Sample records for targeted proteomics experiments
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Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.
Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars
2015-07-15
Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.
MacLean, Brendan; Tomazela, Daniela M; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L; Frewen, Barbara; Kern, Randall; Tabb, David L; Liebler, Daniel C; MacCoss, Michael J
2010-04-01
Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.
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Skyline: an open source document editor for creating and analyzing targeted proteomics experiments
MacLean, Brendan; Tomazela, Daniela M.; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L.; Frewen, Barbara; Kern, Randall; Tabb, David L.; Liebler, Daniel C.; MacCoss, Michael J.
2010-01-01
Summary: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Availability: Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project. Contact: brendanx@u.washington.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20147306
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Optimal de novo design of MRM experiments for rapid assay development in targeted proteomics.
Bertsch, Andreas; Jung, Stephan; Zerck, Alexandra; Pfeifer, Nico; Nahnsen, Sven; Henneges, Carsten; Nordheim, Alfred; Kohlbacher, Oliver
2010-05-07
Targeted proteomic approaches such as multiple reaction monitoring (MRM) overcome problems associated with classical shotgun mass spectrometry experiments. Developing MRM quantitation assays can be time consuming, because relevant peptide representatives of the proteins must be found and their retention time and the product ions must be determined. Given the transitions, hundreds to thousands of them can be scheduled into one experiment run. However, it is difficult to select which of the transitions should be included into a measurement. We present a novel algorithm that allows the construction of MRM assays from the sequence of the targeted proteins alone. This enables the rapid development of targeted MRM experiments without large libraries of transitions or peptide spectra. The approach relies on combinatorial optimization in combination with machine learning techniques to predict proteotypicity, retention time, and fragmentation of peptides. The resulting potential transitions are scheduled optimally by solving an integer linear program. We demonstrate that fully automated construction of MRM experiments from protein sequences alone is possible and over 80% coverage of the targeted proteins can be achieved without further optimization of the assay.
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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.
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Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics
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.
2009-01-01
The relatively small numbers of proteins and fewer possible posttranslational modifications in microbes provides a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a Peptide Atlas (PA) for 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 helped highlight 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. PMID:18652504
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Designing Successful Proteomics Experiments.
Ruderman, Daniel
2017-01-01
Because proteomics experiments are so complex they can readily fail, and do so without clear cause. Using standard experimental design techniques and incorporating quality control can greatly increase the chances of success. This chapter introduces the relevant concepts and provides examples specific to proteomic workflows. Applying these notions to design successful proteomics experiments is straightforward. It can help identify failure causes and greatly increase the likelihood of inter-laboratory reproducibility.
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Quantitative proteomics in cardiovascular research: global and targeted strategies
Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun
2014-01-01
Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501
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Searle, Brian C.; Egertson, Jarrett D.; Bollinger, James G.; Stergachis, Andrew B.; MacCoss, Michael J.
2015-01-01
Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40–85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature. PMID:26100116
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Unbiased and targeted mass spectrometry for the HDL proteome.
Singh, Sasha A; Aikawa, Masanori
2017-02-01
Mass spectrometry is an ever evolving technology that is equipped with a variety of tools for protein research. Some lipoprotein studies, especially those pertaining to HDL biology, have been exploiting the versatility of mass spectrometry to understand HDL function through its proteome. Despite the role of mass spectrometry in advancing research as a whole, however, the technology remains obscure to those without hands on experience, but still wishing to understand it. In this review, we walk the reader through the coevolution of common mass spectrometry workflows and HDL research, starting from the basic unbiased mass spectrometry methods used to profile the HDL proteome to the most recent targeted methods that have enabled an unprecedented view of HDL metabolism. Unbiased global proteomics have demonstrated that the HDL proteome is organized into subgroups across the HDL size fractions providing further evidence that HDL functional heterogeneity is in part governed by its varying protein constituents. Parallel reaction monitoring, a novel targeted mass spectrometry method, was used to monitor the metabolism of HDL apolipoproteins in humans and revealed that apolipoproteins contained within the same HDL size fraction exhibit diverse metabolic properties. Mass spectrometry provides a variety of tools and strategies to facilitate understanding, through its proteins, the complex biology of HDL.
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A Targeted MRM Approach for Tempo-Spatial Proteomics Analyses.
Moradian, Annie; Porras-Yakushi, Tanya R; Sweredoski, Michael J; Hess, Sonja
2016-01-01
When deciding to perform a quantitative proteomics analysis, selectivity, sensitivity, and reproducibility are important criteria to consider. The use of multiple reaction monitoring (MRM) has emerged as a powerful proteomics technique in that regard since it avoids many of the problems typically observed in discovery-based analyses. A prerequisite for such a targeted approach is that the protein targets are known, either as a result of previous global proteomics experiments or because a specific hypothesis is to be tested. When guidelines that have been established in the pharmaceutical industry many decades ago are taken into account, setting up an MRM assay is relatively straightforward. Typically, proteotypic peptides with favorable mass spectrometric properties are synthesized with a heavy isotope for each protein that is to be monitored. Retention times and calibration curves are determined using triple-quadrupole mass spectrometers. The use of iRT peptide standards is both recommended and fully integrated into the bioinformatics pipeline. Digested biological samples are mixed with the heavy and iRT standards and quantified. Here we present a generic protocol for the development of an MRM assay.
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Röst, Hannes L; Liu, Yansheng; D'Agostino, Giuseppe; Zanella, Matteo; Navarro, Pedro; Rosenberger, George; Collins, Ben C; Gillet, Ludovic; Testa, Giuseppe; Malmström, Lars; Aebersold, Ruedi
2016-09-01
Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.
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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
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The role of targeted chemical proteomics in pharmacology
Sutton, Chris W
2012-01-01
Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the ‘hidden’ proteome) from complex mixtures of wide dynamic range (the ‘deep’ proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets. PMID:22074351
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Advances in targeted proteomics and applications to biomedical research
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
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Panorama: A Targeted Proteomics Knowledge Base
2015-01-01
Panorama is a web application for storing, sharing, analyzing, and reusing targeted assays created and refined with Skyline,1 an increasingly popular Windows client software tool for targeted proteomics experiments. Panorama allows laboratories to store and organize curated results contained in Skyline documents with fine-grained permissions, which facilitates distributed collaboration and secure sharing of published and unpublished data via a web-browser interface. It is fully integrated with the Skyline workflow and supports publishing a document directly to a Panorama server from the Skyline user interface. Panorama captures the complete Skyline document information content in a relational database schema. Curated results published to Panorama can be aggregated and exported as chromatogram libraries. These libraries can be used in Skyline to pick optimal targets in new experiments and to validate peak identification of target peptides. Panorama is open-source and freely available. It is distributed as part of LabKey Server,2 an open source biomedical research data management system. Laboratories and organizations can set up Panorama locally by downloading and installing the software on their own servers. They can also request freely hosted projects on https://panoramaweb.org, a Panorama server maintained by the Department of Genome Sciences at the University of Washington. PMID:25102069
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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
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Implementation of statistical process control for proteomic experiments via LC MS/MS.
Bereman, Michael S; Johnson, Richard; Bollinger, James; Boss, Yuval; Shulman, Nick; MacLean, Brendan; Hoofnagle, Andrew N; MacCoss, Michael J
2014-04-01
Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.
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TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics
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
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Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer
Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas
2016-01-01
Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604
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Mohammed, Yassene; Domański, Dominik; Jackson, Angela M; Smith, Derek S; Deelder, André M; Palmblad, Magnus; Borchers, Christoph H
2014-06-25
One challenge in Multiple Reaction Monitoring (MRM)-based proteomics is to select the most appropriate surrogate peptides to represent a target protein. We present here a software package to automatically generate these most appropriate surrogate peptides for an LC/MRM-MS analysis. Our method integrates information about the proteins, their tryptic peptides, and the suitability of these peptides for MRM which is available online in UniProtKB, NCBI's dbSNP, ExPASy, PeptideAtlas, PRIDE, and GPMDB. The scoring algorithm reflects our knowledge in choosing the best candidate peptides for MRM, based on the uniqueness of the peptide in the targeted proteome, its physiochemical properties, and whether it previously has been observed. The modularity of the workflow allows further extension and additional selection criteria to be incorporated. We have developed a simple Web interface where the researcher provides the protein accession number, the subject organism, and peptide-specific options. Currently, the software is designed for human and mouse proteomes, but additional species can be easily be added. Our software improved the peptide selection by eliminating human error, considering multiple data sources and all of the isoforms of the protein, and resulted in faster peptide selection - approximately 50 proteins per hour compared to 8 per day. Compiling a list of optimal surrogate peptides for target proteins to be analyzed by LC/MRM-MS has been a cumbersome process, in which expert researchers retrieved information from different online repositories and used their own reasoning to find the most appropriate peptides. Our scientific workflow automates this process by integrating information from different data sources including UniProt, Global Proteome Machine, NCBI's dbSNP, and PeptideAtlas, simulating the researchers' reasoning, and incorporating their knowledge of how to select the best proteotypic peptides for an MRM analysis. The developed software can help to
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Expediting SRM assay development for large-scale targeted proteomics experiments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Chaochao; Shi, Tujin; Brown, Joseph N.
2014-08-22
Due to their high sensitivity and specificity, targeted proteomics measurements, e.g. selected reaction monitoring (SRM), are becoming increasingly popular for biological and translational applications. Selection of optimal transitions and optimization of collision energy (CE) are important assay development steps for achieving sensitive detection and accurate quantification; however, these steps can be labor-intensive, especially for large-scale applications. Herein, we explored several options for accelerating SRM assay development evaluated in the context of a relatively large set of 215 synthetic peptide targets. We first showed that HCD fragmentation is very similar to CID in triple quadrupole (QQQ) instrumentation, and by selection ofmore » top six y fragment ions from HCD spectra, >86% of top transitions optimized from direct infusion on QQQ instrument are covered. We also demonstrated that the CE calculated by existing prediction tools was less accurate for +3 precursors, and a significant increase in intensity for transitions could be obtained using a new CE prediction equation constructed from the present experimental data. Overall, our study illustrates the feasibility of expediting the development of larger numbers of high-sensitivity SRM assays through automation of transitions selection and accurate prediction of optimal CE to improve both SRM throughput and measurement quality.« less
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Chemical proteomics approaches for identifying the cellular targets of natural products
Sieber, S. A.
2016-01-01
Covering: 2010 up to 2016 Deconvoluting the mode of action of natural products and drugs remains one of the biggest challenges in chemistry and biology today. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to understand protein function. In the context of natural products, chemical proteomics can be used to identify the protein binding partners or targets of small molecules in live cells. Here, we highlight recent examples of chemical probes based on natural products and their application for target identification. The review focuses on probes that can be covalently linked to their target proteins (either via intrinsic chemical reactivity or via the introduction of photocrosslinkers), and can be applied “in situ” – in living systems rather than cell lysates. We also focus here on strategies that employ a click reaction, the copper-catalysed azide–alkyne cycloaddition reaction (CuAAC), to allow minimal functionalisation of natural product scaffolds with an alkyne or azide tag. We also discuss ‘competitive mode’ approaches that screen for natural products that compete with a well-characterised chemical probe for binding to a particular set of protein targets. Fuelled by advances in mass spectrometry instrumentation and bioinformatics, many modern strategies are now embracing quantitative proteomics to help define the true interacting partners of probes, and we highlight the opportunities this rapidly evolving technology provides in chemical proteomics. Finally, some of the limitations and challenges of chemical proteomics approaches are discussed. PMID:27098809
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Chemical proteomics approaches for identifying the cellular targets of natural products.
