitative adverse outcome pathway predictions using aromatase inhibitors in female fathead minnows

EPA Science Inventory

To become more efficient and cost effective regulatory toxicology is increasingly averting from whole animal testing toward collecting data at lower levels of biological organization, through such means as in vitro high throughput screening (HTS) assays. When anchored to relevant...

An Upper Bound for Population Exposure Variability (SOT)

EPA Science Inventory

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

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

PubMed

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Esposito, Alessandro

2006-05-01

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2017-02-21

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

High-throughput technology for novel SO2 oxidation catalysts

PubMed Central

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

2011-01-01

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

Structuring intuition with theory: The high-throughput way

NASA Astrophysics Data System (ADS)

Fornari, Marco

2015-03-01

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

Rapid determination of 1-deoxynojirimycin in Morus alba L. leaves by direct analysis in real time (DART) mass spectrometry.

PubMed

Xu, Bin; Zhang, Dong-Yang; Liu, Ze-Yu; Zhang, Ying; Liu, Li; Li, Long; Liu, Charles C; Wu, Guo-Hua

2015-10-10

A new method based on a Direct Analysis in Real Time (DART) ionization source coupled with triple quadrupole tandem mass spectrometry has been developed for rapid qualitative and quantitative analyses of 1-deoxynojirimycin (DNJ) in mulberry leaves. Two ions produced from DNJ, [M+H](+) (m/z 164) and [M-2H+H](+) (m/z 162), are observed using DART-MS in the positive ion mode. The peak areas of the two selected ions monitoring (SIM) signals of ([M+H](+) (m/z 164) and [M-2H+H](+) (m/z 162)) are integrated to determine the peak area for quantitative analyses. A reasonable linear regression equation is obtained in the range of 1.01 to 40.50 μg/mL, with a linear coefficient (R(2)) of 0.996. The limits of detection (LOD) and quantification (LOQ) of the method are 0.25 and 0.80 μg/mL, respectively. The range of recovery is shown to be 87.73-95.61%. The results derived from the developed DART-MS method are in good agreement with those from the conventional HPLC-FLD method. By contrast, DART-MS in SIM mode is a simple, rapid and high-throughput approach for the determination of the DNJ content in mulberry leaves. The present method is advantageous for the rapid screening of mulberry leaves containing high DNJ contents. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2017-01-01

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

A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

PubMed Central

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-01-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. PMID:24972598

A high-density genetic map with array-based markers facilitates structural and quantitative trait locus analyses of the common wheat genome.

PubMed

Iehisa, Julio Cesar Masaru; Ohno, Ryoko; Kimura, Tatsuro; Enoki, Hiroyuki; Nishimura, Satoru; Okamoto, Yuki; Nasuda, Shuhei; Takumi, Shigeo

2014-10-01

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Quantitative analyses reveal distinct sensitivities of the capture of HIV-1 primary viruses and pseudoviruses to broadly neutralizing antibodies.

PubMed

Kim, Jiae; Jobe, Ousman; Peachman, Kristina K; Michael, Nelson L; Robb, Merlin L; Rao, Mangala; Rao, Venigalla B

2017-08-01

Development of vaccines capable of eliciting broadly neutralizing antibodies (bNAbs) is a key goal to controlling the global AIDS epidemic. To be effective, bNAbs must block the capture of HIV-1 to prevent viral acquisition and establishment of reservoirs. However, the role of bNAbs, particularly during initial exposure of primary viruses to host cells, has not been fully examined. Using a sensitive, quantitative, and high-throughput qRT-PCR assay, we found that primary viruses were captured by host cells and converted into a trypsin-resistant form in less than five minutes. We discovered, unexpectedly, that bNAbs did not block primary virus capture, although they inhibited the capture of pseudoviruses/IMCs and production of progeny viruses at 48h. Further, viruses escaped bNAb inhibition unless the bNAbs were present in the initial minutes of exposure of virus to host cells. These findings will have important implications for HIV-1 vaccine design and determination of vaccine efficacy. Copyright © 2017 The Authors. Published by 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

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

PubMed

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

2012-06-20

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

Adapting the γ-H2AX assay for automated processing in human lymphocytes. 1. Technological aspects.

PubMed

Turner, Helen C; Brenner, David J; Chen, Youhua; Bertucci, Antonella; Zhang, Jian; Wang, Hongliang; Lyulko, Oleksandra V; Xu, Yanping; Shuryak, Igor; Schaefer, Julia; Simaan, Nabil; Randers-Pehrson, Gerhard; Yao, Y Lawrence; Amundson, Sally A; Garty, Guy

2011-03-01

The immunofluorescence-based detection of γ-H2AX is a reliable and sensitive method for quantitatively measuring DNA double-strand breaks (DSBs) in irradiated samples. Since H2AX phosphorylation is highly linear with radiation dose, this well-established biomarker is in current use in radiation biodosimetry. At the Center for High-Throughput Minimally Invasive Radiation Biodosimetry, we have developed a fully automated high-throughput system, the RABIT (Rapid Automated Biodosimetry Tool), that can be used to measure γ-H2AX yields from fingerstick-derived samples of blood. The RABIT workstation has been designed to fully automate the γ-H2AX immunocytochemical protocol, from the isolation of human blood lymphocytes in heparin-coated PVC capillaries to the immunolabeling of γ-H2AX protein and image acquisition to determine fluorescence yield. High throughput is achieved through the use of purpose-built robotics, lymphocyte handling in 96-well filter-bottomed plates, and high-speed imaging. The goal of the present study was to optimize and validate the performance of the RABIT system for the reproducible and quantitative detection of γ-H2AX total fluorescence in lymphocytes in a multiwell format. Validation of our biodosimetry platform was achieved by the linear detection of a dose-dependent increase in γ-H2AX fluorescence in peripheral blood samples irradiated ex vivo with γ rays over the range 0 to 8 Gy. This study demonstrates for the first time the optimization and use of our robotically based biodosimetry workstation to successfully quantify γ-H2AX total fluorescence in irradiated peripheral lymphocytes.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-16

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

QUANTITATIVE IN VITRO MEASUREMENT OF CELLULAR PROCESSES CRITICAL TO THE DEVELOPMENT OF NEURAL CONNECTIVITY USING HCA.

EPA Science Inventory

New methods are needed to screen thousands of environmental chemicals for toxicity, including developmental neurotoxicity. In vitro, cell-based assays that model key cellular events have been proposed for high throughput screening of chemicals for developmental neurotoxicity. Whi...

High Throughput Heuristics for Prioritizing Human Exposure to Environmental Chemicals

EPA Science Inventory

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the potential hazard presented by the chemical, and the possibility of being exposed. Without the capacity to make quantitative, albeit uncertain, f...

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

NASA Astrophysics Data System (ADS)

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

2002-02-01

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

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

PubMed

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

2017-08-15

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

A morphogenetic survey on ciliate plankton from a mountain lake pinpoints the necessity of lineage-specific barcode markers in microbial ecology.

PubMed

Stoeck, Thorsten; Breiner, Hans-Werner; Filker, Sabine; Ostermaier, Veronika; Kammerlander, Barbara; Sonntag, Bettina

2014-02-01

Analyses of high-throughput environmental sequencing data have become the 'gold-standard' to address fundamental questions of microbial diversity, ecology and biogeography. Findings that emerged from sequencing are, e.g. the discovery of the extensive 'rare microbial biosphere' and its potential function as a seed-bank. Even though applied since several years, results from high-throughput environmental sequencing have hardly been validated. We assessed how well pyrosequenced amplicons [the hypervariable eukaryotic V4 region of the small subunit ribosomal RNA (SSU rRNA) gene] reflected morphotype ciliate plankton. Moreover, we assessed if amplicon sequencing had the potential to detect the annual ciliate plankton stock. In both cases, we identified significant quantitative and qualitative differences. Our study makes evident that taxon abundance distributions inferred from amplicon data are highly biased and do not mirror actual morphotype abundances at all. Potential reasons included cell losses after fixation, cryptic morphotypes, resting stages, insufficient sequence data availability of morphologically described species and the unsatisfying resolution of the V4 SSU rRNA fragment for accurate taxonomic assignments. The latter two underline the necessity of barcoding initiatives for eukaryotic microbes to better and fully exploit environmental amplicon data sets, which then will also allow studying the potential of seed-bank taxa as a buffer for environmental changes. © 2013 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.

Applications of Microfluidics in Quantitative Biology.

PubMed

Bai, Yang; Gao, Meng; Wen, Lingling; He, Caiyun; Chen, Yuan; Liu, Chenli; Fu, Xiongfei; Huang, Shuqiang

2018-05-01

Quantitative biology is dedicated to taking advantage of quantitative reasoning and advanced engineering technologies to make biology more predictable. Microfluidics, as an emerging technique, provides new approaches to precisely control fluidic conditions on small scales and collect data in high-throughput and quantitative manners. In this review, the authors present the relevant applications of microfluidics to quantitative biology based on two major categories (channel-based microfluidics and droplet-based microfluidics), and their typical features. We also envision some other microfluidic techniques that may not be employed in quantitative biology right now, but have great potential in the near future. © 2017 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. Biotechnology Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

High throughput computing: a solution for scientific analysis

USGS Publications Warehouse

O'Donnell, M.

2011-01-01

handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses High Throughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

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

PubMed

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

2008-02-01

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

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

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

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

2009-07-20

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

High-throughput syntheses of iron phosphite open frameworks in ionic liquids

NASA Astrophysics Data System (ADS)

Wang, Zhixiu; Mu, Ying; Wang, Yilin; Bing, Qiming; Su, Tan; Liu, Jingyao

2017-02-01

Three open-framework iron phosphites: Feп5(NH4)2(HPO3)6 (1), Feп2Fe♯(NH4)(HPO3)4 (2) and Fe♯2(HPO3)3 (3) have been synthesized under ionothermal conditions. How the different synthesis parameters, such as the gel concentrations, synthetic times, reaction temperatures and solvents affect the products have been monitored by using high-throughput approaches. Within each type of experiment, relevant products have been investigated. The optimal reaction conditions are obtained from a series of experiments by high-throughput approaches. All the structures are determined by single-crystal X-ray diffraction analysis and further characterized by PXRD, TGA and FTIR analyses. Magnetic study reveals that those three compounds show interesting magnetic behavior at low temperature.

Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

Cancer.gov

In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

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

Cancer.gov

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

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

PubMed

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

2013-07-15

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

Virtual Liver: Quantitative Dose-Response Using Systems Biology

EPA Science Inventory

The U.S. EPA’s ToxCast™ program uses hundreds of high-throughput, in vitro assays to screen chemicals in order to rapidly identify signatures of toxicity. These assays measure the in vitro concentrations at which cellular pathways are perturbed by chemicals. The U.S. EPA’s Virtu...

SPECIES-SPECIFIC DETECTION OF THREE HUMAN-PATHOGENIC MICROSPORIDIAL SPECIES FROM THE GENUS ENCEPHALITOZOON VIA FLUOROGENIC 5' NUCLEASE PCR ASSAYS

EPA Science Inventory

This describes fluorogenic 5' nuclease PCR assays suitable for rapid, sensitive, quantitative, high-throughput detection of the human-pathogenic microsporidial species Encephalitozoon hellem, E. cunicli and E. intestinalis. The assays utilize species-specific primer sets and a g...

Analysis of Ingredient Lists to Quantitatively Characterize Chemicals in Consumer Products

EPA Science Inventory

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

Quantitative High-Throughput Screening and Confirmation Studies for Identification of Compounds that Activate the Aryl Hydrocarbon Receptor Pathway (SETAC)

EPA Science Inventory

The aryl hydrocarbon receptor (AhR) is a transcription factor that mediates adaptive responses to known environmental pollutants, such as aromatic hydrocarbons, through regulation of Phase I and II xenobiotic metabolizing enzymes as well as important growth and differentiation pa...

A Call for Nominations of Quantitative High-Throughput Screening Assays from Relevant Human Toxicity Pathways

EPA Science Inventory

The National Research Council of the United States National Academies of Science has recently released a document outlining a long-range vision and strategy for transforming toxicity testing from largely whole animal-based testing to one based on in vitro assays. “Toxicity Testin...

Profiling Environmental Chemicals in the Antioxidant Response Element Pathway using Quantitative High Throughput Screening (qHTS)

EPA Science Inventory

The antioxidant response element (ARE) signaling pathway plays an important role in the amelioration of oxidative stress, which can contribute to a number of diseases, including cancer. We screened 1408 NTP-provided substances in 1536-well qHTS format at concentrations ranging fr...

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

EPA Science Inventory

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

Three classes of glucocerebrosidase inhibitors identified by quantitative high-throughput screening are chaperone leads for Gaucher disease

PubMed Central

Zheng, Wei; Padia, Janak; Urban, Daniel J.; Jadhav, Ajit; Goker-Alpan, Ozlem; Simeonov, Anton; Goldin, Ehud; Auld, Douglas; LaMarca, Mary E.; Inglese, James; Austin, Christopher P.; Sidransky, Ellen

2007-01-01

Gaucher disease is an autosomal recessive lysosomal storage disorder caused by mutations in the glucocerebrosidase gene. Missense mutations result in reduced enzyme activity that may be due to misfolding, raising the possibility of small-molecule chaperone correction of the defect. Screening large compound libraries by quantitative high-throughput screening (qHTS) provides comprehensive information on the potency, efficacy, and structure–activity relationships (SAR) of active compounds directly from the primary screen, facilitating identification of leads for medicinal chemistry optimization. We used qHTS to rapidly identify three structural series of potent, selective, nonsugar glucocerebrosidase inhibitors. The three structural classes had excellent potencies and efficacies and, importantly, high selectivity against closely related hydrolases. Preliminary SAR data were used to select compounds with high activity in both enzyme and cell-based assays. Compounds from two of these structural series increased N370S mutant glucocerebrosidase activity by 40–90% in patient cell lines and enhanced lysosomal colocalization, indicating chaperone activity. These small molecules have potential as leads for chaperone therapy for Gaucher disease, and this paradigm promises to accelerate the development of leads for other rare genetic disorders. PMID:17670938

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

PubMed Central

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

2014-01-01

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

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

PubMed

Liu, Guangbo; Lanham, Clayton; Buchan, J Ross; Kaplan, Matthew E

2017-01-01

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

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.

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

PubMed

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

2017-04-15

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

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

PubMed

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

2009-01-01

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

Molecular Rotors for Universal Quantitation of Nanoscale Hydrophobic Interfaces in Microplate Format.

PubMed

Bisso, Paul W; Tai, Michelle; Katepalli, Hari; Bertrand, Nicolas; Blankschtein, Daniel; Langer, Robert

2018-01-10

Hydrophobic self-assembly pairs diverse chemical precursors and simple formulation processes to access a vast array of functional colloids. Exploration of this design space, however, is stymied by lack of broadly general, high-throughput colloid characterization tools. Here, we show that a narrow structural subset of fluorescent, zwitterionic molecular rotors, dialkylaminostilbazolium sulfonates [DASS] with intermediate-length alkyl tails, fills this major analytical void by quantitatively sensing hydrophobic interfaces in microplate format. DASS dyes supersede existing interfacial probes by avoiding off-target fluorogenic interactions and dye aggregation while preserving hydrophobic partitioning strength. To illustrate the generality of this approach, we demonstrate (i) a microplate-based technique for measuring mass concentration of small (20-200 nm), dilute (submicrogram sensitivity) drug delivery nanoparticles; (ii) elimination of particle size, surfactant chemistry, and throughput constraints on quantifying the complex surfactant/metal oxide adsorption isotherms critical for environmental remediation and enhanced oil recovery; and (iii) more reliable self-assembly onset quantitation for chemically and structurally distinct amphiphiles. These methods could streamline the development of nanotechnologies for a broad range of applications.

pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification.

PubMed

Liu, Ming-Qi; Zeng, Wen-Feng; Fang, Pan; Cao, Wei-Qian; Liu, Chao; Yan, Guo-Quan; Zhang, Yang; Peng, Chao; Wu, Jian-Qiang; Zhang, Xiao-Jin; Tu, Hui-Jun; Chi, Hao; Sun, Rui-Xiang; Cao, Yong; Dong, Meng-Qiu; Jiang, Bi-Yun; Huang, Jiang-Ming; Shen, Hua-Li; Wong, Catherine C L; He, Si-Min; Yang, Peng-Yuan

2017-09-05

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with 15 N/ 13 C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

Diversity and distribution of unicellular opisthokonts along the European coast analysed using high-throughput sequencing.

PubMed

Del Campo, Javier; Mallo, Diego; Massana, Ramon; de Vargas, Colomban; Richards, Thomas A; Ruiz-Trillo, Iñaki

2015-09-01

The opisthokonts are one of the major super groups of eukaryotes. It comprises two major clades: (i) the Metazoa and their unicellular relatives and (ii) the Fungi and their unicellular relatives. There is, however, little knowledge of the role of opisthokont microbes in many natural environments, especially among non-metazoan and non-fungal opisthokonts. Here, we begin to address this gap by analysing high-throughput 18S rDNA and 18S rRNA sequencing data from different European coastal sites, sampled at different size fractions and depths. In particular, we analyse the diversity and abundance of choanoflagellates, filastereans, ichthyosporeans, nucleariids, corallochytreans and their related lineages. Our results show the great diversity of choanoflagellates in coastal waters as well as a relevant representation of the ichthyosporeans and the uncultured marine opisthokonts (MAOP). Furthermore, we describe a new lineage of marine fonticulids (MAFO) that appears to be abundant in sediments. Taken together, our work points to a greater potential ecological role for unicellular opisthokonts than previously appreciated in marine environments, both in water column and sediments, and also provides evidence of novel opisthokont phylogenetic lineages. This study highlights the importance of high-throughput sequencing approaches to unravel the diversity and distribution of both known and novel eukaryotic lineages. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens

PubMed Central

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-01-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue® mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents. PMID:22735701

A high-throughput next-generation sequencing-based method for detecting the mutational fingerprint of carcinogens.

PubMed

Besaratinia, Ahmad; Li, Haiqing; Yoon, Jae-In; Zheng, Albert; Gao, Hanlin; Tommasi, Stella

2012-08-01

Many carcinogens leave a unique mutational fingerprint in the human genome. These mutational fingerprints manifest as specific types of mutations often clustering at certain genomic loci in tumor genomes from carcinogen-exposed individuals. To develop a high-throughput method for detecting the mutational fingerprint of carcinogens, we have devised a cost-, time- and labor-effective strategy, in which the widely used transgenic Big Blue mouse mutation detection assay is made compatible with the Roche/454 Genome Sequencer FLX Titanium next-generation sequencing technology. As proof of principle, we have used this novel method to establish the mutational fingerprints of three prominent carcinogens with varying mutagenic potencies, including sunlight ultraviolet radiation, 4-aminobiphenyl and secondhand smoke that are known to be strong, moderate and weak mutagens, respectively. For verification purposes, we have compared the mutational fingerprints of these carcinogens obtained by our newly developed method with those obtained by parallel analyses using the conventional low-throughput approach, that is, standard mutation detection assay followed by direct DNA sequencing using a capillary DNA sequencer. We demonstrate that this high-throughput next-generation sequencing-based method is highly specific and sensitive to detect the mutational fingerprints of the tested carcinogens. The method is reproducible, and its accuracy is comparable with that of the currently available low-throughput method. In conclusion, this novel method has the potential to move the field of carcinogenesis forward by allowing high-throughput analysis of mutations induced by endogenous and/or exogenous genotoxic agents.

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

PubMed

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

2017-04-04

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

High Throughput Measurement of Extracellular DNA Release and Quantitative NET Formation in Human Neutrophils In Vitro.

PubMed

Sil, Payel; Yoo, Dae-Goon; Floyd, Madison; Gingerich, Aaron; Rada, Balazs

2016-06-18

Neutrophil granulocytes are the most abundant leukocytes in the human blood. Neutrophils are the first to arrive at the site of infection. Neutrophils developed several antimicrobial mechanisms including phagocytosis, degranulation and formation of neutrophil extracellular traps (NETs). NETs consist of a DNA scaffold decorated with histones and several granule markers including myeloperoxidase (MPO) and human neutrophil elastase (HNE). NET release is an active process involving characteristic morphological changes of neutrophils leading to expulsion of their DNA into the extracellular space. NETs are essential to fight microbes, but uncontrolled release of NETs has been associated with several disorders. To learn more about the clinical relevance and the mechanism of NET formation, there is a need to have reliable tools capable of NET quantitation. Here three methods are presented that can assess NET release from human neutrophils in vitro. The first one is a high throughput assay to measure extracellular DNA release from human neutrophils using a membrane impermeable DNA-binding dye. In addition, two other methods are described capable of quantitating NET formation by measuring levels of NET-specific MPO-DNA and HNE-DNA complexes. These microplate-based methods in combination provide great tools to efficiently study the mechanism and regulation of NET formation of human neutrophils.

