From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Large-Scale Proteome Comparative Analysis of Developing Rhizomes of the Ancient Vascular Plant Equisetum Hyemale

PubMed Central

Balbuena, Tiago Santana; He, Ruifeng; Salvato, Fernanda; Gang, David R.; Thelen, Jay J.

2012-01-01

Horsetail (Equisetum hyemale) is a widespread vascular plant species, whose reproduction is mainly dependent on the growth and development of the rhizomes. Due to its key evolutionary position, the identification of factors that could be involved in the existence of the rhizomatous trait may contribute to a better understanding of the role of this underground organ for the successful propagation of this and other plant species. In the present work, we characterized the proteome of E. hyemale rhizomes using a GeLC-MS spectral-counting proteomics strategy. A total of 1,911 and 1,860 non-redundant proteins were identified in the rhizomes apical tip and elongation zone, respectively. Rhizome-characteristic proteins were determined by comparisons of the developing rhizome tissues to developing roots. A total of 87 proteins were found to be up-regulated in both horsetail rhizome tissues in relation to developing roots. Hierarchical clustering indicated a vast dynamic range in the regulation of the 87 characteristic proteins and revealed, based on the regulation profile, the existence of nine major protein groups. Gene ontology analyses suggested an over-representation of the terms involved in macromolecular and protein biosynthetic processes, gene expression, and nucleotide and protein binding functions. Spatial difference analysis between the rhizome apical tip and the elongation zone revealed that only eight proteins were up-regulated in the apical tip including RNA-binding proteins and an acyl carrier protein, as well as a KH domain protein and a T-complex subunit; while only seven proteins were up-regulated in the elongation zone including phosphomannomutase, galactomannan galactosyltransferase, endoglucanase 10 and 25, and mannose-1-phosphate guanyltransferase subunits alpha and beta. This is the first large-scale characterization of the proteome of a plant rhizome. Implications of the findings were discussed in relation to other underground organs and related

Proteomics wants cRacker: automated standardized data analysis of LC-MS derived proteomic data.

PubMed

Zauber, Henrik; Schulze, Waltraud X

2012-11-02

The large-scale analysis of thousands of proteins under various experimental conditions or in mutant lines has gained more and more importance in hypothesis-driven scientific research and systems biology in the past years. Quantitative analysis by large scale proteomics using modern mass spectrometry usually results in long lists of peptide ion intensities. The main interest for most researchers, however, is to draw conclusions on the protein level. Postprocessing and combining peptide intensities of a proteomic data set requires expert knowledge, and the often repetitive and standardized manual calculations can be time-consuming. The analysis of complex samples can result in very large data sets (lists with several 1000s to 100,000 entries of different peptides) that cannot easily be analyzed using standard spreadsheet programs. To improve speed and consistency of the data analysis of LC-MS derived proteomic data, we developed cRacker. cRacker is an R-based program for automated downstream proteomic data analysis including data normalization strategies for metabolic labeling and label free quantitation. In addition, cRacker includes basic statistical analysis, such as clustering of data, or ANOVA and t tests for comparison between treatments. Results are presented in editable graphic formats and in list files.

Improving Design Efficiency for Large-Scale Heterogeneous Circuits

NASA Astrophysics Data System (ADS)

Gregerson, Anthony

Despite increases in logic density, many Big Data applications must still be partitioned across multiple computing devices in order to meet their strict performance requirements. Among the most demanding of these applications is high-energy physics (HEP), which uses complex computing systems consisting of thousands of FPGAs and ASICs to process the sensor data created by experiments at particles accelerators such as the Large Hadron Collider (LHC). Designing such computing systems is challenging due to the scale of the systems, the exceptionally high-throughput and low-latency performance constraints that necessitate application-specific hardware implementations, the requirement that algorithms are efficiently partitioned across many devices, and the possible need to update the implemented algorithms during the lifetime of the system. In this work, we describe our research to develop flexible architectures for implementing such large-scale circuits on FPGAs. In particular, this work is motivated by (but not limited in scope to) high-energy physics algorithms for the Compact Muon Solenoid (CMS) experiment at the LHC. To make efficient use of logic resources in multi-FPGA systems, we introduce Multi-Personality Partitioning, a novel form of the graph partitioning problem, and present partitioning algorithms that can significantly improve resource utilization on heterogeneous devices while also reducing inter-chip connections. To reduce the high communication costs of Big Data applications, we also introduce Information-Aware Partitioning, a partitioning method that analyzes the data content of application-specific circuits, characterizes their entropy, and selects circuit partitions that enable efficient compression of data between chips. We employ our information-aware partitioning method to improve the performance of the hardware validation platform for evaluating new algorithms for the CMS experiment. Together, these research efforts help to improve the efficiency

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data.

PubMed

Gray, Vanessa E; Hause, Ronald J; Luebeck, Jens; Shendure, Jay; Fowler, Douglas M

2018-01-24

Large datasets describing the quantitative effects of mutations on protein function are becoming increasingly available. Here, we leverage these datasets to develop Envision, which predicts the magnitude of a missense variant's molecular effect. Envision combines 21,026 variant effect measurements from nine large-scale experimental mutagenesis datasets, a hitherto untapped training resource, with a supervised, stochastic gradient boosting learning algorithm. Envision outperforms other missense variant effect predictors both on large-scale mutagenesis data and on an independent test dataset comprising 2,312 TP53 variants whose effects were measured using a low-throughput approach. This dataset was never used for hyperparameter tuning or model training and thus serves as an independent validation set. Envision prediction accuracy is also more consistent across amino acids than other predictors. Finally, we demonstrate that Envision's performance improves as more large-scale mutagenesis data are incorporated. We precompute Envision predictions for every possible single amino acid variant in human, mouse, frog, zebrafish, fruit fly, worm, and yeast proteomes (https://envision.gs.washington.edu/). Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment and improvement of statistical tools for comparative proteomics analysis of sparse data sets with few experimental replicates.

PubMed

Schwämmle, Veit; León, Ileana Rodríguez; Jensen, Ole Nørregaard

2013-09-06

Large-scale quantitative analyses of biological systems are often performed with few replicate experiments, leading to multiple nonidentical data sets due to missing values. For example, mass spectrometry driven proteomics experiments are frequently performed with few biological or technical replicates due to sample-scarcity or due to duty-cycle or sensitivity constraints, or limited capacity of the available instrumentation, leading to incomplete results where detection of significant feature changes becomes a challenge. This problem is further exacerbated for the detection of significant changes on the peptide level, for example, in phospho-proteomics experiments. In order to assess the extent of this problem and the implications for large-scale proteome analysis, we investigated and optimized the performance of three statistical approaches by using simulated and experimental data sets with varying numbers of missing values. We applied three tools, including standard t test, moderated t test, also known as limma, and rank products for the detection of significantly changing features in simulated and experimental proteomics data sets with missing values. The rank product method was improved to work with data sets containing missing values. Extensive analysis of simulated and experimental data sets revealed that the performance of the statistical analysis tools depended on simple properties of the data sets. High-confidence results were obtained by using the limma and rank products methods for analyses of triplicate data sets that exhibited more than 1000 features and more than 50% missing values. The maximum number of differentially represented features was identified by using limma and rank products methods in a complementary manner. We therefore recommend combined usage of these methods as a novel and optimal way to detect significantly changing features in these data sets. This approach is suitable for large quantitative data sets from stable isotope labeling

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry.

PubMed

Pflieger, Delphine; Gonnet, Florence; de la Fuente van Bentem, Sergio; Hirt, Heribert; de la Fuente, Alberto

2011-01-01

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks. Copyright © 2010 Wiley Periodicals, Inc.

Principles of proteome allocation are revealed using proteomic data and genome-scale models

PubMed Central

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.

2016-01-01

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205

Principles of proteome allocation are revealed using proteomic data and genome-scale models

DOE PAGES

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...

2016-11-18

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

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

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification*

PubMed Central

Takemori, Nobuaki; Takemori, Ayako; Tanaka, Yuki; Endo, Yaeta; Hurst, Jane L.; Gómez-Baena, Guadalupe; Harman, Victoria M.; Beynon, Robert J.

2017-01-01

A major challenge in proteomics is the absolute accurate quantification of large numbers of proteins. QconCATs, artificial proteins that are concatenations of multiple standard peptides, are well established as an efficient means to generate standards for proteome quantification. Previously, QconCATs have been expressed in bacteria, but we now describe QconCAT expression in a robust, cell-free system. The new expression approach rescues QconCATs that previously were unable to be expressed in bacteria and can reduce the incidence of proteolytic damage to QconCATs. Moreover, it is possible to cosynthesize QconCATs in a highly-multiplexed translation reaction, coexpressing tens or hundreds of QconCATs simultaneously. By obviating bacterial culture and through the gain of high level multiplexing, it is now possible to generate tens of thousands of standard peptides in a matter of weeks, rendering absolute quantification of a complex proteome highly achievable in a reproducible, broadly deployable system. PMID:29055021

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.

PubMed

Di Silvestre, Dario; Bergamaschi, Andrea; Bellini, Edoardo; Mauri, PierLuigi

2018-06-03

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

hEIDI: An Intuitive Application Tool To Organize and Treat Large-Scale Proteomics Data.

PubMed

Hesse, Anne-Marie; Dupierris, Véronique; Adam, Claire; Court, Magali; Barthe, Damien; Emadali, Anouk; Masselon, Christophe; Ferro, Myriam; Bruley, Christophe

2016-10-07

Advances in high-throughput proteomics have led to a rapid increase in the number, size, and complexity of the associated data sets. Managing and extracting reliable information from such large series of data sets require the use of dedicated software organized in a consistent pipeline to reduce, validate, exploit, and ultimately export data. The compilation of multiple mass-spectrometry-based identification and quantification results obtained in the context of a large-scale project represents a real challenge for developers of bioinformatics solutions. In response to this challenge, we developed a dedicated software suite called hEIDI to manage and combine both identifications and semiquantitative data related to multiple LC-MS/MS analyses. This paper describes how, through a user-friendly interface, hEIDI can be used to compile analyses and retrieve lists of nonredundant protein groups. Moreover, hEIDI allows direct comparison of series of analyses, on the basis of protein groups, while ensuring consistent protein inference and also computing spectral counts. hEIDI ensures that validated results are compliant with MIAPE guidelines as all information related to samples and results is stored in appropriate databases. Thanks to the database structure, validated results generated within hEIDI can be easily exported in the PRIDE XML format for subsequent publication. hEIDI can be downloaded from http://biodev.extra.cea.fr/docs/heidi .

Reconsidering Replication: New Perspectives on Large-Scale School Improvement

ERIC Educational Resources Information Center

Peurach, Donald J.; Glazer, Joshua L.

2012-01-01

The purpose of this analysis is to reconsider organizational replication as a strategy for large-scale school improvement: a strategy that features a "hub" organization collaborating with "outlet" schools to enact school-wide designs for improvement. To do so, we synthesize a leading line of research on commercial replication to construct a…

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

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

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets

PubMed Central

Savitski, Mikhail M.; Wilhelm, Mathias; Hahne, Hannes; Kuster, Bernhard; Bantscheff, Marcus

2015-01-01

Calculating the number of confidently identified proteins and estimating false discovery rate (FDR) is a challenge when analyzing very large proteomic data sets such as entire human proteomes. Biological and technical heterogeneity in proteomic experiments further add to the challenge and there are strong differences in opinion regarding the conceptual validity of a protein FDR and no consensus regarding the methodology for protein FDR determination. There are also limitations inherent to the widely used classic target–decoy strategy that particularly show when analyzing very large data sets and that lead to a strong over-representation of decoy identifications. In this study, we investigated the merits of the classic, as well as a novel target–decoy-based protein FDR estimation approach, taking advantage of a heterogeneous data collection comprised of ∼19,000 LC-MS/MS runs deposited in ProteomicsDB (https://www.proteomicsdb.org). The “picked” protein FDR approach treats target and decoy sequences of the same protein as a pair rather than as individual entities and chooses either the target or the decoy sequence depending on which receives the highest score. We investigated the performance of this approach in combination with q-value based peptide scoring to normalize sample-, instrument-, and search engine-specific differences. The “picked” target–decoy strategy performed best when protein scoring was based on the best peptide q-value for each protein yielding a stable number of true positive protein identifications over a wide range of q-value thresholds. We show that this simple and unbiased strategy eliminates a conceptual issue in the commonly used “classic” protein FDR approach that causes overprediction of false-positive protein identification in large data sets. The approach scales from small to very large data sets without losing performance, consistently increases the number of true-positive protein identifications and is readily

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 .

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

PubMed

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Scale-Up: Improving Large Enrollment Physics Courses

NASA Astrophysics Data System (ADS)

Beichner, Robert

1999-11-01

The Student-Centered Activities for Large Enrollment University Physics (SCALE-UP) project is working to establish a learning environment that will promote increased conceptual understanding, improved problem-solving performance, and greater student satisfaction, while still maintaining class sizes of approximately 100. We are also addressing the new ABET engineering accreditation requirements for inquiry-based learning along with communication and team-oriented skills development. Results of studies of our latest classroom design, plans for future classroom space, and the current iteration of instructional materials will be discussed.

A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets.

PubMed

Savitski, Mikhail M; Wilhelm, Mathias; Hahne, Hannes; Kuster, Bernhard; Bantscheff, Marcus

2015-09-01

Calculating the number of confidently identified proteins and estimating false discovery rate (FDR) is a challenge when analyzing very large proteomic data sets such as entire human proteomes. Biological and technical heterogeneity in proteomic experiments further add to the challenge and there are strong differences in opinion regarding the conceptual validity of a protein FDR and no consensus regarding the methodology for protein FDR determination. There are also limitations inherent to the widely used classic target-decoy strategy that particularly show when analyzing very large data sets and that lead to a strong over-representation of decoy identifications. In this study, we investigated the merits of the classic, as well as a novel target-decoy-based protein FDR estimation approach, taking advantage of a heterogeneous data collection comprised of ∼19,000 LC-MS/MS runs deposited in ProteomicsDB (https://www.proteomicsdb.org). The "picked" protein FDR approach treats target and decoy sequences of the same protein as a pair rather than as individual entities and chooses either the target or the decoy sequence depending on which receives the highest score. We investigated the performance of this approach in combination with q-value based peptide scoring to normalize sample-, instrument-, and search engine-specific differences. The "picked" target-decoy strategy performed best when protein scoring was based on the best peptide q-value for each protein yielding a stable number of true positive protein identifications over a wide range of q-value thresholds. We show that this simple and unbiased strategy eliminates a conceptual issue in the commonly used "classic" protein FDR approach that causes overprediction of false-positive protein identification in large data sets. The approach scales from small to very large data sets without losing performance, consistently increases the number of true-positive protein identifications and is readily implemented in

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

Current Progress in Tonoplast Proteomics Reveals Insights into the Function of the Large Central Vacuole

PubMed Central

Trentmann, Oliver; Haferkamp, Ilka

2013-01-01

Vacuoles of plants fulfill various biologically important functions, like turgor generation and maintenance, detoxification, solute sequestration, or protein storage. Different types of plant vacuoles (lytic versus protein storage) are characterized by different functional properties apparently caused by a different composition/abundance and regulation of transport proteins in the surrounding membrane, the tonoplast. Proteome analyses allow the identification of vacuolar proteins and provide an informative basis for assigning observed transport processes to specific carriers or channels. This review summarizes techniques required for vacuolar proteome analyses, like e.g., isolation of the large central vacuole or tonoplast membrane purification. Moreover, an overview about diverse published vacuolar proteome studies is provided. It becomes evident that qualitative proteomes from different plant species represent just the tip of the iceberg. During the past few years, mass spectrometry achieved immense improvement concerning its accuracy, sensitivity, and application. As a consequence, modern tonoplast proteome approaches are suited for detecting alterations in membrane protein abundance in response to changing environmental/physiological conditions and help to clarify the regulation of tonoplast transport processes. PMID:23459586

Applications of Proteomic Technologies to Toxicology

EPA Science Inventory

Proteomics is the large-scale study of gene expression at the protein level. This cutting edge technology has been extensively applied to toxicology research recently. The up-to-date development of proteomics has presented the toxicology community with an unprecedented opportunit...

Large-scale Proteomics Analysis of the Human Kinome

PubMed Central

Oppermann, Felix S.; Gnad, Florian; Olsen, Jesper V.; Hornberger, Renate; Greff, Zoltán; Kéri, György; Mann, Matthias; Daub, Henrik

2009-01-01

Members of the human protein kinase superfamily are the major regulatory enzymes involved in the activity control of eukaryotic signal transduction pathways. As protein kinases reside at the nodes of phosphorylation-based signal transmission, comprehensive analysis of their cellular expression and site-specific phosphorylation can provide important insights into the architecture and functionality of signaling networks. However, in global proteome studies, low cellular abundance of protein kinases often results in rather minor peptide species that are occluded by a vast excess of peptides from other cellular proteins. These analytical limitations create a rationale for kinome-wide enrichment of protein kinases prior to mass spectrometry analysis. Here, we employed stable isotope labeling by amino acids in cell culture (SILAC) to compare the binding characteristics of three kinase-selective affinity resins by quantitative mass spectrometry. The evaluated pre-fractionation tools possessed pyrido[2,3-d]pyrimidine-based kinase inhibitors as immobilized capture ligands and retained considerable subsets of the human kinome. Based on these results, an affinity resin displaying the broadly selective kinase ligand VI16832 was employed to quantify the relative expression of more than 170 protein kinases across three different, SILAC-encoded cancer cell lines. These experiments demonstrated the feasibility of comparative kinome profiling in a compact experimental format. Interestingly, we found high levels of cytoplasmic and low levels of receptor tyrosine kinases in MV4–11 leukemia cells compared with the adherent cancer lines HCT116 and MDA-MB-435S. The VI16832 resin was further exploited to pre-fractionate kinases for targeted phosphoproteomics analysis, which revealed about 1200 distinct phosphorylation sites on more than 200 protein kinases. This hitherto largest survey of site-specific phosphorylation across the kinome significantly expands the basis for functional

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

Infrastructure for Large-Scale Quality-Improvement Projects: Early Lessons from North Carolina Improving Performance in Practice

ERIC Educational Resources Information Center

Newton, Warren P.; Lefebvre, Ann; Donahue, Katrina E.; Bacon, Thomas; Dobson, Allen

2010-01-01

Introduction: Little is known regarding how to accomplish large-scale health care improvement. Our goal is to improve the quality of chronic disease care in all primary care practices throughout North Carolina. Methods: Methods for improvement include (1) common quality measures and shared data system; (2) rapid cycle improvement principles; (3)…

CPTAC | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.

Spermatogenesis in mammals: proteomic insights.

PubMed

Chocu, Sophie; Calvel, Pierre; Rolland, Antoine D; Pineau, Charles

2012-08-01

Spermatogenesis is a highly sophisticated process involved in the transmission of genetic heritage. It includes halving ploidy, repackaging of the chromatin for transport, and the equipment of developing spermatids and eventually spermatozoa with the advanced apparatus (e.g., tightly packed mitochondrial sheat in the mid piece, elongating of the tail, reduction of cytoplasmic volume) to elicit motility once they reach the epididymis. Mammalian spermatogenesis is divided into three phases. In the first the primitive germ cells or spermatogonia undergo a series of mitotic divisions. In the second the spermatocytes undergo two consecutive divisions in meiosis to produce haploid spermatids. In the third the spermatids differentiate into spermatozoa in a process called spermiogenesis. Paracrine, autocrine, juxtacrine, and endocrine pathways all contribute to the regulation of the process. The array of structural elements and chemical factors modulating somatic and germ cell activity is such that the network linking the various cellular activities during spermatogenesis is unimaginably complex. Over the past two decades, advances in genomics have greatly improved our knowledge of spermatogenesis, by identifying numerous genes essential for the development of functional male gametes. Large-scale analyses of testicular function have deepened our insight into normal and pathological spermatogenesis. Progress in genome sequencing and microarray technology have been exploited for genome-wide expression studies, leading to the identification of hundreds of genes differentially expressed within the testis. However, although proteomics has now come of age, the proteomics-based investigation of spermatogenesis remains in its infancy. Here, we review the state-of-the-art of large-scale proteomic analyses of spermatogenesis, from germ cell development during sex determination to spermatogenesis in the adult. Indeed, a few laboratories have undertaken differential protein profiling

Developmental and Subcellular Organization of Single-Cell C₄ Photosynthesis in Bienertia sinuspersici Determined by Large-Scale Proteomics and cDNA Assembly from 454 DNA Sequencing.

PubMed

Offermann, Sascha; Friso, Giulia; Doroshenk, Kelly A; Sun, Qi; Sharpe, Richard M; Okita, Thomas W; Wimmer, Diana; Edwards, Gerald E; van Wijk, Klaas J

2015-05-01

Kranz C4 species strictly depend on separation of primary and secondary carbon fixation reactions in different cell types. In contrast, the single-cell C4 (SCC4) species Bienertia sinuspersici utilizes intracellular compartmentation including two physiologically and biochemically different chloroplast types; however, information on identity, localization, and induction of proteins required for this SCC4 system is currently very limited. In this study, we determined the distribution of photosynthesis-related proteins and the induction of the C4 system during development by label-free proteomics of subcellular fractions and leaves of different developmental stages. This was enabled by inferring a protein sequence database from 454 sequencing of Bienertia cDNAs. Large-scale proteome rearrangements were observed as C4 photosynthesis developed during leaf maturation. The proteomes of the two chloroplasts are different with differential accumulation of linear and cyclic electron transport components, primary and secondary carbon fixation reactions, and a triose-phosphate shuttle that is shared between the two chloroplast types. This differential protein distribution pattern suggests the presence of a mRNA or protein-sorting mechanism for nuclear-encoded, chloroplast-targeted proteins in SCC4 species. The combined information was used to provide a comprehensive model for NAD-ME type carbon fixation in SCC4 species.

ApoptoProteomics, an integrated database for analysis of proteomics data obtained from apoptotic cells.

PubMed

Arntzen, Magnus Ø; Thiede, Bernd

2012-02-01

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no.

CPTC and KIST Join Efforts to Solve Complex Proteomic Issues | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute's (NCI) Clinical Proteomic Technologies for Cancer (CPTC) initiative at the National Institutes of Health has entered into a memorandum of understanding (MOU) with the Korea Institute of Science and Technology (KIST). This MOU promotes proteomic technology optimization and standards implementation in large-scale international programs.

ApoptoProteomics, an Integrated Database for Analysis of Proteomics Data Obtained from Apoptotic Cells*

PubMed Central

Arntzen, Magnus Ø.; Thiede, Bernd

2012-01-01

Apoptosis is the most commonly described form of programmed cell death, and dysfunction is implicated in a large number of human diseases. Many quantitative proteome analyses of apoptosis have been performed to gain insight in proteins involved in the process. This resulted in large and complex data sets that are difficult to evaluate. Therefore, we developed the ApoptoProteomics database for storage, browsing, and analysis of the outcome of large scale proteome analyses of apoptosis derived from human, mouse, and rat. The proteomics data of 52 publications were integrated and unified with protein annotations from UniProt-KB, the caspase substrate database homepage (CASBAH), and gene ontology. Currently, more than 2300 records of more than 1500 unique proteins were included, covering a large proportion of the core signaling pathways of apoptosis. Analysis of the data set revealed a high level of agreement between the reported changes in directionality reported in proteomics studies and expected apoptosis-related function and may disclose proteins without a current recognized involvement in apoptosis based on gene ontology. Comparison between induction of apoptosis by the intrinsic and the extrinsic apoptotic signaling pathway revealed slight differences. Furthermore, proteomics has significantly contributed to the field of apoptosis in identifying hundreds of caspase substrates. The database is available at http://apoptoproteomics.uio.no. PMID:22067098

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

PubMed

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage.

PubMed

Van, Phu T; Schmid, Amy K; King, Nichole L; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T; Goo, Young Ah; Deutsch, Eric W; Reiss, David J; Mallick, Parag; Baliga, Nitin S

2008-09-01

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.

Large-Scale High School Reform through School Improvement Networks: Exploring Possibilities for "Developmental Evaluation"

ERIC Educational Resources Information Center

Peurach, Donald J.; Lenhoff, Sarah Winchell; Glazer, Joshua L.

2016-01-01

Recognizing school improvement networks as a leading strategy for large-scale high school reform, this analysis examines developmental evaluation as an approach to examining school improvement networks as "learning systems" able to produce, use, and refine practical knowledge in large numbers of schools. Through a case study of one…

Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

PubMed

Ali, Mehreen; Khan, Suleiman A; Wennerberg, Krister; Aittokallio, Tero

2018-04-15

Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly targeted anticancer compounds. Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients. Processed datasets, R as well as Matlab implementations of the methods are available at https://github.com/mehr-een/bemkl-rbps. mehreen

Proteomic insights into floral biology.

PubMed

Li, Xiaobai; Jackson, Aaron; Xie, Ming; Wu, Dianxing; Tsai, Wen-Chieh; Zhang, Sheng

2016-08-01

The flower is the most important biological structure for ensuring angiosperms reproductive success. Not only does the flower contain critical reproductive organs, but the wide variation in morphology, color, and scent has evolved to entice specialized pollinators, and arguably mankind in many cases, to ensure the successful propagation of its species. Recent proteomic approaches have identified protein candidates related to these flower traits, which has shed light on a number of previously unknown mechanisms underlying these traits. This review article provides a comprehensive overview of the latest advances in proteomic research in floral biology according to the order of flower structure, from corolla to male and female reproductive organs. It summarizes mainstream proteomic methods for plant research and recent improvements on two dimensional gel electrophoresis and gel-free workflows for both peptide level and protein level analysis. The recent advances in sequencing technologies provide a new paradigm for the ever-increasing genome and transcriptome information on many organisms. It is now possible to integrate genomic and transcriptomic data with proteomic results for large-scale protein characterization, so that a global understanding of the complex molecular networks in flower biology can be readily achieved. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock. Copyright © 2016 Elsevier B.V. All rights reserved.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

Affordable proteomics: the two-hybrid systems.

PubMed

Gillespie, Marc

2003-06-01

Numerous proteomic methodologies exist, but most require a heavy investment in expertise and technology. This puts these approaches out of reach for many laboratories and small companies, rarely allowing proteomics to be used as a pilot approach for biomarker or target identification. Two proteomic approaches, 2D gel electrophoresis and the two-hybrid systems, are currently available to most researchers. The two-hybrid systems, though accommodating to large-scale experiments, were originally designed as practical screens, that by comparison to current proteomics tools were small-scale, affordable and technically feasible. The screens rapidly generated data, identifying protein interactions that were previously uncharacterized. The foundation for a two-hybrid proteomic investigation can be purchased as separate kits from a number of companies. The true power of the technique lies not in its affordability, but rather in its portability. The two-hybrid system puts proteomics back into laboratories where the output of the screens can be evaluated by researchers with experience in the particular fields of basic research, cancer biology, toxicology or drug development.

Large-scale inference of protein tissue origin in gram-positive sepsis plasma using quantitative targeted proteomics

PubMed Central

Malmström, Erik; Kilsgård, Ola; Hauri, Simon; Smeds, Emanuel; Herwald, Heiko; Malmström, Lars; Malmström, Johan

2016-01-01

The plasma proteome is highly dynamic and variable, composed of proteins derived from surrounding tissues and cells. To investigate the complex processes that control the composition of the plasma proteome, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in murine plasma. The strategy relies on the construction of a comprehensive protein tissue atlas from cells and highly vascularized organs using shotgun mass spectrometry. The protein tissue atlas was transformed to a spectral library for highly reproducible quantification of tissue-specific proteins directly in plasma using SWATH-like data-independent mass spectrometry analysis. We show that the method can determine drastic changes of tissue-specific protein profiles in blood plasma from mouse animal models with sepsis. The strategy can be extended to several other species advancing our understanding of the complex processes that contribute to the plasma proteome dynamics. PMID:26732734

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

USING PROTEOMICS TO IMPROVE RISK ASSESSMENT OF HUMAN EXPOSURE TO ENVIRONMENTAL AGENTS

EPA Science Inventory

Using Proteomics to Improve Risk Assessment of Human Exposure to Environmental Agents.
Authors: Witold M. Winnik
Key Words (4): Proteomics, LC/MS, Western Blots, 1D and 2D gel electrophoresis, toxicity

The goal of this project is to use proteomics for the character...

Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM.

PubMed

Tuncbag, Nurcan; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2011-08-11

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank-formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.

Nanoliter-Scale Oil-Air-Droplet Chip-Based Single Cell Proteomic Analysis.

PubMed

Li, Zi-Yi; Huang, Min; Wang, Xiu-Kun; Zhu, Ying; Li, Jin-Song; Wong, Catherine C L; Fang, Qun

2018-04-17

Single cell proteomic analysis provides crucial information on cellular heterogeneity in biological systems. Herein, we describe a nanoliter-scale oil-air-droplet (OAD) chip for achieving multistep complex sample pretreatment and injection for single cell proteomic analysis in the shotgun mode. By using miniaturized stationary droplet microreaction and manipulation techniques, our system allows all sample pretreatment and injection procedures to be performed in a nanoliter-scale droplet with minimum sample loss and a high sample injection efficiency (>99%), thus substantially increasing the analytical sensitivity for single cell samples. We applied the present system in the proteomic analysis of 100 ± 10, 50 ± 5, 10, and 1 HeLa cell(s), and protein IDs of 1360, 612, 192, and 51 were identified, respectively. The OAD chip-based system was further applied in single mouse oocyte analysis, with 355 protein IDs identified at the single oocyte level, which demonstrated its special advantages of high enrichment of sequence coverage, hydrophobic proteins, and enzymatic digestion efficiency over the traditional in-tube system.

Explore, Visualize, and Analyze Functional Cancer Proteomic Data Using the Cancer Proteome Atlas. | Office of Cancer Genomics

Cancer.gov

Reverse-phase protein arrays (RPPA) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and to develop novel cancer therapies. To facilitate community-based investigation of the large-scale protein expression data generated by this platform, we have developed a user-friendly, open-access bioinformatic resource, The Cancer Proteome Atlas (TCPA, http://tcpaportal.org), which contains two separate web applications.

Advanced proteomic liquid chromatography

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

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-10-26

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput.

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Large-Scale Interaction Profiling of Protein Domains Through Proteomic Peptide-Phage Display Using Custom Peptidomes.

PubMed

Seo, Moon-Hyeong; Nim, Satra; Jeon, Jouhyun; Kim, Philip M

2017-01-01

Protein-protein interactions are essential to cellular functions and signaling pathways. We recently combined bioinformatics and custom oligonucleotide arrays to construct custom-made peptide-phage libraries for screening peptide-protein interactions, an approach we call proteomic peptide-phage display (ProP-PD). In this chapter, we describe protocols for phage display for the identification of natural peptide binders for a given protein. We finally describe deep sequencing for the analysis of the proteomic peptide-phage display.

The HUPO proteomics standards initiative--overcoming the fragmentation of proteomics data.

PubMed

Hermjakob, Henning

2006-09-01

Proteomics is a key field of modern biomolecular research, with many small and large scale efforts producing a wealth of proteomics data. However, the vast majority of this data is never exploited to its full potential. Even in publicly funded projects, often the raw data generated in a specific context is analysed, conclusions are drawn and published, but little attention is paid to systematic documentation, archiving, and public access to the data supporting the scientific results. It is often difficult to validate the results stated in a particular publication, and even simple global questions like "In which cellular contexts has my protein of interest been observed?" can currently not be answered with realistic effort, due to a lack of standardised reporting and collection of proteomics data. The Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organisation (HUPO), defines community standards for data representation in proteomics to facilitate systematic data capture, comparison, exchange and verification. In this article we provide an overview of PSI organisational structure, activities, and current results, as well as ways to get involved in the broad-based, open PSI process.

School Improvement Networks as a Strategy for Large-Scale Education Reform: The Role of Educational Environments

ERIC Educational Resources Information Center

Glazer, Joshua L.; Peurach, Donald J.

2013-01-01

The development and scale-up of school improvement networks is among the most important educational innovations of the last decade, and current federal, state, and district efforts attempt to use school improvement networks as a mechanism for supporting large-scale change. The potential of improvement networks, however, rests on the extent to…

Advanced proteomic liquid chromatography

PubMed Central

Xie, Fang; Smith, Richard D.; Shen, Yufeng

2012-01-01

Liquid chromatography coupled with mass spectrometry is the predominant platform used to analyze proteomics samples consisting of large numbers of proteins and their proteolytic products (e.g., truncated polypeptides) and spanning a wide range of relative concentrations. This review provides an overview of advanced capillary liquid chromatography techniques and methodologies that greatly improve separation resolving power and proteomics analysis coverage, sensitivity, and throughput. PMID:22840822

Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry.

PubMed

Pfammatter, Sibylle; Bonneil, Eric; Thibault, Pierre

2016-12-02

Quantitative proteomics using isobaric reagent tandem mass tags (TMT) or isobaric tags for relative and absolute quantitation (iTRAQ) provides a convenient approach to compare changes in protein abundance across multiple samples. However, the analysis of complex protein digests by isobaric labeling can be undermined by the relative large proportion of co-selected peptide ions that lead to distorted reporter ion ratios and affect the accuracy and precision of quantitative measurements. Here, we investigated the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) in proteomic experiments to reduce sample complexity and improve protein quantification using TMT isobaric labeling. LC-FAIMS-MS/MS analyses of human and yeast protein digests led to significant reductions in interfering ions, which increased the number of quantifiable peptides by up to 68% while significantly improving the accuracy of abundance measurements compared to that with conventional LC-MS/MS. The improvement in quantitative measurements using FAIMS is further demonstrated for the temporal profiling of protein abundance of HEK293 cells following heat shock treatment.

Advancing Cell Biology Through Proteomics in Space and Time (PROSPECTS)*

PubMed Central

Lamond, Angus I.; Uhlen, Mathias; Horning, Stevan; Makarov, Alexander; Robinson, Carol V.; Serrano, Luis; Hartl, F. Ulrich; Baumeister, Wolfgang; Werenskiold, Anne Katrin; Andersen, Jens S.; Vorm, Ole; Linial, Michal; Aebersold, Ruedi; Mann, Matthias

2012-01-01

The term “proteomics” encompasses the large-scale detection and analysis of proteins and their post-translational modifications. Driven by major improvements in mass spectrometric instrumentation, methodology, and data analysis, the proteomics field has burgeoned in recent years. It now provides a range of sensitive and quantitative approaches for measuring protein structures and dynamics that promise to revolutionize our understanding of cell biology and molecular mechanisms in both human cells and model organisms. The Proteomics Specification in Time and Space (PROSPECTS) Network is a unique EU-funded project that brings together leading European research groups, spanning from instrumentation to biomedicine, in a collaborative five year initiative to develop new methods and applications for the functional analysis of cellular proteins. This special issue of Molecular and Cellular Proteomics presents 16 research papers reporting major recent progress by the PROSPECTS groups, including improvements to the resolution and sensitivity of the Orbitrap family of mass spectrometers, systematic detection of proteins using highly characterized antibody collections, and new methods for absolute as well as relative quantification of protein levels. Manuscripts in this issue exemplify approaches for performing quantitative measurements of cell proteomes and for studying their dynamic responses to perturbation, both during normal cellular responses and in disease mechanisms. Here we present a perspective on how the proteomics field is moving beyond simply identifying proteins with high sensitivity toward providing a powerful and versatile set of assay systems for characterizing proteome dynamics and thereby creating a new “third generation” proteomics strategy that offers an indispensible tool for cell biology and molecular medicine. PMID:22311636

Toward Increasing Fairness in Score Scale Calibrations Employed in International Large-Scale Assessments

ERIC Educational Resources Information Center

Oliveri, Maria Elena; von Davier, Matthias

2014-01-01

In this article, we investigate the creation of comparable score scales across countries in international assessments. We examine potential improvements to current score scale calibration procedures used in international large-scale assessments. Our approach seeks to improve fairness in scoring international large-scale assessments, which often…

Proteomic Profiling of Mitochondrial Enzymes during Skeletal Muscle Aging.

PubMed

Staunton, Lisa; O'Connell, Kathleen; Ohlendieck, Kay

2011-03-07

Mitochondria are of central importance for energy generation in skeletal muscles. Expression changes or functional alterations in mitochondrial enzymes play a key role during myogenesis, fibre maturation, and various neuromuscular pathologies, as well as natural fibre aging. Mass spectrometry-based proteomics suggests itself as a convenient large-scale and high-throughput approach to catalogue the mitochondrial protein complement and determine global changes during health and disease. This paper gives a brief overview of the relatively new field of mitochondrial proteomics and discusses the findings from recent proteomic surveys of mitochondrial elements in aged skeletal muscles. Changes in the abundance, biochemical activity, subcellular localization, and/or posttranslational modifications in key mitochondrial enzymes might be useful as novel biomarkers of aging. In the long term, this may advance diagnostic procedures, improve the monitoring of disease progression, help in the testing of side effects due to new drug regimes, and enhance our molecular understanding of age-related muscle degeneration.

Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation.

PubMed

Woo, Jongmin; Han, Dohyun; Wang, Joseph Injae; Park, Joonho; Kim, Hyunsoo; Kim, Youngsoo

2017-09-01

The development of systematic proteomic quantification techniques in systems biology research has enabled one to perform an in-depth analysis of cellular systems. We have developed a systematic proteomic approach that encompasses the spectrum from global to targeted analysis on a single platform. We have applied this technique to an activated microglia cell system to examine changes in the intracellular and extracellular proteomes. Microglia become activated when their homeostatic microenvironment is disrupted. There are varying degrees of microglial activation, and we chose to focus on the proinflammatory reactive state that is induced by exposure to such stimuli as lipopolysaccharide (LPS) and interferon-gamma (IFN-γ). Using an improved shotgun proteomics approach, we identified 5497 proteins in the whole-cell proteome and 4938 proteins in the secretome that were associated with the activation of BV2 mouse microglia by LPS or IFN-γ. Of the differentially expressed proteins in stimulated microglia, we classified pathways that were related to immune-inflammatory responses and metabolism. Our label-free parallel reaction monitoring (PRM) approach made it possible to comprehensively measure the hyper-multiplex quantitative value of each protein by high-resolution mass spectrometry. Over 450 peptides that corresponded to pathway proteins and direct or indirect interactors via the STRING database were quantified by label-free PRM in a single run. Moreover, we performed a longitudinal quantification of secreted proteins during microglial activation, in which neurotoxic molecules that mediate neuronal cell loss in the brain are released. These data suggest that latent pathways that are associated with neurodegenerative diseases can be discovered by constructing and analyzing a pathway network model of proteins. Furthermore, this systematic quantification platform has tremendous potential for applications in large-scale targeted analyses. The proteomics data for

The emergence of top-down proteomics in clinical research

PubMed Central

2013-01-01

Proteomic technology has advanced steadily since the development of 'soft-ionization' techniques for mass-spectrometry-based molecular identification more than two decades ago. Now, the large-scale analysis of proteins (proteomics) is a mainstay of biological research and clinical translation, with researchers seeking molecular diagnostics, as well as protein-based markers for personalized medicine. Proteomic strategies using the protease trypsin (known as bottom-up proteomics) were the first to be developed and optimized and form the dominant approach at present. However, researchers are now beginning to understand the limitations of bottom-up techniques, namely the inability to characterize and quantify intact protein molecules from a complex mixture of digested peptides. To overcome these limitations, several laboratories are taking a whole-protein-based approach, in which intact protein molecules are the analytical targets for characterization and quantification. We discuss these top-down techniques and how they have been applied to clinical research and are likely to be applied in the near future. Given the recent improvements in mass-spectrometry-based proteomics and stronger cooperation between researchers, clinicians and statisticians, both peptide-based (bottom-up) strategies and whole-protein-based (top-down) strategies are set to complement each other and help researchers and clinicians better understand and detect complex disease phenotypes. PMID:23806018

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.

Background | Office of Cancer Clinical Proteomics Research

Cancer.gov

The term "proteomics" refers to a large-scale comprehensive study of a specific proteome resulting from its genome, including abundances of proteins, their variations and modifications, and interacting partners and networks in order to understand cellular processes involved.  Similarly, “Cancer proteomics” refers to comprehensive analyses of proteins and their derivatives translated from a specific cancer genome using a human biospecimen or a preclinical model (e.g., cultured cell or animal model).

Psychology in an Interdisciplinary Setting: A Large-Scale Project to Improve University Teaching

ERIC Educational Resources Information Center

Koch, Franziska D.; Vogt, Joachim

2015-01-01

At a German university of technology, a large-scale project was funded as a part of the "Quality Pact for Teaching", a programme launched by the German Federal Ministry of Education and Research to improve the quality of university teaching and study conditions. The project aims at intensifying interdisciplinary networking in teaching,…

BioPlex Display: An Interactive Suite for Large-Scale AP-MS Protein-Protein Interaction Data.

PubMed

Schweppe, Devin K; Huttlin, Edward L; Harper, J Wade; Gygi, Steven P

2018-01-05

The development of large-scale data sets requires a new means to display and disseminate research studies to large audiences. Knowledge of protein-protein interaction (PPI) networks has become a principle interest of many groups within the field of proteomics. At the confluence of technologies, such as cross-linking mass spectrometry, yeast two-hybrid, protein cofractionation, and affinity purification mass spectrometry (AP-MS), detection of PPIs can uncover novel biological inferences at a high-throughput. Thus new platforms to provide community access to large data sets are necessary. To this end, we have developed a web application that enables exploration and dissemination of the growing BioPlex interaction network. BioPlex is a large-scale interactome data set based on AP-MS of baits from the human ORFeome. The latest BioPlex data set release (BioPlex 2.0) contains 56 553 interactions from 5891 AP-MS experiments. To improve community access to this vast compendium of interactions, we developed BioPlex Display, which integrates individual protein querying, access to empirical data, and on-the-fly annotation of networks within an easy-to-use and mobile web application. BioPlex Display enables rapid acquisition of data from BioPlex and development of hypotheses based on protein interactions.

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

PubMed

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

2008-04-01

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

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions.

PubMed

Delaforge, Elise; Milles, Sigrid; Huang, Jie-Rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales.

