Identification of Tyrosine Phosphorylated Proteins by SH2 Domain Affinity Purification and Mass Spectrometry.

PubMed

Buhs, Sophia; Gerull, Helwe; Nollau, Peter

2017-01-01

Phosphotyrosine signaling plays a major role in the control of many important biological functions such as cell proliferation and apoptosis. Deciphering of phosphotyrosine-dependent signaling is therefore of great interest paving the way for the understanding of physiological and pathological processes of signal transduction. On the basis of the specific binding of SH2 domains to phosphotyrosine residues, we here present an experimental workflow for affinity purification and subsequent identification of tyrosine phosphorylated proteins by mass spectrometry. In combination with SH2 profiling, a broadly applicable platform for the characterization of phosphotyrosine profiles in cell extracts, our pull down strategy enables researchers by now to identify proteins in signaling cascades which are differentially phosphorylated and selectively recognized by distinct SH2 domains.

The emerging process of Top Down mass spectrometry for protein analysis: biomarkers, protein-therapeutics, and achieving high throughput†

PubMed Central

Kellie, John F.; Tran, John C.; Lee, Ji Eun; Ahlf, Dorothy R.; Thomas, Haylee M.; Ntai, Ioanna; Catherman, Adam D.; Durbin, Kenneth R.; Zamdborg, Leonid; Vellaichamy, Adaikkalam; Thomas, Paul M.

2011-01-01

Top Down mass spectrometry (MS) has emerged as an alternative to common Bottom Up strategies for protein analysis. In the Top Down approach, intact proteins are fragmented directly in the mass spectrometer to achieve both protein identification and characterization, even capturing information on combinatorial post-translational modifications. Just in the past two years, Top Down MS has seen incremental advances in instrumentation and dedicated software, and has also experienced a major boost from refined separations of whole proteins in complex mixtures that have both high recovery and reproducibility. Combined with steadily advancing commercial MS instrumentation and data processing, a high-throughput workflow covering intact proteins and polypeptides up to 70 kDa is directly visible in the near future. PMID:20711533

Analytical aspects of plant metabolite profiling platforms: current standings and future aims.

PubMed

Seger, Christoph; Sturm, Sonja

2007-02-01

Over the past years, metabolic profiling has been established as a comprehensive systems biology tool. Mass spectrometry or NMR spectroscopy-based technology platforms combined with unsupervised or supervised multivariate statistical methodologies allow a deep insight into the complex metabolite patterns of plant-derived samples. Within this review, we provide a thorough introduction to the analytical hard- and software requirements of metabolic profiling platforms. Methodological limitations are addressed, and the metabolic profiling workflow is exemplified by summarizing recent applications ranging from model systems to more applied topics.

DeMix Workflow for Efficient Identification of Cofragmented Peptides in High Resolution Data-dependent Tandem Mass Spectrometry*

PubMed Central

Zhang, Bo; Pirmoradian, Mohammad; Chernobrovkin, Alexey; Zubarev, Roman A.

2014-01-01

Based on conventional data-dependent acquisition strategy of shotgun proteomics, we present a new workflow DeMix, which significantly increases the efficiency of peptide identification for in-depth shotgun analysis of complex proteomes. Capitalizing on the high resolution and mass accuracy of Orbitrap-based tandem mass spectrometry, we developed a simple deconvolution method of “cloning” chimeric tandem spectra for cofragmented peptides. Additional to a database search, a simple rescoring scheme utilizes mass accuracy and converts the unwanted cofragmenting events into a surprising advantage of multiplexing. With the combination of cloning and rescoring, we obtained on average nine peptide-spectrum matches per second on a Q-Exactive workbench, whereas the actual MS/MS acquisition rate was close to seven spectra per second. This efficiency boost to 1.24 identified peptides per MS/MS spectrum enabled analysis of over 5000 human proteins in single-dimensional LC-MS/MS shotgun experiments with an only two-hour gradient. These findings suggest a change in the dominant “one MS/MS spectrum - one peptide” paradigm for data acquisition and analysis in shotgun data-dependent proteomics. DeMix also demonstrated higher robustness than conventional approaches in terms of lower variation among the results of consecutive LC-MS/MS runs. PMID:25100859

Generation and structural validation of a library of diverse xyloglucan-derived oligosaccharides, including an update on xyloglucan nomenclature.

PubMed

Tuomivaara, Sami T; Yaoi, Katsuro; O'Neill, Malcolm A; York, William S

2015-01-30

Xyloglucans are structurally complex plant cell wall polysaccharides that are involved in cell growth and expansion, energy metabolism, and signaling. Determining the structure-function relationships of xyloglucans would benefit from the availability of a comprehensive and structurally diverse collection of rigorously characterized xyloglucan oligosaccharides. Here, we present a workflow for the semi-preparative scale generation and purification of neutral and acidic xyloglucan oligosaccharides using a combination of enzymatic and chemical treatments and size-exclusion chromatography. Twenty-six of these oligosaccharides were purified to near homogeneity and their structures validated using a combination of matrix-assisted laser desorption/ionization mass spectrometry, high-performance anion exchange chromatography, and 1H nuclear magnetic resonance spectroscopy. Mass spectrometry and analytical chromatography were compared as methods for xyloglucan oligosaccharide quantification. 1H chemical shifts were assigned using two-dimensional correlation spectroscopy. A comprehensive update of the nomenclature describing xyloglucan side-chain structures is provided for reference. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of wastewater samples by direct combination of thin-film microextraction and desorption electrospray ionization mass spectrometry.

PubMed

Strittmatter, Nicole; Düring, Rolf-Alexander; Takáts, Zoltán

2012-09-07

An analysis method for aqueous samples by the direct combination of C18/SCX mixed mode thin-film microextraction (TFME) and desorption electrospray ionization mass spectrometry (DESI-MS) was developed. Both techniques make analytical workflow simpler and faster, hence the combination of the two techniques enables considerably shorter analysis time compared to the traditional liquid chromatography mass spectrometry (LC-MS) approach. The method was characterized using carbamazepine and triclosan as typical examples for pharmaceuticals and personal care product (PPCP) components which draw increasing attention as wastewater-derived environmental contaminants. Both model compounds were successfully detected in real wastewater samples and their concentrations determined using external calibration with isotope labeled standards. Effects of temperature, agitation, sample volume, and exposure time were investigated in the case of spiked aqueous samples. Results were compared to those of parallel HPLC-MS determinations and good agreement was found through a three orders of magnitude wide concentration range. Serious matrix effects were observed in treated wastewater, but lower limits of detection were still found to be in the low ng L(-1) range. Using an Orbitrap mass spectrometer, the technique was found to be ideal for screening purposes and led to the detection of various different PPCP components in wastewater treatment plant effluents, including beta-blockers, nonsteroidal anti-inflammatory drugs, and UV filters.

Non-targeted workflow for identification of antimicrobial compounds in animal feed using bioassay-directed screening in combination with liquid chromatography-high resolution mass spectrometry.

PubMed

Wegh, Robin S; Berendsen, Bjorn J A; Driessen-Van Lankveld, Wilma D M; Pikkemaat, Mariël G; Zuidema, Tina; Van Ginkel, Leen A

2017-11-01

A non-targeted workflow is reported for the isolation and identification of antimicrobial active compounds using bioassay-directed screening and LC coupled to high-resolution MS. Suspect samples are extracted using a generic protocol and fractionated using two different LC conditions (A and B). The behaviour of the bioactive compound under these different conditions yields information about the physicochemical properties of the compound and introduces variations in co-eluting compounds in the fractions, which is essential for peak picking and identification. The fractions containing the active compound(s) obtained with conditions A and B are selected using a microbiological effect-based bioassay. The selected bioactive fractions from A and B are analysed using LC combined with high-resolution MS. Selection of relevant signals is automatically carried out by selecting all signals present in both bioactive fractions A and B, yielding tremendous data reduction. The method was assessed using two spiked feed samples and subsequently applied to two feed samples containing an unidentified compound showing microbial growth inhibition. In all cases, the identity of the compound causing microbiological inhibition was successfully confirmed.

Online Ozonolysis Combined with Ion Mobility-Mass Spectrometry Provides a New Platform for Lipid Isomer Analyses

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

Poad, Berwyck L. J.; Zheng, Xueyun; Mitchell, Todd W.

One of the most significant challenges in contemporary lipidomics lies in the separation and identification of lipid isomers that differ only in site(s) of unsaturation or geometric configuration of the carbon-carbon double bonds. While analytical separation techniques including ion mobility spectrometry (IMS) and liquid chromatography (LC) can separate isomeric lipids under appropriate conditions, conventional tandem mass spectrometry cannot provide unequivocal identification. To address this challenge, we have implemented ozone-induced dissociation (OzID) in-line with LC, IMS and high resolution mass spectrometry. Modification of an IMS- capable quadrupole time-of-flight mass spectrometer was undertaken to allow the introduction of ozone into the high-pressuremore » trapping ion funnel region preceding the IMS cell. This enabled the novel LC-OzID-IMS-MS configuration where ozonolysis of ionized lipids occurred rapidly (10 ms) without prior mass-selection. LC-elution time alignment combined with accurate mass and arrival time extraction of ozonolysis products facilitated correlation of precursor and product ions without mass-selection (and associated reductions in duty cycle). Unsaturated lipids across 11 classes were examined using this workflow in both positive and negative ion modalities and in all cases the positions of carbon-carbon double bonds were unequivocally assigned based on predictable OzID transitions. Under these conditions geometric isomers exhibited different IMS arrival time distributions and distinct OzID product ion ratios providing a means for discrimination of cis/trans double bonds in complex lipids. The combination of OzID with multidimensional separations shows significant promise for facile profiling of unsaturation patterns within complex lipidomes.« less

Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow.

PubMed

Volani, Chiara; Caprioli, Giulia; Calderisi, Giovanni; Sigurdsson, Baldur B; Rainer, Johannes; Gentilini, Ivo; Hicks, Andrew A; Pramstaller, Peter P; Weiss, Guenter; Smarason, Sigurdur V; Paglia, Giuseppe

2017-10-01

Volumetric absorptive microsampling (VAMS) is a novel approach that allows single-drop (10 μL) blood collection. Integration of VAMS with mass spectrometry (MS)-based untargeted metabolomics is an attractive solution for both human and animal studies. However, to boost the use of VAMS in metabolomics, key pre-analytical questions need to be addressed. Therefore, in this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We first evaluated the best extraction procedure for the polar metabolome and found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile/water (70:30). In contrast, basic conditions (pH 9) resulted in divergent metabolite profiles mainly resulting from the extraction of intracellular metabolites originating from red blood cells. In addition, the prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but once the VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months. The time used for drying the sample did also affect the metabolome. In fact, some metabolites were rapidly degraded or accumulated in the sample during the first 48 h at room temperature, indicating that a longer drying step will significantly change the concentration in the sample. Graphical abstract Volumetric absorptive microsampling (VAMS) is a novel technology that allows single-drop blood collection and, in combination with mass spectrometry (MS)-based untargeted metabolomics, represents an attractive solution for both human and animal studies. In this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. The latter revealed that prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but if VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months.

Core lipid, surface lipid and apolipoprotein composition analysis of lipoprotein particles as a function of particle size in one workflow integrating asymmetric flow field-flow fractionation and liquid chromatography-tandem mass spectrometry

PubMed Central

Jones, Jeffery I.; Gardner, Michael S.; Schieltz, David M.; Parks, Bryan A.; Toth, Christopher A.; Rees, Jon C.; Andrews, Michael L.; Carter, Kayla; Lehtikoski, Antony K.; McWilliams, Lisa G.; Williamson, Yulanda M.; Bierbaum, Kevin P.; Pirkle, James L.; Barr, John R.

2018-01-01

Lipoproteins are complex molecular assemblies that are key participants in the intricate cascade of extracellular lipid metabolism with important consequences in the formation of atherosclerotic lesions and the development of cardiovascular disease. Multiplexed mass spectrometry (MS) techniques have substantially improved the ability to characterize the composition of lipoproteins. However, these advanced MS techniques are limited by traditional pre-analytical fractionation techniques that compromise the structural integrity of lipoprotein particles during separation from serum or plasma. In this work, we applied a highly effective and gentle hydrodynamic size based fractionation technique, asymmetric flow field-flow fractionation (AF4), and integrated it into a comprehensive tandem mass spectrometry based workflow that was used for the measurement of apolipoproteins (apos A-I, A-II, A-IV, B, C-I, C-II, C-III and E), free cholesterol (FC), cholesterol esters (CE), triglycerides (TG), and phospholipids (PL) (phosphatidylcholine (PC), sphingomyelin (SM), phosphatidylethanolamine (PE), phosphatidylinositol (PI) and lysophosphatidylcholine (LPC)). Hydrodynamic size in each of 40 size fractions separated by AF4 was measured by dynamic light scattering. Measuring all major lipids and apolipoproteins in each size fraction and in the whole serum, using total of 0.1 ml, allowed the volumetric calculation of lipoprotein particle numbers and expression of composition in molar analyte per particle number ratios. Measurements in 110 serum samples showed substantive differences between size fractions of HDL and LDL. Lipoprotein composition within size fractions was expressed in molar ratios of analytes (A-I/A-II, C-II/C-I, C-II/C-III. E/C-III, FC/PL, SM/PL, PE/PL, and PI/PL), showing differences in sample categories with combinations of normal and high levels of Total-C and/or Total-TG. The agreement with previous studies indirectly validates the AF4-LC-MS/MS approach and demonstrates the potential of this workflow for characterization of lipoprotein composition in clinical studies using small volumes of archived frozen samples. PMID:29634782

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.

PubMed

Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan; Chen, Emily I

2016-11-01

Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

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

Kulkarni, Shilpa; Koller, Antonius; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24more » and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.« less

MPA Portable: A Stand-Alone Software Package for Analyzing Metaproteome Samples on the Go.

PubMed

Muth, Thilo; Kohrs, Fabian; Heyer, Robert; Benndorf, Dirk; Rapp, Erdmann; Reichl, Udo; Martens, Lennart; Renard, Bernhard Y

2018-01-02

Metaproteomics, the mass spectrometry-based analysis of proteins from multispecies samples faces severe challenges concerning data analysis and results interpretation. To overcome these shortcomings, we here introduce the MetaProteomeAnalyzer (MPA) Portable software. In contrast to the original server-based MPA application, this newly developed tool no longer requires computational expertise for installation and is now independent of any relational database system. In addition, MPA Portable now supports state-of-the-art database search engines and a convenient command line interface for high-performance data processing tasks. While search engine results can easily be combined to increase the protein identification yield, an additional two-step workflow is implemented to provide sufficient analysis resolution for further postprocessing steps, such as protein grouping as well as taxonomic and functional annotation. Our new application has been developed with a focus on intuitive usability, adherence to data standards, and adaptation to Web-based workflow platforms. The open source software package can be found at https://github.com/compomics/meta-proteome-analyzer .

Computational methods and challenges in hydrogen/deuterium exchange mass spectrometry.

PubMed

Claesen, Jürgen; Burzykowski, Tomasz

2017-09-01

Hydrogen/Deuterium exchange (HDX) has been applied, since the 1930s, as an analytical tool to study the structure and dynamics of (small) biomolecules. The popularity of using HDX to study proteins increased drastically in the last two decades due to the successful combination with mass spectrometry (MS). Together with this growth in popularity, several technological advances have been made, such as improved quenching and fragmentation. As a consequence of these experimental improvements and the increased use of protein-HDXMS, large amounts of complex data are generated, which require appropriate analysis. Computational analysis of HDXMS requires several steps. A typical workflow for proteins consists of identification of (non-)deuterated peptides or fragments of the protein under study (local analysis), or identification of the deuterated protein as a whole (global analysis); determination of the deuteration level; estimation of the protection extent or exchange rates of the labile backbone amide hydrogen atoms; and a statistically sound interpretation of the estimated protection extent or exchange rates. Several algorithms, specifically designed for HDX analysis, have been proposed. They range from procedures that focus on one specific step in the analysis of HDX data to complete HDX workflow analysis tools. In this review, we provide an overview of the computational methods and discuss outstanding challenges. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:649-667, 2017. © 2016 Wiley Periodicals, Inc.

Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow.

PubMed

Kirwan, J A; Broadhurst, D I; Davidson, R L; Viant, M R

2013-06-01

Direct infusion mass spectrometry (DIMS)-based untargeted metabolomics measures many hundreds of metabolites in a single experiment. While every effort is made to reduce within-experiment analytical variation in untargeted metabolomics, unavoidable sources of measurement error are introduced. This is particularly true for large-scale multi-batch experiments, necessitating the development of robust workflows that minimise batch-to-batch variation. Here, we conducted a purpose-designed, eight-batch DIMS metabolomics study using nanoelectrospray (nESI) Fourier transform ion cyclotron resonance mass spectrometric analyses of mammalian heart extracts. First, we characterised the intrinsic analytical variation of this approach to determine whether our existing workflows are fit for purpose when applied to a multi-batch investigation. Batch-to-batch variation was readily observed across the 7-day experiment, both in terms of its absolute measurement using quality control (QC) and biological replicate samples, as well as its adverse impact on our ability to discover significant metabolic information within the data. Subsequently, we developed and implemented a computational workflow that includes total-ion-current filtering, QC-robust spline batch correction and spectral cleaning, and provide conclusive evidence that this workflow reduces analytical variation and increases the proportion of significant peaks. We report an overall analytical precision of 15.9%, measured as the median relative standard deviation (RSD) for the technical replicates of the biological samples, across eight batches and 7 days of measurements. When compared against the FDA guidelines for biomarker studies, which specify an RSD of <20% as an acceptable level of precision, we conclude that our new workflows are fit for purpose for large-scale, high-throughput nESI DIMS metabolomics studies.

Toward Streamlined Identification of Dioxin-like Compounds in Environmental Samples through Integration of Suspension Bioassay.

PubMed

Xiao, Hongxia; Brinkmann, Markus; Thalmann, Beat; Schiwy, Andreas; Große Brinkhaus, Sigrid; Achten, Christine; Eichbaum, Kathrin; Gembé, Carolin; Seiler, Thomas-Benjamin; Hollert, Henner

2017-03-21

Effect-directed analysis (EDA) is a powerful strategy to identify biologically active compounds in environmental samples. However, in current EDA studies, fractionation and handling procedures are laborious, consist of multiple evaporation steps, and thus bear the risk of contamination and decreased recoveries of the target compounds. The low resulting throughput has been one of the major bottlenecks of EDA. Here, we propose a high-throughput EDA (HT-EDA) work-flow combining reversed phase high-performance liquid chromatography fractionation of samples into 96-well microplates, followed by toxicity assessment in the micro-EROD bioassay with the wild-type rat hepatoma H4IIE cells, and chemical analysis of bioactive fractions. The approach was evaluated using single substances, binary mixtures, and extracts of sediment samples collected at the Three Gorges Reservoir, Yangtze River, China, as well as the rivers Rhine and Elbe, Germany. Selected bioactive fractions were analyzed by highly sensitive gas chromatography-atmospheric pressure laser ionization-time-of-flight-mass spectrometry. In addition, we optimized the work-flow by seeding previously adapted suspension-cultured H4IIE cells directly into the microplate used for fractionation, which makes any transfers of fractionated samples unnecessary. The proposed HT-EDA work-flow simplifies the procedure for wider application in ecotoxicology and environmental routine programs.

A workflow for multiclass determination of 256 pesticides in essential oils by liquid chromatography tandem mass spectrometry using evaporation and dilution approaches: Application to lavandin, lemon and cypress essential oils.

PubMed

Fillatre, Yoann; Rondeau, David; Daguin, Antoine; Communal, Pierre-Yves

2016-01-01

This paper describes the determination of 256 multiclass pesticides in cypress and lemon essential oils (EOs) by the way of liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI/MS/MS) analysis using the scheduled selected reaction monitoring mode (sSRM) available on a hybrid quadrupole linear ion trap (QLIT) mass spectrometer. The performance of a sample preparation of lemon and cypress EOs based on dilution or evaporation under nitrogen assisted by a controlled heating were assessed. The best limits of quantification (LOQs) were achieved with the evaporation under nitrogen method giving LOQs≤10µgL(-1) for 91% of the pesticides. In addition the very satisfactory results obtained for recovery, repeatability and linearity showed that for EOs of relatively low evaporation temperature, a sample preparation based on evaporation under nitrogen is well adapted and preferable to dilution. By compiling these results with those previously published by some of us on lavandin EO, we proposed a workflow dedicated to multiresidue determination of pesticides in various EOs by LC-ESI/sSRM. Among the steps involved in this workflow, the protocol related to mass spectrometry proposes an alternative confirmation method to the classical SRM ratio criteria based on a sSRM survey scan followed by an information-dependent acquisition using the sensitive enhanced product ion (EPI) scan to generate MS/MS spectra then compared to a reference. The submitted workflow was applied to the case of lemon EOs samples highlighting for the first time the simultaneous detection of 20 multiclass pesticides in one EO. Some pesticides showed very high concentration levels with amounts greatly exceeding the mgL(-1). Copyright © 2015 Elsevier B.V. All rights reserved.

Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control

PubMed Central

Kirwan, Jennifer A; Weber, Ralf J M; Broadhurst, David I; Viant, Mark R

2014-01-01

Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment. PMID:25977770

Profiling of Histone Post-Translational Modifications in Mouse Brain with High-Resolution Top-Down Mass Spectrometry.

PubMed

Zhou, Mowei; Paša-Tolić, Ljiljana; Stenoien, David L

2017-02-03

As histones play central roles in most chromosomal functions including regulation of DNA replication, DNA damage repair, and gene transcription, both their basic biology and their roles in disease development have been the subject of intense study. Because multiple post-translational modifications (PTMs) along the entire protein sequence are potential regulators of histones, a top-down approach, where intact proteins are analyzed, is ultimately required for complete characterization of proteoforms. However, significant challenges remain for top-down histone analysis primarily because of deficiencies in separation/resolving power and effective identification algorithms. Here we used state-of-the-art mass spectrometry and a bioinformatics workflow for targeted data analysis and visualization. The workflow uses ProMex for intact mass deconvolution, MSPathFinder as a search engine, and LcMsSpectator as a data visualization tool. When complemented with the open-modification tool TopPIC, this workflow enabled identification of novel histone PTMs including tyrosine bromination on histone H4 and H2A, H3 glutathionylation, and mapping of conventional PTMs along the entire protein for many histone subunits.

The life sciences mass spectrometry research unit.

PubMed

Hopfgartner, Gérard; Varesio, Emmanuel

2012-01-01

The Life Sciences Mass Spectrometry (LSMS) research unit focuses on the development of novel analytical workflows based on innovative mass spectrometric and software tools for the analysis of low molecular weight compounds, peptides and proteins in complex biological matrices. The present article summarizes some of the recent work of the unit: i) the application of matrix-assisted laser desorption/ionization (MALDI) for mass spectrometry imaging (MSI) of drug of abuse in hair, ii) the use of high resolution mass spectrometry for simultaneous qualitative/quantitative analysis in drug metabolism and metabolomics, and iii) the absolute quantitation of proteins by mass spectrometry using the selected reaction monitoring mode.

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF.

PubMed

Théron, Laëtitia; Centeno, Delphine; Coudy-Gandilhon, Cécile; Pujos-Guillot, Estelle; Astruc, Thierry; Rémond, Didier; Barthelemy, Jean-Claude; Roche, Frédéric; Feasson, Léonard; Hébraud, Michel; Béchet, Daniel; Chambon, Christophe

2016-10-26

Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m / z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation.

A Proof of Concept to Bridge the Gap between Mass Spectrometry Imaging, Protein Identification and Relative Quantitation: MSI~LC-MS/MS-LF

PubMed Central

Théron, Laëtitia; Centeno, Delphine; Coudy-Gandilhon, Cécile; Pujos-Guillot, Estelle; Astruc, Thierry; Rémond, Didier; Barthelemy, Jean-Claude; Roche, Frédéric; Feasson, Léonard; Hébraud, Michel; Béchet, Daniel; Chambon, Christophe

2016-01-01

Mass spectrometry imaging (MSI) is a powerful tool to visualize the spatial distribution of molecules on a tissue section. The main limitation of MALDI-MSI of proteins is the lack of direct identification. Therefore, this study focuses on a MSI~LC-MS/MS-LF workflow to link the results from MALDI-MSI with potential peak identification and label-free quantitation, using only one tissue section. At first, we studied the impact of matrix deposition and laser ablation on protein extraction from the tissue section. Then, we did a back-correlation of the m/z of the proteins detected by MALDI-MSI to those identified by label-free quantitation. This allowed us to compare the label-free quantitation of proteins obtained in LC-MS/MS with the peak intensities observed in MALDI-MSI. We managed to link identification to nine peaks observed by MALDI-MSI. The results showed that the MSI~LC-MS/MS-LF workflow (i) allowed us to study a representative muscle proteome compared to a classical bottom-up workflow; and (ii) was sparsely impacted by matrix deposition and laser ablation. This workflow, performed as a proof-of-concept, suggests that a single tissue section can be used to perform MALDI-MSI and protein extraction, identification, and relative quantitation. PMID:28248242

Hekate: Software Suite for the Mass Spectrometric Analysis and Three-Dimensional Visualization of Cross-Linked Protein Samples

PubMed Central

2013-01-01

Chemical cross-linking of proteins combined with mass spectrometry provides an attractive and novel method for the analysis of native protein structures and protein complexes. Analysis of the data however is complex. Only a small number of cross-linked peptides are produced during sample preparation and must be identified against a background of more abundant native peptides. To facilitate the search and identification of cross-linked peptides, we have developed a novel software suite, named Hekate. Hekate is a suite of tools that address the challenges involved in analyzing protein cross-linking experiments when combined with mass spectrometry. The software is an integrated pipeline for the automation of the data analysis workflow and provides a novel scoring system based on principles of linear peptide analysis. In addition, it provides a tool for the visualization of identified cross-links using three-dimensional models, which is particularly useful when combining chemical cross-linking with other structural techniques. Hekate was validated by the comparative analysis of cytochrome c (bovine heart) against previously reported data.1 Further validation was carried out on known structural elements of DNA polymerase III, the catalytic α-subunit of the Escherichia coli DNA replisome along with new insight into the previously uncharacterized C-terminal domain of the protein. PMID:24010795

Recent advances in lipid separations and structural elucidation using mass spectrometry combined with ion mobility spectrometry, ion-molecule reactions and fragmentation approaches

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

Zheng, Xueyun; Smith, Richard D.; Baker, Erin S.

Lipids are a vital class of molecules that play important and varied roles in biological processes. Fully understanding lipid roles, however, is extremely difficult since the number and diversity of lipid species is immense, with cells expressing hundreds of enzymes that synthesize tens of thousands of different lipids. While recent advances in chromatography and high resolution mass spectrometry have greatly progressed the understanding of lipid species and functions, effectively separating many lipids still remains problematic. Isomeric lipids have made lipid characterization especially difficult and occur due to subclasses having the same chemical composition, or species having multiple acyl chains connectivitiesmore » (sn-1, sn-2, or sn-3), double bond positions and orientations (cis or trans), and functional group stereochemistry (R versus S). Fully understanding the roles of lipids in biological processes therefore requires separating and evaluating how isomers change in biological and environmental samples. To address this challenge, ion mobility spectrometry separations, ion-molecule reactions and fragmentation techniques have increasingly been added to lipid analysis workflows to improve identifications. In this manuscript, we review the current state of these approaches and their capabilities for improving the identification of specific lipid species.« less

An efficient laboratory workflow for environmental risk assessment of organic chemicals.

PubMed

Zhu, Linyan; Santiago-Schübel, Beatrix; Xiao, Hongxia; Thiele, Björn; Zhu, Zhiliang; Qiu, Yanling; Hollert, Henner; Küppers, Stephan

2015-07-01

In this study, we demonstrate a fast and efficient workflow to investigate the transformation mechanism of organic chemicals and evaluate the toxicity of their transformation products (TPs) in laboratory scale. The transformation process of organic chemicals was first simulated by electrochemistry coupled online to mass spectrometry (EC-MS). The simulated reactions were scaled up in a batch EC reactor to receive larger amounts of a reaction mixture. The mixture sample was purified and concentrated by solid phase extraction (SPE) for the further ecotoxicological testing. The combined toxicity of the reaction mixture was evaluated in fish egg test (FET) (Danio rerio) compared to the parent compound. The workflow was verified with carbamazepine (CBZ). By using EC-MS seven primary TPs of CBZ were identified; the degradation mechanism was elucidated and confirmed by comparison to literature. The reaction mixture and one primary product (acridine) showed higher ecotoxicity in fish egg assay with 96 h EC50 values of 1.6 and 1.0 mg L(-1) than CBZ with the value of 60.8 mg L(-1). The results highlight the importance of transformation mechanism study and toxicological effect evaluation for organic chemicals brought into the environment since transformation of them may increase the toxicity. The developed process contributes a fast and efficient laboratory method for the risk assessment of organic chemicals and their TPs. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comprehensive high-resolution mass spectrometry approach for characterization of metabolites by combination of ambient ionization, chromatography and imaging methods.

PubMed

Berisha, Arton; Dold, Sebastian; Guenther, Sabine; Desbenoit, Nicolas; Takats, Zoltan; Spengler, Bernhard; Römpp, Andreas

2014-08-30

An ideal method for bioanalytical applications would deliver spatially resolved quantitative information in real time and without sample preparation. In reality these requirements can typically not be met by a single analytical technique. Therefore, we combine different mass spectrometry approaches: chromatographic separation, ambient ionization and imaging techniques, in order to obtain comprehensive information about metabolites in complex biological samples. Samples were analyzed by laser desorption followed by electrospray ionization (LD-ESI) as an ambient ionization technique, by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging for spatial distribution analysis and by high-performance liquid chromatography/electrospray ionization mass spectrometry (HPLC/ESI-MS) for quantitation and validation of compound identification. All MS data were acquired with high mass resolution and accurate mass (using orbital trapping and ion cyclotron resonance mass spectrometers). Grape berries were analyzed and evaluated in detail, whereas wheat seeds and mouse brain tissue were analyzed in proof-of-concept experiments. In situ measurements by LD-ESI without any sample preparation allowed for fast screening of plant metabolites on the grape surface. MALDI imaging of grape cross sections at 20 µm pixel size revealed the detailed distribution of metabolites which were in accordance with their biological function. HPLC/ESI-MS was used to quantify 13 anthocyanin species as well as to separate and identify isomeric compounds. A total of 41 metabolites (amino acids, carbohydrates, anthocyanins) were identified with all three approaches. Mass accuracy for all MS measurements was better than 2 ppm (root mean square error). The combined approach provides fast screening capabilities, spatial distribution information and the possibility to quantify metabolites. Accurate mass measurements proved to be critical in order to reliably combine data from different MS techniques. Initial results on the mycotoxin deoxynivalenol (DON) in wheat seed and phospholipids in mouse brain as a model for mammalian tissue indicate a broad applicability of the presented workflow. Copyright © 2014 John Wiley & Sons, Ltd.

An Internal Standard for Assessing Phosphopeptide Recovery from Metal Ion/Oxide Enrichment Strategies

NASA Astrophysics Data System (ADS)

Paulo, Joao A.; Navarrete-Perea, Jose; Erickson, Alison R.; Knott, Jeffrey; Gygi, Steven P.

2018-04-01

Phosphorylation-mediated signaling pathways have major implications in cellular regulation and disease. However, proteins with roles in these pathways are frequently less abundant and phosphorylation is often sub-stoichiometric. As such, the efficient enrichment, and subsequent recovery of phosphorylated peptides, is vital. Mass spectrometry-based proteomics is a well-established approach for quantifying thousands of phosphorylation events in a single experiment. We designed a peptide internal standard-based assay directed toward sample preparation strategies for mass spectrometry analysis to understand better phosphopeptide recovery from enrichment strategies. We coupled mass-differential tandem mass tag (mTMT) reagents (specifically, TMTzero and TMTsuper-heavy), nine mass spectrometry-amenable phosphopeptides (phos9), and peak area measurements from extracted ion chromatograms to determine phosphopeptide recovery. We showcase this mTMT/phos9 recovery assay by evaluating three phosphopeptide enrichment workflows. Our assay provides data on the recovery of phosphopeptides, which complement other metrics, namely the number of identified phosphopeptides and enrichment specificity. Our mTMT/phos9 assay is applicable to any enrichment protocol in a typical experimental workflow irrespective of sample origin or labeling strategy. [Figure not available: see fulltext.

Analysis of volatiles in fire debris by combination of activated charcoal strips (ACS) and automated thermal desorption-gas chromatography-mass spectrometry (ATD/GC-MS).

PubMed

Martin Fabritius, Marie; Broillet, Alain; König, Stefan; Weinmann, Wolfgang

2018-06-04

Adsorption of volatiles in gaseous phase to activated charcoal strip (ACS) is one possibility for the extraction and concentration of ignitable liquid residues (ILRs) from fire debris in arson investigations. Besides liquid extraction using carbon dioxide or hexane, automated thermo-desorption can be used to transfer adsorbed residues to direct analysis by gas chromatography-mass spectrometry (GC-MS). We present a fire debris analysis work-flow with headspace adsorption of volatiles onto ACS and subsequent automated thermo-desorption (ATD) GC-MS analysis. Only a small portion of the ACS is inserted in the ATD tube for thermal desorption coupled to GC-MS, allowing for subsequent confirmation analysis with another portion of the same ACS. This approach is a promising alternative to the routinely used ACS method with solvent extraction of retained volatiles, and the application to fire debris analysis is demonstrated. Copyright © 2018 Elsevier B.V. All rights reserved.

A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation.

PubMed

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2017-05-31

Label-free mass spectrometry (MS) has developed into an important tool applied in various fields of biological and life sciences. Several software exist to process the raw MS data into quantified protein abundances, including open source and commercial solutions. Each software includes a set of unique algorithms for different tasks of the MS data processing workflow. While many of these algorithms have been compared separately, a thorough and systematic evaluation of their overall performance is missing. Moreover, systematic information is lacking about the amount of missing values produced by the different proteomics software and the capabilities of different data imputation methods to account for them.In this study, we evaluated the performance of five popular quantitative label-free proteomics software workflows using four different spike-in data sets. Our extensive testing included the number of proteins quantified and the number of missing values produced by each workflow, the accuracy of detecting differential expression and logarithmic fold change and the effect of different imputation and filtering methods on the differential expression results. We found that the Progenesis software performed consistently well in the differential expression analysis and produced few missing values. The missing values produced by the other software decreased their performance, but this difference could be mitigated using proper data filtering or imputation methods. Among the imputation methods, we found that the local least squares (lls) regression imputation consistently increased the performance of the software in the differential expression analysis, and a combination of both data filtering and local least squares imputation increased performance the most in the tested data sets. © The Author 2017. Published by Oxford University Press.

What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

PubMed

Hamzeiy, Hamid; Cox, Jürgen

2017-02-01

Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

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

Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.

Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptidemore » biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements« less

Ambient Mass Spectrometry in Cancer Research.

PubMed

Takats, Z; Strittmatter, N; McKenzie, J S

2017-01-01

Ambient ionization mass spectrometry was developed as a sample preparation-free alternative to traditional MS-based workflows. Desorption electrospray ionization (DESI)-MS methods were demonstrated to allow the direct analysis of a broad range of samples including unaltered biological tissue specimens. In contrast to this advantageous feature, nowadays DESI-MS is almost exclusively used for sample preparation intensive mass spectrometric imaging (MSI) in the area of cancer research. As an alternative to MALDI, DESI-MSI offers matrix deposition-free experiment with improved signal in the lower (<500m/z) range. DESI-MSI enables the spatial mapping of tumor metabolism and has been broadly demonstrated to offer an alternative to frozen section histology for intraoperative tissue identification and surgical margin assessment. Rapid evaporative ionization mass spectrometry (REIMS) was developed exclusively for the latter purpose by the direct combination of electrosurgical devices and mass spectrometry. In case of the REIMS technology, aerosol particles produced by electrosurgical dissection are subjected to MS analysis, providing spectral information on the structural lipid composition of tissues. REIMS technology was demonstrated to give real-time information on the histological nature of tissues being dissected, deeming it an ideal tool for intraoperative tissue identification including surgical margin control. More recently, the method has also been used for the rapid lipidomic phenotyping of cancer cell lines as it was demonstrated in case of the NCI-60 cell line collection. © 2017 Elsevier Inc. All rights reserved.

Proteins with High Turnover Rate in Barley Leaves Estimated by Proteome Analysis Combined with in Planta Isotope Labeling1[W][OPEN

PubMed Central

Nelson, Clark J.; Alexova, Ralitza; Jacoby, Richard P.; Millar, A. Harvey

2014-01-01

Protein turnover is a key component in cellular homeostasis; however, there is little quantitative information on degradation kinetics for individual plant proteins. We have used 15N labeling of barley (Hordeum vulgare) plants and gas chromatography-mass spectrometry analysis of free amino acids and liquid chromatography-mass spectrometry analysis of proteins to track the enrichment of 15N into the amino acid pools in barley leaves and then into tryptic peptides derived from newly synthesized proteins. Using information on the rate of growth of barley leaves combined with the rate of degradation of 14N-labeled proteins, we calculate the turnover rates of 508 different proteins in barley and show that they vary by more than 100-fold. There was approximately a 9-h lag from label application until 15N incorporation could be reliably quantified in extracted peptides. Using this information and assuming constant translation rates for proteins during the time course, we were able to quantify degradation rates for several proteins that exhibit half-lives on the order of hours. Our workflow, involving a stringent series of mass spectrometry filtering steps, demonstrates that 15N labeling can be used for large-scale liquid chromatography-mass spectrometry studies of protein turnover in plants. We identify a series of abundant proteins in photosynthesis, photorespiration, and specific subunits of chlorophyll biosynthesis that turn over significantly more rapidly than the average protein involved in these processes. We also highlight a series of proteins that turn over as rapidly as the well-known D1 subunit of photosystem II. While these proteins need further verification for rapid degradation in vivo, they cluster in chlorophyll and thiamine biosynthesis. PMID:25082890

A Retrospective Evaluation of the Use of Mass Spectrometry in FDA Biologics License Applications

NASA Astrophysics Data System (ADS)

Rogstad, Sarah; Faustino, Anneliese; Ruth, Ashley; Keire, David; Boyne, Michael; Park, Jun

2017-05-01

The characterization sections of biologics license applications (BLAs) approved by the United States Food and Drug Administration (FDA) between 2000 and 2015 were investigated to examine the extent of the use of mass spectrometry. Mass spectrometry was found to be integral to the characterization of these biotherapeutics. Of the 80 electronically submitted monoclonal antibody and protein biotherapeutic BLAs included in this study, 79 were found to use mass spectrometric workflows for protein or impurity characterization. To further examine how MS is being used in successful BLAs, the applications were filtered based on the type and number of quality attributes characterized, the mass spectrometric workflows used (peptide mapping, intact mass analysis, and cleaved glycan analysis), the methods used to introduce the proteins into the gas phase (ESI, MALDI, or LC-ESI), and the specific types of instrumentation used. Analyses were conducted over a time course based on the FDA BLA approval to determine if any trends in utilization could be observed over time. Additionally, the different classes of protein-based biotherapeutics among the approved BLAs were clustered to determine if any trends could be attributed to the specific type of biotherapeutic.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Sacks, David B.; Yu, Yi-Kuo

2018-06-01

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

PubMed

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

BioInfra.Prot: A comprehensive proteomics workflow including data standardization, protein inference, expression analysis and data publication.

PubMed

Turewicz, Michael; Kohl, Michael; Ahrens, Maike; Mayer, Gerhard; Uszkoreit, Julian; Naboulsi, Wael; Bracht, Thilo; Megger, Dominik A; Sitek, Barbara; Marcus, Katrin; Eisenacher, Martin

2017-11-10

The analysis of high-throughput mass spectrometry-based proteomics data must address the specific challenges of this technology. To this end, the comprehensive proteomics workflow offered by the de.NBI service center BioInfra.Prot provides indispensable components for the computational and statistical analysis of this kind of data. These components include tools and methods for spectrum identification and protein inference, protein quantification, expression analysis as well as data standardization and data publication. All particular methods of the workflow which address these tasks are state-of-the-art or cutting edge. As has been shown in previous publications, each of these methods is adequate to solve its specific task and gives competitive results. However, the methods included in the workflow are continuously reviewed, updated and improved to adapt to new scientific developments. All of these particular components and methods are available as stand-alone BioInfra.Prot services or as a complete workflow. Since BioInfra.Prot provides manifold fast communication channels to get access to all components of the workflow (e.g., via the BioInfra.Prot ticket system: bioinfraprot@rub.de) users can easily benefit from this service and get support by experts. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Subpopulation-proteomics in prokaryotic populations.

PubMed

Jahn, Michael; Seifert, Jana; von Bergen, Martin; Schmid, Andreas; Bühler, Bruno; Müller, Susann

2013-02-01

Clonal microbial cells do not behave in an identical manner and form subpopulations during cultivation. Besides varying micro-environmental conditions, cell inherent features like cell cycle dependent localization and concentration of regulatory proteins as well as epigenetic properties are well accepted mechanisms creating cell heterogeneity. Another suspected reason is molecular noise on the transcriptional and translational level. A promising tool to unravel reasons for cell heterogeneity is the combination of cell sorting and subpopulation proteomics. This review summarizes recent developments in prokaryotic single-cell analytics and provides a workflow for selection of single cells, low cell number mass spectrometry, and proteomics evaluation. This approach is useful for understanding the dependency of individual cell decisions on inherent protein profiles. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mass Spectrometry: A Technique of Many Faces

PubMed Central

Olshina, Maya A.; Sharon, Michal

2016-01-01

Protein complexes form the critical foundation for a wide range of biological process, however understanding the intricate details of their activities is often challenging. In this review we describe how mass spectrometry plays a key role in the analysis of protein assemblies and the cellular pathways which they are involved in. Specifically, we discuss how the versatility of mass spectrometric approaches provides unprecedented information on multiple levels. We demonstrate this on the ubiquitin-proteasome proteolytic pathway, a process that is responsible for protein turnover. We follow the various steps of this degradation route and illustrate the different mass spectrometry workflows that were applied for elucidating molecular information. Overall, this review aims to stimulate the integrated use of multiple mass spectrometry approaches for analyzing complex biological systems. PMID:28100928

Profiling Changes in Histone Post-translational Modifications by Top-Down Mass Spectrometry

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

Zhou, Mowei; Wu, Si; Stenoien, David L.

Top-down mass spectrometry is a valuable tool for charactering post-translational modifications on histones for understanding of gene control and expression. In this protocol, we describe a top-down workflow using liquid chromatography coupled to mass spectrometry for fast global profiling of changes in histone proteoforms between a wild-type and a mutant of a fungal species. The proteoforms exhibiting different abundances can be subjected to further targeted studies by other mass spectrometric or biochemical assays. This method can be generally adapted for preliminary screening for changes in histone modifications between samples such as wild-type vs. mutant, and control vs. disease.

An Accessible Proteogenomics Informatics Resource for Cancer Researchers.

PubMed

Chambers, Matthew C; Jagtap, Pratik D; Johnson, James E; McGowan, Thomas; Kumar, Praveen; Onsongo, Getiria; Guerrero, Candace R; Barsnes, Harald; Vaudel, Marc; Martens, Lennart; Grüning, Björn; Cooke, Ira R; Heydarian, Mohammad; Reddy, Karen L; Griffin, Timothy J

2017-11-01

Proteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry-based proteomics data to directly identify expressed, variant protein sequences that may have functional roles in cancer. This approach is computationally intensive, requiring integration of disparate software tools into sophisticated workflows, challenging its adoption by nonexpert, bench scientists. To address this need, we have developed an extensible, Galaxy-based resource aimed at providing more researchers access to, and training in, proteogenomic informatics. Our resource brings together software from several leading research groups to address two foundational aspects of proteogenomics: (i) generation of customized, annotated protein sequence databases from RNA-Seq data; and (ii) accurate matching of tandem mass spectrometry data to putative variants, followed by filtering to confirm their novelty. Directions for accessing software tools and workflows, along with instructional documentation, can be found at z.umn.edu/canresgithub. Cancer Res; 77(21); e43-46. ©2017 AACR . ©2017 American Association for Cancer Research.

Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

NASA Astrophysics Data System (ADS)

Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

2018-05-01

In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

Native Mass Spectrometry, Ion mobility, and Collision-Induced Unfolding Categorize Malaria Antigen/Antibody Binding

NASA Astrophysics Data System (ADS)

Huang, Yining; Salinas, Nichole D.; Chen, Edwin; Tolia, Niraj H.; Gross, Michael L.

2017-09-01

Plasmodium vivax Duffy Binding Protein (PvDBP) is a promising vaccine candidate for P. vivax malaria. Recently, we reported the epitopes on PvDBP region II (PvDBP-II) for three inhibitory monoclonal antibodies (2D10, 2H2, and 2C6). In this communication, we describe the combination of native mass spectrometry and ion mobility (IM) with collision induced unfolding (CIU) to study the conformation and stabilities of three malarial antigen-antibody complexes. These complexes, when collisionally activated, undergo conformational changes that depend on the location of the epitope. CIU patterns for PvDBP-II in complex with antibody 2D10 and 2H2 are highly similar, indicating comparable binding topology and stability. A different CIU fingerprint is observed for PvDBP-II/2C6, indicating that 2C6 binds to PvDBP-II on an epitope different from 2D10 and 2H2. This work supports the use of CIU as a means of classifying antigen-antibody complexes by their epitope maps in a high throughput screening workflow. [Figure not available: see fulltext.

Mass Spectrometry of Human Leukocyte Antigen Class I Peptidomes Reveals Strong Effects of Protein Abundance and Turnover on Antigen Presentation*

PubMed Central

Bassani-Sternberg, Michal; Pletscher-Frankild, Sune; Jensen, Lars Juhl; Mann, Matthias

2015-01-01

HLA class I molecules reflect the health state of cells to cytotoxic T cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (p < 0.0001). When analyzing overpresented proteins – those with at least fivefold higher density score than expected for their abundance – we noticed that they are degraded almost 3 h faster than similar but nonpresented proteins (top 20% abundance class; median half-life 20.8h versus 23.6h, p < 0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain, and nucleosomal proteins are particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our data set. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides. Remarkably, we identified five mutated peptides from a human colon cancer cell line, which have very recently been predicted to be HLA-I binders. Altogether, we demonstrate the usefulness of combining MS-analysis with immunogenesis prediction for identifying, ranking, and selecting peptides for therapeutic use. PMID:25576301

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Profiling of Histone Post-Translational Modifications in Mouse Brain with High-Resolution Top-Down Mass Spectrometry

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

Zhou, Mowei; Paša-Tolić, Ljiljana; Stenoien, David L.

Histones play central roles in most chromosomal functions and both their basic biology and roles in disease have been the subject of intense study. Since multiple PTMs along the entire protein sequence are potential regulators of histones, a top-down approach, where intact proteins are analyzed, is ultimately required for complete characterization of proteoforms. However, significant challenges remain for top-down histone analysis primarily because of deficiencies in separation/resolving power and effective identification algorithms. Here, we used state of the art mass spectrometry and a bioinformatics workflow for targeted data analysis and visualization. The workflow uses ProMex for intact mass deconvolution, MSPathFindermore » as search engine, and LcMsSpectator as a data visualization tool. ProMex sums across retention time to maximize sensitivity and accuracy for low abundance species in MS1deconvolution. MSPathFinder searches the MS2 data against protein sequence databases with user-defined modifications. LcMsSpectator presents the results from ProMex and MSPathFinder in a format that allows quick manual evaluation of critical attributes for high-confidence identifications. When complemented with the open-modification tool TopPIC, this workflow enabled identification of novel histone PTMs including tyrosine bromination on histone H4 and H2A, H3 glutathionylation, and mapping of conventional PTMs along the entire protein for many histone subunits.« less

Research and Implementation of Key Technologies in Multi-Agent System to Support Distributed Workflow

NASA Astrophysics Data System (ADS)

Pan, Tianheng

2018-01-01

In recent years, the combination of workflow management system and Multi-agent technology is a hot research field. The problem of lack of flexibility in workflow management system can be improved by introducing multi-agent collaborative management. The workflow management system adopts distributed structure. It solves the problem that the traditional centralized workflow structure is fragile. In this paper, the agent of Distributed workflow management system is divided according to its function. The execution process of each type of agent is analyzed. The key technologies such as process execution and resource management are analyzed.

A rapid diagnostic workflow for cefotaxime-resistant Escherichia coli and Klebsiella pneumoniae detection from blood cultures by MALDI-TOF mass spectrometry.

PubMed

De Carolis, Elena; Paoletti, Silvia; Nagel, Domenico; Vella, Antonietta; Mello, Enrica; Palucci, Ivana; De Angelis, Giulia; D'Inzeo, Tiziana; Sanguinetti, Maurizio; Posteraro, Brunella; Spanu, Teresa

2017-01-01

Nowadays, the global spread of resistance to oxyimino-cephalosporins in Enterobacteriaceae implies the need for novel diagnostics that can rapidly target resistant organisms from these bacterial species. In this study, we developed and evaluated a Direct Mass Spectrometry assay for Beta-Lactamase (D-MSBL) that allows direct identification of (oxyimino)cephalosporin-resistant Escherichia coli or Klebsiella pneumoniae from positive blood cultures (BCs), by using the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) technology. The D-MSBL assay was performed on 93 E. coli or K. pneumoniae growing BC samples that were shortly co-incubated with cefotaxime (CTX) as the indicator cephalosporin. Susceptibility and resistance defining peaks from the samples' mass spectra were analyzed by a novel algorithm for bacterial organism classification. The D-MSBL assay allowed discrimination between E. coli and K. pneumoniae that were resistant or susceptible to CTX with a sensitivity of 86.8% and a specificity of 98.2%. The proposed algorithm-based D-MSBL assay, if integrated in the routine laboratory diagnostic workflow, may be useful to enhance the establishment of appropriate antibiotic therapy and to control the threat of oxyimino-cephalosporin resistance in hospital.

Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies.

PubMed

Surinova, Silvia; Hüttenhain, Ruth; Chang, Ching-Yun; Espona, Lucia; Vitek, Olga; Aebersold, Ruedi

2013-08-01

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope-labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1-2 weeks, depending on the number of replicates used in the experiment.

Multi-level meta-workflows: new concept for regularly occurring tasks in quantum chemistry.

PubMed

Arshad, Junaid; Hoffmann, Alexander; Gesing, Sandra; Grunzke, Richard; Krüger, Jens; Kiss, Tamas; Herres-Pawlis, Sonja; Terstyanszky, Gabor

2016-01-01

In Quantum Chemistry, many tasks are reoccurring frequently, e.g. geometry optimizations, benchmarking series etc. Here, workflows can help to reduce the time of manual job definition and output extraction. These workflows are executed on computing infrastructures and may require large computing and data resources. Scientific workflows hide these infrastructures and the resources needed to run them. It requires significant efforts and specific expertise to design, implement and test these workflows. Many of these workflows are complex and monolithic entities that can be used for particular scientific experiments. Hence, their modification is not straightforward and it makes almost impossible to share them. To address these issues we propose developing atomic workflows and embedding them in meta-workflows. Atomic workflows deliver a well-defined research domain specific function. Publishing workflows in repositories enables workflow sharing inside and/or among scientific communities. We formally specify atomic and meta-workflows in order to define data structures to be used in repositories for uploading and sharing them. Additionally, we present a formal description focused at orchestration of atomic workflows into meta-workflows. We investigated the operations that represent basic functionalities in Quantum Chemistry, developed the relevant atomic workflows and combined them into meta-workflows. Having these workflows we defined the structure of the Quantum Chemistry workflow library and uploaded these workflows in the SHIWA Workflow Repository.Graphical AbstractMeta-workflows and embedded workflows in the template representation.

Anatomy and evolution of database search engines-a central component of mass spectrometry based proteomic workflows.

PubMed

Verheggen, Kenneth; Raeder, Helge; Berven, Frode S; Martens, Lennart; Barsnes, Harald; Vaudel, Marc

2017-09-13

Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines. © 2017 Wiley Periodicals, Inc.

Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC) environments

NASA Astrophysics Data System (ADS)

Kintsakis, Athanassios M.; Psomopoulos, Fotis E.; Symeonidis, Andreas L.; Mitkas, Pericles A.

Hermes introduces a new "describe once, run anywhere" paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

PeptideDepot: Flexible Relational Database for Visual Analysis of Quantitative Proteomic Data and Integration of Existing Protein Information

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2010-01-01

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through tandem mass spectrometry (MS/MS). Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to a variety of experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our High Throughput Autonomous Proteomic Pipeline (HTAPP) used in the automated acquisition and post-acquisition analysis of proteomic data. PMID:19834895

Suspected-target pesticide screening using gas chromatography-quadrupole time-of-flight mass spectrometry with high resolution deconvolution and retention index/mass spectrum library.

PubMed

Zhang, Fang; Wang, Haoyang; Zhang, Li; Zhang, Jing; Fan, Ruojing; Yu, Chongtian; Wang, Wenwen; Guo, Yinlong

2014-10-01

A strategy for suspected-target screening of pesticide residues in complicated matrices was exploited using gas chromatography in combination with hybrid quadrupole time-of-flight mass spectrometry (GC-QTOF MS). The screening workflow followed three key steps of, initial detection, preliminary identification, and final confirmation. The initial detection of components in a matrix was done by a high resolution mass spectrum deconvolution; the preliminary identification of suspected pesticides was based on a special retention index/mass spectrum (RI/MS) library that contained both the first-stage mass spectra (MS(1) spectra) and retention indices; and the final confirmation was accomplished by accurate mass measurements of representative ions with their response ratios from the MS(1) spectra or representative product ions from the second-stage mass spectra (MS(2) spectra). To evaluate the applicability of the workflow in real samples, three matrices of apple, spinach, and scallion, each spiked with 165 test pesticides in a set of concentrations, were selected as the models. The results showed that the use of high-resolution TOF enabled effective extractions of spectra from noisy chromatograms, which was based on a narrow mass window (5 mDa) and suspected-target compounds identified by the similarity match of deconvoluted full mass spectra and filtering of linear RIs. On average, over 74% of pesticides at 50 ng/mL could be identified using deconvolution and the RI/MS library. Over 80% of pesticides at 5 ng/mL or lower concentrations could be confirmed in each matrix using at least two representative ions with their response ratios from the MS(1) spectra. In addition, the application of product ion spectra was capable of confirming suspected pesticides with specificity for some pesticides in complicated matrices. In conclusion, GC-QTOF MS combined with the RI/MS library seems to be one of the most efficient tools for the analysis of suspected-target pesticide residues in complicated matrices. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification and Structural Characterization of Naturally-Occurring Broad-Spectrum Cyclic Antibiotics Isolated from Paenibacillus

NASA Astrophysics Data System (ADS)

Knolhoff, Ann M.; Zheng, Jie; McFarland, Melinda A.; Luo, Yan; Callahan, John H.; Brown, Eric W.; Croley, Timothy R.

2015-08-01

The rise of antimicrobial resistance necessitates the discovery and/or production of novel antibiotics. Isolated strains of Paenibacillus alvei were previously shown to exhibit antimicrobial activity against a number of pathogens, such as E. coli, Salmonella, and methicillin-resistant Staphylococcus aureus (MRSA). The responsible antimicrobial compounds were isolated from these Paenibacillus strains and a combination of low and high resolution mass spectrometry with multiple-stage tandem mass spectrometry was used for identification. A group of closely related cyclic lipopeptides was identified, differing primarily by fatty acid chain length and one of two possible amino acid substitutions. Variation in the fatty acid length resulted in mass differences of 14 Da and yielded groups of related MSn spectra. Despite the inherent complexity of MS/MS spectra of cyclic compounds, straightforward analysis of these spectra was accomplished by determining differences in complementary product ion series between compounds that differ in molecular weight by 14 Da. The primary peptide sequence assignment was confirmed through genome mining; the combination of these analytical tools represents a workflow that can be used for the identification of complex antibiotics. The compounds also share amino acid sequence similarity to a previously identified broad-spectrum antibiotic isolated from Paenibacillus. The presence of such a wide distribution of related compounds produced by the same organism represents a novel class of broad-spectrum antibiotic compounds.

MALDI Mass Spectrometry Imaging: A Novel Tool for the Identification and Classification of Amyloidosis.

PubMed

Winter, Martin; Tholey, Andreas; Kristen, Arnt; Röcken, Christoph

2017-11-01

Amyloidosis is a group of diseases caused by extracellular accumulation of fibrillar polypeptide aggregates. So far, diagnosis is performed by Congo red staining of tissue sections in combination with polarization microscopy. Subsequent identification of the causative protein by immunohistochemistry harbors some difficulties regarding sensitivity and specificity. Mass spectrometry based approaches have been demonstrated to constitute a reliable method to supplement typing of amyloidosis, but still depend on Congo red staining. In the present study, we used matrix-assisted laser desorption/ionization mass spectrometry imaging coupled with ion mobility separation (MALDI-IMS MSI) to investigate amyloid deposits in formalin-fixed and paraffin-embedded tissue samples. Utilizing a novel peptide filter method, we found a universal peptide signature for amyloidoses. Furthermore, differences in the peptide composition of ALλ and ATTR amyloid were revealed and used to build a reliable classification model. Integrating the peptide filter in MALDI-IMS MSI analysis, we developed a bioinformatics workflow facilitating the identification and classification of amyloidosis in a less time and sample-consuming experimental setup. Our findings demonstrate also the feasibility to investigate the amyloid's protein composition, thus paving the way to establish classification models for the diverse types of amyloidoses and to shed further light on the complex process of amyloidogenesis. © 2017 The Authors, Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In-depth analyses of native N-linked glycans facilitated by high-performance anion exchange chromatography-pulsed amperometric detection coupled to mass spectrometry.

PubMed

Szabo, Zoltan; Thayer, James R; Agroskin, Yury; Lin, Shanhua; Liu, Yan; Srinivasan, Kannan; Saba, Julian; Viner, Rosa; Huhmer, Andreas; Rohrer, Jeff; Reusch, Dietmar; Harfouche, Rania; Khan, Shaheer H; Pohl, Christopher

2017-05-01

Characterization of glycans present on glycoproteins has become of increasing importance due to their biological implications, such as protein folding, immunogenicity, cell-cell adhesion, clearance, receptor interactions, etc. In this study, the resolving power of high-performance anion exchange chromatography with pulsed amperometric detection (HPAE-PAD) was applied to glycan separations and coupled to mass spectrometry to characterize native glycans released from different glycoproteins. A new, rapid workflow generates glycans from 200 μg of glycoprotein supporting reliable and reproducible annotation by mass spectrometry (MS). With the relatively high flow rate of HPAE-PAD, post-column splitting diverted 60% of the flow to a novel desalter, then to the mass spectrometer. The delay between PAD and MS detectors is consistent, and salt removal after the column supports MS. HPAE resolves sialylated (charged) glycans and their linkage and positional isomers very well; separations of neutral glycans are sufficient for highly reproducible glycoprofiling. Data-dependent MS 2 in negative mode provides highly informative, mostly C- and Z-type glycosidic and cross-ring fragments, making software-assisted and manual annotation reliable. Fractionation of glycans followed by exoglycosidase digestion confirms MS-based annotations. Combining the isomer resolution of HPAE with MS 2 permitted thorough N-glycan annotation and led to characterization of 17 new structures from glycoproteins with challenging glycan profiles.

A workflow for large-scale empirical identification of cell wall N-linked glycoproteins of tomato (Solanum lycopersicum) fruit by tandem mass spectrometry

USDA-ARS?s Scientific Manuscript database

Glycosylation is a common post-translational modification of plant proteins that impacts a large number of important biological processes. Nevertheless, the impacts of differential site occupancy and the nature of specific glycoforms are obscure. Historically, characterization of glycoproteins has b...

An open workflow to generate “MS Ready” structures and improve non-targeted mass spectrometry (ACS Fall 1 of 3)

EPA Science Inventory

High-throughput non-targeted analyses (NTA) rely on chemical reference databases for tentative identification of observed chemical features. Many of these databases and online resources incorporate chemical structure data not in a form that is readily observed by mass spectromet...

Identifying "known unknowns": A comparison between ChemSpider and the US EPA's CompTox Dashboard (ACS Spring National meeting) 1 of 7

EPA Science Inventory

Non-targeted analysis (NTA) workflows in high-resolution mass spectrometry require mechanisms for compound identification. One strategy for tentative identification is the use of online chemical databases such as ChemSpider. Databases like this use molecular formulae and monois...

On the Reproducibility of Label-Free Quantitative Cross-Linking/Mass Spectrometry

NASA Astrophysics Data System (ADS)

Müller, Fränze; Fischer, Lutz; Chen, Zhuo Angel; Auchynnikava, Tania; Rappsilber, Juri

2018-02-01

Quantitative cross-linking/mass spectrometry (QCLMS) is an emerging approach to study conformational changes of proteins and multi-subunit complexes. Distinguishing protein conformations requires reproducibly identifying and quantifying cross-linked peptides. Here we analyzed the variation between multiple cross-linking reactions using bis[sulfosuccinimidyl] suberate (BS3)-cross-linked human serum albumin (HSA) and evaluated how reproducible cross-linked peptides can be identified and quantified by LC-MS analysis. To make QCLMS accessible to a broader research community, we developed a workflow that integrates the established software tools MaxQuant for spectra preprocessing, Xi for cross-linked peptide identification, and finally Skyline for quantification (MS1 filtering). Out of the 221 unique residue pairs identified in our sample, 124 were subsequently quantified across 10 analyses with coefficient of variation (CV) values of 14% (injection replica) and 32% (reaction replica). Thus our results demonstrate that the reproducibility of QCLMS is in line with the reproducibility of general quantitative proteomics and we establish a robust workflow for MS1-based quantitation of cross-linked peptides.

QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories

PubMed Central

Chiva, Cristina; Olivella, Roger; Borràs, Eva; Espadas, Guadalupe; Pastor, Olga; Solé, Amanda

2018-01-01

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0. PMID:29324744

Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective.

PubMed

Kockmann, Tobias; Trachsel, Christian; Panse, Christian; Wahlander, Asa; Selevsek, Nathalie; Grossmann, Jonas; Wolski, Witold E; Schlapbach, Ralph

2016-08-01

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

msCompare: A Framework for Quantitative Analysis of Label-free LC-MS Data for Comparative Candidate Biomarker Studies*

PubMed Central

Hoekman, Berend; Breitling, Rainer; Suits, Frank; Bischoff, Rainer; Horvatovich, Peter

2012-01-01

Data processing forms an integral part of biomarker discovery and contributes significantly to the ultimate result. To compare and evaluate various publicly available open source label-free data processing workflows, we developed msCompare, a modular framework that allows the arbitrary combination of different feature detection/quantification and alignment/matching algorithms in conjunction with a novel scoring method to evaluate their overall performance. We used msCompare to assess the performance of workflows built from modules of publicly available data processing packages such as SuperHirn, OpenMS, and MZmine and our in-house developed modules on peptide-spiked urine and trypsin-digested cerebrospinal fluid (CSF) samples. We found that the quality of results varied greatly among workflows, and interestingly, heterogeneous combinations of algorithms often performed better than the homogenous workflows. Our scoring method showed that the union of feature matrices of different workflows outperformed the original homogenous workflows in some cases. msCompare is open source software (https://trac.nbic.nl/mscompare), and we provide a web-based data processing service for our framework by integration into the Galaxy server of the Netherlands Bioinformatics Center (http://galaxy.nbic.nl/galaxy) to allow scientists to determine which combination of modules provides the most accurate processing for their particular LC-MS data sets. PMID:22318370

Intact cell MALDI-TOF mass spectrometry on single bovine oocyte and follicular cells combined with top-down proteomics: A novel approach to characterise markers of oocyte maturation.