Wright, M H; Sieber, S A
2016-05-04
Covering: 2010 up to 2016Deconvoluting the mode of action of natural products and drugs remains one of the biggest challenges in chemistry and biology today. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to understand protein function. In the context of natural products, chemical proteomics can be used to identify the protein binding partners or targets of small molecules in live cells. Here, we highlight recent examples of chemical probes based on natural products and their application for target identification. The review focuses on probes that can be covalently linked to their target proteins (either via intrinsic chemical reactivity or via the introduction of photocrosslinkers), and can be applied "in situ" - in living systems rather than cell lysates. We also focus here on strategies that employ a click reaction, the copper-catalysed azide-alkyne cycloaddition reaction (CuAAC), to allow minimal functionalisation of natural product scaffolds with an alkyne or azide tag. We also discuss 'competitive mode' approaches that screen for natural products that compete with a well-characterised chemical probe for binding to a particular set of protein targets. Fuelled by advances in mass spectrometry instrumentation and bioinformatics, many modern strategies are now embracing quantitative proteomics to help define the true interacting partners of probes, and we highlight the opportunities this rapidly evolving technology provides in chemical proteomics. Finally, some of the limitations and challenges of chemical proteomics approaches are discussed.
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Welker, F
2018-02-20
The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized
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Ohtsuki, Sumio; Hirayama, Mio; Ito, Shingo; Uchida, Yasuo; Tachikawa, Masanori; Terasaki, Tetsuya
2014-06-01
The blood-brain barrier (BBB) is formed by brain capillary endothelial cells linked together via complex tight junctions, and serves to prevent entry of drugs into the brain. Multiple transporters are expressed at the BBB, where they control exchange of materials between the circulating blood and brain interstitial fluid, thereby supporting and protecting the CNS. An understanding of the BBB is necessary for efficient development of CNS-acting drugs and to identify potential drug targets for treatment of CNS diseases. Quantitative targeted proteomics can provide detailed information on protein expression levels at the BBB. The present review highlights the latest applications of quantitative targeted proteomics in BBB research, specifically to evaluate species and in vivo-in vitro differences, and to reconstruct in vivo transport activity. Such a BBB quantitative proteomics approach can be considered as pharmacoproteomics.
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Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua
2016-01-01
Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.
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Highly multiplexed targeted proteomics using precise control of peptide retention time.
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.
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The journal Molecular & Cellular Proteomics (MCP), in collaboration with the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), part of the National Institutes of Health, announce new guidelines and requirements for papers describing the development and application of targeted mass spectrometry measurements of peptides, modified peptides and proteins (Mol Cell Proteomics 2017; PMID: 28183812). NCI’s participation is part of NIH’s overall effort to address the r
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Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches
2010-07-01
1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...June 2010 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic 5a. CONTRACT NUMBER...1-0430; W81XWH-08-1-0431; Grant sponsor: NIH/NCRR COBRE Grant; Grant number: 1P20RR020171; Grant sponsor: NIH/NIDDK Grant; Grant number: R01DK053525
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Chamrád, Ivo; Rix, Uwe; Stukalov, Alexey; Gridling, Manuela; Parapatics, Katja; Müller, André C.; Altiok, Soner; Colinge, Jacques; Superti-Furga, Giulio; Haura, Eric B.; Bennett, Keiryn L.
2014-01-01
While targeted therapy based on the idea of attenuating the activity of a preselected, therapeutically relevant protein has become one of the major trends in modern cancer therapy, no truly specific targeted drug has been developed and most clinical agents have displayed a degree of polypharmacology. Therefore, the specificity of anticancer therapeutics has emerged as a highly important but severely underestimated issue. Chemical proteomics is a powerful technique combining postgenomic drug-affinity chromatography with high-end mass spectrometry analysis and bioinformatic data processing to assemble a target profile of a desired therapeutic molecule. Due to high demands on the starting material, however, chemical proteomic studies have been mostly limited to cancer cell lines. Herein, we report a down-scaling of the technique to enable the analysis of very low abundance samples, as those obtained from needle biopsies. By a systematic investigation of several important parameters in pull-downs with the multikinase inhibitor bosutinib, the standard experimental protocol was optimized to 100 µg protein input. At this level, more than 30 well-known targets were detected per single pull-down replicate with high reproducibility. Moreover, as presented by the comprehensive target profile obtained from miniaturized pull-downs with another clinical drug, dasatinib, the optimized protocol seems to be extendable to other drugs of interest. Sixty distinct human and murine targets were finally identified for bosutinib and dasatinib in chemical proteomic experiments utilizing core needle biopsy samples from xenotransplants derived from patient tumor tissue. Altogether, the developed methodology proves robust and generic and holds many promises for the field of personalized health care. PMID:23901793
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CPTAC Assay Portal: a repository of targeted proteomic assays
DOE Office of Scientific and Technical Information (OSTI.GOV)
Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.
2014-06-27
To address these issues, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as a public repository of well-characterized quantitative, MS-based, targeted proteomic assays. The purpose of the CPTAC Assay Portal is to facilitate widespread adoption of targeted MS assays by disseminating SOPs, reagents, and assay characterization data for highly characterized assays. A primary aim of the NCI-supported portal is to bring together clinicians or biologists and analytical chemists to answer hypothesis-driven questions using targeted, MS-based assays. Assay content is easily accessed through queries and filters, enabling investigatorsmore » to find assays to proteins relevant to their areas of interest. Detailed characterization data are available for each assay, enabling researchers to evaluate assay performance prior to launching the assay in their own laboratory.« less
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Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...
2017-07-19
Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less
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Comparative Analysis of Predicted Plastid-Targeted Proteomes of Sequenced Higher Plant Genomes
Schaeffer, Scott; Harper, Artemus; Raja, Rajani; Jaiswal, Pankaj; Dhingra, Amit
2014-01-01
Plastids are actively involved in numerous plant processes critical to growth, development and adaptation. They play a primary role in photosynthesis, pigment and monoterpene synthesis, gravity sensing, starch and fatty acid synthesis, as well as oil, and protein storage. We applied two complementary methods to analyze the recently published apple genome (Malus × domestica) to identify putative plastid-targeted proteins, the first using TargetP and the second using a custom workflow utilizing a set of predictive programs. Apple shares roughly 40% of its 10,492 putative plastid-targeted proteins with that of the Arabidopsis (Arabidopsis thaliana) plastid-targeted proteome as identified by the Chloroplast 2010 project and ∼57% of its entire proteome with Arabidopsis. This suggests that the plastid-targeted proteomes between apple and Arabidopsis are different, and interestingly alludes to the presence of differential targeting of homologs between the two species. Co-expression analysis of 2,224 genes encoding putative plastid-targeted apple proteins suggests that they play a role in plant developmental and intermediary metabolism. Further, an inter-specific comparison of Arabidopsis, Prunus persica (Peach), Malus × domestica (Apple), Populus trichocarpa (Black cottonwood), Fragaria vesca (Woodland Strawberry), Solanum lycopersicum (Tomato) and Vitis vinifera (Grapevine) also identified a large number of novel species-specific plastid-targeted proteins. This analysis also revealed the presence of alternatively targeted homologs across species. Two separate analyses revealed that a small subset of proteins, one representing 289 protein clusters and the other 737 unique protein sequences, are conserved between seven plastid-targeted angiosperm proteomes. Majority of the novel proteins were annotated to play roles in stress response, transport, catabolic processes, and cellular component organization. Our results suggest that the current state of knowledge regarding
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Supramolecular Affinity Chromatography for Methylation-Targeted Proteomics.
Garnett, Graham A E; Starke, Melissa J; Shaurya, Alok; Li, Janessa; Hof, Fraser
2016-04-05
Proteome-wide studies of post-translationally methylated species using mass spectrometry are complicated by high sample diversity, competition for ionization among peptides, and mass redundancies. Antibody-based enrichment has powered methylation proteomics until now, but the reliability, pan-specificity, polyclonal nature, and stability of the available pan-specific antibodies are problematic and do not provide a standard, reliable platform for investigators. We have invented an anionic supramolecular host that can form host-guest complexes selectively with methyllysine-containing peptides and used it to create a methylysine-affinity column. The column resolves peptides on the basis of methylation-a feat impossible with a comparable commercial cation-exchange column. A proteolyzed nuclear extract was separated on the methyl-affinity column prior to standard proteomics analysis. This experiment demonstrates that such chemical methyl-affinity columns are capable of enriching and improving the analysis of methyllysine residues from complex protein mixtures. We discuss the importance of this advance in the context of biomolecule-driven enrichment methods.
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Guidelines for reporting quantitative mass spectrometry based experiments in proteomics.
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
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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.
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Chemical Proteomic Approaches Targeting Cancer Stem Cells: A Review of Current Literature.
Jung, Hye Jin
2017-01-01
Cancer stem cells (CSCs) have been proposed as central drivers of tumor initiation, progression, recurrence, and therapeutic resistance. Therefore, identifying stem-like cells within cancers and understanding their properties is crucial for the development of effective anticancer therapies. Recently, chemical proteomics has become a powerful tool to efficiently determine protein networks responsible for CSC pathophysiology and comprehensively elucidate molecular mechanisms of drug action against CSCs. This review provides an overview of major methodologies utilized in chemical proteomic approaches. In addition, recent successful chemical proteomic applications targeting CSCs are highlighted. Future direction of potential CSC research by integrating chemical genomic and proteomic data obtained from a single biological sample of CSCs are also suggested in this review. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
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Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.; Monroe, Matthew E.; Orton, Daniel J.; Ibrahim, Yehia M.; Gritsenko, Marina A.; Clauss, Therese R. W.; Shukla, Anil K.; Moore, Ronald J.; Purvine, Samuel O.; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S.; Smith, Richard D.
2016-01-01
Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. PMID:27670688
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Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.
Dittrich, Julia; Ceglarek, Uta
2017-01-01
The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.
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Designing biomedical proteomics experiments: state-of-the-art and future perspectives.
Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk
2016-05-01
With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.
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Burnum-Johnson, Kristin E; Nie, Song; Casey, Cameron P; Monroe, Matthew E; Orton, Daniel J; Ibrahim, Yehia M; Gritsenko, Marina A; Clauss, Therese R W; Shukla, Anil K; Moore, Ronald J; Purvine, Samuel O; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S; Smith, Richard D
2016-12-01
Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
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Role of the visual experience-dependent nascent proteome in neuronal plasticity
Liu, Han-Hsuan; McClatchy, Daniel B; Schiapparelli, Lucio; Shen, Wanhua; Yates, John R
2018-01-01
Experience-dependent synaptic plasticity refines brain circuits during development. To identify novel protein synthesis-dependent mechanisms contributing to experience-dependent plasticity, we conducted a quantitative proteomic screen of the nascent proteome in response to visual experience in Xenopus optic tectum using bio-orthogonal metabolic labeling (BONCAT). We identified 83 differentially synthesized candidate plasticity proteins (CPPs). The CPPs form strongly interconnected networks and are annotated to a variety of biological functions, including RNA splicing, protein translation, and chromatin remodeling. Functional analysis of select CPPs revealed the requirement for eukaryotic initiation factor three subunit A (eIF3A), fused in sarcoma (FUS), and ribosomal protein s17 (RPS17) in experience-dependent structural plasticity in tectal neurons and behavioral plasticity in tadpoles. These results demonstrate that the nascent proteome is dynamic in response to visual experience and that de novo synthesis of machinery that regulates RNA splicing and protein translation is required for experience-dependent plasticity. PMID:29412139
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Identification of lactoferricin B intracellular targets using an Escherichia coli proteome chip.
Tu, Yu-Hsuan; Ho, Yu-Hsuan; Chuang, Ying-Chih; Chen, Po-Chung; Chen, Chien-Sheng
2011-01-01
Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach.
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Identification of Lactoferricin B Intracellular Targets Using an Escherichia coli Proteome Chip
Chen, Po-Chung; Chen, Chien-Sheng
2011-01-01
Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach. PMID:22164243
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.
Current proteomics approaches are comprised of both broad discovery measurements as well as more quantitative targeted measurements. These two different measurement types are used to initially identify potentially important proteins (e.g., candidate biomarkers) and then enable improved quantification for a limited number of selected proteins. However, both approaches suffer from limitations, particularly the lower sensitivity, accuracy, and quantitation precision for discovery approaches compared to targeted approaches, and the limited proteome coverage provided by targeted approaches. Herein, we describe a new proteomics approach that allows both discovery and targeted monitoring (DTM) in a single analysis using liquid chromatography, ion mobility spectrometrymore » and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled peptides for target ions are spiked into tryptic digests and both the labeled and unlabeled peptides are broadly detected using LC-IMS-MS instrumentation, allowing the benefits of discovery and targeted approaches. To understand the possible improvement of the DTM approach, it was compared to LC-MS broad measurements using an accurate mass and time tag database and selected reaction monitoring (SRM) targeted measurements. The DTM results yielded greater peptide/protein coverage and a significant improvement in the detection of lower abundance species compared to LC-MS discovery measurements. DTM was also observed to have similar detection limits as SRM for the targeted measurements indicating its potential for combining the discovery and targeted approaches.« less
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Affordable proteomics: the two-hybrid systems.