Investigating the Role of Large-Scale Domain Dynamics in Protein-Protein Interactions

PubMed Central

Delaforge, Elise; Milles, Sigrid; Huang, Jie-rong; Bouvier, Denis; Jensen, Malene Ringkjøbing; Sattler, Michael; Hart, Darren J.; Blackledge, Martin

2016-01-01

Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales. PMID:27679800

An improved method to characterise the modulation of small-scale turbulent by large-scale structures

NASA Astrophysics Data System (ADS)

Agostini, Lionel; Leschziner, Michael; Gaitonde, Datta

2015-11-01

A key aspect of turbulent boundary layer dynamics is ``modulation,'' which refers to degree to which the intensity of coherent large-scale structures (LS) cause an amplification or attenuation of the intensity of the small-scale structures (SS) through large-scale-linkage. In order to identify the variation of the amplitude of the SS motion, the envelope of the fluctuations needs to be determined. Mathis et al. (2009) proposed to define this latter by low-pass filtering the modulus of the analytic signal built from the Hilbert transform of SS. The validity of this definition, as a basis for quantifying the modulated SS signal, is re-examined on the basis of DNS data for a channel flow. The analysis shows that the modulus of the analytic signal is very sensitive to the skewness of its PDF, which is dependent, in turn, on the sign of the LS fluctuation and thus of whether these fluctuations are associated with sweeps or ejections. The conclusion is that generating an envelope by use of a low-pass filtering step leads to an important loss of information associated with the effects of the local skewness of the PDF of the SS on the modulation process. An improved Hilbert-transform-based method is proposed to characterize the modulation of SS turbulence by LS structures

Sequential Extraction Results in Improved Proteome Profiling of Medicinal Plant Pinellia ternata Tubers, Which Contain Large Amounts of High-Abundance Proteins

PubMed Central

An, SuFang; Gong, FangPing; Wang, Wei

2012-01-01

Pinellia ternata tuber is one of the well-known Chinese traditional medicines. In order to understand the pharmacological properties of tuber proteins, it is necessary to perform proteome analysis of P. ternata tubers. However, a few high-abundance proteins (HAPs), mainly mannose-binding lectin (agglutinin), exist in aggregates of various sizes in the tubers and seriously interfere with proteome profiling by two-dimensional electrophoresis (2-DE). Therefore, selective depletion of these HAPs is a prerequisite for enhanced proteome analysis of P. ternata tubers. Based on differential protein solubility, we developed a novel protocol involving two sequential extractions for depletion of some HAPs and prefractionation of tuber proteins prior to 2-DE. The first extraction using 10% acetic acid selectively extracted acid-soluble HAPs and the second extraction using the SDS-containing buffer extracted remaining acid-insoluble proteins. After application of the protocol, 2-DE profiles of P. ternata tuber proteins were greatly improved and more protein spots were detected, especially low-abundance proteins. Moreover, the subunit composition of P. ternata lectin was analyzed by electrophoresis. Native lectin consists of two hydrogen-bonded subunits (11 kDa and 25 kDa) and the 11 kDa subunit was a glycoprotein. Subsequently, major HAPs in the tubers were analyzed by mass spectrometry, with nine protein spots being identified as lectin isoforms. The methodology was easy to perform and required no specialized apparatus. It would be useful for proteome analysis of other tuber plants of Araceae. PMID:23185632

Sequential extraction results in improved proteome profiling of medicinal plant Pinellia ternata tubers, which contain large amounts of high-abundance proteins.

PubMed

Wu, Xiaolin; Xiong, Erhui; An, Sufang; Gong, Fangping; Wang, Wei

2012-01-01

Pinellia ternata tuber is one of the well-known Chinese traditional medicines. In order to understand the pharmacological properties of tuber proteins, it is necessary to perform proteome analysis of P. ternata tubers. However, a few high-abundance proteins (HAPs), mainly mannose-binding lectin (agglutinin), exist in aggregates of various sizes in the tubers and seriously interfere with proteome profiling by two-dimensional electrophoresis (2-DE). Therefore, selective depletion of these HAPs is a prerequisite for enhanced proteome analysis of P. ternata tubers. Based on differential protein solubility, we developed a novel protocol involving two sequential extractions for depletion of some HAPs and prefractionation of tuber proteins prior to 2-DE. The first extraction using 10% acetic acid selectively extracted acid-soluble HAPs and the second extraction using the SDS-containing buffer extracted remaining acid-insoluble proteins. After application of the protocol, 2-DE profiles of P. ternata tuber proteins were greatly improved and more protein spots were detected, especially low-abundance proteins. Moreover, the subunit composition of P. ternata lectin was analyzed by electrophoresis. Native lectin consists of two hydrogen-bonded subunits (11 kDa and 25 kDa) and the 11 kDa subunit was a glycoprotein. Subsequently, major HAPs in the tubers were analyzed by mass spectrometry, with nine protein spots being identified as lectin isoforms. The methodology was easy to perform and required no specialized apparatus. It would be useful for proteome analysis of other tuber plants of Araceae.

Large-scale proteome analysis of abscisic acid and ABSCISIC ACID INSENSITIVE3-dependent proteins related to desiccation tolerance in Physcomitrella patens

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

Yotsui, Izumi, E-mail: izumi.yotsui@riken.jp; Serada, Satoshi, E-mail: serada@nibiohn.go.jp; Naka, Tetsuji, E-mail: tnaka@nibiohn.go.jp

2016-03-18

desiccation tolerance might have evolved in ancestral land plants before the separation of bryophytes and vascular plants. - Highlights: • Large-scale proteomics highlighted proteins related to plant desiccation tolerance. • The proteins were regulated by both the phytohormone ABA and ABI3. • The proteins accumulated in desiccation tolerant cells of both Arabidopsis and moss. • Evolutionary origin of regulatory machinery for desiccation tolerance is proposed.« less

Spectrum-to-Spectrum Searching Using a Proteome-wide Spectral Library*

PubMed Central

Yen, Chia-Yu; Houel, Stephane; Ahn, Natalie G.; Old, William M.

2011-01-01

The unambiguous assignment of tandem mass spectra (MS/MS) to peptide sequences remains a key unsolved problem in proteomics. Spectral library search strategies have emerged as a promising alternative for peptide identification, in which MS/MS spectra are directly compared against a reference library of confidently assigned spectra. Two problems relate to library size. First, reference spectral libraries are limited to rediscovery of previously identified peptides and are not applicable to new peptides, because of their incomplete coverage of the human proteome. Second, problems arise when searching a spectral library the size of the entire human proteome. We observed that traditional dot product scoring methods do not scale well with spectral library size, showing reduction in sensitivity when library size is increased. We show that this problem can be addressed by optimizing scoring metrics for spectrum-to-spectrum searches with large spectral libraries. MS/MS spectra for the 1.3 million predicted tryptic peptides in the human proteome are simulated using a kinetic fragmentation model (MassAnalyzer version2.1) to create a proteome-wide simulated spectral library. Searches of the simulated library increase MS/MS assignments by 24% compared with Mascot, when using probabilistic and rank based scoring methods. The proteome-wide coverage of the simulated library leads to 11% increase in unique peptide assignments, compared with parallel searches of a reference spectral library. Further improvement is attained when reference spectra and simulated spectra are combined into a hybrid spectral library, yielding 52% increased MS/MS assignments compared with Mascot searches. Our study demonstrates the advantages of using probabilistic and rank based scores to improve performance of spectrum-to-spectrum search strategies. PMID:21532008

How Can the Evidence from Global Large-scale Clinical Trials for Cardiovascular Diseases be Improved?

PubMed

Sawata, Hiroshi; Tsutani, Kiichiro

2011-06-29

Clinical investigations are important for obtaining evidence to improve medical treatment. Large-scale clinical trials with thousands of participants are particularly important for this purpose in cardiovascular diseases. Conducting large-scale clinical trials entails high research costs. This study sought to investigate global trends in large-scale clinical trials in cardiovascular diseases. We searched for trials using clinicaltrials.gov (URL: http://www.clinicaltrials.gov/) using the key words 'cardio' and 'event' in all fields on 10 April, 2010. We then selected trials with 300 or more participants examining cardiovascular diseases. The search revealed 344 trials that met our criteria. Of 344 trials, 71% were randomized controlled trials, 15% involved more than 10,000 participants, and 59% were funded by industry. In RCTs whose results were disclosed, 55% of industry-funded trials and 25% of non-industry funded trials reported statistically significant superiority over control (p = 0.012, 2-sided Fisher's exact test). Our findings highlighted concerns regarding potential bias related to funding sources, and that researchers should be aware of the importance of trial information disclosures and conflicts of interest. We should keep considering management and training regarding information disclosures and conflicts of interest for researchers. This could lead to better clinical evidence and further improvements in the development of medical treatment worldwide.

Proteomics meets blood banking: identification of protein targets for the improvement of platelet quality.

PubMed

Schubert, Peter; Devine, Dana V

2010-01-03

Proteomics has brought new perspectives to the fields of hematology and transfusion medicine in the last decade. The steady improvement of proteomic technology is propelling novel discoveries of molecular mechanisms by studying protein expression, post-translational modifications and protein interactions. This review article focuses on the application of proteomics to the identification of molecular mechanisms leading to the deterioration of blood platelets during storage - a critical aspect in the provision of platelet transfusion products. Several proteomic approaches have been employed to analyse changes in the platelet protein profile during storage and the obtained data now need to be translated into platelet biochemistry in order to connect the results to platelet function. Targeted biochemical applications then allow the identification of points for intervention in signal transduction pathways. Once validated and placed in a transfusion context, these data will provide further understanding of the underlying molecular mechanisms leading to platelet storage lesion. Future aspects of proteomics in blood banking will aim to make use of protein markers identified for platelet storage lesion development to monitor proteome changes when alterations such as the use of additive solutions or pathogen reduction strategies are put in place in order to improve platelet quality for patients. (c) 2009 Elsevier B.V. All rights reserved.

Can limited area NWP and/or RCM models improve on large scales inside their domain?

NASA Astrophysics Data System (ADS)

Mesinger, Fedor; Veljovic, Katarina

2017-04-01

In a paper in press in Meteorology and Atmospheric Physics at the time this abstract is being written, Mesinger and Veljovic point out four requirements that need to be fulfilled by a limited area model (LAM), be it in NWP or RCM environment, to improve on large scales inside its domain. First, NWP/RCM model needs to be run on a relatively large domain. Note that domain size in quite inexpensive compared to resolution. Second, NWP/RCM model should not use more forcing at its boundaries than required by the mathematics of the problem. That means prescribing lateral boundary conditions only at its outside boundary, with one less prognostic variable prescribed at the outflow than at the inflow parts of the boundary. Next, nudging towards the large scales of the driver model must not be used, as it would obviously be nudging in the wrong direction if the nested model can improve on large scales inside its domain. And finally, the NWP/RCM model must have features that enable development of large scales improved compared to those of the driver model. This would typically include higher resolution, but obviously does not have to. Integrations showing improvements in large scales by LAM ensemble members are summarized in the mentioned paper in press. Ensemble members referred to are run using the Eta model, and are driven by ECMWF 32-day ensemble members, initialized 0000 UTC 4 October 2012. The Eta model used is the so-called "upgraded Eta," or "sloping steps Eta," which is free of the Gallus-Klemp problem of weak flow in the lee of the bell-shaped topography, seemed to many as suggesting the eta coordinate to be ill suited for high resolution models. The "sloping steps" in fact represent a simple version of the cut cell scheme. Accuracy of forecasting the position of jet stream winds, chosen to be those of speeds greater than 45 m/s at 250 hPa, expressed by Equitable Threat (or Gilbert) skill scores adjusted to unit bias (ETSa) was taken to show the skill at large scales

The Escherichia coli Proteome: Past, Present, and Future Prospects†

PubMed Central

Han, Mee-Jung; Lee, Sang Yup

2006-01-01

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects. PMID:16760308

Automation, parallelism, and robotics for proteomics.

PubMed

Alterovitz, Gil; Liu, Jonathan; Chow, Jijun; Ramoni, Marco F

2006-07-01

The speed of the human genome project (Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C. et al., Nature 2001, 409, 860-921) was made possible, in part, by developments in automation of sequencing technologies. Before these technologies, sequencing was a laborious, expensive, and personnel-intensive task. Similarly, automation and robotics are changing the field of proteomics today. Proteomics is defined as the effort to understand and characterize proteins in the categories of structure, function and interaction (Englbrecht, C. C., Facius, A., Comb. Chem. High Throughput Screen. 2005, 8, 705-715). As such, this field nicely lends itself to automation technologies since these methods often require large economies of scale in order to achieve cost and time-saving benefits. This article describes some of the technologies and methods being applied in proteomics in order to facilitate automation within the field as well as in linking proteomics-based information with other related research areas.

Protein cleavage strategies for an improved analysis of the membrane proteome

PubMed Central

Fischer, Frank; Poetsch, Ansgar

2006-01-01

Background Membrane proteins still remain elusive in proteomic studies. This is in part due to the distribution of the amino acids lysine and arginine, which are less frequent in integral membrane proteins and almost absent in transmembrane helices. As these amino acids are cleavage targets for the commonly used protease trypsin, alternative cleavage conditions, which should improve membrane protein analysis, were tested by in silico digestion for the three organisms Saccharomyces cerevisiae, Halobacterium sp. NRC-1, and Corynebacterium glutamicum as hallmarks for eukaryotes, archea and eubacteria. Results For the membrane proteomes from all three analyzed organisms, we identified cleavage conditions that achieve better sequence and proteome coverage than trypsin. Greater improvement was obtained for bacteria than for yeast, which was attributed to differences in protein size and GRAVY. It was demonstrated for bacteriorhodopsin that the in silico predictions agree well with the experimental observations. Conclusion For all three examined organisms, it was found that a combination of chymotrypsin and staphylococcal peptidase I gave significantly better results than trypsin. As some of the improved cleavage conditions are not more elaborate than trypsin digestion and have been proven useful in practice, we suppose that the cleavage at both hydrophilic and hydrophobic amino acids should facilitate in general the analysis of membrane proteins for all organisms. PMID:16512920

Proteomics and Metabolomics: Two Emerging Areas for Legume Improvement

PubMed Central

Ramalingam, Abirami; Kudapa, Himabindu; Pazhamala, Lekha T.; Weckwerth, Wolfram; Varshney, Rajeev K.

2015-01-01

The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen) in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species, Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signaling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signaling in legumes. In this review, several

Proteomics and circadian rhythms: It’s all about signaling!

PubMed Central

Mauvoisin, Daniel; Dayon, Loïc; Gachon, Frédéric; Kussmann, Martin

2014-01-01

1. Abstract Proteomic technologies using mass spectrometry (MS) offer new perspectives in circadian biology, in particular the possibility to study posttranslational modifications (PTMs). To date, only very few studies have been carried out to decipher the rhythmicity of protein expression in mammals with large-scale proteomics. Although signaling has been shown to be of high relevance, comprehensive characterization studies of PTMs are even more rare. This review aims at describing the actual landscape of circadian proteomics and the opportunities and challenges appearing on the horizon. Emphasis was given to signaling processes for their role in metabolic heath as regulated by circadian clocks and environmental factors. Those signaling processes are expected to be better and more deeply characterized in the coming years with proteomics. PMID:25103677

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.

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis.

PubMed

Deng, Ning; Li, Zhenye; Pan, Chao; Duan, Huilong

2015-01-01

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

Proteomic Characterization of Differential Abundant Proteins Accumulated between Lower and Upper Epidermises of Fleshy Scales in Onion (Allium cepa L.) Bulbs

PubMed Central

Wu, Xiaolin

2016-01-01

The onion (Allium cepa L.) is widely planted worldwide as a valuable vegetable crop. The scales of an onion bulb are a modified type of leaf. The one-layer-cell epidermis of onion scales is commonly used as a model experimental material in botany and molecular biology. The lower epidermis (LE) and upper epidermis (UE) of onion scales display obvious differences in microscopic structure, cell differentiation and pigment synthesis; however, associated proteomic differences are unclear. LE and UE can be easily sampled as single-layer-cell tissues for comparative proteomic analysis. In this study, a proteomic approach based on 2-DE and mass spectrometry (MS) was applied to compare LE and UE of fleshy scales from yellow and red onions. We identified 47 differential abundant protein spots (representing 31 unique proteins) between LE and UE in red and yellow onions. These proteins are mainly involved in pigment synthesis, stress response, and cell division. Particularly, the differentially accumulated chalcone-flavanone isomerase and flavone O-methyltransferase 1-like in LE may result in the differences in the onion scale color between red and yellow onions. Moreover, stress-related proteins abundantly accumulated in both LE and UE. In addition, the differential accumulation of UDP-arabinopyranose mutase 1-like protein and β-1,3-glucanase in the LE may be related to the different cell sizes between LE and UE of the two types of onion. The data derived from this study provides new insight into the differences in differentiation and developmental processes between onion epidermises. This study may also make a contribution to onion breeding, such as improving resistances and changing colors. PMID:28036352

Proteomic Characterization of Differential Abundant Proteins Accumulated between Lower and Upper Epidermises of Fleshy Scales in Onion (Allium cepa L.) Bulbs.

PubMed

Wu, Si; Ning, Fen; Wu, Xiaolin; Wang, Wei

2016-01-01

The onion (Allium cepa L.) is widely planted worldwide as a valuable vegetable crop. The scales of an onion bulb are a modified type of leaf. The one-layer-cell epidermis of onion scales is commonly used as a model experimental material in botany and molecular biology. The lower epidermis (LE) and upper epidermis (UE) of onion scales display obvious differences in microscopic structure, cell differentiation and pigment synthesis; however, associated proteomic differences are unclear. LE and UE can be easily sampled as single-layer-cell tissues for comparative proteomic analysis. In this study, a proteomic approach based on 2-DE and mass spectrometry (MS) was applied to compare LE and UE of fleshy scales from yellow and red onions. We identified 47 differential abundant protein spots (representing 31 unique proteins) between LE and UE in red and yellow onions. These proteins are mainly involved in pigment synthesis, stress response, and cell division. Particularly, the differentially accumulated chalcone-flavanone isomerase and flavone O-methyltransferase 1-like in LE may result in the differences in the onion scale color between red and yellow onions. Moreover, stress-related proteins abundantly accumulated in both LE and UE. In addition, the differential accumulation of UDP-arabinopyranose mutase 1-like protein and β-1,3-glucanase in the LE may be related to the different cell sizes between LE and UE of the two types of onion. The data derived from this study provides new insight into the differences in differentiation and developmental processes between onion epidermises. This study may also make a contribution to onion breeding, such as improving resistances and changing colors.

An effect size filter improves the reproducibility in spectral counting-based comparative proteomics.

PubMed

Gregori, Josep; Villarreal, Laura; Sánchez, Alex; Baselga, José; Villanueva, Josep

2013-12-16

The microarray community has shown that the low reproducibility observed in gene expression-based biomarker discovery studies is partially due to relying solely on p-values to get the lists of differentially expressed genes. Their conclusions recommended complementing the p-value cutoff with the use of effect-size criteria. The aim of this work was to evaluate the influence of such an effect-size filter on spectral counting-based comparative proteomic analysis. The results proved that the filter increased the number of true positives and decreased the number of false positives and the false discovery rate of the dataset. These results were confirmed by simulation experiments where the effect size filter was used to evaluate systematically variable fractions of differentially expressed proteins. Our results suggest that relaxing the p-value cut-off followed by a post-test filter based on effect size and signal level thresholds can increase the reproducibility of statistical results obtained in comparative proteomic analysis. Based on our work, we recommend using a filter consisting of a minimum absolute log2 fold change of 0.8 and a minimum signal of 2-4 SpC on the most abundant condition for the general practice of comparative proteomics. The implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of the results obtained among independent laboratories and MS platforms. Quality control analysis of microarray-based gene expression studies pointed out that the low reproducibility observed in the lists of differentially expressed genes could be partially attributed to the fact that these lists are generated relying solely on p-values. Our study has established that the implementation of an effect size post-test filter improves the statistical results of spectral count-based quantitative proteomics. The results proved that the filter increased the number of true positives whereas decreased

A proteomic approach to obesity and type 2 diabetes

PubMed Central

López-Villar, Elena; Martos-Moreno, Gabriel Á; Chowen, Julie A; Okada, Shigeru; Kopchick, John J; Argente, Jesús

2015-01-01

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area. PMID:25960181

Improved technique that allows the performance of large-scale SNP genotyping on DNA immobilized by FTA technology.

PubMed

He, Hongbin; Argiro, Laurent; Dessein, Helia; Chevillard, Christophe

2007-01-01

FTA technology is a novel method designed to simplify the collection, shipment, archiving and purification of nucleic acids from a wide variety of biological sources. The number of punches that can normally be obtained from a single specimen card are often however, insufficient for the testing of the large numbers of loci required to identify genetic factors that control human susceptibility or resistance to multifactorial diseases. In this study, we propose an improved technique to perform large-scale SNP genotyping. We applied a whole genome amplification method to amplify DNA from buccal cell samples stabilized using FTA technology. The results show that using the improved technique it is possible to perform up to 15,000 genotypes from one buccal cell sample. Furthermore, the procedure is simple. We consider this improved technique to be a promising methods for performing large-scale SNP genotyping because the FTA technology simplifies the collection, shipment, archiving and purification of DNA, while whole genome amplification of FTA card bound DNA produces sufficient material for the determination of thousands of SNP genotypes.

Proteome Characterization of Leaves in Common Bean

PubMed Central

Robison, Faith M.; Heuberger, Adam L.; Brick, Mark A.; Prenni, Jessica E.

2015-01-01

Dry edible bean (Phaseolus vulgaris L.) is a globally relevant food crop. The bean genome was recently sequenced and annotated allowing for proteomics investigations aimed at characterization of leaf phenotypes important to agriculture. The objective of this study was to utilize a shotgun proteomics approach to characterize the leaf proteome and to identify protein abundance differences between two bean lines with known variation in their physiological resistance to biotic stresses. Overall, 640 proteins were confidently identified. Among these are proteins known to be involved in a variety of molecular functions including oxidoreductase activity, binding peroxidase activity, and hydrolase activity. Twenty nine proteins were found to significantly vary in abundance (p-value < 0.05) between the two bean lines, including proteins associated with biotic stress. To our knowledge, this work represents the first large scale shotgun proteomic analysis of beans and our results lay the groundwork for future studies designed to investigate the molecular mechanisms involved in pathogen resistance. PMID:28248269

Current trends in quantitative proteomics - an update.

PubMed

Li, H; Han, J; Pan, J; Liu, T; Parker, C E; Borchers, C H

2017-05-01

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Science, marketing and wishful thinking in quantitative proteomics.

PubMed

Hackett, Murray

2008-11-01

In a recent editorial (J. Proteome Res. 2007, 6, 1633) and elsewhere questions have been raised regarding the lack of attention paid to good analytical practice with respect to the reporting of quantitative results in proteomics. Using those comments as a starting point, several issues are discussed that relate to the challenges involved in achieving adequate sampling with MS-based methods in order to generate valid data for large-scale studies. The discussion touches on the relationships that connect sampling depth and the power to detect protein abundance change, conflict of interest, and strategies to overcome bureaucratic obstacles that impede the use of peer-to-peer technologies for transfer and storage of large data files generated in such experiments.

Evolution of complete proteomes: guanine-cytosine pressure, phylogeny and environmental influences blend the proteomic architecture

PubMed Central

2013-01-01

Background Guanine-cytosine (GC) composition is an important feature of genomes. Likewise, amino acid composition is a distinct, but less valued, feature of proteomes. A major concern is that it is not clear what valuable information can be acquired from amino acid composition data. To address this concern, in-depth analyses of the amino acid composition of the complete proteomes from 63 archaea, 270 bacteria, and 128 eukaryotes were performed. Results Principal component analysis of the amino acid matrices showed that the main contributors to proteomic architecture were genomic GC variation, phylogeny, and environmental influences. GC pressure drove positive selection on Ala, Arg, Gly, Pro, Trp, and Val, and adverse selection on Asn, Lys, Ile, Phe, and Tyr. The physico-chemical framework of the complete proteomes withstood GC pressure by frequency complementation of GC-dependent amino acid pairs with similar physico-chemical properties. Gln, His, Ser, and Val were responsible for phylogeny and their constituted components could differentiate archaea, bacteria, and eukaryotes. Environmental niche was also a significant factor in determining proteomic architecture, especially for archaea for which the main amino acids were Cys, Leu, and Thr. In archaea, hyperthermophiles, acidophiles, mesophiles, psychrophiles, and halophiles gathered successively along the environment-based principal component. Concordance between proteomic architecture and the genetic code was also related closely to genomic GC content, phylogeny, and lifestyles. Conclusions Large-scale analyses of the complete proteomes of a wide range of organisms suggested that amino acid composition retained the trace of GC variation, phylogeny, and environmental influences during evolution. The findings from this study will help in the development of a global understanding of proteome evolution, and even biological evolution. PMID:24088322

Brucella proteomes--a review.

PubMed

DelVecchio, Vito G; Wagner, Mary Ann; Eschenbrenner, Michel; Horn, Troy A; Kraycer, Jo Ann; Estock, Frank; Elzer, Phil; Mujer, Cesar V

2002-12-20

The proteomes of selected Brucella spp. have been extensively analyzed by utilizing current proteomic technology involving 2-DE and MALDI-MS. In Brucella melitensis, more than 500 proteins were identified. The rapid and large-scale identification of proteins in this organism was accomplished by using the annotated B. melitensis genome which is now available in the GenBank. Coupled with new and powerful tools for data analysis, differentially expressed proteins were identified and categorized into several classes. A global overview of protein expression patterns emerged, thereby facilitating the simultaneous analysis of different metabolic pathways in B. melitensis. Such a global characterization would not have been possible by using time consuming and traditional biochemical approaches. The era of post-genomic technology offers new and exciting opportunities to understand the complete biology of different Brucella species.

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders.

PubMed

Cehofski, Lasse Jørgensen; Honoré, Bent; Vorum, Henrik

2017-04-28

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions.

FunRich proteomics software analysis, let the fun begin!

PubMed

Benito-Martin, Alberto; Peinado, Héctor

2015-08-01

Protein MS analysis is the preferred method for unbiased protein identification. It is normally applied to a large number of both small-scale and high-throughput studies. However, user-friendly computational tools for protein analysis are still needed. In this issue, Mathivanan and colleagues (Proteomics 2015, 15, 2597-2601) report the development of FunRich software, an open-access software that facilitates the analysis of proteomics data, providing tools for functional enrichment and interaction network analysis of genes and proteins. FunRich is a reinterpretation of proteomic software, a standalone tool combining ease of use with customizable databases, free access, and graphical representations. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-scale interaction profiling of PDZ domains through proteomic peptide-phage display using human and viral phage peptidomes.

PubMed

Ivarsson, Ylva; Arnold, Roland; McLaughlin, Megan; Nim, Satra; Joshi, Rakesh; Ray, Debashish; Liu, Bernard; Teyra, Joan; Pawson, Tony; Moffat, Jason; Li, Shawn Shun-Cheng; Sidhu, Sachdev S; Kim, Philip M

2014-02-18

The human proteome contains a plethora of short linear motifs (SLiMs) that serve as binding interfaces for modular protein domains. Such interactions are crucial for signaling and other cellular processes, but are difficult to detect because of their low to moderate affinities. Here we developed a dedicated approach, proteomic peptide-phage display (ProP-PD), to identify domain-SLiM interactions. Specifically, we generated phage libraries containing all human and viral C-terminal peptides using custom oligonucleotide microarrays. With these libraries we screened the nine PSD-95/Dlg/ZO-1 (PDZ) domains of human Densin-180, Erbin, Scribble, and Disks large homolog 1 for peptide ligands. We identified several known and putative interactions potentially relevant to cellular signaling pathways and confirmed interactions between full-length Scribble and the target proteins β-PIX, plakophilin-4, and guanylate cyclase soluble subunit α-2 using colocalization and coimmunoprecipitation experiments. The affinities of recombinant Scribble PDZ domains and the synthetic peptides representing the C termini of these proteins were in the 1- to 40-μM range. Furthermore, we identified several well-established host-virus protein-protein interactions, and confirmed that PDZ domains of Scribble interact with the C terminus of Tax-1 of human T-cell leukemia virus with micromolar affinity. Previously unknown putative viral protein ligands for the PDZ domains of Scribble and Erbin were also identified. Thus, we demonstrate that our ProP-PD libraries are useful tools for probing PDZ domain interactions. The method can be extended to interrogate all potential eukaryotic, bacterial, and viral SLiMs and we suggest it will be a highly valuable approach for studying cellular and pathogen-host protein-protein interactions.

Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast

PubMed Central

Dephoure, Noah; Hwang, Sunyoung; O'Sullivan, Ciara; Dodgson, Stacie E; Gygi, Steven P; Amon, Angelika; Torres, Eduardo M

2014-01-01

Aneuploidy causes severe developmental defects and is a near universal feature of tumor cells. Despite its profound effects, the cellular processes affected by aneuploidy are not well characterized. Here, we examined the consequences of aneuploidy on the proteome of aneuploid budding yeast strains. We show that although protein levels largely scale with gene copy number, subunits of multi-protein complexes are notable exceptions. Posttranslational mechanisms attenuate their expression when their encoding genes are in excess. Our proteomic analyses further revealed a novel aneuploidy-associated protein expression signature characteristic of altered metabolism and redox homeostasis. Indeed aneuploid cells harbor increased levels of reactive oxygen species (ROS). Interestingly, increased protein turnover attenuates ROS levels and this novel aneuploidy-associated signature and improves the fitness of most aneuploid strains. Our results show that aneuploidy causes alterations in metabolism and redox homeostasis. Cells respond to these alterations through both transcriptional and posttranscriptional mechanisms. DOI: http://dx.doi.org/10.7554/eLife.03023.001 PMID:25073701

Improvement of Baltic proper water quality using large-scale ecological engineering.

PubMed

Stigebrandt, Anders; Gustafsson, Bo G

2007-04-01

Eutrophication of the Baltic proper has led to impaired water quality, demonstrated by, e.g., extensive blooming of cyanobacteria during the premium summer holiday season and severe oxygen deficit in the deepwater. Sustainable improvements in water quality by the reduction of phosphorus (P) supplies will take several decades before giving full effects because of large P storages both in soils in the watershed and in the water column and bottom sediments of the Baltic proper. In this article it is shown that drastically improved water quality may be obtained within a few years using large-scale ecological engineering methods. Natural variations in the Baltic proper during the last decades have demonstrated how rapid improvements may be achieved. The present article describes the basic dynamics of P, organic matter, and oxygen in the Baltic proper. It also briefly discusses the advantages and disadvantages of different classes of methods of ecological engineering aimed at restoring the Baltic proper from eutrophication effects. Preliminary computations show that the P content might be halved within a few years if about 100 kg O2 s(-1) are supplied to the upper deepwater. This would require 100 pump stations, each transporting about 100 m3 s(-1) of oxygen-rich so-called winter water from about 50 to 125 m depth where the water is released as a buoyant jet. Each pump station needs a power supply of 0.6 MW. Offshore wind power technology seems mature enough to provide the power needed by the pump stations. The cost to install 100 wind-powered pump stations, each with 0.6 MW power, at about 125-m depth is about 200 million Euros.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes.

PubMed

Razban, Rostam M; Gilson, Amy I; Durfee, Niamh; Strobelt, Hendrik; Dinkla, Kasper; Choi, Jeong-Mo; Pfister, Hanspeter; Shakhnovich, Eugene I

2018-05-08

Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the S. cerevisiae and E. coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level. We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S. cerevisiae and E. coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution (Dokholyan et al., 2002). Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.49 (p-value<10-10) and -0.46 (p-value<10-10) for S. cerevisiae and E. coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant (Zhang and Yang, 2015). ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu. Supplementary data are available at Bioinformatics. shakhnovich@chemistry.harvard.edu.

Potential for geophysical experiments in large scale tests.

USGS Publications Warehouse

Dieterich, J.H.

1981-01-01

Potential research applications for large-specimen geophysical experiments include measurements of scale dependence of physical parameters and examination of interactions with heterogeneities, especially flaws such as cracks. In addition, increased specimen size provides opportunities for improved recording resolution and greater control of experimental variables. Large-scale experiments using a special purpose low stress (100MPa).-Author

Improving Large-Scale Image Retrieval Through Robust Aggregation of Local Descriptors.

PubMed

Husain, Syed Sameed; Bober, Miroslaw

2017-09-01

Visual search and image retrieval underpin numerous applications, however the task is still challenging predominantly due to the variability of object appearance and ever increasing size of the databases, often exceeding billions of images. Prior art methods rely on aggregation of local scale-invariant descriptors, such as SIFT, via mechanisms including Bag of Visual Words (BoW), Vector of Locally Aggregated Descriptors (VLAD) and Fisher Vectors (FV). However, their performance is still short of what is required. This paper presents a novel method for deriving a compact and distinctive representation of image content called Robust Visual Descriptor with Whitening (RVD-W). It significantly advances the state of the art and delivers world-class performance. In our approach local descriptors are rank-assigned to multiple clusters. Residual vectors are then computed in each cluster, normalized using a direction-preserving normalization function and aggregated based on the neighborhood rank. Importantly, the residual vectors are de-correlated and whitened in each cluster before aggregation, leading to a balanced energy distribution in each dimension and significantly improved performance. We also propose a new post-PCA normalization approach which improves separability between the matching and non-matching global descriptors. This new normalization benefits not only our RVD-W descriptor but also improves existing approaches based on FV and VLAD aggregation. Furthermore, we show that the aggregation framework developed using hand-crafted SIFT features also performs exceptionally well with Convolutional Neural Network (CNN) based features. The RVD-W pipeline outperforms state-of-the-art global descriptors on both the Holidays and Oxford datasets. On the large scale datasets, Holidays1M and Oxford1M, SIFT-based RVD-W representation obtains a mAP of 45.1 and 35.1 percent, while CNN-based RVD-W achieve a mAP of 63.5 and 44.8 percent, all yielding superior performance to the

A Review: Proteomics in Retinal Artery Occlusion, Retinal Vein Occlusion, Diabetic Retinopathy and Acquired Macular Disorders

PubMed Central

Cehofski, Lasse Jørgensen; Honoré, Bent; Vorum, Henrik

2017-01-01

Retinal artery occlusion (RAO), retinal vein occlusion (RVO), diabetic retinopathy (DR) and age-related macular degeneration (AMD) are frequent ocular diseases with potentially sight-threatening outcomes. In the present review we discuss major findings of proteomic studies of RAO, RVO, DR and AMD, including an overview of ocular proteome changes associated with anti-vascular endothelial growth factor (VEGF) treatments. Despite the severe outcomes of RAO, the proteome of the disease remains largely unstudied. There is also limited knowledge about the proteome of RVO, but proteomic studies suggest that RVO is associated with remodeling of the extracellular matrix and adhesion processes. Proteomic studies of DR have resulted in the identification of potential therapeutic targets such as carbonic anhydrase-I. Proliferative diabetic retinopathy is the most intensively studied stage of DR. Proteomic studies have established VEGF, pigment epithelium-derived factor (PEDF) and complement components as key factors associated with AMD. The aim of this review is to highlight the major milestones in proteomics in RAO, RVO, DR and AMD. Through large-scale protein analyses, proteomics is bringing new important insights into these complex pathological conditions. PMID:28452939

Unifying expression scale for peptide hydrophobicity in proteomic reversed phase high-pressure liquid chromatography experiments.

PubMed

Grigoryan, Marine; Shamshurin, Dmitry; Spicer, Victor; Krokhin, Oleg V

2013-11-19

As an initial step in our efforts to unify the expression of peptide retention times in proteomic liquid chromatography-mass spectrometry (LC-MS) experiments, we aligned the chromatographic properties of a number of peptide retention standards against a collection of peptides commonly observed in proteomic experiments. The standard peptide mixtures and tryptic digests of samples of different origins were separated under the identical chromatographic condition most commonly employed in proteomics: 100 Å C18 sorbent with 0.1% formic acid as an ion-pairing modifier. Following our original approach (Krokhin, O. V.; Spicer, V. Anal. Chem. 2009, 81, 9522-9530) the retention characteristics of these standards and collection of tryptic peptides were mapped into hydrophobicity index (HI) or acetonitrile percentage units. This scale allows for direct visualization of the chromatographic outcome of LC-MS acquisitions, monitors the performance of the gradient LC system, and simplifies method development and interlaboratory data alignment. Wide adoption of this approach would significantly aid understanding the basic principles of gradient peptide RP-HPLC and solidify our collective efforts in acquiring confident peptide retention libraries, a key component in the development of targeted proteomic approaches.

Low Cost, Scalable Proteomics Data Analysis Using Amazon's Cloud Computing Services and Open Source Search Algorithms

PubMed Central

Halligan, Brian D.; Geiger, Joey F.; Vallejos, Andrew K.; Greene, Andrew S.; Twigger, Simon N.

2009-01-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step by step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center website (http://proteomics.mcw.edu/vipdac). PMID:19358578

Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.

PubMed

Halligan, Brian D; Geiger, Joey F; Vallejos, Andrew K; Greene, Andrew S; Twigger, Simon N

2009-06-01

One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).

Comparative evaluation of saliva collection methods for proteome analysis.

PubMed

Golatowski, Claas; Salazar, Manuela Gesell; Dhople, Vishnu Mukund; Hammer, Elke; Kocher, Thomas; Jehmlich, Nico; Völker, Uwe

2013-04-18

Saliva collection devices are widely used for large-scale screening approaches. This study was designed to compare the suitability of three different whole-saliva collection approaches for subsequent proteome analyses. From 9 young healthy volunteers (4 women and 5 men) saliva samples were collected either unstimulated by passive drooling or stimulated using a paraffin gum or Salivette® (cotton swab). Saliva volume, protein concentration and salivary protein patterns were analyzed comparatively. Samples collected using paraffin gum showed the highest saliva volume (4.1±1.5 ml) followed by Salivette® collection (1.8±0.4 ml) and drooling (1.0±0.4 ml). Saliva protein concentrations (average 1145 μg/ml) showed no significant differences between the three sampling schemes. Each collection approach facilitated the identification of about 160 proteins (≥2 distinct peptides) per subject, but collection-method dependent variations in protein composition were observed. Passive drooling, paraffin gum and Salivette® each allows similar coverage of the whole saliva proteome, but the specific proteins observed depended on the collection approach. Thus, only one type of collection device should be used for quantitative proteome analysis in one experiment, especially when performing large-scale cross-sectional or multi-centric studies. Copyright © 2013 Elsevier B.V. All rights reserved.

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach

Comparative bioinformatics analyses and profiling of lysosome-related organelle proteomes

NASA Astrophysics Data System (ADS)

Hu, Zhang-Zhi; Valencia, Julio C.; Huang, Hongzhan; Chi, An; Shabanowitz, Jeffrey; Hearing, Vincent J.; Appella, Ettore; Wu, Cathy

2007-01-01

Complete and accurate profiling of cellular organelle proteomes, while challenging, is important for the understanding of detailed cellular processes at the organelle level. Mass spectrometry technologies coupled with bioinformatics analysis provide an effective approach for protein identification and functional interpretation of organelle proteomes. In this study, we have compiled human organelle reference datasets from large-scale proteomic studies and protein databases for seven lysosome-related organelles (LROs), as well as the endoplasmic reticulum and mitochondria, for comparative organelle proteome analysis. Heterogeneous sources of human organelle proteins and rodent homologs are mapped to human UniProtKB protein entries based on ID and/or peptide mappings, followed by functional annotation and categorization using the iProXpress proteomic expression analysis system. Cataloging organelle proteomes allows close examination of both shared and unique proteins among various LROs and reveals their functional relevance. The proteomic comparisons show that LROs are a closely related family of organelles. The shared proteins indicate the dynamic and hybrid nature of LROs, while the unique transmembrane proteins may represent additional candidate marker proteins for LROs. This comparative analysis, therefore, provides a basis for hypothesis formulation and experimental validation of organelle proteins and their functional roles.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research.

PubMed

Zürbig, Petra; Jahn, Holger

2012-12-01

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-01-01

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

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

A proteomic approach to obesity and type 2 diabetes.

PubMed

López-Villar, Elena; Martos-Moreno, Gabriel Á; Chowen, Julie A; Okada, Shigeru; Kopchick, John J; Argente, Jesús

2015-07-01

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area. © 2015 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Designing a Large-Scale Multilevel Improvement Initiative: The Improving Performance in Practice Program

ERIC Educational Resources Information Center

Margolis, Peter A.; DeWalt, Darren A.; Simon, Janet E.; Horowitz, Sheldon; Scoville, Richard; Kahn, Norman; Perelman, Robert; Bagley, Bruce; Miles, Paul

2010-01-01

Improving Performance in Practice (IPIP) is a large system intervention designed to align efforts and motivate the creation of a tiered system of improvement at the national, state, practice, and patient levels, assisting primary-care physicians and their practice teams to assess and measurably improve the quality of care for chronic illness and…

Mass Defect Labeling of Cysteine for Improving Peptide Assignment in Shotgun Proteomic Analyses

PubMed Central

Hernandez, Hilda; Niehauser, Sarah; Boltz, Stacey A.; Gawandi, Vijay; Phillips, Robert S.; Amster, I. Jonathan

2006-01-01

A method for improving the identification of peptides in a shotgun proteome analysis using accurate mass measurement has been developed. The improvement is based upon the derivatization of cysteine residues with a novel reagent, 2,4-dibromo-(2′-iodo)acetanilide. The derivitization changes the mass defect of cysteine-containing proteolytic peptides in a manner that increases their identification specificity. Peptide masses were measured using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron mass spectrometry. Reactions with protein standards show that the derivatization of cysteine is rapid and quantitative, and the data suggest that the derivatized peptides are more easily ionized or detected than unlabeled cysteine-containing peptides. The reagent was tested on a 15N-metabolically labeled proteome from M. maripaludis. Proteins were identified by their accurate mass values and from their nitrogen stoichiometry. A total of 47% of the labeled peptides are identified versus 27% for the unlabeled peptides. This procedure permits the identification of proteins from the M. maripaludis proteome that are not usually observed by the standard protocol and shows that better protein coverage is obtained with this methodology. PMID:16689545

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

Comparing Simplification Strategies for the Skeletal Muscle Proteome

PubMed Central

Geary, Bethany; Young, Iain S.; Cash, Phillip; Whitfield, Phillip D.; Doherty, Mary K.