PubMed

Labas, Valérie; Teixeira-Gomes, Ana-Paula; Bouguereau, Laura; Gargaros, Audrey; Spina, Lucie; Marestaing, Aurélie; Uzbekova, Svetlana

2018-03-20

Intact cell MALDI-TOF mass spectrometry (ICM-MS) was adapted to bovine follicular cells from individual ovarian follicles to obtain the protein/peptide signatures (<17kDa) of single oocytes, cumulus cells (CC) and granulosa cells (GC), which shared a total of 439 peaks. By comparing the ICM-MS profiles of single oocytes and CC before and after in vitro maturation (IVM), 71 different peaks were characterised, and their relative abundance was found to vary depending on the stage of oocyte meiotic maturation. To identify these endogenous biomolecules, top-down workflow using high resolution MS/MS (TD HR-MS) was performed on the protein extracts from oocytes, CC and GC. The TD HR-MS proteomic approach allowed for: (1) identification of 386 peptide/proteoforms encoded by 194 genes; and (2) characterisation of proteolysis products likely resulting from the action of kallikreins and caspases. In total, 136 peaks observed by ICM-MS were annotated by TD HR-MS (ProteomeXchange PXD004892). Among these, 16 markers of maturation were identified, including IGF2 binding protein 3 and hemoglobin B in the oocyte, thymosins beta-4 and beta-10, histone H2B and ubiquitin in CC. The combination of ICM-MS and TD HR-MS proved to be a suitable strategy to identify non-invasive markers of oocyte quality using limited biological samples. Intact cell MALDI-TOF mass spectrometry on single oocytes and their surrounding cumulus cells, coupled to an optimised top-down HR-MS proteomic approach on ovarian follicular cells, was used to identify specific markers of oocyte meiotic maturation represented by whole low molecular weight proteins or products of degradation by specific proteases. Copyright © 2017 Elsevier B.V. All rights reserved.

Profiling Changes in Histone Post-translational Modifications by Top-Down Mass Spectrometry.

PubMed

Zhou, Mowei; Wu, Si; Stenoien, David L; Zhang, Zhaorui; Connolly, Lanelle; Freitag, Michael; Paša-Tolić, Ljiljana

2017-01-01

Top-down mass spectrometry is a valuable tool for understanding gene expression through characterization of combinatorial histone post-translational modifications (i.e., histone code). In this protocol, we describe a top-down workflow that employs liquid chromatography (LC) coupled to mass spectrometry (MS), for fast global profiling of changes in histone proteoforms, and apply LCMS top-down approach for comparative analysis of a wild-type and a mutant fungal species. The proteoforms exhibiting differential abundances can be subjected to further targeted studies by other MS or orthogonal (e.g., biochemical) assays. This method can be generally adapted for screening of changes in histone modifications between samples such as wild type vs. mutant or healthy vs. diseased.

Targeted Quantification of Phosphorylation Dynamics in the Context of EGFR-MAPK Pathway

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

Yi, Lian; Shi, Tujin; Gritsenko, Marina A.

2018-03-27

Large-scale phosphoproteomics with coverage of over 10,000 sites of phosphorylation have now been routinely achieved with advanced mass spectrometry (MS)-based workflows. However, accurate targeted MS-based quantification of phosphorylation dynamics, an important direction for gaining quantitative understanding of signaling pathways or networks, has been much less investigated. Herein, we report an assessment of the targeted workflow in the context of signal transduction pathways, using the epidermal growth factor receptor (EGFR)–mitogen-activated protein kinase (MAPK) pathway as our model. 43 phosphopeptides from the EGFR–MAPK pathway were selected for the study. The recovery and sensitivity of a workflow consisted of two commonly used enrichmentmore » methods, immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO2), combined with selected reaction monitoring (SRM)-MS, were evaluated. The recovery of phosphopeptides by IMAC and TiO2 enrichment was quantified to be 38 ± 5% and 58 ± 20%, respectively, based on internal standards. Moreover, both enrichment methods provided comparable sensitivity from 1-100 g starting peptides. Robust quantification was consistently achieved for most targeted phosphopeptides when starting with 25-100 g peptides. However, the numbers of quantified targets significantly dropped when peptide samples were in the 1-25g range. Finally, IMAC-SRM was applied to quantify signaling dynamics of EGFR-MAPK pathway in Hs578T cells following 3 ng/mL EGF treatment. The kinetics of phosphorylation clearly revealed early and late phases of phosphorylation, even for very low abundance proteins. These results demonstrate the feasibility of robust targeted quantification of phosphorylation dynamics for specific pathways, even starting with relatively small amounts of protein.« less

Click-MS: Tagless Protein Enrichment Using Bioorthogonal Chemistry for Quantitative Proteomics.

PubMed

Smits, Arne H; Borrmann, Annika; Roosjen, Mark; van Hest, Jan C M; Vermeulen, Michiel

2016-12-16

Epitope-tagging is an effective tool to facilitate protein enrichment from crude cell extracts. Traditionally, N- or C-terminal fused tags are employed, which, however, can perturb protein function. Unnatural amino acids (UAAs) harboring small reactive handles can be site-specifically incorporated into proteins, thus serving as a potential alternative for conventional protein tags. Here, we introduce Click-MS, which combines the power of site-specific UAA incorporation, bioorthogonal chemistry, and quantitative mass spectrometry-based proteomics to specifically enrich a single protein of interest from crude mammalian cell extracts. By genetic encoding of p-azido-l-phenylalanine, the protein of interest can be selectively captured using copper-free click chemistry. We use Click-MS to enrich proteins that function in different cellular compartments, and we identify protein-protein interactions, showing the great potential of Click-MS for interaction proteomics workflows.

Agile parallel bioinformatics workflow management using Pwrake.

PubMed

Mishima, Hiroyuki; Sasaki, Kensaku; Tanaka, Masahiro; Tatebe, Osamu; Yoshiura, Koh-Ichiro

2011-09-08

In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error.Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows.

Agile parallel bioinformatics workflow management using Pwrake

PubMed Central

2011-01-01

Background In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows. PMID:21899774

A rapid approach for characterization of thiol-conjugated antibody-drug conjugates and calculation of drug-antibody ratio by liquid chromatography mass spectrometry.

PubMed

Firth, David; Bell, Leonard; Squires, Martin; Estdale, Sian; McKee, Colin

2015-09-15

We present the demonstration of a rapid "middle-up" liquid chromatography mass spectrometry (LC-MS)-based workflow for use in the characterization of thiol-conjugated maleimidocaproyl-monomethyl auristatin F (mcMMAF) and valine-citrulline-monomethyl auristatin E (vcMMAE) antibody-drug conjugates. Deconvoluted spectra were generated following a combination of deglycosylation, IdeS (immunoglobulin-degrading enzyme from Streptococcus pyogenes) digestion, and reduction steps that provide a visual representation of the product for rapid lot-to-lot comparison-a means to quickly assess the integrity of the antibody structure and the applied conjugation chemistry by mass. The relative abundance of the detected ions also offer information regarding differences in drug conjugation levels between samples, and the average drug-antibody ratio can be calculated. The approach requires little material (<100 μg) and, thus, is amenable to small-scale process development testing or as an early component of a complete characterization project facilitating informed decision making regarding which aspects of a molecule might need to be examined in more detail by orthogonal methodologies. Copyright © 2015 Elsevier Inc. All rights reserved.

Preprocessing Significantly Improves the Peptide/Protein Identification Sensitivity of High-resolution Isobarically Labeled Tandem Mass Spectrometry Data*

PubMed Central

Sheng, Quanhu; Li, Rongxia; Dai, Jie; Li, Qingrun; Su, Zhiduan; Guo, Yan; Li, Chen; Shyr, Yu; Zeng, Rong

2015-01-01

Isobaric labeling techniques coupled with high-resolution mass spectrometry have been widely employed in proteomic workflows requiring relative quantification. For each high-resolution tandem mass spectrum (MS/MS), isobaric labeling techniques can be used not only to quantify the peptide from different samples by reporter ions, but also to identify the peptide it is derived from. Because the ions related to isobaric labeling may act as noise in database searching, the MS/MS spectrum should be preprocessed before peptide or protein identification. In this article, we demonstrate that there are a lot of high-frequency, high-abundance isobaric related ions in the MS/MS spectrum, and removing isobaric related ions combined with deisotoping and deconvolution in MS/MS preprocessing procedures significantly improves the peptide/protein identification sensitivity. The user-friendly software package TurboRaw2MGF (v2.0) has been implemented for converting raw TIC data files to mascot generic format files and can be downloaded for free from https://github.com/shengqh/RCPA.Tools/releases as part of the software suite ProteomicsTools. The data have been deposited to the ProteomeXchange with identifier PXD000994. PMID:25435543

Studies into the phenolic patterns of different tissues of pineapple (Ananas comosus [L.] Merr.) infructescence by HPLC-DAD-ESI-MS (n) and GC-MS analysis.

PubMed

Steingass, Christof B; Glock, Mona P; Schweiggert, Ralf M; Carle, Reinhold

2015-08-01

In a comprehensive study, more than 60 phenolic compounds were detected in methanolic extracts from different tissues of pineapple infructescence by high-performance liquid chromatography with diode array detection and electrospray ionisation multiple-stage mass spectrometry (HPLC-DAD-ESI-MS (n) ) as well as by gas chromatography-mass spectrometry (GC-MS). The analytical workflow combining both methods revealed numerous compounds assigned for the first time as pineapple constituents by their mass fragmentations. Pineapple crown tissue was characterised by depsides of p-coumaric and ferulic acid. In contrast, major phenolic compounds in pineapple pulp extracts were assigned to diverse S-p-coumaryl, S-coniferyl and S-sinapyl derivatives of glutathione, N-L-γ-glutamyl-L-cysteine and L-cysteine, which were also identified in the peel. The latter was additionally characterised by elevated concentrations of p-coumaric, ferulic and caffeic acid depsides and glycerides, respectively. Two peel-specific cyanidin hexosides were found. Elevated concentrations of isomeric N,N'-diferuloylspermidines may be a useful tool for the detection of fraudulent peel usage for pineapple juice production. Mass fragmentation pathways of characteristic pineapple constituents are proposed, and their putative biological functions are discussed.

Recommendations for the generation, quantification, storage and handling of peptides used for mass spectrometry-based assays

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

Hoofnagle, Andrew N.; Whiteaker, Jeffrey R.; Carr, Steven A.

2015-12-30

The Clinical Proteomic Tumor Analysis Consortium (1) (CPTAC) of the National Cancer Institute (NCI) is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of robust technologies and workflows for the quantitative measurements of proteins. The Assay Development Working Group of the CPTAC Program aims to foster broad uptake of targeted mass spectrometry-based assays employing isotopically labeled peptides for confident assignment and quantification, including multiple reaction monitoring (MRM; also referred to as Selected Reaction Monitoring), parallel reaction monitoring (PRM), and other targeted methods.

Ambient ionisation mass spectrometry for in situ analysis of intact proteins

PubMed Central

Kocurek, Klaudia I.; Griffiths, Rian L.

2018-01-01

Abstract Ambient surface mass spectrometry is an emerging field which shows great promise for the analysis of biomolecules directly from their biological substrate. In this article, we describe ambient ionisation mass spectrometry techniques for the in situ analysis of intact proteins. As a broad approach, the analysis of intact proteins offers unique advantages for the determination of primary sequence variations and posttranslational modifications, as well as interrogation of tertiary and quaternary structure and protein‐protein/ligand interactions. In situ analysis of intact proteins offers the potential to couple these advantages with information relating to their biological environment, for example, their spatial distributions within healthy and diseased tissues. Here, we describe the techniques most commonly applied to in situ protein analysis (liquid extraction surface analysis, continuous flow liquid microjunction surface sampling, nano desorption electrospray ionisation, and desorption electrospray ionisation), their advantages, and limitations and describe their applications to date. We also discuss the incorporation of ion mobility spectrometry techniques (high field asymmetric waveform ion mobility spectrometry and travelling wave ion mobility spectrometry) into ambient workflows. Finally, future directions for the field are discussed. PMID:29607564

Optimal turnaround time for direct identification of microorganisms by mass spectrometry in blood culture.

PubMed

Randazzo, Adrien; Simon, Marc; Goffinet, Pierre; Classen, Jean-François; Hougardy, Nicolas; Pierre, Pascal; Kinzinger, Philippe; Mauel, Etienne; Goffinet, Jean-Sébastien

2016-11-01

During the past few years, several studies describing direct identification of bacteria from blood culture using mass spectrometry have been published. These methods cannot, however, be easily integrated into a common laboratory workflow because of the high hands-on time they require. In this paper, we propose a new method of identification with a short hands-on time and a turnaround time shorter than 15min. Positive blood bottles were homogenised and 600μL of blood were transferred to an Eppendorf tube where 600μL of lysis buffer were added. After homogenisation, a centrifugation step of 4min at 10,500g was performed and the supernatant was discarded. The pellet was then washed and loaded in quadruplicate into wells of a Vitek® MS-DS plate. Each well was covered with a saturated matrix solution and a MALDI-TOF mass spectrometry analysis was performed. Species were identified using the software Myla 3.2.0-2. We analysed 266 positive blood culture bottles. A microorganism grew in 261 cultures, while five bottles remained sterile after 48h of incubation in subculture. Our method reaches a probability of detection at the species level of 77.8% (203/261) with a positive predictive value of 99.5% (202/203). We developed a new method for the identification of microorganisms using mass spectrometry, directly performed from a positive blood culture. This method has short hands-on time and turnaround time and can easily take place in the workflow of a laboratory, with comparable results in performance with other methods reported in the literature. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitating Organoleptic Volatile Phenols in Smoke-Exposed Vitis vinifera Berries.

PubMed

Noestheden, Matthew; Thiessen, Katelyn; Dennis, Eric G; Tiet, Ben; Zandberg, Wesley F

2017-09-27

Accurate methods for quantitating volatile phenols (i.e., guaiacol, syringol, 4-ethylphenol, etc.) in smoke-exposed Vitis vinifera berries prior to fermentation are needed to predict the likelihood of perceptible smoke taint following vinification. Reported here is a complete, cross-validated analytical workflow to accurately quantitate free and glycosidically bound volatile phenols in smoke-exposed berries using liquid-liquid extraction, acid-mediated hydrolysis, and gas chromatography-tandem mass spectrometry. The reported workflow addresses critical gaps in existing methods for volatile phenols that impact quantitative accuracy, most notably the effect of injection port temperature and the variability in acid-mediated hydrolytic procedures currently used. Addressing these deficiencies will help the wine industry make accurate, informed decisions when producing wines from smoke-exposed berries.

Molecules and elements for quantitative bioanalysis: The allure of using electrospray, MALDI, and ICP mass spectrometry side-by-side.

PubMed

Linscheid, Michael W

2018-03-30

To understand biological processes, not only reliable identification, but quantification of constituents in biological processes play a pivotal role. This is especially true for the proteome: protein quantification must follow protein identification, since sometimes minute changes in abundance tell the real tale. To obtain quantitative data, many sophisticated strategies using electrospray and MALDI mass spectrometry (MS) have been developed in recent years. All of them have advantages and limitations. Several years ago, we started to work on strategies, which are principally capable to overcome some of these limits. The fundamental idea is to use elemental signals as a measure for quantities. We began by replacing the radioactive 32 P with the "cold" natural 31 P to quantify modified nucleotides and phosphorylated peptides and proteins and later used tagging strategies for quantification of proteins more generally. To do this, we introduced Inductively Coupled Plasma Mass Spectrometry (ICP-MS) into the bioanalytical workflows, allowing not only reliable and sensitive detection but also quantification based on isotope dilution absolute measurements using poly-isotopic elements. The detection capability of ICP-MS becomes particularly attractive with heavy metals. The covalently bound proteins tags developed in our group are based on the well-known DOTA chelate complex (1,4,7,10-tetraazacyclododecane-N,N',N″,N‴-tetraacetic acid) carrying ions of lanthanoides as metal core. In this review, I will outline the development of this mutual assistance between molecular and elemental mass spectrometry and discuss the scope and limitations particularly of peptide and protein quantification. The lanthanoide tags provide low detection limits, but offer multiplexing capabilities due to the number of very similar lanthanoides and their isotopes. With isotope dilution comes previously unknown accuracy. Separation techniques such as electrophoresis and HPLC were used and just slightly adapted workflows, already in use for quantification in bioanalysis. Imaging mass spectrometry (MSI) with MALDI and laser ablation ICP-MS complemented the range of application in recent years. © 2018 Wiley Periodicals, Inc.

Bioprofiling of unknown antibiotics in herbal extracts: Development of a streamlined direct bioautography using Bacillus subtilis linked to mass spectrometry.

PubMed

Jamshidi-Aidji, Maryam; Morlock, Gertrud E

2015-11-13

Working in the field of profiling and identification of bioactive compounds in herbal extracts is faced with the challenge that common chromatographic methods do not directly link to bioactive compounds. Direct bioautography, the combination of TLC/HPTLC with bioassays, linked to structure elucidating techniques is demonstrated to overcome this challenge. The combination of TLC and Bacillus subtilis bioassay was already demonstrated to detect the antibiotics in samples. However, previous studies in this field were faced with some challenges, like being time-consuming, leading not to a homogenous plate background or being restricted to a non-acidic mobile phase. In this study, these aspects were investigated and a streamlined HPTLC-B. subtilis bioassay was developed that generated a homogenous plate background, which was crucial to yield a good baseline for biodensitometry. Two commonly used broths for B. subtilis and a self-designed medium were compared with regard to their capability of detection and baseline noise. The workflow developed allowed the use of acidic mobile phases for the first time. To prove this, 20 herbal extracts were screened for antimicrobial substances developed in parallel with an acidic mobile phase. The main antimicrobial substance in Salvia officinalis tincture detected was further characterized by microchemical reactions, Aliivibrio fischeri, β-glucosidase and acetylcholinesterase (bio)assays as well as mass spectrometry. Scientists looking for new herbal-based medicine may benefit from this time-saving and streamlined bioactivity profiling. Copyright © 2015 Elsevier B.V. All rights reserved.

Isotopic studies of metabolic systems by mass spectrometry: using Pascal's triangle to produce biological standards with fully controlled labeling patterns.

PubMed

Millard, Pierre; Massou, Stéphane; Portais, Jean-Charles; Létisse, Fabien

2014-10-21

Mass spectrometry (MS) is widely used for isotopic studies of metabolism in which detailed information about biochemical processes is obtained from the analysis of isotope incorporation into metabolites. The biological value of such experiments is dependent on the accuracy of the isotopic measurements. Using MS, isotopologue distributions are measured from the quantitative analysis of isotopic clusters. These measurements are prone to various biases, which can occur during the experimental workflow and/or MS analysis. The lack of relevant standards limits investigations of the quality of the measured isotopologue distributions. To meet that need, we developed a complete theoretical and experimental framework for the biological production of metabolites with fully controlled and predictable labeling patterns. This strategy is valid for different isotopes and different types of metabolisms and organisms, and was applied to two model microorganisms, Pichia augusta and Escherichia coli, cultivated on (13)C-labeled methanol and acetate as sole carbon source, respectively. The isotopic composition of the substrates was designed to obtain samples in which the isotopologue distribution of all the metabolites should give the binomial coefficients found in Pascal's triangle. The strategy was validated on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform by quantifying the complete isotopologue distributions of different intracellular metabolites, which were in close agreement with predictions. This strategy can be used to evaluate entire experimental workflows (from sampling to data processing) or different analytical platforms in the context of isotope labeling experiments.

Using MALDI-IMS and MRM to stablish a pipeline for discovery and validation of tumor neovasculature biomarker candidates. — EDRN Public Portal

Cancer.gov

In an effort to circumvent the limitations associated with biomarker discovery workflows involving cell lines and cell cultures, histology-directed MALDI protein profiling and imaging mass spectrometry will be used for identification of vascular endothelial biomarkers suitable for early prostate cancer detection by CEUS targeted molecular imaging

Cloud parallel processing of tandem mass spectrometry based proteomics data.

PubMed

Mohammed, Yassene; Mostovenko, Ekaterina; Henneman, Alex A; Marissen, Rob J; Deelder, André M; Palmblad, Magnus

2012-10-05

Data analysis in mass spectrometry based proteomics struggles to keep pace with the advances in instrumentation and the increasing rate of data acquisition. Analyzing this data involves multiple steps requiring diverse software, using different algorithms and data formats. Speed and performance of the mass spectral search engines are continuously improving, although not necessarily as needed to face the challenges of acquired big data. Improving and parallelizing the search algorithms is one possibility; data decomposition presents another, simpler strategy for introducing parallelism. We describe a general method for parallelizing identification of tandem mass spectra using data decomposition that keeps the search engine intact and wraps the parallelization around it. We introduce two algorithms for decomposing mzXML files and recomposing resulting pepXML files. This makes the approach applicable to different search engines, including those relying on sequence databases and those searching spectral libraries. We use cloud computing to deliver the computational power and scientific workflow engines to interface and automate the different processing steps. We show how to leverage these technologies to achieve faster data analysis in proteomics and present three scientific workflows for parallel database as well as spectral library search using our data decomposition programs, X!Tandem and SpectraST.

Determining the Composition and Stability of Protein Complexes Using an Integrated Label-Free and Stable Isotope Labeling Strategy

PubMed Central

Greco, Todd M.; Guise, Amanda J.; Cristea, Ileana M.

2016-01-01

In biological systems, proteins catalyze the fundamental reactions that underlie all cellular functions, including metabolic processes and cell survival and death pathways. These biochemical reactions are rarely accomplished alone. Rather, they involve a concerted effect from many proteins that may operate in a directed signaling pathway and/or may physically associate in a complex to achieve a specific enzymatic activity. Therefore, defining the composition and regulation of protein complexes is critical for understanding cellular functions. In this chapter, we describe an approach that uses quantitative mass spectrometry (MS) to assess the specificity and the relative stability of protein interactions. Isolation of protein complexes from mammalian cells is performed by rapid immunoaffinity purification, and followed by in-solution digestion and high-resolution mass spectrometry analysis. We employ complementary quantitative MS workflows to assess the specificity of protein interactions using label-free MS and statistical analysis, and the relative stability of the interactions using a metabolic labeling technique. For each candidate protein interaction, scores from the two workflows can be correlated to minimize nonspecific background and profile protein complex composition and relative stability. PMID:26867737

Discovery and characterization of a photo-oxidative histidine-histidine cross-link in IgG1 antibody utilizing ¹⁸O-labeling and mass spectrometry.

PubMed

Liu, Min; Zhang, Zhongqi; Cheetham, Janet; Ren, Da; Zhou, Zhaohui Sunny

2014-05-20

A novel photo-oxidative cross-linking between two histidines (His-His) has been discovered and characterized in an IgG1 antibody via the workflow of XChem-Finder, (18)O labeling and mass spectrometry (Anal. Chem. 2013, 85, 5900-5908). Its structure was elucidated by peptide mapping with multiple proteases with various specificities (e.g., trypsin, Asp-N, and GluC combined with trypsin or Asp-N) and mass spectrometry with complementary fragmentation modes (e.g., collision-induced dissociation (CID) and electron-transfer dissociation (ETD)). Our data indicated that cross-linking occurred across two identical conserved histidine residues on two separate heavy chains in the hinge region, which is highly flexible and solvent accessible. On the basis of model studies with short peptides, it has been proposed that singlet oxygen reacts with the histidyl imidazole ring to form an endoperoxide and then converted to the 2-oxo-histidine (2-oxo-His) and His+32 intermediates, the latter is subject to a nucleophilic attack by the unmodified histidine; and finally, elimination of a water molecule leads to the final adduct with a net mass increase of 14 Da. Our findings are consistent with this mechanism. Successful discovery of cross-linked His-His again demonstrates the broad applicability and utility of our XChem-Finder approach in the discovery and elucidation of protein cross-linking, particularly without a priori knowledge of the chemical nature and site of cross-linking.

CLMSVault: A Software Suite for Protein Cross-Linking Mass-Spectrometry Data Analysis and Visualization.

PubMed

Courcelles, Mathieu; Coulombe-Huntington, Jasmin; Cossette, Émilie; Gingras, Anne-Claude; Thibault, Pierre; Tyers, Mike

2017-07-07

Protein cross-linking mass spectrometry (CL-MS) enables the sensitive detection of protein interactions and the inference of protein complex topology. The detection of chemical cross-links between protein residues can identify intra- and interprotein contact sites or provide physical constraints for molecular modeling of protein structure. Recent innovations in cross-linker design, sample preparation, mass spectrometry, and software tools have significantly improved CL-MS approaches. Although a number of algorithms now exist for the identification of cross-linked peptides from mass spectral data, a dearth of user-friendly analysis tools represent a practical bottleneck to the broad adoption of the approach. To facilitate the analysis of CL-MS data, we developed CLMSVault, a software suite designed to leverage existing CL-MS algorithms and provide intuitive and flexible tools for cross-platform data interpretation. CLMSVault stores and combines complementary information obtained from different cross-linkers and search algorithms. CLMSVault provides filtering, comparison, and visualization tools to support CL-MS analyses and includes a workflow for label-free quantification of cross-linked peptides. An embedded 3D viewer enables the visualization of quantitative data and the mapping of cross-linked sites onto PDB structural models. We demonstrate the application of CLMSVault for the analysis of a noncovalent Cdc34-ubiquitin protein complex cross-linked under different conditions. CLMSVault is open-source software (available at https://gitlab.com/courcelm/clmsvault.git ), and a live demo is available at http://democlmsvault.tyerslab.com/ .

Creating reference gene annotation for the mouse C57BL6/J genome assembly.

PubMed

Mudge, Jonathan M; Harrow, Jennifer

2015-10-01

Annotation on the reference genome of the C57BL6/J mouse has been an ongoing project ever since the draft genome was first published. Initially, the principle focus was on the identification of all protein-coding genes, although today the importance of describing long non-coding RNAs, small RNAs, and pseudogenes is recognized. Here, we describe the progress of the GENCODE mouse annotation project, which combines manual annotation from the HAVANA group with Ensembl computational annotation, alongside experimental and in silico validation pipelines from other members of the consortium. We discuss the more recent incorporation of next-generation sequencing datasets into this workflow, including the usage of mass-spectrometry data to potentially identify novel protein-coding genes. Finally, we will outline how the C57BL6/J genebuild can be used to gain insights into the variant sites that distinguish different mouse strains and species.

Warpgroup: increased precision of metabolomic data processing by consensus integration bound analysis

PubMed Central

Mahieu, Nathaniel G.; Spalding, Jonathan L.; Patti, Gary J.

2016-01-01

Motivation: Current informatic techniques for processing raw chromatography/mass spectrometry data break down under several common, non-ideal conditions. Importantly, hydrophilic liquid interaction chromatography (a key separation technology for metabolomics) produces data which are especially challenging to process. We identify three critical points of failure in current informatic workflows: compound specific drift, integration region variance, and naive missing value imputation. We implement the Warpgroup algorithm to address these challenges. Results: Warpgroup adds peak subregion detection, consensus integration bound detection, and intelligent missing value imputation steps to the conventional informatic workflow. When compared with the conventional workflow, Warpgroup made major improvements to the processed data. The coefficient of variation for peaks detected in replicate injections of a complex Escherichia Coli extract were halved (a reduction of 19%). Integration regions across samples were much more robust. Additionally, many signals lost by the conventional workflow were ‘rescued’ by the Warpgroup refinement, thereby resulting in greater analyte coverage in the processed data. Availability and implementation: Warpgroup is an open source R package available on GitHub at github.com/nathaniel-mahieu/warpgroup. The package includes example data and XCMS compatibility wrappers for ease of use. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: nathaniel.mahieu@wustl.edu or gjpattij@wustl.edu PMID:26424859

Protein kinetic signatures of the remodeling heart following isoproterenol stimulation.

PubMed

Lam, Maggie P Y; Wang, Ding; Lau, Edward; Liem, David A; Kim, Allen K; Ng, Dominic C M; Liang, Xiangbo; Bleakley, Brian J; Liu, Chenguang; Tabaraki, Jason D; Cadeiras, Martin; Wang, Yibin; Deng, Mario C; Ping, Peipei

2014-04-01

Protein temporal dynamics play a critical role in time-dimensional pathophysiological processes, including the gradual cardiac remodeling that occurs in early-stage heart failure. Methods for quantitative assessments of protein kinetics are lacking, and despite knowledge gained from single-protein studies, integrative views of the coordinated behavior of multiple proteins in cardiac remodeling are scarce. Here, we developed a workflow that integrates deuterium oxide (2H2O) labeling, high-resolution mass spectrometry (MS), and custom computational methods to systematically interrogate in vivo protein turnover. Using this workflow, we characterized the in vivo turnover kinetics of 2,964 proteins in a mouse model of β-adrenergic-induced cardiac remodeling. The data provided a quantitative and longitudinal view of cardiac remodeling at the molecular level, revealing widespread kinetic regulations in calcium signaling, metabolism, proteostasis, and mitochondrial dynamics. We translated the workflow to human studies, creating a reference dataset of 496 plasma protein turnover rates from 4 healthy adults. The approach is applicable to short, minimal label enrichment and can be performed on as little as a single biopsy, thereby overcoming critical obstacles to clinical investigations. The protein turnover quantitation experiments and computational workflow described here should be widely applicable to large-scale biomolecular investigations of human disease mechanisms with a temporal perspective.

Protein kinetic signatures of the remodeling heart following isoproterenol stimulation

PubMed Central

Lam, Maggie P.Y.; Wang, Ding; Lau, Edward; Liem, David A.; Kim, Allen K.; Ng, Dominic C.M.; Liang, Xiangbo; Bleakley, Brian J.; Liu, Chenguang; Tabaraki, Jason D.; Cadeiras, Martin; Wang, Yibin; Deng, Mario C.; Ping, Peipei

2014-01-01

Protein temporal dynamics play a critical role in time-dimensional pathophysiological processes, including the gradual cardiac remodeling that occurs in early-stage heart failure. Methods for quantitative assessments of protein kinetics are lacking, and despite knowledge gained from single-protein studies, integrative views of the coordinated behavior of multiple proteins in cardiac remodeling are scarce. Here, we developed a workflow that integrates deuterium oxide (2H2O) labeling, high-resolution mass spectrometry (MS), and custom computational methods to systematically interrogate in vivo protein turnover. Using this workflow, we characterized the in vivo turnover kinetics of 2,964 proteins in a mouse model of β-adrenergic–induced cardiac remodeling. The data provided a quantitative and longitudinal view of cardiac remodeling at the molecular level, revealing widespread kinetic regulations in calcium signaling, metabolism, proteostasis, and mitochondrial dynamics. We translated the workflow to human studies, creating a reference dataset of 496 plasma protein turnover rates from 4 healthy adults. The approach is applicable to short, minimal label enrichment and can be performed on as little as a single biopsy, thereby overcoming critical obstacles to clinical investigations. The protein turnover quantitation experiments and computational workflow described here should be widely applicable to large-scale biomolecular investigations of human disease mechanisms with a temporal perspective. PMID:24614109

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.

File formats commonly used in mass spectrometry proteomics.

PubMed

Deutsch, Eric W

2012-12-01

The application of mass spectrometry (MS) to the analysis of proteomes has enabled the high-throughput identification and abundance measurement of hundreds to thousands of proteins per experiment. However, the formidable informatics challenge associated with analyzing MS data has required a wide variety of data file formats to encode the complex data types associated with MS workflows. These formats encompass the encoding of input instruction for instruments, output products of the instruments, and several levels of information and results used by and produced by the informatics analysis tools. A brief overview of the most common file formats in use today is presented here, along with a discussion of related topics.

Standardization approaches in absolute quantitative proteomics with mass spectrometry.

PubMed

Calderón-Celis, Francisco; Encinar, Jorge Ruiz; Sanz-Medel, Alfredo

2017-07-31

Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and elemental) proteomics is provided in this review. © 2017 Wiley Periodicals, Inc.

Lessons from implementing a combined workflow-informatics system for diabetes management.

PubMed

Zai, Adrian H; Grant, Richard W; Estey, Greg; Lester, William T; Andrews, Carl T; Yee, Ronnie; Mort, Elizabeth; Chueh, Henry C

2008-01-01

Shortcomings surrounding the care of patients with diabetes have been attributed largely to a fragmented, disorganized, and duplicative health care system that focuses more on acute conditions and complications than on managing chronic disease. To address these shortcomings, we developed a diabetes registry population management application to change the way our staff manages patients with diabetes. Use of this new application has helped us coordinate the responsibilities for intervening and monitoring patients in the registry among different users. Our experiences using this combined workflow-informatics intervention system suggest that integrating a chronic disease registry into clinical workflow for the treatment of chronic conditions creates a useful and efficient tool for managing disease.

Unbiased and targeted mass spectrometry for the HDL proteome.

PubMed

Singh, Sasha A; Aikawa, Masanori

2017-02-01

Mass spectrometry is an ever evolving technology that is equipped with a variety of tools for protein research. Some lipoprotein studies, especially those pertaining to HDL biology, have been exploiting the versatility of mass spectrometry to understand HDL function through its proteome. Despite the role of mass spectrometry in advancing research as a whole, however, the technology remains obscure to those without hands on experience, but still wishing to understand it. In this review, we walk the reader through the coevolution of common mass spectrometry workflows and HDL research, starting from the basic unbiased mass spectrometry methods used to profile the HDL proteome to the most recent targeted methods that have enabled an unprecedented view of HDL metabolism. Unbiased global proteomics have demonstrated that the HDL proteome is organized into subgroups across the HDL size fractions providing further evidence that HDL functional heterogeneity is in part governed by its varying protein constituents. Parallel reaction monitoring, a novel targeted mass spectrometry method, was used to monitor the metabolism of HDL apolipoproteins in humans and revealed that apolipoproteins contained within the same HDL size fraction exhibit diverse metabolic properties. Mass spectrometry provides a variety of tools and strategies to facilitate understanding, through its proteins, the complex biology of HDL.

Digitization workflows for flat sheets and packets of plants, algae, and fungi1

PubMed Central

Nelson, Gil; Sweeney, Patrick; Wallace, Lisa E.; Rabeler, Richard K.; Allard, Dorothy; Brown, Herrick; Carter, J. Richard; Denslow, Michael W.; Ellwood, Elizabeth R.; Germain-Aubrey, Charlotte C.; Gilbert, Ed; Gillespie, Emily; Goertzen, Leslie R.; Legler, Ben; Marchant, D. Blaine; Marsico, Travis D.; Morris, Ashley B.; Murrell, Zack; Nazaire, Mare; Neefus, Chris; Oberreiter, Shanna; Paul, Deborah; Ruhfel, Brad R.; Sasek, Thomas; Shaw, Joey; Soltis, Pamela S.; Watson, Kimberly; Weeks, Andrea; Mast, Austin R.

2015-01-01

Effective workflows are essential components in the digitization of biodiversity specimen collections. To date, no comprehensive, community-vetted workflows have been published for digitizing flat sheets and packets of plants, algae, and fungi, even though latest estimates suggest that only 33% of herbarium specimens have been digitally transcribed, 54% of herbaria use a specimen database, and 24% are imaging specimens. In 2012, iDigBio, the U.S. National Science Foundation’s (NSF) coordinating center and national resource for the digitization of public, nonfederal U.S. collections, launched several working groups to address this deficiency. Here, we report the development of 14 workflow modules with 7–36 tasks each. These workflows represent the combined work of approximately 35 curators, directors, and collections managers representing more than 30 herbaria, including 15 NSF-supported plant-related Thematic Collections Networks and collaboratives. The workflows are provided for download as Portable Document Format (PDF) and Microsoft Word files. Customization of these workflows for specific institutional implementation is encouraged. PMID:26421256

Collision induced unfolding of isolated proteins in the gas phase: past, present, and future.

PubMed

Dixit, Sugyan M; Polasky, Daniel A; Ruotolo, Brandon T

2018-02-01

Rapidly characterizing the three-dimensional structures of proteins and the multimeric machines they form remains one of the great challenges facing modern biological and medical sciences. Ion mobility-mass spectrometry based techniques are playing an expanding role in characterizing these functional complexes, especially in drug discovery and development workflows. Despite this expansion, ion mobility-mass spectrometry faces many challenges, especially in the context of detecting small differences in protein tertiary structure that bear functional consequences. Collision induced unfolding is an ion mobility-mass spectrometry method that enables the rapid differentiation of subtly-different protein isoforms based on their unfolding patterns and stabilities. In this review, we summarize the modern implementation of such gas-phase unfolding experiments and provide an overview of recent developments in both methods and applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

LipidFinder: A computational workflow for discovery of lipids identifies eicosanoid-phosphoinositides in platelets

PubMed Central

O’Connor, Anne; Brasher, Christopher J.; Slatter, David A.; Meckelmann, Sven W.; Hawksworth, Jade I.; Allen, Stuart M.; O’Donnell, Valerie B.

2017-01-01

Accurate and high-quality curation of lipidomic datasets generated from plasma, cells, or tissues is becoming essential for cell biology investigations and biomarker discovery for personalized medicine. However, a major challenge lies in removing artifacts otherwise mistakenly interpreted as real lipids from large mass spectrometry files (>60 K features), while retaining genuine ions in the dataset. This requires powerful informatics tools; however, available workflows have not been tailored specifically for lipidomics, particularly discovery research. We designed LipidFinder, an open-source Python workflow. An algorithm is included that optimizes analysis based on users’ own data, and outputs are screened against online databases and categorized into LIPID MAPS classes. LipidFinder outperformed three widely used metabolomics packages using data from human platelets. We show a family of three 12-hydroxyeicosatetraenoic acid phosphoinositides (16:0/, 18:1/, 18:0/12-HETE-PI) generated by thrombin-activated platelets, indicating crosstalk between eicosanoid and phosphoinositide pathways in human cells. The software is available on GitHub (https://github.com/cjbrasher/LipidFinder), with full userguides. PMID:28405621

Basic design of MRM assays for peptide quantification.

PubMed

James, Andrew; Jorgensen, Claus

2010-01-01

With the recent availability and accessibility of mass spectrometry for basic and clinical research, the requirement for stable, sensitive, and reproducible assays to specifically detect proteins of interest has increased. Multiple reaction monitoring (MRM) or selective reaction monitoring (SRM) is a highly selective, sensitive, and robust assay to monitor the presence and amount of biomolecules. Until recently, MRM was typically used for the detection of drugs and other biomolecules from body fluids. With increased focus on biomarkers and systems biology approaches, researchers in the proteomics field have taken advantage of this approach. In this chapter, we will introduce the reader to the basic principle of designing and optimizing an MRM workflow. We provide examples of MRM workflows for standard proteomic samples and provide suggestions for the reader who is interested in using MRM for quantification.

Proteomics data exchange and storage: the need for common standards and public repositories.

PubMed

Jiménez, Rafael C; Vizcaíno, Juan Antonio

2013-01-01

Both the existence of data standards and public databases or repositories have been key factors behind the development of the existing "omics" approaches. In this book chapter we first review the main existing mass spectrometry (MS)-based proteomics resources: PRIDE, PeptideAtlas, GPMDB, and Tranche. Second, we report on the current status of the different proteomics data standards developed by the Proteomics Standards Initiative (PSI): the formats mzML, mzIdentML, mzQuantML, TraML, and PSI-MI XML are then reviewed. Finally, we present an easy way to query and access MS proteomics data in the PRIDE database, as a representative of the existing repositories, using the workflow management system (WMS) tool Taverna. Two different publicly available workflows are explained and described.

LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data.

PubMed

Koelmel, Jeremy P; Kroeger, Nicholas M; Ulmer, Candice Z; Bowden, John A; Patterson, Rainey E; Cochran, Jason A; Beecher, Christopher W W; Garrett, Timothy J; Yost, Richard A

2017-07-10

Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry experiments, including imaging experiments, direct infusion experiments, and experiments employing liquid chromatography. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and determining etiology of disease by covering a greater portion of the lipidome and using annotation which does not over-report biologically relevant structural details of identified lipid molecules.

Tracing Cationic Nutrients from Xylem into Stem Tissue of French Bean by Stable Isotope Tracers and Cryo-Secondary Ion Mass Spectrometry[W][OA

PubMed Central

Metzner, Ralf; Schneider, Heike Ursula; Breuer, Uwe; Thorpe, Michael Robert; Schurr, Ulrich; Schroeder, Walter Heinz

2010-01-01

Fluxes of mineral nutrients in the xylem are strongly influenced by interactions with the surrounding stem tissues and are probably regulated by them. Toward a mechanistic understanding of these interactions, we applied stable isotope tracers of magnesium, potassium, and calcium continuously to the transpiration stream of cut bean (Phaseolus vulgaris) shoots to study their radial exchange at the cell and tissue level with stem tissues between pith and phloem. For isotope localization, we combined sample preparation with secondary ion mass spectrometry in a completely cryogenic workflow. After 20 min of application, tracers were readily detectable to various degrees in all tissues. The xylem parenchyma near the vessels exchanged freely with the vessels, its nutrient elements reaching a steady state of strong exchange with elements in the vessels within 20 min, mainly via apoplastic pathways. A slow exchange between vessels and cambium and phloem suggested that they are separated from the xylem, parenchyma, and pith, possibly by an apoplastic barrier to diffusion for nutrients (as for carbohydrates). There was little difference in these distributions when tracers were applied directly to intact xylem via a microcapillary, suggesting that xylem tension had little effect on radial exchange of these nutrients and that their movement was mainly diffusive. PMID:19965970

Identification of autoantigens in body fluids by combining pull-downs and organic precipitations of intact immune complexes with quantitative label-free mass spectrometry.

PubMed

Merl, Juliane; Deeg, Cornelia A; Swadzba, Margarete E; Ueffing, Marius; Hauck, Stefanie M

2013-12-06

Most autoimmune diseases are multifactorial diseases and are caused by the immunological reaction against a number of autoantigens. Key for understanding autoimmune pathologies is the knowledge of the targeted autoantigens, both initially and during disease progression. We present an approach for autoantigen identification based on isolation of intact autoantibody-antigen complexes from body fluids. After organic precipitation of high molecular weight proteins and free immunoglobulins, released autoantigens were identified by quantitative label-free liquid chromatography mass spectrometry. We confirmed feasibility of target enrichment and identification from highly complex body fluid proteomes by spiking of a predefined antibody-antigen complex at low level of abundance. As a proof of principle, we studied the blinding disease autoimmune uveitis, which is caused by autoreactive T-cells attacking the inner eye and is accompanied by autoantibodies. We identified three novel autoantigens in the spontaneous animal model equine recurrent uveitis (secreted acidic phosphoprotein osteopontin, extracellular matrix protein 1, and metalloproteinase inhibitor 2) and confirmed the presence of the corresponding autoantibodies in 15-25% of patient samples by enzyme-linked immunosorbent assay. Thus, this workflow led to the identification of novel autoantigens in autoimmune uveitis and may provide a versatile and useful tool to identify autoantigens in other autoimmune diseases in the future.

PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets.

PubMed

Martínez-Bartolomé, Salvador; Medina-Aunon, J Alberto; López-García, Miguel Ángel; González-Tejedo, Carmen; Prieto, Gorka; Navajas, Rosana; Salazar-Donate, Emilio; Fernández-Costa, Carolina; Yates, John R; Albar, Juan Pablo

2018-04-06

Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. (1) As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom .

Metabolomics by Gas Chromatography-Mass Spectrometry: the combination of targeted and untargeted profiling

PubMed Central

Fiehn, Oliver

2016-01-01

Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small molecular metabolites (<650 daltons), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds volatile enough for gas chromatography. This unit shows that on GC-MS- based metabolomics easily allows integrating targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated, standardized standard operating procedures, GC-MS can identify and semi-quantify over 200 compounds per study in human body fluids (e.g., plasma, urine or stool) samples. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to liquid chromatography-MS untargeted profiling (LC-MS). Hence, GC-MS is a mature technology that not only uses classic detectors (‘quadrupole’) but also target mass spectrometers (‘triple quadrupole’) and accurate mass instruments (‘quadrupole-time of flight’). This unit covers the following aspects of GC-MS-based metabolomics: (i) sample preparation from mammalian samples, (ii) acquisition of data, (iii) quality control, and (iv) data processing. PMID:27038389

Development of a data independent acquisition mass spectrometry workflow to enable glycopeptide analysis without predefined glycan compositional knowledge.

PubMed

Lin, Chi-Hung; Krisp, Christoph; Packer, Nicolle H; Molloy, Mark P

2018-02-10

Glycoproteomics investigates glycan moieties in a site specific manner to reveal the functional roles of protein glycosylation. Identification of glycopeptides from data-dependent acquisition (DDA) relies on high quality MS/MS spectra of glycopeptide precursors and often requires manual validation to ensure confident assignments. In this study, we investigated pseudo-MRM (MRM-HR) and data-independent acquisition (DIA) as alternative acquisition strategies for glycopeptide analysis. These approaches allow data acquisition over the full MS/MS scan range allowing data re-analysis post-acquisition, without data re-acquisition. The advantage of MRM-HR over DDA for N-glycopeptide detection was demonstrated from targeted analysis of bovine fetuin where all three N-glycosylation sites were detected, which was not the case with DDA. To overcome the duty cycle limitation of MRM-HR acquisition needed for analysis of complex samples such as plasma we trialed DIA. This allowed development of a targeted DIA method to identify N-glycopeptides without pre-defined knowledge of the glycan composition, thus providing the potential to identify N-glycopeptides with unexpected structures. This workflow was demonstrated by detection of 59 N-glycosylation sites from 41 glycoproteins from a HILIC enriched human plasma tryptic digest. 21 glycoforms of IgG1 glycopeptides were identified including two truncated structures that are rarely reported. We developed a data-independent mass spectrometry workflow to identify specific glycopeptides from complex biological mixtures. The novelty is that this approach does not require glycan composition to be pre-defined, thereby allowing glycopeptides carrying unexpected glycans to be identified. This is demonstrated through the analysis of immunoglobulins in human plasma where we detected two IgG1 glycoforms that are rarely observed. Copyright © 2017 Elsevier B.V. All rights reserved.

High-volume workflow management in the ITN/FBI system

NASA Astrophysics Data System (ADS)

Paulson, Thomas L.

1997-02-01

The Identification Tasking and Networking (ITN) Federal Bureau of Investigation system will manage the processing of more than 70,000 submissions per day. The workflow manager controls the routing of each submission through a combination of automated and manual processing steps whose exact sequence is dynamically determined by the results at each step. For most submissions, one or more of the steps involve the visual comparison of fingerprint images. The ITN workflow manager is implemented within a scaleable client/server architecture. The paper describes the key aspects of the ITN workflow manager design which allow the high volume of daily processing to be successfully accomplished.

chemalot and chemalot_knime: Command line programs as workflow tools for drug discovery.

PubMed

Lee, Man-Ling; Aliagas, Ignacio; Feng, Jianwen A; Gabriel, Thomas; O'Donnell, T J; Sellers, Benjamin D; Wiswedel, Bernd; Gobbi, Alberto

2017-06-12

Analyzing files containing chemical information is at the core of cheminformatics. Each analysis may require a unique workflow. This paper describes the chemalot and chemalot_knime open source packages. Chemalot is a set of command line programs with a wide range of functionalities for cheminformatics. The chemalot_knime package allows command line programs that read and write SD files from stdin and to stdout to be wrapped into KNIME nodes. The combination of chemalot and chemalot_knime not only facilitates the compilation and maintenance of sequences of command line programs but also allows KNIME workflows to take advantage of the compute power of a LINUX cluster. Use of the command line programs is demonstrated in three different workflow examples: (1) A workflow to create a data file with project-relevant data for structure-activity or property analysis and other type of investigations, (2) The creation of a quantitative structure-property-relationship model using the command line programs via KNIME nodes, and (3) The analysis of strain energy in small molecule ligand conformations from the Protein Data Bank database. The chemalot and chemalot_knime packages provide lightweight and powerful tools for many tasks in cheminformatics. They are easily integrated with other open source and commercial command line tools and can be combined to build new and even more powerful tools. The chemalot_knime package facilitates the generation and maintenance of user-defined command line workflows, taking advantage of the graphical design capabilities in KNIME. Graphical abstract Example KNIME workflow with chemalot nodes and the corresponding command line pipe.

An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics.

PubMed

Wang, Yang; Feng, Ruibing; He, Chengwei; Su, Huanxing; Ma, Huan; Wan, Jian-Bo

2018-08-05

The narrow linear range and the limited scan time of the given ion make the quantification of the features challenging in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics with the full-scan mode. And metabolite identification is another bottleneck of untargeted analysis owing to the difficulty of acquiring MS/MS information of most metabolites detected. In this study, an integrated workflow was proposed using the newly established multiple ion monitoring mode with time-staggered ion lists (tsMIM) and target-directed data-dependent acquisition with time-staggered ion lists (tsDDA) to improve data acquisition and metabolite identification in UHPLC/Q-TOF MS-based untargeted metabolomics. Compared to the conventional untargeted metabolomics, the proprosed workflow exhibited the better repeatability before and after data normalization. After selecting features with the significant change by statistical analysis, MS/MS information of all these features can be obtained by tsDDA analysis to facilitate metabolite identification. Using time-staggered ion lists, the workflow is more sensitive in data acquisition, especially for the low-abundant features. Moreover, the metabolites with low abundance tend to be wrongly integrated and triggered by full scan-based untargeted analysis with MS E acquisition mode, which can be greatly improved by the proposed workflow. The integrated workflow was also successfully applied to discover serum biosignatures for the genetic modification of fat-1 in mice, which indicated its practicability and great potential in future metabolomics studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification of Molds by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

PubMed Central

Posteraro, Brunella

2016-01-01

ABSTRACT Although to a lesser extent than diagnostic bacteriology, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has recently revolutionized the diagnostic mycology workflow. With regard to filamentous fungi (or molds), the precise recognition of pathogenic species is important for rapid diagnosis and appropriate treatment, especially for invasive diseases. This review summarizes the current experience with MALDI-TOF MS-based identification of common and uncommon mold species of Aspergillus, Fusarium, Mucorales, dimorphic fungi, and dermatophytes. This experience clearly shows that MALDI-TOF MS holds promise as a fast and accurate identification tool, particularly with common species or typical strains of filamentous fungi. PMID:27807151

File Formats Commonly Used in Mass Spectrometry Proteomics*

PubMed Central

Deutsch, Eric W.

2012-01-01

The application of mass spectrometry (MS) to the analysis of proteomes has enabled the high-throughput identification and abundance measurement of hundreds to thousands of proteins per experiment. However, the formidable informatics challenge associated with analyzing MS data has required a wide variety of data file formats to encode the complex data types associated with MS workflows. These formats encompass the encoding of input instruction for instruments, output products of the instruments, and several levels of information and results used by and produced by the informatics analysis tools. A brief overview of the most common file formats in use today is presented here, along with a discussion of related topics. PMID:22956731

LFQProfiler and RNP(xl): Open-Source Tools for Label-Free Quantification and Protein-RNA Cross-Linking Integrated into Proteome Discoverer.

PubMed

Veit, Johannes; Sachsenberg, Timo; Chernev, Aleksandar; Aicheler, Fabian; Urlaub, Henning; Kohlbacher, Oliver

2016-09-02

Modern mass spectrometry setups used in today's proteomics studies generate vast amounts of raw data, calling for highly efficient data processing and analysis tools. Software for analyzing these data is either monolithic (easy to use, but sometimes too rigid) or workflow-driven (easy to customize, but sometimes complex). Thermo Proteome Discoverer (PD) is a powerful software for workflow-driven data analysis in proteomics which, in our eyes, achieves a good trade-off between flexibility and usability. Here, we present two open-source plugins for PD providing additional functionality: LFQProfiler for label-free quantification of peptides and proteins, and RNP(xl) for UV-induced peptide-RNA cross-linking data analysis. LFQProfiler interacts with existing PD nodes for peptide identification and validation and takes care of the entire quantitative part of the workflow. We show that it performs at least on par with other state-of-the-art software solutions for label-free quantification in a recently published benchmark ( Ramus, C.; J. Proteomics 2016 , 132 , 51 - 62 ). The second workflow, RNP(xl), represents the first software solution to date for identification of peptide-RNA cross-links including automatic localization of the cross-links at amino acid resolution and localization scoring. It comes with a customized integrated cross-link fragment spectrum viewer for convenient manual inspection and validation of the results.

Unparalleled sample treatment throughput for proteomics workflows relying on ultrasonic energy.

PubMed

Jorge, Susana; Araújo, J E; Pimentel-Santos, F M; Branco, Jaime C; Santos, Hugo M; Lodeiro, Carlos; Capelo, J L

2018-02-01

We report on the new microplate horn ultrasonic device as a powerful tool to speed proteomics workflows with unparalleled throughput. 96 complex proteomes were digested at the same time in 4min. Variables such as ultrasonication time, ultrasonication amplitude, and protein to enzyme ratio were optimized. The "classic" method relying on overnight protein digestion (12h) and the sonoreactor-based method were also employed for comparative purposes. We found the protein digestion efficiency homogeneously distributed in the entire microplate horn surface using the following conditions: 4min sonication time and 25% amplitude. Using this approach, patients with lymphoma and myeloma were classified using principal component analysis and a 2D gel-mass spectrometry based approach. Furthermore, we demonstrate the excellent performance by using MALDI-mass spectrometry based profiling as a fast way to classify patients with rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Finally, the speed and simplicity of this method were demonstrated by clustering 90 patients with knee osteoarthritis disease (30), with a prosthesis (30, control group) and healthy individuals (30) with no history of joint disease. Overall, the new approach allows profiling a disease in just one week while allows to match the minimalism rules as outlined by Halls. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of the differentially expressed low molecular weight peptides in human serum via an N-terminal isotope labeling technique combining nano-liquid chromatography/matrix-assisted laser desorption/ionization mass spectrometry.

PubMed

Leng, Jiapeng; Zhu, Dong; Wu, Duojiao; Zhu, Tongyu; Zhao, Ningwei; Guo, Yinlong

2012-11-15

Peptidomics analysis of human serum is challenging due to the low abundance of serum peptides and interference from the complex matrix. This study analyzed the differentially expressed (DE) low molecular weight peptides in human serum integrating a DMPITC-based N-terminal isotope labeling technique with nano-liquid chromatography and matrix-assisted laser desorption/ionization mass spectrometry (nano-LC/MALDI-MS). The workflow introduced a [d(6)]-4,6-dimethoxypyrimidine-2-isothiocyanate (DMPITC)-labeled mixture of aliquots from test samples as the internal standard. The spiked [d(0)]-DMPITC-labeled samples were separated by nano-LC then spotted on the MALDI target. Both quantitative and qualitative studies for serum peptides were achieved based on the isotope-labeled peaks. The DMPITC labeling technique combined with nano-LC/MALDI-MS not only minimized the errors in peptide quantitation, but also allowed convenient recognition of the labeled peptides due to the 6 Da mass difference. The data showed that the entire research procedure as well as the subsequent data analysis method were effective, reproducible, and sensitive for the analysis of DE serum peptides. This study successfully established a research model for DE serum peptides using DMPITC-based N-terminal isotope labeling and nano-LC/MALDI-MS. Application of the DMPITC-based N-terminal labeling technique is expected to provide a promising tool for the investigation of peptides in vivo, especially for the analysis of DE peptides under different biological conditions. Copyright © 2012 John Wiley & Sons, Ltd.

In-Depth Characterization of Protein Disulfide Bonds by Online Liquid Chromatography-Electrochemistry-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Switzar, Linda; Nicolardi, Simone; Rutten, Julie W.; Oberstein, Saskia A. J. Lesnik; Aartsma-Rus, Annemieke; van der Burgt, Yuri E. M.

2016-01-01

Disulfide bonds are an important class of protein post-translational modifications, yet this structurally crucial modification type is commonly overlooked in mass spectrometry (MS)-based proteomics approaches. Recently, the benefits of online electrochemistry-assisted reduction of protein S-S bonds prior to MS analysis were exemplified by successful characterization of disulfide bonds in peptides and small proteins. In the current study, we have combined liquid chromatography (LC) with electrochemistry (EC) and mass analysis by Fourier transform ion cyclotron resonance (FTICR) MS in an online LC-EC-MS platform to characterize protein disulfide bonds in a bottom-up proteomics workflow. A key advantage of a LC-based strategy is the use of the retention time in identifying both intra- and interpeptide disulfide bonds. This is demonstrated by performing two sequential analyses of a certain protein digest, once without and once with electrochemical reduction. In this way, the "parent" disulfide-linked peptide detected in the first run has a retention time-based correlation with the EC-reduced peptides detected in the second run, thus simplifying disulfide bond mapping. Using this platform, both inter- and intra-disulfide-linked peptides were characterized in two different proteins, ß-lactoglobulin and ribonuclease B. In order to prevent disulfide reshuffling during the digestion process, proteins were digested at a relatively low pH, using (a combination of) the high specificity proteases trypsin and Glu-C. With this approach, disulfide bonds in ß-lactoglobulin and ribonuclease B were comprehensively identified and localized, showing that online LC-EC-MS is a useful tool for the characterization of protein disulfide bonds.

Ion Mobility Derived Collision Cross Sections to Support Metabolomics Applications

PubMed Central

2015-01-01

Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC–TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches. PMID:24640936

Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

PubMed

Baran, Richard; Northen, Trent R

2013-10-15

Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

Hippocampal lipid differences in Alzheimer's disease: a human brain study using matrix-assisted laser desorption/ionization-imaging mass spectrometry.

PubMed

Mendis, Lakshini H S; Grey, Angus C; Faull, Richard L M; Curtis, Maurice A

2016-10-01

Alzheimer's disease (AD), the leading cause of dementia, is pathologically characterized by β-amyloid plaques and tau tangles. However, there is also evidence of lipid dyshomeostasis-mediated AD pathology. Given the structural diversity of lipids, mass spectrometry is a useful tool for studying lipid changes in AD. Although there have been a few studies investigating lipid changes in the human hippocampus in particular, there are few reports on how lipids change in each hippocampal subfield (e.g., Cornu Ammonis [CA] 1-4, dentate gyrus [DG] etc.). Since each subfield has its own function, we postulated that there could be lipid changes that are unique to each. We used matrix-assisted laser desorption/ionization-imaging mass spectrometry to investigate specific lipid changes in each subfield in AD. Data from the hippocampus region of six age- and gender-matched normal and AD pairs were analyzed with SCiLS lab 2015b software (SCiLS GmbH, Germany; RRID:SCR_014426), using an analysis workflow developed in-house. Hematoxylin, eosin, and luxol fast blue staining were used to precisely delineate each anatomical hippocampal subfield. Putative lipid identities, which were consistent with published data, were assigned using MS/MS. Both positively and negatively charged lipid ion species were abundantly detected in normal and AD tissue. While the distribution pattern of lipids did not change in AD, the abundance of some lipids changed, consistent with trends that have been previously reported. However, our results indicated that the majority of these lipid changes specifically occur in the CA1 region. Additionally, there were many lipid changes that were specific to the DG. Matrix-assisted laser desorption/ionization-imaging mass spectrometry and our analysis workflow provide a novel method to investigate specific lipid changes in hippocampal subfields. Future work will focus on elucidating the role that specific lipid differences in each subfield play in AD pathogenesis.

P185-M Protein Identification and Validation of Results in Workflows that Integrate over Various Instruments, Datasets, Search Engines

PubMed Central

Hufnagel, P.; Glandorf, J.; Körting, G.; Jabs, W.; Schweiger-Hufnagel, U.; Hahner, S.; Lubeck, M.; Suckau, D.

2007-01-01

Analysis of complex proteomes often results in long protein lists, but falls short in measuring the validity of identification and quantification results on a greater number of proteins. Biological and technical replicates are mandatory, as is the combination of the MS data from various workflows (gels, 1D-LC, 2D-LC), instruments (TOF/TOF, trap, qTOF or FTMS), and search engines. We describe a database-driven study that combines two workflows, two mass spectrometers, and four search engines with protein identification following a decoy database strategy. The sample was a tryptically digested lysate (10,000 cells) of a human colorectal cancer cell line. Data from two LC-MALDI-TOF/TOF runs and a 2D-LC-ESI-trap run using capillary and nano-LC columns were submitted to the proteomics software platform ProteinScape. The combined MALDI data and the ESI data were searched using Mascot (Matrix Science), Phenyx (GeneBio), ProteinSolver (Bruker and Protagen), and Sequest (Thermo) against a decoy database generated from IPI-human in order to obtain one protein list across all workflows and search engines at a defined maximum false-positive rate of 5%. ProteinScape combined the data to one LC-MALDI and one LC-ESI dataset. The initial separate searches from the two combined datasets generated eight independent peptide lists. These were compiled into an integrated protein list using the ProteinExtractor algorithm. An initial evaluation of the generated data led to the identification of approximately 1200 proteins. Result integration on a peptide level allowed discrimination of protein isoforms that would not have been possible with a mere combination of protein lists.

Modelling and analysis of workflow for lean supply chains

NASA Astrophysics Data System (ADS)

Ma, Jinping; Wang, Kanliang; Xu, Lida

2011-11-01

Cross-organisational workflow systems are a component of enterprise information systems which support collaborative business process among organisations in supply chain. Currently, the majority of workflow systems is developed in perspectives of information modelling without considering actual requirements of supply chain management. In this article, we focus on the modelling and analysis of the cross-organisational workflow systems in the context of lean supply chain (LSC) using Petri nets. First, the article describes the assumed conditions of cross-organisation workflow net according to the idea of LSC and then discusses the standardisation of collaborating business process between organisations in the context of LSC. Second, the concept of labelled time Petri nets (LTPNs) is defined through combining labelled Petri nets with time Petri nets, and the concept of labelled time workflow nets (LTWNs) is also defined based on LTPNs. Cross-organisational labelled time workflow nets (CLTWNs) is then defined based on LTWNs. Third, the article proposes the notion of OR-silent CLTWNS and a verifying approach to the soundness of LTWNs and CLTWNs. Finally, this article illustrates how to use the proposed method by a simple example. The purpose of this research is to establish a formal method of modelling and analysis of workflow systems for LSC. This study initiates a new perspective of research on cross-organisational workflow management and promotes operation management of LSC in real world settings.

Fabrication of Zirconia-Reinforced Lithium Silicate Ceramic Restorations Using a Complete Digital Workflow

PubMed Central

Rödiger, Matthias; Ziebolz, Dirk; Schmidt, Anne-Kathrin

2015-01-01

This case report describes the fabrication of monolithic all-ceramic restorations using zirconia-reinforced lithium silicate (ZLS) ceramics. The use of powder-free intraoral scanner, generative fabrication technology of the working model, and CAD/CAM of the restorations in the dental laboratory allows a completely digitized workflow. The newly introduced ZLS ceramics offer a unique combination of fracture strength (>420 MPa), excellent optical properties, and optimum polishing characteristics, thus making them an interesting material option for monolithic restorations in the digital workflow. PMID:26509088

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

PubMed

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

2012-12-07

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

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

PubMed Central

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

2015-01-01

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

Application of MALDI-TOF mass spectrometry in clinical diagnostic microbiology.

PubMed

De Carolis, Elena; Vella, Antonietta; Vaccaro, Luisa; Torelli, Riccardo; Spanu, Teresa; Fiori, Barbara; Posteraro, Brunella; Sanguinetti, Maurizio

2014-09-12

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently emerged as a powerful technique for identification of microorganisms, changing the workflow of well-established laboratories so that its impact on microbiological diagnostics has been unparalleled. In comparison with conventional identification methods that rely on biochemical tests and require long incubation procedures, MALDI-TOF MS has the advantage of identifying bacteria and fungi directly from colonies grown on culture plates in a few minutes and with simple procedures. Numerous studies on different systems available demonstrate the reliability and accuracy of the method, and new frontiers have been explored besides microbial species level identification, such as direct identification of pathogens from positive blood cultures, subtyping, and drug susceptibility detection.

Identification of Lasso Peptide Topologies Using Native Nanoelectrospray Ionization-Trapped Ion Mobility Spectrometry-Mass Spectrometry.

PubMed

Dit Fouque, Kevin Jeanne; Moreno, Javier; Hegemann, Julian D; Zirah, Séverine; Rebuffat, Sylvie; Fernandez-Lima, Francisco

2018-04-17

Lasso peptides are a fascinating class of bioactive ribosomal natural products characterized by a mechanically interlocked topology. In contrast to their branched-cyclic forms, lasso peptides have higher stability and have become a scaffold for drug development. However, the identification and separation of lasso peptides from their unthreaded topoisomers (branched-cyclic peptides) is analytically challenging since the higher stability is based solely on differences in their tertiary structures. In the present work, a fast and effective workflow is proposed for the separation and identification of lasso from branched cyclic peptides based on differences in their mobility space under native nanoelectrospray ionization-trapped ion mobility spectrometry-mass spectrometry (nESI-TIMS-MS). The high mobility resolving power ( R) of TIMS resulted in the separation of lasso and branched-cyclic topoisomers ( R up to 250, 150 needed on average). The advantages of alkali metalation reagents (e.g., Na, K, and Cs salts) as a way to increase the analytical power of TIMS is demonstrated for topoisomers with similar mobilities as protonated species, efficiently turning the metal ion adduction into additional separation dimensions.