Comprehensive circular RNA expression profile in radiation-treated HeLa cells and analysis of radioresistance-related circRNAs.

PubMed

Yu, Duo; Li, Yunfeng; Ming, Zhihui; Wang, Hongyong; Dong, Zhuo; Qiu, Ling; Wang, Tiejun

2018-01-01

Cervical cancer is one of the most common cancers in women worldwide. Malignant tumors develop resistance mechanisms and are less sensitive to or do not respond to irradiation. With the development of high-throughput sequencing technologies, circular RNA (circRNA) has been identified in an increasing number of diseases, especially cancers. It has been reported that circRNA can compete with microRNAs (miRNAs) to change the stability or translation of target RNAs, thus regulating gene expression at the transcriptional level. However, the role of circRNAs in cervical cancer and the radioresistance mechanisms of HeLa cells are unknown. The objective of this study is to investigate the role of circRNAs in radioresistance in HeLa cells. High-throughput sequencing and bioinformatics analysis of irradiated and sham-irradiated HeLa cells. The reliability of high-throughput RNA sequencing was validated using quantitative real-time polymerase chain reaction. The most significant circRNA functions and pathways were selected by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A circRNA-miRNA-target gene interaction network was used to find circRNAs associated with radioresistance. Moreover, a protein-protein interaction network was constructed to identify radioresistance-related hub proteins. High-throughput sequencing allowed the identification of 16,893 circRNAs involved in the response of HeLa cells to radiation. Compared with the control group, there were 153 differentially expressed circRNAs, of which 76 were up-regulated and 77 were down-regulated. GO covered three domains: biological process (BP), cellular component (CC) and molecular function (MF). The terms assigned to the BP domain were peptidyl-tyrosine dephosphorylation and regulation of cell migration. The identified CC terms were cell-cell adherens junction, nucleoplasm and cytosol, and the identified MF terms were protein binding and protein tyrosine phosphatase activity. The top five KEGG pathways were MAPK signaling pathway, endocytosis, axon guidance, neurotrophin signaling pathway, and SNARE interactions in vesicular transport. The protein-protein interaction analysis indicated that 19 proteins might be hub proteins. CircRNAs may play a major role in the response to radiation. These findings may improve our understanding of the role of circRNAs in radioresistance in HeLa cells and allow the development of novel therapeutic approaches.

Assessment of the cPAS-based BGISEQ-500 platform for metagenomic sequencing.

PubMed

Fang, Chao; Zhong, Huanzi; Lin, Yuxiang; Chen, Bing; Han, Mo; Ren, Huahui; Lu, Haorong; Luber, Jacob M; Xia, Min; Li, Wangsheng; Stein, Shayna; Xu, Xun; Zhang, Wenwei; Drmanac, Radoje; Wang, Jian; Yang, Huanming; Hammarström, Lennart; Kostic, Aleksandar D; Kristiansen, Karsten; Li, Junhua

2018-03-01

More extensive use of metagenomic shotgun sequencing in microbiome research relies on the development of high-throughput, cost-effective sequencing. Here we present a comprehensive evaluation of the performance of the new high-throughput sequencing platform BGISEQ-500 for metagenomic shotgun sequencing and compare its performance with that of 2 Illumina platforms. Using fecal samples from 20 healthy individuals, we evaluated the intra-platform reproducibility for metagenomic sequencing on the BGISEQ-500 platform in a setup comprising 8 library replicates and 8 sequencing replicates. Cross-platform consistency was evaluated by comparing 20 pairwise replicates on the BGISEQ-500 platform vs the Illumina HiSeq 2000 platform and the Illumina HiSeq 4000 platform. In addition, we compared the performance of the 2 Illumina platforms against each other. By a newly developed overall accuracy quality control method, an average of 82.45 million high-quality reads (96.06% of raw reads) per sample, with 90.56% of bases scoring Q30 and above, was obtained using the BGISEQ-500 platform. Quantitative analyses revealed extremely high reproducibility between BGISEQ-500 intra-platform replicates. Cross-platform replicates differed slightly more than intra-platform replicates, yet a high consistency was observed. Only a low percentage (2.02%-3.25%) of genes exhibited significant differences in relative abundance comparing the BGISEQ-500 and HiSeq platforms, with a bias toward genes with higher GC content being enriched on the HiSeq platforms. Our study provides the first set of performance metrics for human gut metagenomic sequencing data using BGISEQ-500. The high accuracy and technical reproducibility confirm the applicability of the new platform for metagenomic studies, though caution is still warranted when combining metagenomic data from different platforms.

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

PubMed

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

2013-02-01

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

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

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

PubMed

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

2017-04-11

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

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

PubMed

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

2014-01-01

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

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

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.

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.

Epigenetics and Epigenomics of Plants.

PubMed

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

2018-01-23

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

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

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

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

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

A Novel Two-Step Hierarchial Quantitative Structure-Activity Relationship Modeling Workflow for Predicting Acute Toxicity of Chemicals in Rodents

EPA Science Inventory

Background: Accurate prediction of in vivo toxicity from in vitro testing is a challenging problem. Large public–private consortia have been formed with the goal of improving chemical safety assessment by the means of high-throughput screening. Methods and results: A database co...

Use of in Vitro HTS-Derived Concentration-Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity

EPA Science Inventory

Background: Quantitative high-throughput screening (qHTS) assays are increasingly being employed to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in co...

Identifying Environmental Chemicals as Agonists of the Androgen Receptor by Applying a Quantitative High-throughput Screening Platform

EPA Science Inventory

Background: The androgen receptor (AR, NR3C4) is a nuclear receptor whose main function is acting as a transcription factor regulating gene expression for male sexual development and maintaining accessory sexual organ function. It is also a necessary component of female fertility...

Optimization of a resazurin-based microplate assay for large-scale compound screenings against Klebsiella pneumoniae.

PubMed

Kim, Hyung Jun; Jang, Soojin

2018-01-01

A new resazurin-based assay was evaluated and optimized using a microplate (384-well) format for high-throughput screening of antibacterial molecules against Klebsiella pneumoniae . Growth of the bacteria in 384-well plates was more effectively measured and had a > sixfold higher signal-to-background ratio using the resazurin-based assay compared with absorbance measurements at 600 nm. Determination of minimum inhibitory concentrations of the antibiotics revealed that the optimized assay quantitatively measured antibacterial activity of various antibiotics. An edge effect observed in the initial assay was significantly reduced using a 1-h incubation of the bacteria-containing plates at room temperature. There was an approximately 10% decrease in signal variability between the edge and the middle wells along with improvement in the assay robustness ( Z ' = 0.99). This optimized resazurin-based assay is an efficient, inexpensive, and robust assay that can quantitatively measure antibacterial activity using a high-throughput screening system to assess a large number of compounds for discovery of new antibiotics against K. pneumoniae .

A survey of microparasites present in adult migrating Chinook salmon (Oncorhynchus tshawytscha) in south-western British Columbia determined by high-throughput quantitative polymerase chain reaction.

PubMed

Bass, A L; Hinch, S G; Teffer, A K; Patterson, D A; Miller, K M

2017-04-01

Microparasites play an important role in the demography, ecology and evolution of Pacific salmonids. As salmon stocks continue to decline and the impacts of global climate change on fish populations become apparent, a greater understanding of microparasites in wild salmon populations is warranted. We used high-throughput, quantitative PCR (HT-qRT-PCR) to rapidly screen 82 adult Chinook salmon from five geographically or genetically distinct groups (mostly returning to tributaries of the Fraser River) for 45 microparasite taxa. We detected 20 microparasite species, four of which have not previously been documented in Chinook salmon, and four of which have not been previously detected in any salmonids in the Fraser River. Comparisons of microparasite load to blood plasma variables revealed some positive associations between Flavobacterium psychrophilum, Cryptobia salmositica and Ceratonova shasta and physiological indices suggestive of morbidity. We include a comparison of our findings for each microparasite taxa with previous knowledge of its distribution in British Columbia. © 2017 John Wiley & Sons Ltd.

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

PubMed

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

2017-01-01

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

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

PubMed

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

2018-01-18

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

Development of combinatorial chemistry methods for coatings: high-throughput adhesion evaluation and scale-up of combinatorial leads.

PubMed

Potyrailo, Radislav A; Chisholm, Bret J; Morris, William G; Cawse, James N; Flanagan, William P; Hassib, Lamyaa; Molaison, Chris A; Ezbiansky, Karin; Medford, George; Reitz, Hariklia

2003-01-01

Coupling of combinatorial chemistry methods with high-throughput (HT) performance testing and measurements of resulting properties has provided a powerful set of tools for the 10-fold accelerated discovery of new high-performance coating materials for automotive applications. Our approach replaces labor-intensive steps with automated systems for evaluation of adhesion of 8 x 6 arrays of coating elements that are discretely deposited on a single 9 x 12 cm plastic substrate. Performance of coatings is evaluated with respect to their resistance to adhesion loss, because this parameter is one of the primary considerations in end-use automotive applications. Our HT adhesion evaluation provides previously unavailable capabilities of high speed and reproducibility of testing by using a robotic automation, an expanded range of types of tested coatings by using the coating tagging strategy, and an improved quantitation by using high signal-to-noise automatic imaging. Upon testing, the coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Using our HT methodology, we have developed several coatings leads. These HT screening results for the best coating compositions have been validated on the traditional scales of coating formulation and adhesion loss testing. These validation results have confirmed the superb performance of combinatorially developed coatings over conventional coatings on the traditional scale.

Growing trend of CE at the omics level: the frontier of systems biology--an update.

PubMed

Ban, Eunmi; Park, Soo Hyun; Kang, Min-Jung; Lee, Hyun-Jung; Song, Eun Joo; Yoo, Young Sook

2012-01-01

Omics is the study of proteins, peptides, genes, and metabolites in living organisms. Systems biology aims to understand the system through the study of the relationship between elements such as genes and proteins in biological system. Recently, systems biology emerged as the result of the advanced development of high-throughput analysis technologies such as DNA sequencers, DNA arrays, and mass spectrometry for omics studies. Among a number of analytical tools and technologies, CE and CE coupled to MS are promising and relatively rapidly developing tools with the potential to provide qualitative and quantitative analyses of biological molecules. With an emphasis on CE for systems biology, this review summarizes the method developments and applications of CE for the genomic, transcriptomic, proteomic, and metabolomic studies focusing on the drug discovery and disease diagnosis and therapies since 2009. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

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

2016-01-01

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

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation.

PubMed

Chaze, Thibault; Hornez, Louis; Chambon, Christophe; Haddad, Iman; Vinh, Joelle; Peyrat, Jean-Philippe; Benderitter, Marc; Guipaud, Olivier

2013-07-10

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation

PubMed Central

Chaze, Thibault; Hornez, Louis; Chambon, Christophe; Haddad, Iman; Vinh, Joelle; Peyrat, Jean-Philippe; Benderitter, Marc; Guipaud, Olivier

2013-01-01

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes. PMID:28250398

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

PubMed

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

2009-02-01

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

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

PubMed

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

2018-04-27

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

Monitoring the dynamics of syntrophic β-oxidizing bacteria during anaerobic degradation of oleic acid by quantitative PCR.

PubMed

Ziels, Ryan M; Beck, David A C; Martí, Magalí; Gough, Heidi L; Stensel, H David; Svensson, Bo H

2015-04-01

The ecophysiology of long-chain fatty acid-degrading syntrophic β-oxidizing bacteria has been poorly understood due to a lack of quantitative abundance data. Here, TaqMan quantitative PCR (qPCR) assays targeting the 16S rRNA gene of the known mesophilic syntrophic β-oxidizing bacterial genera Syntrophomonas and Syntrophus were developed and validated. Microbial community dynamics were followed using qPCR and Illumina-based high-throughput amplicon sequencing in triplicate methanogenic bioreactors subjected to five consecutive batch feedings of oleic acid. With repeated oleic acid feeding, the initial specific methane production rate significantly increased along with the relative abundances of Syntrophomonas and methanogenic archaea in the bioreactor communities. The novel qPCR assays showed that Syntrophomonas increased from 7 to 31% of the bacterial community 16S rRNA gene concentration, whereas that of Syntrophus decreased from 0.02 to less than 0.005%. High-throughput amplicon sequencing also revealed that Syntrophomonas became the dominant genus within the bioreactor microbiomes. These results suggest that increased specific mineralization rates of oleic acid were attributed to quantitative shifts within the microbial communities toward higher abundances of syntrophic β-oxidizing bacteria and methanogenic archaea. The novel qPCR assays targeting syntrophic β-oxidizing bacteria may thus serve as monitoring tools to indicate the fatty acid β-oxidization potential of anaerobic digester communities. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Increasing the coverage area through relay node deployment in long term evolution advanced cellular networks

NASA Astrophysics Data System (ADS)

Aldhaibani, Jaafar A.; Ahmad, R. B.; Yahya, A.; Azeez, Suzan A.

2015-05-01

Wireless multi-hop relay networks have become very important technologies in mobile communications. These networks ensure high throughput and coverage extension with a low cost. The poor capacity at cell edges is not enough to meet with growing demand of high capacity and throughput irrespective of user's placement in the cellular network. In this paper we propose optimal placement of relay node that provides maximum achievable rate at users and enhances the throughput and coverage at cell edge region. The proposed scheme is based on the outage probability at users and taken on account the interference between nodes. Numerical analyses along with simulation results indicated there are an improvement in capacity for users at the cell edge is 40% increment from all cell capacity.

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

PubMed

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

2012-01-01

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

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

PubMed Central

2012-01-01

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

High-Throughput Quantitative Proteomic Analysis of Dengue Virus Type 2 Infected A549 Cells

PubMed Central

Chiu, Han-Chen; Hannemann, Holger; Heesom, Kate J.; Matthews, David A.; Davidson, Andrew D.

2014-01-01

Disease caused by dengue virus is a global health concern with up to 390 million individuals infected annually worldwide. There are no vaccines or antiviral compounds available to either prevent or treat dengue disease which may be fatal. To increase our understanding of the interaction of dengue virus with the host cell, we analyzed changes in the proteome of human A549 cells in response to dengue virus type 2 infection using stable isotope labelling in cell culture (SILAC) in combination with high-throughput mass spectrometry (MS). Mock and infected A549 cells were fractionated into nuclear and cytoplasmic extracts before analysis to identify proteins that redistribute between cellular compartments during infection and reduce the complexity of the analysis. We identified and quantified 3098 and 2115 proteins in the cytoplasmic and nuclear fractions respectively. Proteins that showed a significant alteration in amount during infection were examined using gene enrichment, pathway and network analysis tools. The analyses revealed that dengue virus infection modulated the amounts of proteins involved in the interferon and unfolded protein responses, lipid metabolism and the cell cycle. The SILAC-MS results were validated for a select number of proteins over a time course of infection by Western blotting and immunofluorescence microscopy. Our study demonstrates for the first time the power of SILAC-MS for identifying and quantifying novel changes in cellular protein amounts in response to dengue virus infection. PMID:24671231

High-Throughput Sequencing and Copy Number Variation Detection Using Formalin Fixed Embedded Tissue in Metastatic Gastric Cancer

PubMed Central

Hong, Min Eui; Do, In-Gu; Kang, So Young; Ha, Sang Yun; Kim, Seung Tae; Park, Se Hoon; Kang, Won Ki; Choi, Min-Gew; Lee, Jun Ho; Sohn, Tae Sung; Bae, Jae Moon; Kim, Sung; Kim, Duk-Hwan; Kim, Kyoung-Mee

2014-01-01

In the era of targeted therapy, mutation profiling of cancer is a crucial aspect of making therapeutic decisions. To characterize cancer at a molecular level, the use of formalin-fixed paraffin-embedded tissue is important. We tested the Ion AmpliSeq Cancer Hotspot Panel v2 and nCounter Copy Number Variation Assay in 89 formalin-fixed paraffin-embedded gastric cancer samples to determine whether they are applicable in archival clinical samples for personalized targeted therapies. We validated the results with Sanger sequencing, real-time quantitative PCR, fluorescence in situ hybridization and immunohistochemistry. Frequently detected somatic mutations included TP53 (28.17%), APC (10.1%), PIK3CA (5.6%), KRAS (4.5%), SMO (3.4%), STK11 (3.4%), CDKN2A (3.4%) and SMAD4 (3.4%). Amplifications of HER2, CCNE1, MYC, KRAS and EGFR genes were observed in 8 (8.9%), 4 (4.5%), 2 (2.2%), 1 (1.1%) and 1 (1.1%) cases, respectively. In the cases with amplification, fluorescence in situ hybridization for HER2 verified gene amplification and immunohistochemistry for HER2, EGFR and CCNE1 verified the overexpression of proteins in tumor cells. In conclusion, we successfully performed semiconductor-based sequencing and nCounter copy number variation analyses in formalin-fixed paraffin-embedded gastric cancer samples. High-throughput screening in archival clinical samples enables faster, more accurate and cost-effective detection of hotspot mutations or amplification in genes. PMID:25372287

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

PubMed

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

2008-04-01

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

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

PubMed

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

2018-05-15

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

High throughput microscopy identifies bisphenol AP, a bisphenol A analog, as a novel AR down-regulator.

PubMed

Stossi, Fabio; Dandekar, Radhika D; Bolt, Michael J; Newberg, Justin Y; Mancini, Maureen G; Kaushik, Akash K; Putluri, Vasanta; Sreekumar, Arun; Mancini, Michael A

2016-03-29

Prostate cancer remains a deadly disease especially when patients become resistant to drugs that target the Androgen Receptor (AR) ligand binding domain. At this stage, patients develop recurring castrate-resistant prostate cancers (CRPCs). Interestingly, CRPC tumors maintain dependency on AR for growth; moreover, in CRPCs, constitutively active AR splice variants (e.g., AR-V7) begin to be expressed at higher levels. These splice variants lack the ligand binding domain and are rendered insensitive to current endocrine therapies. Thus, it is of paramount importance to understand what regulates the expression of AR and its splice variants to identify new therapeutic strategies in CRPCs. Here, we used high throughput microscopy and quantitative image analysis to evaluate effects of selected endocrine disruptors on AR levels in multiple breast and prostate cancer cell lines. Bisphenol AP (BPAP), which is used in chemical and medical industries, was identified as a down-regulator of both full length AR and the AR-V7 splice variant. We validated its activity by performing time-course, dose-response, Western blot and qPCR analyses. BPAP also reduced the percent of cells in S phase, which was accompanied by a ~60% loss in cell numbers and colony formation in anchorage-independent growth assays. Moreover, it affected mitochondria size and cell metabolism. In conclusion, our high content analysis-based screening platform was used to classify the effect of compounds on endogenous ARs, and identified BPAP as being capable of causing AR (both full-length and variants) down-regulation, cell cycle arrest and metabolic alterations in CRPC cell lines.

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

Development and Application of a High Throughput Protein Unfolding Kinetic Assay

PubMed Central

Wang, Qiang; Waterhouse, Nicklas; Feyijinmi, Olusegun; Dominguez, Matthew J.; Martinez, Lisa M.; Sharp, Zoey; Service, Rachel; Bothe, Jameson R.; Stollar, Elliott J.

2016-01-01

The kinetics of folding and unfolding underlie protein stability and quantification of these rates provides important insights into the folding process. Here, we present a simple high throughput protein unfolding kinetic assay using a plate reader that is applicable to the studies of the majority of 2-state folding proteins. We validate the assay by measuring kinetic unfolding data for the SH3 (Src Homology 3) domain from Actin Binding Protein 1 (AbpSH3) and its stabilized mutants. The results of our approach are in excellent agreement with published values. We further combine our kinetic assay with a plate reader equilibrium assay, to obtain indirect estimates of folding rates and use these approaches to characterize an AbpSH3-peptide hybrid. Our high throughput protein unfolding kinetic assays allow accurate screening of libraries of mutants by providing both kinetic and equilibrium measurements and provide a means for in-depth ϕ-value analyses. PMID:26745729

Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity

PubMed Central

Zhong, Qing; Rüschoff, Jan H.; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J.; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J.; Rupp, Niels J.; Fankhauser, Christian; Buhmann, Joachim M.; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A.; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C.; Jochum, Wolfram; Wild, Peter J.