2016-01-01

Skeletal muscle is a complex tissue that is dominated by the presence of a few abundant proteins. This wide dynamic range can mask the presence of lower abundance proteins, which can be a confounding factor in large-scale proteomic experiments. In this study, we have investigated a number of pre-fractionation methods, at both the protein and peptide level, for the characterization of the skeletal muscle proteome. The analyses revealed that the use of OFFGEL isoelectric focusing yielded the largest number of protein identifications (>750) compared to alternative gel-based and protein equalization strategies. Further, OFFGEL led to a substantial enrichment of a different sub-population of the proteome. Filter-aided sample preparation (FASP), coupled to peptide-level OFFGEL provided more confidence in the results due to a substantial increase in the number of peptides assigned to each protein. The findings presented here support the use of a multiplexed approach to proteome characterization of skeletal muscle, which has a recognized imbalance in the dynamic range of its protein complement. PMID:28248220

The online Tabloid Proteome: an annotated database of protein associations

PubMed Central

Turan, Demet; Tavernier, Jan

2018-01-01

Abstract A complete knowledge of the proteome can only be attained by determining the associations between proteins, along with the nature of these associations (e.g. physical contact in protein–protein interactions, participation in complex formation or different roles in the same pathway). Despite extensive efforts in elucidating direct protein interactions, our knowledge on the complete spectrum of protein associations remains limited. We therefore developed a new approach that detects protein associations from identifications obtained after re-processing of large-scale, public mass spectrometry-based proteomics data. Our approach infers protein association based on the co-occurrence of proteins across many different proteomics experiments, and provides information that is almost completely complementary to traditional direct protein interaction studies. We here present a web interface to query and explore the associations derived from this method, called the online Tabloid Proteome. The online Tabloid Proteome also integrates biological knowledge from several existing resources to annotate our derived protein associations. The online Tabloid Proteome is freely available through a user-friendly web interface, which provides intuitive navigation and data exploration options for the user at http://iomics.ugent.be/tabloidproteome. PMID:29040688

A large synthetic peptide and phosphopeptide reference library for mass spectrometry-based proteomics.

PubMed

Marx, Harald; Lemeer, Simone; Schliep, Jan Erik; Matheron, Lucrece; Mohammed, Shabaz; Cox, Jürgen; Mann, Matthias; Heck, Albert J R; Kuster, Bernhard

2013-06-01

We present a peptide library and data resource of >100,000 synthetic, unmodified peptides and their phosphorylated counterparts with known sequences and phosphorylation sites. Analysis of the library by mass spectrometry yielded a data set that we used to evaluate the merits of different search engines (Mascot and Andromeda) and fragmentation methods (beam-type collision-induced dissociation (HCD) and electron transfer dissociation (ETD)) for peptide identification. We also compared the sensitivities and accuracies of phosphorylation-site localization tools (Mascot Delta Score, PTM score and phosphoRS), and we characterized the chromatographic behavior of peptides in the library. We found that HCD identified more peptides and phosphopeptides than did ETD, that phosphopeptides generally eluted later from reversed-phase columns and were easier to identify than unmodified peptides and that current computational tools for proteomics can still be substantially improved. These peptides and spectra will facilitate the development, evaluation and improvement of experimental and computational proteomic strategies, such as separation techniques and the prediction of retention times and fragmentation patterns.

Screening of missing proteins in the human liver proteome by improved MRM-approach-based targeted proteomics.

PubMed

Chen, Chen; Liu, Xiaohui; Zheng, Weimin; Zhang, Lei; Yao, Jun; Yang, Pengyuan

2014-04-04

To completely annotate the human genome, the task of identifying and characterizing proteins that currently lack mass spectrometry (MS) evidence is inevitable and urgent. In this study, as the first effort to screen missing proteins in large scale, we developed an approach based on SDS-PAGE followed by liquid chromatography-multiple reaction monitoring (LC-MRM), for screening of those missing proteins with only a single peptide hit in the previous liver proteome data set. Proteins extracted from normal human liver were separated in SDS-PAGE and digested in split gel slice, and the resulting digests were then subjected to LC-schedule MRM analysis. The MRM assays were developed through synthesized crude peptides for target peptides. In total, the expressions of 57 target proteins were confirmed from 185 MRM assays in normal human liver tissues. Among the proved 57 one-hit wonders, 50 proteins are of the minimally redundant set in the PeptideAtlas database, 7 proteins even have none MS-based information previously in various biological processes. We conclude that our SDS-PAGE-MRM workflow can be a powerful approach to screen missing or poorly characterized proteins in different samples and to provide their quantity if detected. The MRM raw data have been uploaded to ISB/SRM Atlas/PASSEL (PXD000648).

Improved Quantitative Plant Proteomics via the Combination of Targeted and Untargeted Data Acquisition

PubMed Central

Hart-Smith, Gene; Reis, Rodrigo S.; Waterhouse, Peter M.; Wilkins, Marc R.

2017-01-01

Quantitative proteomics strategies – which are playing important roles in the expanding field of plant molecular systems biology – are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) – referred to as TDA/DDA – to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA

Fast and Accurate Protein False Discovery Rates on Large-Scale Proteomics Data Sets with Percolator 3.0

NASA Astrophysics Data System (ADS)

The, Matthew; MacCoss, Michael J.; Noble, William S.; Käll, Lukas

2016-11-01

Percolator is a widely used software tool that increases yield in shotgun proteomics experiments and assigns reliable statistical confidence measures, such as q values and posterior error probabilities, to peptides and peptide-spectrum matches (PSMs) from such experiments. Percolator's processing speed has been sufficient for typical data sets consisting of hundreds of thousands of PSMs. With our new scalable approach, we can now also analyze millions of PSMs in a matter of minutes on a commodity computer. Furthermore, with the increasing awareness for the need for reliable statistics on the protein level, we compared several easy-to-understand protein inference methods and implemented the best-performing method—grouping proteins by their corresponding sets of theoretical peptides and then considering only the best-scoring peptide for each protein—in the Percolator package. We used Percolator 3.0 to analyze the data from a recent study of the draft human proteome containing 25 million spectra (PM:24870542). The source code and Ubuntu, Windows, MacOS, and Fedora binary packages are available from http://percolator.ms/ under an Apache 2.0 license.

Fast and Accurate Protein False Discovery Rates on Large-Scale Proteomics Data Sets with Percolator 3.0.

PubMed

The, Matthew; MacCoss, Michael J; Noble, William S; Käll, Lukas

2016-11-01

Percolator is a widely used software tool that increases yield in shotgun proteomics experiments and assigns reliable statistical confidence measures, such as q values and posterior error probabilities, to peptides and peptide-spectrum matches (PSMs) from such experiments. Percolator's processing speed has been sufficient for typical data sets consisting of hundreds of thousands of PSMs. With our new scalable approach, we can now also analyze millions of PSMs in a matter of minutes on a commodity computer. Furthermore, with the increasing awareness for the need for reliable statistics on the protein level, we compared several easy-to-understand protein inference methods and implemented the best-performing method-grouping proteins by their corresponding sets of theoretical peptides and then considering only the best-scoring peptide for each protein-in the Percolator package. We used Percolator 3.0 to analyze the data from a recent study of the draft human proteome containing 25 million spectra (PM:24870542). The source code and Ubuntu, Windows, MacOS, and Fedora binary packages are available from http://percolator.ms/ under an Apache 2.0 license. Graphical Abstract ᅟ.

The Proteome Folding Project: Proteome-scale prediction of structure and function

PubMed Central

Drew, Kevin; Winters, Patrick; Butterfoss, Glenn L.; Berstis, Viktors; Uplinger, Keith; Armstrong, Jonathan; Riffle, Michael; Schweighofer, Erik; Bovermann, Bill; Goodlett, David R.; Davis, Trisha N.; Shasha, Dennis; Malmström, Lars; Bonneau, Richard

2011-01-01

The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis, rice, mouse, fly, yeast, Escherichia coli, and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions. PMID:21824995

Combinatorial Approach for Large-scale Identification of Linked Peptides from Tandem Mass Spectrometry Spectra*

PubMed Central

Wang, Jian; Anania, Veronica G.; Knott, Jeff; Rush, John; Lill, Jennie R.; Bourne, Philip E.; Bandeira, Nuno

2014-01-01

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein–protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides. PMID:24493012

Highly multiplexed targeted proteomics using precise control of peptide retention time.

PubMed

Gallien, Sebastien; Peterman, Scott; Kiyonami, Reiko; Souady, Jamal; Duriez, Elodie; Schoen, Alan; Domon, Bruno

2012-04-01

Large-scale proteomics applications using SRM analysis on triple quadrupole mass spectrometers present new challenges to LC-MS/MS experimental design. Despite the automation of building large-scale LC-SRM methods, the increased numbers of targeted peptides can compromise the balance between sensitivity and selectivity. To facilitate large target numbers, time-scheduled SRM transition acquisition is performed. Previously published results have demonstrated incorporation of a well-characterized set of synthetic peptides enabled chromatographic characterization of the elution profile for most endogenous peptides. We have extended this application of peptide trainer kits to not only build SRM methods but to facilitate real-time elution profile characterization that enables automated adjustment of the scheduled detection windows. Incorporation of dynamic retention time adjustments better facilitate targeted assays lasting several days without the need for constant supervision. This paper provides an overview of how the dynamic retention correction approach identifies and corrects for commonly observed LC variations. This adjustment dramatically improves robustness in targeted discovery experiments as well as routine quantification experiments. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High throughput profile-profile based fold recognition for the entire human proteome.

PubMed

McGuffin, Liam J; Smith, Richard T; Bryson, Kevin; Sørensen, Søren-Aksel; Jones, David T

2006-06-07

In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

Recent advances in micro-scale and nano-scale high-performance liquid-phase chromatography for proteome research.

PubMed

Tao, Dingyin; Zhang, Lihua; Shan, Yichu; Liang, Zhen; Zhang, Yukui

2011-01-01

High-performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI-MS-MS) is regarded as one of the most powerful techniques for separation and identification of proteins. Recently, much effort has been made to improve the separation capacity, detection sensitivity, and analysis throughput of micro- and nano-HPLC, by increasing column length, reducing column internal diameter, and using integrated techniques. Development of HPLC columns has also been rapid, as a result of the use of submicrometer packing materials and monolithic columns. All these innovations result in clearly improved performance of micro- and nano-HPLC for proteome research.

Large-scale model quality assessment for improving protein tertiary structure prediction.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-06-15

Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

PubMed

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes

PubMed Central

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V.; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J.; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wiśniewski, Jacek R.; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools. PMID:17090601

Large-Scale SRM Screen of Urothelial Bladder Cancer Candidate Biomarkers in Urine.

PubMed

Duriez, Elodie; Masselon, Christophe D; Mesmin, Cédric; Court, Magali; Demeure, Kevin; Allory, Yves; Malats, Núria; Matondo, Mariette; Radvanyi, François; Garin, Jérôme; Domon, Bruno

2017-04-07

Urothelial bladder cancer is a condition associated with high recurrence and substantial morbidity and mortality. Noninvasive urinary tests that would detect bladder cancer and tumor recurrence are required to significantly improve patient care. Over the past decade, numerous bladder cancer candidate biomarkers have been identified in the context of extensive proteomics or transcriptomics studies. To translate these findings in clinically useful biomarkers, the systematic evaluation of these candidates remains the bottleneck. Such evaluation involves large-scale quantitative LC-SRM (liquid chromatography-selected reaction monitoring) measurements, targeting hundreds of signature peptides by monitoring thousands of transitions in a single analysis. The design of highly multiplexed SRM analyses is driven by several factors: throughput, robustness, selectivity and sensitivity. Because of the complexity of the samples to be analyzed, some measurements (transitions) can be interfered by coeluting isobaric species resulting in biased or inconsistent estimated peptide/protein levels. Thus the assessment of the quality of SRM data is critical to allow flagging these inconsistent data. We describe an efficient and robust method to process large SRM data sets, including the processing of the raw data, the detection of low-quality measurements, the normalization of the signals for each protein, and the estimation of protein levels. Using this methodology, a variety of proteins previously associated with bladder cancer have been assessed through the analysis of urine samples from a large cohort of cancer patients and corresponding controls in an effort to establish a priority list of most promising candidates to guide subsequent clinical validation studies.

Next-Generation Proteomics and Its Application to Clinical Breast Cancer Research.

PubMed

Mardamshina, Mariya; Geiger, Tamar

2017-10-01

Proteomics technology aims to map the protein landscapes of biological samples, and it can be applied to a variety of samples, including cells, tissues, and body fluids. Because the proteins are the main functional molecules in the cells, their levels reflect much more accurately the cellular phenotype and the regulatory processes within them than gene levels, mutations, and even mRNA levels. With the advancement in the technology, it is possible now to obtain comprehensive views of the biological systems and to study large patient cohorts in a streamlined manner. In this review we discuss the technological advancements in mass spectrometry-based proteomics, which allow analysis of breast cancer tissue samples, leading to the first large-scale breast cancer proteomics studies. Furthermore, we discuss the technological developments in blood-based biomarker discovery, which provide the basis for future development of assays for routine clinical use. Although these are only the first steps in implementation of proteomics into the clinic, extensive collaborative work between these worlds will undoubtedly lead to major discoveries and advances in clinical practice. Copyright © 2017 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

iTRAQ-based quantitative proteomic analysis reveals proteomic changes in three fenoxaprop-P-ethyl-resistant Beckmannia syzigachne biotypes with differing ACCase mutations.

PubMed

Pan, Lang; Zhang, Jian; Wang, Junzhi; Yu, Qin; Bai, Lianyang; Dong, Liyao

2017-05-08

American sloughgrass (Beckmannia syzigachne Steud.) is a weed widely distributed in wheat fields of China. In recent years, the evolution of herbicide (fenoxaprop-P-ethyl)-resistant populations has decreased the susceptibility of B. syzigachne. This study compared 4 B. syzigachne populations (3 resistant and 1 susceptible) using iTRAQ to characterize fenoxaprop-P-ethyl resistance in B. syzigachne at the proteomic level. Through searching the UniProt database, 3104 protein species were identified from 13,335 unique peptides. Approximately 2834 protein species were assigned to 23 functional classifications provided by the COG database. Among these, 2299 protein species were assigned to 125 predicted pathways. The resistant biotype contained 8 protein species that changed in abundance relative to the susceptible biotype; they were involved in photosynthesis, oxidative phosphorylation, and fatty acid biosynthesis pathways. In contrast to previous studies comparing only 1 resistant and 1 susceptible population, our use of 3 fenoxaprop-resistant B. syzigachne populations with different genetic backgrounds minimized irrelevant differential expression and eliminated false positives. Therefore, we could more confidently link the differentially expressed proteins to herbicide resistance. Proteomic analysis demonstrated that fenoxaprop-P-ethyl resistance is associated with photosynthetic capacity, a connection that might be related to the target-site mutations in resistant B. syzigachne. This is the first large-scale proteomics study examining herbicide stress responses in different B. syzigachne biotypes. This study has biological relevance because it is the first to employ proteomic analysis for understanding the mechanisms underlying Beckmannia syzigachne herbicide resistance. The plant is a major weed in China and negatively affects crop yield, but has developed considerable resistance to the most common herbicide, fenoxaprop-P-ethyl. Through comparisons of resistant and

Enablers and Barriers to Large-Scale Uptake of Improved Solid Fuel Stoves: A Systematic Review

PubMed Central

Puzzolo, Elisa; Stanistreet, Debbi; Pope, Daniel; Bruce, Nigel G.

2013-01-01

Background: Globally, 2.8 billion people rely on household solid fuels. Reducing the resulting adverse health, environmental, and development consequences will involve transitioning through a mix of clean fuels and improved solid fuel stoves (IS) of demonstrable effectiveness. To date, achieving uptake of IS has presented significant challenges. Objectives: We performed a systematic review of factors that enable or limit large-scale uptake of IS in low- and middle-income countries. Methods: We conducted systematic searches through multidisciplinary databases, specialist websites, and consulting experts. The review drew on qualitative, quantitative, and case studies and used standardized methods for screening, data extraction, critical appraisal, and synthesis. We summarized our findings as “factors” relating to one of seven domains—fuel and technology characteristics; household and setting characteristics; knowledge and perceptions; finance, tax, and subsidy aspects; market development; regulation, legislation, and standards; programmatic and policy mechanisms—and also recorded issues that impacted equity. Results: We identified 31 factors influencing uptake from 57 studies conducted in Asia, Africa, and Latin America. All domains matter. Although factors such as offering technologies that meet household needs and save fuel, user training and support, effective financing, and facilitative government action appear to be critical, none guarantee success: All factors can be influential, depending on context. The nature of available evidence did not permit further prioritization. Conclusions: Achieving adoption and sustained use of IS at a large scale requires that all factors, spanning household/community and program/societal levels, be assessed and supported by policy. We propose a planning tool that would aid this process and suggest further research to incorporate an evaluation of effectiveness. Citation: Rehfuess EA, Puzzolo E, Stanistreet D, Pope D, Bruce

Contractual Duration and Investment Incentives: Evidence from Large Scale Production Units in China

NASA Astrophysics Data System (ADS)

Li, Fang; Feng, Shuyi; D'Haese, Marijke; Lu, Hualiang; Qu, Futian

2017-04-01

Large Scale Production Units have become important forces in the supply of agricultural commodities and agricultural modernization in China. Contractual duration in farmland transfer to Large Scale Production Units can be considered to reflect land tenure security. Theoretically, long-term tenancy contracts can encourage Large Scale Production Units to increase long-term investments by ensuring land rights stability or favoring access to credit. Using a unique Large Scale Production Units- and plot-level field survey dataset from Jiangsu and Jiangxi Province, this study aims to examine the effect of contractual duration on Large Scale Production Units' soil conservation behaviours. IV method is applied to take into account the endogeneity of contractual duration and unobserved household heterogeneity. Results indicate that farmland transfer contract duration significantly and positively affects land-improving investments. Policies aimed at improving transaction platforms and intermediary organizations in farmland transfer to facilitate Large Scale Production Units to access farmland with long-term tenancy contracts may therefore play an important role in improving soil quality and land productivity.

Proteome complexity and the forces that drive proteome imbalance.

PubMed

Harper, J Wade; Bennett, Eric J

2016-09-15

The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer.

Moon-based Earth Observation for Large Scale Geoscience Phenomena

NASA Astrophysics Data System (ADS)

Guo, Huadong; Liu, Guang; Ding, Yixing

2016-07-01

The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.

Proteomics research in India: an update.

PubMed

Reddy, Panga Jaipal; Atak, Apurva; Ghantasala, Saicharan; Kumar, Saurabh; Gupta, Shabarni; Prasad, T S Keshava; Zingde, Surekha M; Srivastava, Sanjeeva

2015-09-08

After a successful completion of the Human Genome Project, deciphering the mystery surrounding the human proteome posed a major challenge. Despite not being largely involved in the Human Genome Project, the Indian scientific community contributed towards proteomic research along with the global community. Currently, more than 76 research/academic institutes and nearly 145 research labs are involved in core proteomic research across India. The Indian researchers have been major contributors in drafting the "human proteome map" along with international efforts. In addition to this, virtual proteomics labs, proteomics courses and remote triggered proteomics labs have helped to overcome the limitations of proteomics education posed due to expensive lab infrastructure. The establishment of Proteomics Society, India (PSI) has created a platform for the Indian proteomic researchers to share ideas, research collaborations and conduct annual conferences and workshops. Indian proteomic research is really moving forward with the global proteomics community in a quest to solve the mysteries of proteomics. A draft map of the human proteome enhances the enthusiasm among intellectuals to promote proteomic research in India to the world.This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

Exact-Differential Large-Scale Traffic Simulation

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

Hanai, Masatoshi; Suzumura, Toyotaro; Theodoropoulos, Georgios

2015-01-01

Analyzing large-scale traffics by simulation needs repeating execution many times with various patterns of scenarios or parameters. Such repeating execution brings about big redundancy because the change from a prior scenario to a later scenario is very minor in most cases, for example, blocking only one of roads or changing the speed limit of several roads. In this paper, we propose a new redundancy reduction technique, called exact-differential simulation, which enables to simulate only changing scenarios in later execution while keeping exactly same results as in the case of whole simulation. The paper consists of two main efforts: (i) amore » key idea and algorithm of the exact-differential simulation, (ii) a method to build large-scale traffic simulation on the top of the exact-differential simulation. In experiments of Tokyo traffic simulation, the exact-differential simulation shows 7.26 times as much elapsed time improvement in average and 2.26 times improvement even in the worst case as the whole simulation.« less

Alternative Splicing May Not Be the Key to Proteome Complexity.

PubMed

Tress, Michael L; Abascal, Federico; Valencia, Alfonso

2017-02-01

Alternative splicing is commonly believed to be a major source of cellular protein diversity. However, although many thousands of alternatively spliced transcripts are routinely detected in RNA-seq studies, reliable large-scale mass spectrometry-based proteomics analyses identify only a small fraction of annotated alternative isoforms. The clearest finding from proteomics experiments is that most human genes have a single main protein isoform, while those alternative isoforms that are identified tend to be the most biologically plausible: those with the most cross-species conservation and those that do not compromise functional domains. Indeed, most alternative exons do not seem to be under selective pressure, suggesting that a large majority of predicted alternative transcripts may not even be translated into proteins. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

High-throughput Database Search and Large-scale Negative Polarity Liquid Chromatography–Tandem Mass Spectrometry with Ultraviolet Photodissociation for Complex Proteomic Samples*

PubMed Central

Madsen, James A.; Xu, Hua; Robinson, Michelle R.; Horton, Andrew P.; Shaw, Jared B.; Giles, David K.; Kaoud, Tamer S.; Dalby, Kevin N.; Trent, M. Stephen; Brodbelt, Jennifer S.

2013-01-01

The use of ultraviolet photodissociation (UVPD) for the activation and dissociation of peptide anions is evaluated for broader coverage of the proteome. To facilitate interpretation and assignment of the resulting UVPD mass spectra of peptide anions, the MassMatrix database search algorithm was modified to allow automated analysis of negative polarity MS/MS spectra. The new UVPD algorithms were developed based on the MassMatrix database search engine by adding specific fragmentation pathways for UVPD. The new UVPD fragmentation pathways in MassMatrix were rigorously and statistically optimized using two large data sets with high mass accuracy and high mass resolution for both MS1 and MS2 data acquired on an Orbitrap mass spectrometer for complex Halobacterium and HeLa proteome samples. Negative mode UVPD led to the identification of 3663 and 2350 peptides for the Halo and HeLa tryptic digests, respectively, corresponding to 655 and 645 peptides that were unique when compared with electron transfer dissociation (ETD), higher energy collision-induced dissociation, and collision-induced dissociation results for the same digests analyzed in the positive mode. In sum, 805 and 619 proteins were identified via UVPD for the Halobacterium and HeLa samples, respectively, with 49 and 50 unique proteins identified in contrast to the more conventional MS/MS methods. The algorithm also features automated charge determination for low mass accuracy data, precursor filtering (including intact charge-reduced peaks), and the ability to combine both positive and negative MS/MS spectra into a single search, and it is freely open to the public. The accuracy and specificity of the MassMatrix UVPD search algorithm was also assessed for low resolution, low mass accuracy data on a linear ion trap. Analysis of a known mixture of three mitogen-activated kinases yielded similar sequence coverage percentages for UVPD of peptide anions versus conventional collision-induced dissociation of

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens Using Proteomic Data from a Field Biostimulation Experiment

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

Fang, Yilin; Wilkins, Michael J.; Yabusaki, Steven B.

2012-12-12

Biomass and shotgun global proteomics data that reflected relative protein abundances from samples collected during the 2008 experiment at the U.S. Department of Energy Integrated Field-Scale Subsurface Research Challenge site in Rifle, Colorado, provided an unprecedented opportunity to validate a genome-scale metabolic model of Geobacter metallireducens and assess its performance with respect to prediction of metal reduction, biomass yield, and growth rate under dynamic field conditions. Reconstructed from annotated genomic sequence, biochemical, and physiological data, the constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes.more » Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low fluxes through amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.« less

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers.

PubMed

Runau, Franscois; Arshad, Ali; Isherwood, John; Norris, Leonie; Howells, Lynne; Metcalfe, Matthew; Dennison, Ashley

2015-06-01

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results. © 2015 American Society for Parenteral and Enteral Nutrition.

Lessons Learned from Large-Scale Randomized Experiments

ERIC Educational Resources Information Center

Slavin, Robert E.; Cheung, Alan C. K.

2017-01-01

Large-scale randomized studies provide the best means of evaluating practical, replicable approaches to improving educational outcomes. This article discusses the advantages, problems, and pitfalls of these evaluations, focusing on alternative methods of randomization, recruitment, ensuring high-quality implementation, dealing with attrition, and…

Real-time simulation of large-scale floods

NASA Astrophysics Data System (ADS)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

Fuzzy-based propagation of prior knowledge to improve large-scale image analysis pipelines

PubMed Central

Mikut, Ralf

2017-01-01

Many automatically analyzable scientific questions are well-posed and a variety of information about expected outcomes is available a priori. Although often neglected, this prior knowledge can be systematically exploited to make automated analysis operations sensitive to a desired phenomenon or to evaluate extracted content with respect to this prior knowledge. For instance, the performance of processing operators can be greatly enhanced by a more focused detection strategy and by direct information about the ambiguity inherent in the extracted data. We present a new concept that increases the result quality awareness of image analysis operators by estimating and distributing the degree of uncertainty involved in their output based on prior knowledge. This allows the use of simple processing operators that are suitable for analyzing large-scale spatiotemporal (3D+t) microscopy images without compromising result quality. On the foundation of fuzzy set theory, we transform available prior knowledge into a mathematical representation and extensively use it to enhance the result quality of various processing operators. These concepts are illustrated on a typical bioimage analysis pipeline comprised of seed point detection, segmentation, multiview fusion and tracking. The functionality of the proposed approach is further validated on a comprehensive simulated 3D+t benchmark data set that mimics embryonic development and on large-scale light-sheet microscopy data of a zebrafish embryo. The general concept introduced in this contribution represents a new approach to efficiently exploit prior knowledge to improve the result quality of image analysis pipelines. The generality of the concept makes it applicable to practically any field with processing strategies that are arranged as linear pipelines. The automated analysis of terabyte-scale microscopy data will especially benefit from sophisticated and efficient algorithms that enable a quantitative and fast readout. PMID

Improved Recovery and Identification of Membrane Proteins from Rat Hepatic Cells using a Centrifugal Proteomic Reactor*

PubMed Central

Zhou, Hu; Wang, Fangjun; Wang, Yuwei; Ning, Zhibin; Hou, Weimin; Wright, Theodore G.; Sundaram, Meenakshi; Zhong, Shumei; Yao, Zemin; Figeys, Daniel

2011-01-01

Despite their importance in many biological processes, membrane proteins are underrepresented in proteomic analysis because of their poor solubility (hydrophobicity) and often low abundance. We describe a novel approach for the identification of plasma membrane proteins and intracellular microsomal proteins that combines membrane fractionation, a centrifugal proteomic reactor for streamlined protein extraction, protein digestion and fractionation by centrifugation, and high performance liquid chromatography-electrospray ionization-tandem MS. The performance of this approach was illustrated for the study of the proteome of ER and Golgi microsomal membranes in rat hepatic cells. The centrifugal proteomic reactor identified 945 plasma membrane proteins and 955 microsomal membrane proteins, of which 63 and 47% were predicted as bona fide membrane proteins, respectively. Among these proteins, >800 proteins were undetectable by the conventional in-gel digestion approach. The majority of the membrane proteins only identified by the centrifugal proteomic reactor were proteins with ≥2 transmembrane segments or proteins with high molecular mass (e.g. >150 kDa) and hydrophobicity. The improved proteomic reactor allowed the detection of a group of endocytic and/or signaling receptor proteins on the plasma membrane, as well as apolipoproteins and glycerolipid synthesis enzymes that play a role in the assembly and secretion of apolipoprotein B100-containing very low density lipoproteins. Thus, the centrifugal proteomic reactor offers a new analytical tool for structure and function studies of membrane proteins involved in lipid and lipoprotein metabolism. PMID:21749988

Proteomics data repositories

PubMed Central

Riffle, Michael; Eng, Jimmy K.

2010-01-01

The field of proteomics, particularly the application of mass spectrometry analysis to protein samples, is well-established and growing rapidly. Proteomics studies generate large volumes of raw experimental data and inferred biological results. To facilitate the dissemination of these data, centralized data repositories have been developed that make the data and results accessible to proteomics researchers and biologists alike. This review of proteomics data repositories focuses exclusively on freely-available, centralized data resources that disseminate or store experimental mass spectrometry data and results. The resources chosen reflect a current “snapshot” of the state of resources available with an emphasis placed on resources that may be of particular interest to yeast researchers. Resources are described in terms of their intended purpose and the features and functionality provided to users. PMID:19795424

Proteome complexity and the forces that drive proteome imbalance

PubMed Central

Harper, J. Wade; Bennett, Eric J.

2016-01-01

Summary The cellular proteome is a complex microcosm of structural and regulatory networks that requires continuous surveillance and modification to meet the dynamic needs of the cell. It is therefore crucial that the protein flux of the cell remains in balance to ensure proper cell function. Genetic alterations that range from chromosome imbalance to oncogene activation can affect the speed, fidelity and capacity of protein biogenesis and degradation systems, which often results in proteome imbalance. An improved understanding of the causes and consequences of proteome imbalance is helping to reveal how these systems can be targeted to treat diseases such as cancer. PMID:27629639

Transcriptomic and proteomic responses of Serratia marcescens to spaceflight conditions involve large-scale changes in metabolic pathways

NASA Astrophysics Data System (ADS)

Wang, Yajuan; Yuan, Yanting; Liu, Jinwen; Su, Longxiang; Chang, De; Guo, Yinghua; Chen, Zhenhong; Fang, Xiangqun; Wang, Junfeng; Li, Tianzhi; Zhou, Lisha; Fang, Chengxiang; Yang, Ruifu; Liu, Changting

2014-04-01

The microgravity environment of spaceflight expeditions has been associated with altered microbial responses. This study explores the characterization of Serratia marcescensis grown in a spaceflight environment at the phenotypic, transcriptomic and proteomic levels. From November 1, 2011 to November 17, 2011, a strain of S. marcescensis was sent into space for 398 h on the Shenzhou VIII spacecraft, and ground simulation was performed as a control (LCT-SM213). After the flight, two mutant strains (LCT-SM166 and LCT-SM262) were selected for further analysis. Although no changes in the morphology, post-culture growth kinetics, hemolysis or antibiotic sensitivity were observed, the two mutant strains exhibited significant changes in their metabolic profiles after exposure to spaceflight. Enrichment analysis of the transcriptome showed that the differentially expressed genes of the two spaceflight strains and the ground control strain mainly included those involved in metabolism and degradation. The proteome revealed that changes at the protein level were also associated with metabolic functions, such as glycolysis/gluconeogenesis, pyruvate metabolism, arginine and proline metabolism and the degradation of valine, leucine and isoleucine. In summary S. marcescens showed alterations primarily in genes and proteins that were associated with metabolism under spaceflight conditions, which gave us valuable clues for future research.

CPTAC Evaluates Long-Term Reproducibility of Quantitative Proteomics Using Breast Cancer Xenografts | Office of Cancer Clinical Proteomics Research

Cancer.gov

Liquid chromatography tandem-mass spectrometry (LC-MS/MS)- based methods such as isobaric tags for relative and absolute quantification (iTRAQ) and tandem mass tags (TMT) have been shown to provide overall better quantification accuracy and reproducibility over other LC-MS/MS techniques. However, large scale projects like the Clinical Proteomic Tumor Analysis Consortium (CPTAC) require comparisons across many genomically characterized clinical specimens in a single study and often exceed the capability of traditional iTRAQ-based quantification.

A proteome-scale map of the human interactome network

PubMed Central

Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J.; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D.; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E.; Braun, Pascal; Brehme, Marc; Broly, Martin P.; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J.; Hardy, Madeleine F.; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R.; Palagi, Alexandre; Poulin, Matthew M.; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M.; Scholz, Annemarie; Shah, Akash A.; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O.; Trigg, Shelly A.; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E.; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M.; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A.; Hill, David E.; Hao, Tong; Roth, Frederick P.; Vidal, Marc

2014-01-01

SUMMARY Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution. PMID:25416956

Current advances in esophageal cancer proteomics.

PubMed

Uemura, Norihisa; Kondo, Tadashi

2015-06-01

We review the current status of proteomics for esophageal cancer (EC) from a clinician's viewpoint. The ultimate goal of cancer proteomics is the improvement of clinical outcome. The proteome as a functional translation of the genome is a straightforward representation of genomic mechanisms that trigger carcinogenesis. Cancer proteomics has identified the mechanisms of carcinogenesis and tumor progression, detected biomarker candidates for early diagnosis, and provided novel therapeutic targets for personalized treatments. Our review focuses on three major topics in EC proteomics: diagnostics, treatment, and molecular mechanisms. We discuss the major histological differences between EC types, i.e., esophageal squamous cell carcinoma and adenocarcinoma, and evaluate the clinical significance of published proteomics studies, including promising diagnostic biomarkers and novel therapeutic targets, which should be further validated prior to launching clinical trials. Multi-disciplinary collaborations between basic scientists, clinicians, and pathologists should be established for inter-institutional validation. In conclusion, EC proteomics has provided significant results, which after thorough validation, should lead to the development of novel clinical tools and improvement of the clinical outcome for esophageal cancer patients. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Large-scale database searching using tandem mass spectra: looking up the answer in the back of the book.

PubMed

Sadygov, Rovshan G; Cociorva, Daniel; Yates, John R

2004-12-01

Database searching is an essential element of large-scale proteomics. Because these methods are widely used, it is important to understand the rationale of the algorithms. Most algorithms are based on concepts first developed in SEQUEST and PeptideSearch. Four basic approaches are used to determine a match between a spectrum and sequence: descriptive, interpretative, stochastic and probability-based matching. We review the basic concepts used by most search algorithms, the computational modeling of peptide identification and current challenges and limitations of this approach for protein identification.

Energy transfers in large-scale and small-scale dynamos

NASA Astrophysics Data System (ADS)

Samtaney, Ravi; Kumar, Rohit; Verma, Mahendra

2015-11-01

We present the energy transfers, mainly energy fluxes and shell-to-shell energy transfers in small-scale dynamo (SSD) and large-scale dynamo (LSD) using numerical simulations of MHD turbulence for Pm = 20 (SSD) and for Pm = 0.2 on 10243 grid. For SSD, we demonstrate that the magnetic energy growth is caused by nonlocal energy transfers from the large-scale or forcing-scale velocity field to small-scale magnetic field. The peak of these energy transfers move towards lower wavenumbers as dynamo evolves, which is the reason for the growth of the magnetic fields at the large scales. The energy transfers U2U (velocity to velocity) and B2B (magnetic to magnetic) are forward and local. For LSD, we show that the magnetic energy growth takes place via energy transfers from large-scale velocity field to large-scale magnetic field. We observe forward U2U and B2B energy flux, similar to SSD.

Aptamer-based multiplexed proteomic technology for biomarker discovery.

PubMed

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

Large Scale Processes and Extreme Floods in Brazil

NASA Astrophysics Data System (ADS)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

BIG: a large-scale data integration tool for renal physiology.

PubMed

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya; Knepper, Mark A

2016-10-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: "How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?" This is the type of problem that has motivated the "Big-Data" revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/.

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

PubMed

Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

2012-12-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

Recent advances in stable isotope labeling based techniques for proteome relative quantification.

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2014-10-24

The large scale relative quantification of all proteins expressed in biological samples under different states is of great importance for discovering proteins with important biological functions, as well as screening disease related biomarkers and drug targets. Therefore, the accurate quantification of proteins at proteome level has become one of the key issues in protein science. Herein, the recent advances in stable isotope labeling based techniques for proteome relative quantification were reviewed, from the aspects of metabolic labeling, chemical labeling and enzyme-catalyzed labeling. Furthermore, the future research direction in this field was prospected. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer aided manual validation of mass spectrometry-based proteomic data.

PubMed

Curran, Timothy G; Bryson, Bryan D; Reigelhaupt, Michael; Johnson, Hannah; White, Forest M

2013-06-15

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics. Copyright © 2013 Elsevier Inc. All rights reserved.

Development of proteome-wide binding reagents for research and diagnostics.

PubMed

Taussig, Michael J; Schmidt, Ronny; Cook, Elizabeth A; Stoevesandt, Oda

2013-12-01

Alongside MS, antibodies and other specific protein-binding molecules have a special place in proteomics as affinity reagents in a toolbox of applications for determining protein location, quantitative distribution and function (affinity proteomics). The realisation that the range of research antibodies available, while apparently vast is nevertheless still very incomplete and frequently of uncertain quality, has stimulated projects with an objective of raising comprehensive, proteome-wide sets of protein binders. With progress in automation and throughput, a remarkable number of recent publications refer to the practical possibility of selecting binders to every protein encoded in the genome. Here we review the requirements of a pipeline of production of protein binders for the human proteome, including target prioritisation, antigen design, 'next generation' methods, databases and the approaches taken by ongoing projects in Europe and the USA. While the task of generating affinity reagents for all human proteins is complex and demanding, the benefits of well-characterised and quality-controlled pan-proteome binder resources for biomedical research, industry and life sciences in general would be enormous and justify the effort. Given the technical, personnel and financial resources needed to fulfil this aim, expansion of current efforts may best be addressed through large-scale international collaboration. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CPTC and NIST-sponsored Yeast Reference Material Now Publicly Available | Office of Cancer Clinical Proteomics Research

Cancer.gov

The yeast protein extract (RM8323) developed by National Institute of Standards and Technology (NIST) under the auspices of NCI's CPTC initiative is currently available to the public at https://www-s.nist.gov/srmors/view_detail.cfm?srm=8323. The yeast proteome offers researchers a unique biological reference material. RM8323 is the most extensively characterized complex biological proteome and the only one associated with several large-scale studies to estimate protein abundance across a wide concentration range.

Ubiquitinated Proteome: Ready for Global?*

PubMed Central

Shi, Yi; Xu, Ping; Qin, Jun

2011-01-01

Ubiquitin (Ub) is a small and highly conserved protein that can covalently modify protein substrates. Ubiquitination is one of the major post-translational modifications that regulate a broad spectrum of cellular functions. The advancement of mass spectrometers as well as the development of new affinity purification tools has greatly expedited proteome-wide analysis of several post-translational modifications (e.g. phosphorylation, glycosylation, and acetylation). In contrast, large-scale profiling of lysine ubiquitination remains a challenge. Most recently, new Ub affinity reagents such as Ub remnant antibody and tandem Ub binding domains have been developed, allowing for relatively large-scale detection of several hundreds of lysine ubiquitination events in human cells. Here we review different strategies for the identification of ubiquitination site and discuss several issues associated with data analysis. We suggest that careful interpretation and orthogonal confirmation of MS spectra is necessary to minimize false positive assignments by automatic searching algorithms. PMID:21339389

Microbial Interactions in Plants: Perspectives and Applications of Proteomics.

PubMed

Imam, Jahangir; Shukla, Pratyoosh; Mandal, Nimai Prasad; Variar, Mukund

2017-01-01

The structure and function of proteins involved in plant-microbe interactions is investigated through large-scale proteomics technology in a complex biological sample. Since the whole genome sequences are now available for several plant species and microbes, proteomics study has become easier, accurate and huge amount of data can be generated and analyzed during plant-microbe interactions. Proteomics approaches are highly important and relevant in many studies and showed that only genomics approaches are not sufficient enough as much significant information are lost as the proteins and not the genes coding them are final product that is responsible for the observed phenotype. Novel approaches in proteomics are developing continuously enabling the study of the various aspects in arrangements and configuration of proteins and its functions. Its application is becoming more common and frequently used in plant-microbe interactions with the advancement in new technologies. They are more used for the portrayal of cell and extracellular destructiveness and pathogenicity variables delivered by pathogens. This distinguishes the protein level adjustments in host plants when infected with pathogens and advantageous partners. This review provides a brief overview of different proteomics technology which is currently available followed by their exploitation to study the plant-microbe interaction. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Comparison of the large-scale periplasmic proteomes of the Escherichia coli K-12 and B strains.

PubMed

Han, Mee-Jung; Kim, Jin Young; Kim, Jung A

2014-04-01

Escherichia coli typically secretes many proteins into the periplasmic space, and the periplasmic proteins have been used for the secretory production of various proteins by the biotechnology industry. However, the identity of all of the E. coli periplasmic proteins remains unknown. Here, high-resolution periplasmic proteome reference maps of the E. coli K-12 and B strains were constructed and compared. Of the 145 proteins identified by tandem mass spectrometry, 61 proteins were conserved in the two strains, whereas 11 and 12 strain-specific proteins were identified for the E. coli K-12 and B strains, respectively. In addition, 27 proteins exhibited differences in intensities greater than 2-fold between the K-12 and B strains. The periplasmic proteins MalE and OppA were the most abundant proteins in the two E. coli strains. Distinctive differences between the two strains included several proteins that were caused by genetic variations, such as CybC, FliC, FliY, KpsD, MglB, ModA, and Ybl119, hydrolytic enzymes, particularly phosphatases, glycosylases, and proteases, and many uncharacterized proteins. Compared to previous studies, the localization of many proteins, including 30 proteins for the K-12 strain and 53 proteins for the B strain, was newly identified as periplasmic. This study identifies the largest number of proteins in the E. coli periplasm as well as the dynamics of these proteins. Additionally, these findings are summarized as reference proteome maps that will be useful for studying protein secretion and may provide new strategies for the enhanced secretory production of recombinant proteins. Copyright © 2013. Published by Elsevier B.V.

Validating Bayesian truth serum in large-scale online human experiments.

PubMed

Frank, Morgan R; Cebrian, Manuel; Pickard, Galen; Rahwan, Iyad

2017-01-01

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method's mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon's Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the "honest" distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where "honest" answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers.