Recent advances in applying mass spectrometry and systems biology to determine brain dynamics.

PubMed

Scifo, Enzo; Calza, Giulio; Fuhrmann, Martin; Soliymani, Rabah; Baumann, Marc; Lalowski, Maciej

2017-06-01

Neurological disorders encompass various pathologies which disrupt normal brain physiology and function. Poor understanding of their underlying molecular mechanisms and their societal burden argues for the necessity of novel prevention strategies, early diagnostic techniques and alternative treatment options to reduce the scale of their expected increase. Areas covered: This review scrutinizes mass spectrometry based approaches used to investigate brain dynamics in various conditions, including neurodegenerative and neuropsychiatric disorders. Different proteomics workflows for isolation/enrichment of specific cell populations or brain regions, sample processing; mass spectrometry technologies, for differential proteome quantitation, analysis of post-translational modifications and imaging approaches in the brain are critically deliberated. Future directions, including analysis of cellular sub-compartments, targeted MS platforms (selected/parallel reaction monitoring) and use of mass cytometry are also discussed. Expert commentary: Here, we summarize and evaluate current mass spectrometry based approaches for determining brain dynamics in health and diseases states, with a focus on neurological disorders. Furthermore, we provide insight on current trends and new MS technologies with potential to improve this analysis.

A multi-method approach toward de novo glycan characterization: a Man-5 case study.

PubMed

Prien, Justin M; Prater, Bradley D; Cockrill, Steven L

2010-05-01

Regulatory agencies' expectations for biotherapeutic approval are becoming more stringent with regard to product characterization, where minor species as low as 0.1% of a given profile are typically identified. The mission of this manuscript is to demonstrate a multi-method approach toward de novo glycan characterization and quantitation, including minor species at or approaching the 0.1% benchmark. Recently, unexpected isomers of the Man(5)GlcNAc(2) (M(5)) were reported (Prien JM, Ashline DJ, Lapadula AJ, Zhang H, Reinhold VN. 2009. The high mannose glycans from bovine ribonuclease B isomer characterization by ion trap mass spectrometry (MS). J Am Soc Mass Spectrom. 20:539-556). In the current study, quantitative analysis of these isomers found in commercial M(5) standard demonstrated that they are in low abundance (<1% of the total) and therefore an exemplary "litmus test" for minor species characterization. A simple workflow devised around three core well-established analytical procedures: (1) fluorescence derivatization; (2) online rapid resolution reversed-phase separation coupled with negative-mode sequential mass spectrometry (RRRP-(-)-MS(n)); and (3) permethylation derivatization with nanospray sequential mass spectrometry (NSI-MS(n)) provides comprehensive glycan structural determination. All methods have limitations; however, a multi-method workflow is an at-line stopgap/solution which mitigates each method's individual shortcoming(s) providing greater opportunity for more comprehensive characterization. This manuscript is the first to demonstrate quantitative chromatographic separation of the M(5) isomers and the use of a commercially available stable isotope variant of 2-aminobenzoic acid to detect and chromatographically resolve multiple M(5) isomers in bovine ribonuclease B. With this multi-method approach, we have the capabilities to comprehensively characterize a biotherapeutic's glycan array in a de novo manner, including structural isomers at >/=0.1% of the total chromatographic peak area.

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS

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

Gritsenko, Marina A.; Xu, Zhe; Liu, Tao

Comprehensive, quantitative information on abundances of proteins and their post-translational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labelling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification andmore » quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples, and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.« less

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS.

PubMed

Gritsenko, Marina A; Xu, Zhe; Liu, Tao; Smith, Richard D

2016-01-01

Comprehensive, quantitative information on abundances of proteins and their posttranslational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labeling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification.

PubMed

Beirnaert, Charlie; Meysman, Pieter; Vu, Trung Nghia; Hermans, Nina; Apers, Sandra; Pieters, Luc; Covaci, Adrian; Laukens, Kris

2018-03-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).

speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification

PubMed Central

Pieters, Luc; Covaci, Adrian

2018-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq). PMID:29494588

MZmine 2 Data-Preprocessing To Enhance Molecular Networking Reliability.

PubMed

Olivon, Florent; Grelier, Gwendal; Roussi, Fanny; Litaudon, Marc; Touboul, David

2017-08-01

Molecular networking is becoming more and more popular into the metabolomic community to organize tandem mass spectrometry (MS 2 ) data. Even though this approach allows the treatment and comparison of large data sets, several drawbacks related to the MS-Cluster tool routinely used on the Global Natural Product Social Molecular Networking platform (GNPS) limit its potential. MS-Cluster cannot distinguish between chromatography well-resolved isomers as retention times are not taken into account. Annotation with predicted chemical formulas is also not implemented and semiquantification is only based on the number of MS 2 scans. We propose to introduce a data-preprocessing workflow including the preliminary data treatment by MZmine 2 followed by a homemade Python script freely available to the community that clears the major previously mentioned GNPS drawbacks. The efficiency of this workflow is exemplified with the analysis of six fractions of increasing polarities obtained from a sequential supercritical CO 2 extraction of Stillingia lineata leaves.

Ion Mobility-Derived Collision Cross Section As an Additional Measure for Lipid Fingerprinting and Identification

PubMed Central

2014-01-01

Despite recent advances in analytical and computational chemistry, lipid identification remains a significant challenge in lipidomics. Ion-mobility spectrometry provides an accurate measure of the molecules’ rotationally averaged collision cross-section (CCS) in the gas phase and is thus related to ionic shape. Here, we investigate the use of CCS as a highly specific molecular descriptor for identifying lipids in biological samples. Using traveling wave ion mobility mass spectrometry (MS), we measured the CCS values of over 200 lipids within multiple chemical classes. CCS values derived from ion mobility were not affected by instrument settings or chromatographic conditions, and they were highly reproducible on instruments located in independent laboratories (interlaboratory RSD < 3% for 98% of molecules). CCS values were used as additional molecular descriptors to identify brain lipids using a variety of traditional lipidomic approaches. The addition of CCS improved the reproducibility of analysis in a liquid chromatography-MS workflow and maximized the separation of isobaric species and the signal-to-noise ratio in direct-MS analyses (e.g., “shotgun” lipidomics and MS imaging). These results indicate that adding CCS to databases and lipidomics workflows increases the specificity and selectivity of analysis, thus improving the confidence in lipid identification compared to traditional analytical approaches. The CCS/accurate-mass database described here is made publicly available. PMID:25495617

Multidimensional fractionation is a requirement for quantitation of Golgi-resident glycosylation enzymes from cultured human cells.

PubMed

Lin, Chi-Hung; Chik, Jenny H L; Packer, Nicolle H; Molloy, Mark P

2015-02-06

Glycosylation results from the concerted action of glycosylation enzymes in the secretory pathway. In general, gene expression serves as the primary control mechanism, but post-translational fine-tuning of glycosylation enzyme functions is often necessary for efficient synthesis of specific glycan epitopes. While the field of glycomics has rapidly advanced, there lacks routine proteomic methods to measure expression of specific glycosylation enzymes needed to fill the gap between mRNA expression and the glycomic profile in a "reverse genomics" workflow. Toward developing this workflow we enriched Golgi membranes from two human colon cancer cell lines by sucrose density centrifugation and further mass-based fractionation by SDS-PAGE. We then applied mass spectrometry to demonstrate a doubling in the number of Golgi resident proteins identified, compared to the unenriched, low speed centrifuged supernatant of lysed cells. A total of 35 Golgi-resident glycosylation enzymes, of which 23 were glycosyltransferases, were identified making this the largest protein database so far of Golgi resident glycosylation enzymes experimentally identified in cultured human cells. We developed targeted mass spectrometry assays for specific quantitation of many of these glycosylation enzymes. Our results show that alterations in abundance of glycosylation enzymes at the protein level were generally consistent with the resultant glycomic profiles, but not necessarily with the corresponding glycosyltransferase mRNA expression as exemplified by the case of O-glycan core 1 T synthase.

The MaxQuant computational platform for mass spectrometry-based shotgun proteomics.

PubMed

Tyanova, Stefka; Temu, Tikira; Cox, Juergen

2016-12-01

MaxQuant is one of the most frequently used platforms for mass-spectrometry (MS)-based proteomics data analysis. Since its first release in 2008, it has grown substantially in functionality and can be used in conjunction with more MS platforms. Here we present an updated protocol covering the most important basic computational workflows, including those designed for quantitative label-free proteomics, MS1-level labeling and isobaric labeling techniques. This protocol presents a complete description of the parameters used in MaxQuant, as well as of the configuration options of its integrated search engine, Andromeda. This protocol update describes an adaptation of an existing protocol that substantially modifies the technique. Important concepts of shotgun proteomics and their implementation in MaxQuant are briefly reviewed, including different quantification strategies and the control of false-discovery rates (FDRs), as well as the analysis of post-translational modifications (PTMs). The MaxQuant output tables, which contain information about quantification of proteins and PTMs, are explained in detail. Furthermore, we provide a short version of the workflow that is applicable to data sets with simple and standard experimental designs. The MaxQuant algorithms are efficiently parallelized on multiple processors and scale well from desktop computers to servers with many cores. The software is written in C# and is freely available at http://www.maxquant.org.

Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry.

PubMed

Krämer, Lisa; Jäger, Christian; Trezzi, Jean-Pierre; Jacobs, Doris M; Hiller, Karsten

2018-02-14

Currently, changes in metabolic fluxes following consumption of stable isotope-enriched foods are usually limited to the analysis of postprandial kinetics of glucose. Kinetic information on a larger diversity of metabolites is often lacking, mainly due to the marginal percentage of fully isotopically enriched plant material in the administered food product, and hence, an even weaker 13 C enrichment in downstream plasma metabolites. Therefore, we developed an analytical workflow to determine weak 13 C enrichments of diverse plasma metabolites with conventional gas chromatography-mass spectrometry (GC-MS). The limit of quantification was increased by optimizing (1) the metabolite extraction from plasma, (2) the GC-MS measurement, and (3) most importantly, the computational data processing. We applied our workflow to study the catabolic dynamics of 13 C-enriched wheat bread in three human subjects. For that purpose, we collected time-resolved human plasma samples at 16 timepoints after the consumption of 13 C-labeled bread and quantified 13 C enrichment of 12 metabolites (glucose, lactate, alanine, glycine, serine, citrate, glutamate, glutamine, valine, isoleucine, tyrosine, and threonine). Based on isotopomer specific analysis, we were able to distinguish catabolic profiles of starch and protein hydrolysis. More generally, our study highlights that conventional GC-MS equipment is sufficient to detect isotope traces below 1% if an appropriate data processing is integrated.

PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association

PubMed Central

Ma, Jian; Casey, Cameron P.; Zheng, Xueyun; Ibrahim, Yehia M.; Wilkins, Christopher S.; Renslow, Ryan S.; Thomas, Dennis G.; Payne, Samuel H.; Monroe, Matthew E.; Smith, Richard D.; Teeguarden, Justin G.; Baker, Erin S.; Metz, Thomas O.

2017-01-01

Abstract Motivation: Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. Results: We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. Availability and implementation: PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library. Contact: erin.baker@pnnl.gov or thomas.metz@pnnl.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28505286

PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association.

PubMed

Ma, Jian; Casey, Cameron P; Zheng, Xueyun; Ibrahim, Yehia M; Wilkins, Christopher S; Renslow, Ryan S; Thomas, Dennis G; Payne, Samuel H; Monroe, Matthew E; Smith, Richard D; Teeguarden, Justin G; Baker, Erin S; Metz, Thomas O

2017-09-01

Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library . erin.baker@pnnl.gov or thomas.metz@pnnl.gov. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry

PubMed Central

Krämer, Lisa; Jäger, Christian; Jacobs, Doris M.; Hiller, Karsten

2018-01-01

Currently, changes in metabolic fluxes following consumption of stable isotope-enriched foods are usually limited to the analysis of postprandial kinetics of glucose. Kinetic information on a larger diversity of metabolites is often lacking, mainly due to the marginal percentage of fully isotopically enriched plant material in the administered food product, and hence, an even weaker 13C enrichment in downstream plasma metabolites. Therefore, we developed an analytical workflow to determine weak 13C enrichments of diverse plasma metabolites with conventional gas chromatography-mass spectrometry (GC-MS). The limit of quantification was increased by optimizing (1) the metabolite extraction from plasma, (2) the GC-MS measurement, and (3) most importantly, the computational data processing. We applied our workflow to study the catabolic dynamics of 13C-enriched wheat bread in three human subjects. For that purpose, we collected time-resolved human plasma samples at 16 timepoints after the consumption of 13C-labeled bread and quantified 13C enrichment of 12 metabolites (glucose, lactate, alanine, glycine, serine, citrate, glutamate, glutamine, valine, isoleucine, tyrosine, and threonine). Based on isotopomer specific analysis, we were able to distinguish catabolic profiles of starch and protein hydrolysis. More generally, our study highlights that conventional GC-MS equipment is sufficient to detect isotope traces below 1% if an appropriate data processing is integrated. PMID:29443915

An ontology-based framework for bioinformatics workflows.

PubMed

Digiampietri, Luciano A; Perez-Alcazar, Jose de J; Medeiros, Claudia Bauzer

2007-01-01

The proliferation of bioinformatics activities brings new challenges - how to understand and organise these resources, how to exchange and reuse successful experimental procedures, and to provide interoperability among data and tools. This paper describes an effort toward these directions. It is based on combining research on ontology management, AI and scientific workflows to design, reuse and annotate bioinformatics experiments. The resulting framework supports automatic or interactive composition of tasks based on AI planning techniques and takes advantage of ontologies to support the specification and annotation of bioinformatics workflows. We validate our proposal with a prototype running on real data.

Effect-directed fingerprints of 77 botanical extracts via a generic high-performance thin-layer chromatography method combined with assays and mass spectrometry.

PubMed

Krüger, S; Hüsken, L; Fornasari, R; Scainelli, I; Morlock, G E

2017-12-22

Quantitative effect-directed profiles of 77 industrially and freshly extracted botanicals like herbs, spices, vegetables and fruits, widely used as food ingredients, dietary supplements or traditional medicine, gave relevant information on their quality. It allows the assessment of food, dietary supplements and phytomedicines with regard to potential health-promoting activities. In contrary to sum parameter assays and targeted analysis, chromatography combined with effect-directed analysis allows fast assignment of single active compounds and evaluation of their contribution to the overall activity, originating from a food or botanical sample. High-performance thin-layer chromatography was hyphenated with UV/Vis/FLD detection and effect-directed analysis, using the 2,2-diphenyl-1-picrylhydrazyl radical, Gram-negative Aliivibrio fischeri, Gram-positive Bacillus subtilis, acetylcholinesterase and tyrosinase assays. Bioactive compounds of interest were eluted using an elution head-based interface and further characterized by electrospray ionization (high-resolution) mass spectrometry. This highly streamlined workflow resulted in a hyphenated HPTLC-UV/Vis/FLD-EDA-ESI + /ESI - -(HR)MS method. The excellent quantification power of the method was shown on three compounds. For rosmarinic acid, contents ranged from 4.5mg/g (rooibos) to 32.6mg/g (rosemary), for kaempferol-3-glucoside from 0.6mg/g (caraway) to 4.4mg/g (wine leaves), and for quercetin-3-glucoside from 1.1mg/g (hawthorn leaves) to 17.7mg/g (thyme). Three mean repeatabilities (%RSD) over 18 quantifications for the three compounds were ≤2.2% and the mean intermediate precision over three different days (%RSD, n=3) was 5.2%. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

PubMed

Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

2016-07-01

Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas Chromatography-Mass spectrometry.

Workflow and Electronic Health Records in Small Medical Practices

PubMed Central

Ramaiah, Mala; Subrahmanian, Eswaran; Sriram, Ram D; Lide, Bettijoyce B

2012-01-01

This paper analyzes the workflow and implementation of electronic health record (EHR) systems across different functions in small physician offices. We characterize the differences in the offices based on the levels of computerization in terms of workflow, sources of time delay, and barriers to using EHR systems to support the entire workflow. The study was based on a combination of questionnaires, interviews, in situ observations, and data collection efforts. This study was not intended to be a full-scale time-and-motion study with precise measurements but was intended to provide an overview of the potential sources of delays while performing office tasks. The study follows an interpretive model of case studies rather than a large-sample statistical survey of practices. To identify time-consuming tasks, workflow maps were created based on the aggregated data from the offices. The results from the study show that specialty physicians are more favorable toward adopting EHR systems than primary care physicians are. The barriers to adoption of EHR systems by primary care physicians can be attributed to the complex workflows that exist in primary care physician offices, leading to nonstandardized workflow structures and practices. Also, primary care physicians would benefit more from EHR systems if the systems could interact with external entities. PMID:22737096

A lectin HPLC method to enrich selectively-glycosylated peptides from complex biological samples.

PubMed

Johansen, Eric; Schilling, Birgit; Lerch, Michael; Niles, Richard K; Liu, Haichuan; Li, Bensheng; Allen, Simon; Hall, Steven C; Witkowska, H Ewa; Regnier, Fred E; Gibson, Bradford W; Fisher, Susan J; Drake, Penelope M

2009-10-01

Glycans are an important class of post-translational modifications. Typically found on secreted and extracellular molecules, glycan structures signal the internal status of the cell. Glycans on tumor cells tend to have abundant sialic acid and fucose moieties. We propose that these cancer-associated glycan variants be exploited for biomarker development aimed at diagnosing early-stage disease. Accordingly, we developed a mass spectrometry-based workflow that incorporates chromatography on affinity matrices formed from lectins, proteins that bind specific glycan structures. The lectins Sambucus nigra (SNA) and Aleuria aurantia (AAL), which bind sialic acid and fucose, respectively, were covalently coupled to POROS beads (Applied Biosystems) and packed into PEEK columns for high pressure liquid chromatography (HPLC). Briefly, plasma was depleted of the fourteen most abundant proteins using a multiple affinity removal system (MARS-14; Agilent). Depleted plasma was trypsin-digested and separated into flow-through and bound fractions by SNA or AAL HPLC. The fractions were treated with PNGaseF to remove N-linked glycans, and analyzed by LC-MS/MS on a QStar Elite. Data were analyzed using Mascot software. The experimental design included positive controls-fucosylated and sialylated human lactoferrin glycopeptides-and negative controls-high mannose glycopeptides from Saccharomyces cerevisiae-that were used to monitor the specificity of lectin capture. Key features of this workflow include the reproducibility derived from the HPLC format, the positive identification of the captured and PNGaseF-treated glycopeptides from their deamidated Asn-Xxx-Ser/Thr motifs, and quality assessment using glycoprotein standards. Protocol optimization also included determining the appropriate ratio of starting material to column capacity, identifying the most efficient capture and elution buffers, and monitoring the PNGaseF-treatment to ensure full deglycosylation. Future directions include using this workflow to perform mass spectrometry-based discovery experiments on plasma from breast cancer patients and control individuals.

First field demonstration of cloud datacenter workflow automation employing dynamic optical transport network resources under OpenStack and OpenFlow orchestration.

PubMed

Szyrkowiec, Thomas; Autenrieth, Achim; Gunning, Paul; Wright, Paul; Lord, Andrew; Elbers, Jörg-Peter; Lumb, Alan

2014-02-10

For the first time, we demonstrate the orchestration of elastic datacenter and inter-datacenter transport network resources using a combination of OpenStack and OpenFlow. Programmatic control allows a datacenter operator to dynamically request optical lightpaths from a transport network operator to accommodate rapid changes of inter-datacenter workflows.

ChIP-less analysis of chromatin states.

PubMed

Su, Zhangli; Boersma, Melissa D; Lee, Jin-Hee; Oliver, Samuel S; Liu, Shichong; Garcia, Benjamin A; Denu, John M

2014-01-01

Histone post-translational modifications (PTMs) are key epigenetic regulators in chromatin-based processes. Increasing evidence suggests that vast combinations of PTMs exist within chromatin histones. These complex patterns, rather than individual PTMs, are thought to define functional chromatin states. However, the ability to interrogate combinatorial histone PTM patterns at the nucleosome level has been limited by the lack of direct molecular tools. Here we demonstrate an efficient, quantitative, antibody-free, chromatin immunoprecipitation-less (ChIP-less) method for interrogating diverse epigenetic states. At the heart of the workflow are recombinant chromatin reader domains, which target distinct chromatin states with combinatorial PTM patterns. Utilizing a newly designed combinatorial histone peptide microarray, we showed that three reader domains (ATRX-ADD, ING2-PHD and AIRE-PHD) displayed greater specificity towards combinatorial PTM patterns than corresponding commercial histone antibodies. Such specific recognitions were employed to develop a chromatin reader-based affinity enrichment platform (matrix-assisted reader chromatin capture, or MARCC). We successfully applied the reader-based platform to capture unique chromatin states, which were quantitatively profiled by mass spectrometry to reveal interconnections between nucleosomal histone PTMs. Specifically, a highly enriched signature that harbored H3K4me0, H3K9me2/3, H3K79me0 and H4K20me2/3 within the same nucleosome was identified from chromatin enriched by ATRX-ADD. This newly reported PTM combination was enriched in heterochromatin, as revealed by the associated DNA. Our results suggest the broad utility of recombinant reader domains as an enrichment tool specific to combinatorial PTM patterns, which are difficult to probe directly by antibody-based approaches. The reader affinity platform is compatible with several downstream analyses to investigate the physical coexistence of nucleosomal PTM states associated with specific genomic loci. Collectively, the reader-based workflow will greatly facilitate our understanding of how distinct chromatin states and reader domains function in gene regulatory mechanisms.

Proteomic analysis of formalin-fixed paraffin embedded tissue by MALDI imaging mass spectrometry

PubMed Central

Casadonte, Rita; Caprioli, Richard M

2012-01-01

Archived formalin-fixed paraffin-embedded (FFPE) tissue collections represent a valuable informational resource for proteomic studies. Multiple FFPE core biopsies can be assembled in a single block to form tissue microarrays (TMAs). We describe a protocol for analyzing protein in FFPE -TMAs using matrix-assisted laser desorption/ionization (MAL DI) imaging mass spectrometry (IMS). The workflow incorporates an antigen retrieval step following deparaffinization, in situ trypsin digestion, matrix application and then mass spectrometry signal acquisition. The direct analysis of FFPE -TMA tissue using IMS allows direct analysis of multiple tissue samples in a single experiment without extraction and purification of proteins. The advantages of high speed and throughput, easy sample handling and excellent reproducibility make this technology a favorable approach for the proteomic analysis of clinical research cohorts with large sample numbers. For example, TMA analysis of 300 FFPE cores would typically require 6 h of total time through data acquisition, not including data analysis. PMID:22011652

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

NASA Astrophysics Data System (ADS)

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-06-01

Mass spectrometry-based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications.

Expanding Lipidome Coverage Using LC-MS/MS Data-Dependent Acquisition with Automated Exclusion List Generation

NASA Astrophysics Data System (ADS)

Koelmel, Jeremy P.; Kroeger, Nicholas M.; Gill, Emily L.; Ulmer, Candice Z.; Bowden, John A.; Patterson, Rainey E.; Yost, Richard A.; Garrett, Timothy J.

2017-05-01

Untargeted omics analyses aim to comprehensively characterize biomolecules within a biological system. Changes in the presence or quantity of these biomolecules can indicate important biological perturbations, such as those caused by disease. With current technological advancements, the entire genome can now be sequenced; however, in the burgeoning fields of lipidomics, only a subset of lipids can be identified. The recent emergence of high resolution tandem mass spectrometry (HR-MS/MS), in combination with ultra-high performance liquid chromatography, has resulted in an increased coverage of the lipidome. Nevertheless, identifications from MS/MS are generally limited by the number of precursors that can be selected for fragmentation during chromatographic elution. Therefore, we developed the software IE-Omics to automate iterative exclusion (IE), where selected precursors using data-dependent topN analyses are excluded in sequential injections. In each sequential injection, unique precursors are fragmented until HR-MS/MS spectra of all ions above a user-defined intensity threshold are acquired. IE-Omics was applied to lipidomic analyses in Red Cross plasma and substantia nigra tissue. Coverage of the lipidome was drastically improved using IE. When applying IE-Omics to Red Cross plasma and substantia nigra lipid extracts in positive ion mode, 69% and 40% more molecular identifications were obtained, respectively. In addition, applying IE-Omics to a lipidomics workflow increased the coverage of trace species, including odd-chained and short-chained diacylglycerides and oxidized lipid species. By increasing the coverage of the lipidome, applying IE to a lipidomics workflow increases the probability of finding biomarkers and provides additional information for determining etiology of disease.

Consistency of the Proteome in Primary Human Keratinocytes With Respect to Gender, Age, and Skin Localization*

PubMed Central

Sprenger, Adrian; Weber, Sebastian; Zarai, Mostafa; Engelke, Rudolf; Nascimento, Juliana M.; Gretzmeier, Christine; Hilpert, Martin; Boerries, Melanie; Has, Cristina; Busch, Hauke; Bruckner-Tuderman, Leena; Dengjel, Jörn

2013-01-01

Keratinocytes account for 95% of all cells of the epidermis, the stratified squamous epithelium forming the outer layer of the skin, in which a significant number of skin diseases takes root. Immortalized keratinocyte cell lines are often used as research model systems providing standardized, reproducible, and homogenous biological material. Apart from that, primary human keratinocytes are frequently used for medical studies because the skin provides an important route for drug administration and is readily accessible for biopsies. However, comparability of these cell systems is not known. Cell lines may undergo phenotypic shifts and may differ from the in vivo situation in important aspects. Primary cells, on the other hand, may vary in biological functions depending on gender and age of the donor and localization of the biopsy specimen. Here we employed metabolic labeling in combination with quantitative mass spectrometry-based proteomics to assess A431 and HaCaT cell lines for their suitability as model systems. Compared with cell lines, comprehensive profiling of the primary human keratinocyte proteome with respect to gender, age, and skin localization identified an unexpected high proteomic consistency. The data were analyzed by an improved ontology enrichment analysis workflow designed for the study of global proteomics experiments. It enables a quick, comprehensive and unbiased overview of altered biological phenomena and links experimental data to literature. We guide through our workflow, point out its advantages compared with other methods and apply it to visualize differences of cell lines compared with primary human keratinocytes. PMID:23722187

The variations in the nuclear proteome reveal new transcription factors and mechanisms involved in UV stress response in Pinus radiata.

PubMed

Pascual, Jesús; Alegre, Sara; Nagler, Matthias; Escandón, Mónica; Annacondia, María Luz; Weckwerth, Wolfram; Valledor, Luis; Cañal, María Jesús

2016-06-30

The importance of UV stress and its side-effects over the loss of plant productivity in forest species demands a deeper understanding of how pine trees respond to UV irradiation. Although the response to UV stress has been characterized at system and cellular levels, the dynamics within the nuclear proteome triggered by UV is still unknown despite that they are essential for gene expression and regulation of plant physiology. To fill this gap this work aims to characterize the variations in the nuclear proteome as a response to UV irradiation by using state-of-the-art mass spectrometry-based methods combined with novel bioinformatics workflows. The combination of SEQUEST, de novo sequencing, and novel annotation pipelines allowed cover sensing and transduction pathways, endoplasmic reticulum-related mechanisms and the regulation of chromatin dynamism and gene expression by histones, histone-like NF-Ys, and other transcription factors previously unrelated to this stress source, as well as the role of alternative splicing and other mechanisms involved in RNA translation and protein synthesis. The determination of 33 transcription factors, including NF-YB13, Pp005698_3 (NF-YB) and Pr009668_2 (WD-40), which are correlated to stress responsive mechanisms like an increased accumulation of photoprotective pigments and reduced photosynthesis, pointing them as strong candidate biomarkers for breeding programs aimed to improve UV resistance of pine trees. The description of the nuclear proteome of Pinus radiata combining a classic approach based on the use of SEQUEST and the use of a mass accuracy precursor alignment (MAPA) allowed an unprecedented protein coverage. This workflow provided the methodological basis for characterizing the changes in the nuclear proteome triggered by UV irradiation, allowing the depiction of the nuclear events involved in stress response and adaption. The relevance of some of the discovered proteins will suppose a major advance in stress biology field, also providing a set of transcription factors that can be considered as strong biomarker candidates to select trees more tolerant to UV radiation in forest upgrade programs. Copyright © 2016 Elsevier B.V. All rights reserved.

An Integrated Metabolomic and Genomic Mining Workflow To Uncover the Biosynthetic Potential of Bacteria

PubMed Central

Maansson, Maria; Vynne, Nikolaj G.; Klitgaard, Andreas; Nybo, Jane L.; Melchiorsen, Jette; Nguyen, Don D.; Sanchez, Laura M.; Ziemert, Nadine; Dorrestein, Pieter C.

2016-01-01

ABSTRACT Microorganisms are a rich source of bioactives; however, chemical identification is a major bottleneck. Strategies that can prioritize the most prolific microbial strains and novel compounds are of great interest. Here, we present an integrated approach to evaluate the biosynthetic richness in bacteria and mine the associated chemical diversity. Thirteen strains closely related to Pseudoalteromonas luteoviolacea isolated from all over the Earth were analyzed using an untargeted metabolomics strategy, and metabolomic profiles were correlated with whole-genome sequences of the strains. We found considerable diversity: only 2% of the chemical features and 7% of the biosynthetic genes were common to all strains, while 30% of all features and 24% of the genes were unique to single strains. The list of chemical features was reduced to 50 discriminating features using a genetic algorithm and support vector machines. Features were dereplicated by tandem mass spectrometry (MS/MS) networking to identify molecular families of the same biosynthetic origin, and the associated pathways were probed using comparative genomics. Most of the discriminating features were related to antibacterial compounds, including the thiomarinols that were reported from P. luteoviolacea here for the first time. By comparative genomics, we identified the biosynthetic cluster responsible for the production of the antibiotic indolmycin, which could not be predicted with standard methods. In conclusion, we present an efficient, integrative strategy for elucidating the chemical richness of a given set of bacteria and link the chemistry to biosynthetic genes. IMPORTANCE We here combine chemical analysis and genomics to probe for new bioactive secondary metabolites based on their pattern of distribution within bacterial species. We demonstrate the usefulness of this combined approach in a group of marine Gram-negative bacteria closely related to Pseudoalteromonas luteoviolacea, which is a species known to produce a broad spectrum of chemicals. The approach allowed us to identify new antibiotics and their associated biosynthetic pathways. Combining chemical analysis and genetics is an efficient “mining” workflow for identifying diverse pharmaceutical candidates in a broad range of microorganisms and therefore of great use in bioprospecting. PMID:27822535

Support for Taverna workflows in the VPH-Share cloud platform.

PubMed

Kasztelnik, Marek; Coto, Ernesto; Bubak, Marian; Malawski, Maciej; Nowakowski, Piotr; Arenas, Juan; Saglimbeni, Alfredo; Testi, Debora; Frangi, Alejandro F

2017-07-01

To address the increasing need for collaborative endeavours within the Virtual Physiological Human (VPH) community, the VPH-Share collaborative cloud platform allows researchers to expose and share sequences of complex biomedical processing tasks in the form of computational workflows. The Taverna Workflow System is a very popular tool for orchestrating complex biomedical & bioinformatics processing tasks in the VPH community. This paper describes the VPH-Share components that support the building and execution of Taverna workflows, and explains how they interact with other VPH-Share components to improve the capabilities of the VPH-Share platform. Taverna workflow support is delivered by the Atmosphere cloud management platform and the VPH-Share Taverna plugin. These components are explained in detail, along with the two main procedures that were developed to enable this seamless integration: workflow composition and execution. 1) Seamless integration of VPH-Share with other components and systems. 2) Extended range of different tools for workflows. 3) Successful integration of scientific workflows from other VPH projects. 4) Execution speed improvement for medical applications. The presented workflow integration provides VPH-Share users with a wide range of different possibilities to compose and execute workflows, such as desktop or online composition, online batch execution, multithreading, remote execution, etc. The specific advantages of each supported tool are presented, as are the roles of Atmosphere and the VPH-Share plugin within the VPH-Share project. The combination of the VPH-Share plugin and Atmosphere engenders the VPH-Share infrastructure with far more flexible, powerful and usable capabilities for the VPH-Share community. As both components can continue to evolve and improve independently, we acknowledge that further improvements are still to be developed and will be described. Copyright © 2017 Elsevier B.V. All rights reserved.

DIaaS: Data-Intensive workflows as a service - Enabling easy composition and deployment of data-intensive workflows on Virtual Research Environments

NASA Astrophysics Data System (ADS)

Filgueira, R.; Ferreira da Silva, R.; Deelman, E.; Atkinson, M.

2016-12-01

We present the Data-Intensive workflows as a Service (DIaaS) model for enabling easy data-intensive workflow composition and deployment on clouds using containers. DIaaS model backbone is Asterism, an integrated solution for running data-intensive stream-based applications on heterogeneous systems, which combines the benefits of dispel4py with Pegasus workflow systems. The stream-based executions of an Asterism workflow are managed by dispel4py, while the data movement between different e-Infrastructures, and the coordination of the application execution are automatically managed by Pegasus. DIaaS combines Asterism framework with Docker containers to provide an integrated, complete, easy-to-use, portable approach to run data-intensive workflows on distributed platforms. Three containers integrate the DIaaS model: a Pegasus node, and an MPI and an Apache Storm clusters. Container images are described as Dockerfiles (available online at http://github.com/dispel4py/pegasus_dispel4py), linked to Docker Hub for providing continuous integration (automated image builds), and image storing and sharing. In this model, all required software (workflow systems and execution engines) for running scientific applications are packed into the containers, which significantly reduces the effort (and possible human errors) required by scientists or VRE administrators to build such systems. The most common use of DIaaS will be to act as a backend of VREs or Scientific Gateways to run data-intensive applications, deploying cloud resources upon request. We have demonstrated the feasibility of DIaaS using the data-intensive seismic ambient noise cross-correlation application (Figure 1). The application preprocesses (Phase1) and cross-correlates (Phase2) traces from several seismic stations. The application is submitted via Pegasus (Container1), and Phase1 and Phase2 are executed in the MPI (Container2) and Storm (Container3) clusters respectively. Although both phases could be executed within the same environment, this setup demonstrates the flexibility of DIaaS to run applications across e-Infrastructures. In summary, DIaaS delivers specialized software to execute data-intensive applications in a scalable, efficient, and robust manner reducing the engineering time and computational cost.

Combining transrectal ultrasound and CT for image-guided adaptive brachytherapy of cervical cancer: Proof of concept.

PubMed

Nesvacil, Nicole; Schmid, Maximilian P; Pötter, Richard; Kronreif, Gernot; Kirisits, Christian

To investigate the feasibility of a treatment planning workflow for three-dimensional image-guided cervix cancer brachytherapy, combining volumetric transrectal ultrasound (TRUS) for target definition with CT for dose optimization to organs at risk (OARs), for settings with no access to MRI. A workflow for TRUS/CT-based volumetric treatment planning was developed, based on a customized system including ultrasound probe, stepper unit, and software for image volume acquisition. A full TRUS/CT-based workflow was simulated in a clinical case and compared with MR- or CT-only delineation. High-risk clinical target volume was delineated on TRUS, and OARs were delineated on CT. Manually defined tandem/ring applicator positions on TRUS and CT were used as a reference for rigid registration of the image volumes. Treatment plan optimization for TRUS target and CT organ volumes was performed and compared to MRI and CT target contours. TRUS/CT-based contouring, applicator reconstruction, image fusion, and treatment planning were feasible, and the full workflow could be successfully demonstrated. The TRUS/CT plan fulfilled all clinical planning aims. Dose-volume histogram evaluation of the TRUS/CT-optimized plan (high-risk clinical target volume D 90 , OARs D 2cm³ for) on different image modalities showed good agreement between dose values reported for TRUS/CT and MRI-only reference contours and large deviations for CT-only target parameters. A TRUS/CT-based workflow for full three-dimensional image-guided cervix brachytherapy treatment planning seems feasible and may be clinically comparable to MRI-based treatment planning. Further development to solve challenges with applicator definition in the TRUS volume is required before systematic applicability of this workflow. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Combined Species Identification and Drug Sensitivity Testing in Mycobacteria.

PubMed

Ceyssens, Pieter-Jan; Soetaert, Karine; Timke, Markus; Van den Bossche, An; Sparbier, Katrin; De Cremer, Koen; Kostrzewa, Markus; Hendrickx, Marijke; Mathys, Vanessa

2017-02-01

Species identification and drug susceptibility testing (DST) of mycobacteria are important yet complex processes traditionally reserved for reference laboratories. Recent technical improvements in matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has started to facilitate routine mycobacterial identifications in clinical laboratories. In this paper, we investigate the possibility of performing phenotypic MALDI-based DST in mycobacteriology using the recently described MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA). We randomly selected 72 clinical Mycobacterium tuberculosis and nontuberculous mycobacterial (NTM) strains, subjected them to MBT-ASTRA methodology, and compared its results to current gold-standard methods. Drug susceptibility was tested for rifampin, isoniazid, linezolid, and ethambutol (M. tuberculosis, n = 39), and clarithromycin and rifabutin (NTM, n = 33). Combined species identification was performed using the Biotyper Mycobacteria Library 4.0. Mycobacterium-specific MBT-ASTRA parameters were derived (calculation window, m/z 5,000 to 13,000, area under the curve [AUC] of >0.015, relative growth [RG] of <0.5; see the text for details). Using these settings, MBT-ASTRA analyses returned 175/177 M. tuberculosis and 65/66 NTM drug resistance profiles which corresponded to standard testing results. Turnaround times were not significantly different in M. tuberculosis testing, but the MBT-ASTRA method delivered on average a week faster than routine DST in NTM. Databases searches returned 90.4% correct species-level identifications, which increased to 98.6% when score thresholds were lowered to 1.65. In conclusion, the MBT-ASTRA technology holds promise to facilitate and fasten mycobacterial DST and to combine it directly with high-confidence species-level identifications. Given the ease of interpretation, its application in NTM typing might be the first in finding its way to current diagnostic workflows. However, further validations and automation are required before routine implementation can be envisioned. Copyright © 2017 American Society for Microbiology.

Processing MALDI mass spectra to improve mass spectral direct tissue analysis

NASA Astrophysics Data System (ADS)

Norris, Jeremy L.; Cornett, Dale S.; Mobley, James A.; Andersson, Malin; Seeley, Erin H.; Chaurand, Pierre; Caprioli, Richard M.

2007-02-01

Profiling and imaging biological specimens using MALDI mass spectrometry has significant potential to contribute to our understanding and diagnosis of disease. The technique is efficient and high-throughput providing a wealth of data about the biological state of the sample from a very simple and direct experiment. However, in order for these techniques to be put to use for clinical purposes, the approaches used to process and analyze the data must improve. This study examines some of the existing tools to baseline subtract, normalize, align, and remove spectral noise for MALDI data, comparing the advantages of each. A preferred workflow is presented that can be easily implemented for data in ASCII format. The advantages of using such an approach are discussed for both molecular profiling and imaging mass spectrometry.

Solid-Phase Extraction Strategies to Surmount Body Fluid Sample Complexity in High-Throughput Mass Spectrometry-Based Proteomics

PubMed Central

Bladergroen, Marco R.; van der Burgt, Yuri E. M.

2015-01-01

For large-scale and standardized applications in mass spectrometry- (MS-) based proteomics automation of each step is essential. Here we present high-throughput sample preparation solutions for balancing the speed of current MS-acquisitions and the time needed for analytical workup of body fluids. The discussed workflows reduce body fluid sample complexity and apply for both bottom-up proteomics experiments and top-down protein characterization approaches. Various sample preparation methods that involve solid-phase extraction (SPE) including affinity enrichment strategies have been automated. Obtained peptide and protein fractions can be mass analyzed by direct infusion into an electrospray ionization (ESI) source or by means of matrix-assisted laser desorption ionization (MALDI) without further need of time-consuming liquid chromatography (LC) separations. PMID:25692071

Scientific Workflows + Provenance = Better (Meta-)Data Management

NASA Astrophysics Data System (ADS)

Ludaescher, B.; Cuevas-Vicenttín, V.; Missier, P.; Dey, S.; Kianmajd, P.; Wei, Y.; Koop, D.; Chirigati, F.; Altintas, I.; Belhajjame, K.; Bowers, S.

2013-12-01

The origin and processing history of an artifact is known as its provenance. Data provenance is an important form of metadata that explains how a particular data product came about, e.g., how and when it was derived in a computational process, which parameter settings and input data were used, etc. Provenance information provides transparency and helps to explain and interpret data products. Other common uses and applications of provenance include quality control, data curation, result debugging, and more generally, 'reproducible science'. Scientific workflow systems (e.g. Kepler, Taverna, VisTrails, and others) provide controlled environments for developing computational pipelines with built-in provenance support. Workflow results can then be explained in terms of workflow steps, parameter settings, input data, etc. using provenance that is automatically captured by the system. Scientific workflows themselves provide a user-friendly abstraction of the computational process and are thus a form of ('prospective') provenance in their own right. The full potential of provenance information is realized when combining workflow-level information (prospective provenance) with trace-level information (retrospective provenance). To this end, the DataONE Provenance Working Group (ProvWG) has developed an extension of the W3C PROV standard, called D-PROV. Whereas PROV provides a 'least common denominator' for exchanging and integrating provenance information, D-PROV adds new 'observables' that described workflow-level information (e.g., the functional steps in a pipeline), as well as workflow-specific trace-level information ( timestamps for each workflow step executed, the inputs and outputs used, etc.) Using examples, we will demonstrate how the combination of prospective and retrospective provenance provides added value in managing scientific data. The DataONE ProvWG is also developing tools based on D-PROV that allow scientists to get more mileage from provenance metadata. DataONE is a federation of member nodes that store data and metadata for discovery and access. By enriching metadata with provenance information, search and reuse of data is enhanced, and the 'social life' of data (being the product of many workflow runs, different people, etc.) is revealed. We are currently prototyping a provenance repository (PBase) to demonstrate what can be achieved with advanced provenance queries. The ProvExplorer and ProPub tools support advanced ad-hoc querying and visualization of provenance as well as customized provenance publications (e.g., to address privacy issues, or to focus provenance to relevant details). In a parallel line of work, we are exploring ways to add provenance support to widely-used scripting platforms (e.g. R and Python) and then expose that information via D-PROV.

SearchGUI: A Highly Adaptable Common Interface for Proteomics Search and de Novo Engines.

PubMed

Barsnes, Harald; Vaudel, Marc

2018-05-25

Mass-spectrometry-based proteomics has become the standard approach for identifying and quantifying proteins. A vital step consists of analyzing experimentally generated mass spectra to identify the underlying peptide sequences for later mapping to the originating proteins. We here present the latest developments in SearchGUI, a common open-source interface for the most frequently used freely available proteomics search and de novo engines that has evolved into a central component in numerous bioinformatics workflows.

Metaworkflows and Workflow Interoperability for Heliophysics

NASA Astrophysics Data System (ADS)

Pierantoni, Gabriele; Carley, Eoin P.

2014-06-01

Heliophysics is a relatively new branch of physics that investigates the relationship between the Sun and the other bodies of the solar system. To investigate such relationships, heliophysicists can rely on various tools developed by the community. Some of these tools are on-line catalogues that list events (such as Coronal Mass Ejections, CMEs) and their characteristics as they were observed on the surface of the Sun or on the other bodies of the Solar System. Other tools offer on-line data analysis and access to images and data catalogues. During their research, heliophysicists often perform investigations that need to coordinate several of these services and to repeat these complex operations until the phenomena under investigation are fully analyzed. Heliophysicists combine the results of these services; this service orchestration is best suited for workflows. This approach has been investigated in the HELIO project. The HELIO project developed an infrastructure for a Virtual Observatory for Heliophysics and implemented service orchestration using TAVERNA workflows. HELIO developed a set of workflows that proved to be useful but lacked flexibility and re-usability. The TAVERNA workflows also needed to be executed directly in TAVERNA workbench, and this forced all users to learn how to use the workbench. Within the SCI-BUS and ER-FLOW projects, we have started an effort to re-think and re-design the heliophysics workflows with the aim of fostering re-usability and ease of use. We base our approach on two key concepts, that of meta-workflows and that of workflow interoperability. We have divided the produced workflows in three different layers. The first layer is Basic Workflows, developed both in the TAVERNA and WS-PGRADE languages. They are building blocks that users compose to address their scientific challenges. They implement well-defined Use Cases that usually involve only one service. The second layer is Science Workflows usually developed in TAVERNA. They- implement Science Cases (the definition of a scientific challenge) by composing different Basic Workflows. The third and last layer,Iterative Science Workflows, is developed in WSPGRADE. It executes sub-workflows (either Basic or Science Workflows) as parameter sweep jobs to investigate Science Cases on large multiple data sets. So far, this approach has proven fruitful for three Science Cases of which one has been completed and two are still being tested.

A novel spectral library workflow to enhance protein identifications.

PubMed

Li, Haomin; Zong, Nobel C; Liang, Xiangbo; Kim, Allen K; Choi, Jeong Ho; Deng, Ning; Zelaya, Ivette; Lam, Maggie; Duan, Huilong; Ping, Peipei

2013-04-09

The innovations in mass spectrometry-based investigations in proteome biology enable systematic characterization of molecular details in pathophysiological phenotypes. However, the process of delineating large-scale raw proteomic datasets into a biological context requires high-throughput data acquisition and processing. A spectral library search engine makes use of previously annotated experimental spectra as references for subsequent spectral analyses. This workflow delivers many advantages, including elevated analytical efficiency and specificity as well as reduced demands in computational capacity. In this study, we created a spectral matching engine to address challenges commonly associated with a library search workflow. Particularly, an improved sliding dot product algorithm, that is robust to systematic drifts of mass measurement in spectra, is introduced. Furthermore, a noise management protocol distinguishes spectra correlation attributed from noise and peptide fragments. It enables elevated separation between target spectral matches and false matches, thereby suppressing the possibility of propagating inaccurate peptide annotations from library spectra to query spectra. Moreover, preservation of original spectra also accommodates user contributions to further enhance the quality of the library. Collectively, this search engine supports reproducible data analyses using curated references, thereby broadening the accessibility of proteomics resources to biomedical investigators. This article is part of a Special Issue entitled: From protein structures to clinical applications. Copyright © 2013 Elsevier B.V. All rights reserved.

Next-generation sequencing meets genetic diagnostics: development of a comprehensive workflow for the analysis of BRCA1 and BRCA2 genes

PubMed Central

Feliubadaló, Lídia; Lopez-Doriga, Adriana; Castellsagué, Ester; del Valle, Jesús; Menéndez, Mireia; Tornero, Eva; Montes, Eva; Cuesta, Raquel; Gómez, Carolina; Campos, Olga; Pineda, Marta; González, Sara; Moreno, Victor; Brunet, Joan; Blanco, Ignacio; Serra, Eduard; Capellá, Gabriel; Lázaro, Conxi

2013-01-01

Next-generation sequencing (NGS) is changing genetic diagnosis due to its huge sequencing capacity and cost-effectiveness. The aim of this study was to develop an NGS-based workflow for routine diagnostics for hereditary breast and ovarian cancer syndrome (HBOCS), to improve genetic testing for BRCA1 and BRCA2. A NGS-based workflow was designed using BRCA MASTR kit amplicon libraries followed by GS Junior pyrosequencing. Data analysis combined Variant Identification Pipeline freely available software and ad hoc R scripts, including a cascade of filters to generate coverage and variant calling reports. A BRCA homopolymer assay was performed in parallel. A research scheme was designed in two parts. A Training Set of 28 DNA samples containing 23 unique pathogenic mutations and 213 other variants (33 unique) was used. The workflow was validated in a set of 14 samples from HBOCS families in parallel with the current diagnostic workflow (Validation Set). The NGS-based workflow developed permitted the identification of all pathogenic mutations and genetic variants, including those located in or close to homopolymers. The use of NGS for detecting copy-number alterations was also investigated. The workflow meets the sensitivity and specificity requirements for the genetic diagnosis of HBOCS and improves on the cost-effectiveness of current approaches. PMID:23249957

Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

PubMed

Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

2017-12-01

Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

Performance of Kiestra Total Laboratory Automation Combined with MS in Clinical Microbiology Practice

PubMed Central

Hodiamont, Caspar J.; de Jong, Menno D.; Overmeijer, Hendri P. J.; van den Boogaard, Mandy; Visser, Caroline E.

2014-01-01

Background Microbiological laboratories seek technologically innovative solutions to cope with large numbers of samples and limited personnel and financial resources. One platform that has recently become available is the Kiestra Total Laboratory Automation (TLA) system (BD Kiestra B.V., the Netherlands). This fully automated sample processing system, equipped with digital imaging technology, allows superior detection of microbial growth. Combining this approach with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MS) (Bruker Daltonik, Germany) is expected to enable more rapid identification of pathogens. Methods Early growth detection by digital imaging using Kiestra TLA combined with MS was compared to conventional methods (CM) of detection. Accuracy and time taken for microbial identification were evaluated for the two methods in 219 clinical blood culture isolates. The possible clinical impact of earlier microbial identification was assessed according to antibiotic treatment prescription. Results Pathogen identification using Kiestra TLA combined with MS resulted in a 30.6 hr time gain per isolate compared to CM. Pathogens were successfully identified in 98.4% (249/253) of all tested isolates. Early microbial identification without susceptibility testing led to an adjustment of antibiotic regimen in 12% (24/200) of patients. Conclusions The requisite 24 hr incubation time for microbial pathogens to reach sufficient growth for susceptibility testing and identification would be shortened by the implementation of Kiestra TLA in combination with MS, compared to the use of CM. Not only can this method optimize workflow and reduce costs, but it can allow potentially life-saving switches in antibiotic regimen to be initiated sooner. PMID:24624346

MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

PubMed Central

Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

2014-01-01

Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of 1942. Numerous putative metabolites and pathways were found to be biologically significant from the putative ion identification workflow. PMID:24266674

Parametric Workflow (BIM) for the Repair Construction of Traditional Historic Architecture in Taiwan

NASA Astrophysics Data System (ADS)

Ma, Y.-P.; Hsu, C. C.; Lin, M.-C.; Tsai, Z.-W.; Chen, J.-Y.

2015-08-01

In Taiwan, numerous existing traditional buildings are constructed with wooden structures, brick structures, and stone structures. This paper will focus on the Taiwan traditional historic architecture and target the traditional wooden structure buildings as the design proposition and process the BIM workflow for modeling complex wooden combination geometry, integrating with more traditional 2D documents and for visualizing repair construction assumptions within the 3D model representation. The goal of this article is to explore the current problems to overcome in wooden historic building conservation, and introduce the BIM technology in the case of conserving, documenting, managing, and creating full engineering drawings and information for effectively support historic conservation. Although BIM is mostly oriented to current construction praxis, there have been some attempts to investigate its applicability in historic conservation projects. This article also illustrates the importance and advantages of using BIM workflow in repair construction process, when comparing with generic workflow.

Object-based detection of vehicles using combined optical and elevation data

NASA Astrophysics Data System (ADS)

Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

2018-02-01

The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consists of three consecutive stages: candidate identification, classification, and single vehicle extraction. Unlike in most previous approaches, fusion of both data sources is strongly pursued at all stages. While the first stage utilizes the fact that most man-made objects are rectangular in shape, the second and third stages employ machine learning techniques combined with specific features. The stages are designed to handle multiple sensor input, which results in a significant improvement. A detailed evaluation shows the benefits of our workflow, which includes hand-tailored features; even in comparison with classification approaches based on Convolutional Neural Networks, which are state of the art in computer vision, we could obtain a comparable or superior performance (F1 score of 0.96-0.94).

Direct identification of bacteria from charcoal-containing blood culture bottles using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry.

PubMed

Wüppenhorst, N; Consoir, C; Lörch, D; Schneider, C

2012-10-01

Several protocols for direct matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) from positive blood cultures are currently used to speed up the diagnostic process of bacteraemia. Identification rates are high and results are accurate for the BACTEC™ system and for charcoal-free bottles. Only a few studies have evaluated protocols for charcoal-containing BacT/ALERT bottles reaching substantially lower identification rates. We established a new protocol for sample preparation from aerobic and anaerobic positive charcoal-containing BacT/ALERT blood culture bottles and measured the protein profiles (n = 167). Then, we integrated this protocol in the routine workflow of our laboratory (n = 212). During the establishment of our protocol, 74.3 % of bacteria were correctly identified to the species level, in 23.4 %, no result and in 2.4 %, a false identification were obtained. Reliable criteria for correct species identification were a score value ≥1.400 and a best match on rank 1-3 of the same species. Identification rates during routine workflow were 77.8 % for correct identification, 20.8 % for not identified samples and 1.4 % for discordant identification. In conclusion, our results indicate that MALDI-TOF MS is possible, even from charcoal-containing blood cultures. Reliable criteria for correct species identification are a score value ≥1.400 and a best match on rank 1-3 of a single species.

Coming to Grips with Ambiguity: Ion Mobility-Mass Spectrometry for Protein Quaternary Structure Assignment

NASA Astrophysics Data System (ADS)

Eschweiler, Joseph D.; Frank, Aaron T.; Ruotolo, Brandon T.

2017-10-01

Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein complexes are too often refractory to analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged as a promising approach for characterizing the structures of challenging assemblies due in large part to the ability of these methods to characterize the composition, connectivity, and topology of large, labile complexes. In this Critical Insight, we present a series of bioinformatics studies aimed at assessing the information content of IM-MS datasets for building models of multiprotein structure. Our computational data highlights the limits of current coarse-graining approaches, and compelled us to develop an improved workflow for multiprotein topology modeling, which we benchmark against a subset of the multiprotein complexes within the PDB. This improved workflow has allowed us to ascertain both the minimal experimental restraint sets required for generation of high-confidence multiprotein topologies, and quantify the ambiguity in models where insufficient IM-MS information is available. We conclude by projecting the future of IM-MS in the context of protein quaternary structure assignment, where we predict that a more complete knowledge of the ultimate information content and ambiguity within such models will undoubtedly lead to applications for a broader array of challenging biomolecular assemblies. [Figure not available: see fulltext.

A Systematic Bioinformatics Approach to Identify High Quality Mass Spectrometry Data and Functionally Annotate Proteins and Proteomes.

PubMed

Islam, Mohammad Tawhidul; Mohamedali, Abidali; Ahn, Seong Beom; Nawar, Ishmam; Baker, Mark S; Ranganathan, Shoba

2017-01-01

In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. We present here a simple and intuitive workflow for the research community to investigate and mine this data, not only to extract relevant data but also to segregate usable, quality data to develop hypotheses for investigation and validation. We apply an MS evidence workflow for verifying peptides of proteins from one's own data as well as publicly available databases. We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.

Microfluidic-Mass Spectrometry Interfaces for Translational Proteomics.

PubMed

Pedde, R Daniel; Li, Huiyan; Borchers, Christoph H; Akbari, Mohsen

2017-10-01

Interfacing mass spectrometry (MS) with microfluidic chips (μchip-MS) holds considerable potential to transform a clinician's toolbox, providing translatable methods for the early detection, diagnosis, monitoring, and treatment of noncommunicable diseases by streamlining and integrating laborious sample preparation workflows on high-throughput, user-friendly platforms. Overcoming the limitations of competitive immunoassays - currently the gold standard in clinical proteomics - μchip-MS can provide unprecedented access to complex proteomic assays having high sensitivity and specificity, but without the labor, costs, and complexities associated with conventional MS sample processing. This review surveys recent μchip-MS systems for clinical applications and examines their emerging role in streamlining the development and translation of MS-based proteomic assays by alleviating many of the challenges that currently inhibit widespread clinical adoption. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

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

Ma, Jian; Casey, Cameron P.; Zheng, Xueyun

Motivation: Drift tube ion mobility spectrometry (DTIMS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS coupled with mass spectrometry and compute their associated collisional cross sections (CCS) we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of information necessary to create a reference library containing accu-rate masses, DTIMS arrival times and CCSs for use in high throughput omics analyses. Results: We demonstrate the utility of this approach bymore » automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were identical to those calculated by hand and within error of those calcu-lated using commercially available instrument vendor software.« less

eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows.

PubMed

Kiefer, Patrick; Schmitt, Uwe; Vorholt, Julia A

2013-04-01

The Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS. The framework eMZed and its documentation are freely available at http://emzed.biol.ethz.ch/. eMZed is published under the GPL 3.0 license, and an online discussion group is available at https://groups.google.com/group/emzed-users. Supplementary data are available at Bioinformatics online.

Automated selected reaction monitoring software for accurate label-free protein quantification.

PubMed

Teleman, Johan; Karlsson, Christofer; Waldemarson, Sofia; Hansson, Karin; James, Peter; Malmström, Johan; Levander, Fredrik

2012-07-06

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

Detection of free and covalently bound microcystins in animal tissues by liquid chromatography-tandem mass spectrometry.

PubMed

Neffling, Milla-Riina; Lance, Emilie; Meriluoto, Jussi

2010-03-01

Microcystins are cyanobacterial hepatotoxins capable of accumulation into animal tissues. The toxins act by inhibiting specific protein phosphatases and both non-covalent and covalent interactions occur. The 2-methyl-3-methoxy-4-phenylbutyric acid (MMPB) method determines the total, i.e. the sum of free and protein-bound microcystin in tissues. The aim of the method development in this paper was to tackle the problems with the MMPB methodology: the rather laborious workflow and the loss of material during different steps of the method. In the optimised workflow the oxidation recovery was of acceptable level (29-40%), the extraction efficiency good (62-97%), but the signal suppression effect from the matrix remained severe in our system (16-37% signal left). The extraction efficiency for the determination of the free, extractable microcystins, was found to be good, 52-100%, depending on the sample and the toxin variant and concentration. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Structuring research methods and data with the research object model: genomics workflows as a case study.

PubMed

Hettne, Kristina M; Dharuri, Harish; Zhao, Jun; Wolstencroft, Katherine; Belhajjame, Khalid; Soiland-Reyes, Stian; Mina, Eleni; Thompson, Mark; Cruickshank, Don; Verdes-Montenegro, Lourdes; Garrido, Julian; de Roure, David; Corcho, Oscar; Klyne, Graham; van Schouwen, Reinout; 't Hoen, Peter A C; Bechhofer, Sean; Goble, Carole; Roos, Marco

2014-01-01

One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?". Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well. The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/ro.

From the desktop to the grid: scalable bioinformatics via workflow conversion.

PubMed

de la Garza, Luis; Veit, Johannes; Szolek, Andras; Röttig, Marc; Aiche, Stephan; Gesing, Sandra; Reinert, Knut; Kohlbacher, Oliver

2016-03-12

Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks. There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free -an aspect that could potentially drive away members of the scientific community. We have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources. Our work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.

Clinical review: improving the measurement of serum thyroglobulin with mass spectrometry.

PubMed

Hoofnagle, Andrew N; Roth, Mara Y

2013-04-01

Serum thyroglobulin (Tg) measurements are central to the management of patients treated for differentiated thyroid carcinoma. For decades, Tg measurements have relied on methods that are subject to interference by commonly found substances in human serum and plasma, such as Tg autoantibodies. As a result, many patients need additional imaging studies to rule out cancer persistence or recurrence that could be avoided with more sensitive and specific testing methods. The aims of this review are to: 1) briefly review the interferences common to Tg immunoassays; 2) introduce readers to liquid chromatography-tandem mass spectrometry as a method for quantifying proteins in human serum/plasma; and 3) discuss the potential benefits and limitations of the method in the quantification of serum Tg. Mass spectrometric methods have traditionally lacked the sensitivity, robustness, and throughput to be useful clinical assays. These methods failed to meet the necessary clinical benchmarks due to the nature of the mass spectrometry workflow and instrumentation. Over the past few years, there have been major advances in reagents, automation, and instrumentation for the quantification of proteins using mass spectrometry. More recently, methods using mass spectrometry to detect and quantify Tg have been developed and are of sufficient quality to be used in the management of patients. Novel serum Tg assays that use mass spectrometry may avoid the issue of autoantibody interference and other problems with currently available immunoassays for Tg. Prospective studies are needed to fully understand the potential benefits of novel Tg assays to patients and care providers.

Identification of Acetaminophen Adducts of Rat Liver Microsomal Proteins using 2D-LC-MS/MS.

PubMed

Golizeh, Makan; LeBlanc, André; Sleno, Lekha

2015-11-16

Xenobiotic metabolism in the liver can give rise to reactive metabolites that covalently bind to proteins, and determining which proteins are targeted is important in drug discovery and molecular toxicology. However, there are difficulties in the analysis of these modified proteins in complex biological matrices due to their low abundance. In this study, an analytical approach was developed to systematically identify target proteins of acetaminophen (APAP) in rat liver microsomes (RLM) using two-dimensional chromatography and high-resolution tandem mass spectrometry. In vitro microsomal incubations, with and without APAP, were digested and subjected to strong cation exchange (SCX) fractionation prior to reverse-phase UHPLC-MS/MS. Four data processing strategies were combined into an efficient label-free workflow meant to eliminate potential false positives, using peptide spectral matching, statistical differential analysis, product ion screening, and a custom-built delta-mass filtering tool to pinpoint potential modified peptides. This study revealed four proteins, involved in important cellular processes, to be covalently modified by APAP. Data are available via ProteomeXchange with identifier PXD002590.

The versatility of heart-cutting and comprehensive two-dimensional liquid chromatography in monoclonal antibody clone selection.

PubMed

Sandra, Koen; Steenbeke, Mieke; Vandenheede, Isabel; Vanhoenacker, Gerd; Sandra, Pat

2017-11-10

In recent years, two-dimensional liquid chromatography (2D-LC) has seen an enormous evolution and one of the fields where it is being widely adopted is in the analysis of therapeutic monoclonal antibodies (mAbs). We here further add to the many flavours of this powerful technology. Workflows based on heart-cutting (LC-LC) and comprehensive (LC×LC) 2D-LC are described that allow to guide the clone selection process in mAb and biosimilar development. Combining Protein A affinity chromatography in the first dimension with size exclusion (SEC), cation exchange (CEX) or reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) in the second dimension simultaneously allows to assess mAb titer and critical structural aspects such as aggregation, fragmentation, charge heterogeneity, molecular weight (MW), amino acid sequence and glycosylation. Complementing the LC-LC measurements at intact protein level with LC×LC based peptide mapping provides the necessary information to make clear decisions on which clones to take further into development. Copyright © 2017 Elsevier B.V. All rights reserved.

Andromeda: a peptide search engine integrated into the MaxQuant environment.

PubMed

Cox, Jürgen; Neuhauser, Nadin; Michalski, Annette; Scheltema, Richard A; Olsen, Jesper V; Mann, Matthias

2011-04-01

A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.

Integrated enzyme reactor and high resolving chromatography in "sub-chip" dimensions for sensitive protein mass spectrometry.

PubMed

Hustoft, Hanne Kolsrud; Brandtzaeg, Ole Kristian; Rogeberg, Magnus; Misaghian, Dorna; Torsetnes, Silje Bøen; Greibrokk, Tyge; Reubsaet, Léon; Wilson, Steven Ray; Lundanes, Elsa

2013-12-16

Reliable, sensitive and automatable analytical methodology is of great value in e.g. cancer diagnostics. In this context, an on-line system for enzymatic cleavage of proteins, subsequent peptide separation by liquid chromatography (LC) with mass spectrometric detection has been developed using "sub-chip" columns (10-20 μm inner diameter, ID). The system could detect attomole amounts of isolated cancer biomarker progastrin-releasing peptide (ProGRP), in a more automatable fashion compared to previous methods. The workflow combines protein digestion using an 20 μm ID immobilized trypsin reactor with a polymeric layer of 2-hydroxyethyl methacrylate-vinyl azlactone (HEMA-VDM), desalting on a polystyrene-divinylbenzene (PS-DVB) monolithic trap column, and subsequent separation of resulting peptides on a 10 μm ID (PS-DVB) porous layer open tubular (PLOT) column. The high resolution of the PLOT columns was maintained in the on-line system, resulting in narrow chromatographic peaks of 3-5 seconds. The trypsin reactors provided repeatable performance and were compatible with long-term storage.

Similarities and Differences of Blood N-Glycoproteins in Five Solid Carcinomas at Localized Clinical Stage Analyzed by SWATH-MS.