2016-01-01

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility. PMID:27052161

Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

PubMed

Zhong, Qing; Rüschoff, Jan H; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J; Rupp, Niels J; Fankhauser, Christian; Buhmann, Joachim M; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C; Jochum, Wolfram; Wild, Peter J

2016-04-07

Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.

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

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

Guo, Xuejiang; Tang, Keqi

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

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

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

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

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

PubMed

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

2015-01-01

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

Determination of ¹⁵N-incorporation into plant proteins and their absolute quantitation: a new tool to study nitrogen flux dynamics and protein pool sizes elicited by plant-herbivore interactions.

PubMed

Ullmann-Zeunert, Lynn; Muck, Alexander; Wielsch, Natalie; Hufsky, Franziska; Stanton, Mariana A; Bartram, Stefan; Böcker, Sebastian; Baldwin, Ian T; Groten, Karin; Svatoš, Aleš

2012-10-05

Herbivory leads to changes in the allocation of nitrogen among different pools and tissues; however, a detailed quantitative analysis of these changes has been lacking. Here, we demonstrate that a mass spectrometric data-independent acquisition approach known as LC-MS(E), combined with a novel algorithm to quantify heavy atom enrichment in peptides, is able to quantify elicited changes in protein amounts and (15)N flux in a high throughput manner. The reliable identification/quantitation of rabbit phosphorylase b protein spiked into leaf protein extract was achieved. The linear dynamic range, reproducibility of technical and biological replicates, and differences between measured and expected (15)N-incorporation into the small (SSU) and large (LSU) subunits of ribulose-1,5-bisphosphate-carboxylase/oxygenase (RuBisCO) and RuBisCO activase 2 (RCA2) of Nicotiana attenuata plants grown in hydroponic culture at different known concentrations of (15)N-labeled nitrate were used to further evaluate the procedure. The utility of the method for whole-plant studies in ecologically realistic contexts was demonstrated by using (15)N-pulse protocols on plants growing in soil under unknown (15)N-incorporation levels. Additionally, we quantified the amounts of lipoxygenase 2 (LOX2) protein, an enzyme important in antiherbivore defense responses, demonstrating that the approach allows for in-depth quantitative proteomics and (15)N flux analyses of the metabolic dynamics elicited during plant-herbivore interactions.

MBTH: A novel approach to rapid, spectrophotometric quantitation of total algal carbohydrates

DOE PAGES

Van Wychen, Stefanie; Long, William; Black, Stuart K.; ...

2016-11-24

A high-throughput and robust application of the 3-methyl-2-benzothiazolinone hydrazone (MBTH) method was developed for carbohydrate determination in microalgae. The traditional phenol-sulfuric acid method to quantify carbohydrates is strongly affected by algal biochemical components and exhibits a highly variable response to microalgal monosaccharides. We present a novel use of the MBTH method to accurately quantify carbohydrates in hydrolyzate after acid hydrolysis of algal biomass, without a need for neutralization. As a result, the MBTH method demonstrated consistent and sensitive quantitation of algae-specific monosaccharides down to 5 ug mL -1 without interference from other algae acidic hydrolyzate components.

MBTH: A novel approach to rapid, spectrophotometric quantitation of total algal carbohydrates

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

Van Wychen, Stefanie; Long, William; Black, Stuart K.

A high-throughput and robust application of the 3-methyl-2-benzothiazolinone hydrazone (MBTH) method was developed for carbohydrate determination in microalgae. The traditional phenol-sulfuric acid method to quantify carbohydrates is strongly affected by algal biochemical components and exhibits a highly variable response to microalgal monosaccharides. We present a novel use of the MBTH method to accurately quantify carbohydrates in hydrolyzate after acid hydrolysis of algal biomass, without a need for neutralization. As a result, the MBTH method demonstrated consistent and sensitive quantitation of algae-specific monosaccharides down to 5 ug mL -1 without interference from other algae acidic hydrolyzate components.

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

PubMed

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

2017-12-01

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

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

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

Xu, Zhe; Wu, Chaochao; Xie, Fang

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective andmore » robust analytical platform for comprehensive analyses of tissue peptidomes, and which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Additionally, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. In conclusion, peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.« less

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

DOE PAGES

Xu, Zhe; Wu, Chaochao; Xie, Fang; ...

2014-10-28

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective andmore » robust analytical platform for comprehensive analyses of tissue peptidomes, and which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Additionally, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. In conclusion, peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.« less

Sample preconcentration with chemical derivatization in capillary electrophoresis. Capillary as preconcentrator, microreactor and chiral selector for high-throughput metabolite screening.

PubMed

Ptolemy, Adam S; Britz-McKibbin, Philip

2006-02-17

New strategies for integrating sample pretreatment with chemical analyses under a single format is required for rapid, sensitive and enantioselective analyses of low abundance metabolites in complex biological samples. Capillary electrophoresis (CE) offers a unique environment for controlling analyte/reagent band dispersion and electromigration properties using discontinuous electrolyte systems. Recent work in our laboratory towards developing a high-throughput CE platform for low abundance metabolites via on-line sample preconcentration with chemical derivatization (SPCD) is primarily examined in this review, as there have been surprisingly only a few strategies reported in the literature to date. In-capillary sample preconcentration serves to enhance concentration sensitivity via electrokinetic focusing of long sample injection volumes for lower detection limits, whereas chemical derivatization by zone passing is used to expand detectability and selectivity, notably for enantiomeric resolution of metabolites lacking intrinsic chromophores using nanolitre volumes of reagent. Together, on-line SPCD-CE can provide over a 100-fold improvement in concentration sensitivity, shorter total analysis times, reduced sample handling and improved reliability for a variety of amino acid and amino sugar metabolites, which is also amenable to automated high-throughput screening. This review will highlight basic method development and optimization parameters relevant to SPCD-CE, including applications to bacterial metabolite flux and biomarker analyses. Insight into the mechanism of analyte focusing and labeling by SPCD-CE is also discussed, as well as future directions for continued research.

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.

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

NASA Astrophysics Data System (ADS)

Stoltzfus, Caleb; Mikhailov, Alexandr; Rebane, Aleksander

2017-02-01

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

AI-augmented time stretch microscopy

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

A Robotic Platform for Quantitative High-Throughput Screening

PubMed Central

Michael, Sam; Auld, Douglas; Klumpp, Carleen; Jadhav, Ajit; Zheng, Wei; Thorne, Natasha; Austin, Christopher P.; Inglese, James

2008-01-01

Abstract High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation. PMID:19035846

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

USDA-ARS?s Scientific Manuscript database

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

High Throughput Screen to Identify Novel Drugs that Inhibit Prostate Cancer Metastasis

DTIC Science & Technology

2005-10-01

mutants of the SSeCKS α promoter fused to luciferase reporter cassettes (left) were transiently expressed along with pRL-TK- renilla in either P69 or...DU145 cells, and the resulting luciferase activity was normalized to that of renilla activity. Figure 3. Semi quantitative RT-PCR of SSeCKS (either

Toxcast and the Use of Human Relevant In Vitro Exposures: Incorporating High-Throughput Exposure and Toxicity Testing Data for 21st Century Risk Assessments (British Toxicological Society Annual Congress)

EPA Science Inventory

The path for incorporating new approach methods and technologies into quantitative chemical risk assessment poses a diverse set of scientific challenges. These challenges include sufficient coverage of toxicological mechanisms to meaningfully interpret negative test results, dev...

A noninvasive, direct real-time PCR method for sex determination in multiple avian species

USGS Publications Warehouse

Brubaker, Jessica L.; Karouna-Renier, Natalie K.; Chen, Yu; Jenko, Kathryn; Sprague, Daniel T.; Henry, Paula F.P.

2011-01-01

Polymerase chain reaction (PCR)-based methods to determine the sex of birds are well established and have seen few modifications since they were first introduced in the 1990s. Although these methods allowed for sex determination in species that were previously difficult to analyse, they were not conducive to high-throughput analysis because of the laboriousness of DNA extraction and gel electrophoresis. We developed a high-throughput real-time PCR-based method for analysis of sex in birds, which uses noninvasive sample collection and avoids DNA extraction and gel electrophoresis.

High-throughput bioinformatics with the Cyrille2 pipeline system

PubMed Central

Fiers, Mark WEJ; van der Burgt, Ate; Datema, Erwin; de Groot, Joost CW; van Ham, Roeland CHJ

2008-01-01

Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1) a web based, graphical user interface (GUI) that enables a pipeline operator to manage the system; 2) the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3) the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines. PMID:18269742

Peroxisystem: harnessing systems cell biology to study peroxisomes.

PubMed

Schuldiner, Maya; Zalckvar, Einat

2015-04-01

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

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

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

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

2008-05-03

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

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

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

PubMed

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

2016-01-19

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

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

PubMed

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

2018-05-16

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

False positives complicate ancient pathogen identifications using high-throughput shotgun sequencing

PubMed Central

2014-01-01

Background Identification of historic pathogens is challenging since false positives and negatives are a serious risk. Environmental non-pathogenic contaminants are ubiquitous. Furthermore, public genetic databases contain limited information regarding these species. High-throughput sequencing may help reliably detect and identify historic pathogens. Results We shotgun-sequenced 8 16th-century Mixtec individuals from the site of Teposcolula Yucundaa (Oaxaca, Mexico) who are reported to have died from the huey cocoliztli (‘Great Pestilence’ in Nahautl), an unknown disease that decimated native Mexican populations during the Spanish colonial period, in order to identify the pathogen. Comparison of these sequences with those deriving from the surrounding soil and from 4 precontact individuals from the site found a wide variety of contaminant organisms that confounded analyses. Without the comparative sequence data from the precontact individuals and soil, false positives for Yersinia pestis and rickettsiosis could have been reported. Conclusions False positives and negatives remain problematic in ancient DNA analyses despite the application of high-throughput sequencing. Our results suggest that several studies claiming the discovery of ancient pathogens may need further verification. Additionally, true single molecule sequencing’s short read lengths, inability to sequence through DNA lesions, and limited ancient-DNA-specific technical development hinder its application to palaeopathology. PMID:24568097

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

PubMed Central

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

2015-01-01

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

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.

clubber: removing the bioinformatics bottleneck in big data analyses.

PubMed

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2017-06-13

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these "big data" analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber's goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment.

clubber: removing the bioinformatics bottleneck in big data analyses

PubMed Central

Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

2018-01-01

With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment. PMID:28609295

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

PubMed Central

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

2016-01-01

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

Accurate virus quantitation using a Scanning Transmission Electron Microscopy (STEM) detector in a scanning electron microscope.

PubMed

Blancett, Candace D; Fetterer, David P; Koistinen, Keith A; Morazzani, Elaine M; Monninger, Mitchell K; Piper, Ashley E; Kuehl, Kathleen A; Kearney, Brian J; Norris, Sarah L; Rossi, Cynthia A; Glass, Pamela J; Sun, Mei G

2017-10-01

A method for accurate quantitation of virus particles has long been sought, but a perfect method still eludes the scientific community. Electron Microscopy (EM) quantitation is a valuable technique because it provides direct morphology information and counts of all viral particles, whether or not they are infectious. In the past, EM negative stain quantitation methods have been cited as inaccurate, non-reproducible, and with detection limits that were too high to be useful. To improve accuracy and reproducibility, we have developed a method termed Scanning Transmission Electron Microscopy - Virus Quantitation (STEM-VQ), which simplifies sample preparation and uses a high throughput STEM detector in a Scanning Electron Microscope (SEM) coupled with commercially available software. In this paper, we demonstrate STEM-VQ with an alphavirus stock preparation to present the method's accuracy and reproducibility, including a comparison of STEM-VQ to viral plaque assay and the ViroCyt Virus Counter. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Quantitative trait loci mapping of the mouse plasma proteome (pQTL).

PubMed

Holdt, Lesca M; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-02-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

PubMed Central

Holdt, Lesca M.; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

2013-01-01

A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins. PMID:23172855

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

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

PubMed

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

2017-12-01

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

'PACLIMS': a component LIM system for high-throughput functional genomic analysis.

PubMed

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-04-12

Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the approximately 11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors.

'PACLIMS': A component LIM system for high-throughput functional genomic analysis

PubMed Central

Donofrio, Nicole; Rajagopalon, Ravi; Brown, Douglas; Diener, Stephen; Windham, Donald; Nolin, Shelly; Floyd, Anna; Mitchell, Thomas; Galadima, Natalia; Tucker, Sara; Orbach, Marc J; Patel, Gayatri; Farman, Mark; Pampanwar, Vishal; Soderlund, Cari; Lee, Yong-Hwan; Dean, Ralph A

2005-01-01

Background Recent advances in sequencing techniques leading to cost reduction have resulted in the generation of a growing number of sequenced eukaryotic genomes. Computational tools greatly assist in defining open reading frames and assigning tentative annotations. However, gene functions cannot be asserted without biological support through, among other things, mutational analysis. In taking a genome-wide approach to functionally annotate an entire organism, in this application the ~11,000 predicted genes in the rice blast fungus (Magnaporthe grisea), an effective platform for tracking and storing both the biological materials created and the data produced across several participating institutions was required. Results The platform designed, named PACLIMS, was built to support our high throughput pipeline for generating 50,000 random insertion mutants of Magnaporthe grisea. To be a useful tool for materials and data tracking and storage, PACLIMS was designed to be simple to use, modifiable to accommodate refinement of research protocols, and cost-efficient. Data entry into PACLIMS was simplified through the use of barcodes and scanners, thus reducing the potential human error, time constraints, and labor. This platform was designed in concert with our experimental protocol so that it leads the researchers through each step of the process from mutant generation through phenotypic assays, thus ensuring that every mutant produced is handled in an identical manner and all necessary data is captured. Conclusion Many sequenced eukaryotes have reached the point where computational analyses are no longer sufficient and require biological support for their predicted genes. Consequently, there is an increasing need for platforms that support high throughput genome-wide mutational analyses. While PACLIMS was designed specifically for this project, the source and ideas present in its implementation can be used as a model for other high throughput mutational endeavors. PMID:15826298

Investigation of an enhanced resolution triple quadrupole mass spectrometer for high-throughput liquid chromatography/tandem mass spectrometry assays.

PubMed

Yang, Liyu; Amad, Ma'an; Winnik, Witold M; Schoen, Alan E; Schweingruber, Hans; Mylchreest, Iain; Rudewicz, Patrick J

2002-01-01

Triple quadrupole mass spectrometers, when operated in multiple reaction monitoring (MRM) mode, offer a unique combination of sensitivity, specificity, and dynamic range. Consequently, the triple quadrupole is the workhorse for high-throughput quantitation within the pharmaceutical industry. However, in the past, the unit mass resolution of quadrupole instruments has been a limitation when interference from matrix or metabolites cannot be eliminated. With recent advances in instrument design, triple quadrupole instruments now afford mass resolution of less than 0.1 Dalton (Da) full width at half maximum (FWHM). This paper describes the evaluation of an enhanced resolution triple quadrupole mass spectrometer for high-throughput bioanalysis with emphasis on comparison of selectivity, sensitivity, dynamic range, precision, accuracy, and stability under both unit mass (1 Da FWHM) and enhanced (

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

PubMed

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

2015-08-01

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

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

First quantitative high-throughput screen in zebrafish identifies novel pathways for increasing pancreatic β-cell mass

PubMed Central

Wang, Guangliang; Rajpurohit, Surendra K; Delaspre, Fabien; Walker, Steven L; White, David T; Ceasrine, Alexis; Kuruvilla, Rejji; Li, Ruo-jing; Shim, Joong S; Liu, Jun O; Parsons, Michael J; Mumm, Jeff S

2015-01-01

Whole-organism chemical screening can circumvent bottlenecks that impede drug discovery. However, in vivo screens have not attained throughput capacities possible with in vitro assays. We therefore developed a method enabling in vivo high-throughput screening (HTS) in zebrafish, termed automated reporter quantification in vivo (ARQiv). In this study, ARQiv was combined with robotics to fully actualize whole-organism HTS (ARQiv-HTS). In a primary screen, this platform quantified cell-specific fluorescent reporters in >500,000 transgenic zebrafish larvae to identify FDA-approved (Federal Drug Administration) drugs that increased the number of insulin-producing β cells in the pancreas. 24 drugs were confirmed as inducers of endocrine differentiation and/or stimulators of β-cell proliferation. Further, we discovered novel roles for NF-κB signaling in regulating endocrine differentiation and for serotonergic signaling in selectively stimulating β-cell proliferation. These studies demonstrate the power of ARQiv-HTS for drug discovery and provide unique insights into signaling pathways controlling β-cell mass, potential therapeutic targets for treating diabetes. DOI: http://dx.doi.org/10.7554/eLife.08261.001 PMID:26218223

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

PubMed

Sun, T; Chen, L; Zhang, W

2017-01-01

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

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

PubMed

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

2016-05-01

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

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

Quantitative detection of benzoyl peroxide in wheat flour by line-scan macro-scale Raman chemical imaging

USDA-ARS?s Scientific Manuscript database

A high-throughput Raman chemical imaging method was developed for direct inspection of benzoyl peroxide (BPO) mixed in wheat flour. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source in a push-broom Raman imaging system. Hyperspectral Raman images were collecte...

Deep Learning in Label-free Cell Classification

PubMed Central

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

2016-01-01

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

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

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

2018-05-08

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

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

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

PubMed Central

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

2008-01-01

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

Rapid genotyping by low-coverage resequencing to construct genetic linkage maps of fungi: a case study in Lentinula edodes

PubMed Central

2013-01-01

Background Genetic linkage maps are important tools in breeding programmes and quantitative trait analyses. Traditional molecular markers used for genotyping are limited in throughput and efficiency. The advent of next-generation sequencing technologies has facilitated progeny genotyping and genetic linkage map construction in the major grains. However, the applicability of the approach remains untested in the fungal system. Findings Shiitake mushroom, Lentinula edodes, is a basidiomycetous fungus that represents one of the most popular cultivated edible mushrooms. Here, we developed a rapid genotyping method based on low-coverage (~0.5 to 1.5-fold) whole-genome resequencing. We used the approach to genotype 20 single-spore isolates derived from L. edodes strain L54 and constructed the first high-density sequence-based genetic linkage map of L. edodes. The accuracy of the proposed genotyping method was verified experimentally with results from mating compatibility tests and PCR-single-strand conformation polymorphism on a few known genes. The linkage map spanned a total genetic distance of 637.1 cM and contained 13 linkage groups. Two hundred sequence-based markers were placed on the map, with an average marker spacing of 3.4 cM. The accuracy of the map was confirmed by comparing with previous maps the locations of known genes such as matA and matB. Conclusions We used the shiitake mushroom as an example to provide a proof-of-principle that low-coverage resequencing could allow rapid genotyping of basidiospore-derived progenies, which could in turn facilitate the construction of high-density genetic linkage maps of basidiomycetous fungi for quantitative trait analyses and improvement of genome assembly. PMID:23915543

Toxic Cyanobacterial Bloom Triggers in Missisquoi Bay, Lake Champlain, as Determined by Next-Generation Sequencing and Quantitative PCR

PubMed Central

Fortin, Nathalie; Munoz-Ramos, Valentina; Bird, David; Lévesque, Benoît; Whyte, Lyle G.; Greer, Charles W.

2015-01-01

Missisquoi Bay (MB) is a temperate eutrophic freshwater lake that frequently experiences toxic Microcystis-dominated cyanobacterial blooms. Non-point sources are responsible for the high concentrations of phosphorus and nitrogen in the bay. This study combined data from environmental parameters, E. coli counts, high-throughput sequencing of 16S rRNA gene amplicons, quantitative PCR (16S rRNA and mcyD genes) and toxin analyses to identify the main bloom-promoting factors. In 2009, nutrient concentrations correlated with E. coli counts, abundance of total cyanobacterial cells, Microcystis 16S rRNA and mcyD genes and intracellular microcystin. Total and dissolved phosphorus also correlated significantly with rainfall. The major cyanobacterial taxa were members of the orders Chroococcales and Nostocales. The genus Microcystis was the main mcyD-carrier and main microcystin producer. Our results suggested that increasing nutrient concentrations and total nitrogen:total phosphorus (TN:TP) ratios approaching 11:1, coupled with an increase in temperature, promoted Microcystis-dominated toxic blooms. Although the importance of nutrient ratios and absolute concentrations on cyanobacterial and Microcystis dynamics have been documented in other laboratories, an optimum TN:TP ratio for Microcystis dominance has not been previously observed in situ. This observation provides further support that nutrient ratios are an important determinant of species composition in natural phytoplankton assemblages. PMID:25984732

MBTH: A novel approach to rapid, spectrophotometric quantitation of total algal carbohydrates.