Geospatial Optimization of Siting Large-Scale Solar Projects

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

Macknick, Jordan; Quinby, Ted; Caulfield, Emmet

2014-03-01

Recent policy and economic conditions have encouraged a renewed interest in developing large-scale solar projects in the U.S. Southwest. However, siting large-scale solar projects is complex. In addition to the quality of the solar resource, solar developers must take into consideration many environmental, social, and economic factors when evaluating a potential site. This report describes a proof-of-concept, Web-based Geographical Information Systems (GIS) tool that evaluates multiple user-defined criteria in an optimization algorithm to inform discussions and decisions regarding the locations of utility-scale solar projects. Existing siting recommendations for large-scale solar projects from governmental and non-governmental organizations are not consistent withmore » each other, are often not transparent in methods, and do not take into consideration the differing priorities of stakeholders. The siting assistance GIS tool we have developed improves upon the existing siting guidelines by being user-driven, transparent, interactive, capable of incorporating multiple criteria, and flexible. This work provides the foundation for a dynamic siting assistance tool that can greatly facilitate siting decisions among multiple stakeholders.« less

A Proteomics Approach to the Protein Normalization Problem: Selection of Unvarying Proteins for MS-Based Proteomics and Western Blotting.

PubMed

Wiśniewski, Jacek R; Mann, Matthias

2016-07-01

Proteomics and other protein-based analysis methods such as Western blotting all face the challenge of discriminating changes in the levels of proteins of interest from inadvertent changes in the amount loaded for analysis. Mass-spectrometry-based proteomics can now estimate the relative and absolute amounts of thousands of proteins across diverse biological systems. We reasoned that this new technology could prove useful for selection of very stably expressed proteins that could serve as better loading controls than those traditionally employed. Large-scale proteomic analyses of SDS lysates of cultured cells and tissues revealed deglycase DJ-1 as the protein with the lowest variability in abundance among different cell types in human, mouse, and amphibian cells. The protein constitutes 0.069 ± 0.017% of total cellular protein and occurs at a specific concentration of 34.6 ± 8.7 pmol/mg of total protein. Since DJ-1 is ubiquitous and therefore easily detectable with several peptides, it can be helpful in normalization of proteomic data sets. In addition, DJ-1 appears to be an advantageous loading control for Western blot that is superior to those used commonly used, allowing comparisons between tissues and cells originating from evolutionarily distant vertebrate species. Notably, this is not possible by the detection and quantitation of housekeeping proteins, which are often used in the Western blot technique. The approach introduced here can be applied to select the most appropriate loading controls for MS-based proteomics or Western blotting in any biological system.

Large-scale weakly supervised object localization via latent category learning.

PubMed

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Computational clustering for viral reference proteomes

PubMed Central

Chen, Chuming; Huang, Hongzhan; Mazumder, Raja; Natale, Darren A.; McGarvey, Peter B.; Zhang, Jian; Polson, Shawn W.; Wang, Yuqi; Wu, Cathy H.

2016-01-01

Motivation: The enormous number of redundant sequenced genomes has hindered efforts to analyze and functionally annotate proteins. As the taxonomy of viruses is not uniformly defined, viral proteomes pose special challenges in this regard. Grouping viruses based on the similarity of their proteins at proteome scale can normalize against potential taxonomic nomenclature anomalies. Results: We present Viral Reference Proteomes (Viral RPs), which are computed from complete virus proteomes within UniProtKB. Viral RPs based on 95, 75, 55, 35 and 15% co-membership in proteome similarity based clusters are provided. Comparison of our computational Viral RPs with UniProt’s curator-selected Reference Proteomes indicates that the two sets are consistent and complementary. Furthermore, each Viral RP represents a cluster of virus proteomes that was consistent with virus or host taxonomy. We provide BLASTP search and FTP download of Viral RP protein sequences, and a browser to facilitate the visualization of Viral RPs. Availability and implementation: http://proteininformationresource.org/rps/viruses/ Contact: chenc@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153712

Large-scale structure of randomly jammed spheres

NASA Astrophysics Data System (ADS)

Ikeda, Atsushi; Berthier, Ludovic; Parisi, Giorgio

2017-05-01

We numerically analyze the density field of three-dimensional randomly jammed packings of monodisperse soft frictionless spherical particles, paying special attention to fluctuations occurring at large length scales. We study in detail the two-point static structure factor at low wave vectors in Fourier space. We also analyze the nature of the density field in real space by studying the large-distance behavior of the two-point pair correlation function, of density fluctuations in subsystems of increasing sizes, and of the direct correlation function. We show that such real space analysis can be greatly improved by introducing a coarse-grained density field to disentangle genuine large-scale correlations from purely local effects. Our results confirm that both Fourier and real space signatures of vanishing density fluctuations at large scale are absent, indicating that randomly jammed packings are not hyperuniform. In addition, we establish that the pair correlation function displays a surprisingly complex structure at large distances, which is however not compatible with the long-range negative correlation of hyperuniform systems but fully compatible with an analytic form for the structure factor. This implies that the direct correlation function is short ranged, as we also demonstrate directly. Our results reveal that density fluctuations in jammed packings do not follow the behavior expected for random hyperuniform materials, but display instead a more complex behavior.

Proteome-wide search for functional motifs altered in tumors: Prediction of nuclear export signals inactivated by cancer-related mutations

PubMed Central

Prieto, Gorka; Fullaondo, Asier; Rodríguez, Jose A.

2016-01-01

Large-scale sequencing projects are uncovering a growing number of missense mutations in human tumors. Understanding the phenotypic consequences of these alterations represents a formidable challenge. In silico prediction of functionally relevant amino acid motifs disrupted by cancer mutations could provide insight into the potential impact of a mutation, and guide functional tests. We have previously described Wregex, a tool for the identification of potential functional motifs, such as nuclear export signals (NESs), in proteins. Here, we present an improved version that allows motif prediction to be combined with data from large repositories, such as the Catalogue of Somatic Mutations in Cancer (COSMIC), and to be applied to a whole proteome scale. As an example, we have searched the human proteome for candidate NES motifs that could be altered by cancer-related mutations included in the COSMIC database. A subset of the candidate NESs identified was experimentally tested using an in vivo nuclear export assay. A significant proportion of the selected motifs exhibited nuclear export activity, which was abrogated by the COSMIC mutations. In addition, our search identified a cancer mutation that inactivates the NES of the human deubiquitinase USP21, and leads to the aberrant accumulation of this protein in the nucleus. PMID:27174732

BIG: a large-scale data integration tool for renal physiology

PubMed Central

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya

2016-01-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: “How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?” This is the type of problem that has motivated the “Big-Data” revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/. PMID:27279488

ProteoSign: an end-user online differential proteomics statistical analysis platform.

PubMed

Efstathiou, Georgios; Antonakis, Andreas N; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Divanach, Peter; Trudgian, David C; Thomas, Benjamin; Papanikolaou, Nikolas; Aivaliotis, Michalis; Acuto, Oreste; Iliopoulos, Ioannis

2017-07-03

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Translational plant proteomics: a perspective.

PubMed

Agrawal, Ganesh Kumar; Pedreschi, Romina; Barkla, Bronwyn J; Bindschedler, Laurence Veronique; Cramer, Rainer; Sarkar, Abhijit; Renaut, Jenny; Job, Dominique; Rakwal, Randeep

2012-08-03

Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic values of plants, food security and safety, and energy sustainability. In this review, we highlight the substantial progress reached in plant proteomics during the past decade which has paved the way for translational plant proteomics. Increasing proteomics knowledge in plants is not limited to model and non-model plants, proteogenomics, crop improvement, and food analysis, safety, and nutrition but to many more potential applications. Given the wealth of information generated and to some extent applied, there is the need for more efficient and broader channels to freely disseminate the information to the scientific community. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins

PubMed Central

Kennedy, Jacob J.; Abbatiello, Susan E.; Kim, Kyunggon; Yan, Ping; Whiteaker, Jeffrey R.; Lin, Chenwei; Kim, Jun Seok; Zhang, Yuzheng; Wang, Xianlong; Ivey, Richard G.; Zhao, Lei; Min, Hophil; Lee, Youngju; Yu, Myeong-Hee; Yang, Eun Gyeong; Lee, Cheolju; Wang, Pei; Rodriguez, Henry; Kim, Youngsoo; Carr, Steven A.; Paulovich, Amanda G.

2014-01-01

The successful application of MRM in biological specimens raises the exciting possibility that assays can be configured to measure all human proteins, resulting in an assay resource that would promote advances in biomedical research. We report the results of a pilot study designed to test the feasibility of a large-scale, international effort in MRM assay generation. We have configured, validated across three laboratories, and made publicly available as a resource to the community 645 novel MRM assays representing 319 proteins expressed in human breast cancer. Assays were multiplexed in groups of >150 peptides and deployed to quantify endogenous analyte in a panel of breast cancer-related cell lines. Median assay precision was 5.4%, with high inter-laboratory correlation (R2 >0.96). Peptide measurements in breast cancer cell lines were able to discriminate amongst molecular subtypes and identify genome-driven changes in the cancer proteome. These results establish the feasibility of a scaled, international effort. PMID:24317253

Improved Proteomic Analysis Following Trichloroacetic Acid Extraction of Bacillus anthracis Spore Proteins

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

Kaiser, Brooke LD; Wunschel, David S.; Sydor, Michael A.

2015-08-07

Proteomic analysis of bacterial samples provides valuable information about cellular responses and functions under different environmental pressures. Proteomic analysis is dependent upon efficient extraction of proteins from bacterial samples without introducing bias toward extraction of particular protein classes. While no single method can recover 100% of the bacterial proteins, selected protocols can improve overall protein isolation, peptide recovery, or enrich for certain classes of proteins. The method presented here is technically simple and does not require specialized equipment such as a mechanical disrupter. Our data reveal that for particularly challenging samples, such as B. anthracis Sterne spores, trichloroacetic acid extractionmore » improved the number of proteins identified within a sample compared to bead beating (714 vs 660, respectively). Further, TCA extraction enriched for 103 known spore specific proteins whereas bead beating resulted in 49 unique proteins. Analysis of C. botulinum samples grown to 5 days, composed of vegetative biomass and spores, showed a similar trend with improved protein yields and identification using our method compared to bead beating. Interestingly, easily lysed samples, such as B. anthracis vegetative cells, were equally as effectively processed via TCA and bead beating, but TCA extraction remains the easiest and most cost effective option. As with all assays, supplemental methods such as implementation of an alternative preparation method may provide additional insight to the protein biology of the bacteria being studied.« less

Pressurized Pepsin Digestion in Proteomics

PubMed Central

López-Ferrer, Daniel; Petritis, Konstantinos; Robinson, Errol W.; Hixson, Kim K.; Tian, Zhixin; Lee, Jung Hwa; Lee, Sang-Won; Tolić, Nikola; Weitz, Karl K.; Belov, Mikhail E.; Smith, Richard D.; Paša-Tolić, Ljiljana

2011-01-01

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome. PMID:20627868

Computational Omics Pre-Awardees | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) is pleased to announce the pre-awardees of the Computational Omics solicitation. Working with NVIDIA Foundation's Compute the Cure initiative and Leidos Biomedical Research Inc., the NCI, through this solicitation, seeks to leverage computational efforts to provide tools for the mining and interpretation of large-scale publicly available ‘omics’ datasets.

Validating Bayesian truth serum in large-scale online human experiments

PubMed Central

Frank, Morgan R.; Cebrian, Manuel; Pickard, Galen; Rahwan, Iyad

2017-01-01

Bayesian truth serum (BTS) is an exciting new method for improving honesty and information quality in multiple-choice survey, but, despite the method’s mathematical reliance on large sample sizes, existing literature about BTS only focuses on small experiments. Combined with the prevalence of online survey platforms, such as Amazon’s Mechanical Turk, which facilitate surveys with hundreds or thousands of participants, BTS must be effective in large-scale experiments for BTS to become a readily accepted tool in real-world applications. We demonstrate that BTS quantifiably improves honesty in large-scale online surveys where the “honest” distribution of answers is known in expectation on aggregate. Furthermore, we explore a marketing application where “honest” answers cannot be known, but find that BTS treatment impacts the resulting distributions of answers. PMID:28494000

The amino acid's backup bone - storage solutions for proteomics facilities.

PubMed

Meckel, Hagen; Stephan, Christian; Bunse, Christian; Krafzik, Michael; Reher, Christopher; Kohl, Michael; Meyer, Helmut Erich; Eisenacher, Martin

2014-01-01

Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013. Published by Elsevier B.V.

Large-scale serum protein biomarker discovery in Duchenne muscular dystrophy.

PubMed

Hathout, Yetrib; Brody, Edward; Clemens, Paula R; Cripe, Linda; DeLisle, Robert Kirk; Furlong, Pat; Gordish-Dressman, Heather; Hache, Lauren; Henricson, Erik; Hoffman, Eric P; Kobayashi, Yvonne Monique; Lorts, Angela; Mah, Jean K; McDonald, Craig; Mehler, Bob; Nelson, Sally; Nikrad, Malti; Singer, Britta; Steele, Fintan; Sterling, David; Sweeney, H Lee; Williams, Steve; Gold, Larry

2015-06-09

Serum biomarkers in Duchenne muscular dystrophy (DMD) may provide deeper insights into disease pathogenesis, suggest new therapeutic approaches, serve as acute read-outs of drug effects, and be useful as surrogate outcome measures to predict later clinical benefit. In this study a large-scale biomarker discovery was performed on serum samples from patients with DMD and age-matched healthy volunteers using a modified aptamer-based proteomics technology. Levels of 1,125 proteins were quantified in serum samples from two independent DMD cohorts: cohort 1 (The Parent Project Muscular Dystrophy-Cincinnati Children's Hospital Medical Center), 42 patients with DMD and 28 age-matched normal volunteers; and cohort 2 (The Cooperative International Neuromuscular Research Group, Duchenne Natural History Study), 51 patients with DMD and 17 age-matched normal volunteers. Forty-four proteins showed significant differences that were consistent in both cohorts when comparing DMD patients and healthy volunteers at a 1% false-discovery rate, a large number of significant protein changes for such a small study. These biomarkers can be classified by known cellular processes and by age-dependent changes in protein concentration. Our findings demonstrate both the utility of this unbiased biomarker discovery approach and suggest potential new diagnostic and therapeutic avenues for ameliorating the burden of DMD and, we hope, other rare and devastating diseases.

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines

PubMed Central

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J.; Li, Ming

2013-01-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables. PMID:22552787

Refining comparative proteomics by spectral counting to account for shared peptides and multiple search engines.

PubMed

Chen, Yao-Yi; Dasari, Surendra; Ma, Ze-Qiang; Vega-Montoto, Lorenzo J; Li, Ming; Tabb, David L

2012-09-01

Spectral counting has become a widely used approach for measuring and comparing protein abundance in label-free shotgun proteomics. However, when analyzing complex samples, the ambiguity of matching between peptides and proteins greatly affects the assessment of peptide and protein inventories, differentiation, and quantification. Meanwhile, the configuration of database searching algorithms that assign peptides to MS/MS spectra may produce different results in comparative proteomic analysis. Here, we present three strategies to improve comparative proteomics through spectral counting. We show that comparing spectral counts for peptide groups rather than for protein groups forestalls problems introduced by shared peptides. We demonstrate the advantage and flexibility of this new method in two datasets. We present four models to combine four popular search engines that lead to significant gains in spectral counting differentiation. Among these models, we demonstrate a powerful vote counting model that scales well for multiple search engines. We also show that semi-tryptic searching outperforms tryptic searching for comparative proteomics. Overall, these techniques considerably improve protein differentiation on the basis of spectral count tables.

Age distribution of human gene families shows significant roles of both large- and small-scale duplications in vertebrate evolution.

PubMed

Gu, Xun; Wang, Yufeng; Gu, Jianying

2002-06-01

The classical (two-round) hypothesis of vertebrate genome duplication proposes two successive whole-genome duplication(s) (polyploidizations) predating the origin of fishes, a view now being seriously challenged. As the debate largely concerns the relative merits of the 'big-bang mode' theory (large-scale duplication) and the 'continuous mode' theory (constant creation by small-scale duplications), we tested whether a significant proportion of paralogous genes in the contemporary human genome was indeed generated in the early stage of vertebrate evolution. After an extensive search of major databases, we dated 1,739 gene duplication events from the phylogenetic analysis of 749 vertebrate gene families. We found a pattern characterized by two waves (I, II) and an ancient component. Wave I represents a recent gene family expansion by tandem or segmental duplications, whereas wave II, a rapid paralogous gene increase in the early stage of vertebrate evolution, supports the idea of genome duplication(s) (the big-bang mode). Further analysis indicated that large- and small-scale gene duplications both make a significant contribution during the early stage of vertebrate evolution to build the current hierarchy of the human proteome.

On the scaling of small-scale jet noise to large scale

NASA Technical Reports Server (NTRS)

Soderman, Paul T.; Allen, Christopher S.

1992-01-01

An examination was made of several published jet noise studies for the purpose of evaluating scale effects important to the simulation of jet aeroacoustics. Several studies confirmed that small conical jets, one as small as 59 mm diameter, could be used to correctly simulate the overall or PNL noise of large jets dominated by mixing noise. However, the detailed acoustic spectra of large jets are more difficult to simulate because of the lack of broad-band turbulence spectra in small jets. One study indicated that a jet Reynolds number of 5 x 10 exp 6 based on exhaust diameter enabled the generation of broad-band noise representative of large jet mixing noise. Jet suppressor aeroacoustics is even more difficult to simulate at small scale because of the small mixer nozzles with flows sensitive to Reynolds number. Likewise, one study showed incorrect ejector mixing and entrainment using small-scale, short ejector that led to poor acoustic scaling. Conversely, fairly good results were found with a longer ejector and, in a different study, with a 32-chute suppressor nozzle. Finally, it was found that small-scale aeroacoustic resonance produced by jets impacting ground boards does not reproduce at large scale.

Robust regression for large-scale neuroimaging studies.

PubMed

Fritsch, Virgile; Da Mota, Benoit; Loth, Eva; Varoquaux, Gaël; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Brühl, Rüdiger; Butzek, Brigitte; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Lemaitre, Hervé; Mann, Karl; Nees, Frauke; Paus, Tomas; Schad, Daniel J; Schümann, Gunter; Frouin, Vincent; Poline, Jean-Baptiste; Thirion, Bertrand

2015-05-01

Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Advances in targeted proteomics and applications to biomedical research

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

Shi, Tujin; Song, Ehwang; Nie, Song

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074–1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications inmore » human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.« less

Large-scale retrieval for medical image analytics: A comprehensive review.

PubMed

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of an Improved Proteomics Method for Abundant Protein Cleanup: Molecular and Genomic Mechanisms Study in Plant Defense*

PubMed Central

Zhang, Yixiang; Gao, Peng; Xing, Zhuo; Jin, Shumei; Chen, Zhide; Liu, Lantao; Constantino, Nasie; Wang, Xinwang; Shi, Weibing; Yuan, Joshua S.; Dai, Susie Y.

2013-01-01

High abundance proteins like ribulose-1,5-bisphosphate carboxylase oxygenase (Rubisco) impose a consistent challenge for the whole proteome characterization using shot-gun proteomics. To address this challenge, we developed and evaluated Polyethyleneimine Assisted Rubisco Cleanup (PARC) as a new method by combining both abundant protein removal and fractionation. The new approach was applied to a plant insect interaction study to validate the platform and investigate mechanisms for plant defense against herbivorous insects. Our results indicated that PARC can effectively remove Rubisco, improve the protein identification, and discover almost three times more differentially regulated proteins. The significantly enhanced shot-gun proteomics performance was translated into in-depth proteomic and molecular mechanisms for plant insect interaction, where carbon re-distribution was used to play an essential role. Moreover, the transcriptomic validation also confirmed the reliability of PARC analysis. Finally, functional studies were carried out for two differentially regulated genes as revealed by PARC analysis. Insect resistance was induced by over-expressing either jacalin-like or cupin-like genes in rice. The results further highlighted that PARC can serve as an effective strategy for proteomics analysis and gene discovery. PMID:23943779

Sequential protein extraction as an efficient method for improved proteome coverage in larvae of Atlantic salmon (Salmo salar).

PubMed

Nuez-Ortín, Waldo G; Carter, Chris G; Nichols, Peter D; Wilson, Richard

2016-07-01

Understanding diet- and environmentally induced physiological changes in fish larvae is a major goal for the aquaculture industry. Proteomic analysis of whole fish larvae comprising multiple tissues offers considerable potential but is challenging due to the very large dynamic range of protein abundance. To extend the coverage of the larval phase of the Atlantic salmon (Salmo salar) proteome, we applied a two-step sequential extraction (SE) method, based on differential protein solubility, using a nondenaturing buffer containing 150 mM NaCl followed by a denaturing buffer containing 7 M urea and 2 M thiourea. Extracts prepared using SE and one-step direct extraction were characterized via label-free shotgun proteomics using nanoLC-MS/MS (LTQ-Orbitrap). SE partitioned the proteins into two fractions of approximately equal amounts, but with very distinct protein composition, leading to identification of ∼40% more proteins than direct extraction. This fractionation strategy enabled the most detailed characterization of the salmon larval proteome to date and provides a platform for greater understanding of physiological changes in whole fish larvae. The MS data are available via the ProteomeXchange Consortium PRIDE partner repository, dataset PXD003366. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation

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

Guarnieri, Michael T.; Nag, Ambarish; Yang, Shihui

2013-11-01

Oleaginous microalgae are capable of producing large quantities of fatty acids and triacylglycerides. As such, they are promising feedstocks for the production of biofuels and bioproducts. Genetic strain-engineering strategies offer a means to accelerate the commercialization of algal biofuels by improving the rate and total accumulation of microalgal lipids. However, the industrial potential of these organisms remains to be met, largely due to the incomplete knowledgebase surrounding the mechanisms governing the induction of algal lipid biosynthesis. Such strategies require further elucidation of genes and gene products controlling algal lipid accumulation. In this study, we have set out to examine thesemore » mechanisms and identify novel strain-engineering targets in the oleaginous microalga, Chlorella vulgaris. Comparative shotgun proteomic analyses have identified a number of novel targets, including previously unidentified transcription factors and proteins involved in cell signaling and cell cycle regulation. These results lay the foundation for strain-improvement strategies and demonstrate the power of translational proteomic analysis.« less

Large-Scale Disasters

NASA Astrophysics Data System (ADS)

Gad-El-Hak, Mohamed

"Extreme" events - including climatic events, such as hurricanes, tornadoes, and drought - can cause massive disruption to society, including large death tolls and property damage in the billions of dollars. Events in recent years have shown the importance of being prepared and that countries need to work together to help alleviate the resulting pain and suffering. This volume presents a review of the broad research field of large-scale disasters. It establishes a common framework for predicting, controlling and managing both manmade and natural disasters. There is a particular focus on events caused by weather and climate change. Other topics include air pollution, tsunamis, disaster modeling, the use of remote sensing and the logistics of disaster management. It will appeal to scientists, engineers, first responders and health-care professionals, in addition to graduate students and researchers who have an interest in the prediction, prevention or mitigation of large-scale disasters.

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data.

PubMed

Qeli, Ermir; Omasits, Ulrich; Goetze, Sandra; Stekhoven, Daniel J; Frey, Juerg E; Basler, Konrad; Wollscheid, Bernd; Brunner, Erich; Ahrens, Christian H

2014-08-28

The in silico prediction of the best-observable "proteotypic" peptides in mass spectrometry-based workflows is a challenging problem. Being able to accurately predict such peptides would enable the informed selection of proteotypic peptides for targeted quantification of previously observed and non-observed proteins for any organism, with a significant impact for clinical proteomics and systems biology studies. Current prediction algorithms rely on physicochemical parameters in combination with positive and negative training sets to identify those peptide properties that most profoundly affect their general detectability. Here we present PeptideRank, an approach that uses learning to rank algorithm for peptide detectability prediction from shotgun proteomics data, and that eliminates the need to select a negative dataset for the training step. A large number of different peptide properties are used to train ranking models in order to predict a ranking of the best-observable peptides within a protein. Empirical evaluation with rank accuracy metrics showed that PeptideRank complements existing prediction algorithms. Our results indicate that the best performance is achieved when it is trained on organism-specific shotgun proteomics data, and that PeptideRank is most accurate for short to medium-sized and abundant proteins, without any loss in prediction accuracy for the important class of membrane proteins. Targeted proteomics approaches have been gaining a lot of momentum and hold immense potential for systems biology studies and clinical proteomics. However, since only very few complete proteomes have been reported to date, for a considerable fraction of a proteome there is no experimental proteomics evidence that would allow to guide the selection of the best-suited proteotypic peptides (PTPs), i.e. peptides that are specific to a given proteoform and that are repeatedly observed in a mass spectrometer. We describe a novel, rank-based approach for the prediction

Mass spectrometry-based biomarker discovery: toward a global proteome index of individuality.

PubMed

Hawkridge, Adam M; Muddiman, David C

2009-01-01

Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry-based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed.

Design and analysis issues in quantitative proteomics studies.

PubMed

Karp, Natasha A; Lilley, Kathryn S

2007-09-01

Quantitative proteomics is the comparison of distinct proteomes which enables the identification of protein species which exhibit changes in expression or post-translational state in response to a given stimulus. Many different quantitative techniques are being utilized and generate large datasets. Independent of the technique used, these large datasets need robust data analysis to ensure valid conclusions are drawn from such studies. Approaches to address the problems that arise with large datasets are discussed to give insight into the types of statistical analyses of data appropriate for the various experimental strategies that can be employed by quantitative proteomic studies. This review also highlights the importance of employing a robust experimental design and highlights various issues surrounding the design of experiments. The concepts and examples discussed within will show how robust design and analysis will lead to confident results that will ensure quantitative proteomics delivers.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

PubMed

Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

2012-12-05

For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes

PubMed Central

Virant-Klun, Irma; Leicht, Stefan; Hughes, Christopher; Krijgsveld, Jeroen

2016-01-01

Oocytes undergo a range of complex processes via oogenesis, maturation, fertilization, and early embryonic development, eventually giving rise to a fully functioning organism. To understand proteome composition and diversity during maturation of human oocytes, here we have addressed crucial aspects of oocyte collection and proteome analysis, resulting in the first proteome and secretome maps of human oocytes. Starting from 100 oocytes collected via a novel serum-free hanging drop culture system, we identified 2,154 proteins, whose function indicate that oocytes are largely resting cells with a proteome that is tailored for homeostasis, cellular attachment, and interaction with its environment via secretory factors. In addition, we have identified 158 oocyte-enriched proteins (such as ECAT1, PIWIL3, NLRP7)1 not observed in high-coverage proteomics studies of other human cell lines or tissues. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ∼100 ng per cell, we consistently identified ∼450 proteins from individual oocytes. When comparing individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage, we found that the Tudor and KH domain-containing protein (TDRKH) is preferentially expressed in immature oocytes, while Wee2, PCNA, and DNMT1 were enriched in mature cells, collectively indicating that maintenance of genome integrity is crucial during oocyte maturation. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and preimplantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types. Data associated with this study are available via ProteomeXchange with identifier PXD004142. PMID:27215607

Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes.

PubMed

Virant-Klun, Irma; Leicht, Stefan; Hughes, Christopher; Krijgsveld, Jeroen

2016-08-01

Oocytes undergo a range of complex processes via oogenesis, maturation, fertilization, and early embryonic development, eventually giving rise to a fully functioning organism. To understand proteome composition and diversity during maturation of human oocytes, here we have addressed crucial aspects of oocyte collection and proteome analysis, resulting in the first proteome and secretome maps of human oocytes. Starting from 100 oocytes collected via a novel serum-free hanging drop culture system, we identified 2,154 proteins, whose function indicate that oocytes are largely resting cells with a proteome that is tailored for homeostasis, cellular attachment, and interaction with its environment via secretory factors. In addition, we have identified 158 oocyte-enriched proteins (such as ECAT1, PIWIL3, NLRP7)(1) not observed in high-coverage proteomics studies of other human cell lines or tissues. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ∼100 ng per cell, we consistently identified ∼450 proteins from individual oocytes. When comparing individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage, we found that the Tudor and KH domain-containing protein (TDRKH) is preferentially expressed in immature oocytes, while Wee2, PCNA, and DNMT1 were enriched in mature cells, collectively indicating that maintenance of genome integrity is crucial during oocyte maturation. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and preimplantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types. Data associated with this study are available via ProteomeXchange with identifier PXD004142. © 2016 by The American Society for Biochemistry and Molecular Biology

Confetti: A Multiprotease Map of the HeLa Proteome for Comprehensive Proteomics*

PubMed Central

Guo, Xiaofeng; Trudgian, David C.; Lemoff, Andrew; Yadavalli, Sivaramakrishna; Mirzaei, Hamid

2014-01-01

Bottom-up proteomics largely relies on tryptic peptides for protein identification and quantification. Tryptic digestion often provides limited coverage of protein sequence because of issues such as peptide length, ionization efficiency, and post-translational modification colocalization. Unfortunately, a region of interest in a protein, for example, because of proximity to an active site or the presence of important post-translational modifications, may not be covered by tryptic peptides. Detection limits, quantification accuracy, and isoform differentiation can also be improved with greater sequence coverage. Selected reaction monitoring (SRM) would also greatly benefit from being able to identify additional targetable sequences. In an attempt to improve protein sequence coverage and to target regions of proteins that do not generate useful tryptic peptides, we deployed a multiprotease strategy on the HeLa proteome. First, we used seven commercially available enzymes in single, double, and triple enzyme combinations. A total of 48 digests were performed. 5223 proteins were detected by analyzing the unfractionated cell lysate digest directly; with 42% mean sequence coverage. Additional strong-anion exchange fractionation of the most complementary digests permitted identification of over 3000 more proteins, with improved mean sequence coverage. We then constructed a web application (https://proteomics.swmed.edu/confetti) that allows the community to examine a target protein or protein isoform in order to discover the enzyme or combination of enzymes that would yield peptides spanning a certain region of interest in the sequence. Finally, we examined the use of nontryptic digests for SRM. From our strong-anion exchange fractionation data, we were able to identify three or more proteotypic SRM candidates within a single digest for 6056 genes. Surprisingly, in 25% of these cases the digest producing the most observable proteotypic peptides was neither trypsin nor Lys

On the scaling of small-scale jet noise to large scale

NASA Technical Reports Server (NTRS)

Soderman, Paul T.; Allen, Christopher S.

1992-01-01

An examination was made of several published jet noise studies for the purpose of evaluating scale effects important to the simulation of jet aeroacoustics. Several studies confirmed that small conical jets, one as small as 59 mm diameter, could be used to correctly simulate the overall or perceived noise level (PNL) noise of large jets dominated by mixing noise. However, the detailed acoustic spectra of large jets are more difficult to simulate because of the lack of broad-band turbulence spectra in small jets. One study indicated that a jet Reynolds number of 5 x 10(exp 6) based on exhaust diameter enabled the generation of broad-band noise representative of large jet mixing noise. Jet suppressor aeroacoustics is even more difficult to simulate at small scale because of the small mixer nozzles with flows sensitive to Reynolds number. Likewise, one study showed incorrect ejector mixing and entrainment using a small-scale, short ejector that led to poor acoustic scaling. Conversely, fairly good results were found with a longer ejector and, in a different study, with a 32-chute suppressor nozzle. Finally, it was found that small-scale aeroacoustic resonance produced by jets impacting ground boards does not reproduce at large scale.

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Large-scale identification of target proteins of a glycosyltransferase isozyme by Lectin-IGOT-LC/MS, an LC/MS-based glycoproteomic approach

PubMed Central

Sugahara, Daisuke; Kaji, Hiroyuki; Sugihara, Kazushi; Asano, Masahide; Narimatsu, Hisashi

2012-01-01

Model organisms containing deletion or mutation in a glycosyltransferase-gene exhibit various physiological abnormalities, suggesting that specific glycan motifs on certain proteins play important roles in vivo. Identification of the target proteins of glycosyltransferase isozymes is the key to understand the roles of glycans. Here, we demonstrated the proteome-scale identification of the target proteins specific for a glycosyltransferase isozyme, β1,4-galactosyltransferase-I (β4GalT-I). Although β4GalT-I is the most characterized glycosyltransferase, its distinctive contribution to β1,4-galactosylation has been hardly described so far. We identified a large number of candidates for the target proteins specific to β4GalT-I by comparative analysis of β4GalT-I-deleted and wild-type mice using the LC/MS-based technique with the isotope-coded glycosylation site-specific tagging (IGOT) of lectin-captured N-glycopeptides. Our approach to identify the target proteins in a proteome-scale offers common features and trends in the target proteins, which facilitate understanding of the mechanism that controls assembly of a particular glycan motif on specific proteins. PMID:23002422

Large-scale structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.

1983-01-01

Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

Improved actions and asymptotic scaling in lattice Yang-Mills theory

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

Langfeld, Kurt

2007-11-01

Improved actions in SU(2) and SU(3) lattice gauge theories are investigated with an emphasis on asymptotic scaling. A new scheme for tadpole improvement is proposed. The standard but heuristic tadpole improvement emerges from a mean field approximation from the new approach. Scaling is investigated by means of the large distance static quark potential. Both the generic and the new tadpole scheme yield significant improvements on asymptotic scaling when compared with loop improved actions. A study of the rotational symmetry breaking terms, however, reveals that only the new improvement scheme efficiently eliminates the leading irrelevant term from the action.

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

Development of a 3D Stream Network and Topography for Improved Large-Scale Hydraulic Modeling

NASA Astrophysics Data System (ADS)

Saksena, S.; Dey, S.; Merwade, V.

2016-12-01

Most digital elevation models (DEMs) used for hydraulic modeling do not include channel bed elevations. As a result, the DEMs are complimented with additional bathymetric data for accurate hydraulic simulations. Existing methods to acquire bathymetric information through field surveys or through conceptual models are limited to reach-scale applications. With an increasing focus on large scale hydraulic modeling of rivers, a framework to estimate and incorporate bathymetry for an entire stream network is needed. This study proposes an interpolation-based algorithm to estimate bathymetry for a stream network by modifying the reach-based empirical River Channel Morphology Model (RCMM). The effect of a 3D stream network that includes river bathymetry is then investigated by creating a 1D hydraulic model (HEC-RAS) and 2D hydrodynamic model (Integrated Channel and Pond Routing) for the Upper Wabash River Basin in Indiana, USA. Results show improved simulation of flood depths and storage in the floodplain. Similarly, the impact of river bathymetry incorporation is more significant in the 2D model as compared to the 1D model.

Proteogenomic database construction driven from large scale RNA-seq data.

PubMed

Woo, Sunghee; Cha, Seong Won; Merrihew, Gennifer; He, Yupeng; Castellana, Natalie; Guest, Clark; MacCoss, Michael; Bafna, Vineet

2014-01-03

The advent of inexpensive RNA-seq technologies and other deep sequencing technologies for RNA has the promise to radically improve genomic annotation, providing information on transcribed regions and splicing events in a variety of cellular conditions. Using MS-based proteogenomics, many of these events can be confirmed directly at the protein level. However, the integration of large amounts of redundant RNA-seq data and mass spectrometry data poses a challenging problem. Our paper addresses this by construction of a compact database that contains all useful information expressed in RNA-seq reads. Applying our method to cumulative C. elegans data reduced 496.2 GB of aligned RNA-seq SAM files to 410 MB of splice graph database written in FASTA format. This corresponds to 1000× compression of data size, without loss of sensitivity. We performed a proteogenomics study using the custom data set, using a completely automated pipeline, and identified a total of 4044 novel events, including 215 novel genes, 808 novel exons, 12 alternative splicings, 618 gene-boundary corrections, 245 exon-boundary changes, 938 frame shifts, 1166 reverse strands, and 42 translated UTRs. Our results highlight the usefulness of transcript + proteomic integration for improved genome annotations.

CPTAC Releases Cancer Proteome Confirmatory Ovarian Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying diagnostics and therapies that will improve patients’ lives. Because a comprehensive molecular view of cancer is important for ultimately guiding treatment, the National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) has released the cancer proteome confirmatory ovarian study data sets.

Large-Scale Advanced Prop-Fan (LAP)

NASA Technical Reports Server (NTRS)

Degeorge, C. L.

1988-01-01

In recent years, considerable attention has been directed toward improving aircraft fuel efficiency. Analytical studies and research with wind tunnel models have demonstrated that the high inherent efficiency of low speed turboprop propulsion systems may now be extended to the Mach .8 flight regime of today's commercial airliners. This can be accomplished with a propeller, employing a large number of thin highly swept blades. The term Prop-Fan has been coined to describe such a propulsion system. In 1983 the NASA-Lewis Research Center contracted with Hamilton Standard to design, build and test a near full scale Prop-Fan, designated the Large Scale Advanced Prop-Fan (LAP). This report provides a detailed description of the LAP program. The assumptions and analytical procedures used in the design of Prop-Fan system components are discussed in detail. The manufacturing techniques used in the fabrication of the Prop-Fan are presented. Each of the tests run during the course of the program are also discussed and the major conclusions derived from them stated.

Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

PubMed Central

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N.; Carter, Jeff; Dalby, Andrew B.; Eaton, Bruce E.; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Koch, Tad H.; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K.; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M.; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I.; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D.; Vrkljan, Mike; Walker, Jeffrey J.; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K.; Wolfson, Alexey; Wolk, Steven K.; Zhang, Chi; Zichi, Dom

2010-01-01

Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (∼100 fM–1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. Conclusions/Significance We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of

Large Scale Metal Additive Techniques Review

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

Nycz, Andrzej; Adediran, Adeola I; Noakes, Mark W

2016-01-01

In recent years additive manufacturing made long strides toward becoming a main stream production technology. Particularly strong progress has been made in large-scale polymer deposition. However, large scale metal additive has not yet reached parity with large scale polymer. This paper is a review study of the metal additive techniques in the context of building large structures. Current commercial devices are capable of printing metal parts on the order of several cubic feet compared to hundreds of cubic feet for the polymer side. In order to follow the polymer progress path several factors are considered: potential to scale, economy, environmentmore » friendliness, material properties, feedstock availability, robustness of the process, quality and accuracy, potential for defects, and post processing as well as potential applications. This paper focuses on current state of art of large scale metal additive technology with a focus on expanding the geometric limits.« less

Improving Disease Prediction by Incorporating Family Disease History in Risk Prediction Models with Large-Scale Genetic Data.

PubMed

Gim, Jungsoo; Kim, Wonji; Kwak, Soo Heon; Choi, Hosik; Park, Changyi; Park, Kyong Soo; Kwon, Sunghoon; Park, Taesung; Won, Sungho

2017-11-01

Despite the many successes of genome-wide association studies (GWAS), the known susceptibility variants identified by GWAS have modest effect sizes, leading to notable skepticism about the effectiveness of building a risk prediction model from large-scale genetic data. However, in contrast to genetic variants, the family history of diseases has been largely accepted as an important risk factor in clinical diagnosis and risk prediction. Nevertheless, the complicated structures of the family history of diseases have limited their application in clinical practice. Here, we developed a new method that enables incorporation of the general family history of diseases with a liability threshold model, and propose a new analysis strategy for risk prediction with penalized regression analysis that incorporates both large numbers of genetic variants and clinical risk factors. Application of our model to type 2 diabetes in the Korean population (1846 cases and 1846 controls) demonstrated that single-nucleotide polymorphisms accounted for 32.5% of the variation explained by the predicted risk scores in the test data set, and incorporation of family history led to an additional 6.3% improvement in prediction. Our results illustrate that family medical history provides valuable information on the variation of complex diseases and improves prediction performance. Copyright © 2017 by the Genetics Society of America.

Improved Blood Pressure Control Associated With a Large-Scale Hypertension Program

PubMed Central

Jaffe, Marc G.; Lee, Grace A.; Young, Joseph D.; Sidney, Stephen; Go, Alan S.

2014-01-01

Importance Hypertension control for large populations remains a major challenge. Objective To describe a large-scale hypertension program in northern California and to compare rates of hypertension control of the program to statewide and national estimates. Design, Setting, and Patients The Kaiser Permanente Northern California (KPNC) Hypertension program included a multi-faceted approach to blood pressure control. Patients identified with hypertension within an integrated health care delivery system in northern California from 2001–2009 were included. The comparison group included insured patients in California between 2006–2009 who were included in the Healthcare Effectiveness Data and Information Set (HEDIS) commercial measurement by California health insurance plans participating in the National Committee for Quality Assurance (NQCA) quality measure reporting process. A secondary comparison group was the reported national mean NCQA HEDIS commercial rates of hypertension control from 2001–2009 from health plans that participated in the NQCA HEDIS quality measure reporting process. Main Outcome Measure Hypertension control as defined by NCQA HEDIS. Results The KPNC hypertension registry established in 2001 included 349,937 patients and grew to 652,763 by 2009. The NCQA HEDIS commercial measurement for hypertension control increased from 44% to 80% during the study period. In contrast, the national mean NCQA HEDIS commercial measurement increased modestly from 55.4% to 64.1%. California mean NCQA HEDIS commercial rates of hypertension were similar to those reported nationally from 2006–2009. (63.4% to 69.4%). Conclusion and Relevance Among adults diagnosed with hypertension, implementation of a large-scale hypertension program was associated with a significant increase in hypertension control compared with state and national control rates. PMID:23989679

Current algorithmic solutions for peptide-based proteomics data generation and identification.

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

Peptide-based proteomic data sets are ever increasing in size and complexity. These data sets provide computational challenges when attempting to quickly analyze spectra and obtain correct protein identifications. Database search and de novo algorithms must consider high-resolution MS/MS spectra and alternative fragmentation methods. Protein inference is a tricky problem when analyzing large data sets of degenerate peptide identifications. Combining multiple algorithms for improved peptide identification puts significant strain on computational systems when investigating large data sets. This review highlights some of the recent developments in peptide and protein identification algorithms for analyzing shotgun mass spectrometry data when encountering the aforementioned hurdles. Also explored are the roles that analytical pipelines, public spectral libraries, and cloud computing play in the evolution of peptide-based proteomics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Advances in targeted proteomics and applications to biomedical research

PubMed Central

Shi, Tujin; Song, Ehwang; Nie, Song; Rodland, Karin D.; Liu, Tao; Qian, Wei-Jun; Smith, Richard D.