PubMed

Sajic, Tatjana; Liu, Yansheng; Arvaniti, Eirini; Surinova, Silvia; Williams, Evan G; Schiess, Ralph; Hüttenhain, Ruth; Sethi, Atul; Pan, Sheng; Brentnall, Teresa A; Chen, Ru; Blattmann, Peter; Friedrich, Betty; Niméus, Emma; Malander, Susanne; Omlin, Aurelius; Gillessen, Silke; Claassen, Manfred; Aebersold, Ruedi

2018-05-29

Cancer is mostly incurable when diagnosed at a metastatic stage, making its early detection via blood proteins of immense clinical interest. Proteomic changes in tumor tissue may lead to changes detectable in the protein composition of circulating blood plasma. Using a proteomic workflow combining N-glycosite enrichment and SWATH mass spectrometry, we generate a data resource of 284 blood samples derived from patients with different types of localized-stage carcinomas and from matched controls. We observe whether the changes in the patient's plasma are specific to a particular carcinoma or represent a generic signature of proteins modified uniformly in a common, systemic response to many cancers. A quantitative comparison of the resulting N-glycosite profiles discovers that proteins related to blood platelets are common to several cancers (e.g., THBS1), whereas others are highly cancer-type specific. Available proteomics data, including a SWATH library to study N-glycoproteins, will facilitate follow-up biomarker research into early cancer detection. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Profiling monoterpenol glycoconjugation in Vitis vinifera L. cv. Muscat of Alexandria using a novel putative compound database approach, high resolution mass spectrometry and collision induced dissociation fragmentation analysis.

PubMed

Hjelmeland, Anna K; Zweigenbaum, Jerry; Ebeler, Susan E

2015-08-05

In this work we present a novel approach for the identification of plant metabolites using ultrahigh performance liquid chromatography coupled to accurate mass time-of-flight mass spectrometry. The workflow involves developing an in-house compound database consisting of exact masses of previously identified as well as putative compounds. The database is used to screen accurate mass spectrometry (MS) data to identify possible compound matches. Subsequent tandem MS data is acquired for possible matches and used for structural elucidation. The methodology is applied to profile monoterpene glycosides in Vitis vinifera cv. Muscat of Alexandria grape berries over three developmental stages. Monoterpenes are a subclass of terpenes, the largest class of plant secondary metabolites, and are found in two major forms in the plant, "bound" to one or more sugar moieties or "free" of said sugar moieties. In the free form, monoterpenes are noted for their fragrance and play important roles in plant defense and as attractants for pollinators. However, glycoconjugation renders these compounds odorless, and it is this form that the plant uses for monoterpene storage. In order to gain insight into monoterpene biochemistry and their fate in the plant an analysis of intact glycosides is essential. Eighteen monoterpene glycosides were identified including a monoterpene trisaccharide glycoside, which is tentatively identified here for this first time in any plant. Additionally, while previous studies have identified monoterpene malonylated glucosides in other grapevine tissue, we tentatively identify them for the first time in grape berries. This analytical approach can be readily applied to other plants and the workflow approach can also be used for other classes of compounds. This approach, in general, provides researchers with data to support the identification of putative compounds, which is especially useful when no standard is available. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative liquid chromatography-mass spectrometry-multiple reaction monitoring (LC-MS-MRM) analysis of site-specific glycoforms of haptoglobin in liver disease.

PubMed

Sanda, Miloslav; Pompach, Petr; Brnakova, Zuzana; Wu, Jing; Makambi, Kepher; Goldman, Radoslav

2013-05-01

Development of liver disease is associated with the appearance of multiply fucosylated glycoforms of haptoglobin. To analyze the disease-related haptoglobin glycoforms in liver cirrhosis and hepatocellular carcinoma, we have optimized an LC-MS-multiple reaction monitoring (MRM) workflow for glycopeptide quantification. The final quantitative analysis included 24 site-specific glycoforms generated by treatment of a tryptic digest of haptoglobin with α(2-3,6,8)-neuraminidase and β(1-4)-galactosidase. The combination of LC-MS-MRM with exoglycosidase digests allowed resolution of isobaric glycoforms of the haptoglobin-T3 glycopeptide for quantification of the multiply fucosylated Lewis Y-containing glycoforms we have identified in the context of liver disease. Fourteen multiply fucosylated glycoforms of the 20 examined increased significantly in the liver disease group compared with healthy controls with an average 5-fold increase in intensity (p < 0.05). At the same time, two tri-antennary glycoforms without fucoses did not increase in the liver disease group, and two tetra-antennary glycoforms without fucoses showed a marginal increase (at most 40%) in intensity. Our analysis of 30 individual patient samples (10 healthy controls, 10 cirrhosis patients, and 10 hepatocellular carcinoma patients) showed that these glycoforms were substantially increased in a small subgroup of liver disease patients but did not significantly differ between the groups of hepatocellular carcinoma and cirrhosis patients. The tri- and tetra-antennary singly fucosylated glycoforms are associated with a MELD score and low platelet counts (p < 0.05). The exoglycosidase-assisted LC-MS-MRM workflow, optimized for the quantification of fucosylated glycoforms of haptoglobin, can be used for quantification of these glycoforms on other glycopeptides with appropriate analytical behavior.

Quantitative Liquid Chromatography-Mass Spectrometry-Multiple Reaction Monitoring (LC-MS-MRM) Analysis of Site-specific Glycoforms of Haptoglobin in Liver Disease*

PubMed Central

Sanda, Miloslav; Pompach, Petr; Brnakova, Zuzana; Wu, Jing; Makambi, Kepher; Goldman, Radoslav

2013-01-01

Development of liver disease is associated with the appearance of multiply fucosylated glycoforms of haptoglobin. To analyze the disease-related haptoglobin glycoforms in liver cirrhosis and hepatocellular carcinoma, we have optimized an LC-MS-multiple reaction monitoring (MRM) workflow for glycopeptide quantification. The final quantitative analysis included 24 site-specific glycoforms generated by treatment of a tryptic digest of haptoglobin with α(2–3,6,8)-neuraminidase and β(1–4)-galactosidase. The combination of LC-MS-MRM with exoglycosidase digests allowed resolution of isobaric glycoforms of the haptoglobin-T3 glycopeptide for quantification of the multiply fucosylated Lewis Y-containing glycoforms we have identified in the context of liver disease. Fourteen multiply fucosylated glycoforms of the 20 examined increased significantly in the liver disease group compared with healthy controls with an average 5-fold increase in intensity (p < 0.05). At the same time, two tri-antennary glycoforms without fucoses did not increase in the liver disease group, and two tetra-antennary glycoforms without fucoses showed a marginal increase (at most 40%) in intensity. Our analysis of 30 individual patient samples (10 healthy controls, 10 cirrhosis patients, and 10 hepatocellular carcinoma patients) showed that these glycoforms were substantially increased in a small subgroup of liver disease patients but did not significantly differ between the groups of hepatocellular carcinoma and cirrhosis patients. The tri- and tetra-antennary singly fucosylated glycoforms are associated with a MELD score and low platelet counts (p < 0.05). The exoglycosidase-assisted LC-MS-MRM workflow, optimized for the quantification of fucosylated glycoforms of haptoglobin, can be used for quantification of these glycoforms on other glycopeptides with appropriate analytical behavior. PMID:23389048

Targeted Quantification of Phosphorylation Dynamics in the Context of EGFR-MAPK Pathway.

PubMed

Yi, Lian; Shi, Tujin; Gritsenko, Marina A; X'avia Chan, Chi-Yuet; Fillmore, Thomas L; Hess, Becky M; Swensen, Adam C; Liu, Tao; Smith, Richard D; Wiley, H Steven; Qian, Wei-Jun

2018-04-17

Large-scale phosphoproteomics with coverage of over 10,000 sites of phosphorylation have now been routinely achieved with advanced mass spectrometry (MS)-based workflows. However, accurate targeted MS-based quantification of phosphorylation dynamics, an important direction for gaining quantitative understanding of signaling pathways or networks, has been much less investigated. Herein, we report an assessment of the targeted workflow in the context of signal transduction pathways, using the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway as our model. A total of 43 phosphopeptides from the EGFR-MAPK pathway were selected for the study. The recovery and sensitivity of two commonly used enrichment methods, immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO 2 ), combined with selected reaction monitoring (SRM)-MS were evaluated. The recovery of phosphopeptides by IMAC and TiO 2 enrichment was quantified to be 38 ± 5% and 58 ± 20%, respectively, based on internal standards. Moreover, both enrichment methods provided comparable sensitivity from 1 to 100 μg starting peptides. Robust quantification was consistently achieved for most targeted phosphopeptides when starting with 25-100 μg peptides. However, the numbers of quantified targets significantly dropped when peptide samples were in the 1-25 μg range. Finally, IMAC-SRM was applied to quantify signaling dynamics of EGFR-MAPK pathway in Hs578T cells following 10 ng/mL EGF treatment. The kinetics of phosphorylation clearly revealed early and late phases of phosphorylation, even for very low abundance proteins. These results demonstrate the feasibility of robust targeted quantification of phosphorylation dynamics for specific pathways, even starting with relatively small amounts of protein.

Absorption Mode FT-ICR Mass Spectrometry Imaging

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

Smith, Donald F.; Kilgour, David P.; Konijnenburg, Marco

2013-12-03

Fourier transform ion cyclotron resonance mass spectrometry offers the highest mass resolving power for molecular imaging experiments. This high mass resolving power ensures that closely spaced peaks at the same nominal mass are resolved for proper image generation. Typically higher magnetic fields are used to increase mass resolving power. However, a gain in mass resolving power can also be realized by phase correction of the data for absorption mode display. In addition to mass resolving power, absorption mode offers higher mass accuracy and signal-to-noise ratio over the conventional magnitude mode. Here we present the first use of absorption mode formore » Fourier transform ion cyclotron resonance mass spectrometry imaging. The Autophaser algorithm is used to phase correct each spectrum (pixel) in the image and then these parameters are used by the Chameleon work-flow based data processing software to generate absorption mode ?Datacubes? for image and spectral viewing. Absorption mode reveals new mass and spatial features that are not resolved in magnitude mode and results in improved selected ion image contrast.« less

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

PubMed Central

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.

2015-01-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240

Cognitive Learning, Monitoring and Assistance of Industrial Workflows Using Egocentric Sensor Networks

PubMed Central

Bleser, Gabriele; Damen, Dima; Behera, Ardhendu; Hendeby, Gustaf; Mura, Katharina; Miezal, Markus; Gee, Andrew; Petersen, Nils; Maçães, Gustavo; Domingues, Hugo; Gorecky, Dominic; Almeida, Luis; Mayol-Cuevas, Walterio; Calway, Andrew; Cohn, Anthony G.; Hogg, David C.; Stricker, Didier

2015-01-01

Today, the workflows that are involved in industrial assembly and production activities are becoming increasingly complex. To efficiently and safely perform these workflows is demanding on the workers, in particular when it comes to infrequent or repetitive tasks. This burden on the workers can be eased by introducing smart assistance systems. This article presents a scalable concept and an integrated system demonstrator designed for this purpose. The basic idea is to learn workflows from observing multiple expert operators and then transfer the learnt workflow models to novice users. Being entirely learning-based, the proposed system can be applied to various tasks and domains. The above idea has been realized in a prototype, which combines components pushing the state of the art of hardware and software designed with interoperability in mind. The emphasis of this article is on the algorithms developed for the prototype: 1) fusion of inertial and visual sensor information from an on-body sensor network (BSN) to robustly track the user’s pose in magnetically polluted environments; 2) learning-based computer vision algorithms to map the workspace, localize the sensor with respect to the workspace and capture objects, even as they are carried; 3) domain-independent and robust workflow recovery and monitoring algorithms based on spatiotemporal pairwise relations deduced from object and user movement with respect to the scene; and 4) context-sensitive augmented reality (AR) user feedback using a head-mounted display (HMD). A distinguishing key feature of the developed algorithms is that they all operate solely on data from the on-body sensor network and that no external instrumentation is needed. The feasibility of the chosen approach for the complete action-perception-feedback loop is demonstrated on three increasingly complex datasets representing manual industrial tasks. These limited size datasets indicate and highlight the potential of the chosen technology as a combined entity as well as point out limitations of the system. PMID:26126116

Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics.

PubMed

Muth, Thilo; Rapp, Erdmann; Berven, Frode S; Barsnes, Harald; Vaudel, Marc

2016-01-01

Protein identification via database searches has become the gold standard in mass spectrometry based shotgun proteomics. However, as the quality of tandem mass spectra improves, direct mass spectrum sequencing gains interest as a database-independent alternative. In this chapter, the general principle of this so-called de novo sequencing is introduced along with pitfalls and challenges of the technique. The main tools available are presented with a focus on user friendly open source software which can be directly applied in everyday proteomic workflows.

Successful adaption of a forensic toxicological screening workflow employing nontargeted liquid chromatography-tandem mass spectrometry to water analysis.

PubMed

Steger, Julia; Arnhard, Kathrin; Haslacher, Sandra; Geiger, Klemens; Singer, Klaus; Schlapp, Michael; Pitterl, Florian; Oberacher, Herbert

2016-04-01

Forensic toxicology and environmental water analysis share the common interest and responsibility in ensuring comprehensive and reliable confirmation of drugs and pharmaceutical compounds in samples analyzed. Dealing with similar analytes, detection and identification techniques should be exchangeable between scientific disciplines. Herein, we demonstrate the successful adaption of a forensic toxicological screening workflow employing nontargeted LC/MS/MS under data-dependent acquisition control and subsequent database search to water analysis. The main modification involved processing of an increased sample volume with SPE (500 mL vs. 1-10 mL) to reach LODs in the low ng/L range. Tandem mass spectra acquired with a qTOF instrument were submitted to database search. The targeted data mining strategy was found to be sensitive and specific; automated search produced hardly any false results. To demonstrate the applicability of the adapted workflow to complex samples, 14 wastewater effluent samples collected on seven consecutive days at the local wastewater-treatment plant were analyzed. Of the 88,970 fragment ion mass spectra produced, 8.8% of spectra were successfully assigned to one of the 1040 reference compounds included in the database, and this enabled the identification of 51 compounds representing important illegal drugs, members of various pharmaceutical compound classes, and metabolites thereof. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid Verification of Candidate Serological Biomarkers Using Gel-based, Label-free Multiple Reaction Monitoring

PubMed Central

Tang, Hsin-Yao; Beer, Lynn A.; Barnhart, Kurt T.; Speicher, David W.

2011-01-01

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves, quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1-D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μl serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers. PMID:21726088

Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Barnhart, Kurt T; Speicher, David W

2011-09-02

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

A multimodal imaging workflow to visualize metal mixtures in the human placenta and explore colocalization with biological response markers.

PubMed

Niedzwiecki, Megan M; Austin, Christine; Remark, Romain; Merad, Miriam; Gnjatic, Sacha; Estrada-Gutierrez, Guadalupe; Espejel-Nuñez, Aurora; Borboa-Olivares, Hector; Guzman-Huerta, Mario; Wright, Rosalind J; Wright, Robert O; Arora, Manish

2016-04-01

Fetal exposure to essential and toxic metals can influence life-long health trajectories. The placenta regulates chemical transmission from maternal circulation to the fetus and itself exhibits a complex response to environmental stressors. The placenta can thus be a useful matrix to monitor metal exposures and stress responses in utero, but strategies to explore the biologic effects of metal mixtures in this organ are not well-developed. In this proof-of-concept study, we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to measure the distributions of multiple metals in placental tissue from a low-birth-weight pregnancy, and we developed an approach to identify the components of metal mixtures that colocalized with biological response markers. Our novel workflow, which includes custom-developed software tools and algorithms for spatial outlier identification and background subtraction in multidimensional elemental image stacks, enables rapid image processing and seamless integration of data from elemental imaging and immunohistochemistry. Using quantitative spatial statistics, we identified distinct patterns of metal accumulation at sites of inflammation. Broadly, our multiplexed approach can be used to explore the mechanisms mediating complex metal exposures and biologic responses within placentae and other tissue types. Our LA-ICP-MS image processing workflow can be accessed through our interactive R Shiny application 'shinyImaging', which is available at or through our laboratory's website, .

Widening the adoption of workflows to include human and human-machine scientific processes

NASA Astrophysics Data System (ADS)

Salayandia, L.; Pinheiro da Silva, P.; Gates, A. Q.

2010-12-01

Scientific workflows capture knowledge in the form of technical recipes to access and manipulate data that help scientists manage and reuse established expertise to conduct their work. Libraries of scientific workflows are being created in particular fields, e.g., Bioinformatics, where combined with cyber-infrastructure environments that provide on-demand access to data and tools, result in powerful workbenches for scientists of those communities. The focus in these particular fields, however, has been more on automating rather than documenting scientific processes. As a result, technical barriers have impeded a wider adoption of scientific workflows by scientific communities that do not rely as heavily on cyber-infrastructure and computing environments. Semantic Abstract Workflows (SAWs) are introduced to widen the applicability of workflows as a tool to document scientific recipes or processes. SAWs intend to capture a scientists’ perspective about the process of how she or he would collect, filter, curate, and manipulate data to create the artifacts that are relevant to her/his work. In contrast, scientific workflows describe the process from the point of view of how technical methods and tools are used to conduct the work. By focusing on a higher level of abstraction that is closer to a scientist’s understanding, SAWs effectively capture the controlled vocabularies that reflect a particular scientific community, as well as the types of datasets and methods used in a particular domain. From there on, SAWs provide the flexibility to adapt to different environments to carry out the recipes or processes. These environments range from manual fieldwork to highly technical cyber-infrastructure environments, i.e., such as those already supported by scientific workflows. Two cases, one from Environmental Science and another from Geophysics, are presented as illustrative examples.

Lessons from Implementing a Combined Workflow–Informatics System for Diabetes Management

PubMed Central

Zai, Adrian H.; Grant, Richard W.; Estey, Greg; Lester, William T.; Andrews, Carl T.; Yee, Ronnie; Mort, Elizabeth; Chueh, Henry C.

2008-01-01

Shortcomings surrounding the care of patients with diabetes have been attributed largely to a fragmented, disorganized, and duplicative health care system that focuses more on acute conditions and complications than on managing chronic disease. To address these shortcomings, we developed a diabetes registry population management application to change the way our staff manages patients with diabetes. Use of this new application has helped us coordinate the responsibilities for intervening and monitoring patients in the registry among different users. Our experiences using this combined workflow-informatics intervention system suggest that integrating a chronic disease registry into clinical workflow for the treatment of chronic conditions creates a useful and efficient tool for managing disease. PMID:18436907

From Provenance Standards and Tools to Queries and Actionable Provenance

NASA Astrophysics Data System (ADS)

Ludaescher, B.

2017-12-01

The W3C PROV standard provides a minimal core for sharing retrospective provenance information for scientific workflows and scripts. PROV extensions such as DataONE's ProvONE model are necessary for linking runtime observables in retrospective provenance records with conceptual-level prospective provenance information, i.e., workflow (or dataflow) graphs. Runtime provenance recorders, such as DataONE's RunManager for R, or noWorkflow for Python capture retrospective provenance automatically. YesWorkflow (YW) is a toolkit that allows researchers to declare high-level prospective provenance models of scripts via simple inline comments (YW-annotations), revealing the computational modules and dataflow dependencies in the script. By combining and linking both forms of provenance, important queries and use cases can be supported that neither provenance model can afford on its own. We present existing and emerging provenance tools developed for the DataONE and SKOPE (Synthesizing Knowledge of Past Environments) projects. We show how the different tools can be used individually and in combination to model, capture, share, query, and visualize provenance information. We also present challenges and opportunities for making provenance information more immediately actionable for the researchers who create it in the first place. We argue that such a shift towards "provenance-for-self" is necessary to accelerate the creation, sharing, and use of provenance in support of transparent, reproducible computational and data science.

Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry

PubMed Central

Zubair, Faizan; Laibinis, Paul E.; Swisher, William G.; Yang, Junhai; Spraggins, Jeffrey M.; Norris, Jeremy L.; Caprioli, Richard M.

2017-01-01

Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. PMID:27676701

Rapid MALDI-TOF mass spectrometry strain typing during a large outbreak of Shiga-Toxigenic Escherichia coli.

PubMed

Christner, Martin; Trusch, Maria; Rohde, Holger; Kwiatkowski, Marcel; Schlüter, Hartmut; Wolters, Manuel; Aepfelbacher, Martin; Hentschke, Moritz

2014-01-01

In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification. Specific peaks in the outbreak strain's spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak. Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates. MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow.

Conventions and workflows for using Situs

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

Wriggers, Willy, E-mail: wriggers@biomachina.org

2012-04-01

Recent developments of the Situs software suite for multi-scale modeling are reviewed. Typical workflows and conventions encountered during processing of biophysical data from electron microscopy, tomography or small-angle X-ray scattering are described. Situs is a modular program package for the multi-scale modeling of atomic resolution structures and low-resolution biophysical data from electron microscopy, tomography or small-angle X-ray scattering. This article provides an overview of recent developments in the Situs package, with an emphasis on workflows and conventions that are important for practical applications. The modular design of the programs facilitates scripting in the bash shell that allows specific programs tomore » be combined in creative ways that go beyond the original intent of the developers. Several scripting-enabled functionalities, such as flexible transformations of data type, the use of symmetry constraints or the creation of two-dimensional projection images, are described. The processing of low-resolution biophysical maps in such workflows follows not only first principles but often relies on implicit conventions. Situs conventions related to map formats, resolution, correlation functions and feature detection are reviewed and summarized. The compatibility of the Situs workflow with CCP4 conventions and programs is discussed.« less

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics.

PubMed

Klont, Frank; Bras, Linda; Wolters, Justina C; Ongay, Sara; Bischoff, Rainer; Halmos, Gyorgy B; Horvatovich, Péter

2018-04-17

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

MALDI (matrix assisted laser desorption ionization) Imaging Mass Spectrometry (IMS) of skin: Aspects of sample preparation.

PubMed

de Macedo, Cristiana Santos; Anderson, David M; Schey, Kevin L

2017-11-01

MALDI (matrix assisted laser desorption ionization) Imaging Mass Spectrometry (IMS) allows molecular analysis of biological materials making possible the identification and localization of molecules in tissues, and has been applied to address many questions on skin pathophysiology, as well as on studies about drug absorption and metabolism. Sample preparation for MALDI IMS is the most important part of the workflow, comprising specimen collection and preservation, tissue embedding, cryosectioning, washing, and matrix application. These steps must be carefully optimized for specific analytes of interest (lipids, proteins, drugs, etc.), representing a challenge for skin analysis. In this review, critical parameters for MALDI IMS sample preparation of skin samples will be described. In addition, specific applications of MALDI IMS of skin samples will be presented including wound healing, neoplasia, and infection. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Towards an intelligent hospital environment: OR of the future.

PubMed

Sutherland, Jeffrey V; van den Heuvel, Willem-Jan; Ganous, Tim; Burton, Matthew M; Kumar, Animesh

2005-01-01

Patients, providers, payers, and government demand more effective and efficient healthcare services, and the healthcare industry needs innovative ways to re-invent core processes. Business process reengineering (BPR) showed adopting new hospital information systems can leverage this transformation and workflow management technologies can automate process management. Our research indicates workflow technologies in healthcare require real time patient monitoring, detection of adverse events, and adaptive responses to breakdown in normal processes. Adaptive workflow systems are rarely implemented making current workflow implementations inappropriate for healthcare. The advent of evidence based medicine, guideline based practice, and better understanding of cognitive workflow combined with novel technologies including Radio Frequency Identification (RFID), mobile/wireless technologies, internet workflow, intelligent agents, and Service Oriented Architectures (SOA) opens up new and exciting ways of automating business processes. Total situational awareness of events, timing, and location of healthcare activities can generate self-organizing change in behaviors of humans and machines. A test bed of a novel approach towards continuous process management was designed for the new Weinburg Surgery Building at the University of Maryland Medical. Early results based on clinical process mapping and analysis of patient flow bottlenecks demonstrated 100% improvement in delivery of supplies and instruments at surgery start time. This work has been directly applied to the design of the DARPA Trauma Pod research program where robotic surgery will be performed on wounded soldiers on the battlefield.

Collision Cross Section (CCS) Database: An Additional Measure to Characterize Steroids.

PubMed

Hernández-Mesa, Maykel; Le Bizec, Bruno; Monteau, Fabrice; García-Campaña, Ana M; Dervilly-Pinel, Gaud

2018-04-03

Ion mobility spectrometry enhances the performance characteristics of liquid chromatography-mass spectrometry workflows intended to steroid profiling by providing a new separation dimension and a novel characterization parameter, the so-called collision cross section (CCS). This work proposes the first CCS database for 300 steroids (i.e., endogenous, including phase I and phase II metabolites, and exogenous synthetic compounds), which involves 1080 ions and covers the CCS of 127 androgens, 84 estrogens, 50 corticosteroids, and 39 progestagens. This large database provides information related to all the ionized species identified for each steroid in positive electrospray ionization mode as well as for estrogens in negative ionization mode. CCS values have been measured using nitrogen as drift gas in the ion mobility cell. Generally, direct correlation exists between mass-to-charge ratio ( m/ z) and CCS because both are related parameters. However, several steroids mainly steroid glucuronides and steroid esters have been characterized as more compact or elongated molecules than expected. In such cases, CCS results in additional relevant information to retention time and mass spectral data for the identification of steroids. Moreover, several isomeric steroid pairs (e.g., 5β-androstane-3,17-dione and 5α-androstane-3,17-dione) have been separated based on their CCS differences. These results indicate that adding the CCS to databases in analytical workflows increases selectivity, thus improving the confidence in steroids analysis. Consequences in terms of identification and quantification are discussed. Quality criteria and a construction of an interlaboratory reproducibility approach are also reported for the obtained CCS values. The CCS database described here is made publicly available.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers*

PubMed Central

Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-01-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. PMID:28235782

Identification and quantification of VOCs by proton transfer reaction time of flight mass spectrometry: An experimental workflow for the optimization of specificity, sensitivity, and accuracy

PubMed Central

Hanna, George B.

2018-01-01

Abstract Proton transfer reaction time of flight mass spectrometry (PTR‐ToF‐MS) is a direct injection MS technique, allowing for the sensitive and real‐time detection, identification, and quantification of volatile organic compounds. When aiming to employ PTR‐ToF‐MS for targeted volatile organic compound analysis, some methodological questions must be addressed, such as the need to correctly identify product ions, or evaluating the quantitation accuracy. This work proposes a workflow for PTR‐ToF‐MS method development, addressing the main issues affecting the reliable identification and quantification of target compounds. We determined the fragmentation patterns of 13 selected compounds (aldehydes, fatty acids, phenols). Experiments were conducted under breath‐relevant conditions (100% humid air), and within an extended range of reduced electric field values (E/N = 48–144 Td), obtained by changing drift tube voltage. Reactivity was inspected using H3O+, NO+, and O2 + as primary ions. The results show that a relatively low (<90 Td) E/N often permits to reduce fragmentation enhancing sensitivity and identification capabilities, particularly in the case of aldehydes using NO+, where a 4‐fold increase in sensitivity is obtained by means of drift voltage reduction. We developed a novel calibration methodology, relying on diffusion tubes used as gravimetric standards. For each of the tested compounds, it was possible to define suitable conditions whereby experimental error, defined as difference between gravimetric measurements and calculated concentrations, was 8% or lower. PMID:29336521

Qualitative screening for new psychoactive substances in wastewater collected during a city festival using liquid chromatography coupled to high-resolution mass spectrometry.

PubMed

Causanilles, Ana; Kinyua, Juliet; Ruttkies, Christoph; van Nuijs, Alexander L N; Emke, Erik; Covaci, Adrian; de Voogt, Pim

2017-10-01

The inclusion of new psychoactive substances (NPS) in the wastewater-based epidemiology approach presents challenges, such as the reduced number of users that translates into low concentrations of residues and the limited pharmacokinetics information available, which renders the choice of target biomarker difficult. The sampling during special social settings, the analysis with improved analytical techniques, and data processing with specific workflow to narrow the search, are required approaches for a successful monitoring. This work presents the application of a qualitative screening technique to wastewater samples collected during a city festival, where likely users of recreational substances gather and consequently higher residual concentrations of used NPS are expected. The analysis was performed using liquid chromatography coupled to high-resolution mass spectrometry. Data were processed using an algorithm that involves the extraction of accurate masses (calculated based on molecular formula) of expected m/z from an in-house database containing about 2,000 entries, including NPS and transformation products. We positively identified eight NPS belonging to the classes of synthetic cathinones, phenethylamines and opioids. In addition, the presence of benzodiazepine analogues, classical drugs and other licit substances with potential for abuse was confirmed. The screening workflow based on a database search was useful in the identification of NPS biomarkers in wastewater. The findings highlight the specific classical drugs and low NPS use in the Netherlands. Additionally, meta-chlorophenylpiperazine (mCPP), 2,5-dimethoxy-4-bromophenethylamine (2C-B), and 4-fluoroamphetamine (FA) were identified in wastewater for the first time. Copyright © 2017 Elsevier Ltd. All rights reserved.

Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

PubMed

Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

2017-05-02

Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

Lipid Identification by Untargeted Tandem Mass Spectrometry Coupled with Ultra-High-Pressure Liquid Chromatography.

PubMed

Gugiu, Gabriel B

2017-01-01

Lipidomics refers to the large-scale study of lipids in biological systems (Wenk, Nat Rev Drug Discov 4(7):594-610, 2005; Rolim et al., Gene 554(2):131-139, 2015). From a mass spectrometric point of view, by lipidomics we understand targeted or untargeted mass spectrometric analysis of lipids using either liquid chromatography (LC) (Castro-Perez et al., J Proteome Res 9(5):2377-2389, 2010) or shotgun (Han and Gross, Mass Spectrom Rev 24(3):367-412, 2005) approaches coupled with tandem mass spectrometry. This chapter describes the former methodology, which is becoming rapidly the preferred method for lipid identification owing to similarities with established omics workflows, such as proteomics (Washburn et al., Nat Biotechnol 19(3):242-247, 2001) or genomics (Yadav, J Biomol Tech: JBT 18(5):277, 2007). The workflow described consists in lipid extraction using a modified Bligh and Dyer method (Bligh and Dyer, Can J Biochem Physiol 37(8):911-917, 1959), ultra high pressure liquid chromatography fractionation of lipid samples on a reverse phase C18 column, followed by tandem mass spectrometric analysis and in silico database search for lipid identification based on MSMS spectrum matching (Kind et al., Nat Methods 10(8):755-758, 2013; Yamada et al., J Chromatogr A 1292:211-218, 2013; Taguchi and Ishikawa, J Chromatogr A 1217(25):4229-4239, 2010; Peake et al., Thermoscientifices 1-3, 2015) and accurate mass of parent ion (Sud et al., Nucleic Acids Res 35(database issue):D527-D532, 2007; Wishart et al., Nucleic Acids Res 35(database):D521-D526, 2007).

Asterism: an integrated, complete, and open-source approach for running seismologist continuous data-intensive analysis on heterogeneous systems

NASA Astrophysics Data System (ADS)

Ferreira da Silva, R.; Filgueira, R.; Deelman, E.; Atkinson, M.

2016-12-01

We present Asterism, an open source data-intensive framework, which combines the Pegasus and dispel4py workflow systems. Asterism aims to simplify the effort required to develop data-intensive applications that run across multiple heterogeneous resources, without users having to: re-formulate their methods according to different enactment systems; manage the data distribution across systems; parallelize their methods; co-place and schedule their methods with computing resources; and store and transfer large/small volumes of data. Asterism's key element is to leverage the strengths of each workflow system: dispel4py allows developing scientific applications locally and then automatically parallelize and scale them on a wide range of HPC infrastructures with no changes to the application's code; Pegasus orchestrates the distributed execution of applications while providing portability, automated data management, recovery, debugging, and monitoring, without users needing to worry about the particulars of the target execution systems. Asterism leverages the level of abstractions provided by each workflow system to describe hybrid workflows where no information about the underlying infrastructure is required beforehand. The feasibility of Asterism has been evaluated using the seismic ambient noise cross-correlation application, a common data-intensive analysis pattern used by many seismologists. The application preprocesses (Phase1) and cross-correlates (Phase2) traces from several seismic stations. The Asterism workflow is implemented as a Pegasus workflow composed of two tasks (Phase1 and Phase2), where each phase represents a dispel4py workflow. Pegasus tasks describe the in/output data at a logical level, the data dependency between tasks, and the e-Infrastructures and the execution engine to run each dispel4py workflow. We have instantiated the workflow using data from 1000 stations from the IRIS services, and run it across two heterogeneous resources described as Docker containers: MPI (Container2) and Storm (Container3) clusters (Figure 1). Each dispel4py workflow is mapped to a particular execution engine, and data transfers between resources are automatically handled by Pegasus. Asterism is freely available online at http://github.com/dispel4py/pegasus_dispel4py.

Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially-expressed genes from microarray data.

PubMed

Li, Peter; Castrillo, Juan I; Velarde, Giles; Wassink, Ingo; Soiland-Reyes, Stian; Owen, Stuart; Withers, David; Oinn, Tom; Pocock, Matthew R; Goble, Carole A; Oliver, Stephen G; Kell, Douglas B

2008-08-07

There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.

Performing statistical analyses on quantitative data in Taverna workflows: An example using R and maxdBrowse to identify differentially-expressed genes from microarray data

PubMed Central

Li, Peter; Castrillo, Juan I; Velarde, Giles; Wassink, Ingo; Soiland-Reyes, Stian; Owen, Stuart; Withers, David; Oinn, Tom; Pocock, Matthew R; Goble, Carole A; Oliver, Stephen G; Kell, Douglas B

2008-01-01

Background There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. Results Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. Conclusion Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data. PMID:18687127

Rapid Identification and Susceptibility Testing of Candida spp. from Positive Blood Cultures by Combination of Direct MALDI-TOF Mass Spectrometry and Direct Inoculation of Vitek 2

PubMed Central

Idelevich, Evgeny A.; Grunewald, Camilla M.; Wüllenweber, Jörg; Becker, Karsten

2014-01-01

Fungaemia is associated with high mortality rates and early appropriate antifungal therapy is essential for patient management. However, classical diagnostic workflow takes up to several days due to the slow growth of yeasts. Therefore, an approach for direct species identification and direct antifungal susceptibility testing (AFST) without prior time-consuming sub-culturing of yeasts from positive blood cultures (BCs) is urgently needed. Yeast cell pellets prepared using Sepsityper kit were used for direct identification by MALDI-TOF mass spectrometry (MS) and for direct inoculation of Vitek 2 AST-YS07 card for AFST. For comparison, MALDI-TOF MS and Vitek 2 testing were performed from yeast subculture. A total of twenty four positive BCs including twelve C. glabrata, nine C. albicans, two C. dubliniensis and one C. krusei isolate were processed. Applying modified thresholds for species identification (score ≥1.5 with two identical consecutive propositions), 62.5% of BCs were identified by direct MALDI-TOF MS. AFST results were generated for 72.7% of BCs directly tested by Vitek 2 and for 100% of standardized suspensions from 24 h cultures. Thus, AFST comparison was possible for 70 isolate-antifungal combinations. Essential agreement (minimum inhibitory concentration difference ≤1 double dilution step) was 88.6%. Very major errors (VMEs) (false-susceptibility), major errors (false-resistance) and minor errors (false categorization involving intermediate result) amounted to 33.3% (of resistant isolates), 1.9% (of susceptible isolates) and 1.4% providing 90.0% categorical agreement. All VMEs were due to fluconazole or voriconazole. This direct method saved on average 23.5 h for identification and 15.1 h for AFST, compared to routine procedures. However, performance for azole susceptibility testing was suboptimal and testing from subculture remains indispensable to validate the direct finding. PMID:25489741

Changes in the expression of N- and O-glycopeptides in patients with colorectal cancer and hepatocellular carcinoma quantified by full-MS scan FT-ICR and multiple reaction monitoring.

PubMed

Darebna, Petra; Novak, Petr; Kucera, Radek; Topolcan, Ondrej; Sanda, Miloslav; Goldman, Radoslav; Pompach, Petr

2017-02-05

Alternations in the glycosylation of proteins have been described in connection with several cancers, including hepatocellular carcinoma (HCC) and colorectal cancer. Analytical tools, which use combination of liquid chromatography and mass spectrometry, allow precise and sensitive description of these changes. In this study, we use MRM and FT-ICR operating in full-MS scan, to determine ratios of intensities of specific glycopeptides in HCC, colorectal cancer, and liver metastasis of colorectal cancer. Haptoglobin, hemopexin and complement factor H were detected after albumin depletion and the N-linked glycopeptides with fucosylated glycans were compared with their non-fucosylated forms. In addition, sialylated forms of an O-linked glycopeptide of hemopexin were quantified in the same samples. We observe significant increase in fucosylation of all three proteins and increase in bi-sialylated O-glycopeptide of hemopexin in HCC of hepatitis C viral (HCV) etiology by both LC-MS methods. The results of the MRM and full-MS scan FT-ICR analyses provide comparable quantitative readouts in spite of chromatographic, mass spectrometric and data analysis differences. Our results suggest that both workflows allow adequate relative quantification of glycopeptides and suggest that HCC of HCV etiology differs in glycosylation from colorectal cancer and liver metastasis of colorectal cancer. The article compares N- and O-glycosylation of several serum proteins in different diseases by a fast and easy sample preparation procedure in combination with high resolution Fourier transform ion cyclotron resonance mass spectrometry. The results show successful glycopeptides relative quantification in a complex peptide mixture by the high resolution instrument and the detection of glycan differences between the different types of cancer diseases. The presented method is comparable to conventional targeted MRM approach but allows additional curation of the data. Copyright © 2016 Elsevier B.V. All rights reserved.

Changes in the expression of N- and O-glycopeptides in patients with colorectal cancer and hepatocellular carcinoma quantified by full-MS scan FT-ICR and multiple reaction monitoring

PubMed Central

Darebna, Petra; Novak, Petr; Kucera, Radek; Topolcan, Ondrej; Sanda, Miloslav; Goldman, Radoslav; Pompach, Petr

2018-01-01

Alternations in the glycosylation of proteins have been described in connection with several cancers, including hepatocellular carcinoma (HCC) and colorectal cancer. Analytical tools, which use combination of liquid chromatography and mass spectrometry, allow precise and sensitive description of these changes. In this study, we use MRM and FT-ICR operating in full-MS scan, to determine ratios of intensities of specific glycopeptides in HCC, colorectal cancer, and liver metastasis of colorectal cancer. Haptoglobin, hemopexin and complement factor H were detected after albumin depletion and the N-linked glycopeptides with fucosylated glycans were compared with their non-fucosylated forms. In addition, sialylated forms of an O-linked glycopeptide of hemopexin were quantified in the same samples. We observe significant increase in fucosylation of all three proteins and increase in bisialylated O-glycopeptide of hemopexin in HCC of hepatitis C viral (HCV) etiology by both LC-MS methods. The results of the MRM and full-MS scan FT-ICR analyses provide comparable quantitative readouts in spite of chromatographic, mass spectrometric and data analysis differences. Our results suggest that both workflows allow adequate relative quantification of glycopeptides and suggest that HCC of HCV etiology differs in glycosylation from colorectal cancer and liver metastasis of colorectal cancer. Significance The article compares N- and O-glycosylation of several serum proteins in different diseases by a fast and easy sample preparation procedure in combination with high resolution Fourier transform ion cyclotron resonance mass spectrometry. The results show successful glycopeptides relative quantification in a complex peptide mixture by the high resolution instrument and the detection of glycan differences between the different types of cancer diseases. The presented method is comparable to conventional targeted MRM approach but allows additional curation of the data. PMID:27646713

Rapid identification and susceptibility testing of Candida spp. from positive blood cultures by combination of direct MALDI-TOF mass spectrometry and direct inoculation of Vitek 2.

PubMed

Idelevich, Evgeny A; Grunewald, Camilla M; Wüllenweber, Jörg; Becker, Karsten

2014-01-01

Fungaemia is associated with high mortality rates and early appropriate antifungal therapy is essential for patient management. However, classical diagnostic workflow takes up to several days due to the slow growth of yeasts. Therefore, an approach for direct species identification and direct antifungal susceptibility testing (AFST) without prior time-consuming sub-culturing of yeasts from positive blood cultures (BCs) is urgently needed. Yeast cell pellets prepared using Sepsityper kit were used for direct identification by MALDI-TOF mass spectrometry (MS) and for direct inoculation of Vitek 2 AST-YS07 card for AFST. For comparison, MALDI-TOF MS and Vitek 2 testing were performed from yeast subculture. A total of twenty four positive BCs including twelve C. glabrata, nine C. albicans, two C. dubliniensis and one C. krusei isolate were processed. Applying modified thresholds for species identification (score ≥ 1.5 with two identical consecutive propositions), 62.5% of BCs were identified by direct MALDI-TOF MS. AFST results were generated for 72.7% of BCs directly tested by Vitek 2 and for 100% of standardized suspensions from 24 h cultures. Thus, AFST comparison was possible for 70 isolate-antifungal combinations. Essential agreement (minimum inhibitory concentration difference ≤ 1 double dilution step) was 88.6%. Very major errors (VMEs) (false-susceptibility), major errors (false-resistance) and minor errors (false categorization involving intermediate result) amounted to 33.3% (of resistant isolates), 1.9% (of susceptible isolates) and 1.4% providing 90.0% categorical agreement. All VMEs were due to fluconazole or voriconazole. This direct method saved on average 23.5 h for identification and 15.1 h for AFST, compared to routine procedures. However, performance for azole susceptibility testing was suboptimal and testing from subculture remains indispensable to validate the direct finding.

High-Throughput Industrial Coatings Research at The Dow Chemical Company.

PubMed

Kuo, Tzu-Chi; Malvadkar, Niranjan A; Drumright, Ray; Cesaretti, Richard; Bishop, Matthew T

2016-09-12

At The Dow Chemical Company, high-throughput research is an active area for developing new industrial coatings products. Using the principles of automation (i.e., using robotic instruments), parallel processing (i.e., prepare, process, and evaluate samples in parallel), and miniaturization (i.e., reduce sample size), high-throughput tools for synthesizing, formulating, and applying coating compositions have been developed at Dow. In addition, high-throughput workflows for measuring various coating properties, such as cure speed, hardness development, scratch resistance, impact toughness, resin compatibility, pot-life, surface defects, among others have also been developed in-house. These workflows correlate well with the traditional coatings tests, but they do not necessarily mimic those tests. The use of such high-throughput workflows in combination with smart experimental designs allows accelerated discovery and commercialization.

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.

PubMed

Audain, Enrique; Uszkoreit, Julian; Sachsenberg, Timo; Pfeuffer, Julianus; Liang, Xiao; Hermjakob, Henning; Sanchez, Aniel; Eisenacher, Martin; Reinert, Knut; Tabb, David L; Kohlbacher, Oliver; Perez-Riverol, Yasset

2017-01-06

In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF+. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended. Protein inference is one of the major challenges in MS-based proteomics nowadays. Currently, there are a vast number of protein inference algorithms and implementations available for the proteomics community. Protein assembly impacts in the final results of the research, the quantitation values and the final claims in the research manuscript. Even though protein inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF+ and combinations thereof were evaluated for every protein inference tool. In total >186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could, concerning the question behind the study, compensate for slightly shorter reports using the parsimonious reports. 4) The current workflow can be easily extended to support new algorithms and search engine combinations. Copyright © 2016. Published by Elsevier B.V.

Advancing the global proteome survey platform by using an oriented single chain antibody fragment immobilization approach.

PubMed

Säll, Anna; Persson, Helena; Ohlin, Mats; Borrebaeck, Carl A K; Wingren, Christer

2016-09-25

Increasing the understanding of a proteome and how its protein composition is affected by for example different diseases, such as cancer, has the potential to improve strategies for early diagnosis and therapeutics. The Global Proteome Survey or GPS is a method that combines mass spectrometry and affinity enrichment with the use of antibodies. The technology enables profiling of complex proteomes in a species independent manner. The sensitivity of GPS, and other methods relying on affinity enrichment, is largely affected by the activity of the exploited affinity reagent. We here present an improvement of the GPS platform by utilizing an antibody immobilization approach which ensures a controlled immobilization process of the antibody to the magnetic bead support. More specifically, we make use of an antibody format that enables site-directed biotinylation and use this in combination with streptavidin coated magnetic beads. The performance of the expanded GPS platform was evaluated by profiling yeast proteome samples. We demonstrate that the oriented antibody immobilization strategy increases the ability of the GPS platform and results in larger fraction of functional antibodies. Additionally, we show that this new antibody format enabled in-solution capture, i.e. immobilization of the antibodies after sample incubation. A workflow has been established that permit the use of an oriented immobilization strategy for the GPS platform. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Spatiotemporal analysis of tropical disease research combining Europe PMC and affiliation mapping web services.

PubMed

Palmblad, Magnus; Torvik, Vetle I

2017-01-01

Tropical medicine appeared as a distinct sub-discipline in the late nineteenth century, during a period of rapid European colonial expansion in Africa and Asia. After a dramatic drop after World War II, research on tropical diseases have received more attention and research funding in the twenty-first century. We used Apache Taverna to integrate Europe PMC and MapAffil web services, containing the spatiotemporal analysis workflow from a list of PubMed queries to a list of publication years and author affiliations geoparsed to latitudes and longitudes. The results could then be visualized in the Quantum Geographic Information System (QGIS). Our workflows automatically matched 253,277 affiliations to geographical coordinates for the first authors of 379,728 papers on tropical diseases in a single execution. The bibliometric analyses show how research output in tropical diseases follow major historical shifts in the twentieth century and renewed interest in and funding for tropical disease research in the twenty-first century. They show the effects of disease outbreaks, WHO eradication programs, vaccine developments, wars, refugee migrations, and peace treaties. Literature search and geoparsing web services can be combined in scientific workflows performing a complete spatiotemporal bibliometric analyses of research in tropical medicine. The workflows and datasets are freely available and can be used to reproduce or refine the analyses and test specific hypotheses or look into particular diseases or geographic regions. This work exceeds all previously published bibliometric analyses on tropical diseases in both scale and spatiotemporal range.

Expanding the Described Metabolome of the Marine Cyanobacterium Moorea producens JHB through Orthogonal Natural Products Workflows

PubMed Central

Boudreau, Paul D.; Monroe, Emily A.; Mehrotra, Suneet; Desfor, Shane; Korobeynikov, Anton; Sherman, David H.; Murray, Thomas F.; Gerwick, Lena; Dorrestein, Pieter C.; Gerwick, William H.

2015-01-01

Moorea producens JHB, a Jamaican strain of tropical filamentous marine cyanobacteria, has been extensively studied by traditional natural products techniques. These previous bioassay and structure guided isolations led to the discovery of two exciting classes of natural products, hectochlorin (1) and jamaicamides A (2) and B (3). In the current study, mass spectrometry-based ‘molecular networking’ was used to visualize the metabolome of Moorea producens JHB, and both guided and enhanced the isolation workflow, revealing additional metabolites in these compound classes. Further, we developed additional insight into the metabolic capabilities of this strain by genome sequencing analysis, which subsequently led to the isolation of a compound unrelated to the jamaicamide and hectochlorin families. Another approach involved stimulation of the biosynthesis of a minor jamaicamide metabolite by cultivation in modified media, and provided insights about the underlying biosynthetic machinery as well as preliminary structure-activity information within this structure class. This study demonstrated that these orthogonal approaches are complementary and enrich secondary metabolomic coverage even in an extensively studied bacterial strain. PMID:26222584

KNIME for reproducible cross-domain analysis of life science data.

PubMed

Fillbrunn, Alexander; Dietz, Christian; Pfeuffer, Julianus; Rahn, René; Landrum, Gregory A; Berthold, Michael R

2017-11-10

Experiments in the life sciences often involve tools from a variety of domains such as mass spectrometry, next generation sequencing, or image processing. Passing the data between those tools often involves complex scripts for controlling data flow, data transformation, and statistical analysis. Such scripts are not only prone to be platform dependent, they also tend to grow as the experiment progresses and are seldomly well documented, a fact that hinders the reproducibility of the experiment. Workflow systems such as KNIME Analytics Platform aim to solve these problems by providing a platform for connecting tools graphically and guaranteeing the same results on different operating systems. As an open source software, KNIME allows scientists and programmers to provide their own extensions to the scientific community. In this review paper we present selected extensions from the life sciences that simplify data exploration, analysis, and visualization and are interoperable due to KNIME's unified data model. Additionally, we name other workflow systems that are commonly used in the life sciences and highlight their similarities and differences to KNIME. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

GUEST EDITOR'S INTRODUCTION: Guest Editor's introduction

NASA Astrophysics Data System (ADS)

Chrysanthis, Panos K.

1996-12-01

Computer Science Department, University of Pittsburgh, Pittsburgh, PA 15260, USA This special issue focuses on current efforts to represent and support workflows that integrate information systems and human resources within a business or manufacturing enterprise. Workflows may also be viewed as an emerging computational paradigm for effective structuring of cooperative applications involving human users and access to diverse data types not necessarily maintained by traditional database management systems. A workflow is an automated organizational process (also called business process) which consists of a set of activities or tasks that need to be executed in a particular controlled order over a combination of heterogeneous database systems and legacy systems. Within workflows, tasks are performed cooperatively by either human or computational agents in accordance with their roles in the organizational hierarchy. The challenge in facilitating the implementation of workflows lies in developing efficient workflow management systems. A workflow management system (also called workflow server, workflow engine or workflow enactment system) provides the necessary interfaces for coordination and communication among human and computational agents to execute the tasks involved in a workflow and controls the execution orderings of tasks as well as the flow of data that these tasks manipulate. That is, the workflow management system is responsible for correctly and reliably supporting the specification, execution, and monitoring of workflows. The six papers selected (out of the twenty-seven submitted for this special issue of Distributed Systems Engineering) address different aspects of these three functional components of a workflow management system. In the first paper, `Correctness issues in workflow management', Kamath and Ramamritham discuss the important issue of correctness in workflow management that constitutes a prerequisite for the use of workflows in the automation of the critical organizational/business processes. In particular, this paper examines the issues of execution atomicity and failure atomicity, differentiating between correctness requirements of system failures and logical failures, and surveys techniques that can be used to ensure data consistency in workflow management systems. While the first paper is concerned with correctness assuming transactional workflows in which selective transactional properties are associated with individual tasks or the entire workflow, the second paper, `Scheduling workflows by enforcing intertask dependencies' by Attie et al, assumes that the tasks can be either transactions or other activities involving legacy systems. This second paper describes the modelling and specification of conditions involving events and dependencies among tasks within a workflow using temporal logic and finite state automata. It also presents a scheduling algorithm that enforces all stated dependencies by executing at any given time only those events that are allowed by all the dependency automata and in an order as specified by the dependencies. In any system with decentralized control, there is a need to effectively cope with the tension that exists between autonomy and consistency requirements. In `A three-level atomicity model for decentralized workflow management systems', Ben-Shaul and Heineman focus on the specific requirement of enforcing failure atomicity in decentralized, autonomous and interacting workflow management systems. Their paper describes a model in which each workflow manager must be able to specify the sequence of tasks that comprise an atomic unit for the purposes of correctness, and the degrees of local and global atomicity for the purpose of cooperation with other workflow managers. The paper also discusses a realization of this model in which treaties and summits provide an agreement mechanism, while underlying transaction managers are responsible for maintaining failure atomicity. The fourth and fifth papers are experience papers describing a workflow management system and a large scale workflow application, respectively. Schill and Mittasch, in `Workflow management systems on top of OSF DCE and OMG CORBA', describe a decentralized workflow management system and discuss its implementation using two standardized middleware platforms, namely, OSF DCE and OMG CORBA. The system supports a new approach to workflow management, introducing several new concepts such as data type management for integrating various types of data and quality of service for various services provided by servers. A problem common to both database applications and workflows is the handling of missing and incomplete information. This is particularly pervasive in an `electronic market' with a huge number of retail outlets producing and exchanging volumes of data, the application discussed in `Information flow in the DAMA project beyond database managers: information flow managers'. Motivated by the need for a method that allows a task to proceed in a timely manner if not all data produced by other tasks are available by its deadline, Russell et al propose an architectural framework and a language that can be used to detect, approximate and, later on, to adjust missing data if necessary. The final paper, `The evolution towards flexible workflow systems' by Nutt, is complementary to the other papers and is a survey of issues and of work related to both workflow and computer supported collaborative work (CSCW) areas. In particular, the paper provides a model and a categorization of the dimensions which workflow management and CSCW systems share. Besides summarizing the recent advancements towards efficient workflow management, the papers in this special issue suggest areas open to investigation and it is our hope that they will also provide the stimulus for further research and development in the area of workflow management systems.

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.

PubMed

Torgerson, Carinna M; Quinn, Catherine; Dinov, Ivo; Liu, Zhizhong; Petrosyan, Petros; Pelphrey, Kevin; Haselgrove, Christian; Kennedy, David N; Toga, Arthur W; Van Horn, John Darrell

2015-03-01

Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.

Standardized protocols for quality control of MRM-based plasma proteomic workflows.

PubMed

Percy, Andrew J; Chambers, Andrew G; Smith, Derek S; Borchers, Christoph H

2013-01-04

Mass spectrometry (MS)-based proteomics is rapidly emerging as a viable technology for the identification and quantitation of biological samples, such as human plasma--the most complex yet commonly employed biofluid in clinical analyses. The transition from a qualitative to quantitative science is required if proteomics is going to successfully make the transition to a clinically useful technique. MS, however, has been criticized for a lack of reproducibility and interlaboratory transferability. Currently, the MS and plasma proteomics communities lack standardized protocols and reagents to ensure that high-quality quantitative data can be accurately and precisely reproduced by laboratories across the world using different MS technologies. Toward addressing this issue, we have developed standard protocols for multiple reaction monitoring (MRM)-based assays with customized isotopically labeled internal standards for quality control of the sample preparation workflow and the MS platform in quantitative plasma proteomic analyses. The development of reference standards and their application to a single MS platform is discussed herein, along with the results from intralaboratory tests. The tests highlighted the importance of the reference standards in assessing the efficiency and reproducibility of the entire bottom-up proteomic workflow and revealed errors related to the sample preparation and performance quality and deficits of the MS and LC systems. Such evaluations are necessary if MRM-based quantitative plasma proteomics is to be used in verifying and validating putative disease biomarkers across different research laboratories and eventually in clinical laboratories.

MALDI-TOF-MS with PLS Modeling Enables Strain Typing of the Bacterial Plant Pathogen Xanthomonas axonopodis

NASA Astrophysics Data System (ADS)

Sindt, Nathan M.; Robison, Faith; Brick, Mark A.; Schwartz, Howard F.; Heuberger, Adam L.; Prenni, Jessica E.

2018-02-01

Matrix-assisted desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) is a fast and effective tool for microbial species identification. However, current approaches are limited to species-level identification even when genetic differences are known. Here, we present a novel workflow that applies the statistical method of partial least squares discriminant analysis (PLS-DA) to MALDI-TOF-MS protein fingerprint data of Xanthomonas axonopodis, an important bacterial plant pathogen of fruit and vegetable crops. Mass spectra of 32 X. axonopodis strains were used to create a mass spectral library and PLS-DA was employed to model the closely related strains. A robust workflow was designed to optimize the PLS-DA model by assessing the model performance over a range of signal-to-noise ratios (s/n) and mass filter (MF) thresholds. The optimized parameters were observed to be s/n = 3 and MF = 0.7. The model correctly classified 83% of spectra withheld from the model as a test set. A new decision rule was developed, termed the rolled-up Maximum Decision Rule (ruMDR), and this method improved identification rates to 92%. These results demonstrate that MALDI-TOF-MS protein fingerprints of bacterial isolates can be utilized to enable identification at the strain level. Furthermore, the open-source framework of this workflow allows for broad implementation across various instrument platforms as well as integration with alternative modeling and classification algorithms.

Quality Metadata Management for Geospatial Scientific Workflows: from Retrieving to Assessing with Online Tools

NASA Astrophysics Data System (ADS)

Leibovici, D. G.; Pourabdollah, A.; Jackson, M.

2011-12-01

Experts and decision-makers use or develop models to monitor global and local changes of the environment. Their activities require the combination of data and processing services in a flow of operations and spatial data computations: a geospatial scientific workflow. The seamless ability to generate, re-use and modify a geospatial scientific workflow is an important requirement but the quality of outcomes is equally much important [1]. Metadata information attached to the data and processes, and particularly their quality, is essential to assess the reliability of the scientific model that represents a workflow [2]. Managing tools, dealing with qualitative and quantitative metadata measures of the quality associated with a workflow, are, therefore, required for the modellers. To ensure interoperability, ISO and OGC standards [3] are to be adopted, allowing for example one to define metadata profiles and to retrieve them via web service interfaces. However these standards need a few extensions when looking at workflows, particularly in the context of geoprocesses metadata. We propose to fill this gap (i) at first through the provision of a metadata profile for the quality of processes, and (ii) through providing a framework, based on XPDL [4], to manage the quality information. Web Processing Services are used to implement a range of metadata analyses on the workflow in order to evaluate and present quality information at different levels of the workflow. This generates the metadata quality, stored in the XPDL file. The focus is (a) on the visual representations of the quality, summarizing the retrieved quality information either from the standardized metadata profiles of the components or from non-standard quality information e.g., Web 2.0 information, and (b) on the estimated qualities of the outputs derived from meta-propagation of uncertainties (a principle that we have introduced [5]). An a priori validation of the future decision-making supported by the outputs of the workflow once run, is then provided using the meta-propagated qualities, obtained without running the workflow [6], together with the visualization pointing out the need to improve the workflow with better data or better processes on the workflow graph itself. [1] Leibovici, DG, Hobona, G Stock, K Jackson, M (2009) Qualifying geospatial workfow models for adaptive controlled validity and accuracy. In: IEEE 17th GeoInformatics, 1-5 [2] Leibovici, DG, Pourabdollah, A (2010a) Workflow Uncertainty using a Metamodel Framework and Metadata for Data and Processes. OGC TC/PC Meetings, September 2010, Toulouse, France [3] OGC (2011) www.opengeospatial.org [4] XPDL (2008) Workflow Process Definition Interface - XML Process Definition Language.Workflow Management Coalition, Document WfMC-TC-1025, 2008 [5] Leibovici, DG Pourabdollah, A Jackson, M (2011) Meta-propagation of Uncertainties for Scientific Workflow Management in Interoperable Spatial Data Infrastructures. In: Proceedings of the European Geosciences Union (EGU2011), April 2011, Austria [6] Pourabdollah, A Leibovici, DG Jackson, M (2011) MetaPunT: an Open Source tool for Meta-Propagation of uncerTainties in Geospatial Processing. In: Proceedings of OSGIS2011, June 2011, Nottingham, UK

Influences of Normalization Method on Biomarker Discovery in Gas Chromatography-Mass Spectrometry-Based Untargeted Metabolomics: What Should Be Considered?

PubMed

Chen, Jiaqing; Zhang, Pei; Lv, Mengying; Guo, Huimin; Huang, Yin; Zhang, Zunjian; Xu, Fengguo

2017-05-16

Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

NASA Astrophysics Data System (ADS)

Comi, Troy J.; Neumann, Elizabeth K.; Do, Thanh D.; Sweedler, Jonathan V.

2017-09-01

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. [Figure not available: see fulltext.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling.

PubMed

Comi, Troy J; Neumann, Elizabeth K; Do, Thanh D; Sweedler, Jonathan V

2017-09-01

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. Graphical Abstract ᅟ.

Developing a Multiplexed Quantitative Cross-Linking Mass Spectrometry Platform for Comparative Structural Analysis of Protein Complexes.

PubMed

Yu, Clinton; Huszagh, Alexander; Viner, Rosa; Novitsky, Eric J; Rychnovsky, Scott D; Huang, Lan

2016-10-18

Cross-linking mass spectrometry (XL-MS) represents a recently popularized hybrid methodology for defining protein-protein interactions (PPIs) and analyzing structures of large protein assemblies. In particular, XL-MS strategies have been demonstrated to be effective in elucidating molecular details of PPIs at the peptide resolution, providing a complementary set of structural data that can be utilized to refine existing complex structures or direct de novo modeling of unknown protein structures. To study structural and interaction dynamics of protein complexes, quantitative cross-linking mass spectrometry (QXL-MS) strategies based on isotope-labeled cross-linkers have been developed. Although successful, these approaches are mostly limited to pairwise comparisons. In order to establish a robust workflow enabling comparative analysis of multiple cross-linked samples simultaneously, we have developed a multiplexed QXL-MS strategy, namely, QMIX (Quantitation of Multiplexed, Isobaric-labeled cross (X)-linked peptides) by integrating MS-cleavable cross-linkers with isobaric labeling reagents. This study has established a new analytical platform for quantitative analysis of cross-linked peptides, which can be directly applied for multiplexed comparisons of the conformational dynamics of protein complexes and PPIs at the proteome scale in future studies.

Identification of drug metabolites in human plasma or serum integrating metabolite prediction, LC-HRMS and untargeted data processing.

PubMed

Jacobs, Peter L; Ridder, Lars; Ruijken, Marco; Rosing, Hilde; Jager, Nynke Gl; Beijnen, Jos H; Bas, Richard R; van Dongen, William D

2013-09-01

Comprehensive identification of human drug metabolites in first-in-man studies is crucial to avoid delays in later stages of drug development. We developed an efficient workflow for systematic identification of human metabolites in plasma or serum that combines metabolite prediction, high-resolution accurate mass LC-MS and MS vendor independent data processing. Retrospective evaluation of predictions for 14 (14)C-ADME studies published in the period 2007-January 2012 indicates that on average 90% of the major metabolites in human plasma can be identified by searching for accurate masses of predicted metabolites. Furthermore, the workflow can identify unexpected metabolites in the same processing run, by differential analysis of samples of drug-dosed subjects and (placebo-dosed, pre-dose or otherwise blank) control samples. To demonstrate the utility of the workflow we applied it to identify tamoxifen metabolites in serum of a breast cancer patient treated with tamoxifen. Previously published metabolites were confirmed in this study and additional metabolites were identified, two of which are discussed to illustrate the advantages of the workflow.

3D correlative light and electron microscopy of cultured cells using serial blockface scanning electron microscopy

PubMed Central

Lerner, Thomas R.; Burden, Jemima J.; Nkwe, David O.; Pelchen-Matthews, Annegret; Domart, Marie-Charlotte; Durgan, Joanne; Weston, Anne; Jones, Martin L.; Peddie, Christopher J.; Carzaniga, Raffaella; Florey, Oliver; Marsh, Mark; Gutierrez, Maximiliano G.

2017-01-01

ABSTRACT The processes of life take place in multiple dimensions, but imaging these processes in even three dimensions is challenging. Here, we describe a workflow for 3D correlative light and electron microscopy (CLEM) of cell monolayers using fluorescence microscopy to identify and follow biological events, combined with serial blockface scanning electron microscopy to analyse the underlying ultrastructure. The workflow encompasses all steps from cell culture to sample processing, imaging strategy, and 3D image processing and analysis. We demonstrate successful application of the workflow to three studies, each aiming to better understand complex and dynamic biological processes, including bacterial and viral infections of cultured cells and formation of entotic cell-in-cell structures commonly observed in tumours. Our workflow revealed new insight into the replicative niche of Mycobacterium tuberculosis in primary human lymphatic endothelial cells, HIV-1 in human monocyte-derived macrophages, and the composition of the entotic vacuole. The broad application of this 3D CLEM technique will make it a useful addition to the correlative imaging toolbox for biomedical research. PMID:27445312

Rapid MALDI-TOF Mass Spectrometry Strain Typing during a Large Outbreak of Shiga-Toxigenic Escherichia coli

PubMed Central

Christner, Martin; Trusch, Maria; Rohde, Holger; Kwiatkowski, Marcel; Schlüter, Hartmut; Wolters, Manuel; Aepfelbacher, Martin; Hentschke, Moritz

2014-01-01

Background In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification. Methods Specific peaks in the outbreak strain’s spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak. Results Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates. Conclusions MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow. PMID:25003758

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.

Determining Double Bond Position in Lipids Using Online Ozonolysis Coupled to Liquid Chromatography and Ion Mobility-Mass Spectrometry.