PubMed

Van Wychen, Stefanie; Long, William; Black, Stuart K; Laurens, Lieve M L

2017-02-01

A high-throughput and robust application of the 3-methyl-2-benzothiazolinone hydrazone (MBTH) method was developed for carbohydrate determination in microalgae. The traditional phenol-sulfuric acid method to quantify carbohydrates is strongly affected by algal biochemical components and exhibits a highly variable response to microalgal monosaccharides. We present a novel use of the MBTH method to accurately quantify carbohydrates in hydrolyzate after acid hydrolysis of algal biomass, without a need for neutralization. The MBTH method demonstrated consistent and sensitive quantitation of algae-specific monosaccharides down to 5 μg mL -1 without interference from other algae acidic hydrolyzate components. Copyright © 2016 Elsevier Inc. All rights reserved.

Novel method for the high-throughput processing of slides for the comet assay

PubMed Central

Karbaschi, Mahsa; Cooke, Marcus S.

2014-01-01

Single cell gel electrophoresis (the comet assay), continues to gain popularity as a means of assessing DNA damage. However, the assay's low sample throughput and laborious sample workup procedure are limiting factors to its application. “Scoring”, or individually determining DNA damage levels in 50 cells per treatment, is time-consuming, but with the advent of high-throughput scoring, the limitation is now the ability to process significant numbers of comet slides. We have developed a novel method by which multiple slides may be manipulated, and undergo electrophoresis, in batches of 25 rather than individually and, importantly, retains the use of standard microscope comet slides, which are the assay convention. This decreases assay time by 60%, and benefits from an electrophoresis tank with a substantially smaller footprint, and more uniform orientation of gels during electrophoresis. Our high-throughput variant of the comet assay greatly increases the number of samples analysed, decreases assay time, number of individual slide manipulations, reagent requirements and risk of damage to slides. The compact nature of the electrophoresis tank is of particular benefit to laboratories where bench space is at a premium. This novel approach is a significant advance on the current comet assay procedure. PMID:25425241

Novel method for the high-throughput processing of slides for the comet assay.

PubMed

Karbaschi, Mahsa; Cooke, Marcus S

2014-11-26

Single cell gel electrophoresis (the comet assay), continues to gain popularity as a means of assessing DNA damage. However, the assay's low sample throughput and laborious sample workup procedure are limiting factors to its application. "Scoring", or individually determining DNA damage levels in 50 cells per treatment, is time-consuming, but with the advent of high-throughput scoring, the limitation is now the ability to process significant numbers of comet slides. We have developed a novel method by which multiple slides may be manipulated, and undergo electrophoresis, in batches of 25 rather than individually and, importantly, retains the use of standard microscope comet slides, which are the assay convention. This decreases assay time by 60%, and benefits from an electrophoresis tank with a substantially smaller footprint, and more uniform orientation of gels during electrophoresis. Our high-throughput variant of the comet assay greatly increases the number of samples analysed, decreases assay time, number of individual slide manipulations, reagent requirements and risk of damage to slides. The compact nature of the electrophoresis tank is of particular benefit to laboratories where bench space is at a premium. This novel approach is a significant advance on the current comet assay procedure.

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

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

PubMed

Jankowsky, Eckhard; Harris, Michael E

2017-04-15

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

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

Tackling the widespread and critical impact of batch effects in high-throughput data.

PubMed

Leek, Jeffrey T; Scharpf, Robert B; Bravo, Héctor Corrada; Simcha, David; Langmead, Benjamin; Johnson, W Evan; Geman, Donald; Baggerly, Keith; Irizarry, Rafael A

2010-10-01

High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication with such studies is batch effects, which occur because measurements are affected by laboratory conditions, reagent lots and personnel differences. This becomes a major problem when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. Using both published studies and our own analyses, we argue that batch effects (as well as other technical and biological artefacts) are widespread and critical to address. We review experimental and computational approaches for doing so.

Universal and specific quantitative detection of botulinum neurotoxin genes

PubMed Central

2010-01-01

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

Droplet-based microfluidic analysis and screening of single plant cells.

PubMed

Yu, Ziyi; Boehm, Christian R; Hibberd, Julian M; Abell, Chris; Haseloff, Jim; Burgess, Steven J; Reyna-Llorens, Ivan

2018-01-01

Droplet-based microfluidics has been used to facilitate high-throughput analysis of individual prokaryote and mammalian cells. However, there is a scarcity of similar workflows applicable to rapid phenotyping of plant systems where phenotyping analyses typically are time-consuming and low-throughput. We report on-chip encapsulation and analysis of protoplasts isolated from the emergent plant model Marchantia polymorpha at processing rates of >100,000 cells per hour. We use our microfluidic system to quantify the stochastic properties of a heat-inducible promoter across a population of transgenic protoplasts to demonstrate its potential for assessing gene expression activity in response to environmental conditions. We further demonstrate on-chip sorting of droplets containing YFP-expressing protoplasts from wild type cells using dielectrophoresis force. This work opens the door to droplet-based microfluidic analysis of plant cells for applications ranging from high-throughput characterisation of DNA parts to single-cell genomics to selection of rare plant phenotypes.

Quantitative proteomics in teleost fish: insights and challenges for neuroendocrine and neurotoxicology research.

PubMed

Martyniuk, Christopher J; Popesku, Jason T; Chown, Brittany; Denslow, Nancy D; Trudeau, Vance L

2012-05-01

Neuroendocrine systems integrate both extrinsic and intrinsic signals to regulate virtually all aspects of an animal's physiology. In aquatic toxicology, studies have shown that pollutants are capable of disrupting the neuroendocrine system of teleost fish, and many chemicals found in the environment can also have a neurotoxic mode of action. Omics approaches are now used to better understand cell signaling cascades underlying fish neurophysiology and the control of pituitary hormone release, in addition to identifying adverse effects of pollutants in the teleostean central nervous system. For example, both high throughput genomics and proteomic investigations of molecular signaling cascades for both neurotransmitter and nuclear receptor agonists/antagonists have been reported. This review highlights recent studies that have utilized quantitative proteomics methods such as 2D differential in-gel electrophoresis (DIGE) and isobaric tagging for relative and absolute quantitation (iTRAQ) in neuroendocrine regions and uses these examples to demonstrate the challenges of using proteomics in neuroendocrinology and neurotoxicology research. To begin to characterize the teleost neuroproteome, we functionally annotated 623 unique proteins found in the fish hypothalamus and telencephalon. These proteins have roles in biological processes that include synaptic transmission, ATP production, receptor activity, cell structure and integrity, and stress responses. The biological processes most represented by proteins detected in the teleost neuroendocrine brain included transport (8.4%), metabolic process (5.5%), and glycolysis (4.8%). We provide an example of using sub-network enrichment analysis (SNEA) to identify protein networks in the fish hypothalamus in response to dopamine receptor signaling. Dopamine signaling altered the abundance of proteins that are binding partners of microfilaments, integrins, and intermediate filaments, consistent with data suggesting dopaminergic regulation of neuronal stability and structure. Lastly, for fish neuroendocrine studies using both high-throughput genomics and proteomics, we compare gene and protein relationships in the hypothalamus and demonstrate that correlation is often poor for single time point experiments. These studies highlight the need for additional time course analyses to better understand gene-protein relationships and adverse outcome pathways. This is important if both transcriptomics and proteomics are to be used together to investigate neuroendocrine signaling pathways or as bio-monitoring tools in ecotoxicology. Copyright © 2011 Elsevier Inc. All rights reserved.

Single nucleotide polymorphism (SNP) discovery in rainbow trout using restriction site associated DNA (RAD) sequencing of doubled haploids and assessment of polymorphism in a population survey

USDA-ARS?s Scientific Manuscript database

Background: Our goal is to produce a high-throughput SNP genotyping platform for genomic analyses in rainbow trout that will enable fine mapping of QTL, whole genome association studies, genomic selection for improved aquaculture production traits, and genetic analyses of wild populations that aid ...

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

PubMed Central

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

2013-01-01

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

Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing

PubMed Central

Gibson, Joel F.; Shokralla, Shadi; Curry, Colin; Baird, Donald J.; Monk, Wendy A.; King, Ian; Hajibabaei, Mehrdad

2015-01-01

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users. PMID:26488407

Mapping the miRNA interactome by crosslinking ligation and sequencing of hybrids (CLASH)

PubMed Central

Helwak, Aleksandra; Tollervey, David

2014-01-01

RNA-RNA interactions play critical roles in many cellular processes but studying them is difficult and laborious. Here, we describe an experimental procedure, termed crosslinking ligation and sequencing of hybrids (CLASH), which allows high-throughput identification of sites of RNA-RNA interaction. During CLASH, a tagged bait protein is UV crosslinked in vivo to stabilise RNA interactions and purified under denaturing conditions. RNAs associated with the bait protein are partially truncated, and the ends of RNA-duplexes are ligated together. Following linker addition, cDNA library preparation and high-throughput sequencing, the ligated duplexes give rise to chimeric cDNAs, which unambiguously identify RNA-RNA interaction sites independent of bioinformatic predictions. This protocol is optimized for studying miRNA targets bound by Argonaute proteins, but should be easily adapted for other RNA-binding proteins and classes of RNA. The protocol requires around 5 days to complete, excluding the time required for high-throughput sequencing and bioinformatic analyses. PMID:24577361

Synthesis and evaluation of chromogenic and fluorogenic substrates for high-throughput detection of enzymes that hydrolyze inorganic polyphosphate.

PubMed

Hebbard, Carleigh F F; Wang, Yan; Baker, Catherine J; Morrissey, James H

2014-08-11

Inorganic polyphosphates, linear polymers of orthophosphate, occur naturally throughout biology and have many industrial applications. Their biodegradable nature makes them attractive for a multitude of uses, and it would be important to understand how polyphosphates are turned over enzymatically. Studies of inorganic polyphosphatases are, however, hampered by the lack of high-throughput methods for detecting and quantifying rates of polyphosphate degradation. We now report chromogenic and fluorogenic polyphosphate substrates that permit spectrophotometric monitoring of polyphosphate hydrolysis and allow for high-throughput analyses of both endopolyphosphatase and exopolyphosphatase activities, depending on assay configuration. These substrates contain 4-nitrophenol or 4-methylumbelliferone moieties that are covalently attached to the terminal phosphates of polyphosphate via phosphoester linkages formed during reactions mediated by EDAC (1-ethyl-3-(3-(dimethylamino)propyl)carbodiimide). This report identifies Nudt2 as an inorganic polyphosphatase and also adds to the known coupling chemistry for polyphosphates, permitting facile covalent linkage of alcohols with the terminal phosphates of inorganic polyphosphate.

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

PubMed

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

2008-12-01

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

PMAnalyzer: a new web interface for bacterial growth curve analysis.

PubMed

Cuevas, Daniel A; Edwards, Robert A

2017-06-15

Bacterial growth curves are essential representations for characterizing bacteria metabolism within a variety of media compositions. Using high-throughput, spectrophotometers capable of processing tens of 96-well plates, quantitative phenotypic information can be easily integrated into the current data structures that describe a bacterial organism. The PMAnalyzer pipeline performs a growth curve analysis to parameterize the unique features occurring within microtiter wells containing specific growth media sources. We have expanded the pipeline capabilities and provide a user-friendly, online implementation of this automated pipeline. PMAnalyzer version 2.0 provides fast automatic growth curve parameter analysis, growth identification and high resolution figures of sample-replicate growth curves and several statistical analyses. PMAnalyzer v2.0 can be found at https://edwards.sdsu.edu/pmanalyzer/ . Source code for the pipeline can be found on GitHub at https://github.com/dacuevas/PMAnalyzer . Source code for the online implementation can be found on GitHub at https://github.com/dacuevas/PMAnalyzerWeb . dcuevas08@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Fast analysis of triterpenoids in Ganoderma lucidum spores by ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry.

PubMed

Yan, Zhou; Xia, Bing; Qiu, Ming Hua; Li Sheng, Ding; Xu, Hong Xi

2013-11-01

A rapid and reliable method was established for simultaneous determination of main triterpenoids in Ganoderma lucidum spores using ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-TQ-MS). The established method was validated in terms of linearity, sensitivity, precision, accuracy and stability, and was successfully applied to determine the contents of 10 main triterpenoids in different batches of G. lucidum spores. The analysis results showed that moderate levels of triterpenoids were found in G. lucidum spores. In addition, a MS full scan with a daughter ion scan experiment was performed to identify the potential derivatives of triterpenoids present in G. lucidum spores. As a result, a total of 22 triterpenoids from different G. lucidum spores were unequivocally or tentatively identified via comparisons with authentic standards and literatures. This method provides both qualitative and quantitative results without the need for repetitive UPLC-MS analyses, thereby increasing efficiency and productivity, making it suitable for high-throughput applications. Copyright © 2013 John Wiley & Sons, Ltd.

The future of targeted peptidomics.

PubMed

Findeisen, Peter

2013-12-01

Targeted MS is becoming increasingly important for sensitive and specific quantitative detection of proteins and respective PTMs. In this article, Ceglarek et al. [Proteomics Clin. Appl. 2013, 7, 794-801] present an LC-MS-based method for simultaneous quantitation of seven apolipoproteins in serum specimens. The assay fulfills many necessities of routine diagnostic applications, namely, low cost, high throughput, and good reproducibility. We anticipate that validation of new biomarkers will speed up with this technology and the palette of laboratory-based diagnostic tools will hopefully be augmented significantly in the near future. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Establishment of integrated protocols for automated high throughput kinetic chlorophyll fluorescence analyses.

PubMed

Tschiersch, Henning; Junker, Astrid; Meyer, Rhonda C; Altmann, Thomas

2017-01-01

Automated plant phenotyping has been established as a powerful new tool in studying plant growth, development and response to various types of biotic or abiotic stressors. Respective facilities mainly apply non-invasive imaging based methods, which enable the continuous quantification of the dynamics of plant growth and physiology during developmental progression. However, especially for plants of larger size, integrative, automated and high throughput measurements of complex physiological parameters such as photosystem II efficiency determined through kinetic chlorophyll fluorescence analysis remain a challenge. We present the technical installations and the establishment of experimental procedures that allow the integrated high throughput imaging of all commonly determined PSII parameters for small and large plants using kinetic chlorophyll fluorescence imaging systems (FluorCam, PSI) integrated into automated phenotyping facilities (Scanalyzer, LemnaTec). Besides determination of the maximum PSII efficiency, we focused on implementation of high throughput amenable protocols recording PSII operating efficiency (Φ PSII ). Using the presented setup, this parameter is shown to be reproducibly measured in differently sized plants despite the corresponding variation in distance between plants and light source that caused small differences in incident light intensity. Values of Φ PSII obtained with the automated chlorophyll fluorescence imaging setup correlated very well with conventionally determined data using a spot-measuring chlorophyll fluorometer. The established high throughput operating protocols enable the screening of up to 1080 small and 184 large plants per hour, respectively. The application of the implemented high throughput protocols is demonstrated in screening experiments performed with large Arabidopsis and maize populations assessing natural variation in PSII efficiency. The incorporation of imaging systems suitable for kinetic chlorophyll fluorescence analysis leads to a substantial extension of the feature spectrum to be assessed in the presented high throughput automated plant phenotyping platforms, thus enabling the simultaneous assessment of plant architectural and biomass-related traits and their relations to physiological features such as PSII operating efficiency. The implemented high throughput protocols are applicable to a broad spectrum of model and crop plants of different sizes (up to 1.80 m height) and architectures. The deeper understanding of the relation of plant architecture, biomass formation and photosynthetic efficiency has a great potential with respect to crop and yield improvement strategies.

Intellicount: High-Throughput Quantification of Fluorescent Synaptic Protein Puncta by Machine Learning

PubMed Central

Fantuzzo, J. A.; Mirabella, V. R.; Zahn, J. D.

2017-01-01

Abstract Synapse formation analyses can be performed by imaging and quantifying fluorescent signals of synaptic markers. Traditionally, these analyses are done using simple or multiple thresholding and segmentation approaches or by labor-intensive manual analysis by a human observer. Here, we describe Intellicount, a high-throughput, fully-automated synapse quantification program which applies a novel machine learning (ML)-based image processing algorithm to systematically improve region of interest (ROI) identification over simple thresholding techniques. Through processing large datasets from both human and mouse neurons, we demonstrate that this approach allows image processing to proceed independently of carefully set thresholds, thus reducing the need for human intervention. As a result, this method can efficiently and accurately process large image datasets with minimal interaction by the experimenter, making it less prone to bias and less liable to human error. Furthermore, Intellicount is integrated into an intuitive graphical user interface (GUI) that provides a set of valuable features, including automated and multifunctional figure generation, routine statistical analyses, and the ability to run full datasets through nested folders, greatly expediting the data analysis process. PMID:29218324

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2018-06-01

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

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.

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

PubMed Central

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

2015-01-01

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

High throughput secondary electron imaging of organic residues on a graphene surface

NASA Astrophysics Data System (ADS)

Zhou, Yangbo; O'Connell, Robert; Maguire, Pierce; Zhang, Hongzhou

2014-11-01

Surface organic residues inhibit the extraordinary electronic properties of graphene, hindering the development of graphene electronics. However, fundamental understanding of the residue morphology is still absent due to a lack of high-throughput and high-resolution surface characterization methods. Here, we demonstrate that secondary electron (SE) imaging in the scanning electron microscope (SEM) and helium ion microscope (HIM) can provide sub-nanometer information of a graphene surface and reveal the morphology of surface contaminants. Nanoscale polymethyl methacrylate (PMMA) residues are visible in the SE imaging, but their contrast, i.e. the apparent lateral dimension, varies with the imaging conditions. We have demonstrated a quantitative approach to readily obtain the physical size of the surface features regardless of the contrast variation. The fidelity of SE imaging is ultimately determined by the probe size of the primary beam. HIM is thus evaluated to be a superior SE imaging technique in terms of surface sensitivity and image fidelity. A highly efficient method to reveal the residues on a graphene surface has therefore been established.

Universality and predictability in molecular quantitative genetics.

PubMed

Nourmohammad, Armita; Held, Torsten; Lässig, Michael

2013-12-01

Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. Copyright © 2013. Published by Elsevier Ltd.

Understanding RNA-Chromatin Interactions Using Chromatin Isolation by RNA Purification (ChIRP).

PubMed

Chu, Ci; Chang, Howard Y

2016-01-01

ChIRP is a novel and easy-to-use technique for studying long noncoding RNA (lncRNA)-chromatin interactions. RNA and chromatin are cross-linked in vivo using formaldehyde or glutaraldehyde, and purified using biotinylated antisense oligonucleotides that hybridize to the target RNA. Co-precipitated DNA is then purified and analyzed by quantitative PCR (qPCR) or high-throughput sequencing.

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

USDA-ARS?s Scientific Manuscript database

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

Infinium HumanMethylation450 BeadChip

Cancer.gov

The HumanMethylation450 BeadChip offers a unique combination of comprehensive, expert-selected coverage and high throughput at a low price, making it ideal for screening large sample populations such as those used in genome-wide association study cohorts. By providing quantitative methylation measurement at the single-CpG–site level for normal and FFPE samples, this assay offers powerful resolution for understanding epigenetic changes.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2012-12-01

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

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

PubMed

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

2008-09-01

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

Quantitative Analysis for Installation Access Planning at Naval Base San Diego

DTIC Science & Technology

2012-09-01

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

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

PubMed

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

2017-10-23

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-01-01

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

Measurement of replication structures at the nanometer scale using super-resolution light microscopy

PubMed Central

Baddeley, D.; Chagin, V. O.; Schermelleh, L.; Martin, S.; Pombo, A.; Carlton, P. M.; Gahl, A.; Domaing, P.; Birk, U.; Leonhardt, H.; Cremer, C.; Cardoso, M. C.