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.
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Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer*
Gallien, Sebastien; Duriez, Elodie; Crone, Catharina; Kellmann, Markus; Moehring, Thomas; Domon, Bruno
2012-01-01
There is an immediate need for improved methods to systematically and precisely quantify large sets of peptides in complex biological samples. To date protein quantification in biological samples has been routinely performed on triple quadrupole instruments operated in selected reaction monitoring mode (SRM), and two major challenges remain. Firstly, the number of peptides to be included in one survey experiment needs to be increased to routinely reach several hundreds, and secondly, the degree of selectivity should be improved so as to reliably discriminate the targeted analytes from background interferences. High resolution and accurate mass (HR/AM) analysis on the recently developed Q-Exactive mass spectrometer can potentially address these issues. This instrument presents a unique configuration: it is constituted of an orbitrap mass analyzer equipped with a quadrupole mass filter as the front-end for precursor ion mass selection. This configuration enables new quantitative methods based on HR/AM measurements, including targeted analysis in MS mode (single ion monitoring) and in MS/MS mode (parallel reaction monitoring). The ability of the quadrupole to select a restricted m/z range allows one to overcome the dynamic range limitations associated with trapping devices, and the MS/MS mode provides an additional stage of selectivity. When applied to targeted protein quantification in urine samples and benchmarked with the reference SRM technique, the quadrupole-orbitrap instrument exhibits similar or better performance in terms of selectivity, dynamic range, and sensitivity. This high performance is further enhanced by leveraging the multiplexing capability of the instrument to design novel acquisition methods and apply them to large targeted proteomic studies for the first time, as demonstrated on 770 tryptic yeast peptides analyzed in one 60-min experiment. The increased quality of quadrupole-orbitrap data has the potential to improve existing protein
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Proteome-wide survey of the autoimmune target repertoire in autoimmune polyendocrine syndrome type 1
Landegren, Nils; Sharon, Donald; Freyhult, Eva; Hallgren, Åsa; Eriksson, Daniel; Edqvist, Per-Henrik; Bensing, Sophie; Wahlberg, Jeanette; Nelson, Lawrence M.; Gustafsson, Jan; Husebye, Eystein S.; Anderson, Mark S.; Snyder, Michael; Kämpe, Olle
2016-01-01
Autoimmune polyendocrine syndrome type 1 (APS1) is a monogenic disorder that features multiple autoimmune disease manifestations. It is caused by mutations in the Autoimmune regulator (AIRE) gene, which promote thymic display of thousands of peripheral tissue antigens in a process critical for establishing central immune tolerance. We here used proteome arrays to perform a comprehensive study of autoimmune targets in APS1. Interrogation of established autoantigens revealed highly reliable detection of autoantibodies, and by exploring the full panel of more than 9000 proteins we further identified MAGEB2 and PDILT as novel major autoantigens in APS1. Our proteome-wide assessment revealed a marked enrichment for tissue-specific immune targets, mirroring AIRE’s selectiveness for this category of genes. Our findings also suggest that only a very limited portion of the proteome becomes targeted by the immune system in APS1, which contrasts the broad defect of thymic presentation associated with AIRE-deficiency and raises novel questions what other factors are needed for break of tolerance. PMID:26830021
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Statistical issues in the design and planning of proteomic profiling experiments.
Cairns, David A
2015-01-01
The statistical design of a clinical proteomics experiment is a critical part of well-undertaken investigation. Standard concepts from experimental design such as randomization, replication and blocking should be applied in all experiments, and this is possible when the experimental conditions are well understood by the investigator. The large number of proteins simultaneously considered in proteomic discovery experiments means that determining the number of required replicates to perform a powerful experiment is more complicated than in simple experiments. However, by using information about the nature of an experiment and making simple assumptions this is achievable for a variety of experiments useful for biomarker discovery and initial validation.
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Lam, Maggie P Y; Venkatraman, Vidya; Xing, Yi; Lau, Edward; Cao, Quan; Ng, Dominic C M; Su, Andrew I; Ge, Junbo; Van Eyk, Jennifer E; Ping, Peipei
2016-11-04
Amidst the proteomes of human tissues lie subsets of proteins that are closely involved in conserved pathophysiological processes. Much of biomedical research concerns interrogating disease signature proteins and defining their roles in disease mechanisms. With advances in proteomics technologies, it is now feasible to develop targeted proteomics assays that can accurately quantify protein abundance as well as their post-translational modifications; however, with rapidly accumulating number of studies implicating proteins in diseases, current resources are insufficient to target every protein without judiciously prioritizing the proteins with high significance and impact for assay development. We describe here a data science method to prioritize and expedite assay development on high-impact proteins across research fields by leveraging the biomedical literature record to rank and normalize proteins that are popularly and preferentially published by biomedical researchers. We demonstrate this method by finding priority proteins across six major physiological systems (cardiovascular, cerebral, hepatic, renal, pulmonary, and intestinal). The described method is data-driven and builds upon the collective knowledge of previous publications referenced on PubMed to lend objectivity to target selection. The method and resulting popular protein lists may also be useful for exploring biological processes associated with various physiological systems and research topics, in addition to benefiting ongoing efforts to facilitate the broad translation of proteomics technologies.
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How may targeted proteomics complement genomic data in breast cancer?
Guerin, Mathilde; Gonçalves, Anthony; Toiron, Yves; Baudelet, Emilie; Audebert, Stéphane; Boyer, Jean-Baptiste; Borg, Jean-Paul; Camoin, Luc
2017-01-01
Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.
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Boja, Emily S; Rodriguez, Henry
2012-04-01
Traditional shotgun proteomics used to detect a mixture of hundreds to thousands of proteins through mass spectrometric analysis, has been the standard approach in research to profile protein content in a biological sample which could lead to the discovery of new (and all) protein candidates with diagnostic, prognostic, and therapeutic values. In practice, this approach requires significant resources and time, and does not necessarily represent the goal of the researcher who would rather study a subset of such discovered proteins (including their variations or posttranslational modifications) under different biological conditions. In this context, targeted proteomics is playing an increasingly important role in the accurate measurement of protein targets in biological samples in the hope of elucidating the molecular mechanism of cellular function via the understanding of intricate protein networks and pathways. One such (targeted) approach, selected reaction monitoring (or multiple reaction monitoring) mass spectrometry (MRM-MS), offers the capability of measuring multiple proteins with higher sensitivity and throughput than shotgun proteomics. Developing and validating MRM-MS-based assays, however, is an extensive and iterative process, requiring a coordinated and collaborative effort by the scientific community through the sharing of publicly accessible data and datasets, bioinformatic tools, standard operating procedures, and well characterized reagents. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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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
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Pacific Northwest National Laboratory (PNNL) investigators in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), announces the public release of 98 targeted mass spectrometry-based assays for ovarian cancer research studies. Chosen based on proteogenomic observations from the recently published multi-institutional collaborative project between PNNL and Johns Hopkins University that comprehensively examined the collections of proteins in the tumors of ovarian cancer patients (highlighted in a paper in
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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
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Kusebauch, Ulrike; Deutsch, Eric W.; Campbell, David S.; Sun, Zhi; Farrah, Terry; Moritz, Robert L.
2014-01-01
PeptideAtlas, SRMAtlas and PASSEL are web-accessible resources to support discovery and targeted proteomics research. PeptideAtlas is a multi-species compendium of shotgun proteomic data provided by the scientific community, SRMAtlas is a resource of high-quality, complete proteome SRM assays generated in a consistent manner for the targeted identification and quantification of proteins, and PASSEL is a repository that compiles and represents selected reaction monitoring data, all in an easy to use interface. The databases are generated from native mass spectrometry data files that are analyzed in a standardized manner including statistical validation of the results. Each resource offers search functionalities and can be queried by user defined constraints; the query results are provided in tables or are graphically displayed. PeptideAtlas, SRMAtlas and PASSEL are publicly available freely via the website http://www.peptideatlas.org. In this protocol, we describe the use of these resources, we highlight how to submit, search, collate and download data. PMID:24939129
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Triboulet, Sarah; Aude-Garcia, Catherine; Armand, Lucie; Gerdil, Adèle; Diemer, Hélène; Proamer, Fabienne; Collin-Faure, Véronique; Habert, Aurélie; Strub, Jean-Marc; Hanau, Daniel; Herlin, Nathalie; Carrière, Marie; Van Dorsselaer, Alain; Rabilloud, Thierry
2014-06-07
Two different zinc oxide nanoparticles, as well as zinc ions, are used to study the cellular responses of the RAW 264 macrophage cell line. A proteomic screen is used to provide a wide view of the molecular effects of zinc, and the most prominent results are cross-validated by targeted studies. Furthermore, the alteration of important macrophage functions (e.g. phagocytosis) by zinc is also investigated. The intracellular dissolution/uptake of zinc is also studied to further characterize zinc toxicity. Zinc oxide nanoparticles dissolve readily in the cells, leading to high intracellular zinc concentrations, mostly as protein-bound zinc. The proteomic screen reveals a rather weak response in the oxidative stress response pathway, but a strong response both in the central metabolism and in the proteasomal protein degradation pathway. Targeted experiments confirm that carbohydrate catabolism and proteasome are critical determinants of sensitivity to zinc, which also induces DNA damage. Conversely, glutathione levels and phagocytosis appear unaffected at moderately toxic zinc concentrations.
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Development of a Targeted Urine Proteome Assay for kidney diseases.
Cantley, Lloyd G; Colangelo, Christopher M; Stone, Kathryn L; Chung, Lisa; Belcher, Justin; Abbott, Thomas; Cantley, Jennifer L; Williams, Kenneth R; Parikh, Chirag R
2016-01-01
Since human urine is the most readily available biofluid whose proteome changes in response to disease, it is a logical sample for identifying protein biomarkers for kidney diseases. Potential biomarkers were identified by using a multiproteomics workflow to compare urine proteomes of kidney transplant patients with immediate and delayed graft function. Differentially expressed proteins were identified, and corresponding stable isotope labeled internal peptide standards were synthesized for scheduled MRM. The Targeted Urine Proteome Assay (TUPA) was then developed by identifying those peptides for which there were at least two transitions for which interference in a urine matrix across 156 MRM runs was <30%. This resulted in an assay that monitors 224 peptides from 167 quantifiable proteins. TUPA opens the way for using a robust mass spectrometric technology, MRM, for quantifying and validating biomarkers from among 167 urinary proteins. This approach, while developed using differentially expressed urinary proteins from patients with delayed versus immediate graft function after kidney transplant, can be expanded to include differentially expressed urinary proteins in multiple kidney diseases. Thus, TUPA could provide a single assay to help diagnose, prognose, and manage many kidney diseases. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Screening Novel Molecular Targets of Metformin in Breast Cancer by Proteomic Approach
Al-Zaidan, Lobna; El Ruz, Rasha Abu; Malki, Ahmed M.
2017-01-01
increase the understanding of breast cancer prognosis and permit future studies to examine the effect of metformin on the proteomic pathways against other types of cancers. Finally, it suggests the possibility to develop further therapeutic generations of metformin with increased anticancer effect through targeting specific proteomes. PMID:29085821
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.