PubMed

Harris, Rachel A; May, Jody C; Stinson, Craig A; Xia, Yu; McLean, John A

2018-02-06

The increasing focus on lipid metabolism has revealed a need for analytical techniques capable of structurally characterizing lipids with a high degree of specificity. Lipids can exist as any one of a large number of double bond positional isomers, which are indistinguishable by single-stage mass spectrometry alone. Ozonolysis reactions coupled to mass spectrometry have previously been demonstrated as a means for localizing double bonds in unsaturated lipids. Here we describe an online, solution-phase reactor using ozone produced via a low-pressure mercury lamp, which generates aldehyde products diagnostic of cleavage at a particular double bond position. This flow-cell device is utilized in conjunction with structurally selective ion mobility-mass spectrometry. The lamp-mediated reaction was found to be effective for multiple lipid species in both positive and negative ionization modes, and the conversion efficiency from precursor to product ions was tunable across a wide range (20-95%) by varying the flow rate through the ozonolysis device. Ion mobility separation of the ozonolysis products generated additional structural information and revealed the presence of saturated species in a complex mixture. The method presented here is simple, robust, and readily coupled to existing instrument platforms with minimal modifications necessary. For these reasons, application to standard lipidomic workflows is possible and aids in more comprehensive structural characterization of a myriad of lipid species.

Executing SADI services in Galaxy.

PubMed

Aranguren, Mikel Egaña; González, Alejandro Rodríguez; Wilkinson, Mark D

2014-01-01

In recent years Galaxy has become a popular workflow management system in bioinformatics, due to its ease of installation, use and extension. The availability of Semantic Web-oriented tools in Galaxy, however, is limited. This is also the case for Semantic Web Services such as those provided by the SADI project, i.e. services that consume and produce RDF. Here we present SADI-Galaxy, a tool generator that deploys selected SADI Services as typical Galaxy tools. SADI-Galaxy is a Galaxy tool generator: through SADI-Galaxy, any SADI-compliant service becomes a Galaxy tool that can participate in other out-standing features of Galaxy such as data storage, history, workflow creation, and publication. Galaxy can also be used to execute and combine SADI services as it does with other Galaxy tools. Finally, we have semi-automated the packing and unpacking of data into RDF such that other Galaxy tools can easily be combined with SADI services, plugging the rich SADI Semantic Web Service environment into the popular Galaxy ecosystem. SADI-Galaxy bridges the gap between Galaxy, an easy to use but "static" workflow system with a wide user-base, and SADI, a sophisticated, semantic, discovery-based framework for Web Services, thus benefiting both user communities.

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach.

PubMed

Guruceaga, Elizabeth; Garin-Muga, Alba; Prieto, Gorka; Bejarano, Bartolomé; Marcilla, Miguel; Marín-Vicente, Consuelo; Perez-Riverol, Yasset; Casal, J Ignacio; Vizcaíno, Juan Antonio; Corrales, Fernando J; Segura, Victor

2017-12-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations.

A collection of open source applications for mass spectrometry data mining.

PubMed

Gallardo, Óscar; Ovelleiro, David; Gay, Marina; Carrascal, Montserrat; Abian, Joaquin

2014-10-01

We present several bioinformatics applications for the identification and quantification of phosphoproteome components by MS. These applications include a front-end graphical user interface that combines several Thermo RAW formats to MASCOT™ Generic Format extractors (EasierMgf), two graphical user interfaces for search engines OMSSA and SEQUEST (OmssaGui and SequestGui), and three applications, one for the management of databases in FASTA format (FastaTools), another for the integration of search results from up to three search engines (Integrator), and another one for the visualization of mass spectra and their corresponding database search results (JsonVisor). These applications were developed to solve some of the common problems found in proteomic and phosphoproteomic data analysis and were integrated in the workflow for data processing and feeding on our LymPHOS database. Applications were designed modularly and can be used standalone. These tools are written in Perl and Python programming languages and are supported on Windows platforms. They are all released under an Open Source Software license and can be freely downloaded from our software repository hosted at GoogleCode. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Review of Software Tools for Design and Analysis of Large scale MRM Proteomic Datasets

PubMed Central

Colangelo, Christopher M.; Chung, Lisa; Bruce, Can; Cheung, Kei-Hoi

2013-01-01

Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow. PMID:23702368

Enhanced Missing Proteins Detection in NCI60 Cell Lines Using an Integrative Search Engine Approach

PubMed Central

2017-01-01

The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations. PMID:28960077

Top Down Tandem Mass Spectrometric Analysis of a Chemically Modified Rough-Type Lipopolysaccharide Vaccine Candidate.

PubMed

Oyler, Benjamin L; Khan, Mohd M; Smith, Donald F; Harberts, Erin M; Kilgour, David P A; Ernst, Robert K; Cross, Alan S; Goodlett, David R

2018-06-01

Recent advances in lipopolysaccharide (LPS) biology have led to its use in drug discovery pipelines, including vaccine and vaccine adjuvant discovery. Desirable characteristics for LPS vaccine candidates include both the ability to produce a specific antibody titer in patients and a minimal host inflammatory response directed by the innate immune system. However, in-depth chemical characterization of most LPS extracts has not been performed; hence, biological activities of these extracts are unpredictable. Additionally, the most widely adopted workflow for LPS structure elucidation includes nonspecific chemical decomposition steps before analyses, making structures inferred and not necessarily biologically relevant. In this work, several different mass spectrometry workflows that have not been previously explored were employed to show proof-of-principle for top down LPS primary structure elucidation, specifically for a rough-type mutant (J5) E. coli-derived LPS component of a vaccine candidate. First, ion mobility filtered precursor ions were subjected to collision induced dissociation (CID) to define differences in native J5 LPS v. chemically detoxified J5 LPS (dLPS). Next, ultra-high mass resolving power, accurate mass spectrometry was employed for unequivocal precursor and product ion empirical formulae generation. Finally, MS 3 analyses in an ion trap instrument showed that previous knowledge about dissociation of LPS components can be used to reconstruct and sequence LPS in a top down fashion. A structural rationale is also explained for differential inflammatory dose-response curves, in vitro, when HEK-Blue hTLR4 cells were administered increasing concentrations of native J5 LPS v. dLPS, which will be useful in future drug discovery efforts. Graphical Abstract ᅟ.

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers.

PubMed

Chen, Yi-Ting; Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-05-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Analysis of Serum Total and Free PSA Using Immunoaffinity Depletion Coupled to SRM: Correlation with Clinical Immunoassay Tests

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

Liu, Tao; Hossain, Mahmud; Schepmoes, Athena A.

2012-08-03

Sandwich immunoassay is the standard technique used in clinical labs for quantifying protein biomarkers for disease detection, monitoring and therapeutic intervention. Albeit highly sensitive, the development of a specific immunoassay is rather time-consuming and associated with extremely high cost due to the requirement for paired immunoaffinity reagents of high specificity. Recently, mass spectrometry-based methods, specifically selected reaction monitoring mass spectrometry (SRM-MS), have been increasingly applied to measure low abundance biomarker candidates in tissue and biofluids, owing to high sensitivity and specificity, simplicity of assay configuration, and great multiplexing capability. In this study, we report for the first time the developmentmore » of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. With stable isotope dilution and external calibration, low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed very good correlation (R2 values ranging from 0.90 to 0.99) in several independent clinical serum sample sets, including a set of 33 samples assayed in a blinded test. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring total and free PSA in human blood. Furthermore, simultaneous measurement of free and total PSA and many other biomarkers can be performed in a single analysis using high-resolution liquid chromatographic separation coupled with SRM-MS.« less

Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline*

PubMed Central

Ranninger, Christina; Rurik, Marc; Limonciel, Alice; Ruzek, Silke; Reischl, Roland; Wilmes, Anja; Jennings, Paul; Hewitt, Philip; Dekant, Wolfgang; Kohlbacher, Oliver; Huber, Christian G.

2015-01-01

Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial cell line, RPTEC/TERT1, treated with 10 and 35 μmol·liter−1 of chloroacetaldehyde, a metabolite of the anti-cancer drug ifosfamide. Our study outlines the establishment of an automated and easy to use untargeted metabolomics workflow for HPLC-high resolution mass spectrometry data. Automated data analysis workflows based on open source software (OpenMS, KNIME) enabled a comprehensive and reproducible analysis of the complex and voluminous metabolomics data produced by the profiling approach. Time- and concentration-dependent responses were clearly evident in the metabolomic profiles. To obtain a more comprehensive picture of the mode of action, transcriptomics and proteomics data were also integrated. For toxicity profiling of chloroacetaldehyde, 428 and 317 metabolite features were detectable in positive and negative modes, respectively, after stringent removal of chemical noise and unstable signals. Changes upon treatment were explored using principal component analysis, and statistically significant differences were identified using linear models for microarray assays. The analysis revealed toxic effects only for the treatment with 35 μmol·liter−1 for 3 and 14 days. The most regulated metabolites were glutathione and metabolites related to the oxidative stress response of the cells. These findings are corroborated by proteomics and transcriptomics data, which show, among other things, an activation of the Nrf2 and ATF4 pathways. PMID:26055719

Top Down Tandem Mass Spectrometric Analysis of a Chemically Modified Rough-Type Lipopolysaccharide Vaccine Candidate

NASA Astrophysics Data System (ADS)

Oyler, Benjamin L.; Khan, Mohd M.; Smith, Donald F.; Harberts, Erin M.; Kilgour, David P. A.; Ernst, Robert K.; Cross, Alan S.; Goodlett, David R.

2018-02-01

Recent advances in lipopolysaccharide (LPS) biology have led to its use in drug discovery pipelines, including vaccine and vaccine adjuvant discovery. Desirable characteristics for LPS vaccine candidates include both the ability to produce a specific antibody titer in patients and a minimal host inflammatory response directed by the innate immune system. However, in-depth chemical characterization of most LPS extracts has not been performed; hence, biological activities of these extracts are unpredictable. Additionally, the most widely adopted workflow for LPS structure elucidation includes nonspecific chemical decomposition steps before analyses, making structures inferred and not necessarily biologically relevant. In this work, several different mass spectrometry workflows that have not been previously explored were employed to show proof-of-principle for top down LPS primary structure elucidation, specifically for a rough-type mutant (J5) E. coli-derived LPS component of a vaccine candidate. First, ion mobility filtered precursor ions were subjected to collision induced dissociation (CID) to define differences in native J5 LPS v. chemically detoxified J5 LPS (dLPS). Next, ultra-high mass resolving power, accurate mass spectrometry was employed for unequivocal precursor and product ion empirical formulae generation. Finally, MS3 analyses in an ion trap instrument showed that previous knowledge about dissociation of LPS components can be used to reconstruct and sequence LPS in a top down fashion. A structural rationale is also explained for differential inflammatory dose-response curves, in vitro, when HEK-Blue hTLR4 cells were administered increasing concentrations of native J5 LPS v. dLPS, which will be useful in future drug discovery efforts. [Figure not available: see fulltext.

Metabolomic spectral libraries for data-independent SWATH liquid chromatography mass spectrometry acquisition.

PubMed

Bruderer, Tobias; Varesio, Emmanuel; Hidasi, Anita O; Duchoslav, Eva; Burton, Lyle; Bonner, Ron; Hopfgartner, Gérard

2018-03-01

High-quality mass spectral libraries have become crucial in mass spectrometry-based metabolomics. Here, we investigate a workflow to generate accurate mass discrete and composite spectral libraries for metabolite identification and for SWATH mass spectrometry data processing. Discrete collision energy (5-100 eV) accurate mass spectra were collected for 532 metabolites from the human metabolome database (HMDB) by flow injection analysis and compiled into composite spectra over a large collision energy range (e.g., 10-70 eV). Full scan response factors were also calculated. Software tools based on accurate mass and predictive fragmentation were specially developed and found to be essential for construction and quality control of the spectral library. First, elemental compositions constrained by the elemental composition of the precursor ion were calculated for all fragments. Secondly, all possible fragments were generated from the compound structure and were filtered based on their elemental compositions. From the discrete spectra, it was possible to analyze the specific fragment form at each collision energy and it was found that a relatively large collision energy range (10-70 eV) gives informative MS/MS spectra for library searches. From the composite spectra, it was possible to characterize specific neutral losses as radical losses using in silico fragmentation. Radical losses (generating radical cations) were found to be more prominent than expected. From 532 metabolites, 489 provided a signal in positive mode [M+H] + and 483 in negative mode [M-H] - . MS/MS spectra were obtained for 399 compounds in positive mode and for 462 in negative mode; 329 metabolites generated suitable spectra in both modes. Using the spectral library, LC retention time, response factors to analyze data-independent LC-SWATH-MS data allowed the identification of 39 (positive mode) and 72 (negative mode) metabolites in a plasma pool sample (total 92 metabolites) where 81 previously were reported in HMDB to be found in plasma. Graphical abstract Library generation workflow for LC-SWATH MS, using collision energy spread, accurate mass, and fragment annotation.

a Standardized Approach to Topographic Data Processing and Workflow Management

NASA Astrophysics Data System (ADS)

Wheaton, J. M.; Bailey, P.; Glenn, N. F.; Hensleigh, J.; Hudak, A. T.; Shrestha, R.; Spaete, L.

2013-12-01

An ever-increasing list of options exist for collecting high resolution topographic data, including airborne LIDAR, terrestrial laser scanners, bathymetric SONAR and structure-from-motion. An equally rich, arguably overwhelming, variety of tools exists with which to organize, quality control, filter, analyze and summarize these data. However, scientists are often left to cobble together their analysis as a series of ad hoc steps, often using custom scripts and one-time processes that are poorly documented and rarely shared with the community. Even when literature-cited software tools are used, the input and output parameters differ from tool to tool. These parameters are rarely archived and the steps performed lost, making the analysis virtually impossible to replicate precisely. What is missing is a coherent, robust, framework for combining reliable, well-documented topographic data-processing steps into a workflow that can be repeated and even shared with others. We have taken several popular topographic data processing tools - including point cloud filtering and decimation as well as DEM differencing - and defined a common protocol for passing inputs and outputs between them. This presentation describes a free, public online portal that enables scientists to create custom workflows for processing topographic data using a number of popular topographic processing tools. Users provide the inputs required for each tool and in what sequence they want to combine them. This information is then stored for future reuse (and optionally sharing with others) before the user then downloads a single package that contains all the input and output specifications together with the software tools themselves. The user then launches the included batch file that executes the workflow on their local computer against their topographic data. This ZCloudTools architecture helps standardize, automate and archive topographic data processing. It also represents a forum for discovering and sharing effective topographic processing workflows.

Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases

PubMed Central

Satagopam, Venkata; Gu, Wei; Eifes, Serge; Gawron, Piotr; Ostaszewski, Marek; Gebel, Stephan; Barbosa-Silva, Adriano; Balling, Rudi; Schneider, Reinhard

2016-01-01

Abstract Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services—tranSMART, a Galaxy Server, and a MINERVA platform—are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data. PMID:27441714

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

PubMed

Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

PubMed Central

Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

2015-01-01

Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

Identification of chemical components in Baidianling Capsule based on gas chromatography-mass spectrometry and high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Wu, Wenying; Chen, Yu; Wang, Binjie; Sun, Xiaoyang; Guo, Ping; Chen, Xiaohui

2017-08-01

Baidianling Capsule, which is made from 16 Chinese herbs, has been widely used for treating vitiligo clinically. In this study, the sensitive and rapid method has been developed for the analysis of chemical components in Baidianling Capsule by gas chromatography-mass spectrometry in combination with retention indices and high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry. Firstly, a total of 110 potential volatile compounds obtained from different extraction procedures including alkanes, alkenes, alkynes, ketones, ethers, aldehydes, alcohols, phenols, organic acids, esters, furans, pyrrole, acid amides, heterocycles, and oxides were detected from Baidianling Capsule by gas chromatography-mass spectrometry, of which 75 were identified by mass spectrometry in combination with the retention index. Then, a total of 124 components were tentatively identified by high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry. Fifteen constituents from Baidianling Capsule were accurately identified by comparing the retention times with those of reference compounds, others were identified by comparing the retention times and mass spectrometry data, as well as retrieving the reference literature. This study provides a practical strategy for rapidly screening and identifying the multiple constituents of a complex traditional Chinese medicine. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

PubMed Central

Sheynkman, Gloria M.; Shortreed, Michael R.; Cesnik, Anthony J.; Smith, Lloyd M.

2016-01-01

Mass spectrometry–based proteomics has emerged as the leading method for detection, quantification, and characterization of proteins. Nearly all proteomic workflows rely on proteomic databases to identify peptides and proteins, but these databases typically contain a generic set of proteins that lack variations unique to a given sample, precluding their detection. Fortunately, proteogenomics enables the detection of such proteomic variations and can be defined, broadly, as the use of nucleotide sequences to generate candidate protein sequences for mass spectrometry database searching. Proteogenomics is experiencing heightened significance due to two developments: (a) advances in DNA sequencing technologies that have made complete sequencing of human genomes and transcriptomes routine, and (b) the unveiling of the tremendous complexity of the human proteome as expressed at the levels of genes, cells, tissues, individuals, and populations. We review here the field of human proteogenomics, with an emphasis on its history, current implementations, the types of proteomic variations it reveals, and several important applications. PMID:27049631

Pathology consultation on urine compliance testing and drug abuse screening.

PubMed

Ward, Michael B; Hackenmueller, Sarah A; Strathmann, Frederick G

2014-11-01

Compliance testing in pain management requires a distinct approach compared with classic clinical toxicology testing. Differences in the patient populations and clinical expectations require modifications to established reporting cutoffs, assay performance expectations, and critical review of how best to apply the available testing methods. Although other approaches to testing are emerging, immunoassay screening followed by mass spectrometry confirmation remains the most common testing workflow for pain management compliance and drug abuse testing. A case-based approach was used to illustrate the complexities inherent to and uniqueness of pain management compliance testing for both clinicians and laboratories. A basic understanding of the inherent strengths and weaknesses of immunoassays and mass spectrometry provides the clinician a better understanding of how best to approach pain management compliance testing. Pain management compliance testing is a textbook example of an emerging field requiring open communication between physician and performing laboratory to fully optimize patient care. Copyright© by the American Society for Clinical Pathology.

KDE Bioscience: platform for bioinformatics analysis workflows.

PubMed

Lu, Qiang; Hao, Pei; Curcin, Vasa; He, Weizhong; Li, Yuan-Yuan; Luo, Qing-Ming; Guo, Yi-Ke; Li, Yi-Xue

2006-08-01

Bioinformatics is a dynamic research area in which a large number of algorithms and programs have been developed rapidly and independently without much consideration so far of the need for standardization. The lack of such common standards combined with unfriendly interfaces make it difficult for biologists to learn how to use these tools and to translate the data formats from one to another. Consequently, the construction of an integrative bioinformatics platform to facilitate biologists' research is an urgent and challenging task. KDE Bioscience is a java-based software platform that collects a variety of bioinformatics tools and provides a workflow mechanism to integrate them. Nucleotide and protein sequences from local flat files, web sites, and relational databases can be entered, annotated, and aligned. Several home-made or 3rd-party viewers are built-in to provide visualization of annotations or alignments. KDE Bioscience can also be deployed in client-server mode where simultaneous execution of the same workflow is supported for multiple users. Moreover, workflows can be published as web pages that can be executed from a web browser. The power of KDE Bioscience comes from the integrated algorithms and data sources. With its generic workflow mechanism other novel calculations and simulations can be integrated to augment the current sequence analysis functions. Because of this flexible and extensible architecture, KDE Bioscience makes an ideal integrated informatics environment for future bioinformatics or systems biology research.

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology.

PubMed

Cock, Peter J A; Grüning, Björn A; Paszkiewicz, Konrad; Pritchard, Leighton

2013-01-01

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of "effector" proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen's predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu).

Ursgal, Universal Python Module Combining Common Bottom-Up Proteomics Tools for Large-Scale Analysis.

PubMed

Kremer, Lukas P M; Leufken, Johannes; Oyunchimeg, Purevdulam; Schulze, Stefan; Fufezan, Christian

2016-03-04

Proteomics data integration has become a broad field with a variety of programs offering innovative algorithms to analyze increasing amounts of data. Unfortunately, this software diversity leads to many problems as soon as the data is analyzed using more than one algorithm for the same task. Although it was shown that the combination of multiple peptide identification algorithms yields more robust results, it is only recently that unified approaches are emerging; however, workflows that, for example, aim to optimize search parameters or that employ cascaded style searches can only be made accessible if data analysis becomes not only unified but also and most importantly scriptable. Here we introduce Ursgal, a Python interface to many commonly used bottom-up proteomics tools and to additional auxiliary programs. Complex workflows can thus be composed using the Python scripting language using a few lines of code. Ursgal is easily extensible, and we have made several database search engines (X!Tandem, OMSSA, MS-GF+, Myrimatch, MS Amanda), statistical postprocessing algorithms (qvality, Percolator), and one algorithm that combines statistically postprocessed outputs from multiple search engines ("combined FDR") accessible as an interface in Python. Furthermore, we have implemented a new algorithm ("combined PEP") that combines multiple search engines employing elements of "combined FDR", PeptideShaker, and Bayes' theorem.

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker.

PubMed

Aranguren, Mikel Egaña; Wilkinson, Mark D

2015-01-01

Semantic Web technologies have been widely applied in the life sciences, for example by data providers such as OpenLifeData and through web services frameworks such as SADI. The recently reported OpenLifeData2SADI project offers access to the vast OpenLifeData data store through SADI services. This article describes how to merge data retrieved from OpenLifeData2SADI with other SADI services using the Galaxy bioinformatics analysis platform, thus making this semantic data more amenable to complex analyses. This is demonstrated using a working example, which is made distributable and reproducible through a Docker image that includes SADI tools, along with the data and workflows that constitute the demonstration. The combination of Galaxy and Docker offers a solution for faithfully reproducing and sharing complex data retrieval and analysis workflows based on the SADI Semantic web service design patterns.

Multidimensional Interactive Radiology Report and Analysis: standardization of workflow and reporting for renal mass tracking and quantification

NASA Astrophysics Data System (ADS)

Hwang, Darryl H.; Ma, Kevin; Yepes, Fernando; Nadamuni, Mridula; Nayyar, Megha; Liu, Brent; Duddalwar, Vinay; Lepore, Natasha

2015-12-01

A conventional radiology report primarily consists of a large amount of unstructured text, and lacks clear, concise, consistent and content-rich information. Hence, an area of unmet clinical need consists of developing better ways to communicate radiology findings and information specific to each patient. Here, we design a new workflow and reporting system that combines and integrates advances in engineering technology with those from the medical sciences, the Multidimensional Interactive Radiology Report and Analysis (MIRRA). Until recently, clinical standards have primarily relied on 2D images for the purpose of measurement, but with the advent of 3D processing, many of the manually measured metrics can be automated, leading to better reproducibility and less subjective measurement placement. Hence, we make use this newly available 3D processing in our workflow. Our pipeline is used here to standardize the labeling, tracking, and quantifying of metrics for renal masses.

Towards An Understanding of Mobile Touch Navigation in a Stereoscopic Viewing Environment for 3D Data Exploration.

PubMed

López, David; Oehlberg, Lora; Doger, Candemir; Isenberg, Tobias

2016-05-01

We discuss touch-based navigation of 3D visualizations in a combined monoscopic and stereoscopic viewing environment. We identify a set of interaction modes, and a workflow that helps users transition between these modes to improve their interaction experience. In our discussion we analyze, in particular, the control-display space mapping between the different reference frames of the stereoscopic and monoscopic displays. We show how this mapping supports interactive data exploration, but may also lead to conflicts between the stereoscopic and monoscopic views due to users' movement in space; we resolve these problems through synchronization. To support our discussion, we present results from an exploratory observational evaluation with domain experts in fluid mechanics and structural biology. These experts explored domain-specific datasets using variations of a system that embodies the interaction modes and workflows; we report on their interactions and qualitative feedback on the system and its workflow.

Genetic analysis of circulating tumor cells in pancreatic cancer patients: A pilot study.

PubMed

Görner, Karin; Bachmann, Jeannine; Holzhauer, Claudia; Kirchner, Roland; Raba, Katharina; Fischer, Johannes C; Martignoni, Marc E; Schiemann, Matthias; Alunni-Fabbroni, Marianna

2015-07-01

Pancreatic cancer is one of the most aggressive malignant tumors, mainly due to an aggressive metastasis spreading. In recent years, circulating tumor cells became associated to tumor metastasis. Little is known about their expression profiles. The aim of this study was to develop a complete workflow making it possible to isolate circulating tumor cells from patients with pancreatic cancer and their genetic characterization. We show that the proposed workflow offers a technical sensitivity and specificity high enough to detect and isolate single tumor cells. Moreover our approach makes feasible to genetically characterize single CTCs. Our work discloses a complete workflow to detect, count and genetically analyze individual CTCs isolated from blood samples. This method has a central impact on the early detection of metastasis development. The combination of cell quantification and genetic analysis provides the clinicians with a powerful tool not available so far. Copyright © 2015. Published by Elsevier Inc.

A software-aided workflow for precinct-scale residential redevelopment

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

Glackin, Stephen, E-mail: sglackin@swin.edu.au; Trubka, Roman, E-mail: r.trubka@gmail.com; Dionisio, Maria Rita, E-mail: rita.dionisio@canterbury.ac.nz

2016-09-15

Growing urban populations, combined with environmental challenges, have placed significant pressure on urban planning to supply housing while addressing policy issues such as sustainability, affordability, and liveability. The interrelated nature of these issues, combined with the requirement of evidence-based planning, has made decision-making so complex that urban planners need to combine expertise on energy, water, carbon emissions, transport and economic development along with other bodies of knowledge necessary to make well-informed decisions. This paper presents two geospatial software systems that can assist in the mediation of complexity, by allowing users to assess a variety of planning metrics without expert knowledgemore » in those disciplines. Using Envision and Envision Scenario Planner (ESP), both products of the Greening the Greyfields research project funded by the Cooperative Research Centre for Spatial Information (CRCSI) in Australia, we demonstrate a workflow for identifying potential redevelopment precincts and designing and assessing possible redevelopment scenarios to optimise planning outcomes.« less

Advances in microscale separations towards nanoproteomics applications

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

Yi, Lian; Piehowski, Paul D.; Shi, Tujin

Microscale separations (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. While significant advances have been achieved in MS-based proteomics, the current platforms still face a significant challenge in overall sensitivity towards nanoproteomics (i.e., with less than 1 g total amount of proteins available) applications such as cellular heterogeneity in tissue pathologies. Herein, we review recent advances in microscale separation techniques and integrated sample processing systems that improve the overall sensitivity and coverage of the proteomics workflow, and their contributionsmore » towards nanoproteomics applications.« less

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

PubMed

Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk

2016-05-01

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

A UHPLC-MS/MS method for profiling multifunctional steroids in human hair.

PubMed

Dong, Zhen; Wang, Caihong; Zhang, Jinlan; Wang, Zhe

2017-08-01

It is important to profile steroids in many physiological and pathological processes. Recently, hair has been used for the long-term measurement of endogenous steroid hormones. Analyzing hair has advantages of being noninvasive and time sequential compared with other bio-specimens. Liquid chromatography-mass spectrometry (LC-MS) techniques have been widely used over the past decades; however, it is challenging to profile estrogens in hair by LC-MS, and more comprehensive steroid profiling is required. In this paper, an ultra high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed to simultaneously profile 28 multifunctional steroids, including corticosteroids (n = 6), estrogens (n = 13), androgens (n = 5) and progestogens (n = 4), in human scalp hair in a single run. To optimize the sample preparation procedure, we evaluated extraction time, post-incubation purification and hair fragment length; 30 mg hair samples were washed with hexane, cut into 5 mm pieces and incubated in methanol for 18 h at 25 °C. Methanol extraction derivatized using Girard P and dansyl chloride reagent was analyzed within 25 min using an automated injection program combined with a diverter valve switch and step analysis (AIDSA). The method was well validated in terms of linearity, limit of detection (LOD), limit of quantification (LOQ), precision, accuracy, matrix effect and recovery, and was successfully applied to a steroid profile from male and female hairs. Significant differences were observed between genders. In addition, steroids showed a declining trend from the proximal to more distal hair segments; thus, care should be taken when obtaining hair samples for analysis to account for this difference in steroid levels along the length of hair. Graphical Abstract The workflow of the estabished UHPLC-MS/MS method.

An introduction to hybrid ion trap/time-of-flight mass spectrometry coupled with liquid chromatography applied to drug metabolism studies.

PubMed

Liu, Zhao-Ying

2012-12-01

Metabolism studies play an important role at various stages of drug discovery and development. Liquid chromatography combined with mass spectrometry (LC/MS) has become a most powerful and widely used analytical tool for identifying drug metabolites. The suitability of different types of mass spectrometers for metabolite profiling differs widely, and therefore, the data quality and reliability of the results also depend on which instrumentation is used. As one of the latest LC/MS instrumentation designs, hybrid ion trap/time-of-flight MS coupled with LC (LC-IT-TOF-MS) has successfully integrated ease of operation, compatibility with LC flow rates and data-dependent MS(n) with high mass accuracy and mass resolving power. The MS(n) and accurate mass capabilities are routinely utilized to rapidly confirm the identification of expected metabolites or to elucidate the structures of uncommon or unexpected metabolites. These features make the LC-IT-TOF-MS a very powerful analytical tool for metabolite identification. This paper begins with a brief introduction to some basic principles and main properties of a hybrid IT-TOF instrument. Then, a general workflow for metabolite profiling using LC-IT-TOF-MS, starting from sample collection and preparation to final identification of the metabolite structures, is discussed in detail. The data extraction and mining techniques to find and confirm metabolites are discussed and illustrated with some examples. This paper is directed to readers with no prior experience with LC-IT-TOF-MS and will provide a broad understanding of the development and utility of this instrument for drug metabolism studies. Copyright © 2012 John Wiley & Sons, Ltd.

Deglycosylation systematically improves N-glycoprotein identification in liquid chromatography-tandem mass spectrometry proteomics for analysis of cell wall stress responses in Saccharomyces cerevisiae lacking Alg3p.

PubMed

Bailey, Ulla-Maja; Schulz, Benjamin L

2013-04-01

Post-translational modification of proteins with glycosylation is of key importance in many biological systems in eukaryotes, influencing fundamental biological processes and regulating protein function. Changes in glycosylation are therefore of interest in understanding these processes and are also useful as clinical biomarkers of disease. The presence of glycosylation can also inhibit protease digestion and lower the quality and confidence of protein identification by mass spectrometry. While deglycosylation can improve the efficiency of subsequent protease digest and increase protein coverage, this step is often excluded from proteomic workflows. Here, we performed a systematic analysis that showed that deglycosylation with peptide-N-glycosidase F (PNGase F) prior to protease digestion with AspN or trypsin improved the quality of identification of the yeast cell wall proteome. The improvement in the confidence of identification of glycoproteins following PNGase F deglycosylation correlated with a higher density of glycosylation sites. Optimal identification across the proteome was achieved with PNGase F deglycosylation and complementary proteolysis with either AspN or trypsin. We used this combination of deglycosylation and complementary protease digest to identify changes in the yeast cell wall proteome caused by lack of the Alg3p protein, a key component of the biosynthetic pathway of protein N-glycosylation. The cell wall of yeast lacking Alg3p showed specifically increased levels of Cis3p, a protein important for cell wall integrity. Our results showed that deglycosylation prior to protease digestion improved the quality of proteomic analyses even if protein glycosylation is not of direct relevance to the study at hand. Copyright © 2013 Elsevier B.V. All rights reserved.

Immuno-affinity Capture Followed by TMPP N-Terminus Tagging to Study Catabolism of Therapeutic Proteins.

PubMed

Kullolli, Majlinda; Rock, Dan A; Ma, Ji

2017-02-03

Characterization of in vitro and in vivo catabolism of therapeutic proteins has increasingly become an integral part of discovery and development process for novel proteins. Unambiguous and efficient identification of catabolites can not only facilitate accurate understanding of pharmacokinetic profiles of drug candidates, but also enables follow up protein engineering to generate more catabolically stable molecules with improved properties (pharmacokinetics and pharmacodynamics). Immunoaffinity capture (IC) followed by top-down intact protein analysis using either matrix-assisted laser desorption/ionization or electrospray ionization mass spectrometry analysis have been the primary methods of choice for catabolite identification. However, the sensitivity and efficiency of these methods is not always sufficient for characterization of novel proteins from complex biomatrices such as plasma or serum. In this study a novel bottom-up targeted protein workflow was optimized for analysis of proteolytic degradation of therapeutic proteins. Selective and sensitive tagging of the alpha-amine at the N-terminus of proteins of interest was performed by immunoaffinity capture of therapeutic protein and its catabolites followed by on-bead succinimidyloxycarbonylmethyl tri-(2,4,6-trimethoxyphenyl N-terminus (TMPP-NTT) tagging. The positively charged hydrophobic TMPP tag facilitates unambiguous sequence identification of all N-terminus peptides from complex tryptic digestion samples via data dependent liquid chromatgraphy-tandem mass spectroscopy. Utility of the workflow was illustrated by definitive analysis of in vitro catabolic profile of neurotensin human Fc (NTs-huFc) protein in mouse serum. The results from this study demonstrated that the IC-TMPP-NTT workflow is a simple and efficient method for catabolite formation in therapeutic proteins.

Chairside Fabrication of an All-Ceramic Partial Crown Using a Zirconia-Reinforced Lithium Silicate Ceramic

PubMed Central

Pabel, Anne-Kathrin; Rödiger, Matthias

2016-01-01

The chairside fabrication of a monolithic partial crown using a zirconia-reinforced lithium silicate (ZLS) ceramic is described. The fully digitized model-free workflow in a dental practice is possible due to the use of a powder-free intraoral scanner and the computer-aided design/computer-assisted manufacturing (CAD/CAM) of the restorations. The innovative ZLS material offers a singular combination of fracture strength (>370 Mpa), optimum polishing characteristics, and excellent optical properties. Therefore, this ceramic is an interesting alternative material for monolithic restorations produced in a digital workflow. PMID:27042362

Formalizing an integrative, multidisciplinary cancer therapy discovery workflow

PubMed Central

McGuire, Mary F.; Enderling, Heiko; Wallace, Dorothy I.; Batra, Jaspreet; Jordan, Marie; Kumar, Sushil; Panetta, John C.; Pasquier, Eddy

2014-01-01

Although many clinicians and researchers work to understand cancer, there has been limited success to effectively combine forces and collaborate over time, distance, data and budget constraints. Here we present a workflow template for multidisciplinary cancer therapy that was developed during the 2nd Annual Workshop on Cancer Systems Biology sponsored by Tufts University, Boston, MA in July 2012. The template was applied to the development of a metronomic therapy backbone for neuroblastoma. Three primary groups were identified: clinicians, biologists, and scientists (mathematicians, computer scientists, physicists and engineers). The workflow described their integrative interactions; parallel or sequential processes; data sources and computational tools at different stages as well as the iterative nature of therapeutic development from clinical observations to in vitro, in vivo, and clinical trials. We found that theoreticians in dialog with experimentalists could develop calibrated and parameterized predictive models that inform and formalize sets of testable hypotheses, thus speeding up discovery and validation while reducing laboratory resources and costs. The developed template outlines an interdisciplinary collaboration workflow designed to systematically investigate the mechanistic underpinnings of a new therapy and validate that therapy to advance development and clinical acceptance. PMID:23955390

A reliable computational workflow for the selection of optimal screening libraries.

PubMed

Gilad, Yocheved; Nadassy, Katalin; Senderowitz, Hanoch

2015-01-01

The experimental screening of compound collections is a common starting point in many drug discovery projects. Successes of such screening campaigns critically depend on the quality of the screened library. Many libraries are currently available from different vendors yet the selection of the optimal screening library for a specific project is challenging. We have devised a novel workflow for the rational selection of project-specific screening libraries. The workflow accepts as input a set of virtual candidate libraries and applies the following steps to each library: (1) data curation; (2) assessment of ADME/T profile; (3) assessment of the number of promiscuous binders/frequent HTS hitters; (4) assessment of internal diversity; (5) assessment of similarity to known active compound(s) (optional); (6) assessment of similarity to in-house or otherwise accessible compound collections (optional). For ADME/T profiling, Lipinski's and Veber's rule-based filters were implemented and a new blood brain barrier permeation model was developed and validated (85 and 74 % success rate for training set and test set, respectively). Diversity and similarity descriptors which demonstrated best performances in terms of their ability to select either diverse or focused sets of compounds from three databases (Drug Bank, CMC and CHEMBL) were identified and used for diversity and similarity assessments. The workflow was used to analyze nine common screening libraries available from six vendors. The results of this analysis are reported for each library providing an assessment of its quality. Furthermore, a consensus approach was developed to combine the results of these analyses into a single score for selecting the optimal library under different scenarios. We have devised and tested a new workflow for the rational selection of screening libraries under different scenarios. The current workflow was implemented using the Pipeline Pilot software yet due to the usage of generic components, it can be easily adapted and reproduced by computational groups interested in rational selection of screening libraries. Furthermore, the workflow could be readily modified to include additional components. This workflow has been routinely used in our laboratory for the selection of libraries in multiple projects and consistently selects libraries which are well balanced across multiple parameters.Graphical abstract.

SU-E-T-419: Workflow and FMEA in a New Proton Therapy (PT) Facility

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

Cheng, C; Wessels, B; Hamilton, H

2014-06-01

Purpose: Workflow is an important component in the operational planning of a new proton facility. By integrating the concept of failure mode and effect analysis (FMEA) and traditional QA requirements, a workflow for a proton therapy treatment course is set up. This workflow serves as the blue print for the planning of computer hardware/software requirements and network flow. A slight modification of the workflow generates a process map(PM) for FMEA and the planning of QA program in PT. Methods: A flowchart is first developed outlining the sequence of processes involved in a PT treatment course. Each process consists of amore » number of sub-processes to encompass a broad scope of treatment and QA procedures. For each subprocess, the personnel involved, the equipment needed and the computer hardware/software as well as network requirements are defined by a team of clinical staff, administrators and IT personnel. Results: Eleven intermediate processes with a total of 70 sub-processes involved in a PT treatment course are identified. The number of sub-processes varies, ranging from 2-12. The sub-processes within each process are used for the operational planning. For example, in the CT-Sim process, there are 12 sub-processes: three involve data entry/retrieval from a record-and-verify system, two controlled by the CT computer, two require department/hospital network, and the other five are setup procedures. IT then decides the number of computers needed and the software and network requirement. By removing the traditional QA procedures from the workflow, a PM is generated for FMEA analysis to design a QA program for PT. Conclusion: Significant efforts are involved in the development of the workflow in a PT treatment course. Our hybrid model of combining FMEA and traditional QA program serves a duo purpose of efficient operational planning and designing of a QA program in PT.« less

Seamless online science workflow development and collaboration using IDL and the ENVI Services Engine

NASA Astrophysics Data System (ADS)

Harris, A. T.; Ramachandran, R.; Maskey, M.

2013-12-01

The Exelis-developed IDL and ENVI software are ubiquitous tools in Earth science research environments. The IDL Workbench is used by the Earth science community for programming custom data analysis and visualization modules. ENVI is a software solution for processing and analyzing geospatial imagery that combines support for multiple Earth observation scientific data types (optical, thermal, multi-spectral, hyperspectral, SAR, LiDAR) with advanced image processing and analysis algorithms. The ENVI & IDL Services Engine (ESE) is an Earth science data processing engine that allows researchers to use open standards to rapidly create, publish and deploy advanced Earth science data analytics within any existing enterprise infrastructure. Although powerful in many ways, the tools lack collaborative features out-of-box. Thus, as part of the NASA funded project, Collaborative Workbench to Accelerate Science Algorithm Development, researchers at the University of Alabama in Huntsville and Exelis have developed plugins that allow seamless research collaboration from within IDL workbench. Such additional features within IDL workbench are possible because IDL workbench is built using the Eclipse Rich Client Platform (RCP). RCP applications allow custom plugins to be dropped in for extended functionalities. Specific functionalities of the plugins include creating complex workflows based on IDL application source code, submitting workflows to be executed by ESE in the cloud, and sharing and cloning of workflows among collaborators. All these functionalities are available to scientists without leaving their IDL workbench. Because ESE can interoperate with any middleware, scientific programmers can readily string together IDL processing tasks (or tasks written in other languages like C++, Java or Python) to create complex workflows for deployment within their current enterprise architecture (e.g. ArcGIS Server, GeoServer, Apache ODE or SciFlo from JPL). Using the collaborative IDL Workbench, coupled with ESE for execution in the cloud, asynchronous workflows could be executed in batch mode on large data in the cloud. We envision that a scientist will initially develop a scientific workflow locally on a small set of data. Once tested, the scientist will deploy the workflow to the cloud for execution. Depending on the results, the scientist may share the workflow and results, allowing them to be stored in a community catalog and instantly loaded into the IDL Workbench of other scientists. Thereupon, scientists can clone and modify or execute the workflow with different input parameters. The Collaborative Workbench will provide a platform for collaboration in the cloud, helping Earth scientists solve big-data problems in the Earth and planetary sciences.

New hardware and workflows for semi-automated correlative cryo-fluorescence and cryo-electron microscopy/tomography.

PubMed

Schorb, Martin; Gaechter, Leander; Avinoam, Ori; Sieckmann, Frank; Clarke, Mairi; Bebeacua, Cecilia; Bykov, Yury S; Sonnen, Andreas F-P; Lihl, Reinhard; Briggs, John A G

2017-02-01

Correlative light and electron microscopy allows features of interest defined by fluorescence signals to be located in an electron micrograph of the same sample. Rare dynamic events or specific objects can be identified, targeted and imaged by electron microscopy or tomography. To combine it with structural studies using cryo-electron microscopy or tomography, fluorescence microscopy must be performed while maintaining the specimen vitrified at liquid-nitrogen temperatures and in a dry environment during imaging and transfer. Here we present instrumentation, software and an experimental workflow that improves the ease of use, throughput and performance of correlated cryo-fluorescence and cryo-electron microscopy. The new cryo-stage incorporates a specially modified high-numerical aperture objective lens and provides a stable and clean imaging environment. It is combined with a transfer shuttle for contamination-free loading of the specimen. Optimized microscope control software allows automated acquisition of the entire specimen area by cryo-fluorescence microscopy. The software also facilitates direct transfer of the fluorescence image and associated coordinates to the cryo-electron microscope for subsequent fluorescence-guided automated imaging. Here we describe these technological developments and present a detailed workflow, which we applied for automated cryo-electron microscopy and tomography of various specimens. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A Flexible Workflow for Automated Bioluminescent Kinase Selectivity Profiling.

PubMed

Worzella, Tracy; Butzler, Matt; Hennek, Jacquelyn; Hanson, Seth; Simdon, Laura; Goueli, Said; Cowan, Cris; Zegzouti, Hicham

2017-04-01

Kinase profiling during drug discovery is a necessary process to confirm inhibitor selectivity and assess off-target activities. However, cost and logistical limitations prevent profiling activities from being performed in-house. We describe the development of an automated and flexible kinase profiling workflow that combines ready-to-use kinase enzymes and substrates in convenient eight-tube strips, a bench-top liquid handling device, ADP-Glo Kinase Assay (Promega, Madison, WI) technology to quantify enzyme activity, and a multimode detection instrument. Automated methods were developed for kinase reactions and quantification reactions to be assembled on a Gilson (Middleton, WI) PIPETMAX, following standardized plate layouts for single- and multidose compound profiling. Pipetting protocols were customized at runtime based on user-provided information, including compound number, increment for compound titrations, and number of kinase families to use. After the automated liquid handling procedures, a GloMax Discover (Promega) microplate reader preloaded with SMART protocols was used for luminescence detection and automatic data analysis. The functionality of the automated workflow was evaluated with several compound-kinase combinations in single-dose or dose-response profiling formats. Known target-specific inhibitions were confirmed. Novel small molecule-kinase interactions, including off-target inhibitions, were identified and confirmed in secondary studies. By adopting this streamlined profiling process, researchers can quickly and efficiently profile compounds of interest on site.

MetaNET--a web-accessible interactive platform for biological metabolic network analysis.

PubMed

Narang, Pankaj; Khan, Shawez; Hemrom, Anmol Jaywant; Lynn, Andrew Michael

2014-01-01

Metabolic reactions have been extensively studied and compiled over the last century. These have provided a theoretical base to implement models, simulations of which are used to identify drug targets and optimize metabolic throughput at a systemic level. While tools for the perturbation of metabolic networks are available, their applications are limited and restricted as they require varied dependencies and often a commercial platform for full functionality. We have developed MetaNET, an open source user-friendly platform-independent and web-accessible resource consisting of several pre-defined workflows for metabolic network analysis. MetaNET is a web-accessible platform that incorporates a range of functions which can be combined to produce different simulations related to metabolic networks. These include (i) optimization of an objective function for wild type strain, gene/catalyst/reaction knock-out/knock-down analysis using flux balance analysis. (ii) flux variability analysis (iii) chemical species participation (iv) cycles and extreme paths identification and (v) choke point reaction analysis to facilitate identification of potential drug targets. The platform is built using custom scripts along with the open-source Galaxy workflow and Systems Biology Research Tool as components. Pre-defined workflows are available for common processes, and an exhaustive list of over 50 functions are provided for user defined workflows. MetaNET, available at http://metanet.osdd.net , provides a user-friendly rich interface allowing the analysis of genome-scale metabolic networks under various genetic and environmental conditions. The framework permits the storage of previous results, the ability to repeat analysis and share results with other users over the internet as well as run different tools simultaneously using pre-defined workflows, and user-created custom workflows.

Querying Provenance Information: Basic Notions and an Example from Paleoclimate Reconstruction

NASA Astrophysics Data System (ADS)

Stodden, V.; Ludaescher, B.; Bocinsky, K.; Kintigh, K.; Kohler, T.; McPhillips, T.; Rush, J.

2016-12-01

Computational models are used to reconstruct and explain past environments and to predict likely future environments. For example, Bocinsky and Kohler have performed a 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest. The resulting academic publications not only contain traditional method descriptions, figures, etc. but also links to code and data for basic transparency and reproducibility. Examples include ResearchCompendia.org and the new project "Merging Science and Cyberinfrastructure Pathways: The Whole Tale." Provenance information provides a further critical element to understand a published study and to possibly extend or challenge the findings of the original authors. We present different notions and uses of provenance information using a computational archaeology example, e.g., the common use of "provenance for others" (for transparency and reproducibility), but also the more elusive but equally important use of "provenance for self". To this end, we distinguish prospective provenance (a.k.a. workflow) from retrospective provenance (a.k.a. data lineage) and show how combinations of both forms of provenance can be used to answer different kinds of important questions about a workflow and its execution. Since many workflows are developed using scripting or special purpose languages such as Python and R, we employ an approach and toolkit called YesWorkflow that brings provenance modeling, capture, and querying into the realm of scripting. YesWorkflow employs the basic W3C PROV standard, as well as the ProvONE extension for sharing and exchanging retrospective and prospective provenance information, respectively. Finally, we argue that the utility of provenance information should be maximized by developing different kinds provenance questions and queries during the early phases of computational workflow design and implementation.

Targeted Selected Reaction Monitoring Mass Spectrometric Immunoassay for Insulin-like Growth Factor 1

PubMed Central

Niederkofler, Eric E.; Phillips, David A.; Krastins, Bryan; Kulasingam, Vathany; Kiernan, Urban A.; Tubbs, Kemmons A.; Peterman, Scott M.; Prakash, Amol; Diamandis, Eleftherios P.; Lopez, Mary F.; Nedelkov, Dobrin

2013-01-01

Insulin-like growth factor 1 (IGF1) is an important biomarker of human growth disorders that is routinely analyzed in clinical laboratories. Mass spectrometry-based workflows offer a viable alternative to standard IGF1 immunoassays, which utilize various pre-analytical preparation strategies. In this work we developed an assay that incorporates a novel sample preparation method for dissociating IGF1 from its binding proteins. The workflow also includes an immunoaffinity step using antibody-derivatized pipette tips, followed by elution, trypsin digestion, and LC-MS/MS separation and detection of the signature peptides in a selected reaction monitoring (SRM) mode. The resulting quantitative mass spectrometric immunoassay (MSIA) exhibited good linearity in the range of 1 to 1,500 ng/mL IGF1, intra- and inter-assay precision with CVs of less than 10%, and lowest limits of detection of 1 ng/mL. The linearity and recovery characteristics of the assay were also established, and the new method compared to a commercially available immunoassay using a large cohort of human serum samples. The IGF1 SRM MSIA is well suited for use in clinical laboratories. PMID:24278387

Searching for microbial protein over-expression in a complex matrix using automated high throughput MS-based proteomics tools.

PubMed

Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob

2013-03-10

In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.

Antibody-Coupled Magnetic Beads Can Be Reused in Immuno-MRM Assays To Reduce Cost and Extend Antibody Supply.

PubMed

Zhao, Lei; Whiteaker, Jeffrey R; Voytovich, Uliana J; Ivey, Richard G; Paulovich, Amanda G

2015-10-02

Immunoaffinity enrichment of peptides coupled to targeted, multiple reaction monitoring mass spectrometry (immuno-MRM) enables precise quantification of peptides. Affinity-purified polyclonal antibodies are routinely used as affinity reagents in immuno-MRM assays, but they are not renewable, limiting the number of experiments that can be performed. In this technical note, we describe a workflow to regenerate anti-peptide polyclonal antibodies coupled to magnetic beads for enrichments in multiplex immuno-MRM assays. A multiplexed panel of 44 antibodies (targeting 60 peptides) is used to show that peptide analytes can be effectively stripped off of antibodies using acid washing without compromising assay performance. The performance of the multiplexed panel (determined by correlation, agreement, and precision of reused assays) is reproducible (R(2) between 0.81 and 0.99) and consistent (median CVs 8-15%) for at least 10 times of washing and reuse. Application of this workflow to immuno-MRM studies greatly reduces per sample assay cost and increases the number of samples that can be interrogated with a limited supply of polyclonal antibody reagent. This allows more characterization for promising and desirable targets prior to committing funds and efforts to conversion to a renewable monoclonal antibody.

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

PubMed Central

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

2011-01-01

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

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

PubMed

Lehmann, Sylvain; Hoofnagle, Andrew; Hochstrasser, Denis; Brede, Cato; Glueckmann, Matthias; Cocho, José A; Ceglarek, Uta; Lenz, Christof; Vialaret, Jérôme; Scherl, Alexander; Hirtz, Christophe

2013-05-01

Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).

Mass Spectrometry Based Lipidomics: An Overview of Technological Platforms

PubMed Central

Köfeler, Harald C.; Fauland, Alexander; Rechberger, Gerald N.; Trötzmüller, Martin

2012-01-01

One decade after the genomic and the proteomic life science revolution, new ‘omics’ fields are emerging. The metabolome encompasses the entity of small molecules—Most often end products of a catalytic process regulated by genes and proteins—with the lipidome being its fat soluble subdivision. Within recent years, lipids are more and more regarded not only as energy storage compounds but also as interactive players in various cellular regulation cycles and thus attain rising interest in the bio-medical community. The field of lipidomics is, on one hand, fuelled by analytical technology advances, particularly mass spectrometry and chromatography, but on the other hand new biological questions also drive analytical technology developments. Compared to fairly standardized genomic or proteomic high-throughput protocols, the high degree of molecular heterogeneity adds a special analytical challenge to lipidomic analysis. In this review, we will take a closer look at various mass spectrometric platforms for lipidomic analysis. We will focus on the advantages and limitations of various experimental setups like ‘shotgun lipidomics’, liquid chromatography—Mass spectrometry (LC-MS) and matrix assisted laser desorption ionization-time of flight (MALDI-TOF) based approaches. We will also examine available software packages for data analysis, which nowadays is in fact the rate limiting step for most ‘omics’ workflows. PMID:24957366

The direct analysis of drug distribution of rotigotine-loaded microspheres from tissue sections by LESA coupled with tandem mass spectrometry.

PubMed

Xu, Li-Xiao; Wang, Tian-Tian; Geng, Yin-Yin; Wang, Wen-Yan; Li, Yin; Duan, Xiao-Kun; Xu, Bin; Liu, Charles C; Liu, Wan-Hui

2017-09-01

The direct analysis of drug distribution of rotigotine-loaded microspheres (RoMS) from tissue sections by liquid extraction surface analysis (LESA) coupled with tandem mass spectrometry (MS/MS) was demonstrated. The RoMS distribution in rat tissues assessed by the ambient LESA-MS/MS approach without extensive or tedious sample pretreatment was compared with that obtained by a conventional liquid chromatography tandem mass spectrometry (LC-MS/MS) method in which organ excision and subsequent solvent extraction were commonly employed before analysis. Results obtained from the two were well correlated for a majority of the organs, such as muscle, liver, stomach, and hippocampus. The distribution of RoMS in the brain, however, was found to be mainly focused in the hippocampus and striatum regions as shown by the LESA-imaged profiles. The LESA approach we developed is sensitive enough, with an estimated LLOQ at 0.05 ng/mL of rotigotine in brain tissue, and information-rich with minimal sample preparation, suitable, and promising in assisting the development of new drug delivery systems for controlled drug release and protection. Graphical abstract Workflow for the LESA-MS/MS imaging of brain tissue section after intramuscular RoMS administration.

Influence of heteroatom pre-selection on the molecular formula assignment of soil organic matter components determined by ultrahigh resolution mass spectrometry.

PubMed

Ohno, Tsutomu; Ohno, Paul E

2013-04-01

Soil organic matter (SOM) is involved in many important ecosystem processes. Ultrahigh resolution mass spectrometry has become a powerful technique in the chemical characterization of SOM, allowing assignment of elemental formulae for thousands of peaks resolved in a typical mass spectrum. We investigated how the addition of N, S, and P heteroatoms in the formula calculation stage of the mass spectra processing workflow affected the formula assignments of mass spectra peaks. Dissolved organic matter extracted from plant biomass and soil as well as the soil humic acid fraction was studied. We show that the addition of S and P into the molecular formula calculation increased peak assignments on average by 17.3 % and 10.7 %, respectively, over the assignments based on the CHON elements frequently reported by SOM researchers using ultrahigh resolution mass spectrometry. The organic matter chemical characteristics as represented by van Krevelen diagrams were appreciably affected by differences in the heteroatom pre-selection for the three organic matter samples investigated, especially so for the wheat-derived dissolved organic matter. These results show that inclusion of both S and P heteroatoms into the formula calculation step, which is not routinely done, is important to obtain a more chemically complete interpretation of the ultrahigh resolution mass spectra of SOM.

Biomolecular signatures of diabetic wound healing by structural mass spectrometry

PubMed Central

Hines, Kelly M.; Ashfaq, Samir; Davidson, Jeffrey M.; Opalenik, Susan R.; Wikswo, John P.; McLean, John A.

2013-01-01

Wound fluid is a complex biological sample containing byproducts associated with the wound repair process. Contemporary techniques, such as immunoblotting and enzyme immunoassays, require extensive sample manipulation and do not permit the simultaneous analysis of multiple classes of biomolecular species. Structural mass spectrometry, implemented as ion mobility-mass spectrometry (IM-MS), comprises two sequential, gas-phase dispersion techniques well suited for the study of complex biological samples due to its ability to separate and simultaneously analyze multiple classes of biomolecules. As a model of diabetic wound healing, polyvinyl alcohol (PVA) sponges were inserted subcutaneously into non-diabetic (control) and streptozotocin-induced diabetic rats to elicit a granulation tissue response and to collect acute wound fluid. Sponges were harvested at days 2 or 5 to capture different stages of the early wound healing process. Utilizing IM-MS, statistical analysis, and targeted ultra-performance liquid chromatography (UPLC) analysis, biomolecular signatures of diabetic wound healing have been identified. The protein S100-A8 was highly enriched in the wound fluids collected from day 2 diabetic rats. Lysophosphatidylcholine (20:4) and cholic acid also contributed significantly to the differences between diabetic and control groups. This report provides a generalized workflow for wound fluid analysis demonstrated with a diabetic rat model. PMID:23452326

Mass spectrometry based lipidomics: an overview of technological platforms.

PubMed

Köfeler, Harald C; Fauland, Alexander; Rechberger, Gerald N; Trötzmüller, Martin

2012-01-05

One decade after the genomic and the proteomic life science revolution, new 'omics' fields are emerging. The metabolome encompasses the entity of small molecules-Most often end products of a catalytic process regulated by genes and proteins-with the lipidome being its fat soluble subdivision. Within recent years, lipids are more and more regarded not only as energy storage compounds but also as interactive players in various cellular regulation cycles and thus attain rising interest in the bio-medical community. The field of lipidomics is, on one hand, fuelled by analytical technology advances, particularly mass spectrometry and chromatography, but on the other hand new biological questions also drive analytical technology developments. Compared to fairly standardized genomic or proteomic high-throughput protocols, the high degree of molecular heterogeneity adds a special analytical challenge to lipidomic analysis. In this review, we will take a closer look at various mass spectrometric platforms for lipidomic analysis. We will focus on the advantages and limitations of various experimental setups like 'shotgun lipidomics', liquid chromatography-Mass spectrometry (LC-MS) and matrix assisted laser desorption ionization-time of flight (MALDI-TOF) based approaches. We will also examine available software packages for data analysis, which nowadays is in fact the rate limiting step for most 'omics' workflows.

Improved framework model to allocate optimal rainwater harvesting sites in small watersheds for agro-forestry uses

NASA Astrophysics Data System (ADS)

Terêncio, D. P. S.; Sanches Fernandes, L. F.; Cortes, R. M. V.; Pacheco, F. A. L.

2017-07-01

This study introduces an improved rainwater harvesting (RWH) suitability model to help the implementation of agro-forestry projects (irrigation, wildfire combat) in catchments. The model combines a planning workflow to define suitability of catchments based on physical, socio-economic and ecologic variables, with an allocation workflow to constrain suitable RWH sites as function of project specific features (e.g., distance from rainfall collection to application area). The planning workflow comprises a Multi Criteria Analysis (MCA) implemented on a Geographic Information System (GIS), whereas the allocation workflow is based on a multiple-parameter ranking analysis. When compared to other similar models, improvement comes with the flexible weights of MCA and the entire allocation workflow. The method is tested in a contaminated watershed (the Ave River basin) located in Portugal. The pilot project encompasses the irrigation of a 400 ha crop land that consumes 2.69 Mm3 of water per year. The application of harvested water in the irrigation replaces the use of stream water with excessive anthropogenic nutrients that may raise nitrosamines in the food and accumulation in the food chain, with severe consequences to human health (cancer). The selected rainfall collection catchment is capable to harvest 12 Mm3·yr-1 (≈ 4.5 × the requirement) and is roughly 3 km far from the application area assuring crop irrigation by gravity flow with modest transport costs. The RWH system is an 8-meter high that can be built in earth with reduced costs.

Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

PubMed Central

Grüning, Björn A.; Paszkiewicz, Konrad; Pritchard, Leighton

2013-01-01

The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of “effector” proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen’s predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology. This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols. The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed (http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu). PMID:24109552

Development of a High-Throughput Ion-Exchange Resin Characterization Workflow.

PubMed

Liu, Chun; Dermody, Daniel; Harris, Keith; Boomgaard, Thomas; Sweeney, Jeff; Gisch, Daryl; Goltz, Bob

2017-06-12

A novel high-throughout (HTR) ion-exchange (IEX) resin workflow has been developed for characterizing ion exchange equilibrium of commercial and experimental IEX resins against a range of different applications where water environment differs from site to site. Because of its much higher throughput, design of experiment (DOE) methodology can be easily applied for studying the effects of multiple factors on resin performance. Two case studies will be presented to illustrate the efficacy of the combined HTR workflow and DOE method. In case study one, a series of anion exchange resins have been screened for selective removal of NO 3 - and NO 2 - in water environments consisting of multiple other anions, varied pH, and ionic strength. The response surface model (RSM) is developed to statistically correlate the resin performance with the water composition and predict the best resin candidate. In case study two, the same HTR workflow and DOE method have been applied for screening different cation exchange resins in terms of the selective removal of Mg 2+ , Ca 2+ , and Ba 2+ from high total dissolved salt (TDS) water. A master DOE model including all of the cation exchange resins is created to predict divalent cation removal by different IEX resins under specific conditions, from which the best resin candidates can be identified. The successful adoption of HTR workflow and DOE method for studying the ion exchange of IEX resins can significantly reduce the resources and time to address industry and application needs.

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data*

PubMed Central

Mitchell, Christopher J.; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-01-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, 15N, 13C, or 18O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25–45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. PMID:27231314

Combining Metabolic ¹⁵N Labeling with Improved Tandem MOAC for Enhanced Probing of the Phosphoproteome.

PubMed

Thomas, Martin; Huck, Nicola; Hoehenwarter, Wolfgang; Conrath, Uwe; Beckers, Gerold J M

2015-01-01

In eukaryotic cells many diverse cellular functions are regulated by reversible protein phosphorylation. In recent years, phosphoproteomics has become a powerful tool for studying protein phosphorylation because it enables unbiased localization, and site-specific quantification of in vivo phosphorylation of hundreds of proteins in a single experiment. A common strategy for identifying phosphoproteins and their phosphorylation sites from complex biological samples is the enrichment of phosphopeptides from digested cellular lysates followed by mass spectrometry. However, despite high sensitivity of modern mass spectrometers the large dynamic range of protein abundance and the transient nature of protein phosphorylation remained major pitfalls in MS-based phosphoproteomics. This is particularly true for plants in which the presence of secondary metabolites and endogenous compounds, the overabundance of ribulose-1,5-bisphosphate carboxylase and other components of the photosynthetic apparatus, and the concurrent difficulties in protein extraction necessitate two-step phosphoprotein/phosphopeptide enrichment strategies (Nakagami et al., Plant Cell Physiol 53:118-124, 2012).Approaches for label-free peptide quantification are advantageous due to their low cost and experimental simplicity, but they lack precision. These drawbacks can be overcome by metabolic labeling of whole plants with heavy nitrogen ((15)N) which allows combining two samples very early in the phosphoprotein enrichment workflow. This avoids sample-to-sample variation introduced by the analytical procedures and it results in robust relative quantification values that need no further standardization. The integration of (15)N metabolic labeling into tandem metal-oxide affinity chromatography (MOAC) (Hoehenwarter et al., Mol Cell Proteomics 12:369-380, 2013) presents an improved and highly selective approach for the identification and accurate site-specific quantification of low-abundance phosphoproteins that is based on the successive enrichment of light and heavy nitrogen-labeled phosphoproteins and peptides. This improved strategy combines metabolic labeling of whole plants with the stable heavy nitrogen isotope ((15)N), protein extraction under denaturing conditions, phosphoprotein enrichment using Al(OH)3-based MOAC, and tryptic digest of enriched phosphoproteins followed by TiO2-based MOAC of phosphopeptides and quantitative phosphopeptide measurement by liquid chromatography (LC) and high-resolution accurate mass (HR/AM) mass spectrometry (MS). Thus, tandem MOAC effectively targets the phosphate moiety of phosphoproteins and phosphopeptides and allows probing of the phosphoproteome to unprecedented depth, while (15)N metabolic labeling enables accurate relative quantification of measured peptides and direct comparison between samples.

Anti-Peptide Monoclonal Antibodies Generated for Immuno-Multiple Reaction Monitoring-Mass Spectrometry Assays Have a High Probability of Supporting Western blot and ELISA*

PubMed Central

Schoenherr, Regine M.; Saul, Richard G.; Whiteaker, Jeffrey R.; Yan, Ping; Whiteley, Gordon R.; Paulovich, Amanda G.