2010-01-01

DNA replication, similar to other cellular processes, occurs within dynamic macromolecular structures. Any comprehensive understanding ultimately requires quantitative data to establish and test models of genome duplication. We used two different super-resolution light microscopy techniques to directly measure and compare the size and numbers of replication foci in mammalian cells. This analysis showed that replication foci vary in size from 210 nm down to 40 nm. Remarkably, spatially modulated illumination (SMI) and 3D-structured illumination microscopy (3D-SIM) both showed an average size of 125 nm that was conserved throughout S-phase and independent of the labeling method, suggesting a basic unit of genome duplication. Interestingly, the improved optical 3D resolution identified 3- to 5-fold more distinct replication foci than previously reported. These results show that optical nanoscopy techniques enable accurate measurements of cellular structures at a level previously achieved only by electron microscopy and highlight the possibility of high-throughput, multispectral 3D analyses. PMID:19864256

Apoglobin Stability Is the Major Factor Governing both Cell-free and in Vivo Expression of Holomyoglobin*♦

PubMed Central

Samuel, Premila P.; Smith, Lucian P.; Phillips, George N.; Olson, John S.

2015-01-01

Expression levels in animal muscle tissues and in Escherichia coli vary widely for naturally occurring mammalian myoglobins (Mb). To explore this variation, we developed an in vitro transcription and wheat germ extract-based translation assay to examine quantitatively the factors that govern expression of holoMb. We constructed a library of naturally occurring Mbs from two terrestrial and four deep-diving aquatic mammals and three distal histidine mutants designed to enhance apoglobin stability but decrease hemin affinity. A strong linear correlation is observed between cell-free expression levels of holo-metMb variants and their corresponding apoglobin stabilities, which were measured independently by guanidine HCl-induced unfolding titrations using purified proteins. In contrast, there is little dependence of expression on hemin affinity. Our results confirm quantitatively that deep diving mammals have highly stable Mbs that express to higher levels in animal myocytes, E. coli, and the wheat germ cell-free system than Mbs from terrestrial mammals. Our theoretical analyses show that the rate of aggregation of unfolded apoMb is very large, and as a result, the key factor for high level expression of holoMb, and presumably other heme proteins, is an ultra high fraction of folded, native apoglobin that is capable of rapidly binding hemin. This fraction is determined by the overall equilibrium folding constant and not hemin affinity. These results also demonstrate that the cell-free transcription/translation system can be used as a high throughput platform to screen for apoglobin stability without the need to generate large amounts of protein for in vitro unfolding measurements. PMID:26205820

High-Throughput Assessment of Cellular Mechanical Properties.

PubMed

Darling, Eric M; Di Carlo, Dino

2015-01-01

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

High-throughput quantitative luminescence assay of the growth in planta of Pseudomonas syringae chromosomally tagged with Photorhabdus luminescens luxCDABE.

PubMed

Fan, Jun; Crooks, Casey; Lamb, Chris

2008-01-01

Bioluminescent strains of the Arabidopsis thaliana pathogens Pseudomonas syringae pathovar (pv.) tomato and pv. maculicola were made by insertion of the luxCDABE operon from Photorhabdus luminescens into the P. syringae chromosome under the control of a constitutive promoter. Stable integration of luxCDABE did not affect bacterial fitness, growth in planta or disease outcome. Luminescence accurately and reliably reported bacterial growth in infected Arabidopsis leaves both with a fixed inoculum followed over time and with varying inocula assayed at a single time point. Furthermore, the bioluminescence assay could detect a small (1.3-fold) difference in bacterial growth between different plant genotypes with a precision comparable to that of the standard plate assay. Luminescence of luxCDABE-tagged P. syringae allows rapid and convenient quantification of bacterial growth without the tissue extraction, serial dilution, plating and manual scoring involved in standard assays of bacterial growth by colony formation in plate culture of samples from infected tissue. The utility of the bioluminescence assay was illustrated by surveying the 500-fold variation in growth of the universally virulent P. syringae pv. maculicola ES4326 among more than 100 Arabidopsis ecotypes and identification of two quantitative trait loci accounting for 48% and 16%, respectively, of the variance of basal resistance to P. syringae pv. tomato DC3000 in the Col-0 x Fl-1 F(2) population. Luminescence assay of bacteria chromosomally tagged with luxCDABE should greatly facilitate the genetic dissection of quantitative differences in gene-for-gene, basal and acquired disease resistance and other aspects of plant interactions with bacterial pathogens requiring high-throughput assays or large-scale quantitative screens.

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

PubMed

Omer, Travis; Intes, Xavier; Hahn, Juergen

2015-01-01

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

The Xeno-glycomics database (XDB): a relational database of qualitative and quantitative pig glycome repertoire.

PubMed

Park, Hae-Min; Park, Ju-Hyeong; Kim, Yoon-Woo; Kim, Kyoung-Jin; Jeong, Hee-Jin; Jang, Kyoung-Soon; Kim, Byung-Gee; Kim, Yun-Gon

2013-11-15

In recent years, the improvement of mass spectrometry-based glycomics techniques (i.e. highly sensitive, quantitative and high-throughput analytical tools) has enabled us to obtain a large dataset of glycans. Here we present a database named Xeno-glycomics database (XDB) that contains cell- or tissue-specific pig glycomes analyzed with mass spectrometry-based techniques, including a comprehensive pig glycan information on chemical structures, mass values, types and relative quantities. It was designed as a user-friendly web-based interface that allows users to query the database according to pig tissue/cell types or glycan masses. This database will contribute in providing qualitative and quantitative information on glycomes characterized from various pig cells/organs in xenotransplantation and might eventually provide new targets in the α1,3-galactosyltransferase gene-knock out pigs era. The database can be accessed on the web at http://bioinformatics.snu.ac.kr/xdb.

Mass Spectral Characterization and UPLC Quantitation of 3-Deoxyanthocyanidins in Sorghum bicolor Varietals.

PubMed

Stern, Nathan P; Rana, Jatinder; Chandra, Amitabh; Balles, John

2018-01-01

A quantitative ultra-performance LC (UPLC) method was developed and validated to successfully separate, identify, and quantitate the major polyphenolic compounds present in different varieties of sorghum (Sorghum bicolor) feedstock. The method was linear from 3.2 to 320 ppm, with an r2 of 0.99999 when using luteolinidin chloride as the external standard. Method accuracy was determined to be 99.5%, and precision of replicate preparations was less than 1% RSD. Characterization by UPLC-MS determined that the predominant polyphenolic components of the sorghum varietals were 3-deoxyanthocyanidins (3-DXAs). High-throughput screening for 3-DXA identified four unique classes within the sorghum varieties. Certain feedstock varieties have been found to have a high potential to not only be plant-based colorants, but also provide significant amounts of bioactive 3-DXAs, making them of unique interest to the dietary supplement industry.

System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

PubMed

Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

2017-02-03

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

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

DTIC Science & Technology

2006-10-01

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

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

PubMed

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

2015-05-06

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

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

PubMed Central

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

2017-01-01

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

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

PubMed Central

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

2013-01-01

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

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

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

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

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

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

PubMed Central

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

2015-01-01

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

Precise, High-throughput Analysis of Bacterial Growth.

PubMed

Kurokawa, Masaomi; Ying, Bei-Wen

2017-09-19

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

A comprehensive porcine blood transcriptome

USDA-ARS?s Scientific Manuscript database

Blood sample analyses are extensively used in high throughput assays in biomedicine, as well as animal genetics and physiology research. However, the draft quality of the current pig genome (Sscrofa 10.2) is insufficient for accurate interpretation of many of these assays because of incomplete gene ...

Characterization and complete genome sequence of a panicovirus from Bermuda grass by high-throughput sequencing.

PubMed

Tahir, Muhammad N; Lockhart, Ben; Grinstead, Samuel; Mollov, Dimitre

2017-04-01

Bermuda grass samples were examined by transmission electron microscopy and 28-30 nm spherical virus particles were observed. Total RNA from these plants was subjected to high-throughput sequencing (HTS). The nearly full genome sequence of a panicovirus was identified from one HTS scaffold. Sanger sequencing was used to confirm the HTS results and complete the genome sequence of 4404 nt. This virus was provisionally named Bermuda grass latent virus (BGLV). Its predicted open reading frames follow the typical arrangement of the genus Panicovirus. Based on sequence comparisons and phylogenetic analyses BGLV differs from other viruses and therefore taxonomically it is a new member of the genus Panicovirus, family Tombusviridae.

Emerging Technologies for Gut Microbiome Research

PubMed Central

Arnold, Jason W.; Roach, Jeffrey; Azcarate-Peril, M. Andrea

2016-01-01

Understanding the importance of the gut microbiome on modulation of host health has become a subject of great interest for researchers across disciplines. As an intrinsically multidisciplinary field, microbiome research has been able to reap the benefits of technological advancements in systems and synthetic biology, biomaterials engineering, and traditional microbiology. Gut microbiome research has been revolutionized by high-throughput sequencing technology, permitting compositional and functional analyses that were previously an unrealistic undertaking. Emerging technologies including engineered organoids derived from human stem cells, high-throughput culturing, and microfluidics assays allowing for the introduction of novel approaches will improve the efficiency and quality of microbiome research. Here, we will discuss emerging technologies and their potential impact on gut microbiome studies. PMID:27426971

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

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.

Modeling Steroidogenesis Disruption Using High-Throughput ...

EPA Pesticide Factsheets

Environmental chemicals can elicit endocrine disruption by altering steroid hormone biosynthesis and metabolism (steroidogenesis) causing adverse reproductive and developmental effects. Historically, a lack of assays resulted in few chemicals having been evaluated for effects on steroidogenesis. The steroidogenic pathway is a series of hydroxylation and dehydrogenation steps carried out by CYP450 and hydroxysteroid dehydrogenase enzymes, yet the only enzyme in the pathway for which a high-throughput screening (HTS) assay has been developed is aromatase (CYP19A1), responsible for the aromatization of androgens to estrogens. Recently, the ToxCast HTS program adapted the OECD validated H295R steroidogenesis assay using human adrenocortical carcinoma cells into a high-throughput model to quantitatively assess the concentration-dependent (0.003-100 µM) effects of chemicals on 10 steroid hormones including progestagens, androgens, estrogens and glucocorticoids. These results, in combination with two CYP19A1 inhibition assays, comprise a large dataset amenable to clustering approaches supporting the identification and characterization of putative mechanisms of action (pMOA) for steroidogenesis disruption. In total, 514 chemicals were tested in all CYP19A1 and steroidogenesis assays. 216 chemicals were identified as CYP19A1 inhibitors in at least one CYP19A1 assay. 208 of these chemicals also altered hormone levels in the H295R assay, suggesting 96% sensitivity in the

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

PubMed Central

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

2015-01-01

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

Development of a high-throughput screen to detect inhibitors of TRPS1 sumoylation.

PubMed

Brandt, Martin; Szewczuk, Lawrence M; Zhang, Hong; Hong, Xuan; McCormick, Patricia M; Lewis, Tia S; Graham, Taylor I; Hung, Sunny T; Harper-Jones, Amber D; Kerrigan, John J; Wang, Da-Yuan; Dul, Edward; Hou, Wangfang; Ho, Thau F; Meek, Thomas D; Cheung, Mui H; Johanson, Kyung O; Jones, Christopher S; Schwartz, Benjamin; Kumar, Sanjay; Oliff, Allen I; Kirkpatrick, Robert B

2013-06-01

Small ubiquitin-like modifier (SUMO) belongs to the family of ubiquitin-like proteins (Ubls) that can be reversibly conjugated to target-specific lysines on substrate proteins. Although covalently sumoylated products are readily detectible in gel-based assays, there has been little progress toward the development of robust quantitative sumoylation assay formats for the evaluation of large compound libraries. In an effort to identify inhibitors of ubiquitin carrier protein 9 (Ubc9)-dependent sumoylation, a high-throughput fluorescence polarization assay was developed, which allows detection of Lys-1201 sumoylation, corresponding to the major site of functional sumoylation within the transcriptional repressor trichorhino-phalangeal syndrome type I protein (TRPS1). A minimal hexapeptide substrate peptide, TMR-VVK₁₂₀₁TEK, was used in this assay format to afford high-throughput screening of the GlaxoSmithKline diversity compound collection. A total of 728 hits were confirmed but no specific noncovalent inhibitors of Ubc9 dependent trans-sumoylation were found. However, several diaminopyrimidine compounds were identified as inhibitors in the assay with IC₅₀ values of 12.5 μM. These were further characterized to be competent substrates which were subject to sumoylation by SUMO-Ubc9 and which were competitive with the sumoylation of the TRPS1 peptide substrates.

Sources of PCR-induced distortions in high-throughput sequencing data sets

PubMed Central

Kebschull, Justus M.; Zador, Anthony M.

2015-01-01

PCR permits the exponential and sequence-specific amplification of DNA, even from minute starting quantities. PCR is a fundamental step in preparing DNA samples for high-throughput sequencing. However, there are errors associated with PCR-mediated amplification. Here we examine the effects of four important sources of error—bias, stochasticity, template switches and polymerase errors—on sequence representation in low-input next-generation sequencing libraries. We designed a pool of diverse PCR amplicons with a defined structure, and then used Illumina sequencing to search for signatures of each process. We further developed quantitative models for each process, and compared predictions of these models to our experimental data. We find that PCR stochasticity is the major force skewing sequence representation after amplification of a pool of unique DNA amplicons. Polymerase errors become very common in later cycles of PCR but have little impact on the overall sequence distribution as they are confined to small copy numbers. PCR template switches are rare and confined to low copy numbers. Our results provide a theoretical basis for removing distortions from high-throughput sequencing data. In addition, our findings on PCR stochasticity will have particular relevance to quantification of results from single cell sequencing, in which sequences are represented by only one or a few molecules. PMID:26187991

Fragment screening for drug leads by weak affinity chromatography (WAC-MS).

PubMed

Ohlson, Sten; Duong-Thi, Minh-Dao

2018-02-23

Fragment-based drug discovery is an important tool for design of small molecule hit-to-lead compounds against various biological targets. Several approved drugs have been derived from an initial fragment screen and many such candidates are in various stages of clinical trials. Finding fragment hits, that are suitable for optimisation by medicinal chemists, is still a challenge as the binding between the small fragment and its target is weak in the range of mM to µM of K d and irrelevant non-specific interactions are abundant in this area of transient interactions. Fortunately, there are methods that can study weak interactions quite efficiently of which NMR, surface plasmon resonance (SPR) and X-ray crystallography are the most prominent. Now, a new technology based on zonal affinity chromatography, weak affinity chromatography (WAC), has been introduced which has remedied many of the problems with other technologies. By combining WAC with mass spectrometry (WAC-MS), it is a powerful tool to identify binders quantitatively in terms of affinity and kinetics either from fragment libraries or from complex mixtures of biological extracts. As WAC-MS can be multiplexed by analysing mixtures of fragments (20-100 fragments) in one sample, this approach yields high throughput, where a whole library of e.g. >2000 fragments can be analysed quantitatively within a day. WAC-MS is easy to perform, where the robustness and quality of HPLC is fully utilized. This review will highlight the rationale behind the application of WAC-MS for fragment screening in drug discovery. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Application of High-Throughput In Vitro Assays for Risk-Based ...

EPA Pesticide Factsheets

Multiple drivers shape the types of human-health assessments performed on chemicals by U.S. EPA resulting in chemical assessments are “fit-for-purpose” ranging from prioritization for further testing to full risk assessments. Layered on top of the diverse assessment needs are the resource intensive nature of traditional toxicological studies used to test chemicals and the lack of toxicity information on many chemicals. To address these challenges, the Agency initiated the ToxCast program to screen thousands of chemicals across hundreds of high-throughput screening assays in concentrations-response format. One of the findings of the project has been that the majority of chemicals interact with multiple biological targets within a narrow concentration range and the extent of interactions increases rapidly near the concentration causing cytotoxicity. This means that application of high-throughput in vitro assays to chemical assessments will need to identify both the relative selectivity at chemicals interact with biological targets and the concentration at which these interactions perturb signaling pathways. The integrated analyses will be used to both define a point-of-departure for comparison with human exposure estimates and identify which chemicals may benefit from further studies in a mode-of-action or adverse outcome pathway framework. The application of new technologies in a risk-based, tiered manner provides flexibility in matching throughput and cos

High-throughput electrical characterization for robust overlay lithography control

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

20150325 - Application of High-Throughput In Vitro Assays for ...

EPA Pesticide Factsheets

Multiple drivers shape the types of human-health assessments performed on chemicals by U.S. EPA resulting in chemical assessments are “fit-for-purpose” ranging from prioritization for further testing to full risk assessments. Layered on top of the diverse assessment needs are the resource intensive nature of traditional toxicological studies used to test chemicals and the lack of toxicity information on many chemicals. To address these challenges, the Agency initiated the ToxCast program to screen thousands of chemicals across hundreds of high-throughput screening assays in concentrations-response format. One of the findings of the project has been that the majority of chemicals interact with multiple biological targets within a narrow concentration range and the extent of interactions increases rapidly near the concentration causing cytotoxicity. This means that application of high-throughput in vitro assays to chemical assessments will need to identify both the relative selectivity at chemicals interact with biological targets and the concentration at which these interactions perturb signaling pathways. The integrated analyses will be used to both define a point-of-departure for comparison with human exposure estimates and identify which chemicals may benefit from further studies in a mode-of-action or adverse outcome pathway framework. The application of new technologies in a risk-based, tiered manner provides flexibility in matching throughput and cos

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.

OpenMS - A platform for reproducible analysis of mass spectrometry data.

PubMed

Pfeuffer, Julianus; Sachsenberg, Timo; Alka, Oliver; Walzer, Mathias; Fillbrunn, Alexander; Nilse, Lars; Schilling, Oliver; Reinert, Knut; Kohlbacher, Oliver

2017-11-10

In recent years, several mass spectrometry-based omics technologies emerged to investigate qualitative and quantitative changes within thousands of biologically active components such as proteins, lipids and metabolites. The research enabled through these methods potentially contributes to the diagnosis and pathophysiology of human diseases as well as to the clarification of structures and interactions between biomolecules. Simultaneously, technological advances in the field of mass spectrometry leading to an ever increasing amount of data, demand high standards in efficiency, accuracy and reproducibility of potential analysis software. This article presents the current state and ongoing developments in OpenMS, a versatile open-source framework aimed at enabling reproducible analyses of high-throughput mass spectrometry data. It provides implementations of frequently occurring processing operations on MS data through a clean application programming interface in C++ and Python. A collection of 185 tools and ready-made workflows for typical MS-based experiments enable convenient analyses for non-developers and facilitate reproducible research without losing flexibility. OpenMS will continue to increase its ease of use for developers as well as users with improved continuous integration/deployment strategies, regular trainings with updated training materials and multiple sources of support. The active developer community ensures the incorporation of new features to support state of the art research. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Automation of the ELISpot assay for high-throughput detection of antigen-specific T-cell responses.

PubMed

Almeida, Coral-Ann M; Roberts, Steven G; Laird, Rebecca; McKinnon, Elizabeth; Ahmed, Imran; Pfafferott, Katja; Turley, Joanne; Keane, Niamh M; Lucas, Andrew; Rushton, Ben; Chopra, Abha; Mallal, Simon; John, Mina

2009-05-15

The enzyme linked immunospot (ELISpot) assay is a fundamental tool in cellular immunology, providing both quantitative and qualitative information on cellular cytokine responses to defined antigens. It enables the comprehensive screening of patient derived peripheral blood mononuclear cells to reveal the antigenic restriction of T-cell responses and is an emerging technique in clinical laboratory investigation of certain infectious diseases. As with all cellular-based assays, the final results of the assay are dependent on a number of technical variables that may impact precision if not highly standardised between operators. When studies that are large scale or using multiple antigens are set up manually, these assays may be labour intensive, have many manual handling steps, are subject to data and sample integrity failure and may show large inter-operator variability. Here we describe the successful automated performance of the interferon (IFN)-gamma ELISpot assay from cell counting through to electronic capture of cytokine quantitation and present the results of a comparison between automated and manual performance of the ELISpot assay. The mean number of spot forming units enumerated by both methods for limiting dilutions of CMV, EBV and influenza (CEF)-derived peptides in six healthy individuals were highly correlated (r>0.83, p<0.05). The precision results from the automated system compared favourably with the manual ELISpot and further ensured electronic tracking, increased through-put and reduced turnaround time.

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

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

PubMed

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

2006-08-01

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

New High Throughput Methods to Estimate Chemical ...