2016-01-01

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed. PMID:27302376

Large scale tracking algorithms

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

Hansen, Ross L.; Love, Joshua Alan; Melgaard, David Kennett

2015-01-01

Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For highermore » resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.« less

Time- and polarity-dependent proteomic changes associated with homeostatic scaling at central synapses

PubMed Central

Schanzenbächer, Christoph T

2018-01-01

In homeostatic scaling at central synapses, the depth and breadth of cellular mechanisms that detect the offset from the set-point, detect the duration of the offset and implement a cellular response are not well understood. To understand the time-dependent scaling dynamics we treated cultured rat hippocampal cells with either TTX or bicucculline for 2 hr to induce the process of up- or down-scaling, respectively. During the activity manipulation we metabolically labeled newly synthesized proteins using BONCAT. We identified 168 newly synthesized proteins that exhibited significant changes in expression. To obtain a temporal trajectory of the response, we compared the proteins synthesized within 2 hr or 24 hr of the activity manipulation. Surprisingly, there was little overlap in the significantly regulated newly synthesized proteins identified in the early- and integrated late response datasets. There was, however, overlap in the functional categories that are modulated early and late. These data indicate that within protein function groups, different proteomic choices can be made to effect early and late homeostatic responses that detect the duration and polarity of the activity manipulation. PMID:29447110

Merging Station Observations with Large-Scale Gridded Data to Improve Hydrological Predictions over Chile

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Verbist, K. M. J.

2016-12-01

Hydrological predictions at regional-to-global scales are often hampered by the lack of meteorological forcing data. The use of large-scale gridded meteorological data is able to overcome this limitation, but these data are subject to regional biases and unrealistic values at local scale. This is especially challenging in regions such as Chile, where climate exhibits high spatial heterogeneity as a result of long latitude span and dramatic elevation changes. However, regional station-based observational datasets are not fully exploited and have the potential of constraining biases and spatial patterns. This study aims at adjusting precipitation and temperature estimates from the Princeton University global meteorological forcing (PGF) gridded dataset to improve hydrological simulations over Chile, by assimilating 982 gauges from the Dirección General de Aguas (DGA). To merge station data with the gridded dataset, we use a state-space estimation method to produce optimal gridded estimates, considering both the error of the station measurements and the gridded PGF product. The PGF daily precipitation, maximum and minimum temperature at 0.25° spatial resolution are adjusted for the period of 1979-2010. Precipitation and temperature gauges with long and continuous records (>70% temporal coverage) are selected, while the remaining stations are used for validation. The leave-one-out cross validation verifies the robustness of this data assimilation approach. The merged dataset is then used to force the Variable Infiltration Capacity (VIC) hydrological model over Chile at daily time step which are compared to the observations of streamflow. Our initial results show that the station-merged PGF precipitation effectively captures drizzle and the spatial pattern of storms. Overall the merged dataset has significant improvements compared to the original PGF with reduced biases and stronger inter-annual variability. The invariant spatial pattern of errors between the station

Detectability of large-scale power suppression in the galaxy distribution

NASA Astrophysics Data System (ADS)

Gibelyou, Cameron; Huterer, Dragan; Fang, Wenjuan

2010-12-01

Suppression in primordial power on the Universe’s largest observable scales has been invoked as a possible explanation for large-angle observations in the cosmic microwave background, and is allowed or predicted by some inflationary models. Here we investigate the extent to which such a suppression could be confirmed by the upcoming large-volume redshift surveys. For definiteness, we study a simple parametric model of suppression that improves the fit of the vanilla ΛCDM model to the angular correlation function measured by WMAP in cut-sky maps, and at the same time improves the fit to the angular power spectrum inferred from the maximum likelihood analysis presented by the WMAP team. We find that the missing power at large scales, favored by WMAP observations within the context of this model, will be difficult but not impossible to rule out with a galaxy redshift survey with large-volume (˜100Gpc3). A key requirement for success in ruling out power suppression will be having redshifts of most galaxies detected in the imaging survey.

Improved metabolites of pharmaceutical ingredient grade Ginkgo biloba and the correlated proteomics analysis.

PubMed

Zheng, Wen; Li, Ximin; Zhang, Lin; Zhang, Yanzhen; Lu, Xiaoping; Tian, Jingkui

2015-06-01

Ginkgo biloba is an attractive and traditional medicinal plant, and has been widely used as a phytomedicine in the prevention and treatment of cardiovascular and cerebrovascular diseases. Flavonoids and terpene lactones are the major bioactive components of Ginkgo, whereas the ginkgolic acids (GAs) with strong allergenic properties are strictly controlled. In this study, we tested the content of flavonoids and GAs under ultraviolet-B (UV-B) treatment and performed comparative proteomic analyses to determine the differential proteins that occur upon UV-B radiation. That might play a crucial role in producing flavonoids and GAs. Our phytochemical analyses demonstrated that UV-B irradiation significantly increased the content of active flavonoids, and decreased the content of toxic GAs. We conducted comparative proteomic analysis of both whole leaf and chloroplasts proteins. In total, 27 differential proteins in the whole leaf and 43 differential proteins in the chloroplast were positively identified and functionally annotated. The proteomic data suggested that enhanced UV-B radiation exposure activated antioxidants and stress-responsive proteins as well as reduced the rate of photosynthesis. We demonstrate that UV-B irradiation pharmaceutically improved the metabolic ingredients of Ginkgo, particularly in terms of reducing GAs. With high UV absorption properties, and antioxidant activities, the flavonoids were likely highly induced as protective molecules following UV-B irradiation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

PubMed Central

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L.; Dianes, José A.; del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W.; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-01-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra. PMID:27493588

Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.

PubMed

Griss, Johannes; Perez-Riverol, Yasset; Lewis, Steve; Tabb, David L; Dianes, José A; Del-Toro, Noemi; Rurik, Marc; Walzer, Mathias W; Kohlbacher, Oliver; Hermjakob, Henning; Wang, Rui; Vizcaíno, Juan Antonio

2016-08-01

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.

PubMed

Xu, Ruilian; Tang, Jun; Deng, Quantong; He, Wan; Sun, Xiujie; Xia, Ligang; Cheng, Zhiqiang; He, Lisheng; You, Shuyuan; Hu, Jintao; Fu, Yuxiang; Zhu, Jian; Chen, Yixin; Gao, Weina; He, An; Guo, Zhengyu; Lin, Lin; Li, Hua; Hu, Chaofeng; Tian, Ruijun

2018-05-01

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm 2 and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm 2 and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

The effect of various parameters of large scale radio propagation models on improving performance mobile communications

NASA Astrophysics Data System (ADS)

Pinem, M.; Fauzi, R.

2018-02-01

One technique for ensuring continuity of wireless communication services and keeping a smooth transition on mobile communication networks is the soft handover technique. In the Soft Handover (SHO) technique the inclusion and reduction of Base Station from the set of active sets is determined by initiation triggers. One of the initiation triggers is based on the strong reception signal. In this paper we observed the influence of parameters of large-scale radio propagation models to improve the performance of mobile communications. The observation parameters for characterizing the performance of the specified mobile system are Drop Call, Radio Link Degradation Rate and Average Size of Active Set (AS). The simulated results show that the increase in altitude of Base Station (BS) Antenna and Mobile Station (MS) Antenna contributes to the improvement of signal power reception level so as to improve Radio Link quality and increase the average size of Active Set and reduce the average Drop Call rate. It was also found that Hata’s propagation model contributed significantly to improvements in system performance parameters compared to Okumura’s propagation model and Lee’s propagation model.

A case report of evaluating a large-scale health systems improvement project in an uncontrolled setting: a quality improvement initiative in KwaZulu-Natal, South Africa.

PubMed

Mate, Kedar S; Ngidi, Wilbroda Hlolisile; Reddy, Jennifer; Mphatswe, Wendy; Rollins, Nigel; Barker, Pierre

2013-11-01

New approaches are needed to evaluate quality improvement (QI) within large-scale public health efforts. This case report details challenges to large-scale QI evaluation, and proposes solutions relying on adaptive study design. We used two sequential evaluative methods to study a QI effort to improve delivery of HIV preventive care in public health facilities in three districts in KwaZulu-Natal, South Africa, over a 3-year period. We initially used a cluster randomised controlled trial (RCT) design. During the RCT study period, tensions arose between intervention implementation and evaluation design due to loss of integrity of the randomisation unit over time, pressure to implement changes across the randomisation unit boundaries, and use of administrative rather than functional structures for the randomisation. In response to this loss of design integrity, we switched to a more flexible intervention design and a mixed-methods quasiexperimental evaluation relying on both a qualitative analysis and an interrupted time series quantitative analysis. Cluster RCT designs may not be optimal for evaluating complex interventions to improve implementation in uncontrolled 'real world' settings. More flexible, context-sensitive evaluation designs offer a better balance of the need to adjust the intervention during the evaluation to meet implementation challenges while providing the data required to evaluate effectiveness. Our case study involved HIV care in a resource-limited setting, but these issues likely apply to complex improvement interventions in other settings.

Elucidating the fungal stress response by proteomics.

PubMed

Kroll, Kristin; Pähtz, Vera; Kniemeyer, Olaf

2014-01-31

Fungal species need to cope with stress, both in the natural environment and during interaction of human- or plant pathogenic fungi with their host. Many regulatory circuits governing the fungal stress response have already been discovered. However, there are still large gaps in the knowledge concerning the changes of the proteome during adaptation to environmental stress conditions. With the application of proteomic methods, particularly 2D-gel and gel-free, LC/MS-based methods, first insights into the composition and dynamic changes of the fungal stress proteome could be obtained. Here, we review the recent proteome data generated for filamentous fungi and yeasts. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Skin Friction Reduction Through Large-Scale Forcing

NASA Astrophysics Data System (ADS)

Bhatt, Shibani; Artham, Sravan; Gnanamanickam, Ebenezer

2017-11-01

Flow structures in a turbulent boundary layer larger than an integral length scale (δ), referred to as large-scales, interact with the finer scales in a non-linear manner. By targeting these large-scales and exploiting this non-linear interaction wall shear stress (WSS) reduction of over 10% has been achieved. The plane wall jet (PWJ), a boundary layer which has highly energetic large-scales that become turbulent independent of the near-wall finer scales, is the chosen model flow field. It's unique configuration allows for the independent control of the large-scales through acoustic forcing. Perturbation wavelengths from about 1 δ to 14 δ were considered with a reduction in WSS for all wavelengths considered. This reduction, over a large subset of the wavelengths, scales with both inner and outer variables indicating a mixed scaling to the underlying physics, while also showing dependence on the PWJ global properties. A triple decomposition of the velocity fields shows an increase in coherence due to forcing with a clear organization of the small scale turbulence with respect to the introduced large-scale. The maximum reduction in WSS occurs when the introduced large-scale acts in a manner so as to reduce the turbulent activity in the very near wall region. This material is based upon work supported by the Air Force Office of Scientific Research under Award Number FA9550-16-1-0194 monitored by Dr. Douglas Smith.

Improvement of Soybean Products Through the Response Mechanism Analysis Using Proteomic Technique.

PubMed

Wang, Xin; Komatsu, Setsuko

Soybean is rich in protein/vegetable oil and contains several phytochemicals such as isoflavones and phenolic compounds. Because of the predominated nutritional values, soybean is considered as traditional health benefit food. Soybean is a widely cultivated crop; however, its growth and yield are markedly affected by adverse environmental conditions. Proteomic techniques make it feasible to map protein profiles both during soybean growth and under unfavorable conditions. The stress-responsive mechanisms during soybean growth have been uncovered with the help of proteomic studies. In this review, the history of soybean as food and the morphology/physiology of soybean are described. The utilization of proteomics during soybean germination and development is summarized. In addition, the stress-responsive mechanisms explored using proteomic techniques are reviewed in soybean. © 2017 Elsevier Inc. All rights reserved.

Proteomic Analysis of Pigeonpea (Cajanus cajan) Seeds Reveals the Accumulation of Numerous Stress-Related Proteins.

PubMed

Krishnan, Hari B; Natarajan, Savithiry S; Oehrle, Nathan W; Garrett, Wesley M; Darwish, Omar

2017-06-14

Pigeonpea is one of the major sources of dietary protein for more than a billion people living in South Asia. This hardy legume is often grown in low-input and risk-prone marginal environments. Considerable research effort has been devoted by a global research consortium to develop genomic resources for the improvement of this legume crop. These efforts have resulted in the elucidation of the complete genome sequence of pigeonpea. Despite these developments, little is known about the seed proteome of this important crop. Here, we report the proteome of pigeonpea seed. To enable the isolation of maximum number of seed proteins, including those that are present in very low amounts, three different protein fractions were obtained by employing different extraction media. High-resolution two-dimensional (2-D) electrophoresis followed by MALDI-TOF-TOF-MS/MS analysis of these protein fractions resulted in the identification of 373 pigeonpea seed proteins. Consistent with the reported high degree of synteny between the pigeonpea and soybean genomes, a large number of pigeonpea seed proteins exhibited significant amino acid homology with soybean seed proteins. Our proteomic analysis identified a large number of stress-related proteins, presumably due to its adaptation to drought-prone environments. The availability of a pigeonpea seed proteome reference map should shed light on the roles of these identified proteins in various biological processes and facilitate the improvement of seed composition.

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.

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

PubMed

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

2016-01-01

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

A topology visualization early warning distribution algorithm for large-scale network security incidents.

PubMed

He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

2013-01-01

It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

Profiling and Improving I/O Performance of a Large-Scale Climate Scientific Application

NASA Technical Reports Server (NTRS)

Liu, Zhuo; Wang, Bin; Wang, Teng; Tian, Yuan; Xu, Cong; Wang, Yandong; Yu, Weikuan; Cruz, Carlos A.; Zhou, Shujia; Clune, Tom;

Large-scale neuromorphic computing systems

NASA Astrophysics Data System (ADS)

Furber, Steve

2016-10-01

Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind neuromorphic computing has its origins in the seminal work carried out by Carver Mead at Caltech in the late 1980s. This early work influenced others to carry developments forward, and advances in VLSI technology supported steady growth in the scale and capability of neuromorphic devices. Recently, a number of large-scale neuromorphic projects have emerged, taking the approach to unprecedented scales and capabilities. These large-scale projects are associated with major new funding initiatives for brain-related research, creating a sense that the time and circumstances are right for progress in our understanding of information processing in the brain. In this review we present a brief history of neuromorphic engineering then focus on some of the principal current large-scale projects, their main features, how their approaches are complementary and distinct, their advantages and drawbacks, and highlight the sorts of capabilities that each can deliver to neural modellers.

Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics.

PubMed

Lan, Jiayi; Núñez Galindo, Antonio; Doecke, James; Fowler, Christopher; Martins, Ralph N; Rainey-Smith, Stephanie R; Cominetti, Ornella; Dayon, Loïc

2018-04-06

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP 2 ). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP 2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

Pressurized Pepsin Digestion in Proteomics: An Automatable Alternative to Trypsin for Integrated Top-down Bottom-up Proteomics

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

Lopez-Ferrer, Daniel; Petritis, Konstantinos; Robinson, Errol W.

2011-02-01

Integrated top-down bottom-up proteomics combined with online digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to highthroughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications (PTMs). Herein, we describe recent efforts towards efficient integration of bottom-up and top-down LCMS based proteomic strategies. Since most proteomic platforms (i.e. LC systems) operate in acidic environments, we exploited themore » compatibility of the pepsin (i.e. the enzyme’s natural acidic activity) for the integration of bottom-up and top-down proteomics. Pressure enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an offline mode using a Barocycler or an online mode using a modified high pressure LC system referred to as a fast online digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultra-rapid integrated bottom-up top-down proteomic strategy employing a standard mixture of proteins and a monkey pox virus proteome.« less

The transition of a large-scale quality improvement initiative: a bibliometric analysis of the Productive Ward: Releasing Time to Care programme.

PubMed

White, Mark; Wells, John S G; Butterworth, Tony

2014-09-01

To examine the literature related to a large-scale quality improvement initiative, the 'Productive Ward: Releasing Time to Care', providing a bibliometric profile that tracks the level of interest and scale of roll-out and adoption, discussing the implications for sustainability. Productive Ward: Releasing Time to Care (aka Productive Ward) is probably one of the most ambitious quality improvement efforts engaged by the UK-NHS. Politically and financially supported, its main driver was the NHS Institute for Innovation and Improvement. The NHS institute closed in early 2013 leaving a void of resources, knowledge and expertise. UK roll-out of the initiative is well established and has arguably peaked. International interest in the initiative however continues to develop. A comprehensive literature review was undertaken to identify the literature related to the Productive Ward and its implementation (January 2006-June 2013). A bibliometric analysis examined/reviewed the trends and identified/measured interest, spread and uptake. Overall distribution patterns identify a declining trend of interest, with reduced numbers of grey literature and evaluation publications. However, detailed examination of the data shows no reduction in peer-reviewed outputs. There is some evidence that international uptake of the initiative continues to generate publications and create interest. Sustaining this initiative in the UK will require re-energising, a new focus and financing. The transition period created by the closure of its creator may well contribute to further reduced levels of interest and publication outputs in the UK. However, international implementation, evaluation and associated publications could serve to attract professional/academic interest in this well-established, positively reported, quality improvement initiative. This paper provides nurses and ward teams involved in quality improvement programmes with a detailed, current-state, examination and analysis of the

A flexible statistical model for alignment of label-free proteomics data--incorporating ion mobility and product ion information.

PubMed

Benjamin, Ashlee M; Thompson, J Will; Soderblom, Erik J; Geromanos, Scott J; Henao, Ricardo; Kraus, Virginia B; Moseley, M Arthur; Lucas, Joseph E

2013-12-16

The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples. We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

An interactive display system for large-scale 3D models

NASA Astrophysics Data System (ADS)

Liu, Zijian; Sun, Kun; Tao, Wenbing; Liu, Liman

2018-04-01

With the improvement of 3D reconstruction theory and the rapid development of computer hardware technology, the reconstructed 3D models are enlarging in scale and increasing in complexity. Models with tens of thousands of 3D points or triangular meshes are common in practical applications. Due to storage and computing power limitation, it is difficult to achieve real-time display and interaction with large scale 3D models for some common 3D display software, such as MeshLab. In this paper, we propose a display system for large-scale 3D scene models. We construct the LOD (Levels of Detail) model of the reconstructed 3D scene in advance, and then use an out-of-core view-dependent multi-resolution rendering scheme to realize the real-time display of the large-scale 3D model. With the proposed method, our display system is able to render in real time while roaming in the reconstructed scene and 3D camera poses can also be displayed. Furthermore, the memory consumption can be significantly decreased via internal and external memory exchange mechanism, so that it is possible to display a large scale reconstructed scene with over millions of 3D points or triangular meshes in a regular PC with only 4GB RAM.

Optimizing Algorithm Choice for Metaproteomics: Comparing X!Tandem and Proteome Discoverer for Soil Proteomes

NASA Astrophysics Data System (ADS)

Diaz, K. S.; Kim, E. H.; Jones, R. M.; de Leon, K. C.; Woodcroft, B. J.; Tyson, G. W.; Rich, V. I.

2014-12-01

The growing field of metaproteomics links microbial communities to their expressed functions by using mass spectrometry methods to characterize community proteins. Comparison of mass spectrometry protein search algorithms and their biases is crucial for maximizing the quality and amount of protein identifications in mass spectral data. Available algorithms employ different approaches when mapping mass spectra to peptides against a database. We compared mass spectra from four microbial proteomes derived from high-organic content soils searched with two search algorithms: 1) Sequest HT as packaged within Proteome Discoverer (v.1.4) and 2) X!Tandem as packaged in TransProteomicPipeline (v.4.7.1). Searches used matched metagenomes, and results were filtered to allow identification of high probability proteins. There was little overlap in proteins identified by both algorithms, on average just ~24% of the total. However, when adjusted for spectral abundance, the overlap improved to ~70%. Proteome Discoverer generally outperformed X!Tandem, identifying an average of 12.5% more proteins than X!Tandem, with X!Tandem identifying more proteins only in the first two proteomes. For spectrally-adjusted results, the algorithms were similar, with X!Tandem marginally outperforming Proteome Discoverer by an average of ~4%. We then assessed differences in heat shock proteins (HSP) identification by the two algorithms by BLASTing identified proteins against the Heat Shock Protein Information Resource, because HSP hits typically account for the majority signal in proteomes, due to extraction protocols. Total HSP identifications for each of the 4 proteomes were approximately ~15%, ~11%, ~17%, and ~19%, with ~14% for total HSPs with redundancies removed. Of the ~15% average of proteins from the 4 proteomes identified as HSPs, ~10% of proteins and spectra were identified by both algorithms. On average, Proteome Discoverer identified ~9% more HSPs than X!Tandem.

Enablers and barriers to large-scale uptake of improved solid fuel stoves: a systematic review.

PubMed

Rehfuess, Eva A; Puzzolo, Elisa; Stanistreet, Debbi; Pope, Daniel; Bruce, Nigel G

2014-02-01

Globally, 2.8 billion people rely on household solid fuels. Reducing the resulting adverse health, environmental, and development consequences will involve transitioning through a mix of clean fuels and improved solid fuel stoves (IS) of demonstrable effectiveness. To date, achieving uptake of IS has presented significant challenges. We performed a systematic review of factors that enable or limit large-scale uptake of IS in low- and middle-income countries. We conducted systematic searches through multidisciplinary databases, specialist websites, and consulting experts. The review drew on qualitative, quantitative, and case studies and used standardized methods for screening, data extraction, critical appraisal, and synthesis. We summarized our findings as "factors" relating to one of seven domains-fuel and technology characteristics; household and setting characteristics; knowledge and perceptions; finance, tax, and subsidy aspects; market development; regulation, legislation, and standards; programmatic and policy mechanisms-and also recorded issues that impacted equity. We identified 31 factors influencing uptake from 57 studies conducted in Asia, Africa, and Latin America. All domains matter. Although factors such as offering technologies that meet household needs and save fuel, user training and support, effective financing, and facilitative government action appear to be critical, none guarantee success: All factors can be influential, depending on context. The nature of available evidence did not permit further prioritization. Achieving adoption and sustained use of IS at a large scale requires that all factors, spanning household/community and program/societal levels, be assessed and supported by policy. We propose a planning tool that would aid this process and suggest further research to incorporate an evaluation of effectiveness.

Cell-free protein synthesis: applications in proteomics and biotechnology.

PubMed

He, Mingyue

2008-01-01

Protein production is one of the key steps in biotechnology and functional proteomics. Expression of proteins in heterologous hosts (such as in E. coli) is generally lengthy and costly. Cell-free protein synthesis is thus emerging as an attractive alternative. In addition to the simplicity and speed for protein production, cell-free expression allows generation of functional proteins that are difficult to produce by in vivo systems. Recent exploitation of cell-free systems enables novel development of technologies for rapid discovery of proteins with desirable properties from very large libraries. This article reviews the recent development in cell-free systems and their application in the large scale protein analysis.

Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

PubMed

Boja, Emily S; Fehniger, Thomas E; Baker, Mark S; Marko-Varga, György; Rodriguez, Henry

2014-12-05

Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.

Improving seasonal forecast through the state of large-scale climate signals

NASA Astrophysics Data System (ADS)

Samale, Chiara; Zimmerman, Brian; Giuliani, Matteo; Castelletti, Andrea; Block, Paul

2017-04-01

Increasingly uncertain hydrologic regimes are challenging water systems management worldwide, emphasizing the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. In fact, forecasts are usually skillful over short lead time (from hours to days), but predictability tends to decrease on longer lead times. The forecast lead time might be extended by using climate teleconnection, such as El Nino Southern Oscillation (ENSO). Despite the ENSO teleconnection is well defined in some locations such as Western USA and Australia, there is no consensus on how it can be detected and used in other river basins, particularly in Europe, Africa, and Asia. In this work, we propose the use of the Nino Index Phase Analysis for capturing the state of multiple large-scale climate signals (i.e., ENSO, North Atlantic Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, Dipole Mode Index). This climate state information is used for distinguishing the different phases of the climate signals and for identifying relevant teleconnections between the observations of Sea Surface Temperature (SST) that mostly influence the local hydrologic conditions. The framework is applied to the Lake Como system, a regulated lake in northern Italy which is mainly operated for flood control and irrigation supply. Preliminary results show high correlations between SST and three to six months ahead precipitation in the Lake Como basin. This forecast represents a valuable information to partially anticipate the summer water availability, ultimately supporting the improvement of the Lake Como operations.

Free Flow Zonal Electrophoresis for Fractionation of Plant Membrane Compartments Prior to Proteomic Analysis.

PubMed

Barkla, Bronwyn J

2018-01-01

Free flow zonal electrophoresis (FFZE) is a versatile, reproducible, and potentially high-throughput technique for the separation of plant organelles and membranes by differences in membrane surface charge. It offers considerable benefits over traditional fractionation techniques, such as density gradient centrifugation and two-phase partitioning, as it is relatively fast, sample recovery is high, and the method provides unparalleled sample purity. It has been used to successfully purify chloroplasts and mitochondria from plants but also, to obtain highly pure fractions of plasma membrane, tonoplast, ER, Golgi, and thylakoid membranes. Application of the technique can significantly improve protein coverage in large-scale proteomics studies by decreasing sample complexity. Here, we describe the method for the fractionation of plant cellular membranes from leaves by FFZE.

Beyond the proteome: Mass Spectrometry Special Interest Group (MS-SIG) at ISMB/ECCB 2013

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

Ryu, Soyoung; Payne, Samuel H.; Schaab, Christoph

2014-07-02

Mass spectrometry special interest group (MS-SIG) aims to bring together experts from the global research community to discuss highlights and challenges in the field of mass spectrometry (MS)-based proteomics and computational biology. The rapid echnological developments in MS-based proteomics have enabled the generation of a large amount of meaningful information on hundreds to thousands of proteins simultaneously from a biological sample; however, the complexity of the MS data require sophisticated computational algorithms and software for data analysis and interpretation. This year’s MS-SIG meeting theme was ‘Beyond the Proteome’ with major focuses on improving protein identification/quantification and using proteomics data tomore » solve interesting problems in systems biology and clinical research.« less

Large-Scale Outflows in Seyfert Galaxies

NASA Astrophysics Data System (ADS)

Colbert, E. J. M.; Baum, S. A.

1995-12-01

\\catcode`\\@=11 \\ialign{m @th#1hfil ##hfil \\crcr#2\\crcr\\sim\\crcr}}} \\catcode`\\@=12 Highly collimated outflows extend out to Mpc scales in many radio-loud active galaxies. In Seyfert galaxies, which are radio-quiet, the outflows extend out to kpc scales and do not appear to be as highly collimated. In order to study the nature of large-scale (>~1 kpc) outflows in Seyferts, we have conducted optical, radio and X-ray surveys of a distance-limited sample of 22 edge-on Seyfert galaxies. Results of the optical emission-line imaging and spectroscopic survey imply that large-scale outflows are present in >~{{1} /{4}} of all Seyferts. The radio (VLA) and X-ray (ROSAT) surveys show that large-scale radio and X-ray emission is present at about the same frequency. Kinetic luminosities of the outflows in Seyferts are comparable to those in starburst-driven superwinds. Large-scale radio sources in Seyferts appear diffuse, but do not resemble radio halos found in some edge-on starburst galaxies (e.g. M82). We discuss the feasibility of the outflows being powered by the active nucleus (e.g. a jet) or a circumnuclear starburst.

A multi-protease, multi-dissociation, bottom-up-to-top-down proteomic view of the Loxosceles intermedia venom

PubMed Central

Trevisan-Silva, Dilza; Bednaski, Aline V.; Fischer, Juliana S.G.; Veiga, Silvio S.; Bandeira, Nuno; Guthals, Adrian; Marchini, Fabricio K.; Leprevost, Felipe V.; Barbosa, Valmir C.; Senff-Ribeiro, Andrea; Carvalho, Paulo C.

2017-01-01

Venoms are a rich source for the discovery of molecules with biotechnological applications, but their analysis is challenging even for state-of-the-art proteomics. Here we report on a large-scale proteomic assessment of the venom of Loxosceles intermedia, the so-called brown spider. Venom was extracted from 200 spiders and fractioned into two aliquots relative to a 10 kDa cutoff mass. Each of these was further fractioned and digested with trypsin (4 h), trypsin (18 h), pepsin (18 h), and chymotrypsin (18 h), then analyzed by MudPIT on an LTQ-Orbitrap XL ETD mass spectrometer fragmenting precursors by CID, HCD, and ETD. Aliquots of undigested samples were also analyzed. Our experimental design allowed us to apply spectral networks, thus enabling us to obtain meta-contig assemblies, and consequently de novo sequencing of practically complete proteins, culminating in a deep proteome assessment of the venom. Data are available via ProteomeXchange, with identifier PXD005523. PMID:28696408

Internationalization Measures in Large Scale Research Projects

NASA Astrophysics Data System (ADS)

Soeding, Emanuel; Smith, Nancy

2017-04-01

Internationalization measures in Large Scale Research Projects Large scale research projects (LSRP) often serve as flagships used by universities or research institutions to demonstrate their performance and capability to stakeholders and other interested parties. As the global competition among universities for the recruitment of the brightest brains has increased, effective internationalization measures have become hot topics for universities and LSRP alike. Nevertheless, most projects and universities are challenged with little experience on how to conduct these measures and make internationalization an cost efficient and useful activity. Furthermore, those undertakings permanently have to be justified with the Project PIs as important, valuable tools to improve the capacity of the project and the research location. There are a variety of measures, suited to support universities in international recruitment. These include e.g. institutional partnerships, research marketing, a welcome culture, support for science mobility and an effective alumni strategy. These activities, although often conducted by different university entities, are interlocked and can be very powerful measures if interfaced in an effective way. On this poster we display a number of internationalization measures for various target groups, identify interfaces between project management, university administration, researchers and international partners to work together, exchange information and improve processes in order to be able to recruit, support and keep the brightest heads to your project.

A flexible statistical model for alignment of label-free proteomics data – incorporating ion mobility and product ion information

PubMed Central

2013-01-01

Background The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing - the matching of peptide measurements across samples. Results We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates. Conclusions Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods. PMID:24341404

Large-scale solar magnetic fields and H-alpha patterns

NASA Technical Reports Server (NTRS)

Mcintosh, P. S.

1972-01-01

Coronal and interplanetary magnetic fields computed from measurements of large-scale photospheric magnetic fields suffer from interruptions in day-to-day observations and the limitation of using only measurements made near the solar central meridian. Procedures were devised for inferring the lines of polarity reversal from H-alpha solar patrol photographs that map the same large-scale features found on Mt. Wilson magnetograms. These features may be monitored without interruption by combining observations from the global network of observatories associated with NOAA's Space Environment Services Center. The patterns of inferred magnetic fields may be followed accurately as far as 60 deg from central meridian. Such patterns will be used to improve predictions of coronal features during the next solar eclipse.

Proteomics meets blue biotechnology: a wealth of novelties and opportunities.

PubMed

Hartmann, Erica M; Durighello, Emie; Pible, Olivier; Nogales, Balbina; Beltrametti, Fabrizio; Bosch, Rafael; Christie-Oleza, Joseph A; Armengaud, Jean

2014-10-01

Blue biotechnology, in which aquatic environments provide the inspiration for various products such as food additives, aquaculture, biosensors, green chemistry, bioenergy, and pharmaceuticals, holds enormous promise. Large-scale efforts to sequence aquatic genomes and metagenomes, as well as campaigns to isolate new organisms and culture-based screenings, are helping to push the boundaries of known organisms. Mass spectrometry-based proteomics can complement 16S gene sequencing in the effort to discover new organisms of potential relevance to blue biotechnology by facilitating the rapid screening of microbial isolates and by providing in depth profiles of the proteomes and metaproteomes of marine organisms, both model cultivable isolates and, more recently, exotic non-cultivable species and communities. Proteomics has already contributed to blue biotechnology by identifying aquatic proteins with potential applications to food fermentation, the textile industry, and biomedical drug development. In this review, we discuss historical developments in blue biotechnology, the current limitations to the known marine biosphere, and the ways in which mass spectrometry can expand that knowledge. We further speculate about directions that research in blue biotechnology will take given current and near-future technological advancements in mass spectrometry. Copyright © 2014 Elsevier B.V. All rights reserved.

Synchronization of coupled large-scale Boolean networks

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

Li, Fangfei, E-mail: li-fangfei@163.com

2014-03-15

This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework

PubMed Central

2012-01-01

Background For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. Results We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. Conclusion The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources. PMID:23216909

Effects of Hypertension and Exercise on Cardiac Proteome Remodelling

PubMed Central

Petriz, Bernardo A.; Franco, Octavio L.

2014-01-01

Left ventricle hypertrophy is a common outcome of pressure overload stimulus closely associated with hypertension. This process is triggered by adverse molecular signalling, gene expression, and proteome alteration. Proteomic research has revealed that several molecular targets are associated with pathologic cardiac hypertrophy, including angiotensin II, endothelin-1 and isoproterenol. Several metabolic, contractile, and stress-related proteins are shown to be altered in cardiac hypertrophy derived by hypertension. On the other hand, exercise is a nonpharmacologic agent used for hypertension treatment, where cardiac hypertrophy induced by exercise training is characterized by improvement in cardiac function and resistance against ischemic insult. Despite the scarcity of proteomic research performed with exercise, healthy and pathologic heart proteomes are shown to be modulated in a completely different way. Hence, the altered proteome induced by exercise is mostly associated with cardioprotective aspects such as contractile and metabolic improvement and physiologic cardiac hypertrophy. The present review, therefore, describes relevant studies involving the molecular characteristics and alterations from hypertensive-induced and exercise-induced hypertrophy, as well as the main proteomic research performed in this field. Furthermore, proteomic research into the effect of hypertension on other target-demerged organs is examined. PMID:24877123

Improving Prediction of Large-scale Regime Transitions

NASA Astrophysics Data System (ADS)

Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

2017-12-01

Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these

A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors

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

Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Jacobs, Jon M.

2011-12-01

Quantification of LC-MS peak intensities assigned during peptide identification in a typical comparative proteomics experiment will deviate from run-to-run of the instrument due to both technical and biological variation. Thus, normalization of peak intensities across a LC-MS proteomics dataset is a fundamental step in pre-processing. However, the downstream analysis of LC-MS proteomics data can be dramatically affected by the normalization method selected . Current normalization procedures for LC-MS proteomics data are presented in the context of normalization values derived from subsets of the full collection of identified peptides. The distribution of these normalization values is unknown a priori. If theymore » are not independent from the biological factors associated with the experiment the normalization process can introduce bias into the data, which will affect downstream statistical biomarker discovery. We present a novel approach to evaluate normalization strategies, where a normalization strategy includes the peptide selection component associated with the derivation of normalization values. Our approach evaluates the effect of normalization on the between-group variance structure in order to identify candidate normalization strategies that improve the structure of the data without introducing bias into the normalized peak intensities.« less

Substrate-Mediated Laser Ablation under Ambient Conditions for Spatially-Resolved Tissue Proteomics

PubMed Central

Fatou, Benoit; Wisztorski, Maxence; Focsa, Cristian; Salzet, Michel; Ziskind, Michael; Fournier, Isabelle

2015-01-01

Numerous applications of ambient Mass Spectrometry (MS) have been demonstrated over the past decade. They promoted the emergence of various micro-sampling techniques such as Laser Ablation/Droplet Capture (LADC). LADC consists in the ablation of analytes from a surface and their subsequent capture in a solvent droplet which can then be analyzed by MS. LADC is thus generally performed in the UV or IR range, using a wavelength at which analytes or the matrix absorb. In this work, we explore the potential of visible range LADC (532 nm) as a micro-sampling technology for large-scale proteomics analyses. We demonstrate that biomolecule analyses using 532 nm LADC are possible, despite the low absorbance of biomolecules at this wavelength. This is due to the preponderance of an indirect substrate-mediated ablation mechanism at low laser energy which contrasts with the conventional direct ablation driven by sample absorption. Using our custom LADC system and taking advantage of this substrate-mediated ablation mechanism, we were able to perform large-scale proteomic analyses of micro-sampled tissue sections and demonstrated the possible identification of proteins with relevant biological functions. Consequently, the 532 nm LADC technique offers a new tool for biological and clinical applications. PMID:26674367

Dissecting the large-scale galactic conformity

NASA Astrophysics Data System (ADS)

Seo, Seongu

2018-01-01

Galactic conformity is an observed phenomenon that galaxies located in the same region have similar properties such as star formation rate, color, gas fraction, and so on. The conformity was first observed among galaxies within in the same halos (“one-halo conformity”). The one-halo conformity can be readily explained by mutual interactions among galaxies within a halo. Recent observations however further witnessed a puzzling connection among galaxies with no direct interaction. In particular, galaxies located within a sphere of ~5 Mpc radius tend to show similarities, even though the galaxies do not share common halos with each other ("two-halo conformity" or “large-scale conformity”). Using a cosmological hydrodynamic simulation, Illustris, we investigate the physical origin of the two-halo conformity and put forward two scenarios. First, back-splash galaxies are likely responsible for the large-scale conformity. They have evolved into red galaxies due to ram-pressure stripping in a given galaxy cluster and happen to reside now within a ~5 Mpc sphere. Second, galaxies in strong tidal field induced by large-scale structure also seem to give rise to the large-scale conformity. The strong tides suppress star formation in the galaxies. We discuss the importance of the large-scale conformity in the context of galaxy evolution.

Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging

PubMed Central

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-01-01

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm. PMID:28555057

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

PubMed Central

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

2016-01-01

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

Large Scale Data Mining to Improve Usability of Data: An Intelligent Archive Testbed

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuram; Isaac, David; Yang, Wenli; Morse, Steve

2005-01-01

Research in certain scientific disciplines - including Earth science, particle physics, and astrophysics - continually faces the challenge that the volume of data needed to perform valid scientific research can at times overwhelm even a sizable research community. The desire to improve utilization of this data gave rise to the Intelligent Archives project, which seeks to make data archives active participants in a knowledge building system capable of discovering events or patterns that represent new information or knowledge. Data mining can automatically discover patterns and events, but it is generally viewed as unsuited for large-scale use in disciplines like Earth science that routinely involve very high data volumes. Dozens of research projects have shown promising uses of data mining in Earth science, but all of these are based on experiments with data subsets of a few gigabytes or less, rather than the terabytes or petabytes typically encountered in operational systems. To bridge this gap, the Intelligent Archives project is establishing a testbed with the goal of demonstrating the use of data mining techniques in an operationally-relevant environment. This paper discusses the goals of the testbed and the design choices surrounding critical issues that arose during testbed implementation.

Stable isotope dimethyl labelling for quantitative proteomics and beyond

PubMed Central

Hsu, Jue-Liang; Chen, Shu-Hui

2016-01-01

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644970

Proteomics Insights into Autophagy.

PubMed

Cudjoe, Emmanuel K; Saleh, Tareq; Hawkridge, Adam M; Gewirtz, David A

2017-10-01

Autophagy, a conserved cellular process by which cells recycle their contents either to maintain basal homeostasis or in response to external stimuli, has for the past two decades become one of the most studied physiological processes in cell biology. The 2016 Nobel Prize in Medicine and Biology awarded to Dr. Ohsumi Yoshinori, one of the first scientists to characterize this cellular mechanism, attests to its importance. The induction and consequent completion of the process of autophagy results in wide ranging changes to the cellular proteome as well as the secretome. MS-based proteomics affords the ability to measure, in an unbiased manner, the ubiquitous changes that occur when autophagy is initiated and progresses in the cell. The continuous improvements and advances in mass spectrometers, especially relating to ionization sources and detectors, coupled with advances in proteomics experimental design, has made it possible to study autophagy, among other process, in great detail. Innovative labeling strategies and protein separation techniques as well as complementary methods including immuno-capture/blotting/staining have been used in proteomics studies to provide more specific protein identification. In this review, we will discuss recent advances in proteomics studies focused on autophagy. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving healthcare systems' disclosures of large-scale adverse events: a Department of Veterans Affairs leadership, policymaker, research and stakeholder partnership.

PubMed

Elwy, A Rani; Bokhour, Barbara G; Maguire, Elizabeth M; Wagner, Todd H; Asch, Steven M; Gifford, Allen L; Gallagher, Thomas H; Durfee, Janet M; Martinello, Richard A; Schiffner, Susan; Jesse, Robert L

2014-12-01

The Department of Veterans Affairs (VA) mandates disclosure of large-scale adverse events to patients, even if risk of harm is not clearly present. Concerns about past disclosures warranted further examination of the impact of this policy. Through a collaborative partnership between VA leaders, policymakers, researchers and stakeholders, the objective was to empirically identify critical aspects of disclosure processes as a first step towards improving future disclosures. Semi-structured interviews were conducted with participants at nine VA facilities where recent disclosures took place. Ninety-seven stakeholders participated in the interviews: 38 employees, 28 leaders (from facilities, regions and national offices), 27 Veteran patients and family members, and four congressional staff members. Facility and regional leaders were interviewed by telephone, followed by a two-day site visit where employees, patients and family members were interviewed face-to-face. National leaders and congressional staff also completed telephone interviews. Interviews were analyzed using rapid qualitative assessment processes. Themes were mapped to the stages of the Crisis and Emergency Risk Communication model: pre-crisis, initial event, maintenance, resolution and evaluation. Many areas for improvement during disclosure were identified, such as preparing facilities better (pre-crisis), creating rapid communications, modifying disclosure language, addressing perceptions of harm, reducing complexity, and seeking assistance from others (initial event), managing communication with other stakeholders (maintenance), minimizing effects on staff and improving trust (resolution), and addressing facilities' needs (evaluation). Through the partnership, five recommendations to improve disclosures during each stage of communication have been widely disseminated throughout the VA using non-academic strategies. Some improvements have been made; other recommendations will be addressed through

The Large -scale Distribution of Galaxies

NASA Astrophysics Data System (ADS)

Flin, Piotr

A review of the Large-scale structure of the Universe is given. A connection is made with the titanic work by Johannes Kepler in many areas of astronomy and cosmology. A special concern is made to spatial distribution of Galaxies, voids and walls (cellular structure of the Universe). Finaly, the author is concluding that the large scale structure of the Universe can be observed in much greater scale that it was thought twenty years ago.