2015-01-01

Immunoaffinity enrichment of peptides coupled to targeted, multiple reaction monitoring-mass spectrometry (immuno-MRM) has recently been developed for quantitative analysis of peptide and protein expression. As part of this technology, antibodies are generated to short, linear, tryptic peptides that are well-suited for detection by mass spectrometry. Despite its favorable analytical performance, a major obstacle to widespread adoption of immuno-MRM is a lack of validated affinity reagents because commercial antibody suppliers are reluctant to commit resources to producing anti-peptide antibodies for immuno-MRM while the market is much larger for conventional technologies, especially Western blotting and ELISA. Part of this reluctance has been the concern that affinity reagents generated to short, linear, tryptic peptide sequences may not perform well in traditional assays that detect full-length proteins. In this study, we test the feasibility and success rates of generating immuno-MRM monoclonal antibodies (mAbs) (targeting tryptic peptide antigens) that are also compatible with conventional, protein-based immuno-affinity technologies. We generated 40 novel, peptide immuno-MRM assays and determined that the cross-over success rates for using immuno-MRM monoclonals for Western blotting is 58% and for ELISA is 43%, which compare favorably to cross-over success rates amongst conventional immunoassay technologies. These success rates could most likely be increased if conventional and immuno-MRM antigen design strategies were combined, and we suggest a workflow for such a comprehensive approach. Additionally, the 40 novel immuno-MRM assays underwent fit-for-purpose analytical validation, and all mAbs and assays have been made available as a resource to the community via the Clinical Proteomic Tumor Analysis Consortium's (CPTAC) Antibody (http://antibodies.cancer.gov) and Assay Portals (http://assays.cancer.gov), respectively. This study also represents the first determination of the success rate (92%) for generating mAbs for immuno-MRM using a recombinant B cell cloning approach, which is considerably faster than the traditional hybridoma approach. PMID:25512614

iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation

PubMed Central

2014-01-01

Background Comprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle in mass spectrometry-based proteomic analysis. To provide a solution, an alternative analytic strategy to confidently identify phosphorylated peptides by using the alkaline phosphatase (AP) treatment combined with high-resolution mass spectrometry was provided. While the process is applicable, the key integration along the pipeline was mostly done by tedious manual work. Results We developed a software toolkit, iPhos, to facilitate and streamline the work-flow of AP-assisted phosphoproteome characterization. The iPhos tookit includes one assister and three modules. The iPhos Peak Extraction Assister automates the batch mode peak extraction for multiple liquid chromatography mass spectrometry (LC-MS) runs. iPhos Module-1 can process the peak lists extracted from the LC-MS analyses derived from the original and dephosphorylated samples to mine out potential phosphorylated peptide signals based on mass shift caused by the loss of some multiples of phosphate groups. And iPhos Module-2 provides customized inclusion lists with peak retention time windows for subsequent targeted LC-MS/MS experiments. Finally, iPhos Module-3 facilitates to link the peptide identifications from protein search engines to the quantification results from pattern-based label-free quantification tools. We further demonstrated the utility of the iPhos toolkit on the data of human metastatic lung cancer cells (CL1-5). Conclusions In the comparison study of the control group of CL1-5 cell lysates and the treatment group of dasatinib-treated CL1-5 cell lysates, we demonstrated the applicability of the iPhos toolkit and reported the experimental results based on the iPhos-facilitated phosphoproteome investigation. And further, we also compared the strategy with pure DDA-based LC-MS/MS phosphoproteome investigation. The results of iPhos-facilitated targeted LC-MS/MS analysis convey more thorough and confident phosphopeptide identification than the results of pure DDA-based analysis. PMID:25521246

Performance of combined fragmentation and retention prediction for the identification of organic micropollutants by LC-HRMS.

PubMed

Hu, Meng; Müller, Erik; Schymanski, Emma L; Ruttkies, Christoph; Schulze, Tobias; Brack, Werner; Krauss, Martin

2018-03-01

In nontarget screening, structure elucidation of small molecules from high resolution mass spectrometry (HRMS) data is challenging, particularly the selection of the most likely candidate structure among the many retrieved from compound databases. Several fragmentation and retention prediction methods have been developed to improve this candidate selection. In order to evaluate their performance, we compared two in silico fragmenters (MetFrag and CFM-ID) and two retention time prediction models (based on the chromatographic hydrophobicity index (CHI) and on log D). A set of 78 known organic micropollutants was analyzed by liquid chromatography coupled to a LTQ Orbitrap HRMS with electrospray ionization (ESI) in positive and negative mode using two fragmentation techniques with different collision energies. Both fragmenters (MetFrag and CFM-ID) performed well for most compounds, with average ranking the correct candidate structure within the top 25% and 22 to 37% for ESI+ and ESI- mode, respectively. The rank of the correct candidate structure slightly improved when MetFrag and CFM-ID were combined. For unknown compounds detected in both ESI+ and ESI-, generally positive mode mass spectra were better for further structure elucidation. Both retention prediction models performed reasonably well for more hydrophobic compounds but not for early eluting hydrophilic substances. The log D prediction showed a better accuracy than the CHI model. Although the two fragmentation prediction methods are more diagnostic and sensitive for candidate selection, the inclusion of retention prediction by calculating a consensus score with optimized weighting can improve the ranking of correct candidates as compared to the individual methods. Graphical abstract Consensus workflow for combining fragmentation and retention prediction in LC-HRMS-based micropollutant identification.

SHIWA Services for Workflow Creation and Sharing in Hydrometeorolog

NASA Astrophysics Data System (ADS)

Terstyanszky, Gabor; Kiss, Tamas; Kacsuk, Peter; Sipos, Gergely

2014-05-01

Researchers want to run scientific experiments on Distributed Computing Infrastructures (DCI) to access large pools of resources and services. To run these experiments requires specific expertise that they may not have. Workflows can hide resources and services as a virtualisation layer providing a user interface that researchers can use. There are many scientific workflow systems but they are not interoperable. To learn a workflow system and create workflows may require significant efforts. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows developed in other workflow systems. To overcome it requires creating workflow interoperability solutions to allow workflow sharing. The FP7 'Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs' (SHIWA) project developed the Coarse-Grained Interoperability concept (CGI). It enables recycling and sharing workflows of different workflow systems and executing them on different DCIs. SHIWA developed the SHIWA Simulation Platform (SSP) to implement the CGI concept integrating three major components: the SHIWA Science Gateway, the workflow engines supported by the CGI concept and DCI resources where workflows are executed. The science gateway contains a portal, a submission service, a workflow repository and a proxy server to support the whole workflow life-cycle. The SHIWA Portal allows workflow creation, configuration, execution and monitoring through a Graphical User Interface using the WS-PGRADE workflow system as the host workflow system. The SHIWA Repository stores the formal description of workflows and workflow engines plus executables and data needed to execute them. It offers a wide-range of browse and search operations. To support non-native workflow execution the SHIWA Submission Service imports the workflow and workflow engine from the SHIWA Repository. This service either invokes locally or remotely pre-deployed workflow engines or submits workflow engines with the workflow to local or remote resources to execute workflows. The SHIWA Proxy Server manages certificates needed to execute the workflows on different DCIs. Currently SSP supports sharing of ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflows. Further workflow systems can be added to the simulation platform as required by research communities. The FP7 'Building a European Research Community through Interoperable Workflows and Data' (ER-flow) project disseminates the achievements of the SHIWA project to build workflow user communities across Europe. ER-flow provides application supports to research communities within (Astrophysics, Computational Chemistry, Heliophysics and Life Sciences) and beyond (Hydrometeorology and Seismology) to develop, share and run workflows through the simulation platform. The simulation platform supports four usage scenarios: creating and publishing workflows in the repository, searching and selecting workflows in the repository, executing non-native workflows and creating and running meta-workflows. The presentation will outline the CGI concept, the SHIWA Simulation Platform, the ER-flow usage scenarios and how the Hydrometeorology research community runs simulations on SSP.

Summative Objective Structured Clinical Examination Assessment at the End of Anesthesia Residency for Perioperative Ultrasound.

PubMed

Mitchell, John D; Amir, Rabia; Montealegre-Gallegos, Mario; Mahmood, Feroze; Shnider, Marc; Mashari, Azad; Yeh, Lu; Bose, Ruma; Wong, Vanessa; Hess, Philip; Amador, Yannis; Jeganathan, Jelliffe; Jones, Stephanie B; Matyal, Robina

2018-06-01

While standardized examinations and data from simulators and phantom models can assess knowledge and manual skills for ultrasound, an Objective Structured Clinical Examination (OSCE) could assess workflow understanding. We recruited 8 experts to develop an OSCE to assess workflow understanding in perioperative ultrasound. The experts used a binary grading system to score 19 graduating anesthesia residents at 6 stations. Overall average performance was 86.2%, and 3 stations had an acceptable internal reliability (Kuder-Richardson formula 20 coefficient >0.5). After refinement, this OSCE can be combined with standardized examinations and data from simulators and phantom models to assess proficiency in ultrasound.

From SFM to 3d Print: Automated Workflow Addressed to Practitioner Aimed at the Conservation and Restauration

NASA Astrophysics Data System (ADS)

Inzerillo, L.; Di Paola, F.

2017-08-01

In In the last years there has been an increasing use of digital techniques for conservation and restoration purposes. Among these, a very dominant rule is played by the use of digital photogrammetry packages (Agisoft Photoscan, 3D Zephir) which allow to obtain in few steps 3D textured models of real objects. Combined with digital documentation technologies digital fabrication technologies can be employed in a variety of ways to assist in heritage documentation, conservation and dissemination. This paper will give to practitioners an overview on the state of the art available technologies and a feasible workflow for optimizing point cloud and polygon mesh datasets for the purpose of fabrication using 3D printing. The goal is to give an important contribute to confer an automation aspect at the whole processing. We tried to individuate a workflow that should be applicable to several types of cases apart from small precautions. In our experimentation we used a DELTA WASP 2040 printer with PLA easyfil.

Metavisitor, a Suite of Galaxy Tools for Simple and Rapid Detection and Discovery of Viruses in Deep Sequence Data

PubMed Central

Vernick, Kenneth D.

2017-01-01

Metavisitor is a software package that allows biologists and clinicians without specialized bioinformatics expertise to detect and assemble viral genomes from deep sequence datasets. The package is composed of a set of modular bioinformatic tools and workflows that are implemented in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions. PMID:28045932

Evaluation of Five Chromogenic Agar Media and the Rosco Rapid Carb Screen Kit for Detection and Confirmation of Carbapenemase Production in Gram-Negative Bacilli

PubMed Central

Gilmour, Matthew W.; DeGagne, Pat; Nichol, Kim; Karlowsky, James A.

2014-01-01

An efficient workflow to screen for and confirm the presence of carbapenemase-producing Gram-negative bacilli was developed by evaluating five chromogenic screening agar media and two confirmatory assays, the Rapid Carb screen test (Rosco Diagnostica A/S, Taastrup, Denmark) and the modified Hodge test. A panel of 150 isolates was used, including 49 carbapenemase-producing isolates representing a variety of β-lactamase enzyme classes. An evaluation of analytical performance, assay cost, and turnaround time indicated that the preferred workflow (screening test followed by confirmatory testing) was the chromID Carba agar medium (bioMérieux, Marcy l'Étoile, France), followed by the Rapid Carb screen test, yielding a combined sensitivity of 89.8% and a specificity of 100%. As an optional component of the workflow, a determination of carbapenemase gene class via molecular means could be performed subsequent to confirmatory testing. PMID:25355764

CASAS: A tool for composing automatically and semantically astrophysical services

NASA Astrophysics Data System (ADS)

Louge, T.; Karray, M. H.; Archimède, B.; Knödlseder, J.

2017-07-01

Multiple astronomical datasets are available through internet and the astrophysical Distributed Computing Infrastructure (DCI) called Virtual Observatory (VO). Some scientific workflow technologies exist for retrieving and combining data from those sources. However selection of relevant services, automation of the workflows composition and the lack of user-friendly platforms remain a concern. This paper presents CASAS, a tool for semantic web services composition in astrophysics. This tool proposes automatic composition of astrophysical web services and brings a semantics-based, automatic composition of workflows. It widens the services choice and eases the use of heterogeneous services. Semantic web services composition relies on ontologies for elaborating the services composition; this work is based on Astrophysical Services ONtology (ASON). ASON had its structure mostly inherited from the VO services capacities. Nevertheless, our approach is not limited to the VO and brings VO plus non-VO services together without the need for premade recipes. CASAS is available for use through a simple web interface.

Cyberinfrastructure for End-to-End Environmental Explorations

NASA Astrophysics Data System (ADS)

Merwade, V.; Kumar, S.; Song, C.; Zhao, L.; Govindaraju, R.; Niyogi, D.

2007-12-01

The design and implementation of a cyberinfrastructure for End-to-End Environmental Exploration (C4E4) is presented. The C4E4 framework addresses the need for an integrated data/computation platform for studying broad environmental impacts by combining heterogeneous data resources with state-of-the-art modeling and visualization tools. With Purdue being a TeraGrid Resource Provider, C4E4 builds on top of the Purdue TeraGrid data management system and Grid resources, and integrates them through a service-oriented workflow system. It allows researchers to construct environmental workflows for data discovery, access, transformation, modeling, and visualization. Using the C4E4 framework, we have implemented an end-to-end SWAT simulation and analysis workflow that connects our TeraGrid data and computation resources. It enables researchers to conduct comprehensive studies on the impact of land management practices in the St. Joseph watershed using data from various sources in hydrologic, atmospheric, agricultural, and other related disciplines.

Advances in microscale separations towards nanoproteomics applications

DOE PAGES

Yi, Lian; Piehowski, Paul D.; Shi, Tujin; ...

2017-07-21

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. But, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1 μg total proteins (e.g., cellular heterogeneity in tissue pathologies). We review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, andmore » their contributions towards nanoproteomics applications.« less

Advances in microscale separations towards nanoproteomics applications

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

Yi, Lian; Piehowski, Paul D.; Shi, Tujin

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. But, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1 μg total proteins (e.g., cellular heterogeneity in tissue pathologies). We review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, andmore » their contributions towards nanoproteomics applications.« less

An access control model with high security for distributed workflow and real-time application

NASA Astrophysics Data System (ADS)

Han, Ruo-Fei; Wang, Hou-Xiang

2007-11-01

The traditional mandatory access control policy (MAC) is regarded as a policy with strict regulation and poor flexibility. The security policy of MAC is so compelling that few information systems would adopt it at the cost of facility, except some particular cases with high security requirement as military or government application. However, with the increasing requirement for flexibility, even some access control systems in military application have switched to role-based access control (RBAC) which is well known as flexible. Though RBAC can meet the demands for flexibility but it is weak in dynamic authorization and consequently can not fit well in the workflow management systems. The task-role-based access control (T-RBAC) is then introduced to solve the problem. It combines both the advantages of RBAC and task-based access control (TBAC) which uses task to manage permissions dynamically. To satisfy the requirement of system which is distributed, well defined with workflow process and critically for time accuracy, this paper will analyze the spirit of MAC, introduce it into the improved T&RBAC model which is based on T-RBAC. At last, a conceptual task-role-based access control model with high security for distributed workflow and real-time application (A_T&RBAC) is built, and its performance is simply analyzed.

Review of software tools for design and analysis of large scale MRM proteomic datasets.

PubMed

Colangelo, Christopher M; Chung, Lisa; Bruce, Can; Cheung, Kei-Hoi

2013-06-15

Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

SimPhospho: a software tool enabling confident phosphosite assignment.

PubMed

Suni, Veronika; Suomi, Tomi; Tsubosaka, Tomoya; Imanishi, Susumu Y; Elo, Laura L; Corthals, Garry L

2018-03-27

Mass spectrometry combined with enrichment strategies for phosphorylated peptides has been successfully employed for two decades to identify sites of phosphorylation. However, unambiguous phosphosite assignment is considered challenging. Given that site-specific phosphorylation events function as different molecular switches, validation of phosphorylation sites is of utmost importance. In our earlier study we developed a method based on simulated phosphopeptide spectral libraries, which enables highly sensitive and accurate phosphosite assignments. To promote more widespread use of this method, we here introduce a software implementation with improved usability and performance. We present SimPhospho, a fast and user-friendly tool for accurate simulation of phosphopeptide tandem mass spectra. Simulated phosphopeptide spectral libraries are used to validate and supplement database search results, with a goal to improve reliable phosphoproteome identification and reporting. The presented program can be easily used together with the Trans-Proteomic Pipeline and integrated in a phosphoproteomics data analysis workflow. SimPhospho is available for Windows, Linux and Mac operating systems at https://sourceforge.net/projects/simphospho/. It is open source and implemented in C ++. A user's manual with detailed description of data analysis using SimPhospho as well as test data can be found as supplementary material of this article. Supplementary data are available at https://www.btk.fi/research/ computational-biomedicine/software/.

A first exploration of the venom of the Buthus occitanus scorpion found in southern France

PubMed Central

Martin-Eauclaire, Marie-France; Bosmans, Frank; Céard, Brigitte; Diochot, Sylvie; Bougis, Pierre E.

2014-01-01

Even though Buthus occitanus scorpions are found throughout the Mediterranean region, a lack of distinctive characteristics has hampered their classification into different subspecies. Yet, stings from this particular scorpion family are reported each year to result in pain followed by various toxic symptoms. In order to determine the toxicity origin of the rare French Buthus occitanus Amoreux scorpion, we collected several specimens and studied their venom composition using a nano ultra high performance liquid chromatography and matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (nano UHPLC/MALDI-TOF-MS) automated workflow combined with an enzyme-linked immunosorbent assay (ELISA) approach. Moreover, we compared this dataset to that obtained from highly lethal Androctonus australis and Androctonus mauretanicus scorpions collected in North Africa. As a result, we found that the Buthus occitanus Amoreux venom is toxic to mice, an observation that is most likely caused by venom components that inhibit voltage-gated sodium channel inactivation. Moreover, we identified similarities in venom composition between Buthus occitanus scorpions living in the South of France and other Buthidae collected in Morocco and Algeria. As such, the results of this study should be taken into consideration when treating stings from the Buthus occitanus species living in the South of France. PMID:24418174

A first exploration of the venom of the Buthus occitanus scorpion found in southern France.

PubMed

Martin-Eauclaire, Marie-France; Bosmans, Frank; Céard, Brigitte; Diochot, Sylvie; Bougis, Pierre E

2014-03-01

Even though Buthus occitanus scorpions are found throughout the Mediterranean region, a lack of distinctive characteristics has hampered their classification into different subspecies. Yet, stings from this particular scorpion family are reported each year to result in pain followed by various toxic symptoms. In order to determine the toxicity origin of the rare French B. occitanus Amoreux scorpion, we collected several specimens and studied their venom composition using a nano ultra high performance liquid chromatography and matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (nano UHPLC/MALDI-TOF-MS) automated workflow combined with an enzyme-linked immunosorbent assay (ELISA) approach. Moreover, we compared this dataset to that obtained from highly lethal Androctonus australis and Androctonus mauretanicus scorpions collected in North Africa. As a result, we found that the B. occitanus Amoreux venom is toxic to mice, an observation that is most likely caused by venom components that inhibit voltage-gated sodium channel inactivation. Moreover, we identified similarities in venom composition between B. occitanus scorpions living in the South of France and other Buthidae collected in Morocco and Algeria. As such, the results of this study should be taken into consideration when treating stings from the B. occitanus species living in the South of France. Copyright © 2014 Elsevier Ltd. All rights reserved.

Flexible Early Warning Systems with Workflows and Decision Tables

NASA Astrophysics Data System (ADS)

Riedel, F.; Chaves, F.; Zeiner, H.

2012-04-01

An essential part of early warning systems and systems for crisis management are decision support systems that facilitate communication and collaboration. Often official policies specify how different organizations collaborate and what information is communicated to whom. For early warning systems it is crucial that information is exchanged dynamically in a timely manner and all participants get exactly the information they need to fulfil their role in the crisis management process. Information technology obviously lends itself to automate parts of the process. We have experienced however that in current operational systems the information logistics processes are hard-coded, even though they are subject to change. In addition, systems are tailored to the policies and requirements of a certain organization and changes can require major software refactoring. We seek to develop a system that can be deployed and adapted to multiple organizations with different dynamic runtime policies. A major requirement for such a system is that changes can be applied locally without affecting larger parts of the system. In addition to the flexibility regarding changes in policies and processes, the system needs to be able to evolve; when new information sources become available, it should be possible to integrate and use these in the decision process. In general, this kind of flexibility comes with a significant increase in complexity. This implies that only IT professionals can maintain a system that can be reconfigured and adapted; end-users are unable to utilise the provided flexibility. In the business world similar problems arise and previous work suggested using business process management systems (BPMS) or workflow management systems (WfMS) to guide and automate early warning processes or crisis management plans. However, the usability and flexibility of current WfMS are limited, because current notations and user interfaces are still not suitable for end-users, and workflows are usually only suited for rigid processes. We show how improvements can be achieved by using decision tables and rule-based adaptive workflows. Decision tables have been shown to be an intuitive tool that can be used by domain experts to express rule sets that can be interpreted automatically at runtime. Adaptive workflows use a rule-based approach to increase the flexibility of workflows by providing mechanisms to adapt workflows based on context changes, human intervention and availability of services. The combination of workflows, decision tables and rule-based adaption creates a framework that opens up new possibilities for flexible and adaptable workflows, especially, for use in early warning and crisis management systems.

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

PubMed Central

Brusniak, Mi-Youn; Bodenmiller, Bernd; Campbell, David; Cooke, Kelly; Eddes, James; Garbutt, Andrew; Lau, Hollis; Letarte, Simon; Mueller, Lukas N; Sharma, Vagisha; Vitek, Olga; Zhang, Ning; Aebersold, Ruedi; Watts, Julian D

2008-01-01

Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field. PMID:19087345

Quantification of proteins in urine samples using targeted mass spectrometry methods.

PubMed

Khristenko, Nina; Domon, Bruno

2015-01-01

Numerous clinical proteomics studies are focused on the development of biomarkers to improve either diagnostics for early disease detection or the monitoring of the response to the treatment. Although, a wealth of biomarker candidates are available, their evaluation and validation in a true clinical setup remains challenging. In biomarkers evaluation studies, a panel of proteins of interest are systematically analyzed in a large cohort of samples. However, in spite of the latest progresses in mass spectrometry, the consistent detection of pertinent proteins in high complex biological samples is still a challenging task. Thus, targeted LC-MS/MS methods are better suited for the systematic analysis of biomarkers rather than shotgun approaches. This chapter describes the workflow used to perform targeted quantitative analyses of proteins in urinary samples. The peptides, as surrogates of the protein of interest, are commonly measured using a triple quadrupole mass spectrometers operated in selected reaction monitoring (SRM) mode. More recently, the advances in targeted LC-MS/MS analysis based on parallel reaction monitoring (PRM) performed on a quadrupole-orbitrap instrument have allowed to increase the specificity and selectivity of the measurements.

Proposal for a common nomenclature for fragment ions in mass spectra of lipids

PubMed Central

Hartler, Jürgen; Christiansen, Klaus; Gallego, Sandra F.; Peng, Bing; Ahrends, Robert

2017-01-01

Advances in mass spectrometry-based lipidomics have in recent years prompted efforts to standardize the annotation of the vast number of lipid molecules that can be detected in biological systems. These efforts have focused on cataloguing, naming and drawing chemical structures of intact lipid molecules, but have provided no guidelines for annotation of lipid fragment ions detected using tandem and multi-stage mass spectrometry, albeit these fragment ions are mandatory for structural elucidation and high confidence lipid identification, especially in high throughput lipidomics workflows. Here we propose a nomenclature for the annotation of lipid fragment ions, describe its implementation and present a freely available web application, termed ALEX123 lipid calculator, that can be used to query a comprehensive database featuring curated lipid fragmentation information for more than 430,000 potential lipid molecules from 47 lipid classes covering five lipid categories. We note that the nomenclature is generic, extendable to stable isotope-labeled lipid molecules and applicable to automated annotation of fragment ions detected by most contemporary lipidomics platforms, including LC-MS/MS-based routines. PMID:29161304

Proposal for a common nomenclature for fragment ions in mass spectra of lipids.

PubMed

Pauling, Josch K; Hermansson, Martin; Hartler, Jürgen; Christiansen, Klaus; Gallego, Sandra F; Peng, Bing; Ahrends, Robert; Ejsing, Christer S

2017-01-01

Advances in mass spectrometry-based lipidomics have in recent years prompted efforts to standardize the annotation of the vast number of lipid molecules that can be detected in biological systems. These efforts have focused on cataloguing, naming and drawing chemical structures of intact lipid molecules, but have provided no guidelines for annotation of lipid fragment ions detected using tandem and multi-stage mass spectrometry, albeit these fragment ions are mandatory for structural elucidation and high confidence lipid identification, especially in high throughput lipidomics workflows. Here we propose a nomenclature for the annotation of lipid fragment ions, describe its implementation and present a freely available web application, termed ALEX123 lipid calculator, that can be used to query a comprehensive database featuring curated lipid fragmentation information for more than 430,000 potential lipid molecules from 47 lipid classes covering five lipid categories. We note that the nomenclature is generic, extendable to stable isotope-labeled lipid molecules and applicable to automated annotation of fragment ions detected by most contemporary lipidomics platforms, including LC-MS/MS-based routines.

REVIEW ARTICLE: Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes

NASA Astrophysics Data System (ADS)

Dunn, Warwick B.

2008-03-01

The functional levels of biological cells or organisms can be separated into the genome, transcriptome, proteome and metabolome. Of these the metabolome offers specific advantages to the investigation of the phenotype of biological systems. The investigation of the metabolome (metabolomics) has only recently appeared as a mainstream scientific discipline and is currently developing rapidly for the study of microbial, plant and mammalian metabolomes. The metabolome pipeline or workflow encompasses the processes of sample collection and preparation, collection of analytical data, raw data pre-processing, data analysis and data storage. Of these processes the collection of analytical data will be discussed in this review with specific interest shown in the application of mass spectrometry in the metabolomics pipeline. The current developments in mass spectrometry platforms (GC-MS, LC-MS, DIMS and imaging MS) and applications of specific interest will be highlighted. The current limitations of these platforms and applications will be discussed with areas requiring further development also highlighted. These include the detectable coverage of the metabolome, the identification of metabolites and the process of converting raw data to biological knowledge.

Direct identification of bacteria from positive BacT/ALERT blood culture bottles using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry.

PubMed

Mestas, Javier; Felsenstein, Susanna; Bard, Jennifer Dien

2014-11-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is a fast and robust method for the identification of bacteria. In this study, we evaluate the performance of a laboratory-developed lysis method (LDT) for the rapid identification of bacteria from positive BacT/ALERT blood culture bottles. Of the 168 positive bottles tested, 159 were monomicrobial, the majority of which were Gram-positive organisms (61.0% versus 39.0%). Using a cut-off score of ≥1.7, 80.4% of the organisms were correctly identified to the species level, and the identification rate of Gram-negative organisms (90.3%) was found to be significantly greater than that of Gram-positive organisms (78.4%). The simplicity and cost-effectiveness of the LDT enable it to be fully integrated into the routine workflow of the clinical microbiology laboratory, allowing for rapid identification of Gram-positive and Gram-negative bacteria within an hour of blood culture positivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Secreted autoantibody repertoires in Sjögren's syndrome and systemic lupus erythematosus: A proteomic approach.

PubMed

Al Kindi, Mahmood A; Colella, Alex D; Chataway, Tim K; Jackson, Michael W; Wang, Jing J; Gordon, Tom P

2016-04-01

The structures of epitopes bound by autoantibodies against RNA-protein complexes have been well-defined over several decades, but little is known of the clonality, immunoglobulin (Ig) variable (V) gene usage and mutational status of the autoantibodies themselves at the level of the secreted (serum) proteome. A novel proteomic workflow is presented based on affinity purification of specific Igs from serum, high-resolution two-dimensional gel electrophoresis, and de novo and database-driven sequencing of V-region proteins by mass spectrometry. Analysis of anti-Ro52/Ro60/La proteomes in primary Sjögren's syndrome (SS) and anti-Sm and anti-ribosomal P proteomes in systemic lupus erythematosus (SLE) has revealed that these antibody responses are dominated by restricted sets of public (shared) clonotypes, consistent with common pathways of production across unrelated individuals. The discovery of shared sets of specific V-region peptides can be exploited for diagnostic biomarkers in targeted mass spectrometry platforms and for tracking and removal of pathogenic clones. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of metabolomics datasets with high-performance computing and metabolite atlases

DOE PAGES

Yao, Yushu; Sun, Terence; Wang, Tony; ...

2015-07-20

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged formore » future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.« less

Ms2lda.org: web-based topic modelling for substructure discovery in mass spectrometry.

PubMed

Wandy, Joe; Zhu, Yunfeng; van der Hooft, Justin J J; Daly, Rónán; Barrett, Michael P; Rogers, Simon

2017-09-14

We recently published MS2LDA, a method for the decomposition of sets of molecular fragment data derived from large metabolomics experiments. To make the method more widely available to the community, here we present ms2lda.org, a web application that allows users to upload their data, run MS2LDA analyses and explore the results through interactive visualisations. Ms2lda.org takes tandem mass spectrometry data in many standard formats and allows the user to infer the sets of fragment and neutral loss features that co-occur together (Mass2Motifs). As an alternative workflow, the user can also decompose a dataset onto predefined Mass2Motifs. This is accomplished through the web interface or programmatically from our web service. The website can be found at http://ms2lda.org , while the source code is available at https://github.com/sdrogers/ms2ldaviz under the MIT license. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Quantitation of heat-shock proteins in clinical samples using mass spectrometry.

PubMed

Kaur, Punit; Asea, Alexzander

2011-01-01

Mass spectrometry (MS) is a powerful analytical tool for proteomics research and drug and biomarker discovery. MS enables identification and quantification of known and unknown compounds by revealing their structural and chemical properties. Proper sample preparation for MS-based analysis is a critical step in the proteomics workflow because the quality and reproducibility of sample extraction and preparation for downstream analysis significantly impact the separation and identification capabilities of mass spectrometers. The highly expressed proteins represent potential biomarkers that could aid in diagnosis, therapy, or drug development. Because the proteome is so complex, there is no one standard method for preparing protein samples for MS analysis. Protocols differ depending on the type of sample, source, experiment, and method of analysis. Molecular chaperones play significant roles in almost all biological functions due to their capacity for detecting intracellular denatured/unfolded proteins, initiating refolding or denaturation of such malfolded protein sequences and more recently for their role in the extracellular milieu as chaperokines. In this chapter, we describe the latest techniques for quantitating the expression of molecular chaperones in human clinical samples.

A strategy for identification and structural characterization of compounds from Gardenia jasminoides by integrating macroporous resin column chromatography and liquid chromatography-tandem mass spectrometry combined with ion-mobility spectrometry.

PubMed

Wang, Lu; Liu, Shu; Zhang, Xueju; Xing, Junpeng; Liu, Zhiqiang; Song, Fengrui

2016-06-24

In this paper, an analysis strategy integrating macroporous resin (AB-8) column chromatography and high performance liquid chromatography-electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) combined with ion mobility spectrometry (IMS) was proposed and applied for identification and structural characterization of compounds from the fruits of Gardenia jasminoides. The extracts of G. jasminoides were separated by AB-8 resin column chromatography combined with reversed phase liquid chromatography (C18 column) and detected by electrospray ionization tandem mass spectrometry. Additionally, ion mobility spectrometry (IMS) was employed as a supplementary separation technique to discover previously undetected isomers from the fruits of G. jasminoides. A total of 71 compounds, including iridoids, flavonoids, triterpenes, monoterpenoids, carotenoids and phenolic acids were identified by the characteristic high resolution mass spectrometry and the ESI-MS/MS fragmentations. In conclusion, the IMS-MS technique achieved the separation of isomers in crocin-3 and crocin-4 according to their acquired mobility drift times differing from classical analysis by mass spectrometry. The proposed strategy can be used as a highly sensitive and efficient procedure for identification and separation isomeric components in extracts of herbal medicines. Copyright © 2016 Elsevier B.V. All rights reserved.

On-line characterization of monoclonal antibody variants by liquid chromatography-mass spectrometry operating in a two-dimensional format.

PubMed

Alvarez, Melissa; Tremintin, Guillaume; Wang, Jennifer; Eng, Marian; Kao, Yung-Hsiang; Jeong, Justin; Ling, Victor T; Borisov, Oleg V

2011-12-01

Recombinant monoclonal antibodies (MAbs) have become one of the most rapidly growing classes of biotherapeutics in the treatment of human disease. MAbs are highly heterogeneous proteins, thereby requiring a battery of analytical technologies for their characterization. However, incompatibility between separation and subsequent detection is often encountered. Here we demonstrate the utility of a generic on-line liquid chromatography-mass spectrometry (LC-MS) method operated in a two-dimensional format toward the rapid characterization of MAb charge and size variants. Using a single chromatographic system capable of running two independent gradients, up to six fractions of interest from an ion exchange (IEC) or size exclusion (SEC) separation can be identified by trapping and desalting the fractions onto a series of reversed phase trap cartridges with subsequent on-line analysis by mass spectrometry. Analysis of poorly resolved and low-level peaks in the IEC or SEC profile was facilitated by preconcentrating fractions on the traps using multiple injections. An on-line disulfide reduction step was successfully incorporated into the workflow, allowing more detailed characterization of modified MAbs by providing chain-specific information. The system is fully automated, thereby enabling high-throughput analysis with minimal sample handling. This technology provides rapid data turnaround time, a much needed feature during product characterization and development of multiple biotherapeutic proteins. Copyright © 2011 Elsevier Inc. All rights reserved.

Current controlled vocabularies are insufficient to uniquely map molecular entities to mass spectrometry signal.

PubMed

Smith, Rob; Taylor, Ryan M; Prince, John T

2015-01-01

The comparison of analyte mass spectrometry precursor (MS1) signal is central to many proteomic (and other -omic) workflows. Standard vocabularies for mass spectrometry exist and provide good coverage for most experimental applications yet are insufficient for concise and unambiguous description of data concepts spanning the range of signal provenance from a molecular perspective (e.g. from charged peptides down to fine isotopes). Without a standard unambiguous nomenclature, literature searches, algorithm reproducibility and algorithm evaluation for MS-omics data processing are nearly impossible. We show how terms from current official ontologies are too vague or ambiguous to explicitly map molecular entities to MS signals and we illustrate the inconsistency and ambiguity of current colloquially used terms. We also propose a set of terms for MS1 signal that uniquely, succinctly and intuitively describe data concepts spanning the range of signal provenance from full molecule downs to fine isotopes. We suggest that additional community discussion of these terms should precede any further standardization efforts. We propose a novel nomenclature that spans the range of the required granularity to describe MS data processing from the perspective of the molecular provenance of the MS signal. The proposed nomenclature provides a chain of succinct and unique terms spanning the signal created by a charged molecule down through each of its constituent subsignals. We suggest that additional community discussion of these terms should precede any further standardization efforts.

BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI.

PubMed

Rubel, Oliver; Bowen, Benjamin P

2018-01-01

Mass spectrometry imaging (MSI) is a transformative imaging method that supports the untargeted, quantitative measurement of the chemical composition and spatial heterogeneity of complex samples with broad applications in life sciences, bioenergy, and health. While MSI data can be routinely collected, its broad application is currently limited by the lack of easily accessible analysis methods that can process data of the size, volume, diversity, and complexity generated by MSI experiments. The development and application of cutting-edge analytical methods is a core driver in MSI research for new scientific discoveries, medical diagnostics, and commercial-innovation. However, the lack of means to share, apply, and reproduce analyses hinders the broad application, validation, and use of novel MSI analysis methods. To address this central challenge, we introduce the Berkeley Analysis and Storage Toolkit (BASTet), a novel framework for shareable and reproducible data analysis that supports standardized data and analysis interfaces, integrated data storage, data provenance, workflow management, and a broad set of integrated tools. Based on BASTet, we describe the extension of the OpenMSI mass spectrometry imaging science gateway to enable web-based sharing, reuse, analysis, and visualization of data analyses and derived data products. We demonstrate the application of BASTet and OpenMSI in practice to identify and compare characteristic substructures in the mouse brain based on their chemical composition measured via MSI.

Differential Plasma Glycoproteome of p19 Skin Cancer Mouse Model Using the Corra Label-Free LC-MS Proteomics Platform.

PubMed

Letarte, Simon; Brusniak, Mi-Youn; Campbell, David; Eddes, James; Kemp, Christopher J; Lau, Hollis; Mueller, Lukas; Schmidt, Alexander; Shannon, Paul; Kelly-Spratt, Karen S; Vitek, Olga; Zhang, Hui; Aebersold, Ruedi; Watts, Julian D

2008-12-01

A proof-of-concept demonstration of the use of label-free quantitative glycoproteomics for biomarker discovery workflow is presented here, using a mouse model for skin cancer as an example. Blood plasma was collected from 10 control mice, and 10 mice having a mutation in the p19(ARF) gene, conferring them high propensity to develop skin cancer after carcinogen exposure. We enriched for N-glycosylated plasma proteins, ultimately generating deglycosylated forms of the modified tryptic peptides for liquid chromatography mass spectrometry (LC-MS) analyses. LC-MS runs for each sample were then performed with a view to identifying proteins that were differentially abundant between the two mouse populations. We then used a recently developed computational framework, Corra, to perform peak picking and alignment, and to compute the statistical significance of any observed changes in individual peptide abundances. Once determined, the most discriminating peptide features were then fragmented and identified by tandem mass spectrometry with the use of inclusion lists. We next assessed the identified proteins to see if there were sets of proteins indicative of specific biological processes that correlate with the presence of disease, and specifically cancer, according to their functional annotations. As expected for such sick animals, many of the proteins identified were related to host immune response. However, a significant number of proteins also directly associated with processes linked to cancer development, including proteins related to the cell cycle, localisation, trasport, and cell death. Additional analysis of the same samples in profiling mode, and in triplicate, confirmed that replicate MS analysis of the same plasma sample generated less variation than that observed between plasma samples from different individuals, demonstrating that the reproducibility of the LC-MS platform was sufficient for this application. These results thus show that an LC-MS-based workflow can be a useful tool for the generation of candidate proteins of interest as part of a disease biomarker discovery effort.

Differential Plasma Glycoproteome of p19ARF Skin Cancer Mouse Model Using the Corra Label-Free LC-MS Proteomics Platform

PubMed Central

Letarte, Simon; Brusniak, Mi-Youn; Campbell, David; Eddes, James; Kemp, Christopher J.; Lau, Hollis; Mueller, Lukas; Schmidt, Alexander; Shannon, Paul; Kelly-Spratt, Karen S.; Vitek, Olga; Zhang, Hui; Aebersold, Ruedi; Watts, Julian D.

2010-01-01

A proof-of-concept demonstration of the use of label-free quantitative glycoproteomics for biomarker discovery workflow is presented here, using a mouse model for skin cancer as an example. Blood plasma was collected from 10 control mice, and 10 mice having a mutation in the p19ARF gene, conferring them high propensity to develop skin cancer after carcinogen exposure. We enriched for N-glycosylated plasma proteins, ultimately generating deglycosylated forms of the modified tryptic peptides for liquid chromatography mass spectrometry (LC-MS) analyses. LC-MS runs for each sample were then performed with a view to identifying proteins that were differentially abundant between the two mouse populations. We then used a recently developed computational framework, Corra, to perform peak picking and alignment, and to compute the statistical significance of any observed changes in individual peptide abundances. Once determined, the most discriminating peptide features were then fragmented and identified by tandem mass spectrometry with the use of inclusion lists. We next assessed the identified proteins to see if there were sets of proteins indicative of specific biological processes that correlate with the presence of disease, and specifically cancer, according to their functional annotations. As expected for such sick animals, many of the proteins identified were related to host immune response. However, a significant number of proteins also directly associated with processes linked to cancer development, including proteins related to the cell cycle, localisation, trasport, and cell death. Additional analysis of the same samples in profiling mode, and in triplicate, confirmed that replicate MS analysis of the same plasma sample generated less variation than that observed between plasma samples from different individuals, demonstrating that the reproducibility of the LC-MS platform was sufficient for this application. These results thus show that an LC-MS-based workflow can be a useful tool for the generation of candidate proteins of interest as part of a disease biomarker discovery effort. PMID:20157627

SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.

PubMed

Johnson, Benjamin K; Scholz, Matthew B; Teal, Tracy K; Abramovitch, Robert B

2016-02-04

Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes. In spite of the numerous tools developed for each component of an RNA-seq analysis workflow, easy-to-use bacterially oriented workflow applications to combine multiple tools and automate the process are lacking. With many tools to choose from for each step, the task of identifying a specific tool, adapting the input/output options to the specific use-case, and integrating the tools into a coherent analysis pipeline is not a trivial endeavor, particularly for microbiologists with limited bioinformatics experience. To make bacterial RNA-seq data analysis more accessible, we developed a Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis (SPARTA). SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. SPARTA provides an easy-to-use bacterial RNA-seq transcriptional profiling workflow to identify differentially expressed genes between experimental conditions. This software will enable microbiologists with limited bioinformatics experience to analyze their data and integrate next generation sequencing (NGS) technologies into the classroom. The SPARTA software and tutorial are available at sparta.readthedocs.org.

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

Data Curation: Improving Environmental Health Data Quality.

PubMed

Yang, Lin; Li, Jiao; Hou, Li; Qian, Qing

2015-01-01

With the growing recognition of the influence of climate change on human health, scientists' attention to analyzing the relationship between meteorological factors and adverse health effects. However, the paucity of high quality integrated data is one of the great challenges, especially when scientific studies rely on data-intensive computing. This paper aims to design an appropriate curation process to address this problem. We present a data curation workflow that: (i) follows the guidance of DCC Curation Lifecycle Model; (ii) combines manual curation with automatic curation; (iii) and solves environmental health data curation problem. The workflow was applied to a medical knowledge service system and showed that it was capable of improving work efficiency and data quality.

Isoelectric point-based fractionation by HiRIEF coupled to LC-MS allows for in-depth quantitative analysis of the phosphoproteome.

PubMed

Panizza, Elena; Branca, Rui M M; Oliviusson, Peter; Orre, Lukas M; Lehtiö, Janne

2017-07-03

Protein phosphorylation is involved in the regulation of most eukaryotic cells functions and mass spectrometry-based analysis has made major contributions to our understanding of this regulation. However, low abundance of phosphorylated species presents a major challenge in achieving comprehensive phosphoproteome coverage and robust quantification. In this study, we developed a workflow employing titanium dioxide phospho-enrichment coupled with isobaric labeling by Tandem Mass Tags (TMT) and high-resolution isoelectric focusing (HiRIEF) fractionation to perform in-depth quantitative phosphoproteomics starting with a low sample quantity. To benchmark the workflow, we analyzed HeLa cells upon pervanadate treatment or cell cycle arrest in mitosis. Analyzing 300 µg of peptides per sample, we identified 22,712 phosphorylation sites, of which 19,075 were localized with high confidence and 1,203 are phosphorylated tyrosine residues, representing 6.3% of all detected phospho-sites. HiRIEF fractions with the most acidic isoelectric points are enriched in multiply phosphorylated peptides, which represent 18% of all the phospho-peptides detected in the pH range 2.5-3.7. Cross-referencing with the PhosphoSitePlus database reveals 1,264 phosphorylation sites that have not been previously reported and kinase association analysis suggests that a subset of these may be functional during the mitotic phase.

An integrated workflow for multiplex CSF proteomics and peptidomics-identification of candidate cerebrospinal fluid biomarkers of Alzheimer's disease.

PubMed

Hölttä, Mikko; Minthon, Lennart; Hansson, Oskar; Holmén-Larsson, Jessica; Pike, Ian; Ward, Malcolm; Kuhn, Karsten; Rüetschi, Ulla; Zetterberg, Henrik; Blennow, Kaj; Gobom, Johan

2015-02-06

Many disease processes in the brain are reflected in the protein composition of the cerebrospinal fluid (CSF). In addition to proteins, CSF also contains a large number of endogenous peptides whose potential as disease biomarkers largely remains to be explored. We have developed a novel workflow in which multiplex isobaric labeling is used for simultaneous quantification of endogenous CSF peptides and proteins by liquid chromatography coupled with mass spectrometry. After the labeling of CSF samples, endogenous peptides are separated from proteins by ultrafiltration. The proteins retained on the filters are trypsinized, and the tryptic peptides are collected separately. We evaluated this technique in a comparative pilot study of CSF peptide and protein profiles in eight patients with Alzheimer's disease (AD) and eight nondemented controls. We identified several differences between the AD and control group among endogenous peptides derived from proteins known to be associated with AD, including neurosecretory protein VGF (ratios AD/controls 0.45-0.81), integral membrane protein 2B (ratios AD/controls 0.72-0.84), and metallothionein-3 (ratios AD/controls 0.51-0.61). Analysis of tryptic peptides identified several proteins that were altered in the AD group, some of which have previously been reported as changed in AD, for example, VGF (ratio AD/controls 0.70).

Development of an open source laboratory information management system for 2-D gel electrophoresis-based proteomics workflow

PubMed Central

Morisawa, Hiraku; Hirota, Mikako; Toda, Tosifusa

2006-01-01

Background In the post-genome era, most research scientists working in the field of proteomics are confronted with difficulties in management of large volumes of data, which they are required to keep in formats suitable for subsequent data mining. Therefore, a well-developed open source laboratory information management system (LIMS) should be available for their proteomics research studies. Results We developed an open source LIMS appropriately customized for 2-D gel electrophoresis-based proteomics workflow. The main features of its design are compactness, flexibility and connectivity to public databases. It supports the handling of data imported from mass spectrometry software and 2-D gel image analysis software. The LIMS is equipped with the same input interface for 2-D gel information as a clickable map on public 2DPAGE databases. The LIMS allows researchers to follow their own experimental procedures by reviewing the illustrations of 2-D gel maps and well layouts on the digestion plates and MS sample plates. Conclusion Our new open source LIMS is now available as a basic model for proteome informatics, and is accessible for further improvement. We hope that many research scientists working in the field of proteomics will evaluate our LIMS and suggest ways in which it can be improved. PMID:17018156

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.

Development of a sequential workflow based on LC-PRM for the verification of endometrial cancer protein biomarkers in uterine aspirate samples.

PubMed

Martinez-Garcia, Elena; Lesur, Antoine; Devis, Laura; Campos, Alexandre; Cabrera, Silvia; van Oostrum, Jan; Matias-Guiu, Xavier; Gil-Moreno, Antonio; Reventos, Jaume; Colas, Eva; Domon, Bruno

2016-08-16

About 30% of endometrial cancer (EC) patients are diagnosed at an advanced stage of the disease, which is associated with a drastic decrease in the 5-year survival rate. The identification of biomarkers in uterine aspirate samples, which are collected by a minimally invasive procedure, would improve early diagnosis of EC. We present a sequential workflow to select from a list of potential EC biomarkers, those which are the most promising to enter a validation study. After the elimination of confounding contributions by residual blood proteins, 52 potential biomarkers were analyzed in uterine aspirates from 20 EC patients and 18 non-EC controls by a high-resolution accurate mass spectrometer operated in parallel reaction monitoring mode. The differential abundance of 26 biomarkers was observed, and among them ten proteins showed a high sensitivity and specificity (AUC > 0.9). The study demonstrates that uterine aspirates are valuable samples for EC protein biomarkers screening. It also illustrates the importance of a biomarker verification phase to fill the gap between discovery and validation studies and highlights the benefits of high resolution mass spectrometry for this purpose. The proteins verified in this study have an increased likelihood to become a clinical assay after a subsequent validation phase.

Analysis of Serum Total and Free PSA Using Immunoaffinity Depletion Coupled to SRM: Correlation with Clinical Immunoassay Tests

PubMed Central

Liu, Tao; Hossain, Mahmud; Schepmoes, Athena A.; Fillmore, Thomas L.; Sokoll, Lori J.; Kronewitter, Scott R.; Izmirlian, Grant; Shi, Tujin; Qian, Wei-Jun; Leach, Robin J.; Thompson, Ian M.; Chan, Daniel W.; Smith, Richard D.; Kagan, Jacob; Srivastava, Sudhir; Rodland, Karin D.; Camp, David G.

2012-01-01

Recently, selected reaction monitoring mass spectrometry (SRM-MS) has been more frequently applied to measure low abundance biomarker candidates in tissues and biofluids, owing to its high sensitivity and specificity, simplicity of assay configuration, and exceptional multiplexing capability. In this study, we report for the first time the development of immunoaffinity depletion-based workflows and SRM-MS assays that enable sensitive and accurate quantification of total and free prostate-specific antigen (PSA) in serum without the requirement for specific PSA antibodies. Low ng/mL level detection of both total and free PSA was consistently achieved in both PSA-spiked female serum samples and actual patient serum samples. Moreover, comparison of the results obtained when SRM PSA assays and conventional immunoassays were applied to the same samples showed good correlation in several independent clinical serum sample sets. These results demonstrate that the workflows and SRM assays developed here provide an attractive alternative for reliably measuring candidate biomarkers in human blood, without the need to develop affinity reagents. Furthermore, the simultaneous measurement of multiple biomarkers, including the free and bound forms of PSA, can be performed in a single multiplexed analysis using high-resolution liquid chromatographic separation coupled with SRM-MS. PMID:22846433

Proteogenomics approaches for studying cancer biology and their potential in the identification of acute myeloid leukemia biomarkers.

PubMed

Hernandez-Valladares, Maria; Vaudel, Marc; Selheim, Frode; Berven, Frode; Bruserud, Øystein

2017-08-01

Mass spectrometry (MS)-based proteomics has become an indispensable tool for the characterization of the proteome and its post-translational modifications (PTM). In addition to standard protein sequence databases, proteogenomics strategies search the spectral data against the theoretical spectra obtained from customized protein sequence databases. Up to date, there are no published proteogenomics studies on acute myeloid leukemia (AML) samples. Areas covered: Proteogenomics involves the understanding of genomic and proteomic data. The intersection of both datatypes requires advanced bioinformatics skills. A standard proteogenomics workflow that could be used for the study of AML samples is described. The generation of customized protein sequence databases as well as bioinformatics tools and pipelines commonly used in proteogenomics are discussed in detail. Expert commentary: Drawing on evidence from recent cancer proteogenomics studies and taking into account the public availability of AML genomic data, the interpretation of present and future MS-based AML proteomic data using AML-specific protein sequence databases could discover new biological mechanisms and targets in AML. However, proteogenomics workflows including bioinformatics guidelines can be challenging for the wide AML research community. It is expected that further automation and simplification of the bioinformatics procedures might attract AML investigators to adopt the proteogenomics strategy.

Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome.

PubMed

Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

2018-05-01

Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

An optimized workflow for the integration of biological information into radiotherapy planning: experiences with T1w DCE-MRI

NASA Astrophysics Data System (ADS)

Neff, T.; Kiessling, F.; Brix, G.; Baudendistel, K.; Zechmann, C.; Giesel, F. L.; Bendl, R.

2005-09-01

Planning of radiotherapy is often difficult due to restrictions on morphological images. New imaging techniques enable the integration of biological information into treatment planning and help to improve the detection of vital and aggressive tumour areas. This might improve clinical outcome. However, nowadays morphological data sets are still the gold standard in the planning of radiotherapy. In this paper, we introduce an in-house software platform enabling us to combine images from different imaging modalities yielding biological and morphological information in a workflow driven approach. This is demonstrated for the combination of morphological CT, MRI, functional DCE-MRI and PET data. Data of patients with a tumour of the prostate and with a meningioma were examined with DCE-MRI by applying pharmacokinetic two-compartment models for post-processing. The results were compared with the clinical plans for radiation therapy. Generated parameter maps give additional information about tumour spread, which can be incorporated in the definition of safety margins.

A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Igglessi-Markopoulou, Olga; Kollias, George

2010-05-01

A novel QSAR workflow is constructed that combines MLR with LS-SVM classification techniques for the identification of quinazolinone analogs as "active" or "non-active" CXCR3 antagonists. The accuracy of the LS-SVM classification technique for the training set and test was 100% and 90%, respectively. For the "active" analogs a validated MLR QSAR model estimates accurately their I-IP10 IC(50) inhibition values. The accuracy of the QSAR model (R (2) = 0.80) is illustrated using various evaluation techniques, such as leave-one-out procedure (R(LOO2)) = 0.67) and validation through an external test set (R(pred2) = 0.78). The key conclusion of this study is that the selected molecular descriptors, Highest Occupied Molecular Orbital energy (HOMO), Principal Moment of Inertia along X and Y axes PMIX and PMIZ, Polar Surface Area (PSA), Presence of triple bond (PTrplBnd), and Kier shape descriptor ((1) kappa), demonstrate discriminatory and pharmacophore abilities.

Accelerating materials discovery through the development of polymer databases

NASA Astrophysics Data System (ADS)

Audus, Debra

In our line of business we create chemical solutions for a wide range of applications, such as home and personal care, printing and packaging, automotive and structural coatings, and structural plastics and foams applications. In this environment, stable and highly automated workflows suitable to handle complex systems are a must. By satisfying these prerequisites, efficiency for the development of new materials can be significantly improved by combining modeling and experimental approaches. This is in fact in line with recent Materials Genome Initiative efforts sponsored by the US administration. From our experience, we know, that valuable contributions to product development are possible today by combining existing modeling techniques in an intelligent fashion, provided modeling and experiment work closely together. In my presentation I intend to review approaches to build and parameterize soft matter systems. As an example of our standard workflow, I will show a few applications, which include the design of a stabilizer molecule for dispersing polymer particles and the simulation of polystyrene dispersions.

Laser Ablation-Aerosol Mass Spectrometry-Chemical Ionization Mass Spectrometry for Ambient Surface Imaging

DOE PAGES

Berry, Jennifer L.; Day, Douglas A.; Elseberg, Tim; ...

2018-02-20

Mass spectrometry imaging is becoming an increasingly common analytical technique due to its ability to provide spatially resolved chemical information. In this paper, we report a novel imaging approach combining laser ablation with two mass spectrometric techniques, aerosol mass spectrometry and chemical ionization mass spectrometry, separately and in parallel. Both mass spectrometric methods provide the fast response, rapid data acquisition, low detection limits, and high-resolution peak separation desirable for imaging complex samples. Additionally, the two techniques provide complementary information with aerosol mass spectrometry providing near universal detection of all aerosol molecules and chemical ionization mass spectrometry with a heated inletmore » providing molecular-level detail of both gases and aerosols. The two techniques operate with atmospheric pressure interfaces and require no matrix addition for ionization, allowing for samples to be investigated in their native state under ambient pressure conditions. We demonstrate the ability of laser ablation-aerosol mass spectrometry-chemical ionization mass spectrometry (LA-AMS-CIMS) to create 2D images of both standard compounds and complex mixtures. Finally, the results suggest that LA-AMS-CIMS, particularly when combined with advanced data analysis methods, could have broad applications in mass spectrometry imaging applications.« less

Laser Ablation-Aerosol Mass Spectrometry-Chemical Ionization Mass Spectrometry for Ambient Surface Imaging

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

Berry, Jennifer L.; Day, Douglas A.; Elseberg, Tim

Mass spectrometry imaging is becoming an increasingly common analytical technique due to its ability to provide spatially resolved chemical information. In this paper, we report a novel imaging approach combining laser ablation with two mass spectrometric techniques, aerosol mass spectrometry and chemical ionization mass spectrometry, separately and in parallel. Both mass spectrometric methods provide the fast response, rapid data acquisition, low detection limits, and high-resolution peak separation desirable for imaging complex samples. Additionally, the two techniques provide complementary information with aerosol mass spectrometry providing near universal detection of all aerosol molecules and chemical ionization mass spectrometry with a heated inletmore » providing molecular-level detail of both gases and aerosols. The two techniques operate with atmospheric pressure interfaces and require no matrix addition for ionization, allowing for samples to be investigated in their native state under ambient pressure conditions. We demonstrate the ability of laser ablation-aerosol mass spectrometry-chemical ionization mass spectrometry (LA-AMS-CIMS) to create 2D images of both standard compounds and complex mixtures. Finally, the results suggest that LA-AMS-CIMS, particularly when combined with advanced data analysis methods, could have broad applications in mass spectrometry imaging applications.« less

Flexible workflow sharing and execution services for e-scientists

NASA Astrophysics Data System (ADS)

Kacsuk, Péter; Terstyanszky, Gábor; Kiss, Tamas; Sipos, Gergely

2013-04-01

The sequence of computational and data manipulation steps required to perform a specific scientific analysis is called a workflow. Workflows that orchestrate data and/or compute intensive applications on Distributed Computing Infrastructures (DCIs) recently became standard tools in e-science. At the same time the broad and fragmented landscape of workflows and DCIs slows down the uptake of workflow-based work. The development, sharing, integration and execution of workflows is still a challenge for many scientists. The FP7 "Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs" (SHIWA) project significantly improved the situation, with a simulation platform that connects different workflow systems, different workflow languages, different DCIs and workflows into a single, interoperable unit. The SHIWA Simulation Platform is a service package, already used by various scientific communities, and used as a tool by the recently started ER-flow FP7 project to expand the use of workflows among European scientists. The presentation will introduce the SHIWA Simulation Platform and the services that ER-flow provides based on the platform to space and earth science researchers. The SHIWA Simulation Platform includes: 1. SHIWA Repository: A database where workflows and meta-data about workflows can be stored. The database is a central repository to discover and share workflows within and among communities . 2. SHIWA Portal: A web portal that is integrated with the SHIWA Repository and includes a workflow executor engine that can orchestrate various types of workflows on various grid and cloud platforms. 3. SHIWA Desktop: A desktop environment that provides similar access capabilities than the SHIWA Portal, however it runs on the users' desktops/laptops instead of a portal server. 4. Workflow engines: the ASKALON, Galaxy, GWES, Kepler, LONI Pipeline, MOTEUR, Pegasus, P-GRADE, ProActive, Triana, Taverna and WS-PGRADE workflow engines are already integrated with the execution engine of the SHIWA Portal. Other engines can be added when required. Through the SHIWA Portal one can define and run simulations on the SHIWA Virtual Organisation, an e-infrastructure that gathers computing and data resources from various DCIs, including the European Grid Infrastructure. The Portal via third party workflow engines provides support for the most widely used academic workflow engines and it can be extended with other engines on demand. Such extensions translate between workflow languages and facilitate the nesting of workflows into larger workflows even when those are written in different languages and require different interpreters for execution. Through the workflow repository and the portal lonely scientists and scientific collaborations can share and offer workflows for reuse and execution. Given the integrated nature of the SHIWA Simulation Platform the shared workflows can be executed online, without installing any special client environment and downloading workflows. The FP7 "Building a European Research Community through Interoperable Workflows and Data" (ER-flow) project disseminates the achievements of the SHIWA project and use these achievements to build workflow user communities across Europe. ER-flow provides application supports to research communities within and beyond the project consortium to develop, share and run workflows with the SHIWA Simulation Platform.

Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

PubMed

Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

2011-07-26

Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

Provenance for Runtime Workflow Steering and Validation in Computational Seismology

NASA Astrophysics Data System (ADS)

Spinuso, A.; Krischer, L.; Krause, A.; Filgueira, R.; Magnoni, F.; Muraleedharan, V.; David, M.

2014-12-01

Provenance systems may be offered by modern workflow engines to collect metadata about the data transformations at runtime. If combined with effective visualisation and monitoring interfaces, these provenance recordings can speed up the validation process of an experiment, suggesting interactive or automated interventions with immediate effects on the lifecycle of a workflow run. For instance, in the field of computational seismology, if we consider research applications performing long lasting cross correlation analysis and high resolution simulations, the immediate notification of logical errors and the rapid access to intermediate results, can produce reactions which foster a more efficient progress of the research. These applications are often executed in secured and sophisticated HPC and HTC infrastructures, highlighting the need for a comprehensive framework that facilitates the extraction of fine grained provenance and the development of provenance aware components, leveraging the scalability characteristics of the adopted workflow engines, whose enactment can be mapped to different technologies (MPI, Storm clusters, etc). This work looks at the adoption of W3C-PROV concepts and data model within a user driven processing and validation framework for seismic data, supporting also computational and data management steering. Validation needs to balance automation with user intervention, considering the scientist as part of the archiving process. Therefore, the provenance data is enriched with community-specific metadata vocabularies and control messages, making an experiment reproducible and its description consistent with the community understandings. Moreover, it can contain user defined terms and annotations. The current implementation of the system is supported by the EU-Funded VERCE (http://verce.eu). It provides, as well as the provenance generation mechanisms, a prototypal browser-based user interface and a web API built on top of a NoSQL storage technology, experimenting ways to ensure a rapid and flexible access to the lineage traces. It supports the users with the visualisation of graphical products and offers combined operations to access and download the data which may be selectively stored at runtime, into dedicated data archives.

A Time-Motion Study of ICU Workflow and the Impact of Strain.

PubMed

Hefter, Yosefa; Madahar, Purnema; Eisen, Lewis A; Gong, Michelle N

2016-08-01

Understanding ICU workflow and how it is impacted by ICU strain is necessary for implementing effective improvements. This study aimed to quantify how ICU physicians spend time and to examine the impact of ICU strain on workflow. Prospective, observational time-motion study. Five ICUs in two hospitals at an academic medical center. Thirty attending and resident physicians. None. In 137 hours of field observations, the most time-84 hours (62% of total observation time)-was spent on professional communication. Reviewing patient data and documentation occupied a combined 52 hours (38%), whereas direct patient care and education occupied 24 hours (17%) and 13 hours (9%), respectively. The most frequently used tool was the computer, used in tasks that occupied 51 hours (37%). Severity of illness of the ICU on day of observation was the only strain factor that significantly impacted work patterns. In a linear regression model, increase in average ICU Sequential Organ Failure Assessment was associated with more time spent on direct patient care (β = 4.3; 95% CI, 0.9-7.7) and education (β = 3.2; 95% CI, 0.7-5.8), and less time spent on documentation (β = -7.4; 95% CI, -11.6 to -3.2) and on tasks using the computer (β = -7.8; 95% CI, -14.1 to -1.6). These results were more pronounced with a combined strain score that took into account unit census and Sequential Organ Failure Assessment score. After accounting for ICU type (medical vs surgical) and staffing structure (resident staffed vs physician assistant staffed), results changed minimally. Clinicians spend the bulk of their time in the ICU on professional communication and tasks involving computers. With the strain of high severity of illness and a full unit, clinicians reallocate time from documentation to patient care and education. Further efforts are needed to examine system-related aspects of care to understand the impact of workflow and strain on patient care.

Integrating Visualizations into Modeling NEST Simulations

PubMed Central

Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W.

2015-01-01

Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work. PMID:26733860

Scientist-Centered Workflow Abstractions via Generic Actors, Workflow Templates, and Context-Awareness for Groundwater Modeling and Analysis

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

Chin, George; Sivaramakrishnan, Chandrika; Critchlow, Terence J.

2011-07-04

A drawback of existing scientific workflow systems is the lack of support to domain scientists in designing and executing their own scientific workflows. Many domain scientists avoid developing and using workflows because the basic objects of workflows are too low-level and high-level tools and mechanisms to aid in workflow construction and use are largely unavailable. In our research, we are prototyping higher-level abstractions and tools to better support scientists in their workflow activities. Specifically, we are developing generic actors that provide abstract interfaces to specific functionality, workflow templates that encapsulate workflow and data patterns that can be reused and adaptedmore » by scientists, and context-awareness mechanisms to gather contextual information from the workflow environment on behalf of the scientist. To evaluate these scientist-centered abstractions on real problems, we apply them to construct and execute scientific workflows in the specific domain area of groundwater modeling and analysis.« less

Forensic applications of supercritical fluid chromatography - mass spectrometry.

PubMed

Pauk, Volodymyr; Lemr, Karel

2018-06-01

Achievements of supercritical fluid chromatography with mass spectrometric detection made in the field of forensic science during the last decade are reviewed. The main topics include analysis of traditional drugs of abuse (e.g. cannabis, methamphetamine) as well as new psychoactive substances (synthetic cannabinoids, cathinones and phenethylamines), doping agents (anabolic steroids, stimulants, diuretics, analgesics etc.) and chemical warfare agents. Control of food authenticity, detection of adulteration and identification of toxic substances in food are also pointed out. Main aspects of an analytical workflow, such as sample preparation, separation and detection are discussed. A special attention is paid to the performance characteristics and validation parameters of supercritical fluid chromatography-mass spectrometric methods in comparison with other separation techniques. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular signature of complex regional pain syndrome (CRPS) and its analysis.

PubMed

König, Simone; Schlereth, Tanja; Birklein, Frank

2017-10-01

Complex Regional Pain Syndrome (CRPS) is a rare, but often disabling pain disease. Biomarkers are lacking, but several inflammatory substances have been associated with the pathophysiology. This review outlines the current knowledge with respect to target biomolecules and the analytical tools available to measure them. Areas covered: Targets include cytokines, neuropeptides and resolvins; analysis strategies are thus needed for different classes of substances such as proteins, peptides, lipids and small molecules. Traditional methods like immunoassays are of importance next to state-of-the art high-resolution mass spectrometry techniques and 'omics' approaches. Expert commentary: Future biomarker studies need larger cohorts, which improve subgrouping of patients due to their presumed pathophysiology, and highly standardized workflows from sampling to analysis.

Less label, more free: approaches in label-free quantitative mass spectrometry.

PubMed

Neilson, Karlie A; Ali, Naveid A; Muralidharan, Sridevi; Mirzaei, Mehdi; Mariani, Michael; Assadourian, Gariné; Lee, Albert; van Sluyter, Steven C; Haynes, Paul A

2011-02-01

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values.

PubMed

Ulmer, Candice Z; Ragland, Jared M; Koelmel, Jeremy P; Heckert, Alan; Jones, Christina M; Garrett, Timothy J; Yost, Richard A; Bowden, John A

2017-12-19

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, "Metabolites in Frozen Human Plasma", against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise.