EPA Pesticide Factsheets

EPA has made many recent advances in high throughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing and screening chemicals. A recent report by the National Research Council of the National Academies, Exposure Science in the 21st Century: A Vision and a Strategy (NRC 2012) laid out a number of applications in chemical evaluation of both toxicity and risk in critical need of quantitative exposure predictions, including screening and prioritization of chemicals for targeted toxicity testing, focused exposure assessments or monitoring studies, and quantification of population vulnerability. Despite these significant needs, for the majority of chemicals (e.g. non-pesticide environmental compounds) there are no or limited estimates of exposure. For example, exposure estimates exist for only 7% of the ToxCast Phase II chemical list. In addition, the data required for generating exposure estimates for large numbers of chemicals is severely lacking (Egeghy et al. 2012). This SAP reviewed the use of EPA's ExpoCast model to rapidly estimate potential chemical exposures for prioritization and screening purposes. The focus was on bounded chemical exposure values for people and the environment for the Endocrine Disruptor Screening Program (EDSP) Universe of Chemicals. In addition to exposure, the SAP

Deep Learning in Label-free Cell Classification

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

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

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

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

Isotonic Regression Based-Method in Quantitative High-Throughput Screenings for Genotoxicity

PubMed Central

Fujii, Yosuke; Narita, Takeo; Tice, Raymond Richard; Takeda, Shunich

2015-01-01

Quantitative high-throughput screenings (qHTSs) for genotoxicity are conducted as part of comprehensive toxicology screening projects. The most widely used method is to compare the dose-response data of a wild-type and DNA repair gene knockout mutants, using model-fitting to the Hill equation (HE). However, this method performs poorly when the observed viability does not fit the equation well, as frequently happens in qHTS. More capable methods must be developed for qHTS where large data variations are unavoidable. In this study, we applied an isotonic regression (IR) method and compared its performance with HE under multiple data conditions. When dose-response data were suitable to draw HE curves with upper and lower asymptotes and experimental random errors were small, HE was better than IR, but when random errors were big, there was no difference between HE and IR. However, when the drawn curves did not have two asymptotes, IR showed better performance (p < 0.05, exact paired Wilcoxon test) with higher specificity (65% in HE vs. 96% in IR). In summary, IR performed similarly to HE when dose-response data were optimal, whereas IR clearly performed better in suboptimal conditions. These findings indicate that IR would be useful in qHTS for comparing dose-response data. PMID:26673567

Deep Learning in Label-free Cell Classification

DOE PAGES

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

2016-03-15

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

Quantitative High-Throughput Identification of Drugs as Modulators of Human Constitutive Androstane Receptor

PubMed Central

Lynch, Caitlin; Zhao, Jinghua; Huang, Ruili; Xiao, Jingwei; Li, Linhao; Heyward, Scott; Xia, Menghang; Wang, Hongbing

2015-01-01

The constitutive androstane receptor (CAR, NR1I3) plays a key role in governing the transcription of numerous hepatic genes that involve xenobiotic metabolism/clearance, energy homeostasis, and cell proliferation. Thus, identification of novel human CAR (hCAR) modulators may not only enhance early prediction of drug-drug interactions but also offer potentially novel therapeutics for diseases such as metabolic disorders and cancer. In this study, we have generated a double stable cell line expressing both hCAR and a CYP2B6-driven luciferase reporter for quantitative high-throughput screening (qHTS) of hCAR modulators. Approximately 2800 compounds from the NIH Chemical Genomics Center Pharmaceutical Collection were screened employing both the activation and deactivation modes of the qHTS. Activators (115) and deactivators (152) of hCAR were identified from the primary qHTS, among which 10 agonists and 10 antagonists were further validated in the physiologically relevant human primary hepatocytes for compound-mediated hCAR nuclear translocation and target gene expression. Collectively, our results reveal that hCAR modulators can be efficiently identified through this newly established qHTS assay. Profiling drug collections for hCAR activity would facilitate the prediction of metabolism-based drug-drug interactions, and may lead to the identification of potential novel therapeutics. PMID:25993555

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

PubMed Central

Sulyok, Michael; Liu, Xingzhong; Rao, Mingyong

2016-01-01

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

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

PubMed Central

2015-01-01

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

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

PubMed

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

2016-09-01

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

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

PubMed

Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

2018-05-17

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Condor-COPASI: high-throughput computing for biochemical networks

PubMed Central

2012-01-01

Background Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. Results We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays. Conclusions Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage. PMID:22834945

Single nucleotide polymorphism discovery in rainbow trout by deep sequencing of a reduced representation library.

PubMed

Sánchez, Cecilia Castaño; Smith, Timothy P L; Wiedmann, Ralph T; Vallejo, Roger L; Salem, Mohamed; Yao, Jianbo; Rexroad, Caird E

2009-11-25

To enhance capabilities for genomic analyses in rainbow trout, such as genomic selection, a large suite of polymorphic markers that are amenable to high-throughput genotyping protocols must be identified. Expressed Sequence Tags (ESTs) have been used for single nucleotide polymorphism (SNP) discovery in salmonids. In those strategies, the salmonid semi-tetraploid genomes often led to assemblies of paralogous sequences and therefore resulted in a high rate of false positive SNP identification. Sequencing genomic DNA using primers identified from ESTs proved to be an effective but time consuming methodology of SNP identification in rainbow trout, therefore not suitable for high throughput SNP discovery. In this study, we employed a high-throughput strategy that used pyrosequencing technology to generate data from a reduced representation library constructed with genomic DNA pooled from 96 unrelated rainbow trout that represent the National Center for Cool and Cold Water Aquaculture (NCCCWA) broodstock population. The reduced representation library consisted of 440 bp fragments resulting from complete digestion with the restriction enzyme HaeIII; sequencing produced 2,000,000 reads providing an average 6 fold coverage of the estimated 150,000 unique genomic restriction fragments (300,000 fragment ends). Three independent data analyses identified 22,022 to 47,128 putative SNPs on 13,140 to 24,627 independent contigs. A set of 384 putative SNPs, randomly selected from the sets produced by the three analyses were genotyped on individual fish to determine the validation rate of putative SNPs among analyses, distinguish apparent SNPs that actually represent paralogous loci in the tetraploid genome, examine Mendelian segregation, and place the validated SNPs on the rainbow trout linkage map. Approximately 48% (183) of the putative SNPs were validated; 167 markers were successfully incorporated into the rainbow trout linkage map. In addition, 2% of the sequences from the validated markers were associated with rainbow trout transcripts. The use of reduced representation libraries and pyrosequencing technology proved to be an effective strategy for the discovery of a high number of putative SNPs in rainbow trout; however, modifications to the technique to decrease the false discovery rate resulting from the evolutionary recent genome duplication would be desirable.

Rigorous quantitative elemental microanalysis by scanning electron microscopy/energy dispersive x-ray spectrometry (SEM/EDS) with spectrum processing by NIST DTSA-II

NASA Astrophysics Data System (ADS)

Newbury, Dale E.; Ritchie, Nicholas W. M.

2014-09-01

Quantitative electron-excited x-ray microanalysis by scanning electron microscopy/silicon drift detector energy dispersive x-ray spectrometry (SEM/SDD-EDS) is capable of achieving high accuracy and high precision equivalent to that of the high spectral resolution wavelength dispersive x-ray spectrometer even when severe peak interference occurs. The throughput of the SDD-EDS enables high count spectra to be measured that are stable in calibration and resolution (peak shape) across the full deadtime range. With this high spectral stability, multiple linear least squares peak fitting is successful for separating overlapping peaks and spectral background. Careful specimen preparation is necessary to remove topography on unknowns and standards. The standards-based matrix correction procedure embedded in the NIST DTSA-II software engine returns quantitative results supported by a complete error budget, including estimates of the uncertainties from measurement statistics and from the physical basis of the matrix corrections. NIST DTSA-II is available free for Java-platforms at: http://www.cstl.nist.gov/div837/837.02/epq/dtsa2/index.html).

Bimodal imprint chips for peptide screening: integration of high-throughput sequencing by MS and affinity analyses by surface plasmon resonance imaging.

PubMed

Wang, Weizhi; Li, Menglin; Wei, Zewen; Wang, Zihua; Bu, Xiangli; Lai, Wenjia; Yang, Shu; Gong, He; Zheng, Hui; Wang, Yuqiao; Liu, Ying; Li, Qin; Fang, Qiaojun; Hu, Zhiyuan

2014-04-15

Peptide probes and drugs have widespread applications in disease diagnostics and therapy. The demand for peptides ligands with high affinity and high specificity toward various targets has surged in the biomedical field in recent years. The traditional peptide screening procedure involves selection, sequencing, and characterization steps, and each step is manual and tedious. Herein, we developed a bimodal imprint microarray system to embrace the whole peptide screening process. Silver-sputtered silicon chip fabricated with microwell array can trap and pattern the candidate peptide beads in a one-well-one-bead manner. Peptides on beads were photocleaved in situ. A portion of the peptide in each well was transferred to a gold-coated chip to print the peptide array for high-throughput affinity analyses by surface plasmon resonance imaging (SPRi), and the peptide left in the silver-sputtered chip was ready for in situ single bead sequencing by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Using the bimodal imprint chip system, affinity peptides toward AHA were efficiently screened out from the 7 × 10(4) peptide library. The method provides a solution for high efficiency peptide screening.

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

DOE PAGES

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

2015-07-08

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

Web-based visual analysis for high-throughput genomics

PubMed Central

2013-01-01

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

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

PubMed

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

2014-02-07

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

High-throughput sequencing reveals unprecedented diversities of Aspergillus species in outdoor air.

PubMed

Lee, S; An, C; Xu, S; Lee, S; Yamamoto, N

2016-09-01

This study used the Illumina MiSeq to analyse compositions and diversities of Aspergillus species in outdoor air. The seasonal air samplings were performed at two locations in Seoul, South Korea. The results showed the relative abundances of all Aspergillus species combined ranging from 0·20 to 18% and from 0·19 to 21% based on the number of the internal transcribed spacer 1 (ITS1) and β-tubulin (BenA) gene sequences respectively. Aspergillus fumigatus was the most dominant species with the mean relative abundances of 1·2 and 5·5% based on the number of the ITS1 and BenA sequences respectively. A total of 29 Aspergillus species were detected and identified down to the species rank, among which nine species were known opportunistic pathogens. Remarkably, eight of the nine pathogenic species were detected by either one of the two markers, suggesting the need of using multiple markers and/or primer pairs when the assessments are made based on the high-throughput sequencing. Due to diversity of species within the genus Aspergillus, the high-throughput sequencing was useful to characterize their compositions and diversities in outdoor air, which are thought to be difficult to be accurately characterized by conventional culture and/or Sanger sequencing-based techniques. Aspergillus is a diverse genus of fungi with more than 300 species reported in literature. Aspergillus is important since some species are known allergens and opportunistic human pathogens. Traditionally, growth-dependent methods have been used to detect Aspergillus species in air. However, these methods are limited in the number of isolates that can be analysed for their identities, resulting in inaccurate characterizations of Aspergillus diversities. This study used the high-throughput sequencing to explore Aspergillus diversities in outdoor, which are thought to be difficult to be accurately characterized by traditional growth-dependent techniques. © 2016 The Society for Applied Microbiology.

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

PubMed

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

2010-04-15

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

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

PubMed Central

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

2010-01-01

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

High-Throughput 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.

Real-time quantitative fluorescence measurement of microscale cell culture analog systems

NASA Astrophysics Data System (ADS)

Oh, Taek-il; Kim, Donghyun; Tatosian, Daniel; Sung, Jong Hwan; Shuler, Michael

2007-02-01

A microscale cell culture analog (μCCA) is a cell-based lab-on-a-chip assay that, as an animal surrogate, is applied to pharmacological studies for toxicology tests. A μCCA typically comprises multiple chambers and microfluidics that connect the chambers, which represent animal organs and blood flow to mimic animal metabolism more realistically. A μCCA is expected to provide a tool for high-throughput drug discovery. Previously, a portable fluorescence detection system was investigated for a single μCCA device in real-time. In this study, we present a fluorescence-based imaging system that provides quantitative real-time data of the metabolic interactions in μCCAs with an emphasis on measuring multiple μCCA samples simultaneously for high-throughput screening. The detection system is based on discrete optics components, with a high-power LED and a charge-coupled device (CCD) camera as a light source and a detector, for monitoring cellular status on the chambers of each μCCA sample. Multiple samples are characterized mechanically on a motorized linear stage, which is fully-automated. Each μCCA sample has four chambers, where cell lines MES-SA/DX- 5, and MES-SA (tumor cells of human uterus) have been cultured. All cell-lines have been transfected to express the fusion protein H2B-GFP, which is a human histone protein fused at the amino terminus to EGFP. As a model cytotoxic drug, 10 μM doxorubicin (DOX) was used. Real-time quantitative data of the intensity loss of enhanced green fluorescent protein (EGFP) during cell death of target cells have been collected over several minutes to 40 hours. Design issues and improvements are also discussed.

Deterministic Migration-Based Separation of White Blood Cells.

PubMed

Kim, Byeongyeon; Choi, Young Joon; Seo, Hyekyung; Shin, Eui-Cheol; Choi, Sungyoung

2016-10-01

Functional and phenotypic analyses of peripheral white blood cells provide useful clinical information. However, separation of white blood cells from peripheral blood requires a time-consuming, inconvenient process and thus analyses of separated white blood cells are limited in clinical settings. To overcome this limitation, a microfluidic separation platform is developed to enable deterministic migration of white blood cells, directing the cells into designated positions according to a ridge pattern. The platform uses slant ridge structures on the channel top to induce the deterministic migration, which allows efficient and high-throughput separation of white blood cells from unprocessed whole blood. The extent of the deterministic migration under various rheological conditions is explored, enabling highly efficient migration of white blood cells in whole blood and achieving high-throughput separation of the cells (processing 1 mL of whole blood less than 7 min). In the separated cell population, the composition of lymphocyte subpopulations is well preserved, and T cells secrete cytokines without any functional impairment. On the basis of the results, this microfluidic platform is a promising tool for the rapid enrichment of white blood cells, and it is useful for functional and phenotypic analyses of peripheral white blood cells. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Pretreatment drug resistance in a large countrywide Ethiopian HIV-1C cohort: a comparison of Sanger and high-throughput sequencing.

PubMed

Telele, Nigus Fikrie; Kalu, Amare Worku; Gebre-Selassie, Solomon; Fekade, Daniel; Abdurahman, Samir; Marrone, Gaetano; Neogi, Ujjwal; Tegbaru, Belete; Sönnerborg, Anders

2018-05-15

Baseline plasma samples of 490 randomly selected antiretroviral therapy (ART) naïve patients from seven hospitals participating in the first nationwide Ethiopian HIV-1 cohort were analysed for surveillance drug resistance mutations (sDRM) by population based Sanger sequencing (PBSS). Also next generation sequencing (NGS) was used in a subset of 109 baseline samples of patients. Treatment outcome after 6- and 12-months was assessed by on-treatment (OT) and intention-to-treat (ITT) analyses. Transmitted drug resistance (TDR) was detected in 3.9% (18/461) of successfully sequenced samples by PBSS. However, NGS detected sDRM more often (24%; 26/109) than PBSS (6%; 7/109) (p = 0.0001) and major integrase strand transfer inhibitors (INSTI) DRMs were also found in minor viral variants from five patients. Patients with sDRM had more frequent treatment failure in both OT and ITT analyses. The high rate of TDR by NGS and the identification of preexisting INSTI DRMs in minor wild-type HIV-1 subtype C viral variants infected Ethiopian patients underscores the importance of TDR surveillance in low- and middle-income countries and shows added value of high-throughput NGS in such studies.

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

PubMed

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

2017-05-05

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

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

PubMed Central

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

2017-01-01

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

A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

PubMed

Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J

2014-02-01

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

Advances in analytical methodologies to guide bioprocess engineering for bio-therapeutics.

PubMed

Saldova, Radka; Kilcoyne, Michelle; Stöckmann, Henning; Millán Martín, Silvia; Lewis, Amanda M; Tuite, Catherine M E; Gerlach, Jared Q; Le Berre, Marie; Borys, Michael C; Li, Zheng Jian; Abu-Absi, Nicholas R; Leister, Kirk; Joshi, Lokesh; Rudd, Pauline M

2017-03-01

This study was performed to monitor the glycoform distribution of a recombinant antibody fusion protein expressed in CHO cells over the course of fed-batch bioreactor runs using high-throughput methods to accurately determine the glycosylation status of the cell culture and its product. Three different bioreactors running similar conditions were analysed at the same five time-points using the advanced methods described here. N-glycans from cell and secreted glycoproteins from CHO cells were analysed by HILIC-UPLC and MS, and the total glycosylation (both N- and O-linked glycans) secreted from the CHO cells were analysed by lectin microarrays. Cell glycoproteins contained mostly high mannose type N-linked glycans with some complex glycans; sialic acid was α-(2,3)-linked, galactose β-(1,4)-linked, with core fucose. Glycans attached to secreted glycoproteins were mostly complex with sialic acid α-(2,3)-linked, galactose β-(1,4)-linked, with mostly core fucose. There were no significant differences noted among the bioreactors in either the cell pellets or supernatants using the HILIC-UPLC method and only minor differences at the early time-points of days 1 and 3 by the lectin microarray method. In comparing different time-points, significant decreases in sialylation and branching with time were observed for glycans attached to both cell and secreted glycoproteins. Additionally, there was a significant decrease over time in high mannose type N-glycans from the cell glycoproteins. A combination of the complementary methods HILIC-UPLC and lectin microarrays could provide a powerful and rapid HTP profiling tool capable of yielding qualitative and quantitative data for a defined biopharmaceutical process, which would allow valuable near 'real-time' monitoring of the biopharmaceutical product. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-11-01

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

Development of a tiered screening strategy for a molecular-initiating event: thyroperoxidase inhibition (SOT)

EPA Science Inventory

Adverse outcome pathway (AOP) analyses illustrate that some molecular-initiating events (MIEs) for thyroid disruption, including thyroperoxidase (TPO) inhibition, are not evaluated by current ToxCast/Tox21 high-throughput screening (HTS) assays. A novel HTS assay for TPO inhibiti...

Biofilm-Growing Bacteria Involved in the Corrosion of Concrete Wastewater Pipes: Protocols for Comparative Metagenomic Analyses

EPA Science Inventory

Advances in high-throughput next-generation sequencing (NGS) technology for direct sequencing of environmental DNA (i.e. shotgun metagenomics) is transforming the field of microbiology. NGS technologies are now regularly being applied in comparative metagenomic studies, which pr...

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.

The Secret Life of RNA: Lessons from Emerging Methodologies.

PubMed

Medioni, Caroline; Besse, Florence

2018-01-01

The last past decade has witnessed a revolution in our appreciation of transcriptome complexity and regulation. This remarkable expansion in our knowledge largely originates from the advent of high-throughput methodologies, and the consecutive discovery that up to 90% of eukaryotic genomes are transcribed, thus generating an unanticipated large range of noncoding RNAs (Hangauer et al., 15(4):112, 2014). Besides leading to the identification of new noncoding RNA species, transcriptome-wide studies have uncovered novel layers of posttranscriptional regulatory mechanisms controlling RNA processing, maturation or translation, and each contributing to the precise and dynamic regulation of gene expression. Remarkably, the development of systems-level studies has been accompanied by tremendous progress in the visualization of individual RNA molecules in single cells, such that it is now possible to image RNA species with a single-molecule resolution from birth to translation or decay. Monitoring quantitatively, with unprecedented spatiotemporal resolution, the fate of individual molecules has been key to understanding the molecular mechanisms underlying the different steps of RNA regulation. This has also revealed biologically relevant, intracellular and intercellular heterogeneities in RNA distribution or regulation. More recently, the convergence of imaging and high-throughput technologies has led to the emergence of spatially resolved transcriptomic techniques that provide a means to perform large-scale analyses while preserving spatial information. By generating transcriptome-wide data on single-cell RNA content, or even subcellular RNA distribution, these methodologies are opening avenues to a wide range of network-level studies at the cell and organ-level, and promise to strongly improve disease diagnostic and treatment.In this introductory chapter, we highlight how recently developed technologies aiming at detecting and visualizing RNA molecules have contributed to the emergence of entirely new research fields, and to dramatic progress in our understanding of gene expression regulation.

Antibody Epitope Analysis to Investigate Folded Structure, Allosteric Conformation, and Evolutionary Lineage of Proteins.