Subgrid-scale models for large-eddy simulation of rotating turbulent channel flows

NASA Astrophysics Data System (ADS)

Silvis, Maurits H.; Bae, Hyunji Jane; Trias, F. Xavier; Abkar, Mahdi; Moin, Parviz; Verstappen, Roel

2017-11-01

We aim to design subgrid-scale models for large-eddy simulation of rotating turbulent flows. Rotating turbulent flows form a challenging test case for large-eddy simulation due to the presence of the Coriolis force. The Coriolis force conserves the total kinetic energy while transporting it from small to large scales of motion, leading to the formation of large-scale anisotropic flow structures. The Coriolis force may also cause partial flow laminarization and the occurrence of turbulent bursts. Many subgrid-scale models for large-eddy simulation are, however, primarily designed to parametrize the dissipative nature of turbulent flows, ignoring the specific characteristics of transport processes. We, therefore, propose a new subgrid-scale model that, in addition to the usual dissipative eddy viscosity term, contains a nondissipative nonlinear model term designed to capture transport processes, such as those due to rotation. We show that the addition of this nonlinear model term leads to improved predictions of the energy spectra of rotating homogeneous isotropic turbulence as well as of the Reynolds stress anisotropy in spanwise-rotating plane-channel flows. This work is financed by the Netherlands Organisation for Scientific Research (NWO) under Project Number 613.001.212.

Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

PubMed

Lindsey, Merry L; Mayr, Manuel; Gomes, Aldrin V; Delles, Christian; Arrell, D Kent; Murphy, Anne M; Lange, Richard A; Costello, Catherine E; Jin, Yu-Fang; Laskowitz, Daniel T; Sam, Flora; Terzic, Andre; Van Eyk, Jennifer; Srinivas, Pothur R

2015-09-01

The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings. © 2015 American Heart Association, Inc.

Proteomics Improves the New Understanding of Honeybee Biology.

PubMed

Hora, Zewdu Ararso; Altaye, Solomon Zewdu; Wubie, Abebe Jemberie; Li, Jianke

2018-04-11

The honeybee is one of the most valuable insect pollinators, playing a key role in pollinating wild vegetation and agricultural crops, with significant contribution to the world's food production. Although honeybees have long been studied as model for social evolution, honeybee biology at the molecular level remained poorly understood until the year 2006. With the availability of the honeybee genome sequence and technological advancements in protein separation, mass spectrometry, and bioinformatics, aspects of honeybee biology such as developmental biology, physiology, behavior, neurobiology, and immunology have been explored to new depths at molecular and biochemical levels. This Review comprehensively summarizes the recent progress in honeybee biology using proteomics to study developmental physiology, task transition, and physiological changes in some of the organs, tissues, and cells based on achievements from the authors' laboratory in this field. The research advances of honeybee proteomics provide new insights for understanding of honeybee biology and future research directions.

Integrating cell biology and proteomic approaches in plants.

PubMed

Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

2017-10-03

Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of

[ProteoСat: a tool for planning of proteomic experiments].

PubMed

Skvortsov, V S; Alekseychuk, N N; Khudyakov, D V; Mikurova, A V; Rybina, A V; Novikova, S E; Tikhonova, O V

2015-01-01

ProteoCat is a computer program has been designed to help researchers in the planning of large-scale proteomic experiments. The central part of this program is the subprogram of hydrolysis simulation that supports 4 proteases (trypsin, lysine C, endoproteinases AspN and GluC). For the peptides obtained after virtual hydrolysis or loaded from data file a number of properties important in mass-spectrometric experiments can be calculated or predicted. The data can be analyzed or filtered to reduce a set of peptides. The program is using new and improved modification of our methods developed to predict pI and probability of peptide detection; pI can also be predicted for a number of popular pKa's scales, proposed by other investigators. The algorithm for prediction of peptide retention time was realized similar to the algorithm used in the program SSRCalc. ProteoCat can estimate the coverage of amino acid sequences of proteins under defined limitation on peptides detection, as well as the possibility of assembly of peptide fragments with user-defined size of "sticky" ends. The program has a graphical user interface, written on JAVA and available at http://www.ibmc.msk.ru/LPCIT/ProteoCat.

Cytology of DNA Replication Reveals Dynamic Plasticity of Large-Scale Chromatin Fibers.

PubMed

Deng, Xiang; Zhironkina, Oxana A; Cherepanynets, Varvara D; Strelkova, Olga S; Kireev, Igor I; Belmont, Andrew S

2016-09-26

In higher eukaryotic interphase nuclei, the 100- to >1,000-fold linear compaction of chromatin is difficult to reconcile with its function as a template for transcription, replication, and repair. It is challenging to imagine how DNA and RNA polymerases with their associated molecular machinery would move along the DNA template without transient decondensation of observed large-scale chromatin "chromonema" fibers [1]. Transcription or "replication factory" models [2], in which polymerases remain fixed while DNA is reeled through, are similarly difficult to conceptualize without transient decondensation of these chromonema fibers. Here, we show how a dynamic plasticity of chromatin folding within large-scale chromatin fibers allows DNA replication to take place without significant changes in the global large-scale chromatin compaction or shape of these large-scale chromatin fibers. Time-lapse imaging of lac-operator-tagged chromosome regions shows no major change in the overall compaction of these chromosome regions during their DNA replication. Improved pulse-chase labeling of endogenous interphase chromosomes yields a model in which the global compaction and shape of large-Mbp chromatin domains remains largely invariant during DNA replication, with DNA within these domains undergoing significant movements and redistribution as they move into and then out of adjacent replication foci. In contrast to hierarchical folding models, this dynamic plasticity of large-scale chromatin organization explains how localized changes in DNA topology allow DNA replication to take place without an accompanying global unfolding of large-scale chromatin fibers while suggesting a possible mechanism for maintaining epigenetic programming of large-scale chromatin domains throughout DNA replication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Large scale dynamic systems

NASA Technical Reports Server (NTRS)

Doolin, B. F.

1975-01-01

Classes of large scale dynamic systems were discussed in the context of modern control theory. Specific examples discussed were in the technical fields of aeronautics, water resources and electric power.

Proteomics Analysis of the Causative Agent of Typhoid Fever

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

Ansong, Charles; Yoon, Hyunjin; Norbeck, Angela D.

2008-02-01

Typhoid fever is a potentially fatal disease caused by the bacterial pathogen Salmonella enterica serovar Typhi (S. typhi). S. typhi infection is a complex process that involves numerous bacterially-encoded virulence determinants, and these are thought to confer both stringent human host specificity and a high mortality rate. In the present study we used a liquid chromatography-mass spectrometry (LC-MS) based proteomics strategy to investigate the proteome of logarithmic, stationary phase, and low pH/low magnesium (MgM) S. typhi cultures. This represents the first large scale comprehensive characterization of the S. typhi proteome. Our analysis identified a total of 2066 S. typhi proteins.more » In an effort to identify putative S. typhi-specific virulence factors, we then compared our S. typhi results to those obtained in a previously published study of the S. typhimurium proteome under similar conditions (Adkins J.N. et al (2006) Mol Cell Prot). Comparative proteomic analysis of S. typhi (strain Ty2) and S. typhimurium (strains LT2 and 14028) revealed a subset of highly expressed proteins unique to S. typhi that were exclusively detected under conditions that mimic the infective state in macrophage cells. These proteins included CdtB, HlyE, and a conserved protein encoded by t1476. The differential expression of selected proteins was confirmed by Western blot analysis. Taken together with the current literature, our observations suggest that this subset of proteins may play a role in S. typhi pathogenesis and human host specificity. In addition, we observed products of the biotin (bio) operon displayed a higher abundance in the more virulent strains S. typhi-Ty2 and S. typhimurium-14028 compared to the virulence attenuated S. typhimurium strain LT2, suggesting bio proteins may contribute to Salmonella pathogenesis.« less

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

Large-scale synthesis of high-quality hexagonal boron nitride nanosheets for large-area graphene electronics.

PubMed

Lee, Kang Hyuck; Shin, Hyeon-Jin; Lee, Jinyeong; Lee, In-yeal; Kim, Gil-Ho; Choi, Jae-Young; Kim, Sang-Woo

2012-02-08

Hexagonal boron nitride (h-BN) has received a great deal of attention as a substrate material for high-performance graphene electronics because it has an atomically smooth surface, lattice constant similar to that of graphene, large optical phonon modes, and a large electrical band gap. Herein, we report the large-scale synthesis of high-quality h-BN nanosheets in a chemical vapor deposition (CVD) process by controlling the surface morphologies of the copper (Cu) catalysts. It was found that morphology control of the Cu foil is much critical for the formation of the pure h-BN nanosheets as well as the improvement of their crystallinity. For the first time, we demonstrate the performance enhancement of CVD-based graphene devices with large-scale h-BN nanosheets. The mobility of the graphene device on the h-BN nanosheets was increased 3 times compared to that without the h-BN nanosheets. The on-off ratio of the drain current is 2 times higher than that of the graphene device without h-BN. This work suggests that high-quality h-BN nanosheets based on CVD are very promising for high-performance large-area graphene electronics. © 2012 American Chemical Society

Development and application of automated systems for plasmid-based functional proteomics to improve syntheitc biology of engineered industrial microbes for high level expression of proteases for biofertilizer production

USDA-ARS?s Scientific Manuscript database

In addition to microarray technology, which provides a robust method to study protein function in a rapid, economical, and proteome-wide fashion, plasmid-based functional proteomics is an important technology for rapidly obtaining large quantities of protein and determining protein function across a...

The pepATTRACT web server for blind, large-scale peptide-protein docking.

PubMed

de Vries, Sjoerd J; Rey, Julien; Schindler, Christina E M; Zacharias, Martin; Tuffery, Pierre

2017-07-03

Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. pepATTRACT is a novel docking protocol that is fully blind, i.e. it does not require any information about the binding site. In various stages of its development, pepATTRACT has participated in CAPRI, making successful predictions for five out of seven protein-peptide targets. Its performance is similar or better than state-of-the-art local docking protocols that do require binding site information. Here we present a novel web server that carries out the rigid-body stage of pepATTRACT. On the peptiDB benchmark, the web server generates a correct model in the top 50 in 34% of the cases. Compared to the full pepATTRACT protocol, this leads to some loss of performance, but the computation time is reduced from ∼18 h to ∼10 min. Combined with the fact that it is fully blind, this makes the web server well-suited for large-scale in silico protein-peptide docking experiments. The rigid-body pepATTRACT server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/pepATTRACT. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Evaluation of empirical rule of linearly correlated peptide selection (ERLPS) for proteotypic peptide-based quantitative proteomics.

PubMed

Liu, Kehui; Zhang, Jiyang; Fu, Bin; Xie, Hongwei; Wang, Yingchun; Qian, Xiaohong

2014-07-01

Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide-based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an "empirical rule for linearly correlated peptide selection (ERLPS)" in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label-free to O18/O16-labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide-based quantitative proteomics over a large dynamic range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Unexpected features of the dark proteome.

PubMed

Perdigão, Nelson; Heinrich, Julian; Stolte, Christian; Sabir, Kenneth S; Buckley, Michael J; Tabor, Bruce; Signal, Beth; Gloss, Brian S; Hammang, Christopher J; Rost, Burkhard; Schafferhans, Andrea; O'Donoghue, Seán I

2015-12-29

We surveyed the "dark" proteome-that is, regions of proteins never observed by experimental structure determination and inaccessible to homology modeling. For 546,000 Swiss-Prot proteins, we found that 44-54% of the proteome in eukaryotes and viruses was dark, compared with only ∼14% in archaea and bacteria. Surprisingly, most of the dark proteome could not be accounted for by conventional explanations, such as intrinsic disorder or transmembrane regions. Nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. Dark proteins fulfill a wide variety of functions, but a subset showed distinct and largely unexpected features, such as association with secretion, specific tissues, the endoplasmic reticulum, disulfide bonding, and proteolytic cleavage. Dark proteins also had short sequence length, low evolutionary reuse, and few known interactions with other proteins. These results suggest new research directions in structural and computational biology.

Protein homology model refinement by large-scale energy optimization.

PubMed

Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

2018-03-20

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

PubMed

Emery, Samantha J; Lacey, Ernest; Haynes, Paul A

2016-08-01

Giardia duodenalis (syn. G. lamblia and G. intestinalis) is a protozoan parasite of vertebrates and a major contributor to the global burden of diarrheal diseases and gastroenteritis. The publication of multiple genome sequences in the G. duodenalis species complex has provided important insights into parasite biology, and made post-genomic technologies, including proteomics, significantly more accessible. The aims of proteomics are to identify and quantify proteins present in a cell, and assign functions to them within the context of dynamic biological systems. In Giardia, proteomics in the post-genomic era has transitioned from reliance on gel-based systems to utilisation of a diverse array of techniques based on bottom-up LC-MS/MS technologies. Together, these have generated crucial foundations for subcellular proteomes, elucidated intra- and inter-assemblage isolate variation, and identified pathways and markers in differentiation, host-parasite interactions and drug resistance. However, in Giardia, proteomics remains an emerging field, with considerable shortcomings evident from the published research. These include a bias towards assemblage A, a lack of emphasis on quantitative analytical techniques, and limited information on post-translational protein modifications. Additionally, there are multiple areas of research for which proteomic data is not available to add value to published transcriptomic data. The challenge of amalgamating data in the systems biology paradigm necessitates the further generation of large, high-quality quantitative datasets to accurately model parasite biology. This review surveys the current proteomic research available for Giardia and evaluates their technical and quantitative approaches, while contextualising their biological insights into parasite pathology, isolate variation and eukaryotic evolution. Finally, we propose areas of priority for the generation of future proteomic data to explore fundamental questions in Giardia

Contribution of large scale coherence to wind turbine power: A large eddy simulation study in periodic wind farms

NASA Astrophysics Data System (ADS)

Chatterjee, Tanmoy; Peet, Yulia T.

2018-03-01

Length scales of eddies involved in the power generation of infinite wind farms are studied by analyzing the spectra of the turbulent flux of mean kinetic energy (MKE) from large eddy simulations (LES). Large-scale structures with an order of magnitude bigger than the turbine rotor diameter (D ) are shown to have substantial contribution to wind power. Varying dynamics in the intermediate scales (D -10 D ) are also observed from a parametric study involving interturbine distances and hub height of the turbines. Further insight about the eddies responsible for the power generation have been provided from the scaling analysis of two-dimensional premultiplied spectra of MKE flux. The LES code is developed in a high Reynolds number near-wall modeling framework, using an open-source spectral element code Nek5000, and the wind turbines have been modelled using a state-of-the-art actuator line model. The LES of infinite wind farms have been validated against the statistical results from the previous literature. The study is expected to improve our understanding of the complex multiscale dynamics in the domain of large wind farms and identify the length scales that contribute to the power. This information can be useful for design of wind farm layout and turbine placement that take advantage of the large-scale structures contributing to wind turbine power.

Inflation physics from the cosmic microwave background and large scale structure

NASA Astrophysics Data System (ADS)

Abazajian, K. N.; Arnold, K.; Austermann, J.; Benson, B. A.; Bischoff, C.; Bock, J.; Bond, J. R.; Borrill, J.; Buder, I.; Burke, D. L.; Calabrese, E.; Carlstrom, J. E.; Carvalho, C. S.; Chang, C. L.; Chiang, H. C.; Church, S.; Cooray, A.; Crawford, T. M.; Crill, B. P.; Dawson, K. S.; Das, S.; Devlin, M. J.; Dobbs, M.; Dodelson, S.; Doré, O.; Dunkley, J.; Feng, J. L.; Fraisse, A.; Gallicchio, J.; Giddings, S. B.; Green, D.; Halverson, N. W.; Hanany, S.; Hanson, D.; Hildebrandt, S. R.; Hincks, A.; Hlozek, R.; Holder, G.; Holzapfel, W. L.; Honscheid, K.; Horowitz, G.; Hu, W.; Hubmayr, J.; Irwin, K.; Jackson, M.; Jones, W. C.; Kallosh, R.; Kamionkowski, M.; Keating, B.; Keisler, R.; Kinney, W.; Knox, L.; Komatsu, E.; Kovac, J.; Kuo, C.-L.; Kusaka, A.; Lawrence, C.; Lee, A. T.; Leitch, E.; Linde, A.; Linder, E.; Lubin, P.; Maldacena, J.; Martinec, E.; McMahon, J.; Miller, A.; Mukhanov, V.; Newburgh, L.; Niemack, M. D.; Nguyen, H.; Nguyen, H. T.; Page, L.; Pryke, C.; Reichardt, C. L.; Ruhl, J. E.; Sehgal, N.; Seljak, U.; Senatore, L.; Sievers, J.; Silverstein, E.; Slosar, A.; Smith, K. M.; Spergel, D.; Staggs, S. T.; Stark, A.; Stompor, R.; Vieregg, A. G.; Wang, G.; Watson, S.; Wollack, E. J.; Wu, W. L. K.; Yoon, K. W.; Zahn, O.; Zaldarriaga, M.

2015-03-01

Fluctuations in the intensity and polarization of the cosmic microwave background (CMB) and the large-scale distribution of matter in the universe each contain clues about the nature of the earliest moments of time. The next generation of CMB and large-scale structure (LSS) experiments are poised to test the leading paradigm for these earliest moments-the theory of cosmic inflation-and to detect the imprints of the inflationary epoch, thereby dramatically increasing our understanding of fundamental physics and the early universe. A future CMB experiment with sufficient angular resolution and frequency coverage that surveys at least 1% of the sky to a depth of 1 uK-arcmin can deliver a constraint on the tensor-to-scalar ratio that will either result in a 5 σ measurement of the energy scale of inflation or rule out all large-field inflation models, even in the presence of foregrounds and the gravitational lensing B-mode signal. LSS experiments, particularly spectroscopic surveys such as the Dark Energy Spectroscopic Instrument, will complement the CMB effort by improving current constraints on running of the spectral index by up to a factor of four, improving constraints on curvature by a factor of ten, and providing non-Gaussianity constraints that are competitive with the current CMB bounds.

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Inflation Physics from the Cosmic Microwave Background and Large Scale Structure

NASA Technical Reports Server (NTRS)

Abazajian, K.N.; Arnold,K.; Austermann, J.; Benson, B.A.; Bischoff, C.; Bock, J.; Bond, J.R.; Borrill, J.; Buder, I.; Burke, D.L.;

A Proteome-wide Domain-centric Perspective on Protein Phosphorylation *

PubMed Central

Palmeri, Antonio; Ausiello, Gabriele; Ferrè, Fabrizio; Helmer-Citterich, Manuela; Gherardini, Pier Federico

2014-01-01

Phosphorylation is a widespread post-translational modification that modulates the function of a large number of proteins. Here we show that a significant proportion of all the domains in the human proteome is significantly enriched or depleted in phosphorylation events. A substantial improvement in phosphosites prediction is achieved by leveraging this observation, which has not been tapped by existing methods. Phosphorylation sites are often not shared between multiple occurrences of the same domain in the proteome, even when the phosphoacceptor residue is conserved. This is partly because of different functional constraints acting on the same domain in different protein contexts. Moreover, by augmenting domain alignments with structural information, we were able to provide direct evidence that phosphosites in protein-protein interfaces need not be positionally conserved, likely because they can modulate interactions simply by sitting in the same general surface area. PMID:24830415

Transition from large-scale to small-scale dynamo.

PubMed

Ponty, Y; Plunian, F

2011-04-15

The dynamo equations are solved numerically with a helical forcing corresponding to the Roberts flow. In the fully turbulent regime the flow behaves as a Roberts flow on long time scales, plus turbulent fluctuations at short time scales. The dynamo onset is controlled by the long time scales of the flow, in agreement with the former Karlsruhe experimental results. The dynamo mechanism is governed by a generalized α effect, which includes both the usual α effect and turbulent diffusion, plus all higher order effects. Beyond the onset we find that this generalized α effect scales as O(Rm(-1)), suggesting the takeover of small-scale dynamo action. This is confirmed by simulations in which dynamo occurs even if the large-scale field is artificially suppressed.

Role of Proteomics in the Development of Personalized Medicine.

PubMed

Jain, Kewal K

2016-01-01

Advances in proteomic technologies have made import contribution to the development of personalized medicine by facilitating detection of protein biomarkers, proteomics-based molecular diagnostics, as well as protein biochips and pharmacoproteomics. Application of nanobiotechnology in proteomics, nanoproteomics, has further enhanced applications in personalized medicine. Proteomics-based molecular diagnostics will have an important role in the diagnosis of certain conditions and understanding the pathomechanism of disease. Proteomics will be a good bridge between diagnostics and therapeutics; the integration of these will be important for advancing personalized medicine. Use of proteomic biomarkers and combination of pharmacoproteomics with pharmacogenomics will enable stratification of clinical trials and improve monitoring of patients for development of personalized therapies. Proteomics is an important component of several interacting technologies used for development of personalized medicine, which is depicted graphically. Finally, cancer is a good example of applications of proteomic technologies for personalized management of cancer. © 2016 Elsevier Inc. All rights reserved.

A unique large-scale undergraduate research experience in molecular systems biology for non-mathematics majors.

PubMed

Kappler, Ulrike; Rowland, Susan L; Pedwell, Rhianna K

2017-05-01

Systems biology is frequently taught with an emphasis on mathematical modeling approaches. This focus effectively excludes most biology, biochemistry, and molecular biology students, who are not mathematics majors. The mathematical focus can also present a misleading picture of systems biology, which is a multi-disciplinary pursuit requiring collaboration between biochemists, bioinformaticians, and mathematicians. This article describes an authentic large-scale undergraduate research experience (ALURE) in systems biology that incorporates proteomics, bacterial genomics, and bioinformatics in the one exercise. This project is designed to engage students who have a basic grounding in protein chemistry and metabolism and no mathematical modeling skills. The pedagogy around the research experience is designed to help students attack complex datasets and use their emergent metabolic knowledge to make meaning from large amounts of raw data. On completing the ALURE, participants reported a significant increase in their confidence around analyzing large datasets, while the majority of the cohort reported good or great gains in a variety of skills including "analysing data for patterns" and "conducting database or internet searches." An environmental scan shows that this ALURE is the only undergraduate-level system-biology research project offered on a large-scale in Australia; this speaks to the perceived difficulty of implementing such an opportunity for students. We argue however, that based on the student feedback, allowing undergraduate students to complete a systems-biology project is both feasible and desirable, even if the students are not maths and computing majors. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(3):235-248, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

Reflections on the Increasing Relevance of Large-Scale Professional Development

ERIC Educational Resources Information Center

Krainer, Konrad

2015-01-01

This paper focuses on commonalities and differences of three approaches to large-scale professional development (PD) in mathematics education, based on two studies from Germany and one from the United States of America. All three initiatives break new ground in improving PD targeted at educating "multipliers", and in all three cases…

The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes.

PubMed

O'Dwyer, David N; Norman, Katy C; Xia, Meng; Huang, Yong; Gurczynski, Stephen J; Ashley, Shanna L; White, Eric S; Flaherty, Kevin R; Martinez, Fernando J; Murray, Susan; Noth, Imre; Arnold, Kelly B; Moore, Bethany B

2017-04-25

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial pneumonia. The disease pathophysiology is poorly understood and the etiology remains unclear. Recent advances have generated new therapies and improved knowledge of the natural history of IPF. These gains have been brokered by advances in technology and improved insight into the role of various genes in mediating disease, but gene expression and protein levels do not always correlate. Thus, in this paper we apply a novel large scale high throughput aptamer approach to identify more than 1100 proteins in the peripheral blood of well-characterized IPF patients and normal volunteers. We use systems biology approaches to identify a unique IPF proteome signature and give insight into biological processes driving IPF. We found IPF plasma to be altered and enriched for proteins involved in defense response, wound healing and protein phosphorylation when compared to normal human plasma. Analysis also revealed a minimal protein signature that differentiated IPF patients from normal controls, which may allow for accurate diagnosis of IPF based on easily-accessible peripheral blood. This report introduces large scale unbiased protein discovery analysis to IPF and describes distinct biological processes that further inform disease biology.

Large-scale exact diagonalizations reveal low-momentum scales of nuclei

NASA Astrophysics Data System (ADS)

Forssén, C.; Carlsson, B. D.; Johansson, H. T.; Sääf, D.; Bansal, A.; Hagen, G.; Papenbrock, T.

2018-03-01

Ab initio methods aim to solve the nuclear many-body problem with controlled approximations. Virtually exact numerical solutions for realistic interactions can only be obtained for certain special cases such as few-nucleon systems. Here we extend the reach of exact diagonalization methods to handle model spaces with dimension exceeding 1010 on a single compute node. This allows us to perform no-core shell model (NCSM) calculations for 6Li in model spaces up to Nmax=22 and to reveal the 4He+d halo structure of this nucleus. Still, the use of a finite harmonic-oscillator basis implies truncations in both infrared (IR) and ultraviolet (UV) length scales. These truncations impose finite-size corrections on observables computed in this basis. We perform IR extrapolations of energies and radii computed in the NCSM and with the coupled-cluster method at several fixed UV cutoffs. It is shown that this strategy enables information gain also from data that is not fully UV converged. IR extrapolations improve the accuracy of relevant bound-state observables for a range of UV cutoffs, thus making them profitable tools. We relate the momentum scale that governs the exponential IR convergence to the threshold energy for the first open decay channel. Using large-scale NCSM calculations we numerically verify this small-momentum scale of finite nuclei.

Proteome | Office of Cancer Clinical Proteomics Research

Cancer.gov

A proteome is the entire complement of proteins, including modifications made to a particular set of proteins, produced by an organism or a cellular system. This will vary with time and distinct requirements such as growth conditions and stresses, and thus is highly dynamic and spatial. Proteomics is the study of the proteome.

Large-Scale Hybrid Motor Testing. Chapter 10

NASA Technical Reports Server (NTRS)

Story, George

2006-01-01

Hybrid rocket motors can be successfully demonstrated at a small scale virtually anywhere. There have been many suitcase sized portable test stands assembled for demonstration of hybrids. They show the safety of hybrid rockets to the audiences. These small show motors and small laboratory scale motors can give comparative burn rate data for development of different fuel/oxidizer combinations, however questions that are always asked when hybrids are mentioned for large scale applications are - how do they scale and has it been shown in a large motor? To answer those questions, large scale motor testing is required to verify the hybrid motor at its true size. The necessity to conduct large-scale hybrid rocket motor tests to validate the burn rate from the small motors to application size has been documented in several place^'^^.^. Comparison of small scale hybrid data to that of larger scale data indicates that the fuel burn rate goes down with increasing port size, even with the same oxidizer flux. This trend holds for conventional hybrid motors with forward oxidizer injection and HTPB based fuels. While the reason this is occurring would make a great paper or study or thesis, it is not thoroughly understood at this time. Potential causes include the fact that since hybrid combustion is boundary layer driven, the larger port sizes reduce the interaction (radiation, mixing and heat transfer) from the core region of the port. This chapter focuses on some of the large, prototype sized testing of hybrid motors. The largest motors tested have been AMROC s 250K-lbf thrust motor at Edwards Air Force Base and the Hybrid Propulsion Demonstration Program s 250K-lbf thrust motor at Stennis Space Center. Numerous smaller tests were performed to support the burn rate, stability and scaling concepts that went into the development of those large motors.

Why small-scale cannabis growers stay small: five mechanisms that prevent small-scale growers from going large scale.

PubMed

Hammersvik, Eirik; Sandberg, Sveinung; Pedersen, Willy

2012-11-01

Over the past 15-20 years, domestic cultivation of cannabis has been established in a number of European countries. New techniques have made such cultivation easier; however, the bulk of growers remain small-scale. In this study, we explore the factors that prevent small-scale growers from increasing their production. The study is based on 1 year of ethnographic fieldwork and qualitative interviews conducted with 45 Norwegian cannabis growers, 10 of whom were growing on a large-scale and 35 on a small-scale. The study identifies five mechanisms that prevent small-scale indoor growers from going large-scale. First, large-scale operations involve a number of people, large sums of money, a high work-load and a high risk of detection, and thus demand a higher level of organizational skills than for small growing operations. Second, financial assets are needed to start a large 'grow-site'. Housing rent, electricity, equipment and nutrients are expensive. Third, to be able to sell large quantities of cannabis, growers need access to an illegal distribution network and knowledge of how to act according to black market norms and structures. Fourth, large-scale operations require advanced horticultural skills to maximize yield and quality, which demands greater skills and knowledge than does small-scale cultivation. Fifth, small-scale growers are often embedded in the 'cannabis culture', which emphasizes anti-commercialism, anti-violence and ecological and community values. Hence, starting up large-scale production will imply having to renegotiate or abandon these values. Going from small- to large-scale cannabis production is a demanding task-ideologically, technically, economically and personally. The many obstacles that small-scale growers face and the lack of interest and motivation for going large-scale suggest that the risk of a 'slippery slope' from small-scale to large-scale growing is limited. Possible political implications of the findings are discussed. Copyright

Neural Stem Cells (NSCs) and Proteomics*

PubMed Central

Shoemaker, Lorelei D.; Kornblum, Harley I.

2016-01-01

Neural stem cells (NSCs) can self-renew and give rise to the major cell types of the CNS. Studies of NSCs include the investigation of primary, CNS-derived cells as well as animal and human embryonic stem cell (ESC)-derived and induced pluripotent stem cell (iPSC)-derived sources. NSCs provide a means with which to study normal neural development, neurodegeneration, and neurological disease and are clinically relevant sources for cellular repair to the damaged and diseased CNS. Proteomics studies of NSCs have the potential to delineate molecules and pathways critical for NSC biology and the means by which NSCs can participate in neural repair. In this review, we provide a background to NSC biology, including the means to obtain them and the caveats to these processes. We then focus on advances in the proteomic interrogation of NSCs. This includes the analysis of posttranslational modifications (PTMs); approaches to analyzing different proteomic compartments, such the secretome; as well as approaches to analyzing temporal differences in the proteome to elucidate mechanisms of differentiation. We also discuss some of the methods that will undoubtedly be useful in the investigation of NSCs but which have not yet been applied to the field. While many proteomics studies of NSCs have largely catalogued the proteome or posttranslational modifications of specific cellular states, without delving into specific functions, some have led to understandings of functional processes or identified markers that could not have been identified via other means. Many challenges remain in the field, including the precise identification and standardization of NSCs used for proteomic analyses, as well as how to translate fundamental proteomics studies to functional biology. The next level of investigation will require interdisciplinary approaches, combining the skills of those interested in the biochemistry of proteomics with those interested in modulating NSC function. PMID:26494823

Neural Stem Cells (NSCs) and Proteomics.

PubMed

Shoemaker, Lorelei D; Kornblum, Harley I

2016-02-01

Neural stem cells (NSCs) can self-renew and give rise to the major cell types of the CNS. Studies of NSCs include the investigation of primary, CNS-derived cells as well as animal and human embryonic stem cell (ESC)-derived and induced pluripotent stem cell (iPSC)-derived sources. NSCs provide a means with which to study normal neural development, neurodegeneration, and neurological disease and are clinically relevant sources for cellular repair to the damaged and diseased CNS. Proteomics studies of NSCs have the potential to delineate molecules and pathways critical for NSC biology and the means by which NSCs can participate in neural repair. In this review, we provide a background to NSC biology, including the means to obtain them and the caveats to these processes. We then focus on advances in the proteomic interrogation of NSCs. This includes the analysis of posttranslational modifications (PTMs); approaches to analyzing different proteomic compartments, such the secretome; as well as approaches to analyzing temporal differences in the proteome to elucidate mechanisms of differentiation. We also discuss some of the methods that will undoubtedly be useful in the investigation of NSCs but which have not yet been applied to the field. While many proteomics studies of NSCs have largely catalogued the proteome or posttranslational modifications of specific cellular states, without delving into specific functions, some have led to understandings of functional processes or identified markers that could not have been identified via other means. Many challenges remain in the field, including the precise identification and standardization of NSCs used for proteomic analyses, as well as how to translate fundamental proteomics studies to functional biology. The next level of investigation will require interdisciplinary approaches, combining the skills of those interested in the biochemistry of proteomics with those interested in modulating NSC function. © 2016 by The

Proteome-wide analysis and diel proteomic profiling of the cyanobacterium Arthrospira platensis PCC 8005.

PubMed

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation.

Generation of Large-Scale Magnetic Fields by Small-Scale Dynamo in Shear Flows.

PubMed

Squire, J; Bhattacharjee, A

2015-10-23

We propose a new mechanism for a turbulent mean-field dynamo in which the magnetic fluctuations resulting from a small-scale dynamo drive the generation of large-scale magnetic fields. This is in stark contrast to the common idea that small-scale magnetic fields should be harmful to large-scale dynamo action. These dynamos occur in the presence of a large-scale velocity shear and do not require net helicity, resulting from off-diagonal components of the turbulent resistivity tensor as the magnetic analogue of the "shear-current" effect. Given the inevitable existence of nonhelical small-scale magnetic fields in turbulent plasmas, as well as the generic nature of velocity shear, the suggested mechanism may help explain the generation of large-scale magnetic fields across a wide range of astrophysical objects.

[Drug Repositioning Research Utilizing a Large-scale Medical Claims Database to Improve Survival Rates after Cardiopulmonary Arrest].

PubMed

Zamami, Yoshito; Niimura, Takahiro; Takechi, Kenshi; Imanishi, Masaki; Koyama, Toshihiro; Ishizawa, Keisuke

2017-01-01

 Approximately 100000 people suffer cardiopulmonary arrest in Japan every year, and the aging of society means that this number is expected to increase. Worldwide, approximately 100 million develop cardiac arrest annually, making it an international issue. Although survival has improved thanks to advances in cardiopulmonary resuscitation, there is a high rate of postresuscitation encephalopathy after the return of spontaneous circulation, and the proportion of patients who can return to normal life is extremely low. Treatment for postresuscitation encephalopathy is long term, and if sequelae persist then nursing care is required, causing immeasurable economic burdens as a result of ballooning medical costs. As at present there is no drug treatment to improve postresuscitation encephalopathy as a complication of cardiopulmonary arrest, the development of novel drug treatments is desirable. In recent years, new efficacy for existing drugs used in the clinical setting has been discovered, and drug repositioning has been proposed as a strategy for developing those drugs as therapeutic agents for different diseases. This review describes a large-scale database study carried out following a discovery strategy for drug repositioning with the objective of improving survival rates after cardiopulmonary arrest and discusses future repositioning prospects.

Shaping biological knowledge: applications in proteomics.

PubMed

Lisacek, F; Chichester, C; Gonnet, P; Jaillet, O; Kappus, S; Nikitin, F; Roland, P; Rossier, G; Truong, L; Appel, R

2004-01-01

The central dogma of molecular biology has provided a meaningful principle for data integration in the field of genomics. In this context, integration reflects the known transitions from a chromosome to a protein sequence: transcription, intron splicing, exon assembly and translation. There is no such clear principle for integrating proteomics data, since the laws governing protein folding and interactivity are not quite understood. In our effort to bring together independent pieces of information relative to proteins in a biologically meaningful way, we assess the bias of bioinformatics resources and consequent approximations in the framework of small-scale studies. We analyse proteomics data while following both a data-driven (focus on proteins smaller than 10 kDa) and a hypothesis-driven (focus on whole bacterial proteomes) approach. These applications are potentially the source of specialized complements to classical biological ontologies.

MaxReport: An Enhanced Proteomic Result Reporting Tool for MaxQuant.

PubMed

Zhou, Tao; Li, Chuyu; Zhao, Wene; Wang, Xinru; Wang, Fuqiang; Sha, Jiahao

2016-01-01

MaxQuant is a proteomic software widely used for large-scale tandem mass spectrometry data. We have designed and developed an enhanced result reporting tool for MaxQuant, named as MaxReport. This tool can optimize the results of MaxQuant and provide additional functions for result interpretation. MaxReport can generate report tables for protein N-terminal modifications. It also supports isobaric labelling based relative quantification at the protein, peptide or site level. To obtain an overview of the results, MaxReport performs general descriptive statistical analyses for both identification and quantification results. The output results of MaxReport are well organized and therefore helpful for proteomic users to better understand and share their data. The script of MaxReport, which is freely available at http://websdoor.net/bioinfo/maxreport/, is developed using Python code and is compatible across multiple systems including Windows and Linux.

Large scale rigidity-based flexibility analysis of biomolecules

PubMed Central

Streinu, Ileana

2016-01-01

KINematics And RIgidity (KINARI) is an on-going project for in silico flexibility analysis of proteins. The new version of the software, Kinari-2, extends the functionality of our free web server KinariWeb, incorporates advanced web technologies, emphasizes the reproducibility of its experiments, and makes substantially improved tools available to the user. It is designed specifically for large scale experiments, in particular, for (a) very large molecules, including bioassemblies with high degree of symmetry such as viruses and crystals, (b) large collections of related biomolecules, such as those obtained through simulated dilutions, mutations, or conformational changes from various types of dynamics simulations, and (c) is intended to work as seemlessly as possible on the large, idiosyncratic, publicly available repository of biomolecules, the Protein Data Bank. We describe the system design, along with the main data processing, computational, mathematical, and validation challenges underlying this phase of the KINARI project. PMID:26958583

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

PubMed

Wimmer, Helge; Gundacker, Nina C; Griss, Johannes; Haudek, Verena J; Stättner, Stefan; Mohr, Thomas; Zwickl, Hannes; Paulitschke, Verena; Baron, David M; Trittner, Wolfgang; Kubicek, Markus; Bayer, Editha; Slany, Astrid; Gerner, Christopher

2009-06-01

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Scale-Similar Models for Large-Eddy Simulations

NASA Technical Reports Server (NTRS)

Sarghini, F.

1999-01-01

Scale-similar models employ multiple filtering operations to identify the smallest resolved scales, which have been shown to be the most active in the interaction with the unresolved subgrid scales. They do not assume that the principal axes of the strain-rate tensor are aligned with those of the subgrid-scale stress (SGS) tensor, and allow the explicit calculation of the SGS energy. They can provide backscatter in a numerically stable and physically realistic manner, and predict SGS stresses in regions that are well correlated with the locations where large Reynolds stress occurs. In this paper, eddy viscosity and mixed models, which include an eddy-viscosity part as well as a scale-similar contribution, are applied to the simulation of two flows, a high Reynolds number plane channel flow, and a three-dimensional, nonequilibrium flow. The results show that simulations without models or with the Smagorinsky model are unable to predict nonequilibrium effects. Dynamic models provide an improvement of the results: the adjustment of the coefficient results in more accurate prediction of the perturbation from equilibrium. The Lagrangian-ensemble approach [Meneveau et al., J. Fluid Mech. 319, 353 (1996)] is found to be very beneficial. Models that included a scale-similar term and a dissipative one, as well as the Lagrangian ensemble averaging, gave results in the best agreement with the direct simulation and experimental data.

An exploratory, large-scale study of pain and quality of life outcomes in cancer patients with moderate or severe pain, and variables predicting improvement.

PubMed

Maximiano, Constanza; López, Iker; Martín, Cristina; Zugazabeitia, Luis; Martí-Ciriquián, Juan L; Núñez, Miguel A; Contreras, Jorge; Herdman, Michael; Traseira, Susana; Provencio, Mariano

2018-01-01

There have been few large-scale, real world studies in Spain to assess change in pain and quality of life (QOL) outcomes in cancer patients with moderate to severe pain. This study aimed to assess changes on both outcomes after 3 months of usual care and to investigate factors associated with change in QoL. Large, multi-centre, observational study in patients with lung, head and neck, colorectal or breast cancer experiencing a first episode of moderate to severe pain while attending one of the participating centres. QoL was assessed using the EuroQol-5D questionnaire and pain using the Brief Pain Inventory (BPI). Instruments were administered at baseline and after 3 months of follow up. Multivariate analyses were used to assess the impact of treatment factors, demographic and clinical variables, pain and other symptoms on QoL scores. 1711 patients were included for analysis. After 3 months of usual care, a significant improvement was observed in pain and QoL in all four cancer groups (p<0.001). Effect sizes were medium to large on the BPI and EQ-5D Index and Visual Analogue Scale (VAS). Improvements were seen on the majority of EQ-5D dimensions in all patient groups, though breast cancer patients showed the largest gains. Poorer baseline performance status (ECOG) and the presence of anxiety/depression were associated with significantly poorer QOL outcomes. Improvements in BPI pain scores were associated with improved QoL. In the four cancer types studied, pain and QoL outcomes improved considerably after 3 months of usual care. Improvements in pain made a substantial contribution to QoL gains whilst the presence of anxiety and depression and poor baseline performance status significantly constrained improvement.

Advances in crop proteomics: PTMs of proteins under abiotic stress.

PubMed

Wu, Xiaolin; Gong, Fangping; Cao, Di; Hu, Xiuli; Wang, Wei

2016-03-01

Under natural conditions, crop plants are frequently subjected to various abiotic environmental stresses such as drought and heat wave, which may become more prevalent in the coming decades. Plant acclimation and tolerance to an abiotic stress are always associated with significant changes in PTMs of specific proteins. PTMs are important for regulating protein function, subcellular localization and protein activity and stability. Studies of plant responses to abiotic stress at the PTMs level are essential to the process of plant phenotyping for crop improvement. The ability to identify and quantify PTMs on a large-scale will contribute to a detailed protein functional characterization that will improve our understanding of the processes of crop plant stress acclimation and stress tolerance acquisition. Hundreds of PTMs have been reported, but it is impossible to review all of the possible protein modifications. In this review, we briefly summarize several main types of PTMs regarding their characteristics and detection methods, review the advances in PTMs research of crop proteomics, and highlight the importance of specific PTMs in crop response to abiotic stress. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large Scale Traffic Simulations

DOT National Transportation Integrated Search

1997-01-01

Large scale microscopic (i.e. vehicle-based) traffic simulations pose high demands on computation speed in at least two application areas: (i) real-time traffic forecasting, and (ii) long-term planning applications (where repeated "looping" between t...

Proteomic Approaches to Quantify Cysteine Reversible Modifications in Aging and Neurodegenerative Diseases

PubMed Central

Gu, Liqing; Robinson, Renã A. S.

2016-01-01

Cysteine is a highly reactive amino acid and is subject to a variety of reversible post-translational modifications (PTMs), including nitrosylation, glutathionylation, palmitoylation, as well as formation of sulfenic acid and disulfides. These modifications are not only involved in normal biological activities, such as enzymatic catalysis, redox signaling and cellular homeostasis, but can also be the result of oxidative damage. Especially in aging and neurodegenerative diseases, oxidative stress leads to aberrant cysteine oxidations that affect protein structure and function leading to neurodegeneration as well as other detrimental effects. Methods that can identify cysteine modifications by type, including the site of modification, as well as the relative stoichiometry of the modification can be very helpful for understanding the role of the thiol proteome and redox homeostasis in the context of disease. Cysteine reversible modifications however, are challenging to investigate as they are low abundant, diverse, and labile especially under endogenous conditions. Thanks to the development of redox proteomic approaches, large-scale quantification of cysteine reversible modifications is possible. These approaches cover a range of strategies to enrich, identify, and quantify cysteine reversible modifications from biological samples. This review will focus on nongel-based redox proteomics workflows that give quantitative information about cysteine PTMs and highlight how these strategies have been useful for investigating the redox thiol proteome in aging and neurodegenerative diseases. PMID:27666938

Large-scale bioenergy production: how to resolve sustainability trade-offs?