DEWEY: the DICOM-enabled workflow engine system.

PubMed

Erickson, Bradley J; Langer, Steve G; Blezek, Daniel J; Ryan, William J; French, Todd L

2014-06-01

Workflow is a widely used term to describe the sequence of steps to accomplish a task. The use of workflow technology in medicine and medical imaging in particular is limited. In this article, we describe the application of a workflow engine to improve workflow in a radiology department. We implemented a DICOM-enabled workflow engine system in our department. We designed it in a way to allow for scalability, reliability, and flexibility. We implemented several workflows, including one that replaced an existing manual workflow and measured the number of examinations prepared in time without and with the workflow system. The system significantly increased the number of examinations prepared in time for clinical review compared to human effort. It also met the design goals defined at its outset. Workflow engines appear to have value as ways to efficiently assure that complex workflows are completed in a timely fashion.

Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support.

PubMed

Abouelhoda, Mohamed; Issa, Shadi Alaa; Ghanem, Moustafa

2012-05-04

Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts. In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure. Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis.The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org.

Workflow of the Grover algorithm simulation incorporating CUDA and GPGPU

NASA Astrophysics Data System (ADS)

Lu, Xiangwen; Yuan, Jiabin; Zhang, Weiwei

2013-09-01

The Grover quantum search algorithm, one of only a few representative quantum algorithms, can speed up many classical algorithms that use search heuristics. No true quantum computer has yet been developed. For the present, simulation is one effective means of verifying the search algorithm. In this work, we focus on the simulation workflow using a compute unified device architecture (CUDA). Two simulation workflow schemes are proposed. These schemes combine the characteristics of the Grover algorithm and the parallelism of general-purpose computing on graphics processing units (GPGPU). We also analyzed the optimization of memory space and memory access from this perspective. We implemented four programs on CUDA to evaluate the performance of schemes and optimization. Through experimentation, we analyzed the organization of threads suited to Grover algorithm simulations, compared the storage costs of the four programs, and validated the effectiveness of optimization. Experimental results also showed that the distinguished program on CUDA outperformed the serial program of libquantum on a CPU with a speedup of up to 23 times (12 times on average), depending on the scale of the simulation.

KNIME4NGS: a comprehensive toolbox for next generation sequencing analysis.

PubMed

Hastreiter, Maximilian; Jeske, Tim; Hoser, Jonathan; Kluge, Michael; Ahomaa, Kaarin; Friedl, Marie-Sophie; Kopetzky, Sebastian J; Quell, Jan-Dominik; Mewes, H Werner; Küffner, Robert

2017-05-15

Analysis of Next Generation Sequencing (NGS) data requires the processing of large datasets by chaining various tools with complex input and output formats. In order to automate data analysis, we propose to standardize NGS tasks into modular workflows. This simplifies reliable handling and processing of NGS data, and corresponding solutions become substantially more reproducible and easier to maintain. Here, we present a documented, linux-based, toolbox of 42 processing modules that are combined to construct workflows facilitating a variety of tasks such as DNAseq and RNAseq analysis. We also describe important technical extensions. The high throughput executor (HTE) helps to increase the reliability and to reduce manual interventions when processing complex datasets. We also provide a dedicated binary manager that assists users in obtaining the modules' executables and keeping them up to date. As basis for this actively developed toolbox we use the workflow management software KNIME. See http://ibisngs.github.io/knime4ngs for nodes and user manual (GPLv3 license). robert.kueffner@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Preservation of protein fluorescence in embedded human dendritic cells for targeted 3D light and electron microscopy

PubMed Central

HÖHN, K.; FUCHS, J.; FRÖBER, A.; KIRMSE, R.; GLASS, B.; ANDERS‐ÖSSWEIN, M.; WALTHER, P.; KRÄUSSLICH, H.‐G.

2015-01-01

Summary In this study, we present a correlative microscopy workflow to combine detailed 3D fluorescence light microscopy data with ultrastructural information gained by 3D focused ion beam assisted scanning electron microscopy. The workflow is based on an optimized high pressure freezing/freeze substitution protocol that preserves good ultrastructural detail along with retaining the fluorescence signal in the resin embedded specimens. Consequently, cellular structures of interest can readily be identified and imaged by state of the art 3D confocal fluorescence microscopy and are precisely referenced with respect to an imprinted coordinate system on the surface of the resin block. This allows precise guidance of the focused ion beam assisted scanning electron microscopy and limits the volume to be imaged to the structure of interest. This, in turn, minimizes the total acquisition time necessary to conduct the time consuming ultrastructural scanning electron microscope imaging while eliminating the risk to miss parts of the target structure. We illustrate the value of this workflow for targeting virus compartments, which are formed in HIV‐pulsed mature human dendritic cells. PMID:25786567

XML schemas for common bioinformatic data types and their application in workflow systems

PubMed Central

Seibel, Philipp N; Krüger, Jan; Hartmeier, Sven; Schwarzer, Knut; Löwenthal, Kai; Mersch, Henning; Dandekar, Thomas; Giegerich, Robert

2006-01-01

Background Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data – therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. Results Acknowledging the need for common formats, the Helmholtz Open BioInformatics Technology network (HOBIT) identified several basic data types used in bioinformatics and developed appropriate format descriptions, formally defined by XML schemas, and incorporated them in a Java library (BioDOM). These schemas currently cover sequence, sequence alignment, RNA secondary structure and RNA secondary structure alignment formats in a form that is independent of any specific program, thus enabling seamless interoperation of different tools. All XML formats are available at , the BioDOM library can be obtained at . Conclusion The HOBIT XML schemas and the BioDOM library simplify adding XML support to newly created and existing bioinformatic tools, enabling these tools to interoperate seamlessly in workflow scenarios. PMID:17087823

Procedural Modeling for Rapid-Prototyping of Multiple Building Phases

NASA Astrophysics Data System (ADS)

Saldana, M.; Johanson, C.

2013-02-01

RomeLab is a multidisciplinary working group at UCLA that uses the city of Rome as a laboratory for the exploration of research approaches and dissemination practices centered on the intersection of space and time in antiquity. In this paper we present a multiplatform workflow for the rapid-prototyping of historical cityscapes through the use of geographic information systems, procedural modeling, and interactive game development. Our workflow begins by aggregating archaeological data in a GIS database. Next, 3D building models are generated from the ArcMap shapefiles in Esri CityEngine using procedural modeling techniques. A GIS-based terrain model is also adjusted in CityEngine to fit the building elevations. Finally, the terrain and city models are combined in Unity, a game engine which we used to produce web-based interactive environments which are linked to the GIS data using keyhole markup language (KML). The goal of our workflow is to demonstrate that knowledge generated within a first-person virtual world experience can inform the evaluation of data derived from textual and archaeological sources, and vice versa.

Intuitive presentation of clinical forensic data using anonymous and person-specific 3D reference manikins.

PubMed

Urschler, Martin; Höller, Johannes; Bornik, Alexander; Paul, Tobias; Giretzlehner, Michael; Bischof, Horst; Yen, Kathrin; Scheurer, Eva

2014-08-01

The increasing use of CT/MR devices in forensic analysis motivates the need to present forensic findings from different sources in an intuitive reference visualization, with the aim of combining 3D volumetric images along with digital photographs of external findings into a 3D computer graphics model. This model allows a comprehensive presentation of forensic findings in court and enables comparative evaluation studies correlating data sources. The goal of this work was to investigate different methods to generate anonymous and patient-specific 3D models which may be used as reference visualizations. The issue of registering 3D volumetric as well as 2D photographic data to such 3D models is addressed to provide an intuitive context for injury documentation from arbitrary modalities. We present an image processing and visualization work-flow, discuss the major parts of this work-flow, compare the different investigated reference models, and show a number of cases studies that underline the suitability of the proposed work-flow for presenting forensically relevant information in 3D visualizations. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

CLEW: A Cooperative Learning Environment for the Web.

ERIC Educational Resources Information Center

Ribeiro, Marcelo Blois; Noya, Ricardo Choren; Fuks, Hugo

This paper outlines CLEW (collaborative learning environment for the Web). The project combines MUD (Multi-User Dimension), workflow, VRML (Virtual Reality Modeling Language) and educational concepts like constructivism in a learning environment where students actively participate in the learning process. The MUD shapes the environment structure.…

Scrambled eggs: A highly sensitive molecular diagnostic workflow for Fasciola species specific detection from faecal samples.

PubMed

Calvani, Nichola Eliza Davies; Windsor, Peter Andrew; Bush, Russell David; Šlapeta, Jan

2017-09-01

Fasciolosis, due to Fasciola hepatica and Fasciola gigantica, is a re-emerging zoonotic parasitic disease of worldwide importance. Human and animal infections are commonly diagnosed by the traditional sedimentation and faecal egg-counting technique. However, this technique is time-consuming and prone to sensitivity errors when a large number of samples must be processed or if the operator lacks sufficient experience. Additionally, diagnosis can only be made once the 12-week pre-patent period has passed. Recently, a commercially available coprological antigen ELISA has enabled detection of F. hepatica prior to the completion of the pre-patent period, providing earlier diagnosis and increased throughput, although species differentiation is not possible in areas of parasite sympatry. Real-time PCR offers the combined benefits of highly sensitive species differentiation for medium to large sample sizes. However, no molecular diagnostic workflow currently exists for the identification of Fasciola spp. in faecal samples. A new molecular diagnostic workflow for the highly-sensitive detection and quantification of Fasciola spp. in faecal samples was developed. The technique involves sedimenting and pelleting the samples prior to DNA isolation in order to concentrate the eggs, followed by disruption by bead-beating in a benchtop homogeniser to ensure access to DNA. Although both the new molecular workflow and the traditional sedimentation technique were sensitive and specific, the new molecular workflow enabled faster sample throughput in medium to large epidemiological studies, and provided the additional benefit of speciation. Further, good correlation (R2 = 0.74-0.76) was observed between the real-time PCR values and the faecal egg count (FEC) using the new molecular workflow for all herds and sampling periods. Finally, no effect of storage in 70% ethanol was detected on sedimentation and DNA isolation outcomes; enabling transport of samples from endemic to non-endemic countries without the requirement of a complete cold chain. The commercially-available ELISA displayed poorer sensitivity, even after adjustment of the positive threshold (65-88%), compared to the sensitivity (91-100%) of the new molecular diagnostic workflow. Species-specific assays for sensitive detection of Fasciola spp. enable ante-mortem diagnosis in both human and animal settings. This includes Southeast Asia where there are potentially many undocumented human cases and where post-mortem examination of production animals can be difficult. The new molecular workflow provides a sensitive and quantitative diagnostic approach for the rapid testing of medium to large sample sizes, potentially superseding the traditional sedimentation and FEC technique and enabling surveillance programs in locations where animal and human health funding is limited.

A Web Interface for Eco System Modeling

NASA Astrophysics Data System (ADS)

McHenry, K.; Kooper, R.; Serbin, S. P.; LeBauer, D. S.; Desai, A. R.; Dietze, M. C.

2012-12-01

We have developed the Predictive Ecosystem Analyzer (PEcAn) as an open-source scientific workflow system and ecoinformatics toolbox that manages the flow of information in and out of regional-scale terrestrial biosphere models, facilitates heterogeneous data assimilation, tracks data provenance, and enables more effective feedback between models and field research. The over-arching goal of PEcAn is to make otherwise complex analyses transparent, repeatable, and accessible to a diverse array of researchers, allowing both novice and expert users to focus on using the models to examine complex ecosystems rather than having to deal with complex computer system setup and configuration questions in order to run the models. Through the developed web interface we hide much of the data and model details and allow the user to simply select locations, ecosystem models, and desired data sources as inputs to the model. Novice users are guided by the web interface through setting up a model execution and plotting the results. At the same time expert users are given enough freedom to modify specific parameters before the model gets executed. This will become more important as more and more models are added to the PEcAn workflow as well as more and more data that will become available as NEON comes online. On the backend we support the execution of potentially computationally expensive models on different High Performance Computers (HPC) and/or clusters. The system can be configured with a single XML file that gives it the flexibility needed for configuring and running the different models on different systems using a combination of information stored in a database as well as pointers to files on the hard disk. While the web interface usually creates this configuration file, expert users can still directly edit it to fine tune the configuration.. Once a workflow is finished the web interface will allow for the easy creation of plots over result data while also allowing the user to download the results for further processing. The current workflow in the web interface is a simple linear workflow, but will be expanded to allow for more complex workflows. We are working with Kepler and Cyberintegrator to allow for these more complex workflows as well as collecting provenance of the workflow being executed. This provenance regarding model executions is stored in a database along with the derived results. All of this information is then accessible using the BETY database web frontend. The PEcAn interface.

Inferring Clinical Workflow Efficiency via Electronic Medical Record Utilization

PubMed Central

Chen, You; Xie, Wei; Gunter, Carl A; Liebovitz, David; Mehrotra, Sanjay; Zhang, He; Malin, Bradley

2015-01-01

Complexity in clinical workflows can lead to inefficiency in making diagnoses, ineffectiveness of treatment plans and uninformed management of healthcare organizations (HCOs). Traditional strategies to manage workflow complexity are based on measuring the gaps between workflows defined by HCO administrators and the actual processes followed by staff in the clinic. However, existing methods tend to neglect the influences of EMR systems on the utilization of workflows, which could be leveraged to optimize workflows facilitated through the EMR. In this paper, we introduce a framework to infer clinical workflows through the utilization of an EMR and show how such workflows roughly partition into four types according to their efficiency. Our framework infers workflows at several levels of granularity through data mining technologies. We study four months of EMR event logs from a large medical center, including 16,569 inpatient stays, and illustrate that over approximately 95% of workflows are efficient and that 80% of patients are on such workflows. At the same time, we show that the remaining 5% of workflows may be inefficient due to a variety of factors, such as complex patients. PMID:26958173

Cryogenic IR spectroscopy combined with ion mobility spectrometry for the analysis of human milk oligosaccharides.

PubMed

Khanal, Neelam; Masellis, Chiara; Kamrath, Michael Z; Clemmer, David E; Rizzo, Thomas R

2018-04-16

We report here our combination of cryogenic, messenger-tagging, infrared (IR) spectroscopy with ion mobility spectrometry (IMS) and mass spectrometry (MS) as a way to identify and analyze a set of human milk oligosaccharides (HMOs) ranging from trisaccharides to hexasaccharides. The added dimension of IR spectroscopy provides a diagnostic fingerprint in the OH and NH stretching region, which is crucial to identify these oligosaccharides, which are difficult to distinguish by IMS alone. These results extend our previous work in demonstrating the generality of this combined approach for distinguishing subtly different structural and regioisomers of glycans of biologically relevant size.

Workflow management systems in radiology

NASA Astrophysics Data System (ADS)

Wendler, Thomas; Meetz, Kirsten; Schmidt, Joachim

1998-07-01

In a situation of shrinking health care budgets, increasing cost pressure and growing demands to increase the efficiency and the quality of medical services, health care enterprises are forced to optimize or complete re-design their processes. Although information technology is agreed to potentially contribute to cost reduction and efficiency improvement, the real success factors are the re-definition and automation of processes: Business Process Re-engineering and Workflow Management. In this paper we discuss architectures for the use of workflow management systems in radiology. We propose to move forward from information systems in radiology (RIS, PACS) to Radiology Management Systems, in which workflow functionality (process definitions and process automation) is implemented through autonomous workflow management systems (WfMS). In a workflow oriented architecture, an autonomous workflow enactment service communicates with workflow client applications via standardized interfaces. In this paper, we discuss the need for and the benefits of such an approach. The separation of workflow management system and application systems is emphasized, and the consequences that arise for the architecture of workflow oriented information systems. This includes an appropriate workflow terminology, and the definition of standard interfaces for workflow aware application systems. Workflow studies in various institutions have shown that most of the processes in radiology are well structured and suited for a workflow management approach. Numerous commercially available Workflow Management Systems (WfMS) were investigated, and some of them, which are process- oriented and application independent, appear suitable for use in radiology.

Size, weight and position: ion mobility spectrometry and imaging MS combined.

PubMed

Kiss, András; Heeren, Ron M A

2011-03-01

Size, weight and position are three of the most important parameters that describe a molecule in a biological system. Ion mobility spectrometry is capable of separating molecules on the basis of their size or shape, whereas imaging mass spectrometry is an effective tool to measure the molecular weight and spatial distribution of molecules. Recent developments in both fields enabled the combination of the two technologies. As a result, ion-mobility-based imaging mass spectrometry is gaining more and more popularity as a (bio-)analytical tool enabling the determination of the size, weight and position of several molecules simultaneously on biological surfaces. This paper reviews the evolution of ion-mobility-based imaging mass spectrometry and provides examples of its application in analytical studies of biological surfaces.

Data Provenance Hybridization Supporting Extreme-Scale Scientific WorkflowApplications

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

Elsethagen, Todd O.; Stephan, Eric G.; Raju, Bibi

As high performance computing (HPC) infrastructures continue to grow in capability and complexity, so do the applications that they serve. HPC and distributed-area computing (DAC) (e.g. grid and cloud) users are looking increasingly toward workflow solutions to orchestrate their complex application coupling, pre- and post-processing needs To gain insight and a more quantitative understanding of a workflow’s performance our method includes not only the capture of traditional provenance information, but also the capture and integration of system environment metrics helping to give context and explanation for a workflow’s execution. In this paper, we describe IPPD’s provenance management solution (ProvEn) andmore » its hybrid data store combining both of these data provenance perspectives.« less

Guidelines for reporting quantitative mass spectrometry based experiments in proteomics.

PubMed

Martínez-Bartolomé, Salvador; Deutsch, Eric W; Binz, Pierre-Alain; Jones, Andrew R; Eisenacher, Martin; Mayer, Gerhard; Campos, Alex; Canals, Francesc; Bech-Serra, Joan-Josep; Carrascal, Montserrat; Gay, Marina; Paradela, Alberto; Navajas, Rosana; Marcilla, Miguel; Hernáez, María Luisa; Gutiérrez-Blázquez, María Dolores; Velarde, Luis Felipe Clemente; Aloria, Kerman; Beaskoetxea, Jabier; Medina-Aunon, J Alberto; Albar, Juan P

2013-12-16

Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML [1]. The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and Quality Control. Copyright © 2013 Elsevier B.V. All rights reserved.

Bioinformatics workflows and web services in systems biology made easy for experimentalists.

PubMed

Jimenez, Rafael C; Corpas, Manuel

2013-01-01

Workflows are useful to perform data analysis and integration in systems biology. Workflow management systems can help users create workflows without any previous knowledge in programming and web services. However the computational skills required to build such workflows are usually above the level most biological experimentalists are comfortable with. In this chapter we introduce workflow management systems that reuse existing workflows instead of creating them, making it easier for experimentalists to perform computational tasks.

PyQuant: A Versatile Framework for Analysis of Quantitative Mass Spectrometry Data.

PubMed

Mitchell, Christopher J; Kim, Min-Sik; Na, Chan Hyun; Pandey, Akhilesh

2016-08-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, (15)N, (13)C, or (18)O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25-45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Methods and apparatuses for preparing a surface to have catalytic activity

DOEpatents

Cooks, Robert G [West Lafayette, IN; Peng, Wen-Ping [West Lafayette, IN; Ouyang, Zheng [West Lafayette, IN; Goodwin, Michael P [West Lafayette, IN

2011-03-22

The invention provides methods and apparatuses that utilize mass spectrometry for preparation of a surface to have catalytic activity through molecular soft-landing of mass selected ions. Mass spectrometry is used to generate combinations of atoms in a particular geometrical arrangement, and ion soft-landing selects this molecular entity or combination of entities and gently deposits the entity or combination intact onto a surface.

Tavaxy: Integrating Taverna and Galaxy workflows with cloud computing support

PubMed Central

2012-01-01

Background Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts. Results In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure. Conclusions Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis. The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org. PMID:22559942

Determination of novel brominated flame retardants and polybrominated diphenyl ethers in serum using gas chromatography-mass spectrometry with two simplified sample preparation procedures.

PubMed

Gao, Le; Li, Jian; Wu, Yandan; Yu, Miaohao; Chen, Tian; Shi, Zhixiong; Zhou, Xianqing; Sun, Zhiwei

2016-11-01

Two simple and efficient pretreatment procedures have been developed for the simultaneous extraction and cleanup of six novel brominated flame retardants (NBFRs) and eight common polybrominated diphenyl ethers (PBDEs) in human serum. The first sample pretreatment procedure was a quick, easy, cheap, effective, rugged, and safe (QuEChERS)-based approach. An acetone/hexane mixture was employed to isolate the lipid and analytes from the serum with a combination of MgSO 4 and NaCl, followed by a dispersive solid-phase extraction (d-SPE) step using C18 particles as a sorbent. The second sample pretreatment procedure was based on solid-phase extraction. The sample extraction and cleanup were conducted directly on an Oasis HLB SPE column using 5 % aqueous isopropanol, concentrated sulfuric acid, and 10 % aqueous methanol, followed by elution with dichloromethane. The NBFRs and PBDEs were then detected using gas chromatography-negative chemical ionization mass spectrometry (GC-NCI MS). The methods were assessed for repeatability, accuracy, selectivity, limits of detection (LODs), and linearity. The results of spike recovery experiments in fetal bovine serum showed that average recoveries ranged from 77.9 % to 128.8 % with relative standard deviations (RSDs) from 0.73 % to 12.37 % for most of the analytes. The LODs for the analytes in fetal bovine serum ranged from 0.3 to 50.8 pg/mL except for decabromodiphenyl ethane. The proposed method was successfully applied to the determination of the 14 brominated flame retardants in human serum. The two pretreatment procedures described here are simple, accurate, and precise, and are suitable for the routine analysis of human serum. Graphical Abstract Workflow of a QuEChERS-based approach (top) and an SPE-based approach (bottom) for the detection of PBDEs and NBFRs in serum.

Kwf-Grid workflow management system for Earth science applications

NASA Astrophysics Data System (ADS)

Tran, V.; Hluchy, L.

2009-04-01

In this paper, we present workflow management tool for Earth science applications in EGEE. The workflow management tool was originally developed within K-wf Grid project for GT4 middleware and has many advanced features like semi-automatic workflow composition, user-friendly GUI for managing workflows, knowledge management. In EGEE, we are porting the workflow management tool to gLite middleware for Earth science applications K-wf Grid workflow management system was developed within "Knowledge-based Workflow System for Grid Applications" under the 6th Framework Programme. The workflow mangement system intended to - semi-automatically compose a workflow of Grid services, - execute the composed workflow application in a Grid computing environment, - monitor the performance of the Grid infrastructure and the Grid applications, - analyze the resulting monitoring information, - capture the knowledge that is contained in the information by means of intelligent agents, - and finally to reuse the joined knowledge gathered from all participating users in a collaborative way in order to efficiently construct workflows for new Grid applications. Kwf Grid workflow engines can support different types of jobs (e.g. GRAM job, web services) in a workflow. New class of gLite job has been added to the system, allows system to manage and execute gLite jobs in EGEE infrastructure. The GUI has been adapted to the requirements of EGEE users, new credential management servlet is added to portal. Porting K-wf Grid workflow management system to gLite would allow EGEE users to use the system and benefit from its avanced features. The system is primarly tested and evaluated with applications from ES clusters.

The challenge of on-tissue digestion for MALDI MSI- a comparison of different protocols to improve imaging experiments.

PubMed

Diehl, Hanna C; Beine, Birte; Elm, Julian; Trede, Dennis; Ahrens, Maike; Eisenacher, Martin; Marcus, Katrin; Meyer, Helmut E; Henkel, Corinna

2015-03-01

Mass spectrometry imaging (MSI) has become a powerful and successful tool in the context of biomarker detection especially in recent years. This emerging technique is based on the combination of histological information of a tissue and its corresponding spatial resolved mass spectrometric information. The identification of differentially expressed protein peaks between samples is still the method's bottleneck. Therefore, peptide MSI compared to protein MSI is closer to the final goal of identification since peptides are easier to measure than proteins. Nevertheless, the processing of peptide imaging samples is challenging due to experimental complexity. To address this issue, a method development study for peptide MSI using cryoconserved and formalin-fixed paraffin-embedded (FFPE) rat brain tissue is provided. Different digestion times, matrices, and proteases were tested to define an optimal workflow for peptide MSI. All practical experiments were done in triplicates and analyzed by the SCiLS Lab software, using structures derived from myelin basic protein (MBP) peaks, principal component analysis (PCA) and probabilistic latent semantic analysis (pLSA) to rate the experiments' quality. Blinded experimental evaluation in case of defining countable structures in the datasets was performed by three individuals. Such an extensive method development for peptide matrix-assisted laser desorption/ionization (MALDI) imaging experiments has not been performed so far, and the resulting problems and consequences were analyzed and discussed.

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio *

PubMed Central

Sarpe, Vladimir; Rafiei, Atefeh; Hepburn, Morgan; Ostan, Nicholas; Schryvers, Anthony B.; Schriemer, David C.

2016-01-01

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae. Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca. PMID:27412762

Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer

NASA Astrophysics Data System (ADS)

Huan, Tao; Troyer, Dean A.; Li, Liang

2016-08-01

We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy.

Quantitative analysis of glycerophospholipids by LC-MS: acquisition, data handling, and interpretation

PubMed Central

Myers, David S.; Ivanova, Pavlina T.; Milne, Stephen B.; Brown, H. Alex

2012-01-01

As technology expands what it is possible to accurately measure, so too the challenges faced by modern mass spectrometry applications expand. A high level of accuracy in lipid quantitation across thousands of chemical species simultaneously is demanded. While relative changes in lipid amounts with varying conditions may provide initial insights or point to novel targets, there are many questions that require determination of lipid analyte absolute quantitation. Glycerophospholipids present a significant challenge in this regard, given the headgroup diversity, large number of possible acyl chain combinations, and vast range of ionization efficiency of species. Lipidomic output is being used more often not just for profiling of the masses of species, but also for highly-targeted flux-based measurements which put additional burdens on the quantitation pipeline. These first two challenges bring into sharp focus the need for a robust lipidomics workflow including deisotoping, differentiation from background noise, use of multiple internal standards per lipid class, and the use of a scriptable environment in order to create maximum user flexibility and maintain metadata on the parameters of the data analysis as it occurs. As lipidomics technology develops and delivers more output on a larger number of analytes, so must the sophistication of statistical post-processing also continue to advance. High-dimensional data analysis methods involving clustering, lipid pathway analysis, and false discovery rate limitation are becoming standard practices in a maturing field. PMID:21683157

High Sensitivity Crosslink Detection Coupled With Integrative Structure Modeling in the Mass Spec Studio.

PubMed

Sarpe, Vladimir; Rafiei, Atefeh; Hepburn, Morgan; Ostan, Nicholas; Schryvers, Anthony B; Schriemer, David C

2016-09-01

The Mass Spec Studio package was designed to support the extraction of hydrogen-deuterium exchange and covalent labeling data for a range of mass spectrometry (MS)-based workflows, to integrate with restraint-driven protein modeling activities. In this report, we present an extension of the underlying Studio framework and provide a plug-in for crosslink (XL) detection. To accommodate flexibility in XL methods and applications, while maintaining efficient data processing, the plug-in employs a peptide library reduction strategy via a presearch of the tandem-MS data. We demonstrate that prescoring linear unmodified peptide tags using a probabilistic approach substantially reduces search space by requiring both crosslinked peptides to generate sparse data attributable to their linear forms. The method demonstrates highly sensitive crosslink peptide identification with a low false positive rate. Integration with a Haddock plug-in provides a resource that can combine multiple sources of data for protein modeling activities. We generated a structural model of porcine transferrin bound to TbpB, a membrane-bound receptor essential for iron acquisition in Actinobacillus pleuropneumoniae Using mutational data and crosslinking restraints, we confirm the mechanism by which TbpB recognizes the iron-loaded form of transferrin, and note the requirement for disparate sources of restraint data for accurate model construction. The software plugin is freely available at www.msstudio.ca. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Wavelet-Based Peak Detection and a New Charge Inference Procedure for MS/MS Implemented in ProteoWizard’s msConvert

PubMed Central

2015-01-01

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1–100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets. PMID:25411686

Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert.

PubMed

French, William R; Zimmerman, Lisa J; Schilling, Birgit; Gibson, Bradford W; Miller, Christine A; Townsend, R Reid; Sherrod, Stacy D; Goodwin, Cody R; McLean, John A; Tabb, David L

2015-02-06

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1-100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets.

Annotation: a computational solution for streamlining metabolomics analysis

PubMed Central

Domingo-Almenara, Xavier; Montenegro-Burke, J. Rafael; Benton, H. Paul; Siuzdak, Gary

2017-01-01

Metabolite identification is still considered an imposing bottleneck in liquid chromatography mass spectrometry (LC/MS) untargeted metabolomics. The identification workflow usually begins with detecting relevant LC/MS peaks via peak-picking algorithms and retrieving putative identities based on accurate mass searching. However, accurate mass search alone provides poor evidence for metabolite identification. For this reason, computational annotation is used to reveal the underlying metabolites monoisotopic masses, improving putative identification in addition to confirmation with tandem mass spectrometry. This review examines LC/MS data from a computational and analytical perspective, focusing on the occurrence of neutral losses and in-source fragments, to understand the challenges in computational annotation methodologies. Herein, we examine the state-of-the-art strategies for computational annotation including: (i) peak grouping or full scan (MS1) pseudo-spectra extraction, i.e., clustering all mass spectral signals stemming from each metabolite; (ii) annotation using ion adduction and mass distance among ion peaks; (iii) incorporation of biological knowledge such as biotransformations or pathways; (iv) tandem MS data; and (v) metabolite retention time calibration, usually achieved by prediction from molecular descriptors. Advantages and pitfalls of each of these strategies are discussed, as well as expected future trends in computational annotation. PMID:29039932

Direct identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) from positive blood culture bottles: An opportunity to customize growth conditions for fastidious organisms causing bloodstream infections.

PubMed

Sharma, Megha; Gautam, Vikas; Mahajan, Monika; Rana, Sudesh; Majumdar, Manasi; Ray, Pallab

2017-10-01

Culture-negative bacteraemia has been an enigmatic entity with respect to its aetiological agents. In an attempt to actively identify those positive blood cultures that escape isolation and detection on routine workflow, an additional step of MALDI-TOF MS (matrix-assisted laser desorption ionization-time of flight mass spectrometry) based detection was carried out directly from the flagged blood culture bottles. Blood samples from 200 blood culture bottles that beeped positive with automated (BACTEC) system and showed no growth of organism on routine culture media, were subjected to analysis by MALDI-TOF MS. Forty seven of the 200 (23.5%) bacterial aetiology could be established by bottle-based method. Based on these results, growth on culture medium could be achieved for the isolates by providing special growth conditions to the fastidious organisms. Direct identification by MALDI-TOF MS from BACTEC-positive bottles provided an opportunity to isolate those fastidious organisms that failed to grow on routine culture medium by providing them with necessary alterations in growth environment.

Xylose Migration During Tandem Mass Spectrometry of N-Linked Glycans

NASA Astrophysics Data System (ADS)

Hecht, Elizabeth S.; Loziuk, Philip L.; Muddiman, David C.

2017-04-01

Understanding the rearrangement of gas-phase ions via tandem mass spectrometry is critical to improving manual and automated interpretation of complex datasets. N-glycan analysis may be carried out under collision induced (CID) or higher energy collision dissociation (HCD), which favors cleavage at the glycosidic bond. However, fucose migration has been observed in tandem MS, leading to the formation of new bonds over four saccharide units away. In the following work, we report the second instance of saccharide migration ever to occur for N-glycans. Using horseradish peroxidase as a standard, the beta-1,2 xylose was observed to migrate from a hexose to a glucosamine residue on the (Xyl)Man3GlcNac2 glycan. This investigation was followed up in a complex N-linked glycan mixture derived from stem differentiating xylem tissue, and the rearranged product ion was observed for 75% of the glycans. Rearrangement was not favored in isomeric glycans with a core or antennae fucose and unobserved in glycans predicted to have a permanent core-fucose modification. As the first empirical observation of this rearrangement, this work warrants dissemination so it may be searched in de novo sequencing glycan workflows.

The VERCE platform: Enabling Computational Seismology via Streaming Workflows and Science Gateways

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Filgueira, Rosa; Krause, Amrey; Matser, Jonas; Casarotti, Emanuele; Magnoni, Federica; Gemund, Andre; Frobert, Laurent; Krischer, Lion; Atkinson, Malcolm

2015-04-01

The VERCE project is creating an e-Science platform to facilitate innovative data analysis and coding methods that fully exploit the wealth of data in global seismology. One of the technologies developed within the project is the Dispel4Py python library, which allows to describe abstract stream-based workflows for data-intensive applications and to execute them in a distributed environment. At runtime Dispel4Py is able to map workflow descriptions dynamically onto a number of computational resources (Apache Storm clusters, MPI powered clusters, and shared-memory multi-core machines, single-core machines), setting it apart from other workflow frameworks. Therefore, Dispel4Py enables scientists to focus on their computation instead of being distracted by details of the computing infrastructure they use. Among the workflows developed with Dispel4Py in VERCE, we mention here those for Seismic Ambient Noise Cross-Correlation and MISFIT calculation, which address two data-intensive problems that are common in computational seismology. The former, also called Passive Imaging, allows the detection of relative seismic-wave velocity variations during the time of recording, to be associated with the stress-field changes that occurred in the test area. The MISFIT instead, takes as input the synthetic seismograms generated from HPC simulations for a certain Earth model and earthquake and, after a preprocessing stage, compares them with real observations in order to foster subsequent model updates and improvement (Inversion). The VERCE Science Gateway exposes the MISFIT calculation workflow as a service, in combination with the simulation phase. Both phases can be configured, controlled and monitored by the user via a rich user interface which is integrated within the gUSE Science Gateway framework, hiding the complexity of accessing third parties data services, security mechanisms and enactment on the target resources. Thanks to a modular extension to the Dispel4Py framework, the system collects provenance data adopting the W3C-PROV data model. Provenance recordings can be explored and analysed at run time for rapid diagnostic and workflow steering, or later for further validation and comparisons across runs. We will illustrate the interactive services of the gateway and the capabilities of the produced metadata, coupled with the VERCE data management layer based on iRODS. The Cross-Correlation workflow was evaluated on SuperMUC, a supercomputing cluster at the Leibniz Supercomputing Centre in Munich, with 155,656 processor cores in 9400 compute nodes. SuperMUC is based on the Intel Xeon architecture consisting of 18 Thin Node Islands and one Fat Node Island. This work has only had access to the Thin Node Islands, which contain Sandy Bridge nodes, each having 16 cores and 32 GB of memory. In the evaluations we used 1000 stations, and we applied two types of methods (whiten and non-whiten) for pre-processing the data. The workflow was tested on a varying number of cores (16, 32, 64, 128, and 256 cores) using the MPI mapping of Dispel4Py. The results show that Dispel4Py is able to improve the performance by increasing the number of cores without changing the description of the workflow.

Profiling and characterization of sialylated N-glycans by 2D-HPLC (HIAX/PGC) with online orbitrap MS/MS and offline MSn.

PubMed

Hanneman, Andrew J S; Strand, James; Huang, Chi-Ting

2014-02-01

Glycosylation is a critical parameter used to evaluate protein quality and consistency. N-linked glycan profiling is fundamental to the support of biotherapeutic protein manufacturing from early stage process development through drug product commercialization. Sialylated glycans impact the serum half-life of receptor-Fc fusion proteins (RFPs), making their quality and consistency a concern during the production of fusion proteins. Here, we describe an analytical approach providing both quantitative profiling and in-depth mass spectrometry (MS)-based structural characterization of sialylated RFP N-glycans. Aiming to efficiently link routine comparability studies with detailed structural characterization, an integrated workflow was implemented employing fluorescence detection, online positive and negative ion tandem mass spectrometry (MS/MS), and offline static nanospray ionization-sequential mass spectrometry (NSI-MS(n)). For routine use, high-performance liquid chromatography profiling employs established fluorescence detection of 2-aminobenzoic acid derivatives (2AA) and hydrophilic interaction anion-exchange chromatography (HIAX) charge class separation. Further characterization of HIAX peak fractions is achieved by online (-) ion orbitrap MS/MS, offering the advantages of high mass accuracy and data-dependent MS/MS. As required, additional characterization uses porous graphitized carbon in the second chromatographic dimension to provide orthogonal (+) ion MS/MS spectra and buffer-free liquid chromatography peak eluants that are optimum for offline (+)/(-) NSI-MS(n) investigations to characterize low-abundance species and specific moieties including O-acetylation and sulfation. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Online Hydrogen-Deuterium Exchange Traveling Wave Ion Mobility Mass Spectrometry (HDX-IM-MS): a Systematic Evaluation

NASA Astrophysics Data System (ADS)

Cryar, Adam; Groves, Kate; Quaglia, Milena

2017-06-01

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is an important tool for measuring and monitoring protein structure. A bottom-up approach to HDX-MS provides peptide level deuterium uptake values and a more refined localization of deuterium incorporation compared with global HDX-MS measurements. The degree of localization provided by HDX-MS is proportional to the number of peptides that can be identified and monitored across an exchange experiment. Ion mobility spectrometry (IMS) has been shown to improve MS-based peptide analysis of biological samples through increased separation capacity. The integration of IMS within HDX-MS workflows has been commercialized but presently its adoption has not been widespread. The potential benefits of IMS, therefore, have not yet been fully explored. We herein describe a comprehensive evaluation of traveling wave ion mobility integrated within an online-HDX-MS system and present the first reported example of UDMSE acquisition for HDX analysis. Instrument settings required for optimal peptide identifications are described and the effects of detector saturation due to peak compression are discussed. A model system is utilized to confirm the comparability of HDX-IM-MS and HDX-MS uptake values prior to an evaluation of the benefits of IMS at increasing sample complexity. Interestingly, MS and IM-MS acquisitions were found to identify distinct populations of peptides that were unique to the respective methods, a property that can be utilized to increase the spatial resolution of HDX-MS experiments by >60%. [Figure not available: see fulltext.

Beyond the ridge pattern: multi-informative analysis of latent fingermarks by MALDI mass spectrometry.

PubMed

Francese, S; Bradshaw, R; Ferguson, L S; Wolstenholme, R; Clench, M R; Bleay, S

2013-08-07

After over a century, fingerprints are still one of the most powerful means of biometric identification. The conventional forensic workflow for suspect identification consists of (i) recovering latent marks from crime scenes using the appropriate enhancement technique and (ii) obtaining an image of the mark to compare either against known suspect prints and/or to search in a Fingerprint Database. The suspect is identified through matching the ridge pattern and local characteristics of the ridge pattern (minutiae). However successful, there are a number of scenarios in which this process may fail; they include the recovery of partial, distorted or smudged marks, poor quality of the image resulting from inadequacy of the enhancement technique applied, extensive scarring/abrasion of the fingertips or absence of suspect's fingerprint records in the database. In all of these instances it would be very desirable to have a technology able to provide additional information from a fingermark exploiting its endogenous and exogenous chemical content. This opportunity could potentially provide new investigative leads, especially when the fingermark comparison and match process fails. We have demonstrated that Matrix Assisted Laser Desorption Ionisation Mass Spectrometry and Mass Spectrometry Imaging (MALDI MSI) can provide multiple images of the same fingermark in one analysis simultaneous with additional intelligence. Here, a review on the pioneering use and development of MALDI MSI for the analysis of latent fingermarks is presented along with the latest achievements on the forensic intelligence retrievable.

Current controlled vocabularies are insufficient to uniquely map molecular entities to mass spectrometry signal

PubMed Central

2015-01-01

Background The comparison of analyte mass spectrometry precursor (MS1) signal is central to many proteomic (and other -omic) workflows. Standard vocabularies for mass spectrometry exist and provide good coverage for most experimental applications yet are insufficient for concise and unambiguous description of data concepts spanning the range of signal provenance from a molecular perspective (e.g. from charged peptides down to fine isotopes). Without a standard unambiguous nomenclature, literature searches, algorithm reproducibility and algorithm evaluation for MS-omics data processing are nearly impossible. Results We show how terms from current official ontologies are too vague or ambiguous to explicitly map molecular entities to MS signals and we illustrate the inconsistency and ambiguity of current colloquially used terms. We also propose a set of terms for MS1 signal that uniquely, succinctly and intuitively describe data concepts spanning the range of signal provenance from full molecule downs to fine isotopes. We suggest that additional community discussion of these terms should precede any further standardization efforts. We propose a novel nomenclature that spans the range of the required granularity to describe MS data processing from the perspective of the molecular provenance of the MS signal. Conclusions The proposed nomenclature provides a chain of succinct and unique terms spanning the signal created by a charged molecule down through each of its constituent subsignals. We suggest that additional community discussion of these terms should precede any further standardization efforts. PMID:25952148

Integrated quantification and identification of aldehydes and ketones in biological samples.

PubMed

Siegel, David; Meinema, Anne C; Permentier, Hjalmar; Hopfgartner, Gérard; Bischoff, Rainer

2014-05-20

The identification of unknown compounds remains to be a bottleneck of mass spectrometry (MS)-based metabolomics screening experiments. Here, we present a novel approach which facilitates the identification and quantification of analytes containing aldehyde and ketone groups in biological samples by adding chemical information to MS data. Our strategy is based on rapid autosampler-in-needle-derivatization with p-toluenesulfonylhydrazine (TSH). The resulting TSH-hydrazones are separated by ultrahigh-performance liquid chromatography (UHPLC) and detected by electrospray ionization-quadrupole-time-of-flight (ESI-QqTOF) mass spectrometry using a SWATH (Sequential Window Acquisition of all Theoretical Fragment-Ion Spectra) data-independent high-resolution mass spectrometry (HR-MS) approach. Derivatization makes small, poorly ionizable or retained analytes amenable to reversed phase chromatography and electrospray ionization in both polarities. Negatively charged TSH-hydrazone ions furthermore show a simple and predictable fragmentation pattern upon collision induced dissociation, which enables the chemo-selective screening for unknown aldehydes and ketones via a signature fragment ion (m/z 155.0172). By means of SWATH, targeted and nontargeted application scenarios of the suggested derivatization route are enabled in the frame of a single UHPLC-ESI-QqTOF-HR-MS workflow. The method's ability to simultaneously quantify and identify molecules containing aldehyde and ketone groups is demonstrated using 61 target analytes from various compound classes and a (13)C labeled yeast matrix. The identification of unknowns in biological samples is detailed using the example of indole-3-acetaldehyde.

Workflows for Full Waveform Inversions

NASA Astrophysics Data System (ADS)

Boehm, Christian; Krischer, Lion; Afanasiev, Michael; van Driel, Martin; May, Dave A.; Rietmann, Max; Fichtner, Andreas

2017-04-01

Despite many theoretical advances and the increasing availability of high-performance computing clusters, full seismic waveform inversions still face considerable challenges regarding data and workflow management. While the community has access to solvers which can harness modern heterogeneous computing architectures, the computational bottleneck has fallen to these often manpower-bounded issues that need to be overcome to facilitate further progress. Modern inversions involve huge amounts of data and require a tight integration between numerical PDE solvers, data acquisition and processing systems, nonlinear optimization libraries, and job orchestration frameworks. To this end we created a set of libraries and applications revolving around Salvus (http://salvus.io), a novel software package designed to solve large-scale full waveform inverse problems. This presentation focuses on solving passive source seismic full waveform inversions from local to global scales with Salvus. We discuss (i) design choices for the aforementioned components required for full waveform modeling and inversion, (ii) their implementation in the Salvus framework, and (iii) how it is all tied together by a usable workflow system. We combine state-of-the-art algorithms ranging from high-order finite-element solutions of the wave equation to quasi-Newton optimization algorithms using trust-region methods that can handle inexact derivatives. All is steered by an automated interactive graph-based workflow framework capable of orchestrating all necessary pieces. This naturally facilitates the creation of new Earth models and hopefully sparks new scientific insights. Additionally, and even more importantly, it enhances reproducibility and reliability of the final results.

The potential of combining ion trap/MS/MS and TOF/MS for identification of emerging contaminants

USGS Publications Warehouse

Ferrer, I.; Furlong, E.T.; Heine, C.E.; Thurman, E.M.

2002-01-01

The use of a method combining ion trap tandem mass spectrometry (MS/MS) and time of flight mass spectrometry (TOF/MS) for identification of emerging contaminates was discussed. The two tools together complemented each other in sensitivity, fragmentation and accurate mass determination. Liquid chromatography/electrospray ionization/ion-trap tandem mass spectrometry (LC/ESI/MS/MS), in positive ion mode of operation, was used to separate and identify specific compounds. Diagnostic fragment ions were obtained for a polyethyleneglycol(PEG) homolog by ion trap MS/MS, and fragments were measured by TOF/MS. It was observed that the combined method gave an exact mass measurement that differed from the calculated mass.

CyberShake: Running Seismic Hazard Workflows on Distributed HPC Resources

NASA Astrophysics Data System (ADS)

Callaghan, S.; Maechling, P. J.; Graves, R. W.; Gill, D.; Olsen, K. B.; Milner, K. R.; Yu, J.; Jordan, T. H.

2013-12-01

As part of its program of earthquake system science research, the Southern California Earthquake Center (SCEC) has developed a simulation platform, CyberShake, to perform physics-based probabilistic seismic hazard analysis (PSHA) using 3D deterministic wave propagation simulations. CyberShake performs PSHA by simulating a tensor-valued wavefield of Strain Green Tensors, and then using seismic reciprocity to calculate synthetic seismograms for about 415,000 events per site of interest. These seismograms are processed to compute ground motion intensity measures, which are then combined with probabilities from an earthquake rupture forecast to produce a site-specific hazard curve. Seismic hazard curves for hundreds of sites in a region can be used to calculate a seismic hazard map, representing the seismic hazard for a region. We present a recently completed PHSA study in which we calculated four CyberShake seismic hazard maps for the Southern California area to compare how CyberShake hazard results are affected by different SGT computational codes (AWP-ODC and AWP-RWG) and different community velocity models (Community Velocity Model - SCEC (CVM-S4) v11.11 and Community Velocity Model - Harvard (CVM-H) v11.9). We present our approach to running workflow applications on distributed HPC resources, including systems without support for remote job submission. We show how our approach extends the benefits of scientific workflows, such as job and data management, to large-scale applications on Track 1 and Leadership class open-science HPC resources. We used our distributed workflow approach to perform CyberShake Study 13.4 on two new NSF open-science HPC computing resources, Blue Waters and Stampede, executing over 470 million tasks to calculate physics-based hazard curves for 286 locations in the Southern California region. For each location, we calculated seismic hazard curves with two different community velocity models and two different SGT codes, resulting in over 1100 hazard curves. We will report on the performance of this CyberShake study, four times larger than previous studies. Additionally, we will examine the challenges we face applying these workflow techniques to additional open-science HPC systems and discuss whether our workflow solutions continue to provide value to our large-scale PSHA calculations.

From Peer-Reviewed to Peer-Reproduced in Scholarly Publishing: The Complementary Roles of Data Models and Workflows in Bioinformatics

PubMed Central

Zhao, Jun; Avila-Garcia, Maria Susana; Roos, Marco; Thompson, Mark; van der Horst, Eelke; Kaliyaperumal, Rajaram; Luo, Ruibang; Lee, Tin-Lap; Lam, Tak-wah; Edmunds, Scott C.; Sansone, Susanna-Assunta

2015-01-01

Motivation Reproducing the results from a scientific paper can be challenging due to the absence of data and the computational tools required for their analysis. In addition, details relating to the procedures used to obtain the published results can be difficult to discern due to the use of natural language when reporting how experiments have been performed. The Investigation/Study/Assay (ISA), Nanopublications (NP), and Research Objects (RO) models are conceptual data modelling frameworks that can structure such information from scientific papers. Computational workflow platforms can also be used to reproduce analyses of data in a principled manner. We assessed the extent by which ISA, NP, and RO models, together with the Galaxy workflow system, can capture the experimental processes and reproduce the findings of a previously published paper reporting on the development of SOAPdenovo2, a de novo genome assembler. Results Executable workflows were developed using Galaxy, which reproduced results that were consistent with the published findings. A structured representation of the information in the SOAPdenovo2 paper was produced by combining the use of ISA, NP, and RO models. By structuring the information in the published paper using these data and scientific workflow modelling frameworks, it was possible to explicitly declare elements of experimental design, variables, and findings. The models served as guides in the curation of scientific information and this led to the identification of inconsistencies in the original published paper, thereby allowing its authors to publish corrections in the form of an errata. Availability SOAPdenovo2 scripts, data, and results are available through the GigaScience Database: http://dx.doi.org/10.5524/100044; the workflows are available from GigaGalaxy: http://galaxy.cbiit.cuhk.edu.hk; and the representations using the ISA, NP, and RO models are available through the SOAPdenovo2 case study website http://isa-tools.github.io/soapdenovo2/. Contact: philippe.rocca-serra@oerc.ox.ac.uk and susanna-assunta.sansone@oerc.ox.ac.uk. PMID:26154165

Successful Completion of FY18/Q1 ASC L2 Milestone 6355: Electrical Analysis Calibration Workflow Capability Demonstration.

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

Copps, Kevin D.

The Sandia Analysis Workbench (SAW) project has developed and deployed a production capability for SIERRA computational mechanics analysis workflows. However, the electrical analysis workflow capability requirements have only been demonstrated in early prototype states, with no real capability deployed for analysts’ use. This milestone aims to improve the electrical analysis workflow capability (via SAW and related tools) and deploy it for ongoing use. We propose to focus on a QASPR electrical analysis calibration workflow use case. We will include a number of new capabilities (versus today’s SAW), such as: 1) support for the XYCE code workflow component, 2) data managementmore » coupled to electrical workflow, 3) human-in-theloop workflow capability, and 4) electrical analysis workflow capability deployed on the restricted (and possibly classified) network at Sandia. While far from the complete set of capabilities required for electrical analysis workflow over the long term, this is a substantial first step toward full production support for the electrical analysts.« less

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

PubMed Central

2011-01-01

Background Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology. Result We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site. This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser. Conclusions Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html PMID:21414234

Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach.

PubMed

Haston, Elspeth; Cubey, Robert; Pullan, Martin; Atkins, Hannah; Harris, David J

2012-01-01

Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow.The specimen workflow is strongly linked to curatorial processes which will impact on the prioritisation, selection and preparation of the specimens. The importance of including a conservation element within the digitisation workflow is highlighted. The data workflow includes the concept of three main categories of collection data: label data, curatorial data and supplementary data. It is shown that each category of data has its own properties which influence the timing of data capture within the workflow. Development of software has been carried out for the rapid capture of curatorial data, and optical character recognition (OCR) software is being used to increase the efficiency of capturing label data and supplementary data. The large number and size of the images has necessitated the inclusion of automated systems within the image workflow.

Proteomics Analysis of Skeletal Muscle from Leptin-Deficient ob/ob Mice Reveals Adaptive Remodeling of Metabolic Characteristics and Fiber Type Composition.

PubMed

Schönke, Milena; Björnholm, Marie; Chibalin, Alexander V; Zierath, Juleen R; Deshmukh, Atul S

2018-03-01

Skeletal muscle insulin resistance, an early metabolic defect in the pathogenesis of type 2 diabetes (T2D), may be a cause or consequence of altered protein expression profiles. Proteomics technology offers enormous promise to investigate molecular mechanisms underlying pathologies, however, the analysis of skeletal muscle is challenging. Using state-of-the-art multienzyme digestion and filter-aided sample preparation (MED-FASP) and a mass spectrometry (MS)-based workflow, we performed a global proteomics analysis of skeletal muscle from leptin-deficient, obese, insulin resistant (ob/ob) and lean mice in mere two fractions in a short time (8 h per sample). We identified more than 6000 proteins with 118 proteins differentially regulated in obesity. This included protein kinases, phosphatases, and secreted and fiber type associated proteins. Enzymes involved in lipid metabolism in skeletal muscle from ob/ob mice were increased, providing evidence against reduced fatty acid oxidation in lipid-induced insulin resistance. Mitochondrial and peroxisomal proteins, as well as components of pyruvate and lactate metabolism, were increased. Finally, the skeletal muscle proteome from ob/ob mice displayed a shift toward the "slow fiber type." This detailed characterization of an obese rodent model of T2D demonstrates an efficient workflow for skeletal muscle proteomics, which may easily be adapted to other complex tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Achieving accurate compound concentration in cell-based screening: validation of acoustic droplet ejection technology.

PubMed

Grant, Richard John; Roberts, Karen; Pointon, Carly; Hodgson, Clare; Womersley, Lynsey; Jones, Darren Craig; Tang, Eric

2009-06-01

Compound handling is a fundamental and critical step in compound screening throughout the drug discovery process. Although most compound-handling processes within compound management facilities use 100% DMSO solvent, conventional methods of manual or robotic liquid-handling systems in screening workflows often perform dilutions in aqueous solutions to maintain solvent tolerance of the biological assay. However, the use of aqueous media in these applications can lead to suboptimal data quality due to compound carryover or precipitation during the dilution steps. In cell-based assays, this effect is worsened by the unpredictable physical characteristics of compounds and the low DMSO tolerance within the assay. In some cases, the conventional approaches using manual or automated liquid handling resulted in variable IC(50) dose responses. This study examines the cause of this variability and evaluates the accuracy of screening data in these case studies. A number of liquid-handling options have been explored to address the issues and establish a generic compound-handling workflow to support cell-based screening across our screening functions. The authors discuss the validation of the Labcyte Echo reformatter as an effective noncontact solution for generic compound-handling applications against diverse compound classes using triple-quad liquid chromatography/mass spectrometry. The successful validation and implementation challenges of this technology for direct dosing onto cells in cell-based screening is discussed.

Image analysis tools and emerging algorithms for expression proteomics

PubMed Central

English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

2012-01-01

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

Spatially resolved proteome mapping of laser capture microdissected tissue with automated sample transfer to nanodroplets.

PubMed

Zhu, Ying; Dou, Maowei; Piehowski, Paul D; Liang, Yiran; Wang, Fangjun; Chu, Rosalie K; Chrisler, Will; Smith, Jordan N; Schwarz, Kaitlynn C; Shen, Yufeng; Shukla, Anil K; Moore, Ronald J; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T

2018-06-24

Current mass spectrometry (MS)-based proteomics approaches are ineffective for mapping protein expression in tissue sections with high spatial resolution due to the limited overall sensitivity of conventional workflows. Here we report an integrated and automated method to advance spatially resolved proteomics by seamlessly coupling laser capture microdissection (LCM) with a recently developed nanoliter-scale sample preparation system termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples). The workflow is enabled by prepopulating nanowells with DMSO, which serves as a sacrificial capture liquid for microdissected tissues. The DMSO droplets efficiently collect laser-pressure catapulted LCM tissues as small as 20 µm in diameter with success rates >87%. We also demonstrate that tissue treatment with DMSO can significantly improve proteome coverage, likely due to its ability to dissolve lipids from tissue and enhance protein extraction efficiency. The LCM-nanoPOTS platform was able to identify 180, 695, and 1827 protein groups on average from 12-µm-thick rat brain cortex tissue sections with diameters of 50, 100, and 200 µm, respectively. We also analyzed 100-µm-diameter sections corresponding to 10-18 cells from three different regions of rat brain and comparatively quantified ~1000 proteins, demonstrating the potential utility for high-resolution spatially resolved mapping of protein expression in tissues. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

Improving mass measurement accuracy in mass spectrometry based proteomics by combining open source tools for chromatographic alignment and internal calibration.

PubMed

Palmblad, Magnus; van der Burgt, Yuri E M; Dalebout, Hans; Derks, Rico J E; Schoenmaker, Bart; Deelder, André M

2009-05-02

Accurate mass determination enhances peptide identification in mass spectrometry based proteomics. We here describe the combination of two previously published open source software tools to improve mass measurement accuracy in Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS). The first program, msalign, aligns one MS/MS dataset with one FTICRMS dataset. The second software, recal2, uses peptides identified from the MS/MS data for automated internal calibration of the FTICR spectra, resulting in sub-ppm mass measurement errors.

Discovered acetylcholinesterase inhibition and antibacterial activity of polyacetylenes in tansy root extract via effect-directed chromatographic fingerprints.

PubMed

Móricz, Ágnes M; Ott, Péter G; Morlock, Gertrud E

2018-03-30

The knowledge about the activity of polyacetylenes was extended by their new acetylcholinesterase inhibition and antibacterial activity against plant pathogenic bacteria. For this discovery, an utmost streamlined workflow, which we consider to be of high potential in the field of natural product or superfood search was developed. It demonstrates the combined power of biological, biochemical and chemical fingerprints. Bioactive components of tansy (Tanacetum vulgare L.) root extract were profiled and identified by high-performance thin-layer chromatography hyphenated with in situ effect-directed analysis, chemical derivatizations and high-resolution mass spectrometry (HPTLC-UV/Vis/FLD-EDA-HRMS). The effect-directed profiling was performed using four bacterial bioassays including two plant pathogens, an antioxidant assay and acetyl- and butyrylcholinesterase inhibitory assays. The chromatographic, spectral and powerful mass spectrometric study of zones that exerted substantial antibacterial and/or antioxidant and/or acetylcholinesterase inhibitory effects allowed these multi-potent zones to be identified as polyacetylenes. Five polyacetylene compounds were assigned to be 2-non-1-ene-3,5,7-triynyl-3-vinyl-oxirane, 2-(2,4-hexadiynylidene)-3,4-epoxy-1,6-dioxaspiro[4.5]decane, trans- and cis-2-(2,4-hexadiynylidene)-1,6-dioxaspiro[4.5]dec-3-ene and tetradeca-2,4,6-triine-8-en-12-one. This study clearly showed the advantage of the combined use of different ionization sources, i.e. electrospray ionization via an elution-head based interface and also the Direct Analysis in Real Time interface, for HRMS analysis of compounds from the same class with very similar chromatographic behavior and polarity. Copyright © 2018 Elsevier B.V. All rights reserved.

RESTFul based heterogeneous Geoprocessing workflow interoperation for Sensor Web Service

NASA Astrophysics Data System (ADS)

Yang, Chao; Chen, Nengcheng; Di, Liping

2012-10-01

Advanced sensors on board satellites offer detailed Earth observations. A workflow is one approach for designing, implementing and constructing a flexible and live link between these sensors' resources and users. It can coordinate, organize and aggregate the distributed sensor Web services to meet the requirement of a complex Earth observation scenario. A RESTFul based workflow interoperation method is proposed to integrate heterogeneous workflows into an interoperable unit. The Atom protocols are applied to describe and manage workflow resources. The XML Process Definition Language (XPDL) and Business Process Execution Language (BPEL) workflow standards are applied to structure a workflow that accesses sensor information and one that processes it separately. Then, a scenario for nitrogen dioxide (NO2) from a volcanic eruption is used to investigate the feasibility of the proposed method. The RESTFul based workflows interoperation system can describe, publish, discover, access and coordinate heterogeneous Geoprocessing workflows.

Scientific Data Management (SDM) Center for Enabling Technologies. 2007-2012

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

Ludascher, Bertram; Altintas, Ilkay

Over the past five years, our activities have both established Kepler as a viable scientific workflow environment and demonstrated its value across multiple science applications. We have published numerous peer-reviewed papers on the technologies highlighted in this short paper and have given Kepler tutorials at SC06,SC07,SC08,and SciDAC 2007. Our outreach activities have allowed scientists to learn best practices and better utilize Kepler to address their individual workflow problems. Our contributions to advancing the state-of-the-art in scientific workflows have focused on the following areas. Progress in each of these areas is described in subsequent sections. Workflow development. The development of amore » deeper understanding of scientific workflows "in the wild" and of the requirements for support tools that allow easy construction of complex scientific workflows; Generic workflow components and templates. The development of generic actors (i.e.workflow components and processes) which can be broadly applied to scientific problems; Provenance collection and analysis. The design of a flexible provenance collection and analysis infrastructure within the workflow environment; and, Workflow reliability and fault tolerance. The improvement of the reliability and fault-tolerance of workflow environments.« less

New on-line separation workflow of microbial metabolites via hyphenation of analytical and preparative comprehensive two-dimensional liquid chromatography.

PubMed

Yan, Xia; Wang, Li-Juan; Wu, Zhen; Wu, Yun-Long; Liu, Xiu-Xiu; Chang, Fang-Rong; Fang, Mei-Juan; Qiu, Ying-Kun

2016-10-15

Microbial metabolites represent an important source of bioactive natural products, but always exhibit diverse of chemical structures or complicated chemical composition with low active ingredients content. Traditional separation methods rely mainly on off-line combination of open-column chromatography and preparative high performance liquid chromatography (HPLC). However, the multi-step and prolonged separation procedure might lead to exposure to oxygen and structural transformation of metabolites. In the present work, a new two-dimensional separation workflow for fast isolation and analysis of microbial metabolites from Chaetomium globosum SNSHI-5, a cytotoxic fungus derived from extreme environment. The advantage of this analytical comprehensive two-dimensional liquid chromatography (2D-LC) lies on its ability to analyze the composition of the metabolites, and to optimize the separation conditions for the preparative 2D-LC. Furthermore, gram scale preparative 2D-LC separation of the crude fungus extract could be performed on a medium-pressure liquid chromatograph×preparative high-performance liquid chromatography system, under the optimized condition. Interestingly, 12 cytochalasan derivatives, including two new compounds named cytoglobosin Ab (3) and isochaetoglobosin Db (8), were successfully obtained with high purity in a short period of time. The structures of the isolated metabolites were comprehensively characterized by HR ESI-MS and NMR. To be highlighted, this is the first report on the combination of analytical and preparative 2D-LC for the separation of microbial metabolites. The new workflow exhibited apparent advantages in separation efficiency and sample treatment capacity compared with conventional methods. Copyright © 2016 Elsevier B.V. All rights reserved.

Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges.

PubMed

Töpfer, Nadine; Seaver, Samuel M D; Aharoni, Asaph

2018-01-01

In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

PubMed Central

Clasquin, Michelle F.; Melamud, Eugene; Rabinowitz, Joshua D.

2014-01-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. PMID:22389014

Metabolomics and Diabetes: Analytical and Computational Approaches

PubMed Central

Sas, Kelli M.; Karnovsky, Alla; Michailidis, George

2015-01-01

Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field. PMID:25713200

Phenotypic mapping of metabolic profiles using self-organizing maps of high-dimensional mass spectrometry data.

PubMed

Goodwin, Cody R; Sherrod, Stacy D; Marasco, Christina C; Bachmann, Brian O; Schramm-Sapyta, Nicole; Wikswo, John P; McLean, John A

2014-07-01

A metabolic system is composed of inherently interconnected metabolic precursors, intermediates, and products. The analysis of untargeted metabolomics data has conventionally been performed through the use of comparative statistics or multivariate statistical analysis-based approaches; however, each falls short in representing the related nature of metabolic perturbations. Herein, we describe a complementary method for the analysis of large metabolite inventories using a data-driven approach based upon a self-organizing map algorithm. This workflow allows for the unsupervised clustering, and subsequent prioritization of, correlated features through Gestalt comparisons of metabolic heat maps. We describe this methodology in detail, including a comparison to conventional metabolomics approaches, and demonstrate the application of this method to the analysis of the metabolic repercussions of prolonged cocaine exposure in rat sera profiles.

LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

PubMed

Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

2012-03-01

MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

Identification of ATM Protein Kinase Phosphorylation Sites by Mass Spectrometry.

PubMed

Graham, Mark E; Lavin, Martin F; Kozlov, Sergei V

2017-01-01

ATM (ataxia-telangiectasia mutated) protein kinase is a key regulator of cellular responses to DNA damage and oxidative stress. DNA damage triggers complex cascade of signaling events leading to numerous posttranslational modification on multitude of proteins. Understanding the regulation of ATM kinase is therefore critical not only for understanding the human genetic disorder ataxia-telangiectasia and potential treatment strategies, but essential for deciphering physiological responses of cells to stress. These responses play an important role in carcinogenesis, neurodegeneration, and aging. We focus here on the identification of DNA damage inducible ATM phosphorylation sites to understand the importance of autophosphorylation in the mechanism of ATM kinase activation. We demonstrate the utility of using immunoprecipitated ATM in quantitative LC-MS/MS workflow with stable isotope dimethyl labeling of ATM peptides for identification of phosphorylation sites.