2016-02-12
The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative tomore » other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and post-translational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.« less
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Whiteaker, Jeffrey R; Halusa, Goran N; Hoofnagle, Andrew N; Sharma, Vagisha; MacLean, Brendan; Yan, Ping; Wrobel, John A; Kennedy, Jacob; Mani, D R; Zimmerman, Lisa J; Meyer, Matthew R; Mesri, Mehdi; Boja, Emily; Carr, Steven A; Chan, Daniel W; Chen, Xian; Chen, Jing; Davies, Sherri R; Ellis, Matthew J C; Fenyö, David; Hiltke, Tara; Ketchum, Karen A; Kinsinger, Chris; Kuhn, Eric; Liebler, Daniel C; Liu, Tao; Loss, Michael; MacCoss, Michael J; Qian, Wei-Jun; Rivers, Robert; Rodland, Karin D; Ruggles, Kelly V; Scott, Mitchell G; Smith, Richard D; Thomas, Stefani; Townsend, R Reid; Whiteley, Gordon; Wu, Chaochao; Zhang, Hui; Zhang, Zhen; Rodriguez, Henry; Paulovich, Amanda G
2016-01-01
The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.
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Abegg, Daniel; Frei, Reto; Cerato, Luca; Prasad Hari, Durga; Wang, Chao; Waser, Jerome; Adibekian, Alexander
2015-09-07
In this study, we present a highly efficient method for proteomic profiling of cysteine residues in complex proteomes and in living cells. Our method is based on alkynylation of cysteines in complex proteomes using a "clickable" alkynyl benziodoxolone bearing an azide group. This reaction proceeds fast, under mild physiological conditions, and with a very high degree of chemoselectivity. The formed azide-capped alkynyl-cysteine adducts are readily detectable by LC-MS/MS, and can be further functionalized with TAMRA or biotin alkyne via CuAAC. We demonstrate the utility of alkynyl benziodoxolones for chemical proteomics applications by identifying the proteomic targets of curcumin, a diarylheptanoid natural product that was and still is part of multiple human clinical trials as anticancer agent. Our results demonstrate that curcumin covalently modifies several key players of cellular signaling and metabolism, most notably the enzyme casein kinase I gamma. We anticipate that this new method for cysteine profiling will find broad application in chemical proteomics and drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Statistical design of quantitative mass spectrometry-based proteomic experiments.
Oberg, Ann L; Vitek, Olga
2009-05-01
We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.
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Matrix metalloproteinase proteomics: substrates, targets, and therapy.
Morrison, Charlotte J; Butler, Georgina S; Rodríguez, David; Overall, Christopher M
2009-10-01
Proteomics encompasses powerful techniques termed 'degradomics' for unbiased high-throughput protease substrate discovery screens that have been applied to an important family of extracellular proteases, the matrix metalloproteinases (MMPs). Together with the data generated from genetic deletion and transgenic mouse models and genomic profiling, these screens can uncover the diverse range of MMP functions, reveal which MMPs and MMP-mediated pathways exacerbate pathology, and which are involved in protection and the resolution of disease. This information can be used to identify and validate candidate drug targets and antitargets, and is critical for the development of new inhibitors of MMP function. Such inhibitors may target either the MMP directly in a specific manner or pathways upstream and downstream of MMP activity that are mediating deleterious effects in disease. Since MMPs do not operate alone but are part of the 'protease web', it is necessary to use system-wide approaches to understand MMP proteolysis in vivo, to discover new biological roles and their potential for therapeutic modification.
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Application of targeted proteomics to metabolically engineered Escherichia coli.
Singh, Pragya; Batth, Tanveer S; Juminaga, Darmawi; Dahl, Robert H; Keasling, Jay D; Adams, Paul D; Petzold, Christopher J
2012-04-01
As synthetic biology matures to compete with chemical transformation of commodity and high-value compounds, a wide variety of well-characterized biological parts are needed to facilitate system design. Protein quantification based on selected-reaction monitoring (SRM) mass spectrometry compliments metabolite and transcript analysis for system characterization and optimizing flux through engineered pathways. By using SRM quantification, we assayed red fluorescent protein (RFP) expressed from plasmids containing several inducible and constitutive promoters and subsequently assessed protein production from the same promoters driving expression of eight mevalonate pathway proteins in Escherichia coli. For each of the promoter systems, the protein level for the first gene in the operon followed that of RFP, however, the levels of proteins produced from genes farther from the promoter were much less consistent. Second, we used targeted proteomics to characterize tyrosine biosynthesis pathway proteins after removal of native regulation. The changes were not expected to cause significant impact on protein levels, yet significant variation in protein abundance was observed and tyrosine production for these strains spanned a range from less than 1 mg/L to greater than 250 mg/L. Overall, our results underscore the importance of targeted proteomics for determining accurate protein levels in engineered systems and fine-tuning metabolic pathways. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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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.
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Andreev, Victor P; Gillespie, Brenda W; Helfand, Brian T; Merion, Robert M
2016-01-01
Unsupervised classification methods are gaining acceptance in omics studies of complex common diseases, which are often vaguely defined and are likely the collections of disease subtypes. Unsupervised classification based on the molecular signatures identified in omics studies have the potential to reflect molecular mechanisms of the subtypes of the disease and to lead to more targeted and successful interventions for the identified subtypes. Multiple classification algorithms exist but none is ideal for all types of data. Importantly, there are no established methods to estimate sample size in unsupervised classification (unlike power analysis in hypothesis testing). Therefore, we developed a simulation approach allowing comparison of misclassification errors and estimating the required sample size for a given effect size, number, and correlation matrix of the differentially abundant proteins in targeted proteomics studies. All the experiments were performed in silico. The simulated data imitated the expected one from the study of the plasma of patients with lower urinary tract dysfunction with the aptamer proteomics assay Somascan (SomaLogic Inc, Boulder, CO), which targeted 1129 proteins, including 330 involved in inflammation, 180 in stress response, 80 in aging, etc. Three popular clustering methods (hierarchical, k-means, and k-medoids) were compared. K-means clustering performed much better for the simulated data than the other two methods and enabled classification with misclassification error below 5% in the simulated cohort of 100 patients based on the molecular signatures of 40 differentially abundant proteins (effect size 1.5) from among the 1129-protein panel. PMID:27524871
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Mohammed, Yassene; Percy, Andrew J; Chambers, Andrew G; Borchers, Christoph H
2015-02-06
Multiplexed targeted quantitative proteomics typically utilizes multiple reaction monitoring and allows the optimized quantification of a large number of proteins. One challenge, however, is the large amount of data that needs to be reviewed, analyzed, and interpreted. Different vendors provide software for their instruments, which determine the recorded responses of the heavy and endogenous peptides and perform the response-curve integration. Bringing multiplexed data together and generating standard curves is often an off-line step accomplished, for example, with spreadsheet software. This can be laborious, as it requires determining the concentration levels that meet the required accuracy and precision criteria in an iterative process. We present here a computer program, Qualis-SIS, that generates standard curves from multiplexed MRM experiments and determines analyte concentrations in biological samples. Multiple level-removal algorithms and acceptance criteria for concentration levels are implemented. When used to apply the standard curve to new samples, the software flags each measurement according to its quality. From the user's perspective, the data processing is instantaneous due to the reactivity paradigm used, and the user can download the results of the stepwise calculations for further processing, if necessary. This allows for more consistent data analysis and can dramatically accelerate the downstream data analysis.
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Interaction Analysis through Proteomic Phage Display
2014-01-01
Phage display is a powerful technique for profiling specificities of peptide binding domains. The method is suited for the identification of high-affinity ligands with inhibitor potential when using highly diverse combinatorial peptide phage libraries. Such experiments further provide consensus motifs for genome-wide scanning of ligands of potential biological relevance. A complementary but considerably less explored approach is to display expression products of genomic DNA, cDNA, open reading frames (ORFs), or oligonucleotide libraries designed to encode defined regions of a target proteome on phage particles. One of the main applications of such proteomic libraries has been the elucidation of antibody epitopes. This review is focused on the use of proteomic phage display to uncover protein-protein interactions of potential relevance for cellular function. The method is particularly suited for the discovery of interactions between peptide binding domains and their targets. We discuss the largely unexplored potential of this method in the discovery of domain-motif interactions of potential biological relevance. PMID:25295249
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Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D
2016-01-01
Objective: This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Methods: Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Results: Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. Conclusions: High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the
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Manousopoulou, A; Koutmani, Y; Karaliota, S; Woelk, C H; Manolakos, E S; Karalis, K; Garbis, S D
2016-04-25
This study examined the proteomic profile of the hypothalamus in mice exposed to a high-fat diet (HFD) or with the anorexia of acute illness. This comparison could provide insight on the effects of these two opposite states of energy balance on appetite regulation. Four to six-week-old male C56BL/6J mice were fed a normal (control 1 group; n=7) or a HFD (HFD group; n=10) for 8 weeks. The control 2 (n=7) and lipopolysaccharide (LPS) groups (n=10) were fed a normal diet for 8 weeks before receiving an injection of saline and LPS, respectively. Hypothalamic regions were analysed using a quantitative proteomics method based on a combination of techniques including iTRAQ stable isotope labeling, orthogonal two-dimensional liquid chromatography hyphenated with nanospray ionization and high-resolution mass spectrometry. Key proteins were validated with quantitative PCR. Quantitative proteomics of the hypothalamous regions profiled a total of 9249 protein groups (q<0.05). Of these, 7718 protein groups were profiled with a minimum of two unique peptides for each. Hierachical clustering of the differentiated proteome revealed distinct proteomic signatures for the hypothalamus under the HFD and LPS nutritional conditions. Literature research with in silico bioinformatics interpretation of the differentiated proteome identified key biological relevant proteins and implicated pathways. Furthermore, the study identified potential pharmacologic targets. In the LPS groups, the anorexigen pro-opiomelanocortin was downregulated. In mice with obesity, nuclear factor-κB, glycine receptor subunit alpha-4 (GlyR) and neuropeptide Y levels were elevated, whereas serotonin receptor 1B levels decreased. High-precision quantitative proteomics revealed that under acute systemic inflammation in the hypothalamus as a response to LPS, homeostatic mechanisms mediating loss of appetite take effect. Conversely, under chronic inflammation in the hypothalamus as a response to HFD, mechanisms
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Targeted Proteomics Approach for Precision Plant Breeding.
Chawade, Aakash; Alexandersson, Erik; Bengtsson, Therese; Andreasson, Erik; Levander, Fredrik
2016-02-05
Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that enables precise quantitation of hundreds of peptides in a single run. This technique provides new opportunities for multiplexed protein biomarker measurements. For precision plant breeding, DNA-based markers have been used extensively, but the potential of protein biomarkers has not been exploited. In this work, we developed an SRM marker panel with assays for 104 potato (Solanum tuberosum) peptides selected using univariate and multivariate statistics. Thereafter, using random forest classification, the prediction markers were identified for Phytopthora infestans resistance in leaves, P. infestans resistance in tubers, and plant yield in potato leaf secretome samples. The results suggest that the marker panel has the predictive potential for three traits, two of which have no commercial DNA markers so far. Furthermore, the marker panel was also tested and found to be applicable to potato clones not used during the marker development. The proposed workflow is thus a proof-of-concept for targeted proteomics as an efficient readout in accelerated breeding for complex and agronomically important traits.
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Proteomic Approaches and Identification of Novel Therapeutic Targets for Alcoholism
Gorini, Giorgio; Adron Harris, R; Dayne Mayfield, R
2014-01-01
Recent studies have shown that gene regulation is far more complex than previously believed and does not completely explain changes at the protein level. Therefore, the direct study of the proteome, considerably different in both complexity and dynamicity to the genome/transcriptome, has provided unique insights to an increasing number of researchers. During the past decade, extraordinary advances in proteomic techniques have changed the way we can analyze the composition, regulation, and function of protein complexes and pathways underlying altered neurobiological conditions. When combined with complementary approaches, these advances provide the contextual information for decoding large data sets into meaningful biologically adaptive processes. Neuroproteomics offers potential breakthroughs in the field of alcohol research by leading to a deeper understanding of how alcohol globally affects protein structure, function, interactions, and networks. The wealth of information gained from these advances can help pinpoint relevant biomarkers for early diagnosis and improved prognosis of alcoholism and identify future pharmacological targets for the treatment of this addiction. PMID:23900301
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Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia.