NASA Astrophysics Data System (ADS)

Humpenöder, Florian; Popp, Alexander; Bodirsky, Benjamin Leon; Weindl, Isabelle; Biewald, Anne; Lotze-Campen, Hermann; Dietrich, Jan Philipp; Klein, David; Kreidenweis, Ulrich; Müller, Christoph; Rolinski, Susanne; Stevanovic, Miodrag

2018-02-01

Large-scale 2nd generation bioenergy deployment is a key element of 1.5 °C and 2 °C transformation pathways. However, large-scale bioenergy production might have negative sustainability implications and thus may conflict with the Sustainable Development Goal (SDG) agenda. Here, we carry out a multi-criteria sustainability assessment of large-scale bioenergy crop production throughout the 21st century (300 EJ in 2100) using a global land-use model. Our analysis indicates that large-scale bioenergy production without complementary measures results in negative effects on the following sustainability indicators: deforestation, CO2 emissions from land-use change, nitrogen losses, unsustainable water withdrawals and food prices. One of our main findings is that single-sector environmental protection measures next to large-scale bioenergy production are prone to involve trade-offs among these sustainability indicators—at least in the absence of more efficient land or water resource use. For instance, if bioenergy production is accompanied by forest protection, deforestation and associated emissions (SDGs 13 and 15) decline substantially whereas food prices (SDG 2) increase. However, our study also shows that this trade-off strongly depends on the development of future food demand. In contrast to environmental protection measures, we find that agricultural intensification lowers some side-effects of bioenergy production substantially (SDGs 13 and 15) without generating new trade-offs—at least among the sustainability indicators considered here. Moreover, our results indicate that a combination of forest and water protection schemes, improved fertilization efficiency, and agricultural intensification would reduce the side-effects of bioenergy production most comprehensively. However, although our study includes more sustainability indicators than previous studies on bioenergy side-effects, our study represents only a small subset of all indicators relevant for the

Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation

PubMed Central

Chen, Ke; Gao, Ye; Mih, Nathan; O’Brien, Edward J.; Yang, Laurence; Palsson, Bernhard O.

2017-01-01

Maintenance of a properly folded proteome is critical for bacterial survival at notably different growth temperatures. Understanding the molecular basis of thermoadaptation has progressed in two main directions, the sequence and structural basis of protein thermostability and the mechanistic principles of protein quality control assisted by chaperones. Yet we do not fully understand how structural integrity of the entire proteome is maintained under stress and how it affects cellular fitness. To address this challenge, we reconstruct a genome-scale protein-folding network for Escherichia coli and formulate a computational model, FoldME, that provides statistical descriptions of multiscale cellular response consistent with many datasets. FoldME simulations show (i) that the chaperones act as a system when they respond to unfolding stress rather than achieving efficient folding of any single component of the proteome, (ii) how the proteome is globally balanced between chaperones for folding and the complex machinery synthesizing the proteins in response to perturbation, (iii) how this balancing determines growth rate dependence on temperature and is achieved through nonspecific regulation, and (iv) how thermal instability of the individual protein affects the overall functional state of the proteome. Overall, these results expand our view of cellular regulation, from targeted specific control mechanisms to global regulation through a web of nonspecific competing interactions that modulate the optimal reallocation of cellular resources. The methodology developed in this study enables genome-scale integration of environment-dependent protein properties and a proteome-wide study of cellular stress responses. PMID:29073085

Generation of large-scale magnetic fields by small-scale dynamo in shear flows

DOE PAGES

Squire, J.; Bhattacharjee, A.

2015-10-20

We propose a new mechanism for a turbulent mean-field dynamo in which the magnetic fluctuations resulting from a small-scale dynamo drive the generation of large-scale magnetic fields. This is in stark contrast to the common idea that small-scale magnetic fields should be harmful to large-scale dynamo action. These dynamos occur in the presence of a large-scale velocity shear and do not require net helicity, resulting from off-diagonal components of the turbulent resistivity tensor as the magnetic analogue of the "shear-current" effect. Furthermore, given the inevitable existence of nonhelical small-scale magnetic fields in turbulent plasmas, as well as the generic naturemore » of velocity shear, the suggested mechanism may help explain the generation of large-scale magnetic fields across a wide range of astrophysical objects.« less

Large-scale hydrological modeling for calculating water stress indices: implications of improved spatiotemporal resolution, surface-groundwater differentiation, and uncertainty characterization.

PubMed

Scherer, Laura; Venkatesh, Aranya; Karuppiah, Ramkumar; Pfister, Stephan

2015-04-21

Physical water scarcities can be described by water stress indices. These are often determined at an annual scale and a watershed level; however, such scales mask seasonal fluctuations and spatial heterogeneity within a watershed. In order to account for this level of detail, first and foremost, water availability estimates must be improved and refined. State-of-the-art global hydrological models such as WaterGAP and UNH/GRDC have previously been unable to reliably reflect water availability at the subbasin scale. In this study, the Soil and Water Assessment Tool (SWAT) was tested as an alternative to global models, using the case study of the Mississippi watershed. While SWAT clearly outperformed the global models at the scale of a large watershed, it was judged to be unsuitable for global scale simulations due to the high calibration efforts required. The results obtained in this study show that global assessments miss out on key aspects related to upstream/downstream relations and monthly fluctuations, which are important both for the characterization of water scarcity in the Mississippi watershed and for water footprints. Especially in arid regions, where scarcity is high, these models provide unsatisfying results.

Proteomics of the Human Placenta: Promises and Realities

PubMed Central

Robinson, J.M.; Ackerman, W.E.; Kniss, D.A.; Takizawa, T.; Vandré, D.D.

2015-01-01

Proteomics is an area of study that sets as its ultimate goal the global analysis of all of the proteins expressed in a biological system of interest. However, technical limitations currently hamper proteome-wide analyses of complex systems. In a more practical sense, a desired outcome of proteomics research is the translation of large protein data sets into formats that provide meaningful information regarding clinical conditions (e.g., biomarkers to serve as diagnostic and/or prognostic indicators of disease). Herein, we discuss placental proteomics by describing existing studies, pointing out their strengths and weaknesses. In so doing, we strive to inform investigators interested in this area of research about the current gap between hyperbolic promises and realities. Additionally, we discuss the utility of proteomics in discovery-based research, particularly as regards the capacity to unearth novel insights into placental biology. Importantly, when considering under studied systems such as the human placenta and diseases associated with abnormalities in placental function, proteomics can serve as a robust ‘shortcut’ to obtaining information unlikely to be garnered using traditional approaches. PMID:18222537

Dentistry proteomics: from laboratory development to clinical practice.

PubMed

Rezende, Taia M B; Lima, Stella M F; Petriz, Bernardo A; Silva, Osmar N; Freire, Mirna S; Franco, Octávio L

2013-12-01

Despite all the dental information acquired over centuries and the importance of proteome research, the cross-link between these two areas only emerged around mid-nineties. Proteomic tools can help dentistry in the identification of risk factors, early diagnosis, prevention, and systematic control that will promote the evolution of treatment in all dentistry specialties. This review mainly focuses on the evolution of dentistry in different specialties based on proteomic research and how these tools can improve knowledge in dentistry. The subjects covered are an overview of proteomics in dentistry, specific information on different fields in dentistry (dental structure, restorative dentistry, endodontics, periodontics, oral pathology, oral surgery, and orthodontics) and future directions. There are many new proteomic technologies that have never been used in dentistry studies and some dentistry areas that have never been explored by proteomic tools. It is expected that a greater integration of these areas will help to understand what is still unknown in oral health and disease. Copyright © 2013 Wiley Periodicals, Inc.

Very Large Scale Integration (VLSI).

ERIC Educational Resources Information Center

Yeaman, Andrew R. J.

Very Large Scale Integration (VLSI), the state-of-the-art production techniques for computer chips, promises such powerful, inexpensive computing that, in the future, people will be able to communicate with computer devices in natural language or even speech. However, before full-scale VLSI implementation can occur, certain salient factors must be…

Opportunities for Breakthroughs in Large-Scale Computational Simulation and Design

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Alter, Stephen J.; Atkins, Harold L.; Bey, Kim S.; Bibb, Karen L.; Biedron, Robert T.; Carpenter, Mark H.; Cheatwood, F. McNeil; Drummond, Philip J.; Gnoffo, Peter A.

2002-01-01

Opportunities for breakthroughs in the large-scale computational simulation and design of aerospace vehicles are presented. Computational fluid dynamics tools to be used within multidisciplinary analysis and design methods are emphasized. The opportunities stem from speedups and robustness improvements in the underlying unit operations associated with simulation (geometry modeling, grid generation, physical modeling, analysis, etc.). Further, an improved programming environment can synergistically integrate these unit operations to leverage the gains. The speedups result from reducing the problem setup time through geometry modeling and grid generation operations, and reducing the solution time through the operation counts associated with solving the discretized equations to a sufficient accuracy. The opportunities are addressed only at a general level here, but an extensive list of references containing further details is included. The opportunities discussed are being addressed through the Fast Adaptive Aerospace Tools (FAAST) element of the Advanced Systems Concept to Test (ASCoT) and the third Generation Reusable Launch Vehicles (RLV) projects at NASA Langley Research Center. The overall goal is to enable greater inroads into the design process with large-scale simulations.

Elucidation of salt stress defense and tolerance mechanisms of crop plants using proteomics--current achievements and perspectives.

PubMed

Barkla, Bronwyn J; Castellanos-Cervantes, Thelma; de León, José L Diaz; Matros, Andrea; Mock, Hans-Peter; Perez-Alfocea, Francisco; Salekdeh, Ghasem H; Witzel, Katja; Zörb, Christian

2013-06-01

Salinity is a major threat limiting the productivity of crop plants. A clear demand for improving the salinity tolerance of the major crop plants is imposed by the rapidly growing world population. This review summarizes the achievements of proteomic studies to elucidate the response mechanisms of selected model and crop plants to cope with salinity stress. We also aim at identifying research areas, which deserve increased attention in future proteome studies, as a prerequisite to identify novel targets for breeding strategies. Such areas include the impact of plant-microbial communities on the salinity tolerance of crops under field conditions, the importance of hormone signaling in abiotic stress tolerance, and the significance of control mechanisms underlying the observed changes in the proteome patterns. We briefly highlight the impact of novel tools for future proteome studies and argue for the use of integrated approaches. The evaluation of genetic resources by means of novel automated phenotyping facilities will have a large impact on the application of proteomics especially in combination with metabolomics or transcriptomics. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Leading Educational Change and Improvement at Scale: Some Inconvenient Truths about System Performance

ERIC Educational Resources Information Center

Harris, Alma; Jones, Michelle

2017-01-01

The challenges of securing educational change and transformation, at scale, remain considerable. While sustained progress has been made in some education systems (Fullan, 2009; Hargreaves & Shirley, 2009) generally, it remains the case that the pathway to large-scale, system improvement is far from easy or straightforward. While large-scale…

Rescuing discarded spectra: Full comprehensive analysis of a minimal proteome.

PubMed

Lluch-Senar, Maria; Mancuso, Francesco M; Climente-González, Héctor; Peña-Paz, Marcia I; Sabido, Eduard; Serrano, Luis

2016-02-01

A common problem encountered when performing large-scale MS proteome analysis is the loss of information due to the high percentage of unassigned spectra. To determine the causes behind this loss we have analyzed the proteome of one of the smallest living bacteria that can be grown axenically, Mycoplasma pneumoniae (729 ORFs). The proteome of M. pneumoniae cells, grown in defined media, was analyzed by MS. An initial search with both Mascot and a species-specific NCBInr database with common contaminants (NCBImpn), resulted in around 79% of the acquired spectra not having an assignment. The percentage of non-assigned spectra was reduced to 27% after re-analysis of the data with the PEAKS software, thereby increasing the proteome coverage of M. pneumoniae from the initial 60% to over 76%. Nonetheless, 33,413 spectra with assigned amino acid sequences could not be mapped to any NCBInr database protein sequence. Approximately, 1% of these unassigned peptides corresponded to PTMs and 4% to M. pneumoniae protein variants (deamidation and translation inaccuracies). The most abundant peptide sequence variants (Phe-Tyr and Ala-Ser) could be explained by alterations in the editing capacity of the corresponding tRNA synthases. About another 1% of the peptides not associated to any protein had repetitions of the same aromatic/hydrophobic amino acid at the N-terminus, or had Arg/Lys at the C-terminus. Thus, in a model system, we have maximized the number of assigned spectra to 73% (51,453 out of the 70,040 initial acquired spectra). All MS data have been deposited in the ProteomeXchange with identifier PXD002779 (http://proteomecentral.proteomexchange.org/dataset/PXD002779). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

First Large-Scale Proteogenomic Study of Breast Cancer Provides Insight into Potential Therapeutic Targets | Office of Cancer Clinical Proteomics Research

Cancer.gov

News Release: May 25, 2016 — Building on data from The Cancer Genome Atlas (TCGA) project, a multi-institutional team of scientists has completed the first large-scale “proteogenomic” study of breast cancer, linking DNA mutations to protein signaling and helping pinpoint the genes that drive cancer.

Inflation physics from the cosmic microwave background and large scale structure

DOE PAGES

Abazajian, K. N.; Arnold, K.; Austermann, J.; ...

2014-06-26

Here, fluctuations in the intensity and polarization of the cosmic microwave background (CMB) and the large-scale distribution of matter in the universe each contain clues about the nature of the earliest moments of time. The next generation of CMB and large-scale structure (LSS) experiments are poised to test the leading paradigm for these earliest moments—the theory of cosmic inflation—and to detect the imprints of the inflationary epoch, thereby dramatically increasing our understanding of fundamental physics and the early universe. A future CMB experiment with sufficient angular resolution and frequency coverage that surveys at least 1% of the sky to amore » depth of 1 uK-arcmin can deliver a constraint on the tensor-to-scalar ratio that will either result in a 5σ measurement of the energy scale of inflation or rule out all large-field inflation models, even in the presence of foregrounds and the gravitational lensing B -mode signal. LSS experiments, particularly spectroscopic surveys such as the Dark Energy Spectroscopic Instrument, will complement the CMB effort by improving current constraints on running of the spectral index by up to a factor of four, improving constraints on curvature by a factor of ten, and providing non-Gaussianity constraints that are competitive with the current CMB bounds.« less

Top-Down Characterization of the Post-Translationally Modified Intact Periplasmic Proteome from the Bacterium Novosphingobium aromaticivorans

DOE PAGES

Wu, Si; Brown, Roslyn N.; Payne, Samuel H.; ...

2013-01-01

The periplasm of Gram-negative bacteria is a dynamic and physiologically important subcellular compartment where the constant exposure to potential environmental insults amplifies the need for proper protein folding and modifications. Top-down proteomics analysis of the periplasmic fraction at the intact protein level provides unrestricted characterization and annotation of the periplasmic proteome, including the post-translational modifications (PTMs) on these proteins. Here, we used single-dimension ultra-high pressure liquid chromatography coupled with the Fourier transform mass spectrometry (FTMS) to investigate the intact periplasmic proteome of Novosphingobium aromaticivorans . Our top-down analysis provided the confident identification of 55 proteins in the periplasm and characterizedmore » their PTMs including signal peptide removal, N-terminal methionine excision, acetylation, glutathionylation, pyroglutamate, and disulfide bond formation. This study provides the first experimental evidence for the expression and periplasmic localization of many hypothetical and uncharacterized proteins and the first unrestrictive, large-scale data on PTMs in the bacterial periplasm.« less

Survey on large scale system control methods

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1987-01-01

The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

Algorithm of OMA for large-scale orthology inference

PubMed Central

Roth, Alexander CJ; Gonnet, Gaston H; Dessimoz, Christophe

2008-01-01

Background OMA is a project that aims to identify orthologs within publicly available, complete genomes. With 657 genomes analyzed to date, OMA is one of the largest projects of its kind. Results The algorithm of OMA improves upon standard bidirectional best-hit approach in several respects: it uses evolutionary distances instead of scores, considers distance inference uncertainty, includes many-to-many orthologous relations, and accounts for differential gene losses. Herein, we describe in detail the algorithm for inference of orthology and provide the rationale for parameter selection through multiple tests. Conclusion OMA contains several novel improvement ideas for orthology inference and provides a unique dataset of large-scale orthology assignments. PMID:19055798

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

NASA Astrophysics Data System (ADS)

Bowden, Jared H.; Nolte, Christopher G.; Otte, Tanya L.

2013-04-01

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscaling of global climate model (GCM) output for air quality applications under a changing climate. In this study we downscale the NCEP-Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis using three continuous 20-year WRF simulations: one simulation without interior grid nudging and two using different interior grid nudging methods. The biases in 2-m temperature and precipitation for the simulation without interior grid nudging are unreasonably large with respect to the North American Regional Reanalysis (NARR) over the eastern half of the contiguous United States (CONUS) during the summer when air quality concerns are most relevant. This study examines how these differences arise from errors in predicting the large-scale atmospheric circulation. It is demonstrated that the Bermuda high, which strongly influences the regional climate for much of the eastern half of the CONUS during the summer, is poorly simulated without interior grid nudging. In particular, two summers when the Bermuda high was west (1993) and east (2003) of its climatological position are chosen to illustrate problems in the large-scale atmospheric circulation anomalies. For both summers, WRF without interior grid nudging fails to simulate the placement of the upper-level anticyclonic (1993) and cyclonic (2003) circulation anomalies. The displacement of the large-scale circulation impacts the lower atmosphere moisture transport and precipitable water, affecting the convective environment and precipitation. Using interior grid nudging improves the large-scale circulation aloft and moisture transport/precipitable water anomalies, thereby improving the simulated 2-m temperature and precipitation

Measurement repeatability of a large-scale inventory of forest fuels

Treesearch

J.A. Westfall; C.W. Woodall

2007-01-01

An efficient and accurate inventory of forest fuels at large scales is critical for assessment of forest fire hazards across landscapes. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a national inventory of fuels along with blind remeasurement of a portion of inventory plots to monitor and improve data quality. The goal of this...

Large-Scale 3D Printing: The Way Forward

NASA Astrophysics Data System (ADS)

Jassmi, Hamad Al; Najjar, Fady Al; Ismail Mourad, Abdel-Hamid

2018-03-01

Research on small-scale 3D printing has rapidly evolved, where numerous industrial products have been tested and successfully applied. Nonetheless, research on large-scale 3D printing, directed to large-scale applications such as construction and automotive manufacturing, yet demands a great a great deal of efforts. Large-scale 3D printing is considered an interdisciplinary topic and requires establishing a blended knowledge base from numerous research fields including structural engineering, materials science, mechatronics, software engineering, artificial intelligence and architectural engineering. This review article summarizes key topics of relevance to new research trends on large-scale 3D printing, particularly pertaining (1) technological solutions of additive construction (i.e. the 3D printers themselves), (2) materials science challenges, and (3) new design opportunities.

Novel method to construct large-scale design space in lubrication process utilizing Bayesian estimation based on a small-scale design-of-experiment and small sets of large-scale manufacturing data.

PubMed

Maeda, Jin; Suzuki, Tatsuya; Takayama, Kozo

2012-12-01

A large-scale design space was constructed using a Bayesian estimation method with a small-scale design of experiments (DoE) and small sets of large-scale manufacturing data without enforcing a large-scale DoE. The small-scale DoE was conducted using various Froude numbers (X(1)) and blending times (X(2)) in the lubricant blending process for theophylline tablets. The response surfaces, design space, and their reliability of the compression rate of the powder mixture (Y(1)), tablet hardness (Y(2)), and dissolution rate (Y(3)) on a small scale were calculated using multivariate spline interpolation, a bootstrap resampling technique, and self-organizing map clustering. The constant Froude number was applied as a scale-up rule. Three experiments under an optimal condition and two experiments under other conditions were performed on a large scale. The response surfaces on the small scale were corrected to those on a large scale by Bayesian estimation using the large-scale results. Large-scale experiments under three additional sets of conditions showed that the corrected design space was more reliable than that on the small scale, even if there was some discrepancy in the pharmaceutical quality between the manufacturing scales. This approach is useful for setting up a design space in pharmaceutical development when a DoE cannot be performed at a commercial large manufacturing scale.

Study of multi-functional precision optical measuring system for large scale equipment

NASA Astrophysics Data System (ADS)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

Using Proteomics to Understand How Leishmania Parasites Survive inside the Host and Establish Infection

PubMed Central

Veras, Patrícia Sampaio Tavares; Bezerra de Menezes, Juliana Perrone

2016-01-01

Leishmania is a protozoan parasite that causes a wide range of different clinical manifestations in mammalian hosts. It is a major public health risk on different continents and represents one of the most important neglected diseases. Due to the high toxicity of the drugs currently used, and in the light of increasing drug resistance, there is a critical need to develop new drugs and vaccines to control Leishmania infection. Over the past few years, proteomics has become an important tool to understand the underlying biology of Leishmania parasites and host interaction. The large-scale study of proteins, both in parasites and within the host in response to infection, can accelerate the discovery of new therapeutic targets. By studying the proteomes of host cells and tissues infected with Leishmania, as well as changes in protein profiles among promastigotes and amastigotes, scientists hope to better understand the biology involved in the parasite survival and the host-parasite interaction. This review demonstrates the feasibility of proteomics as an approach to identify new proteins involved in Leishmania differentiation and intracellular survival. PMID:27548150

Using Proteomics to Understand How Leishmania Parasites Survive inside the Host and Establish Infection.

PubMed

Veras, Patrícia Sampaio Tavares; Bezerra de Menezes, Juliana Perrone

2016-08-19

Leishmania is a protozoan parasite that causes a wide range of different clinical manifestations in mammalian hosts. It is a major public health risk on different continents and represents one of the most important neglected diseases. Due to the high toxicity of the drugs currently used, and in the light of increasing drug resistance, there is a critical need to develop new drugs and vaccines to control Leishmania infection. Over the past few years, proteomics has become an important tool to understand the underlying biology of Leishmania parasites and host interaction. The large-scale study of proteins, both in parasites and within the host in response to infection, can accelerate the discovery of new therapeutic targets. By studying the proteomes of host cells and tissues infected with Leishmania, as well as changes in protein profiles among promastigotes and amastigotes, scientists hope to better understand the biology involved in the parasite survival and the host-parasite interaction. This review demonstrates the feasibility of proteomics as an approach to identify new proteins involved in Leishmania differentiation and intracellular survival.

Multi-level discriminative dictionary learning with application to large scale image classification.

PubMed

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Proteome-Wide Analysis and Diel Proteomic Profiling of the Cyanobacterium Arthrospira platensis PCC 8005

PubMed Central

Matallana-Surget, Sabine; Derock, Jérémy; Leroy, Baptiste; Badri, Hanène; Deschoenmaeker, Frédéric; Wattiez, Ruddy

2014-01-01

The filamentous cyanobacterium Arthrospira platensis has a long history of use as a food supply and it has been used by the European Space Agency in the MELiSSA project, an artificial microecosystem which supports life during long-term manned space missions. This study assesses progress in the field of cyanobacterial shotgun proteomics and light/dark diurnal cycles by focusing on Arthrospira platensis. Several fractionation workflows including gel-free and gel-based protein/peptide fractionation procedures were used and combined with LC-MS/MS analysis, enabling the overall identification of 1306 proteins, which represents 21% coverage of the theoretical proteome. A total of 30 proteins were found to be significantly differentially regulated under light/dark growth transition. Interestingly, most of the proteins showing differential abundance were related to photosynthesis, the Calvin cycle and translation processes. A novel aspect and major achievement of this work is the successful improvement of the cyanobacterial proteome coverage using a 3D LC-MS/MS approach, based on an immobilized metal affinity chromatography, a suitable tool that enabled us to eliminate the most abundant protein, the allophycocyanin. We also demonstrated that cell growth follows a light/dark cycle in A. platensis. This preliminary proteomic study has highlighted new characteristics of the Arthrospira platensis proteome in terms of diurnal regulation. PMID:24914774

SPS' Digest: the Swiss Proteomics Society selection of proteomics articles.

PubMed

Hoogland, Christine; Lion, Niels; Palagi, Patricia M; Sanchez, Jean-Charles; Tissot, Jean-Daniel

2005-08-01

Despite the consolidation of the specialized proteomics literature around a few established journals, such as Proteomics, Molecular and Cellular Proteomics, and the Journal of Proteome Research, a lot of information is still spread in many different publications from different fields, such as analytical sciences, MS, bioinformatics, etc. The purpose of SPS' Digest is to gather a selection of proteomics articles, to categorize them, and to make the list available on a periodic basis through a web page and email alerts.

Self-consistency tests of large-scale dynamics parameterizations for single-column modeling

DOE PAGES

Edman, Jacob P.; Romps, David M.

2015-03-18

Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, butmore » WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.« less

Spatial and temporal dynamics of the cardiac mitochondrial proteome.

PubMed

Lau, Edward; Huang, Derrick; Cao, Quan; Dincer, T Umut; Black, Caitie M; Lin, Amanda J; Lee, Jessica M; Wang, Ding; Liem, David A; Lam, Maggie P Y; Ping, Peipei

2015-04-01

Mitochondrial proteins alter in their composition and quantity drastically through time and space in correspondence to changing energy demands and cellular signaling events. The integrity and permutations of this dynamism are increasingly recognized to impact the functions of the cardiac proteome in health and disease. This article provides an overview on recent advances in defining the spatial and temporal dynamics of mitochondrial proteins in the heart. Proteomics techniques to characterize dynamics on a proteome scale are reviewed and the physiological consequences of altered mitochondrial protein dynamics are discussed. Lastly, we offer our perspectives on the unmet challenges in translating mitochondrial dynamics markers into the clinic.

Engineering management of large scale systems

NASA Technical Reports Server (NTRS)

Sanders, Serita; Gill, Tepper L.; Paul, Arthur S.

1989-01-01

The organization of high technology and engineering problem solving, has given rise to an emerging concept. Reasoning principles for integrating traditional engineering problem solving with system theory, management sciences, behavioral decision theory, and planning and design approaches can be incorporated into a methodological approach to solving problems with a long range perspective. Long range planning has a great potential to improve productivity by using a systematic and organized approach. Thus, efficiency and cost effectiveness are the driving forces in promoting the organization of engineering problems. Aspects of systems engineering that provide an understanding of management of large scale systems are broadly covered here. Due to the focus and application of research, other significant factors (e.g., human behavior, decision making, etc.) are not emphasized but are considered.

A relativistic signature in large-scale structure

NASA Astrophysics Data System (ADS)

Bartolo, Nicola; Bertacca, Daniele; Bruni, Marco; Koyama, Kazuya; Maartens, Roy; Matarrese, Sabino; Sasaki, Misao; Verde, Licia; Wands, David

2016-09-01

In General Relativity, the constraint equation relating metric and density perturbations is inherently nonlinear, leading to an effective non-Gaussianity in the dark matter density field on large scales-even if the primordial metric perturbation is Gaussian. Intrinsic non-Gaussianity in the large-scale dark matter overdensity in GR is real and physical. However, the variance smoothed on a local physical scale is not correlated with the large-scale curvature perturbation, so that there is no relativistic signature in the galaxy bias when using the simplest model of bias. It is an open question whether the observable mass proxies such as luminosity or weak lensing correspond directly to the physical mass in the simple halo bias model. If not, there may be observables that encode this relativistic signature.

Recent advances in proteomics of cereals.

PubMed

Bansal, Monika; Sharma, Madhu; Kanwar, Priyanka; Goyal, Aakash

Cereals contribute a major part of human nutrition and are considered as an integral source of energy for human diets. With genomic databases already available in cereals such as rice, wheat, barley, and maize, the focus has now moved to proteome analysis. Proteomics studies involve the development of appropriate databases based on developing suitable separation and purification protocols, identification of protein functions, and can confirm their functional networks based on already available data from other sources. Tremendous progress has been made in the past decade in generating huge data-sets for covering interactions among proteins, protein composition of various organs and organelles, quantitative and qualitative analysis of proteins, and to characterize their modulation during plant development, biotic, and abiotic stresses. Proteomics platforms have been used to identify and improve our understanding of various metabolic pathways. This article gives a brief review of efforts made by different research groups on comparative descriptive and functional analysis of proteomics applications achieved in the cereal science so far.

Using the High-Level Based Program Interface to Facilitate the Large Scale Scientific Computing

PubMed Central

Shang, Yizi; Shang, Ling; Gao, Chuanchang; Lu, Guiming; Ye, Yuntao; Jia, Dongdong

2014-01-01

This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based Gauss Jordan algorithm as a real example of large-scale scientific computing is used to evaluate those issues presented above. The results show that the high-level based program interface makes the complex scientific applications on large-scale scientific platform easier, though a little overhead is unavoidable. Also, the data anticipation migration mechanism can improve the efficiency of the platform which needs to process big data based scientific applications. PMID:24574931

Nano-LC FTICR tandem mass spectrometry for top-down proteomics: routine baseline unit mass resolution of whole cell lysate proteins up to 72 kDa.

PubMed

Tipton, Jeremiah D; Tran, John C; Catherman, Adam D; Ahlf, Dorothy R; Durbin, Kenneth R; Lee, Ji Eun; Kellie, John F; Kelleher, Neil L; Hendrickson, Christopher L; Marshall, Alan G

2012-03-06

Current high-throughput top-down proteomic platforms provide routine identification of proteins less than 25 kDa with 4-D separations. This short communication reports the application of technological developments over the past few years that improve protein identification and characterization for masses greater than 25 kDa. Advances in separation science have allowed increased numbers of proteins to be identified, especially by nanoliquid chromatography (nLC) prior to mass spectrometry (MS) analysis. Further, a goal of high-throughput top-down proteomics is to extend the mass range for routine nLC MS analysis up to 80 kDa because gene sequence analysis predicts that ~70% of the human proteome is transcribed to be less than 80 kDa. Normally, large proteins greater than 50 kDa are identified and characterized by top-down proteomics through fraction collection and direct infusion at relatively low throughput. Further, other MS-based techniques provide top-down protein characterization, however at low resolution for intact mass measurement. Here, we present analysis of standard (up to 78 kDa) and whole cell lysate proteins by Fourier transform ion cyclotron resonance mass spectrometry (nLC electrospray ionization (ESI) FTICR MS). The separation platform reduced the complexity of the protein matrix so that, at 14.5 T, proteins from whole cell lysate up to 72 kDa are baseline mass resolved on a nano-LC chromatographic time scale. Further, the results document routine identification of proteins at improved throughput based on accurate mass measurement (less than 10 ppm mass error) of precursor and fragment ions for proteins up to 50 kDa.

Policy Incentives in Canadian Large-Scale Assessment: How Policy Levers Influence Teacher Decisions about Instructional Change

ERIC Educational Resources Information Center

Copp, Derek T.

2017-01-01

Large-scale assessment (LSA) is a tool used by education authorities for several purposes, including the promotion of teacher-based instructional change. In Canada, all 10 provinces engage in large-scale testing across several grade levels and subjects, and also have the common expectation that the results data will be used to improve instruction…

Sound production due to large-scale coherent structures

NASA Technical Reports Server (NTRS)

Gatski, T. B.

1979-01-01

The acoustic pressure fluctuations due to large-scale finite amplitude disturbances in a free turbulent shear flow are calculated. The flow is decomposed into three component scales; the mean motion, the large-scale wave-like disturbance, and the small-scale random turbulence. The effect of the large-scale structure on the flow is isolated by applying both a spatial and phase average on the governing differential equations and by initially taking the small-scale turbulence to be in energetic equilibrium with the mean flow. The subsequent temporal evolution of the flow is computed from global energetic rate equations for the different component scales. Lighthill's theory is then applied to the region with the flowfield as the source and an observer located outside the flowfield in a region of uniform velocity. Since the time history of all flow variables is known, a minimum of simplifying assumptions for the Lighthill stress tensor is required, including no far-field approximations. A phase average is used to isolate the pressure fluctuations due to the large-scale structure, and also to isolate the dynamic process responsible. Variation of mean square pressure with distance from the source is computed to determine the acoustic far-field location and decay rate, and, in addition, spectra at various acoustic field locations are computed and analyzed. Also included are the effects of varying the growth and decay of the large-scale disturbance on the sound produced.

Large-scale influences in near-wall turbulence.

PubMed

Hutchins, Nicholas; Marusic, Ivan

2007-03-15

Hot-wire data acquired in a high Reynolds number facility are used to illustrate the need for adequate scale separation when considering the coherent structure in wall-bounded turbulence. It is found that a large-scale motion in the log region becomes increasingly comparable in energy to the near-wall cycle as the Reynolds number increases. Through decomposition of fluctuating velocity signals, it is shown that this large-scale motion has a distinct modulating influence on the small-scale energy (akin to amplitude modulation). Reassessment of DNS data, in light of these results, shows similar trends, with the rate and intensity of production due to the near-wall cycle subject to a modulating influence from the largest-scale motions.

Designing for Scale: Reflections on Rolling Out Reading Improvement in Kenya and Liberia.

PubMed

Gove, Amber; Korda Poole, Medina; Piper, Benjamin

2017-03-01

Since 2008, the Ministries of Education in Liberia and Kenya have undertaken transitions from small-scale pilot programs to improve reading outcomes among primary learners to the large-scale implementation of reading interventions. The effects of the pilots on learning outcomes were significant, but questions remained regarding whether such large gains could be sustained at scale. In this article, the authors dissect the Liberian and Kenyan experiences with implementing large-scale reading programs, documenting the critical components and conditions of the program designs that affected the likelihood of successfully transitioning from pilot to scale. They also review the design, deployment, and effectiveness of each pilot program and the scale, design, duration, enabling conditions, and initial effectiveness results of the scaled programs in each country. The implications of these results for the design of both pilot and large-scale reading programs are discussed in light of the experiences of both the Liberian and Kenyan programs. © 2017 Wiley Periodicals, Inc.

Generation of large-scale magnetic fields by small-scale dynamo in shear flows

NASA Astrophysics Data System (ADS)

Squire, Jonathan; Bhattacharjee, Amitava

2015-11-01

A new mechanism for turbulent mean-field dynamo is proposed, in which the magnetic fluctuations resulting from a small-scale dynamo drive the generation of large-scale magnetic fields. This is in stark contrast to the common idea that small-scale magnetic fields should be harmful to large-scale dynamo action. These dynamos occur in the presence of large-scale velocity shear and do not require net helicity, resulting from off-diagonal components of the turbulent resistivity tensor as the magnetic analogue of the ``shear-current'' effect. The dynamo is studied using a variety of computational and analytic techniques, both when the magnetic fluctuations arise self-consistently through the small-scale dynamo and in lower Reynolds number regimes. Given the inevitable existence of non-helical small-scale magnetic fields in turbulent plasmas, as well as the generic nature of velocity shear, the suggested mechanism may help to explain generation of large-scale magnetic fields across a wide range of astrophysical objects. This work was supported by a Procter Fellowship at Princeton University, and the US Department of Energy Grant DE-AC02-09-CH11466.

Trends in mass spectrometry instrumentation for proteomics

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

Smith, Richard D.

2002-12-01

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

Environmental proteomics: a paradigm shift in characterizing microbial activities at the molecular level.

PubMed

Keller, Martin; Hettich, Robert

2009-03-01

The increase in sequencing capacity led to a new wave of metagenomic projects, enabling and setting the prerequisite for the application of environmental proteomics technologies. This review describes the current status of environmental proteomics. It describes sample preparation as well as the two major technologies applied within this field: two-dimensional electrophoresis-based environmental proteomics and liquid chromatography-mass spectrometry-based environmental proteomics. It also highlights current publications and describes major scientific findings. The review closes with a discussion of critical improvements in the area of integrating experimental mass spectrometry technologies with bioinformatics as well as improved sample handling.

NMR in the SPINE Structural Proteomics project.

PubMed

Ab, E; Atkinson, A R; Banci, L; Bertini, I; Ciofi-Baffoni, S; Brunner, K; Diercks, T; Dötsch, V; Engelke, F; Folkers, G E; Griesinger, C; Gronwald, W; Günther, U; Habeck, M; de Jong, R N; Kalbitzer, H R; Kieffer, B; Leeflang, B R; Loss, S; Luchinat, C; Marquardsen, T; Moskau, D; Neidig, K P; Nilges, M; Piccioli, M; Pierattelli, R; Rieping, W; Schippmann, T; Schwalbe, H; Travé, G; Trenner, J; Wöhnert, J; Zweckstetter, M; Kaptein, R

2006-10-01

This paper describes the developments, role and contributions of the NMR spectroscopy groups in the Structural Proteomics In Europe (SPINE) consortium. Focusing on the development of high-throughput (HTP) pipelines for NMR structure determinations of proteins, all aspects from sample preparation, data acquisition, data processing, data analysis to structure determination have been improved with respect to sensitivity, automation, speed, robustness and validation. Specific highlights are protonless (13)C-direct detection methods and inferential structure determinations (ISD). In addition to technological improvements, these methods have been applied to deliver over 60 NMR structures of proteins, among which are five that failed to crystallize. The inclusion of NMR spectroscopy in structural proteomics pipelines improves the success rate for protein structure determinations.

Extending large-scale forest inventories to assess urban forests.

PubMed

Corona, Piermaria; Agrimi, Mariagrazia; Baffetta, Federica; Barbati, Anna; Chiriacò, Maria Vincenza; Fattorini, Lorenzo; Pompei, Enrico; Valentini, Riccardo; Mattioli, Walter

2012-03-01

Urban areas are continuously expanding today, extending their influence on an increasingly large proportion of woods and trees located in or nearby urban and urbanizing areas, the so-called urban forests. Although these forests have the potential for significantly improving the quality the urban environment and the well-being of the urban population, data to quantify the extent and characteristics of urban forests are still lacking or fragmentary on a large scale. In this regard, an expansion of the domain of multipurpose forest inventories like National Forest Inventories (NFIs) towards urban forests would be required. To this end, it would be convenient to exploit the same sampling scheme applied in NFIs to assess the basic features of urban forests. This paper considers approximately unbiased estimators of abundance and coverage of urban forests, together with estimators of the corresponding variances, which can be achieved from the first phase of most large-scale forest inventories. A simulation study is carried out in order to check the performance of the considered estimators under various situations involving the spatial distribution of the urban forests over the study area. An application is worked out on the data from the Italian NFI.

Office Overview | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Office of Cancer Clinical Proteomics Research (OCCPR) at the National Cancer Institute (NCI) aims to improve prevention, early detection, diagnosis, and treatment of cancer by enhancing the understanding of the molecular mechanisms of cancer, advancing proteome/proteogenome science and technology development through community resources (data and reagents), and accelerating the translation of molecular findings into the clinic.

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.

Feasibility of large-scale power plants based on thermoelectric effects

NASA Astrophysics Data System (ADS)

Liu, Liping

2014-12-01

Heat resources of small temperature difference are easily accessible, free and enormous on the Earth. Thermoelectric effects provide the technology for converting these heat resources directly into electricity. We present designs for electricity generators based on thermoelectric effects that utilize heat resources of small temperature difference, e.g., ocean water at different depths and geothermal resources, and conclude that large-scale power plants based on thermoelectric effects are feasible and economically competitive. The key observation is that the power factor of thermoelectric materials, unlike the figure of merit, can be improved by orders of magnitude upon laminating good conductors and good thermoelectric materials. The predicted large-scale power generators based on thermoelectric effects, if validated, will have the advantages of the scalability, renewability, and free supply of heat resources of small temperature difference on the Earth.

Large-scale structure perturbation theory without losing stream crossing

NASA Astrophysics Data System (ADS)

McDonald, Patrick; Vlah, Zvonimir

2018-01-01

We suggest an approach to perturbative calculations of large-scale clustering in the Universe that includes from the start the stream crossing (multiple velocities for mass elements at a single position) that is lost in traditional calculations. Starting from a functional integral over displacement, the perturbative series expansion is in deviations from (truncated) Zel'dovich evolution, with terms that can be computed exactly even for stream-crossed displacements. We evaluate the one-loop formulas for displacement and density power spectra numerically in 1D, finding dramatic improvement in agreement with N-body simulations compared to the Zel'dovich power spectrum (which is exact in 1D up to stream crossing). Beyond 1D, our approach could represent an improvement over previous expansions even aside from the inclusion of stream crossing, but we have not investigated this numerically. In the process we show how to achieve effective-theory-like regulation of small-scale fluctuations without free parameters.

Large-scale structure perturbation theory without losing stream crossing

DOE PAGES

McDonald, Patrick; Vlah, Zvonimir

2018-01-10

Here, we suggest an approach to perturbative calculations of large-scale clustering in the Universe that includes from the start the stream crossing (multiple velocities for mass elements at a single position) that is lost in traditional calculations. Starting from a functional integral over displacement, the perturbative series expansion is in deviations from (truncated) Zel’dovich evolution, with terms that can be computed exactly even for stream-crossed displacements. We evaluate the one-loop formulas for displacement and density power spectra numerically in 1D, finding dramatic improvement in agreement with N-body simulations compared to the Zel’dovich power spectrum (which is exact in 1D upmore » to stream crossing). Beyond 1D, our approach could represent an improvement over previous expansions even aside from the inclusion of stream crossing, but we have not investigated this numerically. In the process we show how to achieve effective-theory-like regulation of small-scale fluctuations without free parameters.« less

Large-scale structure perturbation theory without losing stream crossing

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

McDonald, Patrick; Vlah, Zvonimir

Here, we suggest an approach to perturbative calculations of large-scale clustering in the Universe that includes from the start the stream crossing (multiple velocities for mass elements at a single position) that is lost in traditional calculations. Starting from a functional integral over displacement, the perturbative series expansion is in deviations from (truncated) Zel’dovich evolution, with terms that can be computed exactly even for stream-crossed displacements. We evaluate the one-loop formulas for displacement and density power spectra numerically in 1D, finding dramatic improvement in agreement with N-body simulations compared to the Zel’dovich power spectrum (which is exact in 1D upmore » to stream crossing). Beyond 1D, our approach could represent an improvement over previous expansions even aside from the inclusion of stream crossing, but we have not investigated this numerically. In the process we show how to achieve effective-theory-like regulation of small-scale fluctuations without free parameters.« less

Studies of Sub-Synchronous Oscillations in Large-Scale Wind Farm Integrated System

NASA Astrophysics Data System (ADS)

Yue, Liu; Hang, Mend

2018-01-01

With the rapid development and construction of large-scale wind farms and grid-connected operation, the series compensation wind power AC transmission is gradually becoming the main way of power usage and improvement of wind power availability and grid stability, but the integration of wind farm will change the SSO (Sub-Synchronous oscillation) damping characteristics of synchronous generator system. Regarding the above SSO problem caused by integration of large-scale wind farms, this paper focusing on doubly fed induction generator (DFIG) based wind farms, aim to summarize the SSO mechanism in large-scale wind power integrated system with series compensation, which can be classified as three types: sub-synchronous control interaction (SSCI), sub-synchronous torsional interaction (SSTI), sub-synchronous resonance (SSR). Then, SSO modelling and analysis methods are categorized and compared by its applicable areas. Furthermore, this paper summarizes the suppression measures of actual SSO projects based on different control objectives. Finally, the research prospect on this field is explored.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications.