PubMed

Wong, Sienna; Jin, J-P

2017-01-01

Study of folded structure of proteins provides insights into their biological functions, conformational dynamics and molecular evolution. Current methods of elucidating folded structure of proteins are laborious, low-throughput, and constrained by various limitations. Arising from these methods is the need for a sensitive, quantitative, rapid and high-throughput method not only analysing the folded structure of proteins, but also to monitor dynamic changes under physiological or experimental conditions. In this focused review, we outline the foundation and limitations of current protein structure-determination methods prior to discussing the advantages of an emerging antibody epitope analysis for applications in structural, conformational and evolutionary studies of proteins. We discuss the application of this method using representative examples in monitoring allosteric conformation of regulatory proteins and the determination of the evolutionary lineage of related proteins and protein isoforms. The versatility of the method described herein is validated by the ability to modulate a variety of assay parameters to meet the needs of the user in order to monitor protein conformation. Furthermore, the assay has been used to clarify the lineage of troponin isoforms beyond what has been depicted by sequence homology alone, demonstrating the nonlinear evolutionary relationship between primary structure and tertiary structure of proteins. The antibody epitope analysis method is a highly adaptable technique of protein conformation elucidation, which can be easily applied without the need for specialized equipment or technical expertise. When applied in a systematic and strategic manner, this method has the potential to reveal novel and biomedically meaningful information for structure-function relationship and evolutionary lineage of proteins. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Unbiased Characterization of Anopheles Mosquito Blood Meals by Targeted High-Throughput Sequencing

PubMed Central

Logue, Kyle; Keven, John Bosco; Cannon, Matthew V.; Reimer, Lisa; Siba, Peter; Walker, Edward D.; Zimmerman, Peter A.; Serre, David

2016-01-01

Understanding mosquito host choice is important for assessing vector competence or identifying disease reservoirs. Unfortunately, the availability of an unbiased method for comprehensively evaluating the composition of insect blood meals is very limited, as most current molecular assays only test for the presence of a few pre-selected species. These approaches also have limited ability to identify the presence of multiple mammalian hosts in a single blood meal. Here, we describe a novel high-throughput sequencing method that enables analysis of 96 mosquitoes simultaneously and provides a comprehensive and quantitative perspective on the composition of each blood meal. We validated in silico that universal primers targeting the mammalian mitochondrial 16S ribosomal RNA genes (16S rRNA) should amplify more than 95% of the mammalian 16S rRNA sequences present in the NCBI nucleotide database. We applied this method to 442 female Anopheles punctulatus s. l. mosquitoes collected in Papua New Guinea (PNG). While human (52.9%), dog (15.8%) and pig (29.2%) were the most common hosts identified in our study, we also detected DNA from mice, one marsupial species and two bat species. Our analyses also revealed that 16.3% of the mosquitoes fed on more than one host. Analysis of the human mitochondrial hypervariable region I in 102 human blood meals showed that 5 (4.9%) of the mosquitoes unambiguously fed on more than one person. Overall, analysis of PNG mosquitoes illustrates the potential of this approach to identify unsuspected hosts and characterize mixed blood meals, and shows how this approach can be adapted to evaluate inter-individual variations among human blood meals. Furthermore, this approach can be applied to any disease-transmitting arthropod and can be easily customized to investigate non-mammalian host sources. PMID:26963245

Quantitation and Identification of Intact Major Milk Proteins for High-Throughput LC-ESI-Q-TOF MS Analyses.

PubMed

Vincent, Delphine; Elkins, Aaron; Condina, Mark R; Ezernieks, Vilnis; Rochfort, Simone

2016-01-01

Cow's milk is an important source of proteins in human nutrition. On average, cow's milk contains 3.5% protein. The most abundant proteins in bovine milk are caseins and some of the whey proteins, namely beta-lactoglobulin, alpha-lactalbumin, and serum albumin. A number of allelic variants and post-translationally modified forms of these proteins have been identified. Their occurrence varies with breed, individuality, stage of lactation, and health and nutritional status of the animal. It is therefore essential to have reliable methods of detection and quantitation of these proteins. Traditionally, major milk proteins are quantified using liquid chromatography (LC) and ultra violet detection method. However, as these protein variants co-elute to some degree, another dimension of separation is beneficial to accurately measure their amounts. Mass spectrometry (MS) offers such a tool. In this study, we tested several RP-HPLC and MS parameters to optimise the analysis of intact bovine proteins from milk. From our tests, we developed an optimum method that includes a 20-28-40% phase B gradient with 0.02% TFA in both mobile phases, at 0.2 mL/min flow rate, using 75°C for the C8 column temperature, scanning every 3 sec over a 600-3000 m/z window. The optimisations were performed using external standards commercially purchased for which ionisation efficiency, linearity of calibration, LOD, LOQ, sensitivity, selectivity, precision, reproducibility, and mass accuracy were demonstrated. From the MS analysis, we can use extracted ion chromatograms (EICs) of specific ion series of known proteins and integrate peaks at defined retention time (RT) window for quantitation purposes. This optimum quantitative method was successfully applied to two bulk milk samples from different breeds, Holstein-Friesian and Jersey, to assess differences in protein variant levels.

Improved Protein Arrays for Quantitative Systems Analysis of the Dynamics of Signaling Pathway Interactions

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

Yang, Chin-Rang

Astronauts and workers in nuclear plants who repeatedly exposed to low doses of ionizing radiation (IR, <10 cGy) are likely to incur specific changes in signal transduction and gene expression in various tissues of their body. Remarkable advances in high throughput genomics and proteomics technologies enable researchers to broaden their focus from examining single gene/protein kinetics to better understanding global gene/protein expression profiling and biological pathway analyses, namely Systems Biology. An ultimate goal of systems biology is to develop dynamic mathematical models of interacting biological systems capable of simulating living systems in a computer. This Glue Grant is to complementmore » Dr. Boothman’s existing DOE grant (No. DE-FG02-06ER64186) entitled “The IGF1/IGF-1R-MAPK-Secretory Clusterin (sCLU) Pathway: Mediator of a Low Dose IR-Inducible Bystander Effect” to develop sensitive and quantitative proteomic technology that suitable for low dose radiobiology researches. An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states for systems biology modeling is presented. The signals are amplified by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots and show the good linearity that is impossible for the signals of HRP-amplification. Therefore this improved protein array technology is suitable to detect weak responses of low dose radiation. Software is developed to facilitate the quantitative readout of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways.« less

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

PubMed

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

2006-10-16

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

Pathway analyses and understanding disease associations

PubMed Central

Liu, Yu; Chance, Mark R

2013-01-01

High throughput technologies have been applied to investigate the underlying mechanisms of complex diseases, identify disease-associations and help to improve treatment. However it is challenging to derive biological insight from conventional single gene based analysis of “omics” data from high throughput experiments due to sample and patient heterogeneity. To address these challenges, many novel pathway and network based approaches were developed to integrate various “omics” data, such as gene expression, copy number alteration, Genome Wide Association Studies, and interaction data. This review will cover recent methodological developments in pathway analysis for the detection of dysregulated interactions and disease-associated subnetworks, prioritization of candidate disease genes, and disease classifications. For each application, we will also discuss the associated challenges and potential future directions. PMID:24319650

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

PubMed

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

2016-07-01

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

Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format

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

Pinzon, NM; Aukema, KG; Gralnick, JA

A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone productionmore » as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. IMPORTANCE In recent years, there has been renewed interest in advanced biofuel sources such as bacterial hydrocarbon production. Previous studies used solvent extraction of bacterial cultures followed by gas chromatography-mass spectrometry (GC-MS) to detect and quantify ketones and hydrocarbons (Beller HR, Goh EB, Keasling JD, Appl. Environ. Microbiol. 76: 1212-1223, 2010; Sukovich DJ, Seffernick JL, Richman JE, Gralnick JA, Wackett LP, Appl. Environ. Microbiol. 76: 3850-3862, 2010). While these analyses are powerful and accurate, their labor-intensive nature makes them intractable to high-throughput screening; therefore, methods for rapid identification of bacterial strains that are overproducing hydrocarbons are needed. The use of high-throughput evaluation of bacterial and algal hydrophobic molecule production via Nile red fluorescence from lipids and esters was extended in this study to include hydrocarbons and ketones. This work demonstrated accurate, high-throughput detection of high-level bacterial long-chain ketone and hydrocarbon production by screening for increased fluorescence of the hydrophobic dye Nile red.« less

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

PubMed Central

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

2016-01-01

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

Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues.

PubMed

Mangeot-Peter, Lauralie; Legay, Sylvain; Hausman, Jean-Francois; Esposito, Sergio; Guerriero, Gea

2016-09-15

Gene expression profiling via quantitative real-time PCR is a robust technique widely used in the life sciences to compare gene expression patterns in, e.g., different tissues, growth conditions, or after specific treatments. In the field of plant science, real-time PCR is the gold standard to study the dynamics of gene expression and is used to validate the results generated with high throughput techniques, e.g., RNA-Seq. An accurate relative quantification of gene expression relies on the identification of appropriate reference genes, that need to be determined for each experimental set-up used and plant tissue studied. Here, we identify suitable reference genes for expression profiling in stems of textile hemp (Cannabis sativa L.), whose tissues (isolated bast fibres and core) are characterized by remarkable differences in cell wall composition. We additionally validate the reference genes by analysing the expression of putative candidates involved in the non-oxidative phase of the pentose phosphate pathway and in the first step of the shikimate pathway. The goal is to describe the possible regulation pattern of some genes involved in the provision of the precursors needed for lignin biosynthesis in the different hemp stem tissues. The results here shown are useful to design future studies focused on gene expression analyses in hemp.

Unbiased profiling of volatile organic compounds in the headspace of Allium plants using an in-tube extraction device.

PubMed

Kusano, Miyako; Kobayashi, Makoto; Iizuka, Yumiko; Fukushima, Atsushi; Saito, Kazuki

2016-02-29

Plants produce and emit important volatile organic compounds (VOCs), which have an essential role in biotic and abiotic stress responses and in plant-plant and plant-insect interactions. In order to study the bouquets from plants qualitatively and quantitatively, a comprehensive, analytical method yielding reproducible results is required. We applied in-tube extraction (ITEX) and solid-phase microextraction (SPME) for studying the emissions of Allium plants. The collected HS samples were analyzed by gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS), and the results were subjected to multivariate analysis. In case of ITEX-method Allium cultivars released more than 300 VOCs, out of which we provisionally identified 50 volatiles. We also used the VOC profiles of Allium samples to discriminate among groups of A. fistulosum, A. chinense (rakkyo), and A. tuberosum (Oriental garlic). As we found 12 metabolite peaks including dipropyl disulphide with significant changes in A. chinense and A. tuberosum when compared to the control cultivar, these metabolite peaks can be used for chemotaxonomic classification of A. chinense, tuberosum, and A. fistulosum. Compared to SPME-method our ITEX-based VOC profiling technique contributes to automatic and reproducible analyses. Hence, it can be applied to high-throughput analyses such as metabolite profiling.

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

PubMed

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

2017-10-01

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

High-throughput electrical measurement and microfluidic sorting of semiconductor nanowires.

PubMed

Akin, Cevat; Feldman, Leonard C; Durand, Corentin; Hus, Saban M; Li, An-Ping; Hui, Ho Yee; Filler, Michael A; Yi, Jingang; Shan, Jerry W

2016-05-24

Existing nanowire electrical characterization tools not only are expensive and require sophisticated facilities, but are far too slow to enable statistical characterization of highly variable samples. They are also generally not compatible with further sorting and processing of nanowires. Here, we demonstrate a high-throughput, solution-based electro-orientation-spectroscopy (EOS) method, which is capable of automated electrical characterization of individual nanowires by direct optical visualization of their alignment behavior under spatially uniform electric fields of different frequencies. We demonstrate that EOS can quantitatively characterize the electrical conductivities of nanowires over a 6-order-of-magnitude range (10(-5) to 10 S m(-1), corresponding to typical carrier densities of 10(10)-10(16) cm(-3)), with different fluids used to suspend the nanowires. By implementing EOS in a simple microfluidic device, continuous electrical characterization is achieved, and the sorting of nanowires is demonstrated as a proof-of-concept. With measurement speeds two orders of magnitude faster than direct-contact methods, the automated EOS instrument enables for the first time the statistical characterization of highly variable 1D nanomaterials.

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.

In silico study of in vitro GPCR assays by QSAR modeling

EPA Science Inventory

The U.S. EPA is screening thousands of chemicals of environmental interest in hundreds of in vitro high-throughput screening (HTS) assays (the ToxCast program). One goal is to prioritize chemicals for more detailed analyses based on activity in molecular initiating events (MIE) o...

Aggregating Data for Computational Toxicology Applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System

EPA Science Inventory

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for...

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource

USDA-ARS?s Scientific Manuscript database

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic mode...

Single-Cell Based Quantitative Assay of Chromosome Transmission Fidelity

PubMed Central

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

2015-01-01

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

Single-Cell Based Quantitative Assay of Chromosome Transmission Fidelity.

PubMed

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

2015-03-30

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

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

PubMed Central

Schaufele, Fred

2013-01-01

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

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

PubMed

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

2015-01-01

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

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

PubMed

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

2012-10-21

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

Advances in Quantitative Proteomics of Microbes and Microbial Communities

NASA Astrophysics Data System (ADS)

Waldbauer, J.; Zhang, L.; Rizzo, A. I.

2015-12-01

Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

High-Throughput Characterization of Vapor-Deposited Organic Glasses

NASA Astrophysics Data System (ADS)

Dalal, Shakeel S.

Glasses are non-equilibrium materials which on short timescales behave like solids, and on long timescales betray their liquid-like structure. The most common way of preparing a glass is to cool the liquid faster than it can structurally rearrange. Until recently, most preparation schemes for a glass were considered to result in materials with undifferentiable structure and properties. This thesis utilizes a particular preparation method, physical vapor deposition, in order to prepare glasses of organic molecules with properties otherwise considered to be unobtainable. The glasses are characterized using spectroscopic ellipsometry, both as a dilatometric technique and as a reporter of molecular packing. The results reported here develop ellipsometry as a dilatometric technique on a pair of model glass formers, alpha,alpha,beta-trisnaphthylbenzene and indomethacin. It is found that the molecular orientation, as measured by birefringence, can be tuned by changing the substrate temperature during the deposition. In order to efficiently characterize the properties of vapor-deposited indomethacin as a function of substrate temperature, a high-throughput method is developed to capture the entire interesting range of substrate temperatures in just a few experiments. This high-throughput method is then leveraged to describe molecular mobility in vapor-deposited indomethacin. It is also used to demonstrate that the behavior of organic semiconducting molecules agrees with indomethacin quantitatively, and this agreement has implications for emerging technologies such as light-emitting diodes, photovoltaics and thin-film transistors made from organic molecules.

Accelerating evaluation of converged lattice thermal conductivity

NASA Astrophysics Data System (ADS)

Qin, Guangzhao; Hu, Ming

2018-01-01

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

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

PubMed Central

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

2011-01-01

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

Utility of High Throughput Screening Techniques to Predict Stability of Monoclonal Antibody Formulations During Early Stage Development.

PubMed

Goldberg, Deborah S; Lewus, Rachael A; Esfandiary, Reza; Farkas, David C; Mody, Neil; Day, Katrina J; Mallik, Priyanka; Tracka, Malgorzata B; Sealey, Smita K; Samra, Hardeep S

2017-08-01

Selecting optimal formulation conditions for monoclonal antibodies for first time in human clinical trials is challenging due to short timelines and reliance on predictive assays to ensure product quality and adequate long-term stability. Accelerated stability studies are considered to be the gold standard for excipient screening, but they are relatively low throughput and time consuming. High throughput screening (HTS) techniques allow for large amounts of data to be collected quickly and easily, and can be used to screen solution conditions for early formulation development. The utility of using accelerated stability compared to HTS techniques (differential scanning light scattering and differential scanning fluorescence) for early formulation screening was evaluated along with the impact of excipients of various types on aggregation of monoclonal antibodies from multiple IgG subtypes. The excipient rank order using quantitative HTS measures was found to correlate with accelerated stability aggregation rate ranking for only 33% (by differential scanning fluorescence) to 42% (by differential scanning light scattering) of the antibodies tested, due to the high intrinsic stability and minimal impact of excipients on aggregation rates and HTS data. Also explored was a case study of employing a platform formulation instead of broader formulation screening for early formulation development. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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

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

Leung, Elo; Huang, Amy; Cadag, Eithon

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

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

DOE PAGES

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

2016-01-20

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

Generalized empirical Bayesian methods for discovery of differential data in high-throughput biology.

PubMed

Hardcastle, Thomas J

2016-01-15

High-throughput data are now commonplace in biological research. Rapidly changing technologies and application mean that novel methods for detecting differential behaviour that account for a 'large P, small n' setting are required at an increasing rate. The development of such methods is, in general, being done on an ad hoc basis, requiring further development cycles and a lack of standardization between analyses. We present here a generalized method for identifying differential behaviour within high-throughput biological data through empirical Bayesian methods. This approach is based on our baySeq algorithm for identification of differential expression in RNA-seq data based on a negative binomial distribution, and in paired data based on a beta-binomial distribution. Here we show how the same empirical Bayesian approach can be applied to any parametric distribution, removing the need for lengthy development of novel methods for differently distributed data. Comparisons with existing methods developed to address specific problems in high-throughput biological data show that these generic methods can achieve equivalent or better performance. A number of enhancements to the basic algorithm are also presented to increase flexibility and reduce computational costs. The methods are implemented in the R baySeq (v2) package, available on Bioconductor http://www.bioconductor.org/packages/release/bioc/html/baySeq.html. tjh48@cam.ac.uk 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.

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

PubMed

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

2018-01-01

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

Rhizoslides: paper-based growth system for non-destructive, high throughput phenotyping of root development by means of image analysis.

PubMed

Le Marié, Chantal; Kirchgessner, Norbert; Marschall, Daniela; Walter, Achim; Hund, Andreas

2014-01-01

A quantitative characterization of root system architecture is currently being attempted for various reasons. Non-destructive, rapid analyses of root system architecture are difficult to perform due to the hidden nature of the root. Hence, improved methods to measure root architecture are necessary to support knowledge-based plant breeding and to analyse root growth responses to environmental changes. Here, we report on the development of a novel method to reveal growth and architecture of maize root systems. The method is based on the cultivation of different root types within several layers of two-dimensional, large (50 × 60 cm) plates (rhizoslides). A central plexiglass screen stabilizes the system and is covered on both sides with germination paper providing water and nutrients for the developing root, followed by a transparent cover foil to prevent the roots from falling dry and to stabilize the system. The embryonic roots grow hidden between a Plexiglas surface and paper, whereas crown roots grow visible between paper and the transparent cover. Long cultivation with good image quality up to 20 days (four fully developed leaves) was enhanced by suppressing fungi with a fungicide. Based on hyperspectral microscopy imaging, the quality of different germination papers was tested and three provided sufficient contrast to distinguish between roots and background (segmentation). Illumination, image acquisition and segmentation were optimised to facilitate efficient root image analysis. Several software packages were evaluated with regard to their precision and the time investment needed to measure root system architecture. The software 'Smart Root' allowed precise evaluation of root development but needed substantial user interference. 'GiaRoots' provided the best segmentation method for batch processing in combination with a good analysis of global root characteristics but overestimated root length due to thinning artefacts. 'WhinRhizo' offered the most rapid and precise evaluation of root lengths in diameter classes, but had weaknesses with respect to image segmentation and analysis of root system architecture. A new technique has been established for non-destructive root growth studies and quantification of architectural traits beyond seedlings stages. However, automation of the scanning process and appropriate software remains the bottleneck for high throughput analysis.

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

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

PubMed

Bell, Steven E J; Sirimuthu, Narayana M S

2004-11-01

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

Quantitative mass spectrometric analysis of glycoproteins combined with enrichment methods.