Yu, Lei; Petyuk, Vladislav A; Gaiteri, Chris; Mostafavi, Sara; Young-Pearse, Tracy; Shah, Raj C; Buchman, Aron S; Schneider, Julie A; Piehowski, Paul D; Sontag, Ryan L; Fillmore, Thomas L; Shi, Tujin; Smith, Richard D; De Jager, Philip L; Bennett, David A
2018-06-16
Previous gene expression analysis identified a network of co-expressed genes that is associated with β-amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. Data came from 834 community-based older persons who were followed annually, died and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of β-amyloid and other common age-related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with β-amyloid load and other neuropathologic indices as well as cognitive decline over multiple years prior to death. The average age at death was 88.6 years. 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more β-amyloid load (p=1.0 × 10 -7 ) and higher PHFtau tangle density (p=2.3 × 10 -7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, AK4 and lower ITPK1 levels were associated with faster cognitive decline and, unlike PLXNB1, these associations were not fully explained by common neuropathologic indices, suggesting novel mechanisms leading to cognitive decline. Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting β-amyloid deposition and another affecting resilience without a known pathologic footprint. This article is protected by copyright. All rights reserved. © 2018 American Neurological Association.
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Byrne, Guerard W.; Stalboerger, Paul G.; Davila, Eduardo; Heppelmann, Carrie J.; Gazi, Mozammel H.; McGregor, Hugh C. J.; LaBreche, Peter T.; Davies, William R.; Rao, Vinay P.; Oi, Keiji; Tazelaar, Henry D.; Logan, John S.; McGregor, Christopher G. A.
2008-01-01
Background Experience with non-antigenic galactose α1,3 galactose (αGal) polymers and development of αGal deficient pigs has reduced or eliminated the significance of this antigen in xenograft rejection. Despite these advances, delayed xenograft rejection (DXR) continues to occur most likely due to antibody responses to non-Gal endothelial cell (EC) antigens. Methods To gauge the diversity of the non-Gal antibody response we used antibody derived from CD46 transgenic heterotopic cardiac xenografts performed without T-cell immunosuppression, Group A (n = 4) and Gal knockout (GT-KO) heart transplants under tacrolimus and sirolimus immunosuppression, Group B (n = 8). Non-Gal antibody was measured by flow cytometry and by Western blots using GT-KO EC membrane antigens. A nanoLC/MS/MS analysis of proteins recovered from 2D gels was used to identify target antigens. Results Group A recipients exhibited a mixed cellular and humoral rejection. Group B recipients mainly exhibited classical DXR. Western blot analysis showed a non-Gal antibody response induced by GT+ and GT-KO hearts to an overlapping set of pig aortic EC membrane antigens. Proteomic analysis identified 14 potential target antigens but failed to define several immunodominant targets. Conclusions These experiments indicate that the non-Gal antibody response is directed to a number of stress response and inflammation related pig EC antigens and a few undefined targets. Further analysis of these antibody specificities using alternative methods is required to more fully define the repertoire of non-Gal antibody responses. PMID:18957049
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Brusniak, Mi-Youn; Bodenmiller, Bernd; Campbell, David; Cooke, Kelly; Eddes, James; Garbutt, Andrew; Lau, Hollis; Letarte, Simon; Mueller, Lukas N; Sharma, Vagisha; Vitek, Olga; Zhang, Ning; Aebersold, Ruedi; Watts, Julian D
2008-01-01
Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to
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Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique
Xu, Jingwen; Zhang, Shijun; Jiang, Haiqiang; Wang, Nan; Lin, Haiqing
2017-01-01
Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect. PMID:28408942
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Strickland, Erin C; Geer, M Ariel; Hong, Jiyong; Fitzgerald, Michael C
2014-01-01
Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2% and <0.8% are calculated for SPROX experiments using Q-TOF and Orbitrap mass spectrometer systems, respectively. Our results indicate that the false-positive rate is largely determined by random errors associated with the mass spectral analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.
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Uddin, Reaz; Jamil, Faiza
2018-06-01
Pseudomonas aeruginosa is an opportunistic gram-negative bacterium that has the capability to acquire resistance under hostile conditions and become a threat worldwide. It is involved in nosocomial infections. In the current study, potential novel drug targets against P. aeruginosa have been identified using core proteomic analysis and Protein-Protein Interactions (PPIs) studies. The non-redundant reference proteome of 68 strains having complete genome and latest assembly version of P. aeruginosa were downloaded from ftp NCBI RefSeq server in October 2016. The standalone CD-HIT tool was used to cluster ortholog proteins (having >=80% amino acid identity) present in all strains. The pan-proteome was clustered in 12,380 Clusters of Orthologous Proteins (COPs). By using in-house shell scripts, 3252 common COPs were extracted out and designated as clusters of core proteome. The core proteome of PAO1 strain was selected by fetching PAO1's proteome from common COPs. As a result, 1212 proteins were shortlisted that are non-homologous to the human but essential for the survival of the pathogen. Among these 1212 proteins, 321 proteins are conserved hypothetical proteins. Considering their potential as drug target, those 321 hypothetical proteins were selected and their probable functions were characterized. Based on the druggability criteria, 18 proteins were shortlisted. The interacting partners were identified by investigating the PPIs network using STRING v10 database. Subsequently, 8 proteins were shortlisted as 'hub proteins' and proposed as potential novel drug targets against P. aeruginosa. The study is interesting for the scientific community working to identify novel drug targets against MDR pathogens particularly P. aeruginosa. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Banfi, Cristina; Baetta, Roberta; Gianazza, Erica; Tremoli, Elena
2017-06-01
Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Assembling proteomics data as a prerequisite for the analysis of large scale experiments
Schmidt, Frank; Schmid, Monika; Thiede, Bernd; Pleißner, Klaus-Peter; Böhme, Martina; Jungblut, Peter R
2009-01-01
Background Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. Results In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. Conclusion The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed
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Uddin, Reaz; Sufian, Muhammad
2016-01-01
Infections caused by Salmonella enterica, a Gram-negative facultative anaerobic bacteria belonging to the family of Enterobacteriaceae, are major threats to the health of humans and animals. The recent availability of complete genome data of pathogenic strains of the S. enterica gives new avenues for the identification of drug targets and drug candidates. We have used the genomic and metabolic pathway data to identify pathways and proteins essential to the pathogen and absent from the host. We took the whole proteome sequence data of 42 strains of S. enterica and Homo sapiens along with KEGG-annotated metabolic pathway data, clustered proteins sequences using CD-HIT, identified essential genes using DEG database and discarded S. enterica homologs of human proteins in unique metabolic pathways (UMPs) and characterized hypothetical proteins with SVM-prot and InterProScan. Through this core proteomic analysis we have identified enzymes essential to the pathogen. The identification of 73 enzymes common in 42 strains of S. enterica is the real strength of the current study. We proposed all 73 unexplored enzymes as potential drug targets against the infections caused by the S. enterica. The study is comprehensive around S. enterica and simultaneously considered every possible pathogenic strain of S. enterica. This comprehensiveness turned the current study significant since, to the best of our knowledge it is the first subtractive core proteomic analysis of the unique metabolic pathways applied to any pathogen for the identification of drug targets. We applied extensive computational methods to shortlist few potential drug targets considering the druggability criteria e.g. Non-homologous to the human host, essential to the pathogen and playing significant role in essential metabolic pathways of the pathogen (i.e. S. enterica). In the current study, the subtractive proteomics through a novel approach was applied i.e. by considering only proteins of the unique metabolic
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Chemical Proteomics Reveals Ferrochelatase as a Common Off-target of Kinase Inhibitors.
Klaeger, Susan; Gohlke, Bjoern; Perrin, Jessica; Gupta, Vipul; Heinzlmeir, Stephanie; Helm, Dominic; Qiao, Huichao; Bergamini, Giovanna; Handa, Hiroshi; Savitski, Mikhail M; Bantscheff, Marcus; Médard, Guillaume; Preissner, Robert; Kuster, Bernhard
2016-05-20
Many protein kinases are valid drug targets in oncology because they are key components of signal transduction pathways. The number of clinical kinase inhibitors is on the rise, but these molecules often exhibit polypharmacology, potentially eliciting desired and toxic effects. Therefore, a comprehensive assessment of a compound's target space is desirable for a better understanding of its biological effects. The enzyme ferrochelatase (FECH) catalyzes the conversion of protoporphyrin IX into heme and was recently found to be an off-target of the BRAF inhibitor Vemurafenib, likely explaining the phototoxicity associated with this drug in melanoma patients. This raises the question of whether FECH binding is a more general feature of kinase inhibitors. To address this, we applied a chemical proteomics approach using kinobeads to evaluate 226 clinical kinase inhibitors for their ability to bind FECH. Surprisingly, low or submicromolar FECH binding was detected for 29 of all compounds tested and isothermal dose response measurements confirmed target engagement in cells. We also show that Vemurafenib, Linsitinib, Neratinib, and MK-2461 reduce heme levels in K562 cells, verifying that drug binding leads to a loss of FECH activity. Further biochemical and docking experiments identified the protoporphyrin pocket in FECH as one major drug binding site. Since the genetic loss of FECH activity leads to photosensitivity in humans, our data strongly suggest that FECH inhibition by kinase inhibitors is the molecular mechanism triggering photosensitivity in patients. We therefore suggest that a FECH assay should generally be part of the preclinical molecular toxicology package for the development of kinase inhibitors.
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Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics.
Keich, Uri; Kertesz-Farkas, Attila; Noble, William Stafford
2015-08-07
Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Käll et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications.
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Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics
2016-01-01
Interpreting the potentially vast number of hypotheses generated by a shotgun proteomics experiment requires a valid and accurate procedure for assigning statistical confidence estimates to identified tandem mass spectra. Despite the crucial role such procedures play in most high-throughput proteomics experiments, the scientific literature has not reached a consensus about the best confidence estimation methodology. In this work, we evaluate, using theoretical and empirical analysis, four previously proposed protocols for estimating the false discovery rate (FDR) associated with a set of identified tandem mass spectra: two variants of the target-decoy competition protocol (TDC) of Elias and Gygi and two variants of the separate target-decoy search protocol of Käll et al. Our analysis reveals significant biases in the two separate target-decoy search protocols. Moreover, the one TDC protocol that provides an unbiased FDR estimate among the target PSMs does so at the cost of forfeiting a random subset of high-scoring spectrum identifications. We therefore propose the mix-max procedure to provide unbiased, accurate FDR estimates in the presence of well-calibrated scores. The method avoids biases associated with the two separate target-decoy search protocols and also avoids the propensity for target-decoy competition to discard a random subset of high-scoring target identifications. PMID:26152888
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Tomar, Anil Kumar; Sooch, Balwinder Singh; Singh, Sarman; Yadav, Savita
2012-04-01
The clinical fertility tests, available in the market, fail to define the exact cause of male infertility in almost half of the cases and point toward a crucial need of developing better ways of infertility investigations. The protein biomarkers may help us toward better understanding of unknown cases of male infertility that, in turn, can guide us to find better therapeutic solutions. Many clinical attempts have been made to identify biomarkers of male infertility in sperm proteome but only few studies have targeted seminal plasma. Human seminal plasma is a rich source of proteins that are essentially required for development of sperm and successful fertilization. This viewpoint article highlights the importance of human seminal plasma proteome in reproductive physiology and suggests that differential proteomics integrated with functional analysis may help us in searching potential biomarkers of male infertility. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Expression proteomics study to determine metallodrug targets and optimal drug combinations.
Lee, Ronald F S; Chernobrovkin, Alexey; Rutishauser, Dorothea; Allardyce, Claire S; Hacker, David; Johnsson, Kai; Zubarev, Roman A; Dyson, Paul J
2017-05-08
The emerging technique termed functional identification of target by expression proteomics (FITExP) has been shown to identify the key protein targets of anti-cancer drugs. Here, we use this approach to elucidate the proteins involved in the mechanism of action of two ruthenium(II)-based anti-cancer compounds, RAPTA-T and RAPTA-EA in breast cancer cells, revealing significant differences in the proteins upregulated. RAPTA-T causes upregulation of multiple proteins suggesting a broad mechanism of action involving suppression of both metastasis and tumorigenicity. RAPTA-EA bearing a GST inhibiting ethacrynic acid moiety, causes upregulation of mainly oxidative stress related proteins. The approach used in this work could be applied to the prediction of effective drug combinations to test in cancer chemotherapy clinical trials.