PubMed

Jimenez, Connie R; Verheul, Henk M W

2014-01-01

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Placental Proteomics: A Shortcut to Biological Insight

PubMed Central

Robinson, John M.; Vandré, Dale D.; Ackerman, William E.

2012-01-01

Proteomics analysis of biological samples has the potential to identify novel protein expression patterns and/or changes in protein expression patterns in different developmental or disease states. An important component of successful proteomics research, at least in its present form, is to reduce the complexity of the sample if it is derived from cells or tissues. One method to simplify complex tissues is to focus on a specific, highly purified sub-proteome. Using this approach we have developed methods to prepare highly enriched fractions of the apical plasma membrane of the syncytiotrophoblast. Through proteomics analysis of this fraction we have identified over five hundred proteins several of which were previously not known to reside in the syncytiotrophoblast. Herein, we focus on two of these, dysferlin and myoferlin. These proteins, largely known from studies of skeletal muscle, may not have been found in the human placenta were it not for discovery-based proteomics analysis. This new knowledge, acquired through a discovery-driven approach, can now be applied for the generation of hypothesis-based experimentation. Thus discovery-based and hypothesis-based research are complimentary approaches that when coupled together can hasten scientific discoveries. PMID:19070895

PKI security in large-scale healthcare networks.

PubMed

Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos

2012-06-01

During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.

The Status of Large-Scale Assessment in the Pacific Region. REL Technical Brief. REL 2008-No. 003

ERIC Educational Resources Information Center

Ryan, Jennifer; Keir, Scott

2008-01-01

This technical brief describes the large-scale assessment measures and practices used in the jurisdictions served by the Pacific Regional Educational Laboratory. The need for effective large-scale assessment was identified as a major priority for improving student achievement in the Pacific Region jurisdictions: American Samoa, Guam, Hawaii, the…

Large-scale velocities and primordial non-Gaussianity

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

Schmidt, Fabian

2010-09-15

We study the peculiar velocities of density peaks in the presence of primordial non-Gaussianity. Rare, high-density peaks in the initial density field can be identified with tracers such as galaxies and clusters in the evolved matter distribution. The distribution of relative velocities of peaks is derived in the large-scale limit using two different approaches based on a local biasing scheme. Both approaches agree, and show that halos still stream with the dark matter locally as well as statistically, i.e. they do not acquire a velocity bias. Nonetheless, even a moderate degree of (not necessarily local) non-Gaussianity induces a significant skewnessmore » ({approx}0.1-0.2) in the relative velocity distribution, making it a potentially interesting probe of non-Gaussianity on intermediate to large scales. We also study two-point correlations in redshift space. The well-known Kaiser formula is still a good approximation on large scales, if the Gaussian halo bias is replaced with its (scale-dependent) non-Gaussian generalization. However, there are additional terms not encompassed by this simple formula which become relevant on smaller scales (k > or approx. 0.01h/Mpc). Depending on the allowed level of non-Gaussianity, these could be of relevance for future large spectroscopic surveys.« less

Fuzzy adaptive strong tracking scaled unscented Kalman filter for initial alignment of large misalignment angles

NASA Astrophysics Data System (ADS)

Li, Jing; Song, Ningfang; Yang, Gongliu; Jiang, Rui

2016-07-01

In the initial alignment process of strapdown inertial navigation system (SINS), large misalignment angles always bring nonlinear problem, which can usually be processed using the scaled unscented Kalman filter (SUKF). In this paper, the problem of large misalignment angles in SINS alignment is further investigated, and the strong tracking scaled unscented Kalman filter (STSUKF) is proposed with fixed parameters to improve convergence speed, while these parameters are artificially constructed and uncertain in real application. To further improve the alignment stability and reduce the parameters selection, this paper proposes a fuzzy adaptive strategy combined with STSUKF (FUZZY-STSUKF). As a result, initial alignment scheme of large misalignment angles based on FUZZY-STSUKF is designed and verified by simulations and turntable experiment. The results show that the scheme improves the accuracy and convergence speed of SINS initial alignment compared with those based on SUKF and STSUKF.

Implicity restarted Arnoldi/Lanczos methods for large scale eigenvalue calculations

NASA Technical Reports Server (NTRS)

Sorensen, Danny C.

1996-01-01

Eigenvalues and eigenfunctions of linear operators are important to many areas of applied mathematics. The ability to approximate these quantities numerically is becoming increasingly important in a wide variety of applications. This increasing demand has fueled interest in the development of new methods and software for the numerical solution of large-scale algebraic eigenvalue problems. In turn, the existence of these new methods and software, along with the dramatically increased computational capabilities now available, has enabled the solution of problems that would not even have been posed five or ten years ago. Until very recently, software for large-scale nonsymmetric problems was virtually non-existent. Fortunately, the situation is improving rapidly. The purpose of this article is to provide an overview of the numerical solution of large-scale algebraic eigenvalue problems. The focus will be on a class of methods called Krylov subspace projection methods. The well-known Lanczos method is the premier member of this class. The Arnoldi method generalizes the Lanczos method to the nonsymmetric case. A recently developed variant of the Arnoldi/Lanczos scheme called the Implicitly Restarted Arnoldi Method is presented here in some depth. This method is highlighted because of its suitability as a basis for software development.

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

DTIC Science & Technology

2010-01-25

2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

A new framework to increase the efficiency of large-scale solar power plants.

NASA Astrophysics Data System (ADS)

Alimohammadi, Shahrouz; Kleissl, Jan P.

2015-11-01

A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.

Platelet proteomics: from discovery to diagnosis.

PubMed

Looße, Christina; Swieringa, Frauke; Heemskerk, Johan W M; Sickmann, Albert; Lorenz, Christin

2018-05-22

Platelets are the smallest cells within the circulating blood with key roles in physiological haemostasis and pathological thrombosis regulated by the onset of activating/inhibiting processes via receptor responses and signalling cascades. Areas covered: Proteomics as well as genomic approaches have been fundamental in identifying and quantifying potential targets for future diagnostic strategies in the prevention of bleeding and thrombosis, and uncovering the complexity of platelet functions in health and disease. In this article, we provide a critical overview on current functional tests used in diagnostics and the future perspectives for platelet proteomics in clinical applications. Expert commentary: Proteomics represents a valuable tool for the identification of patients with diverse platelet associated defects. In-depth validation of identified biomarkers, e.g. receptors, signalling proteins, post-translational modifications, in large cohorts is decisive for translation into routine clinical diagnostics.

Large-scale regions of antimatter

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

Grobov, A. V., E-mail: alexey.grobov@gmail.com; Rubin, S. G., E-mail: sgrubin@mephi.ru

2015-07-15

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era.

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing

PubMed Central

Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. Methods: We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the ‘learning to rank’ framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. Results: DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. Availability and Implementation: The software is available upon request. Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307646

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing.

PubMed

Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-06-15

Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the 'learning to rank' framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. The software is available upon request. zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Towards large scale multi-target tracking

NASA Astrophysics Data System (ADS)

Vo, Ba-Ngu; Vo, Ba-Tuong; Reuter, Stephan; Lam, Quang; Dietmayer, Klaus

2014-06-01

Multi-target tracking is intrinsically an NP-hard problem and the complexity of multi-target tracking solutions usually do not scale gracefully with problem size. Multi-target tracking for on-line applications involving a large number of targets is extremely challenging. This article demonstrates the capability of the random finite set approach to provide large scale multi-target tracking algorithms. In particular it is shown that an approximate filter known as the labeled multi-Bernoulli filter can simultaneously track one thousand five hundred targets in clutter on a standard laptop computer.

The Expanded Large Scale Gap Test

DTIC Science & Technology

1987-03-01

NSWC TR 86-32 DTIC THE EXPANDED LARGE SCALE GAP TEST BY T. P. LIDDIARD D. PRICE RESEARCH AND TECHNOLOGY DEPARTMENT ’ ~MARCH 1987 Ap~proved for public...arises, to reduce the spread in the LSGT 50% gap value.) The worst charges, such as those with the highest or lowest densities, the largest re-pressed...Arlington, VA 22217 PE 62314N INS3A 1 RJ14E31 7R4TBK 11 TITLE (Include Security CIlmsilficatiorn The Expanded Large Scale Gap Test . 12. PEIRSONAL AUTHOR() T

Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

PubMed Central

Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

2009-01-01

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins

Performance of Extended Local Clustering Organization (LCO) for Large Scale Job-Shop Scheduling Problem (JSP)

NASA Astrophysics Data System (ADS)

Konno, Yohko; Suzuki, Keiji

This paper describes an approach to development of a solution algorithm of a general-purpose for large scale problems using “Local Clustering Organization (LCO)” as a new solution for Job-shop scheduling problem (JSP). Using a performance effective large scale scheduling in the study of usual LCO, a solving JSP keep stability induced better solution is examined. In this study for an improvement of a performance of a solution for JSP, processes to a optimization by LCO is examined, and a scheduling solution-structure is extended to a new solution-structure based on machine-division. A solving method introduced into effective local clustering for the solution-structure is proposed as an extended LCO. An extended LCO has an algorithm which improves scheduling evaluation efficiently by clustering of parallel search which extends over plural machines. A result verified by an application of extended LCO on various scale of problems proved to conduce to minimizing make-span and improving on the stable performance.

An informal paper on large-scale dynamic systems

NASA Technical Reports Server (NTRS)

Ho, Y. C.

1975-01-01

Large scale systems are defined as systems requiring more than one decision maker to control the system. Decentralized control and decomposition are discussed for large scale dynamic systems. Information and many-person decision problems are analyzed.

QC-ART: A tool for real-time quality control assessment of mass spectrometry-based proteomics data.

PubMed

Stanfill, Bryan A; Nakayasu, Ernesto S; Bramer, Lisa M; Thompson, Allison M; Ansong, Charles K; Clauss, Therese; Gritsenko, Marina A; Monroe, Matthew E; Moore, Ronald J; Orton, Daniel J; Piehowski, Paul D; Schepmoes, Athena A; Smith, Richard D; Webb-Robertson, Bobbie-Jo; Metz, Thomas O

2018-04-17

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected.  In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration.  To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality.  QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis.  We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics.

PubMed

Gao, Yan; Lim, Teck Kwang; Lin, Qingsong; Li, Sam Fong Yau

2016-04-29

Cypermethrin (CYP) is one of the most widely used pesticides in large scale for agricultural and domestic purpose and the residue often seriously affects aquatic system. Environmental pollutant-induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of action. While proteomics investigations of CYP stress in some animal models have been well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001μg/L, 0.01μg/L and 1μg/L) of CYP on green algae Chlorella vulgaris for 24h and 96h was investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrate metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticide-exposed plant and algae. Copyright © 2016 Elsevier B.V. All rights reserved.

The Response of the Root Proteome to the Synthetic Strigolactone GR24 in Arabidopsis*

PubMed Central

Walton, Alan; Stes, Elisabeth; Goeminne, Geert; Braem, Lukas; Vuylsteke, Marnik; Matthys, Cedrick; De Cuyper, Carolien; Staes, An; Vandenbussche, Jonathan; Boyer, François-Didier; Vanholme, Ruben; Fromentin, Justine; Boerjan, Wout; Gevaert, Kris; Goormachtig, Sofie

2016-01-01

Strigolactones are plant metabolites that act as phytohormones and rhizosphere signals. Whereas most research on unraveling the action mechanisms of strigolactones is focused on plant shoots, we investigated proteome adaptation during strigolactone signaling in the roots of Arabidopsis thaliana. Through large-scale, time-resolved, and quantitative proteomics, the impact of the strigolactone analog rac-GR24 was elucidated on the root proteome of the wild type and the signaling mutant more axillary growth 2 (max2). Our study revealed a clear MAX2-dependent rac-GR24 response: an increase in abundance of enzymes involved in flavonol biosynthesis, which was reduced in the max2–1 mutant. Mass spectrometry-driven metabolite profiling and thin-layer chromatography experiments demonstrated that these changes in protein expression lead to the accumulation of specific flavonols. Moreover, quantitative RT-PCR revealed that the flavonol-related protein expression profile was caused by rac-GR24-induced changes in transcript levels of the corresponding genes. This induction of flavonol production was shown to be activated by the two pure enantiomers that together make up rac-GR24. Finally, our data provide much needed clues concerning the multiple roles played by MAX2 in the roots and a comprehensive view of the rac-GR24-induced response in the root proteome. PMID:27317401

On large-scale dynamo action at high magnetic Reynolds number

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

Cattaneo, F.; Tobias, S. M., E-mail: smt@maths.leeds.ac.uk

2014-07-01

We consider the generation of magnetic activity—dynamo waves—in the astrophysical limit of very large magnetic Reynolds number. We consider kinematic dynamo action for a system consisting of helical flow and large-scale shear. We demonstrate that large-scale dynamo waves persist at high Rm if the helical flow is characterized by a narrow band of spatial scales and the shear is large enough. However, for a wide band of scales the dynamo becomes small scale with a further increase of Rm, with dynamo waves re-emerging only if the shear is then increased. We show that at high Rm, the key effect ofmore » the shear is to suppress small-scale dynamo action, allowing large-scale dynamo action to be observed. We conjecture that this supports a general 'suppression principle'—large-scale dynamo action can only be observed if there is a mechanism that suppresses the small-scale fluctuations.« less

Large-scale dynamos in rapidly rotating plane layer convection

NASA Astrophysics Data System (ADS)

Bushby, P. J.; Käpylä, P. J.; Masada, Y.; Brandenburg, A.; Favier, B.; Guervilly, C.; Käpylä, M. J.

2018-05-01

Context. Convectively driven flows play a crucial role in the dynamo processes that are responsible for producing magnetic activity in stars and planets. It is still not fully understood why many astrophysical magnetic fields have a significant large-scale component. Aims: Our aim is to investigate the dynamo properties of compressible convection in a rapidly rotating Cartesian domain, focusing upon a parameter regime in which the underlying hydrodynamic flow is known to be unstable to a large-scale vortex instability. Methods: The governing equations of three-dimensional non-linear magnetohydrodynamics (MHD) are solved numerically. Different numerical schemes are compared and we propose a possible benchmark case for other similar codes. Results: In keeping with previous related studies, we find that convection in this parameter regime can drive a large-scale dynamo. The components of the mean horizontal magnetic field oscillate, leading to a continuous overall rotation of the mean field. Whilst the large-scale vortex instability dominates the early evolution of the system, the large-scale vortex is suppressed by the magnetic field and makes a negligible contribution to the mean electromotive force that is responsible for driving the large-scale dynamo. The cycle period of the dynamo is comparable to the ohmic decay time, with longer cycles for dynamos in convective systems that are closer to onset. In these particular simulations, large-scale dynamo action is found only when vertical magnetic field boundary conditions are adopted at the upper and lower boundaries. Strongly modulated large-scale dynamos are found at higher Rayleigh numbers, with periods of reduced activity (grand minima-like events) occurring during transient phases in which the large-scale vortex temporarily re-establishes itself, before being suppressed again by the magnetic field.

On the improvement for charging large-scale flexible electrostatic actuators

NASA Astrophysics Data System (ADS)

Liao, Hsu-Ching; Chen, Han-Long; Su, Yu-Hao; Chen, Yu-Chi; Ko, Wen-Ching; Liou, Chang-Ho; Wu, Wen-Jong; Lee, Chih-Kung

2011-04-01

Recently, the development of flexible electret based electrostatic actuator has been widely discussed. The devices was shown to have high sound quality, energy saving, flexible structure and can be cut to any shape. However, achieving uniform charge on the electret diaphragm is one of the most critical processes needed to have the speaker ready for large-scale production. In this paper, corona discharge equipment contains multi-corona probes and grid bias was set up to inject spatial charges within the electret diaphragm. The optimal multi-corona probes system was adjusted to achieve uniform charge distribution of electret diaphragm. The processing conditions include the distance between the corona probes, the voltages of corona probe and grid bias, etc. We assembled the flexible electret loudspeakers first and then measured their sound pressure and beam pattern. The uniform charge distribution within the electret diaphragm based flexible electret loudspeaker provided us with the opportunity to shape the loudspeaker arbitrarily and to tailor the sound distribution per specifications request. Some of the potential futuristic applications for this device such as sound poster, smart clothes, and sound wallpaper, etc. were discussed as well.

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

Galaxy clustering and the origin of large-scale flows

NASA Technical Reports Server (NTRS)

Juszkiewicz, R.; Yahil, A.

1989-01-01

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

Large-scale anisotropy of the cosmic microwave background radiation

NASA Technical Reports Server (NTRS)

Silk, J.; Wilson, M. L.

1981-01-01

Inhomogeneities in the large-scale distribution of matter inevitably lead to the generation of large-scale anisotropy in the cosmic background radiation. The dipole, quadrupole, and higher order fluctuations expected in an Einstein-de Sitter cosmological model have been computed. The dipole and quadrupole anisotropies are comparable to the measured values, and impose important constraints on the allowable spectrum of large-scale matter density fluctuations. A significant dipole anisotropy is generated by the matter distribution on scales greater than approximately 100 Mpc. The large-scale anisotropy is insensitive to the ionization history of the universe since decoupling, and cannot easily be reconciled with a galaxy formation theory that is based on primordial adiabatic density fluctuations.

Evaluating the Large-Scale Environment of Extreme Events Using Reanalyses

NASA Astrophysics Data System (ADS)

Bosilovich, M. G.; Schubert, S. D.; Koster, R. D.; da Silva, A. M., Jr.; Eichmann, A.

2014-12-01

Extreme conditions and events have always been a long standing concern in weather forecasting and national security. While some evidence indicates extreme weather will increase in global change scenarios, extremes are often related to the large scale atmospheric circulation, but also occurring infrequently. Reanalyses assimilate substantial amounts of weather data and a primary strength of reanalysis data is the representation of the large-scale atmospheric environment. In this effort, we link the occurrences of extreme events or climate indicators to the underlying regional and global weather patterns. Now, with greater than 3o years of data, reanalyses can include multiple cases of extreme events, and thereby identify commonality among the weather to better characterize the large-scale to global environment linked to the indicator or extreme event. Since these features are certainly regionally dependent, and also, the indicators of climate are continually being developed, we outline various methods to analyze the reanalysis data and the development of tools to support regional evaluation of the data. Here, we provide some examples of both individual case studies and composite studies of similar events. For example, we will compare the large scale environment for Northeastern US extreme precipitation with that of highest mean precipitation seasons. Likewise, southerly winds can shown to be a major contributor to very warm days in the Northeast winter. While most of our development has involved NASA's MERRA reanalysis, we are also looking forward to MERRA-2 which includes several new features that greatly improve the representation of weather and climate, especially for the regions and sectors involved in the National Climate Assessment.

Redox Proteomics of Protein-bound Methionine Oxidation*

PubMed Central

Ghesquière, Bart; Jonckheere, Veronique; Colaert, Niklaas; Van Durme, Joost; Timmerman, Evy; Goethals, Marc; Schymkowitz, Joost; Rousseau, Frederic; Vandekerckhove, Joël; Gevaert, Kris

2011-01-01

We here present a new method to measure the degree of protein-bound methionine sulfoxide formation at a proteome-wide scale. In human Jurkat cells that were stressed with hydrogen peroxide, over 2000 oxidation-sensitive methionines in more than 1600 different proteins were mapped and their extent of oxidation was quantified. Meta-analysis of the sequences surrounding the oxidized methionine residues revealed a high preference for neighboring polar residues. Using synthetic methionine sulfoxide containing peptides designed according to the observed sequence preferences in the oxidized Jurkat proteome, we discovered that the substrate specificity of the cellular methionine sulfoxide reductases is a major determinant for the steady-state of methionine oxidation. This was supported by a structural modeling of the MsrA catalytic center. Finally, we applied our method onto a serum proteome from a mouse sepsis model and identified 35 in vivo methionine oxidation events in 27 different proteins. PMID:21406390

Building ProteomeTools based on a complete synthetic human proteome

PubMed Central

Zolg, Daniel P.; Wilhelm, Mathias; Schnatbaum, Karsten; Zerweck, Johannes; Knaute, Tobias; Delanghe, Bernard; Bailey, Derek J.; Gessulat, Siegfried; Ehrlich, Hans-Christian; Weininger, Maximilian; Yu, Peng; Schlegl, Judith; Kramer, Karl; Schmidt, Tobias; Kusebauch, Ulrike; Deutsch, Eric W.; Aebersold, Ruedi; Moritz, Robert L.; Wenschuh, Holger; Moehring, Thomas; Aiche, Stephan; Huhmer, Andreas; Reimer, Ulf; Kuster, Bernhard

2018-01-01

The ProteomeTools project builds molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we report the generation and multimodal LC-MS/MS analysis of >330,000 synthetic tryptic peptides representing essentially all canonical human gene products and exemplify the utility of this data. The resource will be extended to >1 million peptides and all data will be shared with the community via ProteomicsDB and proteomeXchange. PMID:28135259

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Limited accessibility to designs and results of Japanese large-scale clinical trials for cardiovascular diseases.

PubMed

Sawata, Hiroshi; Ueshima, Kenji; Tsutani, Kiichiro

2011-04-14

Clinical evidence is important for improving the treatment of patients by health care providers. In the study of cardiovascular diseases, large-scale clinical trials involving thousands of participants are required to evaluate the risks of cardiac events and/or death. The problems encountered in conducting the Japanese Acute Myocardial Infarction Prospective (JAMP) study highlighted the difficulties involved in obtaining the financial and infrastructural resources necessary for conducting large-scale clinical trials. The objectives of the current study were: 1) to clarify the current funding and infrastructural environment surrounding large-scale clinical trials in cardiovascular and metabolic diseases in Japan, and 2) to find ways to improve the environment surrounding clinical trials in Japan more generally. We examined clinical trials examining cardiovascular diseases that evaluated true endpoints and involved 300 or more participants using Pub-Med, Ichushi (by the Japan Medical Abstracts Society, a non-profit organization), websites of related medical societies, the University Hospital Medical Information Network (UMIN) Clinical Trials Registry, and clinicaltrials.gov at three points in time: 30 November, 2004, 25 February, 2007 and 25 July, 2009. We found a total of 152 trials that met our criteria for 'large-scale clinical trials' examining cardiovascular diseases in Japan. Of these, 72.4% were randomized controlled trials (RCTs). Of 152 trials, 9.2% of the trials examined more than 10,000 participants, and 42.8% examined between 1,000 and 10,000 participants. The number of large-scale clinical trials markedly increased from 2001 to 2004, but suddenly decreased in 2007, then began to increase again. Ischemic heart disease (39.5%) was the most common target disease. Most of the larger-scale trials were funded by private organizations such as pharmaceutical companies. The designs and results of 13 trials were not disclosed. To improve the quality of clinical

Characterization of the canine urinary proteome.

PubMed

Brandt, Laura E; Ehrhart, E J; Scherman, Hataichanok; Olver, Christine S; Bohn, Andrea A; Prenni, Jessica E

2014-06-01

Urine is an attractive biofluid for biomarker discovery as it is easy and minimally invasive to obtain. While numerous studies have focused on the characterization of human urine, much less research has focused on canine urine. The objectives of this study were to characterize the universal canine urinary proteome (both soluble and exosomal), to determine the overlap between the canine proteome and a representative human urinary proteome study, to generate a resource for future canine studies, and to determine the suitability of the dog as a large animal model for human diseases. The soluble and exosomal fractions of normal canine urine were characterized using liquid chromatography tandem mass spectrometry (LC-MS/MS). Biological Networks Gene Ontology (BiNGO) software was utilized to assign the canine urinary proteome to respective Gene Ontology categories, such as Cellular Component, Molecular Function, and Biological Process. Over 500 proteins were confidently identified in normal canine urine. Gene Ontology analysis revealed that exosomal proteins were largely derived from an intracellular location, while soluble proteins included both extracellular and membrane proteins. Exosome proteins were assigned to metabolic processes and localization, while soluble proteins were primarily annotated to specific localization processes. Several proteins identified in normal canine urine have previously been identified in human urine where these proteins are related to various extrarenal and renal diseases. The results of this study illustrate the potential of the dog as an animal model for human disease states and provide the framework for future studies of canine renal diseases. © 2014 American Society for Veterinary Clinical Pathology and European Society for Veterinary Clinical Pathology.

Large-scale production of lipoplexes with long shelf-life.

PubMed

Clement, Jule; Kiefer, Karin; Kimpfler, Andrea; Garidel, Patrick; Peschka-Süss, Regine

2005-01-01

The instability of lipoplex formulations is a major obstacle to overcome before their commercial application in gene therapy. In this study, a continuous mixing technique for the large-scale preparation of lipoplexes followed by lyophilisation for increased stability and shelf-life has been developed. Lipoplexes were analysed for transfection efficiency and cytotoxicity in human aorta smooth muscle cells (HASMC) and a rat smooth muscle cell line (A-10 SMC). Homogeneity of lipid/DNA-products was investigated by photon correlation spectroscopy (PCS) and cryotransmission electron microscopy (cryo-TEM). Studies have been undertaken with DAC-30, a composition of 3beta-[N-(N,N'-dimethylaminoethane)-carbamoyl]-cholesterol (DAC-Chol) and dioleylphosphatidylethanolamine (DOPE) and a green fluorescent protein (GFP) expressing marker plasmid. A continuous mixing technique was compared to the small-scale preparation of lipoplexes by pipetting. Individual steps of the continuous mixing process were evaluated in order to optimise the manufacturing technique: lipid/plasmid ratio, composition of transfection medium, pre-treatment of the lipid, size of the mixing device, mixing procedure and the influence of the lyophilisation process. It could be shown that the method developed for production of lipoplexes on a large scale under sterile conditions led to lipoplexes with good transfection efficiencies combined with low cytotoxicity, improved characteristics and long shelf-life.

Economically viable large-scale hydrogen liquefaction

NASA Astrophysics Data System (ADS)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Large-Scale Coronal Heating from the Solar Magnetic Network

NASA Technical Reports Server (NTRS)

Falconer, David A.; Moore, Ronald L.; Porter, Jason G.; Hathaway, David H.

1999-01-01

In Fe 12 images from SOHO/EIT, the quiet solar corona shows structure on scales ranging from sub-supergranular (i.e., bright points and coronal network) to multi- supergranular. In Falconer et al 1998 (Ap.J., 501, 386) we suppressed the large-scale background and found that the network-scale features are predominantly rooted in the magnetic network lanes at the boundaries of the supergranules. The emission of the coronal network and bright points contribute only about 5% of the entire quiet solar coronal Fe MI emission. Here we investigate the large-scale corona, the supergranular and larger-scale structure that we had previously treated as a background, and that emits 95% of the total Fe XII emission. We compare the dim and bright halves of the large- scale corona and find that the bright half is 1.5 times brighter than the dim half, has an order of magnitude greater area of bright point coverage, has three times brighter coronal network, and has about 1.5 times more magnetic flux than the dim half These results suggest that the brightness of the large-scale corona is more closely related to the large- scale total magnetic flux than to bright point activity. We conclude that in the quiet sun: (1) Magnetic flux is modulated (concentrated/diluted) on size scales larger than supergranules. (2) The large-scale enhanced magnetic flux gives an enhanced, more active, magnetic network and an increased incidence of network bright point formation. (3) The heating of the large-scale corona is dominated by more widespread, but weaker, network activity than that which heats the bright points. This work was funded by the Solar Physics Branch of NASA's office of Space Science through the SR&T Program and the SEC Guest Investigator Program.

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.

Modification of the Creator recombination system for proteomics applications--improved expression by addition of splice sites.

PubMed

Colwill, Karen; Wells, Clark D; Elder, Kelly; Goudreault, Marilyn; Hersi, Kadija; Kulkarni, Sarang; Hardy, W Rod; Pawson, Tony; Morin, Gregg B

2006-03-06

Recombinational systems have been developed to rapidly shuttle Open Reading Frames (ORFs) into multiple expression vectors in order to analyze the large number of cDNAs available in the post-genomic era. In the Creator system, an ORF introduced into a donor vector can be transferred with Cre recombinase to a library of acceptor vectors optimized for different applications. Usability of the Creator system is impacted by the ability to easily manipulate DNA, the number of acceptor vectors for downstream applications, and the level of protein expression from Creator vectors. To date, we have developed over 20 novel acceptor vectors that employ a variety of promoters and epitope tags commonly employed for proteomics applications and gene function analysis. We also made several enhancements to the donor vectors including addition of different multiple cloning sites to allow shuttling from pre-existing vectors and introduction of the lacZ alpha reporter gene to allow for selection. Importantly, in order to ameliorate any effects on protein expression of the loxP site between a 5' tag and ORF, we introduced a splicing event into our expression vectors. The message produced from the resulting 'Creator Splice' vector undergoes splicing in mammalian systems to remove the loxP site. Upon analysis of our Creator Splice constructs, we discovered that protein expression levels were also significantly increased. The development of new donor and acceptor vectors has increased versatility during the cloning process and made this system compatible with a wider variety of downstream applications. The modifications introduced in our Creator Splice system were designed to remove extraneous sequences due to recombination but also aided in downstream analysis by increasing protein expression levels. As a result, we can now employ epitope tags that are detected less efficiently and reduce our assay scale to allow for higher throughput. The Creator Splice system appears to be an extremely

Large- and Very-Large-Scale Motions in Katabatic Flows Over Steep Slopes

NASA Astrophysics Data System (ADS)

Giometto, M. G.; Fang, J.; Salesky, S.; Parlange, M. B.

2016-12-01

Evidence of large- and very-large-scale motions populating the boundary layer in katabatic flows over steep slopes is presented via direct numerical simulations (DNSs). DNSs are performed at a modified Reynolds number (Rem = 967), considering four sloping angles (α = 60°, 70°, 80° and 90°). Large coherent structures prove to be strongly dependent on the inclination of the underlying surface. Spectra and co-spectra consistently show signatures of large-scale motions (LSMs), with streamwise extension on the order of the boundary layer thickness. A second low-wavenumber mode characterizes pre-multiplied spectra and co-spectra when the slope angle is below 70°, indicative of very-large-scale motions (VLSMs). In addition, conditional sampling and averaging shows how LSMs and VLSMs are induced by counter-rotating roll modes, in agreement with findings from canonical wall-bounded flows. VLSMs contribute to the stream-wise velocity variance and shear stress in the above-jet regions up to 30% and 45% respectively, whereas both LSMs and VLSMs are inactive in the near-wall regions.

Direct Detection of Alternative Open Reading Frames Translation Products in Human Significantly Expands the Proteome

PubMed Central

Vanderperre, Benoît; Lucier, Jean-François; Bissonnette, Cyntia; Motard, Julie; Tremblay, Guillaume; Vanderperre, Solène; Wisztorski, Maxence; Salzet, Michel; Boisvert, François-Michel; Roucou, Xavier

2013-01-01

A fully mature mRNA is usually associated to a reference open reading frame encoding a single protein. Yet, mature mRNAs contain unconventional alternative open reading frames (AltORFs) located in untranslated regions (UTRs) or overlapping the reference ORFs (RefORFs) in non-canonical +2 and +3 reading frames. Although recent ribosome profiling and footprinting approaches have suggested the significant use of unconventional translation initiation sites in mammals, direct evidence of large-scale alternative protein expression at the proteome level is still lacking. To determine the contribution of alternative proteins to the human proteome, we generated a database of predicted human AltORFs revealing a new proteome mainly composed of small proteins with a median length of 57 amino acids, compared to 344 amino acids for the reference proteome. We experimentally detected a total of 1,259 alternative proteins by mass spectrometry analyses of human cell lines, tissues and fluids. In plasma and serum, alternative proteins represent up to 55% of the proteome and may be a potential unsuspected new source for biomarkers. We observed constitutive co-expression of RefORFs and AltORFs from endogenous genes and from transfected cDNAs, including tumor suppressor p53, and provide evidence that out-of-frame clones representing AltORFs are mistakenly rejected as false positive in cDNAs screening assays. Functional importance of alternative proteins is strongly supported by significant evolutionary conservation in vertebrates, invertebrates, and yeast. Our results imply that coding of multiple proteins in a single gene by the use of AltORFs may be a common feature in eukaryotes, and confirm that translation of unconventional ORFs generates an as yet unexplored proteome. PMID:23950983

EFT of large scale structures in redshift space [On the EFT of large scale structures in redshift space

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

Lewandowski, Matthew; Senatore, Leonardo; Prada, Francisco

Here, we further develop the description of redshift-space distortions within the effective field theory of large scale structures. First, we generalize the counterterms to include the effect of baryonic physics and primordial non-Gaussianity. Second, we evaluate the IR resummation of the dark matter power spectrum in redshift space. This requires us to identify a controlled approximation that makes the numerical evaluation straightforward and efficient. Third, we compare the predictions of the theory at one loop with the power spectrum from numerical simulations up to ℓ = 6. We find that the IR resummation allows us to correctly reproduce the baryonmore » acoustic oscillation peak. The k reach—or, equivalently, the precision for a given k—depends on additional counterterms that need to be matched to simulations. Since the nonlinear scale for the velocity is expected to be longer than the one for the overdensity, we consider a minimal and a nonminimal set of counterterms. The quality of our numerical data makes it hard to firmly establish the performance of the theory at high wave numbers. Within this limitation, we find that the theory at redshift z = 0.56 and up to ℓ = 2 matches the data at the percent level approximately up to k~0.13 hMpc –1 or k~0.18 hMpc –1, depending on the number of counterterms used, with a potentially large improvement over former analytical techniques.« less

EFT of large scale structures in redshift space [On the EFT of large scale structures in redshift space

DOE PAGES

Lewandowski, Matthew; Senatore, Leonardo; Prada, Francisco; ...

2018-03-15

Here, we further develop the description of redshift-space distortions within the effective field theory of large scale structures. First, we generalize the counterterms to include the effect of baryonic physics and primordial non-Gaussianity. Second, we evaluate the IR resummation of the dark matter power spectrum in redshift space. This requires us to identify a controlled approximation that makes the numerical evaluation straightforward and efficient. Third, we compare the predictions of the theory at one loop with the power spectrum from numerical simulations up to ℓ = 6. We find that the IR resummation allows us to correctly reproduce the baryonmore » acoustic oscillation peak. The k reach—or, equivalently, the precision for a given k—depends on additional counterterms that need to be matched to simulations. Since the nonlinear scale for the velocity is expected to be longer than the one for the overdensity, we consider a minimal and a nonminimal set of counterterms. The quality of our numerical data makes it hard to firmly establish the performance of the theory at high wave numbers. Within this limitation, we find that the theory at redshift z = 0.56 and up to ℓ = 2 matches the data at the percent level approximately up to k~0.13 hMpc –1 or k~0.18 hMpc –1, depending on the number of counterterms used, with a potentially large improvement over former analytical techniques.« less

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Generation of large-scale density fluctuations by buoyancy

NASA Technical Reports Server (NTRS)

Chasnov, J. R.; Rogallo, R. S.

1990-01-01

The generation of fluid motion from a state of rest by buoyancy forces acting on a homogeneous isotropic small-scale density field is considered. Nonlinear interactions between the generated fluid motion and the initial isotropic small-scale density field are found to create an anisotropic large-scale density field with spectrum proportional to kappa(exp 4). This large-scale density field is observed to result in an increasing Reynolds number of the fluid turbulence in its final period of decay.

A proteomics performance standard to support measurement quality in proteomics.

PubMed

Beasley-Green, Ashley; Bunk, David; Rudnick, Paul; Kilpatrick, Lisa; Phinney, Karen

2012-04-01

The emergence of MS-based proteomic platforms as a prominent technology utilized in biochemical and biomedical research has increased the need for high-quality MS measurements. To address this need, National Institute of Standards and Technology (NIST) reference material (RM) 8323 yeast protein extract is introduced as a proteomics quality control material for benchmarking the preanalytical and analytical performance of proteomics-based experimental workflows. RM 8323 yeast protein extract is based upon the well-characterized eukaryote Saccharomyces cerevisiae and can be utilized in the design and optimization of proteomics-based methodologies from sample preparation to data analysis. To demonstrate its utility as a proteomics quality control material, we coupled LC-MS/MS measurements of RM 8323 with the NIST MS Quality Control (MSQC) performance metrics to quantitatively assess the LC-MS/MS instrumentation parameters that influence measurement accuracy, repeatability, and reproducibility. Due to the complexity of the yeast proteome, we also demonstrate how NIST RM 8323, along with the NIST MSQC performance metrics, can be used in the evaluation and optimization of proteomics-based sample preparation methods. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards Large-area Field-scale Operational Evapotranspiration for Water Use Mapping

NASA Astrophysics Data System (ADS)

Senay, G. B.; Friedrichs, M.; Morton, C.; Huntington, J. L.; Verdin, J.

2017-12-01

Field-scale evapotranspiration (ET) estimates are needed for improving surface and groundwater use and water budget studies. Ideally, field-scale ET estimates would be at regional to national levels and cover long time periods. As a result of large data storage and computational requirements associated with processing field-scale satellite imagery such as Landsat, numerous challenges remain to develop operational ET estimates over large areas for detailed water use and availability studies. However, the combination of new science, data availability, and cloud computing technology is enabling unprecedented capabilities for ET mapping. To demonstrate this capability, we used Google's Earth Engine cloud computing platform to create nationwide annual ET estimates with 30-meter resolution Landsat ( 16,000 images) and gridded weather data using the Operational Simplified Surface Energy Balance (SSEBop) model in support of the National Water Census, a USGS research program designed to build decision support capacity for water management agencies and other natural resource managers. By leveraging Google's Earth Engine Application Programming Interface (API) and developing software in a collaborative, open-platform environment, we rapidly advance from research towards applications for large-area field-scale ET mapping. Cloud computing of the Landsat image archive combined with other satellite, climate, and weather data, is creating never imagined opportunities for assessing ET model behavior and uncertainty, and ultimately providing the ability for more robust operational monitoring and assessment of water use at field-scales.

An introduction to statistical process control in research proteomics.

PubMed

Bramwell, David

2013-12-16

Statistical process control is a well-established and respected method which provides a general purpose, and consistent framework for monitoring and improving the quality of a process. It is routinely used in many industries where the quality of final products is critical and is often required in clinical diagnostic laboratories [1,2]. To date, the methodology has been little utilised in research proteomics. It has been shown to be capable of delivering quantitative QC procedures for qualitative clinical assays [3] making it an ideal methodology to apply to this area of biological research. To introduce statistical process control as an objective strategy for quality control and show how it could be used to benefit proteomics researchers and enhance the quality of the results they generate. We demonstrate that rules which provide basic quality control are easy to derive and implement and could have a major impact on data quality for many studies. Statistical process control is a powerful tool for investigating and improving proteomics research work-flows. The process of characterising measurement systems and defining control rules forces the exploration of key questions that can lead to significant improvements in performance. This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 The Author. Published by Elsevier

Construction of large scale switch matrix by interconnecting integrated optical switch chips with EDFAs

NASA Astrophysics Data System (ADS)

Liao, Mingle; Wu, Baojian; Hou, Jianhong; Qiu, Kun

2018-03-01

Large scale optical switches are essential components in optical communication network. We aim to build up a large scale optical switch matrix by the interconnection of silicon-based optical switch chips using 3-stage CLOS structure, where EDFAs are needed to compensate for the insertion loss of the chips. The optical signal-to-noise ratio (OSNR) performance of the resulting large scale optical switch matrix is investigated for TE-mode light and the experimental results are in agreement with the theoretical analysis. We build up a 64 ×64 switch matrix by use of 16 ×16 optical switch chips and the OSNR and receiver sensibility can respectively be improved by 0.6 dB and 0.2 dB by optimizing the gain configuration of the EDFAs.

Review of Dynamic Modeling and Simulation of Large Scale Belt Conveyor System

NASA Astrophysics Data System (ADS)

He, Qing; Li, Hong

Belt conveyor is one of the most important devices to transport bulk-solid material for long distance. Dynamic analysis is the key to decide whether the design is rational in technique, safe and reliable in running, feasible in economy. It is very important to study dynamic properties, improve efficiency and productivity, guarantee conveyor safe, reliable and stable running. The dynamic researches and applications of large scale belt conveyor are discussed. The main research topics, the state-of-the-art of dynamic researches on belt conveyor are analyzed. The main future works focus on dynamic analysis, modeling and simulation of main components and whole system, nonlinear modeling, simulation and vibration analysis of large scale conveyor system.

TUBEs-Mass Spectrometry for Identification and Analysis of the Ubiquitin-Proteome.

PubMed

Azkargorta, Mikel; Escobes, Iraide; Elortza, Felix; Matthiesen, Rune; Rodríguez, Manuel S

2016-01-01

Mass spectrometry (MS) has become the method of choice for the large-scale analysis of protein ubiquitylation. There exist a number of proposed methods for mapping ubiquitin sites, each with different pros and cons. We present here a protocol for the MS analysis of the ubiquitin-proteome captured by TUBEs and subsequent data analysis. Using dedicated software and algorithms, specific information on the presence of ubiquitylated peptides can be obtained from the MS search results. In addition, a quantitative and functional analysis of the ubiquitylated proteins and their interacting partners helps to unravel the biological and molecular processes they are involved in.