Measuring the Impact of Technology on Nurse Workflow: A Mixed Methods Approach

ERIC Educational Resources Information Center

Cady, Rhonda Guse

2012-01-01

Background. Investment in health information technology (HIT) is rapidly accelerating. The absence of contextual or situational analysis of the environment in which HIT is incorporated makes it difficult to measure success or failure. The methodology introduced in this paper combines observational research with time-motion study to measure the…

Making Information Literacy Instruction More Efficient by Providing Individual Feedback

ERIC Educational Resources Information Center

Peter, Johannes; Leichner, Nikolas; Mayer, Anne-Kathrin; Krampen, Günter

2017-01-01

This paper presents an approach to information literacy instruction in colleges and universities that combines online and classroom learning (Blended Learning). The concept includes only one classroom seminar, so the approach presented here can replace existing one-shot sessions at colleges and universities without changes to the current workflow.…

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

Functional assessment of ubiquitin-depended processes under microgravity conditions

NASA Astrophysics Data System (ADS)

Zhabereva, Anastasia; Shenkman, Boris S.; Gainullin, Murat; Gurev, Eugeny; Kondratieva, Ekaterina; Kopylov, Arthur

Ubiquitylation, a widespread and important posttranslational modification of eukaryotic proteins, controls a multitude of critical cellular processes, both in normal and pathological conditions. The present work aims to study involvement of ubiquitin-dependent regulation in adaptive response to the external stimuli. Experiments were carried out on C57BL/6 mice. The microgravity state under conditions of real spaceflight on the biosatellite “BION-M1” was used as a model of stress impact. Additionally, number of control series including the vivarium control and experiments in Ground-based analog were also studied. The aggregate of endogenously ubiquitylated proteins was selected as specific feature of ubiquitin-dependent processes. Dynamic changes of modification pattern were characterized in liver tissue by combination of some methods, particularly by specific isolation of explicit protein pool, followed by immunodetection and/or mass spectrometry-based identification. The main approach includes specific extraction of proteins, modified by multiubiquitin chains of different length and topology. For this purpose two techniques were applied: 1) immunoprecipitation with antibodies against ubiquitin and/or multiubiquitin chains; 2) pull-down using synthetic protein construct termed Tandem Ubiquitin Binding Entities (TUBE, LifeSensors). TUBE represents fusion protein, composed of well characterized ubiquitin-binding domains, and thereby allows specific high-affinity binding and extraction of ubiquitylated proteins. Resulting protein fractions were analyzed by immunoblotting with antibodies against different types of multiubiquitin chains. Using this method we mapped endogenously modified proteins involved in two different types of ubiquitin-dependent processes, namely catabolic and non-catabolic ubiquitylation, in liver tissues, obtained from both control as well as experimental groups of animals, mentioned above. Then, isolated fractions of ubiquitylated proteins, were separated by SDS-PAGE and subjected for mass spectrometry-based analysis.With the described workflow, we identified more than 200 proteins including of 26S proteasome subunits, members of SUMO (Small Ubiquitin-like Modifier) family and ubiquitylated substrates. On the whole, our results provide an unbiased view of ubiquitylation state under microgravity conditions and thereby demonstrate the utility of proposed combination of analytical methods for functional assessment of ubiquitin-depended processes. Acknowledgment - We thank teams of Institute of Biomedical Problems of Russian Academy of Sciences and TsSKB “Progress” Samara for organization and preparation for spaceflight. This work is partially supported by the Russian Foundation for Basic Research (grant12-04-01836).

Integrated work-flow for quantitative metabolome profiling of plants, Peucedani Radix as a case.

PubMed

Song, Yuelin; Song, Qingqing; Liu, Yao; Li, Jun; Wan, Jian-Bo; Wang, Yitao; Jiang, Yong; Tu, Pengfei

2017-02-08

Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only holistically provide qualitative information, but also straightforwardly generate accurate quantitative dataset. Copyright © 2016 Elsevier B.V. All rights reserved.

Cytoscape: the network visualization tool for GenomeSpace workflows.

PubMed

Demchak, Barry; Hull, Tim; Reich, Michael; Liefeld, Ted; Smoot, Michael; Ideker, Trey; Mesirov, Jill P

2014-01-01

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013.

Cytoscape: the network visualization tool for GenomeSpace workflows

PubMed Central

Demchak, Barry; Hull, Tim; Reich, Michael; Liefeld, Ted; Smoot, Michael; Ideker, Trey; Mesirov, Jill P.

2014-01-01

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013. PMID:25165537

Scrambled eggs: A highly sensitive molecular diagnostic workflow for Fasciola species specific detection from faecal samples

PubMed Central

Calvani, Nichola Eliza Davies; Windsor, Peter Andrew; Bush, Russell David

2017-01-01

Background Fasciolosis, due to Fasciola hepatica and Fasciola gigantica, is a re-emerging zoonotic parasitic disease of worldwide importance. Human and animal infections are commonly diagnosed by the traditional sedimentation and faecal egg-counting technique. However, this technique is time-consuming and prone to sensitivity errors when a large number of samples must be processed or if the operator lacks sufficient experience. Additionally, diagnosis can only be made once the 12-week pre-patent period has passed. Recently, a commercially available coprological antigen ELISA has enabled detection of F. hepatica prior to the completion of the pre-patent period, providing earlier diagnosis and increased throughput, although species differentiation is not possible in areas of parasite sympatry. Real-time PCR offers the combined benefits of highly sensitive species differentiation for medium to large sample sizes. However, no molecular diagnostic workflow currently exists for the identification of Fasciola spp. in faecal samples. Methodology/Principal findings A new molecular diagnostic workflow for the highly-sensitive detection and quantification of Fasciola spp. in faecal samples was developed. The technique involves sedimenting and pelleting the samples prior to DNA isolation in order to concentrate the eggs, followed by disruption by bead-beating in a benchtop homogeniser to ensure access to DNA. Although both the new molecular workflow and the traditional sedimentation technique were sensitive and specific, the new molecular workflow enabled faster sample throughput in medium to large epidemiological studies, and provided the additional benefit of speciation. Further, good correlation (R2 = 0.74–0.76) was observed between the real-time PCR values and the faecal egg count (FEC) using the new molecular workflow for all herds and sampling periods. Finally, no effect of storage in 70% ethanol was detected on sedimentation and DNA isolation outcomes; enabling transport of samples from endemic to non-endemic countries without the requirement of a complete cold chain. The commercially-available ELISA displayed poorer sensitivity, even after adjustment of the positive threshold (65–88%), compared to the sensitivity (91–100%) of the new molecular diagnostic workflow. Conclusions/Significance Species-specific assays for sensitive detection of Fasciola spp. enable ante-mortem diagnosis in both human and animal settings. This includes Southeast Asia where there are potentially many undocumented human cases and where post-mortem examination of production animals can be difficult. The new molecular workflow provides a sensitive and quantitative diagnostic approach for the rapid testing of medium to large sample sizes, potentially superseding the traditional sedimentation and FEC technique and enabling surveillance programs in locations where animal and human health funding is limited. PMID:28915255

Developing integrated workflows for the digitisation of herbarium specimens using a modular and scalable approach

PubMed Central

Haston, Elspeth; Cubey, Robert; Pullan, Martin; Atkins, Hannah; Harris, David J

2012-01-01

Abstract Digitisation programmes in many institutes frequently involve disparate and irregular funding, diverse selection criteria and scope, with different members of staff managing and operating the processes. These factors have influenced the decision at the Royal Botanic Garden Edinburgh to develop an integrated workflow for the digitisation of herbarium specimens which is modular and scalable to enable a single overall workflow to be used for all digitisation projects. This integrated workflow is comprised of three principal elements: a specimen workflow, a data workflow and an image workflow. The specimen workflow is strongly linked to curatorial processes which will impact on the prioritisation, selection and preparation of the specimens. The importance of including a conservation element within the digitisation workflow is highlighted. The data workflow includes the concept of three main categories of collection data: label data, curatorial data and supplementary data. It is shown that each category of data has its own properties which influence the timing of data capture within the workflow. Development of software has been carried out for the rapid capture of curatorial data, and optical character recognition (OCR) software is being used to increase the efficiency of capturing label data and supplementary data. The large number and size of the images has necessitated the inclusion of automated systems within the image workflow. PMID:22859881

Combined Multidimensional Microscopy as a Histopathology Imaging Tool.

PubMed

Shami, Gerald J; Cheng, Delfine; Braet, Filip

2017-02-01

Herein, we present a highly versatile bioimaging workflow for the multidimensional imaging of biological structures across vastly different length scales. Such an approach allows for the optimised preparation of samples in one go for consecutive X-ray micro-computed tomography, bright-field light microscopy and backscattered scanning electron microscopy, thus, facilitating the disclosure of combined structural information ranging from the gross tissue or cellular level, down to the nanometre scale. In this current study, we characterize various aspects of the hepatic vasculature, ranging from such large vessels as branches of the hepatic portal vein and hepatic artery, down to the smallest sinusoidal capillaries. By employing high-resolution backscattered scanning electron microscopy, we were able to further characterize the subcellular features of a range of hepatic sinusoidal cells including, liver sinusoidal endothelial cells, pit cells and Kupffer cells. Above all, we demonstrate the capabilities of a specimen manipulation workflow that can be applied and adapted to a plethora of functional and structural investigations and experimental models. Such an approach harnesses the fundamental advantages inherent to the various imaging modalities presented herein, and when combined, offers information not currently available by any single imaging platform. J. Cell. Physiol. 232: 249-256, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dispel4py: An Open-Source Python library for Data-Intensive Seismology

NASA Astrophysics Data System (ADS)

Filgueira, Rosa; Krause, Amrey; Spinuso, Alessandro; Klampanos, Iraklis; Danecek, Peter; Atkinson, Malcolm

2015-04-01

Scientific workflows are a necessary tool for many scientific communities as they enable easy composition and execution of applications on computing resources while scientists can focus on their research without being distracted by the computation management. Nowadays, scientific communities (e.g. Seismology) have access to a large variety of computing resources and their computational problems are best addressed using parallel computing technology. However, successful use of these technologies requires a lot of additional machinery whose use is not straightforward for non-experts: different parallel frameworks (MPI, Storm, multiprocessing, etc.) must be used depending on the computing resources (local machines, grids, clouds, clusters) where applications are run. This implies that for achieving the best applications' performance, users usually have to change their codes depending on the features of the platform selected for running them. This work presents dispel4py, a new open-source Python library for describing abstract stream-based workflows for distributed data-intensive applications. Special care has been taken to provide dispel4py with the ability to map abstract workflows to different platforms dynamically at run-time. Currently dispel4py has four mappings: Apache Storm, MPI, multi-threading and sequential. The main goal of dispel4py is to provide an easy-to-use tool to develop and test workflows in local resources by using the sequential mode with a small dataset. Later, once a workflow is ready for long runs, it can be automatically executed on different parallel resources. dispel4py takes care of the underlying mappings by performing an efficient parallelisation. Processing Elements (PE) represent the basic computational activities of any dispel4Py workflow, which can be a seismologic algorithm, or a data transformation process. For creating a dispel4py workflow, users only have to write very few lines of code to describe their PEs and how they are connected by using Python, which is widely supported on many platforms and is popular in many scientific domains, such as in geosciences. Once, a dispel4py workflow is written, a user only has to select which mapping they would like to use, and everything else (parallelisation, distribution of data) is carried on by dispel4py without any cost to the user. Among all dispel4py features we would like to highlight the following: * The PEs are connected by streams and not by writing to and reading from intermediate files, avoiding many IO operations. * The PEs can be stored into a registry. Therefore, different users can recombine PEs in many different workflows. * dispel4py has been enriched with a provenance mechanism to support runtime provenance analysis. We have adopted the W3C-PROV data model, which is accessible via a prototypal browser-based user interface and a web API. It supports the users with the visualisation of graphical products and offers combined operations to access and download the data, which may be selectively stored at runtime, into dedicated data archives. dispel4py has been already used by seismologists in the VERCE project to develop different seismic workflows. One of them is the Seismic Ambient Noise Cross-Correlation workflow, which preprocesses and cross-correlates traces from several stations. First, this workflow was tested on a local machine by using a small number of stations as input data. Later, it was executed on different parallel platforms (SuperMUC cluster, and Terracorrelator machine), automatically scaling up by using MPI and multiprocessing mappings and up to 1000 stations as input data. The results show that the dispel4py achieves scalable performance in both mappings tested on different parallel platforms.

Building asynchronous geospatial processing workflows with web services

NASA Astrophysics Data System (ADS)

Zhao, Peisheng; Di, Liping; Yu, Genong

2012-02-01

Geoscience research and applications often involve a geospatial processing workflow. This workflow includes a sequence of operations that use a variety of tools to collect, translate, and analyze distributed heterogeneous geospatial data. Asynchronous mechanisms, by which clients initiate a request and then resume their processing without waiting for a response, are very useful for complicated workflows that take a long time to run. Geospatial contents and capabilities are increasingly becoming available online as interoperable Web services. This online availability significantly enhances the ability to use Web service chains to build distributed geospatial processing workflows. This paper focuses on how to orchestrate Web services for implementing asynchronous geospatial processing workflows. The theoretical bases for asynchronous Web services and workflows, including asynchrony patterns and message transmission, are examined to explore different asynchronous approaches to and architecture of workflow code for the support of asynchronous behavior. A sample geospatial processing workflow, issued by the Open Geospatial Consortium (OGC) Web Service, Phase 6 (OWS-6), is provided to illustrate the implementation of asynchronous geospatial processing workflows and the challenges in using Web Services Business Process Execution Language (WS-BPEL) to develop them.

XML schemas for common bioinformatic data types and their application in workflow systems.

PubMed

Seibel, Philipp N; Krüger, Jan; Hartmeier, Sven; Schwarzer, Knut; Löwenthal, Kai; Mersch, Henning; Dandekar, Thomas; Giegerich, Robert

2006-11-06

Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data--therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. Acknowledging the need for common formats, the Helmholtz Open BioInformatics Technology network (HOBIT) identified several basic data types used in bioinformatics and developed appropriate format descriptions, formally defined by XML schemas, and incorporated them in a Java library (BioDOM). These schemas currently cover sequence, sequence alignment, RNA secondary structure and RNA secondary structure alignment formats in a form that is independent of any specific program, thus enabling seamless interoperation of different tools. All XML formats are available at http://bioschemas.sourceforge.net, the BioDOM library can be obtained at http://biodom.sourceforge.net. The HOBIT XML schemas and the BioDOM library simplify adding XML support to newly created and existing bioinformatic tools, enabling these tools to interoperate seamlessly in workflow scenarios.

I'll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets

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

Chard, Kyle; D'Arcy, Mike; Heavner, Benjamin D.

Big data workflows often require the assembly and exchange of complex, multi-element datasets. For example, in biomedical applications, the input to an analytic pipeline can be a dataset consisting thousands of images and genome sequences assembled from diverse repositories, requiring a description of the contents of the dataset in a concise and unambiguous form. Typical approaches to creating datasets for big data workflows assume that all data reside in a single location, requiring costly data marshaling and permitting errors of omission and commission because dataset members are not explicitly specified. We address these issues by proposing simple methods and toolsmore » for assembling, sharing, and analyzing large and complex datasets that scientists can easily integrate into their daily workflows. These tools combine a simple and robust method for describing data collections (BDBags), data descriptions (Research Objects), and simple persistent identifiers (Minids) to create a powerful ecosystem of tools and services for big data analysis and sharing. We present these tools and use biomedical case studies to illustrate their use for the rapid assembly, sharing, and analysis of large datasets.« less

Preservation of protein fluorescence in embedded human dendritic cells for targeted 3D light and electron microscopy.

PubMed

Höhn, K; Fuchs, J; Fröber, A; Kirmse, R; Glass, B; Anders-Össwein, M; Walther, P; Kräusslich, H-G; Dietrich, C

2015-08-01

In this study, we present a correlative microscopy workflow to combine detailed 3D fluorescence light microscopy data with ultrastructural information gained by 3D focused ion beam assisted scanning electron microscopy. The workflow is based on an optimized high pressure freezing/freeze substitution protocol that preserves good ultrastructural detail along with retaining the fluorescence signal in the resin embedded specimens. Consequently, cellular structures of interest can readily be identified and imaged by state of the art 3D confocal fluorescence microscopy and are precisely referenced with respect to an imprinted coordinate system on the surface of the resin block. This allows precise guidance of the focused ion beam assisted scanning electron microscopy and limits the volume to be imaged to the structure of interest. This, in turn, minimizes the total acquisition time necessary to conduct the time consuming ultrastructural scanning electron microscope imaging while eliminating the risk to miss parts of the target structure. We illustrate the value of this workflow for targeting virus compartments, which are formed in HIV-pulsed mature human dendritic cells. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Automated Purification of Recombinant Proteins: Combining High-throughput with High Yield

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

Lin, Chiann Tso; Moore, Priscilla A.; Auberry, Deanna L.

2006-05-01

Protein crystallography, mapping protein interactions and other approaches of current functional genomics require not only purifying large numbers of proteins but also obtaining sufficient yield and homogeneity for downstream high-throughput applications. There is a need for the development of robust automated high-throughput protein expression and purification processes to meet these requirements. We developed and compared two alternative workflows for automated purification of recombinant proteins based on expression of bacterial genes in Escherichia coli: First - a filtration separation protocol based on expression of 800 ml E. coli cultures followed by filtration purification using Ni2+-NTATM Agarose (Qiagen). Second - a smallermore » scale magnetic separation method based on expression in 25 ml cultures of E.coli followed by 96-well purification on MagneHisTM Ni2+ Agarose (Promega). Both workflows provided comparable average yields of proteins about 8 ug of purified protein per unit of OD at 600 nm of bacterial culture. We discuss advantages and limitations of the automated workflows that can provide proteins more than 90 % pure in the range of 100 ug – 45 mg per purification run as well as strategies for optimization of these protocols.« less

Workflow-Based Software Development Environment

NASA Technical Reports Server (NTRS)

Izygon, Michel E.

2013-01-01

The Software Developer's Assistant (SDA) helps software teams more efficiently and accurately conduct or execute software processes associated with NASA mission-critical software. SDA is a process enactment platform that guides software teams through project-specific standards, processes, and procedures. Software projects are decomposed into all of their required process steps or tasks, and each task is assigned to project personnel. SDA orchestrates the performance of work required to complete all process tasks in the correct sequence. The software then notifies team members when they may begin work on their assigned tasks and provides the tools, instructions, reference materials, and supportive artifacts that allow users to compliantly perform the work. A combination of technology components captures and enacts any software process use to support the software lifecycle. It creates an adaptive workflow environment that can be modified as needed. SDA achieves software process automation through a Business Process Management (BPM) approach to managing the software lifecycle for mission-critical projects. It contains five main parts: TieFlow (workflow engine), Business Rules (rules to alter process flow), Common Repository (storage for project artifacts, versions, history, schedules, etc.), SOA (interface to allow internal, GFE, or COTS tools integration), and the Web Portal Interface (collaborative web environment

Big data analytics in immunology: a knowledge-based approach.

PubMed

Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

2014-01-01

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

The CARMEN software as a service infrastructure.

PubMed

Weeks, Michael; Jessop, Mark; Fletcher, Martyn; Hodge, Victoria; Jackson, Tom; Austin, Jim

2013-01-28

The CARMEN platform allows neuroscientists to share data, metadata, services and workflows, and to execute these services and workflows remotely via a Web portal. This paper describes how we implemented a service-based infrastructure into the CARMEN Virtual Laboratory. A Software as a Service framework was developed to allow generic new and legacy code to be deployed as services on a heterogeneous execution framework. Users can submit analysis code typically written in Matlab, Python, C/C++ and R as non-interactive standalone command-line applications and wrap them as services in a form suitable for deployment on the platform. The CARMEN Service Builder tool enables neuroscientists to quickly wrap their analysis software for deployment to the CARMEN platform, as a service without knowledge of the service framework or the CARMEN system. A metadata schema describes each service in terms of both system and user requirements. The search functionality allows services to be quickly discovered from the many services available. Within the platform, services may be combined into more complicated analyses using the workflow tool. CARMEN and the service infrastructure are targeted towards the neuroscience community; however, it is a generic platform, and can be targeted towards any discipline.

Fast liquid chromatography combined with mass spectrometry for the analysis of metabolites and proteins in human body fluids.

PubMed

Kortz, Linda; Helmschrodt, Christin; Ceglarek, Uta

2011-03-01

In the last decade various analytical strategies have been established to enhance separation speed and efficiency in high performance liquid chromatography applications. Chromatographic supports based on monolithic material, small porous particles, and porous layer beads have been developed and commercialized to improve throughput and separation efficiency. This paper provides an overview of current developments in fast chromatography combined with mass spectrometry for the analysis of metabolites and proteins in clinical applications. Advances and limitations of fast chromatography for the combination with mass spectrometry are discussed. Practical aspects of, recent developments in, and the present status of high-throughput analysis of human body fluids for therapeutic drug monitoring, toxicology, clinical metabolomics, and proteomics are presented.

Classical workflow nets and workflow nets with reset arcs: using Lyapunov stability for soundness verification

NASA Astrophysics Data System (ADS)

Clempner, Julio B.

2017-01-01

This paper presents a novel analytical method for soundness verification of workflow nets and reset workflow nets, using the well-known stability results of Lyapunov for Petri nets. We also prove that the soundness property is decidable for workflow nets and reset workflow nets. In addition, we provide evidence of several outcomes related with properties such as boundedness, liveness, reversibility and blocking using stability. Our approach is validated theoretically and by a numerical example related to traffic signal-control synchronisation.

Quantitation of mycotoxins using direct analysis in real time (DART)-mass spectrometry (MS)

USDA-ARS?s Scientific Manuscript database

Ambient ionization represents a new generation of mass spectrometry ion sources which is used for rapid ionization of small molecules under ambient conditions. The combination of ambient ionization and mass spectrometry allows analyzing multiple food samples with simple or no sample treatment, or in...

Biowep: a workflow enactment portal for bioinformatics applications.

PubMed

Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano

2007-03-08

The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical databases and analysis software and the creation of effective workflows can significantly improve automation of in-silico analysis. Biowep is available for interested researchers as a reference portal. They are invited to submit their workflows to the workflow repository. Biowep is further being developed in the sphere of the Laboratory of Interdisciplinary Technologies in Bioinformatics - LITBIO.

Biowep: a workflow enactment portal for bioinformatics applications

PubMed Central

Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano

2007-01-01

Background The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. Results We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. Conclusion We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical databases and analysis software and the creation of effective workflows can significantly improve automation of in-silico analysis. Biowep is available for interested researchers as a reference portal. They are invited to submit their workflows to the workflow repository. Biowep is further being developed in the sphere of the Laboratory of Interdisciplinary Technologies in Bioinformatics – LITBIO. PMID:17430563

Introducing students to digital geological mapping: A workflow based on cheap hardware and free software

NASA Astrophysics Data System (ADS)

Vrabec, Marko; Dolžan, Erazem

2016-04-01

The undergraduate field course in Geological Mapping at the University of Ljubljana involves 20-40 students per year, which precludes the use of specialized rugged digital field equipment as the costs would be way beyond the capabilities of the Department. A different mapping area is selected each year with the aim to provide typical conditions that a professional geologist might encounter when doing fieldwork in Slovenia, which includes rugged relief, dense tree cover, and moderately-well- to poorly-exposed bedrock due to vegetation and urbanization. It is therefore mandatory that the digital tools and workflows are combined with classical methods of fieldwork, since, for example, full-time precise GNSS positioning is not viable under such circumstances. Additionally, due to the prevailing combination of complex geological structure with generally poor exposure, students cannot be expected to produce line (vector) maps of geological contacts on the go, so there is no need for such functionality in hardware and software that we use in the field. Our workflow therefore still relies on paper base maps, but is strongly complemented with digital tools to provide robust positioning, track recording, and acquisition of various point-based data. Primary field hardware are students' Android-based smartphones and optionally tablets. For our purposes, the built-in GNSS chips provide adequate positioning precision most of the time, particularly if they are GLONASS-capable. We use Oruxmaps, a powerful free offline map viewer for the Android platform, which facilitates the use of custom-made geopositioned maps. For digital base maps, which we prepare in free Windows QGIS software, we use scanned topographic maps provided by the National Geodetic Authority, but also other maps such as aerial imagery, processed Digital Elevation Models, scans of existing geological maps, etc. Point data, like important outcrop locations or structural measurements, are entered into Oruxmaps as waypoints. Students are also encouraged to directly measure structural data with specialized Android apps such as the MVE FieldMove Clino. Digital field data is exported from Oruxmaps to Windows computers primarily in the ubiquitous GPX data format and then integrated in the QGIS environment. Recorded GPX tracks are also used with the free Geosetter Windows software to geoposition and tag any digital photographs taken in the field. With minimal expenses, our workflow provides the students with basic familiarity and experience in using digital field tools and methods. The workflow is also practical enough for the prevailing field conditions of Slovenia that the faculty staff is using it in geological mapping for scientific research and consultancy work.

Combination of atomic force microscopy and mass spectrometry for the detection of target protein in the serum samples of children with autism spectrum disorders

NASA Astrophysics Data System (ADS)

Kaysheva, A. L.; Pleshakova, T. O.; Kopylov, A. T.; Shumov, I. D.; Iourov, I. Y.; Vorsanova, S. G.; Yurov, Y. B.; Ziborov, V. S.; Archakov, A. I.; Ivanov, Y. D.

2017-10-01

Possibility of detection of target proteins associated with development of autistic disorders in children with use of combined atomic force microscopy and mass spectrometry (AFM/MS) method is demonstrated. The proposed method is based on the combination of affine enrichment of proteins from biological samples and visualization of these proteins by AFM and MS analysis with quantitative detection of target proteins.

Exploring the impact of an automated prescription-filling device on community pharmacy technician workflow.

PubMed

Walsh, Kristin E; Chui, Michelle Anne; Kieser, Mara A; Williams, Staci M; Sutter, Susan L; Sutter, John G

2011-01-01

To explore community pharmacy technician workflow change after implementation of an automated robotic prescription-filling device. At an independent community pharmacy in rural Mayville, WI, pharmacy technicians were observed before and 3 months after installation of an automated robotic prescription-filling device. The main outcome measures were sequences and timing of technician workflow steps, workflow interruptions, automation surprises, and workarounds. Of the 77 and 80 observations made before and 3 months after robot installation, respectively, 17 different workflow sequences were observed before installation and 38 after installation. Average prescription filling time was reduced by 40 seconds per prescription with use of the robot. Workflow interruptions per observation increased from 1.49 to 1.79 (P = 0.11), and workarounds increased from 10% to 36% after robot use. Although automated prescription-filling devices can increase efficiency, workflow interruptions and workarounds may negate that efficiency. Assessing changes in workflow and sequencing of tasks that may result from the use of automation can help uncover opportunities for workflow policy and procedure redesign.

JTSA: an open source framework for time series abstractions.

PubMed

Sacchi, Lucia; Capozzi, Davide; Bellazzi, Riccardo; Larizza, Cristiana

2015-10-01

The evaluation of the clinical status of a patient is frequently based on the temporal evolution of some parameters, making the detection of temporal patterns a priority in data analysis. Temporal abstraction (TA) is a methodology widely used in medical reasoning for summarizing and abstracting longitudinal data. This paper describes JTSA (Java Time Series Abstractor), a framework including a library of algorithms for time series preprocessing and abstraction and an engine to execute a workflow for temporal data processing. The JTSA framework is grounded on a comprehensive ontology that models temporal data processing both from the data storage and the abstraction computation perspective. The JTSA framework is designed to allow users to build their own analysis workflows by combining different algorithms. Thanks to the modular structure of a workflow, simple to highly complex patterns can be detected. The JTSA framework has been developed in Java 1.7 and is distributed under GPL as a jar file. JTSA provides: a collection of algorithms to perform temporal abstraction and preprocessing of time series, a framework for defining and executing data analysis workflows based on these algorithms, and a GUI for workflow prototyping and testing. The whole JTSA project relies on a formal model of the data types and of the algorithms included in the library. This model is the basis for the design and implementation of the software application. Taking into account this formalized structure, the user can easily extend the JTSA framework by adding new algorithms. Results are shown in the context of the EU project MOSAIC to extract relevant patterns from data coming related to the long term monitoring of diabetic patients. The proof that JTSA is a versatile tool to be adapted to different needs is given by its possible uses, both as a standalone tool for data summarization and as a module to be embedded into other architectures to select specific phenotypes based on TAs in a large dataset. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Facilitating hydrological data analysis workflows in R: the RHydro package

NASA Astrophysics Data System (ADS)

Buytaert, Wouter; Moulds, Simon; Skoien, Jon; Pebesma, Edzer; Reusser, Dominik

2015-04-01

The advent of new technologies such as web-services and big data analytics holds great promise for hydrological data analysis and simulation. Driven by the need for better water management tools, it allows for the construction of much more complex workflows, that integrate more and potentially more heterogeneous data sources with longer tool chains of algorithms and models. With the scientific challenge of designing the most adequate processing workflow comes the technical challenge of implementing the workflow with a minimal risk for errors. A wide variety of new workbench technologies and other data handling systems are being developed. At the same time, the functionality of available data processing languages such as R and Python is increasing at an accelerating pace. Because of the large diversity of scientific questions and simulation needs in hydrology, it is unlikely that one single optimal method for constructing hydrological data analysis workflows will emerge. Nevertheless, languages such as R and Python are quickly gaining popularity because they combine a wide array of functionality with high flexibility and versatility. The object-oriented nature of high-level data processing languages makes them particularly suited for the handling of complex and potentially large datasets. In this paper, we explore how handling and processing of hydrological data in R can be facilitated further by designing and implementing a set of relevant classes and methods in the experimental R package RHydro. We build upon existing efforts such as the sp and raster packages for spatial data and the spacetime package for spatiotemporal data to define classes for hydrological data (HydroST). In order to handle simulation data from hydrological models conveniently, a HM class is defined. Relevant methods are implemented to allow for an optimal integration of the HM class with existing model fitting and simulation functionality in R. Lastly, we discuss some of the design challenges of the RHydro package, including integration with big data technologies, web technologies, and emerging data models in hydrology.

Introducing W.A.T.E.R.S.: a workflow for the alignment, taxonomy, and ecology of ribosomal sequences.

PubMed

Hartman, Amber L; Riddle, Sean; McPhillips, Timothy; Ludäscher, Bertram; Eisen, Jonathan A

2010-06-12

For more than two decades microbiologists have used a highly conserved microbial gene as a phylogenetic marker for bacteria and archaea. The small-subunit ribosomal RNA gene, also known as 16 S rRNA, is encoded by ribosomal DNA, 16 S rDNA, and has provided a powerful comparative tool to microbial ecologists. Over time, the microbial ecology field has matured from small-scale studies in a select number of environments to massive collections of sequence data that are paired with dozens of corresponding collection variables. As the complexity of data and tool sets have grown, the need for flexible automation and maintenance of the core processes of 16 S rDNA sequence analysis has increased correspondingly. We present WATERS, an integrated approach for 16 S rDNA analysis that bundles a suite of publicly available 16 S rDNA analysis software tools into a single software package. The "toolkit" includes sequence alignment, chimera removal, OTU determination, taxonomy assignment, phylogentic tree construction as well as a host of ecological analysis and visualization tools. WATERS employs a flexible, collection-oriented 'workflow' approach using the open-source Kepler system as a platform. By packaging available software tools into a single automated workflow, WATERS simplifies 16 S rDNA analyses, especially for those without specialized bioinformatics, programming expertise. In addition, WATERS, like some of the newer comprehensive rRNA analysis tools, allows researchers to minimize the time dedicated to carrying out tedious informatics steps and to focus their attention instead on the biological interpretation of the results. One advantage of WATERS over other comprehensive tools is that the use of the Kepler workflow system facilitates result interpretation and reproducibility via a data provenance sub-system. Furthermore, new "actors" can be added to the workflow as desired and we see WATERS as an initial seed for a sizeable and growing repository of interoperable, easy-to-combine tools for asking increasingly complex microbial ecology questions.

Generic worklist handler for workflow-enabled products

NASA Astrophysics Data System (ADS)

Schmidt, Joachim; Meetz, Kirsten; Wendler, Thomas

1999-07-01

Workflow management (WfM) is an emerging field of medical information technology. It appears as a promising key technology to model, optimize and automate processes, for the sake of improved efficiency, reduced costs and improved patient care. The Application of WfM concepts requires the standardization of architectures and interfaces. A component of central interest proposed in this report is a generic work list handler: A standardized interface between a workflow enactment service and application system. Application systems with embedded work list handlers will be called 'Workflow Enabled Application Systems'. In this paper we discus functional requirements of work list handlers, as well as their integration into workflow architectures and interfaces. To lay the foundation for this specification, basic workflow terminology, the fundamentals of workflow management and - later in the paper - the available standards as defined by the Workflow Management Coalition are briefly reviewed.

Workflow with pitfalls to derive a regional airborne magnetic compilation

NASA Astrophysics Data System (ADS)

Brönner, Marco; Baykiev, Eldar; Ebbing, Jörg

2017-04-01

Today, large scale magnetic maps are usually a patchwork of different airborne surveys from different size, different resolution and different years. Airborne magnetic acquisition is a fast and economic method to map and gain geological and tectonic information for large areas, onshore and offshore. Depending on the aim of a survey, acquisition parameters like altitude and profile distance are usually adjusted to match the purpose of investigation. The subsequent data processing commonly follows a standardized workflow comprising core-field subtraction and line leveling to yield a coherent crustal field magnetic grid for a survey area. The resulting data makes it possible to correlate with geological and tectonic features in the subsurface, which is of importance for e.g. oil and mineral exploration. Crustal scale magnetic interpretation and modeling demand regional compilation of magnetic data and the merger of adjacent magnetic surveys. These studies not only focus on shallower sources, reflected by short to intermediate magnetic wavelength anomalies, but also have a particular interest in the long wavelength deriving from deep seated sources. However, whilst the workflow to produce such a merger is supported by quite a few powerful routines, the resulting compilation contains several pitfalls and limitations, which were discussed before, but still are very little recognized. The maximum wavelength that can be resolved of each individual survey is directly related to the survey size and consequently a merger will contribute erroneous long-wavelength components in the magnetic data compilation. To minimize this problem and to homogenous the longer wavelengths, a first order approach is the combination of airborne and satellite magnetic data commonly combined with the compilation from airborne data, which is sufficient only under particular preconditions. A more advanced approach considers the gap in frequencies between airborne and satellite data, which motivated countries like Sweden and Australia (AWAGS) to collect high altitude- long distance airborne magnetic data for the entire country to homogenous the high-resolution magnetic data before the merger with satellite data. We present the compilation of a regional magnetic map for an area in northern Europe and discuss the problems and pitfalls for a common workflow applied.

Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms.

PubMed

Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

2014-01-01

With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies.

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

DOE PAGES

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi; ...

2016-07-21

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

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

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Optimization by infusion of multiple reaction monitoring transitions for sensitive quantification of peptides by liquid chromatography/mass spectrometry.

PubMed

Alghanem, Bandar; Nikitin, Frédéric; Stricker, Thomas; Duchoslav, Eva; Luban, Jeremy; Strambio-De-Castillia, Caterina; Muller, Markus; Lisacek, Frédérique; Varesio, Emmanuel; Hopfgartner, Gérard

2017-05-15

In peptide quantification by liquid chromatography/mass spectrometry (LC/MS), the optimization of multiple reaction monitoring (MRM) parameters is essential for sensitive detection. We have compared different approaches to build MRM assays, based either on flow injection analysis (FIA) of isotopically labelled peptides, or on the knowledge and the prediction of the best settings for MRM transitions and collision energies (CE). In this context, we introduce MRMOptimizer, an open-source software tool that processes spectra and assists the user in selecting transitions in the FIA workflow. MS/MS spectral libraries with CE voltages from 10 to 70 V are automatically acquired in FIA mode for isotopically labelled peptides. Then MRMOptimizer determines the optimal MRM settings for each peptide. To assess the quantitative performance of our approach, 155 peptides, representing 84 proteins, were analysed by LC/MRM-MS and the peak areas were compared between: (A) the MRMOptimizer-based workflow, (B1) the SRMAtlas transitions set used 'as-is'; (B2) the same SRMAtlas set with CE parameters optimized by Skyline. 51% of the three most intense transitions per peptide were shown to be common to both A and B1/B2 methods, and displayed similar sensitivity and peak area distributions. The peak areas obtained with MRMOptimizer for transitions sharing either the precursor ion charge state or the fragment ions with the SRMAtlas set at unique transitions were increased 1.8- to 2.3-fold. The gain in sensitivity using MRMOptimizer for transitions with different precursor ion charge state and fragment ions (8% of the total), reaches a ~ 11-fold increase. Isotopically labelled peptides can be used to optimize MRM transitions more efficiently in FIA than by searching databases. The MRMOptimizer software is MS independent and enables the post-acquisition selection of MRM parameters. Coefficients of variation for optimal CE values are lower than those obtained with the SRMAtlas approach (B2) and one additional peptide was detected. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments.

PubMed

Allmer, Jens; Kuhlgert, Sebastian; Hippler, Michael

2008-07-07

The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed. In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application. We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage.

Development of isotope labeling liquid chromatography mass spectrometry for mouse urine metabolomics: quantitative metabolomic study of transgenic mice related to Alzheimer's disease.

PubMed

Peng, Jun; Guo, Kevin; Xia, Jianguo; Zhou, Jianjun; Yang, Jing; Westaway, David; Wishart, David S; Li, Liang

2014-10-03

Because of a limited volume of urine that can be collected from a mouse, it is very difficult to apply the common strategy of using multiple analytical techniques to analyze the metabolites to increase the metabolome coverage for mouse urine metabolomics. We report an enabling method based on differential isotope labeling liquid chromatography mass spectrometry (LC-MS) for relative quantification of over 950 putative metabolites using 20 μL of urine as the starting material. The workflow involves aliquoting 10 μL of an individual urine sample for ¹²C-dansylation labeling that target amines and phenols. Another 10 μL of aliquot was taken from each sample to generate a pooled sample that was subjected to ¹³C-dansylation labeling. The ¹²C-labeled individual sample was mixed with an equal volume of the ¹³C-labeled pooled sample. The mixture was then analyzed by LC-MS to generate information on metabolite concentration differences among different individual samples. The interday repeatability for the LC-MS runs was assessed, and the median relative standard deviation over 4 days was 5.0%. This workflow was then applied to a metabolomic biomarker discovery study using urine samples obtained from the TgCRND8 mouse model of early onset familial Alzheimer's disease (FAD) throughout the course of their pathological deposition of beta amyloid (Aβ). It was showed that there was a distinct metabolomic separation between the AD prone mice and the wild type (control) group. As early as 15-17 weeks of age (presymptomatic), metabolomic differences were observed between the two groups, and after the age of 25 weeks the metabolomic alterations became more pronounced. The metabolomic changes at different ages corroborated well with the phenotype changes in this transgenic mice model. Several useful candidate biomarkers including methionine, desaminotyrosine, taurine, N1-acetylspermidine, and 5-hydroxyindoleacetic acid were identified. Some of them were found in previous metabolomics studies in human cerebrospinal fluid or blood samples. This work illustrates the utility of this isotope labeling LC-MS method for biomarker discovery using mouse urine metabolomics.

Standardizing clinical trials workflow representation in UML for international site comparison.

PubMed

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M O; Rodrigues, Maria J; Shah, Jatin; Loures, Marco R; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-11-09

With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.

Standardizing Clinical Trials Workflow Representation in UML for International Site Comparison

PubMed Central

de Carvalho, Elias Cesar Araujo; Jayanti, Madhav Kishore; Batilana, Adelia Portero; Kozan, Andreia M. O.; Rodrigues, Maria J.; Shah, Jatin; Loures, Marco R.; Patil, Sunita; Payne, Philip; Pietrobon, Ricardo

2010-01-01

Background With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. Methods Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. Results Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. Conclusions This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows. PMID:21085484

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Xing, Z.; Fetzer, E.

2008-12-01

NASA's Earth Observing System (EOS) is the world's most ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the A-Train platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the cloud scenes from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time matchups between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, and assemble merged datasets for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, and perform pairwise instrument matchups for A-Train datasets. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Xing, Z.; Fetzer, E.

2009-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, perform pairwise instrument matchups for A-Train datasets, and compute fused products. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Visualisation methods for large provenance collections in data-intensive collaborative platforms

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Fligueira, Rosa; Atkinson, Malcolm; Gemuend, Andre

2016-04-01

This work investigates improving the methods of visually representing provenance information in the context of modern data-driven scientific research. It explores scenarios where data-intensive workflows systems are serving communities of researchers within collaborative environments, supporting the sharing of data and methods, and offering a variety of computation facilities, including HPC, HTC and Cloud. It focuses on the exploration of big-data visualization techniques aiming at producing comprehensive and interactive views on top of large and heterogeneous provenance data. The same approach is applicable to control-flow and data-flow workflows or to combinations of the two. This flexibility is achieved using the W3C-PROV recommendation as a reference model, especially its workflow oriented profiles such as D-PROV (Messier et al. 2013). Our implementation is based on the provenance records produced by the dispel4py data-intensive processing library (Filgueira et al. 2015). dispel4py is an open-source Python framework for describing abstract stream-based workflows for distributed data-intensive applications, developed during the VERCE project. dispel4py enables scientists to develop their scientific methods and applications on their laptop and then run them at scale on a wide range of e-Infrastructures (Cloud, Cluster, etc.) without making changes. Users can therefore focus on designing their workflows at an abstract level, describing actions, input and output streams, and how they are connected. The dispel4py system then maps these descriptions to the enactment platforms, such as MPI, Storm, multiprocessing. It provides a mechanism which allows users to determine the provenance information to be collected and to analyze it at runtime. For this work we consider alternative visualisation methods for provenance data, from infinite lists and localised interactive graphs, to radial-views. The latter technique has been positively explored in many fields, from text data visualisation to genomics and social networking analysis. Its adoption for provenance has been presented in literature (Borkin et al. 2013) in the context of parent-child relationships across processes, constructed from control-flow information. Computer graphics research has focused on the advantage of this radial distribution of interlinked information and on ways to improve the visual efficiency and tunability of such representations, like the Hierarchical Edge Bundles visualisation method, (Holten et al. 2006), which aims at reducing visual clutter of highly connected structures via the generation of bundles. Our approach explores the potential of the combination of these methods. It serves environments where the size of the provenance collection, coupled with the diversity of the infrastructures and the domain metadata, make the extrapolation of usage trends extremely challenging. Applications of such visualisation systems can engage groups of scientists, data providers and computational engineers, by serving visual snapshots that highlight relationships between an item and its connected processes. We will present examples of comprehensive views on the distribution of processing and data transfers during a workflow's execution in HPC, as well as cross workflows interactions and internal dynamics. The latter in the context of faceted searches on domain metadata values-range. These are obtained from the analysis of real provenance data generated by the processing of seismic traces performed through the VERCE platform.

Workflow and maintenance characteristics of five automated laboratory instruments for the diagnosis of sexually transmitted infections.

PubMed

Ratnam, Sam; Jang, Dan; Gilchrist, Jodi; Smieja, Marek; Poirier, Andre; Hatchette, Todd; Flandin, Jean-Frederic; Chernesky, Max

2014-07-01

The choice of a suitable automated system for a diagnostic laboratory depends on various factors. Comparative workflow studies provide quantifiable and objective metrics to determine hands-on time during specimen handling and processing, reagent preparation, return visits and maintenance, and test turnaround time and throughput. Using objective time study techniques, workflow characteristics for processing 96 and 192 tests were determined on m2000 RealTime (Abbott Molecular), Viper XTR (Becton Dickinson), cobas 4800 (Roche Molecular Diagnostics), Tigris (Hologic Gen-Probe), and Panther (Hologic Gen-Probe) platforms using second-generation assays for Chlamydia trachomatis and Neisseria gonorrhoeae. A combination of operational and maintenance steps requiring manual labor showed that Panther had the shortest overall hands-on times and Viper XTR the longest. Both Panther and Tigris showed greater efficiency whether 96 or 192 tests were processed. Viper XTR and Panther had the shortest times to results and m2000 RealTime the longest. Sample preparation and loading time was the shortest for Panther and longest for cobas 4800. Mandatory return visits were required only for m2000 RealTime and cobas 4800 when 96 tests were processed, and both required substantially more hands-on time than the other systems due to increased numbers of return visits when 192 tests were processed. These results show that there are substantial differences in the amount of labor required to operate each system. Assay performance, instrumentation, testing capacity, workflow, maintenance, and reagent costs should be considered in choosing a system. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

FY 1992-1993 RDT&E Descriptive Summaries: DARPA

DTIC Science & Technology

1991-02-01

combining natural language and user workflow model information. * Determine effectiveness of auditory models as preprocessors for robust speech...for indexing and retrieving design knowledge. * Evaluate ability of message understanding systems to extract crisis -situation data from news wires...energy effects , underwater vehicles, neutrino detection, speech, tailored nuclear weapons, hypervelocity, nanosecond timing, and MAD/RPV. FY 1991 Planned

Quantitative workflow based on NN for weighting criteria in landfill suitability mapping

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Alkhasawneh, Mutasem Sh.; Aziz, Hamidi Abdul

2017-10-01

Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.

Topographical and Chemical Imaging of a Phase Separated Polymer Using a Combined Atomic Force Microscopy/Infrared Spectroscopy/Mass Spectrometry Platform

DOE PAGES

Tai, Tamin; Karácsony, Orsolya; Bocharova, Vera; ...

2016-02-18

This article describes how the use of a hybrid atomic force microscopy/infrared spectroscopy/mass spectrometry imaging platform was demonstrated for the acquisition and correlation of nanoscale sample surface topography and chemical images based on infrared spectroscopy and mass spectrometry.

Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms

PubMed Central

Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

2017-01-01

With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies. PMID:29399237

Scientific Data Management (SDM) Center for Enabling Technologies. Final Report, 2007-2012

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

Ludascher, Bertram; Altintas, Ilkay

Our contributions to advancing the State of the Art in scientific workflows have focused on the following areas: Workflow development; Generic workflow components and templates; Provenance collection and analysis; and, Workflow reliability and fault tolerance.

Exploring the impact of an automated prescription-filling device on community pharmacy technician workflow

PubMed Central

Walsh, Kristin E.; Chui, Michelle Anne; Kieser, Mara A.; Williams, Staci M.; Sutter, Susan L.; Sutter, John G.

2012-01-01

Objective To explore community pharmacy technician workflow change after implementation of an automated robotic prescription-filling device. Methods At an independent community pharmacy in rural Mayville, WI, pharmacy technicians were observed before and 3 months after installation of an automated robotic prescription-filling device. The main outcome measures were sequences and timing of technician workflow steps, workflow interruptions, automation surprises, and workarounds. Results Of the 77 and 80 observations made before and 3 months after robot installation, respectively, 17 different workflow sequences were observed before installation and 38 after installation. Average prescription filling time was reduced by 40 seconds per prescription with use of the robot. Workflow interruptions per observation increased from 1.49 to 1.79 (P = 0.11), and workarounds increased from 10% to 36% after robot use. Conclusion Although automated prescription-filling devices can increase efficiency, workflow interruptions and workarounds may negate that efficiency. Assessing changes in workflow and sequencing of tasks that may result from the use of automation can help uncover opportunities for workflow policy and procedure redesign. PMID:21896459

Model Checking for Verification of Interactive Health IT Systems

PubMed Central

Butler, Keith A.; Mercer, Eric; Bahrami, Ali; Tao, Cui

2015-01-01

Rigorous methods for design and verification of health IT systems have lagged far behind their proliferation. The inherent technical complexity of healthcare, combined with the added complexity of health information technology makes their resulting behavior unpredictable and introduces serious risk. We propose to mitigate this risk by formalizing the relationship between HIT and the conceptual work that increasingly typifies modern care. We introduce new techniques for modeling clinical workflows and the conceptual products within them that allow established, powerful modeling checking technology to be applied to interactive health IT systems. The new capability can evaluate the workflows of a new HIT system performed by clinicians and computers to improve safety and reliability. We demonstrate the method on a patient contact system to demonstrate model checking is effective for interactive systems and that much of it can be automated. PMID:26958166

Progress in digital color workflow understanding in the International Color Consortium (ICC) Workflow WG

NASA Astrophysics Data System (ADS)

McCarthy, Ann

2006-01-01

The ICC Workflow WG serves as the bridge between ICC color management technologies and use of those technologies in real world color production applications. ICC color management is applicable to and is used in a wide range of color systems, from highly specialized digital cinema color special effects to high volume publications printing to home photography. The ICC Workflow WG works to align ICC technologies so that the color management needs of these diverse use case systems are addressed in an open, platform independent manner. This report provides a high level summary of the ICC Workflow WG objectives and work to date, focusing on the ways in which workflow can impact image quality and color systems performance. The 'ICC Workflow Primitives' and 'ICC Workflow Patterns and Dimensions' workflow models are covered in some detail. Consider the questions, "How much of dissatisfaction with color management today is the result of 'the wrong color transformation at the wrong time' and 'I can't get to the right conversion at the right point in my work process'?" Put another way, consider how image quality through a workflow can be negatively affected when the coordination and control level of the color management system is not sufficient.

On-line capillary electrophoresis/laser-induced fluorescence/mass spectrometry analysis of glycans labeled with Teal™ fluorescent dye using an electrokinetic sheath liquid pump-based nanospray ion source.

PubMed

Khan, Shaheer; Liu, Jenkuei; Szabo, Zoltan; Kunnummal, Baburaj; Han, Xiaorui; Ouyang, Yilan; Linhardt, Robert J; Xia, Qiangwei

2018-06-15

N-linked glycan analysis of recombinant therapeutic proteins, such as monoclonal antibodies, Fc-fusion proteins, and antibody-drug conjugates, provides valuable information regarding protein therapeutics glycosylation profile. Both qualitative identification and quantitative analysis of N-linked glycans on recombinant therapeutic proteins are critical analytical tasks in the biopharma industry during the development of a biotherapeutic. Currently, such analyses are mainly carried out using capillary electrophoresis/laser-induced fluorescence (CE/LIF), liquid chromatography/fluorescence (LC/FLR), and liquid chromatography/fluorescence/mass spectrometry (LC/FLR/MS) technologies. N-linked glycans are first released from glycoproteins by enzymatic digestion, then labeled with fluorescence dyes for subsequent CE or LC separation, and LIF or MS detection. Here we present an on-line CE/LIF/MS N-glycan analysis workflow that incorporates the fluorescent Teal™ dye and an electrokinetic pump-based nanospray sheath liquid capillary electrophoresis/mass spectrometry (CE/MS) ion source. Electrophoresis running buffer systems using ammonium acetate and ammonium hydroxide were developed for the negative ion mode CE/MS analysis of fluorescence-labeled N-linked glycans. Results show that on-line CE/LIF/MS analysis can be readily achieved using this versatile CE/MS ion source on common CE/MS instrument platforms. This on-line CE/LIF/MS method using Teal™ fluorescent dye and electrokinetic pump-based nanospray sheath liquid CE/MS coupling technology holds promise for on-line quantitation and identification of N-linked glycans on recombinant therapeutic proteins. Copyright © 2018 John Wiley & Sons, Ltd.

Protein biomarker discovery and fast monitoring for the identification and detection of Anisakids by parallel reaction monitoring (PRM) mass spectrometry.

PubMed

Carrera, Mónica; Gallardo, José M; Pascual, Santiago; González, Ángel F; Medina, Isabel

2016-06-16

Anisakids are fish-borne parasites that are responsible for a large number of human infections and allergic reactions around the world. World health organizations and food safety authorities aim to control and prevent this emerging health problem. In the present work, a new method for the fast monitoring of these parasites is described. The strategy is divided in three steps: (i) purification of thermostable proteins from fish-borne parasites (Anisakids), (ii) in-solution HIFU trypsin digestion and (iii) monitoring of several peptide markers by parallel reaction monitoring (PRM) mass spectrometry. This methodology allows the fast detection of Anisakids in <2h. An affordable assay utilizing this methodology will facilitate testing for regulatory and safety applications. The work describes for the first time, the Protein Biomarker Discovery and the Fast Monitoring for the identification and detection of Anisakids in fishery products. The strategy is based on the purification of thermostable proteins, the use of accelerated in-solution trypsin digestions under an ultrasonic field provided by High-Intensity Focused Ultrasound (HIFU) and the monitoring of several peptide biomarkers by Parallel Reaction Monitoring (PRM) Mass Spectrometry in a linear ion trap mass spectrometer. The workflow allows the unequivocal detection of Anisakids, in <2h. The present strategy constitutes the fastest method for Anisakids detection, whose application in the food quality control area, could provide to the authorities an effective and rapid method to guarantee the safety to the consumers. Copyright © 2016 Elsevier B.V. All rights reserved.

Automated Transition State Search and Its Application to Diverse Types of Organic Reactions.

PubMed

Jacobson, Leif D; Bochevarov, Art D; Watson, Mark A; Hughes, Thomas F; Rinaldo, David; Ehrlich, Stephan; Steinbrecher, Thomas B; Vaitheeswaran, S; Philipp, Dean M; Halls, Mathew D; Friesner, Richard A

2017-11-14

Transition state search is at the center of multiple types of computational chemical predictions related to mechanistic investigations, reactivity and regioselectivity predictions, and catalyst design. The process of finding transition states in practice is, however, a laborious multistep operation that requires significant user involvement. Here, we report a highly automated workflow designed to locate transition states for a given elementary reaction with minimal setup overhead. The only essential inputs required from the user are the structures of the separated reactants and products. The seamless workflow combining computational technologies from the fields of cheminformatics, molecular mechanics, and quantum chemistry automatically finds the most probable correspondence between the atoms in the reactants and the products, generates a transition state guess, launches a transition state search through a combined approach involving the relaxing string method and the quadratic synchronous transit, and finally validates the transition state via the analysis of the reactive chemical bonds and imaginary vibrational frequencies as well as by the intrinsic reaction coordinate method. Our approach does not target any specific reaction type, nor does it depend on training data; instead, it is meant to be of general applicability for a wide variety of reaction types. The workflow is highly flexible, permitting modifications such as a choice of accuracy, level of theory, basis set, or solvation treatment. Successfully located transition states can be used for setting up transition state guesses in related reactions, saving computational time and increasing the probability of success. The utility and performance of the method are demonstrated in applications to transition state searches in reactions typical for organic chemistry, medicinal chemistry, and homogeneous catalysis research. In particular, applications of our code to Michael additions, hydrogen abstractions, Diels-Alder cycloadditions, carbene insertions, and an enzyme reaction model involving a molybdenum complex are shown and discussed.

Epiviz: a view inside the design of an integrated visual analysis software for genomics

PubMed Central

2015-01-01

Background Computational and visual data analysis for genomics has traditionally involved a combination of tools and resources, of which the most ubiquitous consist of genome browsers, focused mainly on integrative visualization of large numbers of big datasets, and computational environments, focused on data modeling of a small number of moderately sized datasets. Workflows that involve the integration and exploration of multiple heterogeneous data sources, small and large, public and user specific have been poorly addressed by these tools. In our previous work, we introduced Epiviz, which bridges the gap between the two types of tools, simplifying these workflows. Results In this paper we expand on the design decisions behind Epiviz, and introduce a series of new advanced features that further support the type of interactive exploratory workflow we have targeted. We discuss three ways in which Epiviz advances the field of genomic data analysis: 1) it brings code to interactive visualizations at various different levels; 2) takes the first steps in the direction of collaborative data analysis by incorporating user plugins from source control providers, as well as by allowing analysis states to be shared among the scientific community; 3) combines established analysis features that have never before been available simultaneously in a genome browser. In our discussion section, we present security implications of the current design, as well as a series of limitations and future research steps. Conclusions Since many of the design choices of Epiviz are novel in genomics data analysis, this paper serves both as a document of our own approaches with lessons learned, as well as a start point for future efforts in the same direction for the genomics community. PMID:26328750

Radiology information system: a workflow-based approach.

PubMed

Zhang, Jinyan; Lu, Xudong; Nie, Hongchao; Huang, Zhengxing; van der Aalst, W M P

2009-09-01

Introducing workflow management technology in healthcare seems to be prospective in dealing with the problem that the current healthcare Information Systems cannot provide sufficient support for the process management, although several challenges still exist. The purpose of this paper is to study the method of developing workflow-based information system in radiology department as a use case. First, a workflow model of typical radiology process was established. Second, based on the model, the system could be designed and implemented as a group of loosely coupled components. Each component corresponded to one task in the process and could be assembled by the workflow management system. The legacy systems could be taken as special components, which also corresponded to the tasks and were integrated through transferring non-work- flow-aware interfaces to the standard ones. Finally, a workflow dashboard was designed and implemented to provide an integral view of radiology processes. The workflow-based Radiology Information System was deployed in the radiology department of Zhejiang Chinese Medicine Hospital in China. The results showed that it could be adjusted flexibly in response to the needs of changing process, and enhance the process management in the department. It can also provide a more workflow-aware integration method, comparing with other methods such as IHE-based ones. The workflow-based approach is a new method of developing radiology information system with more flexibility, more functionalities of process management and more workflow-aware integration. The work of this paper is an initial endeavor for introducing workflow management technology in healthcare.

Information Issues and Contexts that Impair Team Based Communication Workflow: A Palliative Sedation Case Study.

PubMed

Cornett, Alex; Kuziemsky, Craig

2015-01-01

Implementing team based workflows can be complex because of the scope of providers involved and the extent of information exchange and communication that needs to occur. While a workflow may represent the ideal structure of communication that needs to occur, information issues and contextual factors may impact how the workflow is implemented in practice. Understanding these issues will help us better design systems to support team based workflows. In this paper we use a case study of palliative sedation therapy (PST) to model a PST workflow and then use it to identify purposes of communication, information issues and contextual factors that impact them. We then suggest how our findings could inform health information technology (HIT) design to support team based communication workflows.

A Workflow to Improve the Alignment of Prostate Imaging with Whole-mount Histopathology.

PubMed

Yamamoto, Hidekazu; Nir, Dror; Vyas, Lona; Chang, Richard T; Popert, Rick; Cahill, Declan; Challacombe, Ben; Dasgupta, Prokar; Chandra, Ashish

2014-08-01

Evaluation of prostate imaging tests against whole-mount histology specimens requires accurate alignment between radiologic and histologic data sets. Misalignment results in false-positive and -negative zones as assessed by imaging. We describe a workflow for three-dimensional alignment of prostate imaging data against whole-mount prostatectomy reference specimens and assess its performance against a standard workflow. Ethical approval was granted. Patients underwent motorized transrectal ultrasound (Prostate Histoscanning) to generate a three-dimensional image of the prostate before radical prostatectomy. The test workflow incorporated steps for axial alignment between imaging and histology, size adjustments following formalin fixation, and use of custom-made parallel cutters and digital caliper instruments. The control workflow comprised freehand cutting and assumed homogeneous block thicknesses at the same relative angles between pathology and imaging sections. Thirty radical prostatectomy specimens were histologically and radiologically processed, either by an alignment-optimized workflow (n = 20) or a control workflow (n = 10). The optimized workflow generated tissue blocks of heterogeneous thicknesses but with no significant drifting in the cutting plane. The control workflow resulted in significantly nonparallel blocks, accurately matching only one out of four histology blocks to their respective imaging data. The image-to-histology alignment accuracy was 20% greater in the optimized workflow (P < .0001), with higher sensitivity (85% vs. 69%) and specificity (94% vs. 73%) for margin prediction in a 5 × 5-mm grid analysis. A significantly better alignment was observed in the optimized workflow. Evaluation of prostate imaging biomarkers using whole-mount histology references should include a test-to-reference spatial alignment workflow. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Conceptual-level workflow modeling of scientific experiments using NMR as a case study

PubMed Central

Verdi, Kacy K; Ellis, Heidi JC; Gryk, Michael R

2007-01-01

Background Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. Results We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Conclusion Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment. PMID:17263870

FAST: A fully asynchronous and status-tracking pattern for geoprocessing services orchestration

NASA Astrophysics Data System (ADS)

Wu, Huayi; You, Lan; Gui, Zhipeng; Gao, Shuang; Li, Zhenqiang; Yu, Jingmin

2014-09-01

Geoprocessing service orchestration (GSO) provides a unified and flexible way to implement cross-application, long-lived, and multi-step geoprocessing service workflows by coordinating geoprocessing services collaboratively. Usually, geoprocessing services and geoprocessing service workflows are data and/or computing intensive. The intensity feature may make the execution process of a workflow time-consuming. Since it initials an execution request without blocking other interactions on the client side, an asynchronous mechanism is especially appropriate for GSO workflows. Many critical problems remain to be solved in existing asynchronous patterns for GSO including difficulties in improving performance, status tracking, and clarifying the workflow structure. These problems are a challenge when orchestrating performance efficiency, making statuses instantly available, and constructing clearly structured GSO workflows. A Fully Asynchronous and Status-Tracking (FAST) pattern that adopts asynchronous interactions throughout the whole communication tier of a workflow is proposed for GSO. The proposed FAST pattern includes a mechanism that actively pushes the latest status to clients instantly and economically. An independent proxy was designed to isolate the status tracking logic from the geoprocessing business logic, which assists the formation of a clear GSO workflow structure. A workflow was implemented in the FAST pattern to simulate the flooding process in the Poyang Lake region. Experimental results show that the proposed FAST pattern can efficiently tackle data/computing intensive geoprocessing tasks. The performance of all collaborative partners was improved due to the asynchronous mechanism throughout communication tier. A status-tracking mechanism helps users retrieve the latest running status of a GSO workflow in an efficient and instant way. The clear structure of the GSO workflow lowers the barriers for geospatial domain experts and model designers to compose asynchronous GSO workflows. Most importantly, it provides better support for locating and diagnosing potential exceptions.

Conceptual-level workflow modeling of scientific experiments using NMR as a case study.

PubMed

Verdi, Kacy K; Ellis, Heidi Jc; Gryk, Michael R

2007-01-30

Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process. Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration. We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment.

Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma.

PubMed

O'Grady, John P; Meyer, Kevin W; Poe, Derrick N

2017-01-01

The improving efficacy of many biological therapeutics and identification of low-level biomarkers are driving the analytical proteomics community to deal with extremely high levels of sample complexity relative to their analytes. Many protein quantitation and biomarker validation procedures utilize an immunoaffinity enrichment step to purify the sample and maximize the sensitivity of the corresponding liquid chromatography tandem mass spectrometry measurements. In order to generate surrogate peptides with better mass spectrometric properties, protein enrichment is followed by a proteolytic cleavage step. This is often a time-consuming multistep process. Presented here is a workflow which enables rapid protein enrichment and proteolytic cleavage to be performed in a single, easy-to-use reactor. Using this strategy Klotho, a low-abundance biomarker found in plasma, can be accurately quantitated using a protocol that takes under 5 h from start to finish.

Characterization of protein N-glycosylation by tandem mass spectrometry using complementary fragmentation techniques

DOE PAGES

Ford, Kristina L.; Zeng, Wei; Heazlewood, Joshua L.; ...

2015-08-28

The analysis of post-translational modifications (PTMs) by proteomics is regarded as a technically challenging undertaking. While in recent years approaches to examine and quantify protein phosphorylation have greatly improved, the analysis of many protein modifications, such as glycosylation, are still regarded as problematic. Limitations in the standard proteomics workflow, such as use of suboptimal peptide fragmentation methods, can significantly prevent the identification of glycopeptides. The current generation of tandem mass spectrometers has made available a variety of fragmentation options, many of which are becoming standard features on these instruments. Lastly, we have used three common fragmentation techniques, namely CID, HCD,more » and ETD, to analyze a glycopeptide and highlight how an integrated fragmentation approach can be used to identify the modified residue and characterize the N-glycan on a peptide.« less

A Sensitive and Effective Proteomic Approach to Identify She-Donkey’s and Goat’s Milk Adulterations by MALDI-TOF MS Fingerprinting

PubMed Central

Di Girolamo, Francesco; Masotti, Andrea; Salvatori, Guglielmo; Scapaticci, Margherita; Muraca, Maurizio; Putignani, Lorenza

2014-01-01

She-donkey’s milk (DM) and goat’s milk (GM) are commonly used in newborn and infant feeding because they are less allergenic than other milk types. It is, therefore, mandatory to avoid adulteration and contamination by other milk allergens, developing fast and efficient analytical methods to assess the authenticity of these precious nutrients. In this experimental work, a sensitive and robust matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling was designed to assess the genuineness of DM and GM milks. This workflow allows the identification of DM and GM adulteration at levels of 0.5%, thus, representing a sensitive tool for milk adulteration analysis, if compared with other laborious and time-consuming analytical procedures. PMID:25110863