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Proteome complexity and the forces that drive proteome imbalance.
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.
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University of Victoria Genome British Columbia Proteomics Centre, a leader in proteomic technology development, has partnered with the U.S. National Cancer Institute (NCI) to make targeted proteomic assays accessible to the community through NCI’s CPTAC Assay Portal (https://assays.cancer.gov).
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NCI's Office of Cancer Clinical Proteomics Research authored a review of the current state of clinical proteomics in the peer-reviewed Journal of Proteome Research. The review highlights outcomes from the CPTC program and also provides a thorough overview of the different technologies that have pushed the field forward. Additionally, the review provides a vision for moving the field forward through linking advances in genomic and proteomic analysis to develop new, molecularly targeted interventions.
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Current advances in esophageal cancer proteomics.
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.
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Automated Big Data Analysis in Bottom-up and Targeted Proteomics
van der Plas-Duivesteijn, Suzanne; Domański, Dominik; Smith, Derek; Borchers, Christoph; Palmblad, Magnus; Mohamme, Yassene
2014-01-01
Similar to other data intensive sciences, analyzing mass spectrometry-based proteomics data involves multiple steps and diverse software using different algorithms and data formats and sizes. Besides that the distributed and evolving nature of the data in online repositories, another challenge is that a scientists have to deal with many steps of analysis pipelines. A documented data processing is also becoming an essential part for the overall reproducibility of the results. Thanks to different e-Science initiatives, scientific workflow engines have become a means for automated, sharable and reproducible data processing. While these are designed as general tools, they can be employed to solve different challenges that we are facing in handling our Big Data. Here we present three use cases: improving the performance of different spectral search engines by decomposing input data and recomposing the resulting files, building spectral libraries from more than 20 million spectra, and integrating information from multiple resources to select most appropriate peptides for targeted proteomics analyses. The three use cases demonstrate different challenges in exploiting proteomics data analysis. In the first we integrate local and cloud processing resources in order to obtain better performance resulting in more than 30-fold speed improvement. By considering search engines as legacy software our solution is applicable to multiple search algorithms. The second use case is an example of automated processing of many data files of different sizes and locations, starting with raw data and ending with the final, ready-to-use library. This demonstrates the robustness and fault tolerance when dealing with huge amount data stored in multiple files. The third use case demonstrates retrieval and integration of information and data from multiple online repositories. In addition to the diversity of data formats and Web interfaces, this use case also illustrates how to deal with
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Moon, Eunjung; Park, Hye Min; Lee, Choong Hwan; Do, Seon-Gil; Park, Jong-Moon; Han, Na-Young; Do, Moon Ho; Lee, Jong Ha; Lee, Hookeun; Kim, Sun Yeou
2015-03-18
Photodamage is extrinsically induced by overexposure to ultraviolet (UV) radiation, and it increases the risk of various skin disorders. Therefore, discovery of novel biomarkers of photodamage is important. In this study, using LC-MS/MS analysis of epidermis from UVB-irradiated hairless mice, we identified 57 proteins whose levels changed after UVB exposure, and selected 7 proteins related to the tricarboxylic acid (TCA) cycle through pathway analysis. Dihydrolipoyl dehydrogenase (DLD) was the only TCA cycle-associated protein that showed a decreased expression after the UVB exposure. We also performed targeted analysis to detect intermediates and products of the TCA cycle using GC-TOF-MS. Interestingly, malic acid and fumaric acid levels significantly decreased in the UVB-treated group. Our results demonstrate that DLD and its associated metabolites, malic acid and fumaric acid, may be candidate biomarkers of UVB-induced skin photoaging. Additionally, we showed that Aloe vera, a natural skin moisturizer, regulated DLD, malic acid and fumaric acid levels in UVB-exposed epidermis. Our strategy to integrate the proteome and targeted metabolite to detect novel UVB targets will lead to a better understanding of skin photoaging and photodamage. Our study also supports that A. vera exerts significant anti-photodamage activity via regulation of DLD, a novel UVB target, in the epidermis. This study is the first example of an integration of proteomic and metabolite analysis techniques to find new biomarker candidates for the regulation of the UVB-induced skin photoaging. DLD, malic acid, and fumaric acid can be used for development of cosmeceuticals and nutraceuticals regulating the change of skin metabolism induced by the UVB overexposure. Moreover, this is also the first attempt to investigate the role of the TCA cycle in photodamaged epidermis. Our integration of the proteomic and targeted metabolite analyses will lead to a better understanding of the unidentified
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Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches
2012-07-01
1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...July 2012 2. REPORT TYPE Final 3. DATES COVERED (From - To) 1 July 2008 – 30 June 2012 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic...Department of Defense Synergistic Idea Development Award W81XWH-08-1-0430 (to H.Z) and W81XWH-08-1-0431 (to N.K.), an NIH/NCRR COBRE grant 1P20RR020171 (to
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Proteome complexity and the forces that drive proteome imbalance
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
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Bostanci, Nagihan; Selevsek, Nathalie; Wolski, Witold; Grossmann, Jonas; Bao, Kai; Wahlander, Asa; Trachsel, Christian; Schlapbach, Ralph; Özturk, Veli Özgen; Afacan, Beral; Emingil, Gulnur; Belibasakis, Georgios N
2018-04-02
Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. We carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n=67, health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n=82). The LFQ platform led to the discovery of 119 proteins with at least two-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1), with maximum area under the receiver operating curve >0.97. This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum
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Yang, Ting; Chen, Fei; Xu, Feifei; Wang, Fengliang; Xu, Qingqing; Chen, Yun
2014-09-25
P-glycoprotein (P-gp) can efflux drugs from cancer cells, and its overexpression is commonly associated with multi-drug resistance (MDR). Thus, the accurate quantification of P-gp would help predict the response to chemotherapy and for prognosis of breast cancer patients. An advanced liquid chromatography-tandem mass spectrometry (LC/MS/MS)-based targeted proteomics assay was developed and validated for monitoring P-gp levels in breast tissue. Tryptic peptide 368IIDNKPSIDSYSK380 was selected as a surrogate analyte for quantification, and immuno-depleted tissue extract was used as a surrogate matrix. Matched pairs of breast tissue samples from 60 patients who were suspected to have drug resistance were subject to analysis. The levels of P-gp were quantified. Using data from normal tissue, we suggested a P-gp reference interval. The experimental values of tumor tissue samples were compared with those obtained from Western blotting and immunohistochemistry (IHC). The result indicated that the targeted proteomics approach was comparable to IHC but provided a lower limit of quantification (LOQ) and could afford more reliable results at low concentrations than the other two methods. LC/MS/MS-based targeted proteomics may allow the quantification of P-gp in breast tissue in a more accurate manner. Copyright © 2014 Elsevier B.V. All rights reserved.
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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.
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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.
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Yang, Peng-Yu; Liu, Kai; Ngai, Mun Hong; Lear, Martin J; Wenk, Markus R; Yao, Shao Q
2010-01-20
Orlistat, or tetrahydrolipstatin (THL), is an FDA-approved antiobesity drug with potential antitumor activities. Cellular off-targets and potential side effects of Orlistat in cancer therapies, however, have not been extensively explored thus far. In this study, we report the total of synthesis of THL-like protein-reactive probes, in which extremely conservative modifications (i.e., an alkyne handle) were introduced in the parental THL structure to maintain the native biological properties of Orlistat, while providing the necessary functionality for target identification via the bio-orthogonal click chemistry. With these natural productlike, cell-permeable probes, we were able to demonstrate, for the first time, this chemical proteomic approach is suitable for the identification of previously unknown cellular targets of Orlistat. In addition to the expected fatty acid synthase (FAS), we identified a total of eight new targets, some of which were further validated by experiments including Western blotting, recombinant protein expression, and site-directed mutagenesis. Our findings have important implications in the consideration of Orlistat as a potential anticancer drug at its early stages of development for cancer therapy. Our strategy should be broadly useful for off-target identification against quite a number of existing drugs and/or candidates, which are also covalent modifiers of their biological targets.
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Assay Portal | Office of Cancer Clinical Proteomics Research
The CPTAC Assay Portal serves as a centralized public repository of "fit-for-purpose," multiplexed quantitative mass spectrometry-based proteomic targeted assays. Targeted proteomic assays eliminate issues that are commonly observed using conventional protein detection systems.
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In an effort to provide well-characterized monoclonal antibodies to the scientific community, the National Cancer Institute (NCI) Antibody Characterization Program requests cancer-related protein targets for affinity production and distribution. The program from The Office of Cancer Clinical Proteomics Research provides reagents and other critical resources that support protein and/or peptide measurements and analysis.
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Zhang, Cheng-Cheng; Li, Ru; Jiang, Honghui; Lin, Shujun; Rogalski, Jason C; Liu, Kate; Kast, Juergen
2015-02-06
Small GTPases are a family of key signaling molecules that are ubiquitously expressed in various types of cells. Their activity is often analyzed by western blot, which is limited by its multiplexing capability, the quality of isoform-specific antibodies, and the accuracy of quantification. To overcome these issues, a quantitative multiplexed small GTPase activity assay has been developed. Using four different binding domains, this assay allows the binding of up to 12 active small GTPase isoforms simultaneously in a single experiment. To accurately quantify the closely related small GTPase isoforms, a targeted proteomic approach, i.e., selected/multiple reaction monitoring, was developed, and its functionality and reproducibility were validated. This assay was successfully applied to human platelets and revealed time-resolved coactivation of multiple small GTPase isoforms in response to agonists and differential activation of these isoforms in response to inhibitor treatment. This widely applicable approach can be used for signaling pathway studies and inhibitor screening in many cellular systems.
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Scientific Approaches | Office of Cancer Clinical Proteomics Research
CPTAC employs two complementary scientific approaches, a "Targeting Genome to Proteome" (Targeting G2P) approach and a "Mapping Proteome to Genome" (Mapping P2G) approach, in order to address biological questions from data generated on a sample.
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Poersch, Aline; Grassi, Mariana Lopes; Carvalho, Vinícius Pereira de; Lanfredi, Guilherme Pauperio; Palma, Camila de Souza; Greene, Lewis Joel; de Sousa, Christiani Bisinoto; Carrara, Hélio Humberto Angotti; Candido Dos Reis, Francisco José; Faça, Vitor Marcel
2016-08-11
Tumor fluid samples have emerged as a rich source for the identification of ovarian cancer in the context of proteomics studies. To uncover differences among benign and malignant ovarian samples, we performed a quantitative proteomic study consisting of albumin immunodepletion, isotope labeling with acrylamide and in-depth proteomic profiling by LC-MS/MS in a pool of 10 samples of each histological type. 1135 proteins were identified, corresponding to 505 gene products. 223 proteins presented associated quantification and the comparative analysis of histological types revealed 75 differentially abundant proteins. Based on this, we developed a panel for targeted proteomic analysis using the multiple reaction monitoring (MRM) method for validation of 51 proteins in individual samples of high-grade serous ovarian tumor fluids (malignant) and benign serous cystadenoma tumor fluids. This analysis showed concordant results in terms of average amounts of proteins, and APOE, SERPINF2, SERPING1, ADAM17, CD44 and OVGP1 were statistically significant between benign and malignant group. The results observed in the MRM for APOE were confirmed by western blotting, where APOE was more abundant in malignant samples. This molecular signature can contribute to improve tumor stratification and shall be investigated in combination with current biomarkers in larger cohorts to improve ovarian cancer diagnosis. Despite advances in cancer research, ovarian cancer has a high mortality and remains a major challenge due to a number of particularities of the disease, especially late diagnosis caused by vague clinical symptoms, the cellular and molecular heterogeneity of tumors, and the lack of effective treatment. Thus, efforts are directed to better understand this neoplasia, its origin, development and, particularly the identification and validation of biomarkers for early detection of the disease in asymptomatic stage. In the present work, we confirmed by MRM method in individual ovarian
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Novel targets of sulforaphane in primary cardiomyocytes identified by proteomic analysis.