PubMed

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

2015-01-01

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

Optical properties of acute kidney injury measured by quantitative phase imaging

PubMed Central

Ban, Sungbea; Min, Eunjung; Baek, Songyee; Kwon, Hyug Moo; Popescu, Gabriel

2018-01-01

The diagnosis of acute kidney disease (AKI) has been examined mainly by histology, immunohistochemistry and western blot. Though these approaches are widely accepted in the field, it has an inherent limitation due to the lack of high-throughput and quantitative information. For a better understanding of prognosis in AKI, we present a new approach using quantitative phase imaging combined with a wide-field scanning platform. Through the phase-delay information from the tissue, we were able to predict a stage of AKI based on various optical properties such as light scattering coefficient and anisotropy. These optical parameters quantify the deterioration process of the AKI model of tissue. Our device would be a very useful tool when it is required to deliver fast feedback of tissue pathology or when diseases are related to mechanical properties such as fibrosis. PMID:29541494

A Novel High Throughput Assay for Anthelmintic Drug Screening and Resistance Diagnosis by Real-Time Monitoring of Parasite Motility

PubMed Central

Smout, Michael J.; Kotze, Andrew C.; McCarthy, James S.; Loukas, Alex

2010-01-01

Background Helminth parasites cause untold morbidity and mortality to billions of people and livestock. Anthelmintic drugs are available but resistance is a problem in livestock parasites, and is a looming threat for human helminths. Testing the efficacy of available anthelmintic drugs and development of new drugs is hindered by the lack of objective high-throughput screening methods. Currently, drug effect is assessed by observing motility or development of parasites using laborious, subjective, low-throughput methods. Methodology/Principal Findings Here we describe a novel application for a real-time cell monitoring device (xCELLigence) that can simply and objectively assess anthelmintic effects by measuring parasite motility in real time in a fully automated high-throughput fashion. We quantitatively assessed motility and determined real time IC50 values of different anthelmintic drugs against several developmental stages of major helminth pathogens of humans and livestock, including larval Haemonchus contortus and Strongyloides ratti, and adult hookworms and blood flukes. The assay enabled quantification of the onset of egg hatching in real time, and the impact of drugs on hatch rate, as well as discriminating between the effects of drugs on motility of drug-susceptible and –resistant isolates of H. contortus. Conclusions/Significance Our findings indicate that this technique will be suitable for discovery and development of new anthelmintic drugs as well as for detection of phenotypic resistance to existing drugs for the majority of helminths and other pathogens where motility is a measure of pathogen viability. The method is also amenable to use for other purposes where motility is assessed, such as gene silencing or antibody-mediated killing. PMID:21103363

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.

High-throughput ocular artifact reduction in multichannel electroencephalography (EEG) using component subspace projection.

PubMed

Ma, Junshui; Bayram, Sevinç; Tao, Peining; Svetnik, Vladimir

2011-03-15

After a review of the ocular artifact reduction literature, a high-throughput method designed to reduce the ocular artifacts in multichannel continuous EEG recordings acquired at clinical EEG laboratories worldwide is proposed. The proposed method belongs to the category of component-based methods, and does not rely on any electrooculography (EOG) signals. Based on a concept that all ocular artifact components exist in a signal component subspace, the method can uniformly handle all types of ocular artifacts, including eye-blinks, saccades, and other eye movements, by automatically identifying ocular components from decomposed signal components. This study also proposes an improved strategy to objectively and quantitatively evaluate artifact reduction methods. The evaluation strategy uses real EEG signals to synthesize realistic simulated datasets with different amounts of ocular artifacts. The simulated datasets enable us to objectively demonstrate that the proposed method outperforms some existing methods when no high-quality EOG signals are available. Moreover, the results of the simulated datasets improve our understanding of the involved signal decomposition algorithms, and provide us with insights into the inconsistency regarding the performance of different methods in the literature. The proposed method was also applied to two independent clinical EEG datasets involving 28 volunteers and over 1000 EEG recordings. This effort further confirms that the proposed method can effectively reduce ocular artifacts in large clinical EEG datasets in a high-throughput fashion. Copyright © 2011 Elsevier B.V. All rights reserved.

Application of Computational and High-Throughput in vitro ...

EPA Pesticide Factsheets

Abstract: There are tens of thousands of man-made chemicals to which humans are exposed, but only a fraction of these have the extensive in vivo toxicity data used in most traditional risk assessments. This lack of data, coupled with concerns about testing costs and animal use, are driving the development of new methods for assessing the risk of toxicity. These methods include the use of in vitro high-throughput screening assays and computational models. This talk will review a variety of high-throughput, non-animal methods being used at the U.S. EPA to screen chemicals for a variety of toxicity endpoints, with a focus on their potential to be endocrine disruptors as part of the Endocrine Disruptor Screening Program (EDSP). These methods all start with the use of in vitro assays, e.g. for activity against the estrogen and androgen receptors (ER and AR) and targets in the steroidogenesis and thyroid signaling pathways. Because all individual assays are subject to a variety of noise processes and technology-specific assay artefacts, we have developed methods to create consensus predictions from multiple assays against the same target. The goal of these models is to both robustly predict in vivo activity, and also to provide quantitative estimates of uncertainty. This talk will describe these models, and how they are validated against both in vitro and in vivo reference chemicals. The U.S. EPA has deemed the in vitro ER model results to be of high enough accuracy t

Application of computational and high-throughput in vitro ...

EPA Pesticide Factsheets

Abstract: There are tens of thousands of man-made chemicals to which humans are exposed, but only a fraction of these have the extensive in vivo toxicity data used in most traditional risk assessments. This lack of data, coupled with concerns about testing costs and animal use, are driving the development of new methods for assessing the risk of toxicity. These methods include the use of in vitro high-throughput screening assays and computational models. This talk will review a variety of high-throughput, non-animal methods being used at the U.S. EPA to screen chemicals for their potential to be endocrine disruptors as part of the Endocrine Disruptor Screening Program (EDSP). These methods all start with the use of in vitro assays, e.g. for activity against the estrogen and androgen receptors (ER and AR) and targets in the steroidogenesis and thyroid signaling pathways. Because all individual assays are subject to a variety of noise processes and technology-specific assay artefacts, we have developed methods to create consensus predictions from multiple assays against the same target. The goal of these models is to both robustly predict in vivo activity, and also to provide quantitative estimates of uncertainty. This talk will describe these models, and how they are validated against both in vitro and in vivo reference chemicals. The U.S. EPA has deemed the in vitro ER model results to be of high enough accuracy to be used as a substitute for the current EDSP Ti

High-Density Droplet Microarray of Individually Addressable Electrochemical Cells.

PubMed

Zhang, Huijie; Oellers, Tobias; Feng, Wenqian; Abdulazim, Tarik; Saw, En Ning; Ludwig, Alfred; Levkin, Pavel A; Plumeré, Nicolas

2017-06-06

Microarray technology has shown great potential for various types of high-throughput screening applications. The main read-out methods of most microarray platforms, however, are based on optical techniques, limiting the scope of potential applications of such powerful screening technology. Electrochemical methods possess numerous complementary advantages over optical detection methods, including its label-free nature, capability of quantitative monitoring of various reporter molecules, and the ability to not only detect but also address compositions of individual compartments. However, application of electrochemical methods for the purpose of high-throughput screening remains very limited. In this work, we develop a high-density individually addressable electrochemical droplet microarray (eDMA). The eDMA allows for the detection of redox-active reporter molecules irrespective of their electrochemical reversibility in individual nanoliter-sized droplets. Orthogonal band microelectrodes are arranged to form at their intersections an array of three-electrode systems for precise control of the applied potential, which enables direct read-out of the current related to analyte detection. The band microelectrode array is covered with a layer of permeable porous polymethacrylate functionalized with a highly hydrophobic-hydrophilic pattern, forming spatially separated nanoliter-sized droplets on top of each electrochemical cell. Electrochemical characterization of single droplets demonstrates that the underlying electrode system is accessible to redox-active molecules through the hydrophilic polymeric pattern and that the nonwettable hydrophobic boundaries can spatially separate neighboring cells effectively. The eDMA technology opens the possibility to combine the high-throughput biochemical or living cell screenings using the droplet microarray platform with the sequential electrochemical read-out of individual droplets.

Systems cell biology

PubMed Central

Mast, Fred D.; Ratushny, Alexander V.

2014-01-01

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

Integrating prediction, provenance, and optimization into high energy workflows

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

Schram, M.; Bansal, V.; Friese, R. D.

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

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 Call for Nominations of Quantitative High-Throughput ...

EPA Pesticide Factsheets

The National Research Council of the United States National Academies of Science has recently released a document outlining a long-range vision and strategy for transforming toxicity testing from largely whole animal-based testing to one based on in vitro assays. “Toxicity Testing in the 21st Century: A Vision and a Strategy” advises a focus on relevant human toxicity pathway assays. Toxicity pathways are defined in the document as “Cellular response pathways that, when sufficiently perturbed, are expected to result in adverse health effects”. Results of such pathway screens would serve as a filter to drive selection of more specific, targeted testing that will complement and validate the pathway assays. In response to this report, the US EPA has partnered with two NIH organizations, the National Toxicology Program and the NIH Chemical Genomics Center (NCGC), in a program named Tox21. A major goal of this collaboration is to screen chemical libraries consisting of known toxicants, chemicals of environmental and occupational exposure concern, and human pharmaceuticals in cell-based pathway assays. Currently, approximately 3000 compounds (increasing to 9000 by the end of 2009) are being validated and screened in quantitative high-throughput (qHTS) format at the NCGC producing extensive concentration-response data for a diverse set of potential toxicity pathways. The Tox21 collaboration is extremely interested in accessing additional toxicity pathway assa

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

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

Bhandari, Deepak; Van Berkel, Gary J

2012-01-01

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

Prevalence of Perkinsus marinus (dermo), Haplosporidium nelsoni (MSX), and QPX in bivalves of Delaware's inland bays and quantitative, high-throughput diagnosis of dermo by QPCR.

PubMed

Ulrich, Paul N; Ewart, John W; Marsh, Adam G

2007-01-01

Restoration of oyster reef habitat in the Inland Bays of Delaware was accompanied by an effort to detect and determine relative abundance of the bivalve pathogens Perkinsus marinus, Haplosporidium nelsoni, and QPX. Both the oyster Crassostrea virginica and the clam Mercenaria mercenaria were sampled from the bays. In addition, oysters were deployed at eight sites around the bays as sentinels for the three parasites. Perkinsus marinus prevalence was measured with a real-time, quantitative polymerase chain reaction (PCR) methodology that enabled high-throughput detection of as few as 31 copies of the ribosomal non-transcribed spacer region in 500 ng oyster DNA. The other pathogens were assayed using PCR with species-specific primers. Perkinsus marinus was identified in Indian River Bay at moderate prevalence ( approximately 40%) in both an artificial reef and a wild oyster population whereas sentinel oysters were PCR-negative after 3-months exposure during summer and early fall. Haplosporidium nelsoni was restricted to one oyster deployed in Little Assawoman Bay. QPX and P. marinus were not detected among wild clams. While oysters in these bays have historically been under the greatest threat by MSX, it is apparent that P. marinus currently poses a greater threat to recovery of oyster aquaculture in Delaware's Inland Bays.

High-Throughput Multiplexed Quantitation of Protein Aggregation and Cytotoxicity in a Huntington’s Disease Model

PubMed Central

Titus, Steven A; Southall, Noel; Marugan, Juan; Austin, Christopher P; Zheng, Wei

2012-01-01

A hallmark of Huntington’s disease is the presence of a large polyglutamine expansion in the first exon of the Huntingtin protein and the propensity of protein aggregation by the mutant proteins. Aberrant protein aggregation also occurs in other polyglutamine expansion disorders, as well as in other neurodegenerative diseases including Parkinson’s, Alzheimer’s, and prion diseases. However, the pathophysiological role of these aggregates in the cell death that characterizes the diseases remains unclear. Identification of small molecule probes that modulate protein aggregation and cytotoxicity caused by aggregated proteins may greatly facilitate the studies on pathogenesis of these diseases and potentially lead to development of new therapies. Based on a detergent insoluble property of the Huntingtin protein aggregates, we have developed a homogenous assay to rapidly quantitate the levels of protein aggregates in a cellular model of Huntington’s disease. The protein aggregation assay has also been multiplexed with a protease release assay for the measurement of cytotoxicity resulting from aggregated proteins in the same cells. Through a testing screen of a compound library, we have demonstrated that this multiplexed cytotoxicity and protein aggregation assay has ability to identify active compounds that prevent cell death and/or modulate protein aggregation in cells of the Huntington’s disease model. Therefore, this multiplexed screening approach is also useful for development of high-throughput screening assays for other neurodegenerative diseases involving protein aggregation. PMID:23346268

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.

A High-Throughput, Precipitating Colorimetric Sandwich ELISA Microarray for Shiga Toxins

PubMed Central

Gehring, Andrew; He, Xiaohua; Fratamico, Pina; Lee, Joseph; Bagi, Lori; Brewster, Jeffrey; Paoli, George; He, Yiping; Xie, Yanping; Skinner, Craig; Barnett, Charlie; Harris, Douglas

2014-01-01

Shiga toxins 1 and 2 (Stx1 and Stx2) from Shiga toxin-producing E. coli (STEC) bacteria were simultaneously detected with a newly developed, high-throughput antibody microarray platform. The proteinaceous toxins were immobilized and sandwiched between biorecognition elements (monoclonal antibodies) and pooled horseradish peroxidase (HRP)-conjugated monoclonal antibodies. Following the reaction of HRP with the precipitating chromogenic substrate (metal enhanced 3,3-diaminobenzidine tetrahydrochloride or DAB), the formation of a colored product was quantitatively measured with an inexpensive flatbed page scanner. The colorimetric ELISA microarray was demonstrated to detect Stx1 and Stx2 at levels as low as ~4.5 ng/mL within ~2 h of total assay time with a narrow linear dynamic range of ~1–2 orders of magnitude and saturation levels well above background. Stx1 and/or Stx2 produced by various strains of STEC were also detected following the treatment of cultured cells with mitomycin C (a toxin-inducing antibiotic) and/or B-PER (a cell-disrupting, protein extraction reagent). Semi-quantitative detection of Shiga toxins was demonstrated to be sporadic among various STEC strains following incubation with mitomycin C; however, further reaction with B-PER generally resulted in the detection of or increased detection of Stx1, relative to Stx2, produced by STECs inoculated into either axenic broth culture or culture broth containing ground beef. PMID:24921195

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.

Ultrahigh-throughput exfoliation of graphite into pristine 'single-layer' graphene using microwaves and molecularly engineered ionic liquids.

PubMed

Matsumoto, Michio; Saito, Yusuke; Park, Chiyoung; Fukushima, Takanori; Aida, Takuzo

2015-09-01

Graphene has shown much promise as an organic electronic material but, despite recent achievements in the production of few-layer graphene, the quantitative exfoliation of graphite into pristine single-layer graphene has remained one of the main challenges in developing practical devices. Recently, reduced graphene oxide has been recognized as a non-feasible alternative to graphene owing to variable defect types and levels, and attention is turning towards reliable methods for the high-throughput exfoliation of graphite. Here we report that microwave irradiation of graphite suspended in molecularly engineered oligomeric ionic liquids allows for ultrahigh-efficiency exfoliation (93% yield) with a high selectivity (95%) towards 'single-layer' graphene (that is, with thicknesses <1 nm) in a short processing time (30 minutes). The isolated graphene sheets show negligible structural deterioration. They are also readily redispersible in oligomeric ionic liquids up to ~100 mg ml(-1), and form physical gels in which an anisotropic orientation of graphene sheets, once induced by a magnetic field, is maintained.

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE PAGES

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; ...

2017-02-21

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

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

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

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

PubMed Central

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

2015-01-01

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

Ultra-high-throughput screening method for the directed evolution of glucose oxidase.

PubMed

Ostafe, Raluca; Prodanovic, Radivoje; Nazor, Jovana; Fischer, Rainer

2014-03-20

Glucose oxidase (GOx) is used in many industrial processes that could benefit from improved versions of the enzyme. Some improvements like higher activity under physiological conditions and thermal stability could be useful for GOx applications in biosensors and biofuel cells. Directed evolution is one of the currently available methods to engineer improved GOx variants. Here, we describe an ultra-high-throughput screening system for sorting the best enzyme variants generated by directed evolution that incorporates several methodological refinements: flow cytometry, in vitro compartmentalization, yeast surface display, fluorescent labeling of the expressed enzyme, delivery of glucose substrate to the reaction mixture through the oil phase, and covalent labeling of the cells with fluorescein-tyramide. The method enables quantitative screening of gene libraries to identify clones with improved activity and it also allows cells to be selected based not only on the overall activity but also on the specific activity of the enzyme. Copyright © 2014 Elsevier Ltd. All rights reserved.

High-throughput identification of antigen-specific TCRs by TCR gene capture.

PubMed

Linnemann, Carsten; Heemskerk, Bianca; Kvistborg, Pia; Kluin, Roelof J C; Bolotin, Dmitriy A; Chen, Xiaojing; Bresser, Kaspar; Nieuwland, Marja; Schotte, Remko; Michels, Samira; Gomez-Eerland, Raquel; Jahn, Lorenz; Hombrink, Pleun; Legrand, Nicolas; Shu, Chengyi Jenny; Mamedov, Ilgar Z; Velds, Arno; Blank, Christian U; Haanen, John B A G; Turchaninova, Maria A; Kerkhoven, Ron M; Spits, Hergen; Hadrup, Sine Reker; Heemskerk, Mirjam H M; Blankenstein, Thomas; Chudakov, Dmitriy M; Bendle, Gavin M; Schumacher, Ton N M

2013-11-01

The transfer of T cell receptor (TCR) genes into patient T cells is a promising approach for the treatment of both viral infections and cancer. Although efficient methods exist to identify antibodies for the treatment of these diseases, comparable strategies to identify TCRs have been lacking. We have developed a high-throughput DNA-based strategy to identify TCR sequences by the capture and sequencing of genomic DNA fragments encoding the TCR genes. We establish the value of this approach by assembling a large library of cancer germline tumor antigen-reactive TCRs. Furthermore, by exploiting the quantitative nature of TCR gene capture, we show the feasibility of identifying antigen-specific TCRs in oligoclonal T cell populations from either human material or TCR-humanized mice. Finally, we demonstrate the ability to identify tumor-reactive TCRs within intratumoral T cell subsets without knowledge of antigen specificities, which may be the first step toward the development of autologous TCR gene therapy to target patient-specific neoantigens in human cancer.

Real-time reliable determination of binding kinetics of DNA hybridization using a multi-channel graphene biosensor

NASA Astrophysics Data System (ADS)

Xu, Shicai; Zhan, Jian; Man, Baoyuan; Jiang, Shouzhen; Yue, Weiwei; Gao, Shoubao; Guo, Chengang; Liu, Hanping; Li, Zhenhua; Wang, Jihua; Zhou, Yaoqi

2017-03-01

Reliable determination of binding kinetics and affinity of DNA hybridization and single-base mismatches plays an essential role in systems biology, personalized and precision medicine. The standard tools are optical-based sensors that are difficult to operate in low cost and to miniaturize for high-throughput measurement. Biosensors based on nanowire field-effect transistors have been developed, but reliable and cost-effective fabrication remains a challenge. Here, we demonstrate that a graphene single-crystal domain patterned into multiple channels can measure time- and concentration-dependent DNA hybridization kinetics and affinity reliably and sensitively, with a detection limit of 10 pM for DNA. It can distinguish single-base mutations quantitatively in real time. An analytical model is developed to estimate probe density, efficiency of hybridization and the maximum sensor response. The results suggest a promising future for cost-effective, high-throughput screening of drug candidates, genetic variations and disease biomarkers by using an integrated, miniaturized, all-electrical multiplexed, graphene-based DNA array.

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 detection of ethanol-producing cyanobacteria in a microdroplet platform

PubMed Central

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

2015-01-01

Ethanol production by microorganisms is an important renewable energy source. Most processes involve fermentation of sugars from plant feedstock, but there is increasing interest in direct ethanol production by photosynthetic organisms. To facilitate this, a high-throughput screening technique for the detection of ethanol is required. Here, a method for the quantitative detection of ethanol in a microdroplet-based platform is described that can be used for screening cyanobacterial strains to identify those with the highest ethanol productivity levels. The detection of ethanol by enzymatic assay was optimized both in bulk and in microdroplets. In parallel, the encapsulation of engineered ethanol-producing cyanobacteria in microdroplets and their growth dynamics in microdroplet reservoirs were demonstrated. The combination of modular microdroplet operations including droplet generation for cyanobacteria encapsulation, droplet re-injection and pico-injection, and laser-induced fluorescence, were used to create this new platform to screen genetically engineered strains of cyanobacteria with different levels of ethanol production. PMID:25878135

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

RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli.

PubMed

McCloskey, Douglas; Xu, Julia; Schrübbers, Lars; Christensen, Hanne B; Herrgård, Markus J

2018-04-25

Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics of biochemical reactions between strains that could have implications when choosing a host for bioprocessing. Copyright © 2018. Published by Elsevier Inc.

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

PubMed

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

2016-02-01

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