Angeloni, Cristina; Turroni, Silvia; Bianchi, Laura; Fabbri, Daniele; Motori, Elisa; Malaguti, Marco; Leoncini, Emanuela; Maraldi, Tullia; Bini, Luca; Brigidi, Patrizia; Hrelia, Silvana
2013-01-01
Cardiovascular diseases represent the main cause of mortality in the industrialized world and the identification of effective preventive strategies is of fundamental importance. Sulforaphane, an isothiocyanate from cruciferous vegetables, has been shown to up-regulate phase II enzymes in cardiomyocytes and counteract oxidative stress-induced apoptosis. Aim of the present study was the identification and characterization of novel sulforaphane targets in cardiomyocytes applying a proteomic approach. Two-dimensional gel electrophoresis and mass spectrometry were used to generate protein profiles of primary neonatal rat cardiomyocytes treated and untreated with 5 µM sulforaphane for 1-48 h. According to image analysis, 64 protein spots were found as differentially expressed and their functional correlations were investigated using the MetaCore program. We mainly focused on 3 proteins: macrophage migration inhibitory factor (MIF), CLP36 or Elfin, and glyoxalase 1, due to their possible involvement in cardioprotection. Validation of the time-dependent differential expression of these proteins was performed by western blotting. In particular, to gain insight into the cardioprotective role of the modulation of glyoxalase 1 by sulforaphane, further experiments were performed using methylglyoxal to mimic glycative stress. Sulforaphane was able to counteract methylglyoxal-induced apoptosis, ROS production, and glycative stress, likely through glyoxalase 1 up-regulation. In this study, we reported for the first time new molecular targets of sulforaphane, such as MIF, CLP36 and glyoxalase 1. In particular, we gave new insights into the anti-glycative role of sulforaphane in cardiomyocytes, confirming its pleiotropic behavior in counteracting cardiovascular diseases.
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Hung, Chien-Wen; Klein, Tobias; Cassidy, Liam; Linke, Dennis; Lange, Sabrina; Anders, Uwe; Bureik, Matthias; Heinzle, Elmar; Schneider, Konstantin; Tholey, Andreas
2016-01-01
Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe. Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016. PMID:27477394
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Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome.
Ghodasara, P; Sadowski, P; Satake, N; Kopp, S; Mills, P C
2017-12-01
Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Odongo, Steven; Sterckx, Yann G J; Stijlemans, Benoît; Pillay, Davita; Baltz, Théo; Muyldermans, Serge; Magez, Stefan
2016-02-01
Infectious diseases pose a severe worldwide threat to human and livestock health. While early diagnosis could enable prompt preventive interventions, the majority of diseases are found in rural settings where basic laboratory facilities are scarce. Under such field conditions, point-of-care immunoassays provide an appropriate solution for rapid and reliable diagnosis. The limiting steps in the development of the assay are the identification of a suitable target antigen and the selection of appropriate high affinity capture and detection antibodies. To meet these challenges, we describe the development of a Nanobody (Nb)-based antigen detection assay generated from a Nb library directed against the soluble proteome of an infectious agent. In this study, Trypanosoma congolense was chosen as a model system. An alpaca was vaccinated with whole-parasite soluble proteome to generate a Nb library from which the most potent T. congolense specific Nb sandwich immunoassay (Nb474H-Nb474B) was selected. First, the Nb474-homologous sandwich ELISA (Nb474-ELISA) was shown to detect experimental infections with high Positive Predictive Value (98%), Sensitivity (87%) and Specificity (94%). Second, it was demonstrated under experimental conditions that the assay serves as test-of-cure after Berenil treatment. Finally, this assay allowed target antigen identification. The latter was independently purified through immuno-capturing from (i) T. congolense soluble proteome, (ii) T. congolense secretome preparation and (iii) sera of T. congolense infected mice. Subsequent mass spectrometry analysis identified the target as T. congolense glycosomal aldolase. The results show that glycosomal aldolase is a candidate biomarker for active T. congolense infections. In addition, and by proof-of-principle, the data demonstrate that the Nb strategy devised here offers a unique approach to both diagnostic development and target discovery that could be widely applied to other infectious diseases.
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In an effort to improve rigor and reproducibility, the National Cancer Institute (NCI) Antibody Characterization Program requests cancer-related protein targets for monoclonal antibody production and distribution to the scientific community. The program from The Office of Cancer Clinical Proteomics Research provides well-characterized
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Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio
2015-03-01
Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. © 2014 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Targeting human pathogenic bacteria by siderophores: A proteomics review.
Ferreira, Daniela; Seca, Ana M L; C G A, Diana; Silva, Artur M S
2016-08-11
Human bacterial infections are still a major public health problem throughout the world. Therefore it is fundamental to understand how pathogenic bacteria interact with their human host and to develop more advanced drugs or vaccines in response to the increasing bacterial resistance. Since iron is essential to bacterial survival and growth inside the host tissues, these microorganisms have developed highly efficient iron-acquisition systems; the most common one involves the secretion of iron chelators into the extracellular environment, known as siderophores, and the corresponding siderophore-membrane receptors or transporters responsible for the iron uptake. In the past few decades, several biochemical methods and genetic screens have been employed to track down and identify these iron-scavenging molecules. However, compared with the previous "static" approaches, proteomic identification is revealing far more molecules through full protein mapping and becoming more rapid and selective, leading the scientific and medical community to consider standardizing proteomic tools for clinical biomarker detection of bacterial infectious diseases. In this review, we focus on human pathogenic Gram-negative bacteria and discuss the importance of siderophores in their virulence and the available proteomic strategies to identify siderophore-related proteins and their expression level under different growth conditions. The promising use of siderophore antibiotics to overcome bacterial resistance and the future of proteomics in the routine clinical care are also mentioned. Proteomic strategies to identify siderophore-related proteins and their expression level can be helpful to control and/or find a cure of infectious deseases especially if related with multidrug resistance. Siderophores are low-molecular-weight compounds produced by bacteria which can become clinical biomarkers and/or antibiotics used mainly in "Trojan horse" type strategies. Due to the above mention we think
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Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio
2015-01-01
Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. PMID:25158685
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Schacherer, Lindsey J; Xie, Weiping; Owens, Michaela A; Alarcon, Clara; Hu, Tiger X
2016-09-01
Liquid chromatography coupled with tandem mass spectrometry is increasingly used for protein detection for transgenic crops research. Currently this is achieved with protein reference standards which may take a significant time or efforts to obtain and there is a need for rapid protein detection without protein reference standards. A sensitive and specific method was developed to detect target proteins in transgenic maize leaf crude extract at concentrations as low as ∼30 ng mg(-1) dry leaf without the need of reference standards or any sample enrichment. A hybrid Q-TRAP mass spectrometer was used to monitor all potential tryptic peptides of the target proteins in both transgenic and non-transgenic samples. The multiple reaction monitoring-initiated detection and sequencing (MIDAS) approach was used for initial peptide/protein identification via Mascot database search. Further confirmation was achieved by direct comparison between transgenic and non-transgenic samples. Definitive confirmation was provided by running the same experiments of synthetic peptides or protein standards, if available. A targeted proteomic mass spectrometry method using MIDAS approach is an ideal methodology for detection of new proteins in early stages of transgenic crop research and development when neither protein reference standards nor antibodies are available. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.
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A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*
Xiao, Yongsheng; Guo, Lei; Wang, Yinsheng
2014-01-01
Kinases are among the most intensively pursued enzyme superfamilies as targets for anti-cancer drugs. Large data sets on inhibitor potency and selectivity for more than 400 human kinases became available recently, offering the opportunity to design rationally novel kinase-based anti-cancer therapies. However, the expression levels and activities of kinases are highly heterogeneous among different types of cancer and even among different stages of the same cancer. The lack of effective strategy for profiling the global kinome hampers the development of kinase-targeted cancer chemotherapy. Here, we introduced a novel global kinome profiling method, based on our recently developed isotope-coded ATP-affinity probe and a targeted proteomic method using multiple-reaction monitoring (MRM), for assessing simultaneously the expression of more than 300 kinases in human cells and tissues. This MRM-based assay displayed much better sensitivity, reproducibility, and accuracy than the discovery-based shotgun proteomic method. Approximately 250 kinases could be routinely detected in the lysate of a single cell line. Additionally, the incorporation of iRT into MRM kinome library rendered our MRM kinome assay easily transferrable across different instrument platforms and laboratories. We further employed this approach for profiling kinase expression in two melanoma cell lines, which revealed substantial kinome reprogramming during cancer progression and demonstrated an excellent correlation between the anti-proliferative effects of kinase inhibitors and the expression levels of their target kinases. Therefore, this facile and accurate kinome profiling assay, together with the kinome-inhibitor interaction map, could provide invaluable knowledge to predict the effectiveness of kinase inhibitor drugs and offer the opportunity for individualized cancer chemotherapy. PMID:24520089
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Targeted Feature Detection for Data-Dependent Shotgun Proteomics.
Weisser, Hendrik; Choudhary, Jyoti S
2017-08-04
Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification ("FFId"), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between "internal" and "external" (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the "uncertain" feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards that provide a known
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Omasits, Ulrich; Quebatte, Maxime; Stekhoven, Daniel J.; Fortes, Claudia; Roschitzki, Bernd; Robinson, Mark D.; Dehio, Christoph; Ahrens, Christian H.
2013-01-01
Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, we could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ∼90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor. PMID:23878158
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Omasits, U.; Quebatte, Maxime; Stekhoven, Daniel J.
2013-11-01
Prokaryotes, due to their moderate complexity, are particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant, and membrane localized, wemore » could eliminate their initial underrepresentation compared to the estimated endpoint. A total of 1250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and ~90% of the expressed protein-coding genes. Genes that were detected at the transcript but not protein level, were found to be highly enriched in several genomic islands. Furthermore, genes that lacked an ortholog and a functional annotation were not detected at the protein level; these may represent examples of overprediction in genome annotations. A dramatic membrane proteome reorganization was observed, including differential regulation of autotransporters, adhesins, and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage, which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor.« less
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Hopkins, Julia F.; Spencer, David F.; Laboissiere, Sylvie; Neilson, Jonathan A.D.; Eveleigh, Robert J.M.; Durnford, Dion G.; Gray, Michael W.; Archibald, John M.
2012-01-01
Chlorarachniophytes are unicellular marine algae with plastids (chloroplasts) of secondary endosymbiotic origin. Chlorarachniophyte cells retain the remnant nucleus (nucleomorph) and cytoplasm (periplastidial compartment, PPC) of the green algal endosymbiont from which their plastid was derived. To characterize the diversity of nucleus-encoded proteins targeted to the chlorarachniophyte plastid, nucleomorph, and PPC, we isolated plastid–nucleomorph complexes from the model chlorarachniophyte Bigelowiella natans and subjected them to high-pressure liquid chromatography-tandem mass spectrometry. Our proteomic analysis, the first of its kind for a nucleomorph-bearing alga, resulted in the identification of 324 proteins with 95% confidence. Approximately 50% of these proteins have predicted bipartite leader sequences at their amino termini. Nucleus-encoded proteins make up >90% of the proteins identified. With respect to biological function, plastid-localized light-harvesting proteins were well represented, as were proteins involved in chlorophyll biosynthesis. Phylogenetic analyses revealed that many, but by no means all, of the proteins identified in our proteomic screen are of apparent green algal ancestry, consistent with the inferred evolutionary origin of the plastid and nucleomorph in chlorarachniophytes. PMID:23221610
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Proteomics of ovarian cancer: functional insights and clinical applications
Elzek, Mohamed A.; Rodland, Karin D.
2015-03-04
In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification ofmore » aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics’ contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. In conclusion, we propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.« less
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Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing*
Manes, Nathan P.; Angermann, Bastian R.; Koppenol-Raab, Marijke; An, Eunkyung; Sjoelund, Virginie H.; Sun, Jing; Ishii, Masaru; Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra
2015-01-01
Osteoclasts are monocyte-derived multinuclear cells that directly attach to and resorb bone. Sphingosine-1-phosphate (S1P)1 regulates bone resorption by functioning as both a chemoattractant and chemorepellent of osteoclast precursors through two G-protein coupled receptors that antagonize each other in an S1P-concentration-dependent manner. To quantitatively explore the behavior of this chemosensing pathway, we applied targeted proteomics, transcriptomics, and rule-based pathway modeling using the Simmune toolset. RAW264.7 cells (a mouse monocyte/macrophage cell line) were used as model osteoclast precursors, RNA-seq was used to identify expressed target proteins, and selected reaction monitoring (SRM) mass spectrometry using internal peptide standards was used to perform absolute abundance measurements of pathway proteins. The resulting transcript and protein abundance values were strongly correlated. Measured protein abundance values, used as simulation input parameters, led to in silico pathway behavior matching in vitro measurements. Moreover, once model parameters were established, even simulated responses toward stimuli that were not used for parameterization were consistent with experimental findings. These findings demonstrate the feasibility and value of combining targeted mass spectrometry with pathway modeling for advancing biological insight. PMID:26199343
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Xu, Qingqing; Xu, Feifei; Liu, Liang; Chen, Yun
2016-09-06
Protein arginine methylation is one of the common post-translational modifications in cellular processes. To date, two isomeric forms of dimethylated arginine have been identified: asymmetric N(G),N(G)-dimethylarginine (aDMA), and symmetric N(G),N'(G)-dimethylarginine (sDMA). Evidence indicated that these isomers can coexist and have different or even opposite functions, with aDMA and sDMA forms of arginine 2 on histone H3 (i.e., H3R2me2a and H3R2me2s) being an example. Thus, specific detection and quantification of each isomeric form is important. Current methods are capable of predicting and detecting thousands of methylarginine sites in proteins, whereas differentiation and stoichiometric measurement of dimethylated protein isomers are still challenging. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted proteomics has emerged as a promising technique for site-specific quantification of protein methylation using enzymatic peptides as surrogates of target proteins. However, it should be pointed out that a routine targeted proteomics strategy cannot easily distinguish sDMA- and aDMA-containing surrogate peptides due to their common nature. The estimated amount should be considered as the sum of both arginine dimethylated isomers. In this study, compositional analysis based on a linear algebra algorithm as an add-on to targeted proteomics was employed to quantify H3R2me2a and H3R2me2s (i.e., surrogate peptides of AR(me2a)TK(me1/2)QT and AR(me2s)TK(me1/2)QT). To achieve this simultaneous quantification, a targeted proteomics assay was developed and validated for each isomer first. With the slope and intercept of their calibration curves for each multiple reaction monitoring (MRM) transition, linear algebraic equations were derived. Using a series of mock mixtures consisting of isomers in varying concentrations, the reliability of the method was confirmed. Finally, the H3R2 dimethylation status was analyzed in normal MCF-10A cells
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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).
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Schwenk, Jochen M; Omenn, Gilbert S; Sun, Zhi; Campbell, David S; Baker, Mark S; Overall, Christopher M; Aebersold, Ruedi; Moritz, Robert L; Deutsch, Eric W
2017-12-01
Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.
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Schnell, Gilles; Boeuf, Amandine; Westermann, Benoît; Jaulhac, Benoît; Lipsker, Dan; Carapito, Christine; Boulanger, Nathalie; Ehret-Sabatier, Laurence
2015-01-01
Lyme disease is the most important vector-borne disease in the Northern hemisphere and represents a major public health challenge with insufficient means of reliable diagnosis. Skin is rarely investigated in proteomics but constitutes in the case of Lyme disease the key interface where the pathogens can enter, persist, and multiply. Therefore, we investigated proteomics on skin samples to detect Borrelia proteins directly in cutaneous biopsies in a robust and specific way. We first set up a discovery gel prefractionation-LC-MS/MS approach on a murine model infected by Borrelia burgdorferi sensu stricto that allowed the identification of 25 Borrelia proteins among more than 1300 mouse proteins. Then we developed a targeted gel prefractionation-LC-selected reaction monitoring (SRM) assay to detect 9/33 Borrelia proteins/peptides in mouse skin tissue samples using heavy labeled synthetic peptides. We successfully transferred this assay from the mouse model to human skin biopsies (naturally infected by Borrelia), and we were able to detect two Borrelia proteins: OspC and flagellin. Considering the extreme variability of OspC, we developed an extended SRM assay to target a large set of variants. This assay afforded the detection of nine peptides belonging to either OspC or flagellin in human skin biopsies. We further shortened the sample preparation and showed that Borrelia is detectable in mouse and human skin biopsies by directly using a liquid digestion followed by LC-SRM analysis without any prefractionation. This study thus shows that a targeted SRM approach is a promising tool for the early direct diagnosis of Lyme disease with high sensitivity (<10 fmol of OspC/mg of human skin biopsy). PMID:25713121
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Yang, Wei; Kim, Yongsoo; Kim, Taek-Kyun; Keay, Susan K; Kim, Kwang Pyo; Steen, Hanno; Freeman, Michael R; Hwang, Daehee; Kim, Jayoung
2012-12-01
identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting. • Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF. • This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway. © 2012 THE AUTHORS. BJU INTERNATIONAL © 2012 BJU INTERNATIONAL.
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Mechanism-based Proteomic Screening Identifies Targets of Thioredoxin-like Proteins*
Nakao, Lia S.; Everley, Robert A.; Marino, Stefano M.; Lo, Sze M.; de Souza, Luiz E.; Gygi, Steven P.; Gladyshev, Vadim N.
2015-01-01
Thioredoxin (Trx)-fold proteins are protagonists of numerous cellular pathways that are subject to thiol-based redox control. The best characterized regulator of thiols in proteins is Trx1 itself, which together with thioredoxin reductase 1 (TR1) and peroxiredoxins (Prxs) comprises a key redox regulatory system in mammalian cells. However, there are numerous other Trx-like proteins, whose functions and redox interactors are unknown. It is also unclear if the principles of Trx1-based redox control apply to these proteins. Here, we employed a proteomic strategy to four Trx-like proteins containing CXXC motifs, namely Trx1, Rdx12, Trx-like protein 1 (Txnl1) and nucleoredoxin 1 (Nrx1), whose cellular targets were trapped in vivo using mutant Trx-like proteins, under conditions of low endogenous expression of these proteins. Prxs were detected as key redox targets of Trx1, but this approach also supported the detection of TR1, which is the Trx1 reductant, as well as mitochondrial intermembrane proteins AIF and Mia40. In addition, glutathione peroxidase 4 was found to be a Rdx12 redox target. In contrast, no redox targets of Txnl1 and Nrx1 could be detected, suggesting that their CXXC motifs do not engage in mixed disulfides with cellular proteins. For some Trx-like proteins, the method allowed distinguishing redox and non-redox interactions. Parallel, comparative analyses of multiple thiol oxidoreductases revealed differences in the functions of their CXXC motifs, providing important insights into thiol-based redox control of cellular processes. PMID:25561728
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Butler, G S; Overall, C M
2007-01-01
We illustrate the use of quantitative proteomics, namely isotope-coded affinity tag labelling and tandem mass spectrometry, to assess the targets and effects of the blockade of matrix metalloproteinases by an inhibitor drug in a breast cancer cell culture system. Treatment of MT1-MMP-transfected MDA-MB-231 cells with AG3340 (Prinomastat) directly affected the processing a multitude of matrix metalloproteinase substrates, and indirectly altered the expression of an array of other proteins with diverse functions. Therefore, broad spectrum blockade of MMPs has wide-ranging biological consequences. In this human breast cancer cell line, secreted substrates accumulated uncleaved in the conditioned medium and plasma membrane protein substrates were retained on the cell surface, due to reduced processing and shedding of these proteins (cell surface receptors, growth factors and bioactive molecules) to the medium in the presence of the matrix metalloproteinase inhibitor. Hence, proteomic investigation of drug-perturbed cellular proteomes can identify new protease substrates and at the same time provides valuable information for target validation, drug efficacy and potential side effects prior to commitment to clinical trials.
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Stangeland, Biljana; Mughal, Awais A; Grieg, Zanina; Sandberg, Cecilie Jonsgar; Joel, Mrinal; Nygård, Ståle; Meling, Torstein; Murrell, Wayne; Vik Mo, Einar O; Langmoen, Iver A
2015-09-22
Glioblastoma (GBM) is both the most common and the most lethal primary brain tumor. It is thought that GBM stem cells (GSCs) are critically important in resistance to therapy. Therefore, there is a strong rationale to target these cells in order to develop new molecular therapies.To identify molecular targets in GSCs, we compared gene expression in GSCs to that in neural stem cells (NSCs) from the adult human brain, using microarrays. Bioinformatic filtering identified 20 genes (PBK/TOPK, CENPA, KIF15, DEPDC1, CDC6, DLG7/DLGAP5/HURP, KIF18A, EZH2, HMMR/RHAMM/CD168, NOL4, MPP6, MDM1, RAPGEF4, RHBDD1, FNDC3B, FILIP1L, MCC, ATXN7L4/ATXN7L1, P2RY5/LPAR6 and FAM118A) that were consistently expressed in GSC cultures and consistently not expressed in NSC cultures. The expression of these genes was confirmed in clinical samples (TCGA and REMBRANDT). The first nine genes were highly co-expressed in all GBM subtypes and were part of the same protein-protein interaction network. Furthermore, their combined up-regulation correlated negatively with patient survival in the mesenchymal GBM subtype. Using targeted proteomics and the COGNOSCENTE database we linked these genes to GBM signalling pathways.Nine genes: PBK, CENPA, KIF15, DEPDC1, CDC6, DLG7, KIF18A, EZH2 and HMMR should be further explored as targets for treatment of GBM.
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HIGÓN, MELISSA; COWAN, GRAEME; NAUSCH, NORMAN; CAVANAGH, DAVID; OLEAGA, ANA; TOLEDO, RAFAEL; STOTHARD, J. RUSSELL; ANTÚNEZ, ORETO; MARCILLA, ANTONIO; BURCHMORE, RICHARD; MUTAPI, FRANCISCA
2011-01-01
SUMMARY With the current paucity of vaccine targets for parasitic diseases, particularly those in childhood, the aim of this study was to compare protein expression and immune cross-reactivity between the trematodes Schistosoma haematobium, S. bovis and Echinostoma caproni in the hope of identifying novel intervention targets. Native adult parasite proteins were separated by 2-dimensional gel electrophoresis and identified through electrospray ionisation tandem mass spectrometry to produce a reference gel. Proteins from differential gel electrophoresis analyses of the three parasite proteomes were compared and screened against sera from hamsters infected with S. haematobium and E. caproni following 2-dimensional Western blotting. Differential protein expression between the three species was observed with circa 5% of proteins from S. haematobium showing expression up-regulation compared to the other two species. There was 91% similarity between the proteomes of the two Schistosoma species and 81% and 78·6% similarity between S. haematobium and S. bovis versus E. caproni, respectively. Although there were some common cross-species antigens, species-species targets were revealed which, despite evolutionary homology, could be due to phenotypic plasticity arising from different host-parasite relationships. Nevertheless, this approach helps to identify novel intervention targets which could be used as broad-spectrum candidates for future use in human and veterinary vaccines. PMID:21729355
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Targeted Feature Detection for Data-Dependent Shotgun Proteomics
2017-01-01
Label-free quantification of shotgun LC–MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that directly targets identified peptides (minimizing missing values) but also offers robustness against false-positive features (by assigning meaningful confidence scores) would thus be highly desirable. We developed a new feature detection algorithm within the OpenMS software framework, leveraging ideas and algorithms from the OpenSWATH toolset for DIA/SRM data analysis. Our software, FeatureFinderIdentification (“FFId”), implements a targeted approach to feature detection based on information from identified peptides. This information is encoded in an MS1 assay library, based on which ion chromatogram extraction and detection of feature candidates are carried out. Significantly, when analyzing data from experiments comprising multiple samples, our approach distinguishes between “internal” and “external” (inferred) peptide identifications (IDs) for each sample. On the basis of internal IDs, two sets of positive (true) and negative (decoy) feature candidates are defined. A support vector machine (SVM) classifier is then trained to discriminate between the sets and is subsequently applied to the “uncertain” feature candidates from external IDs, facilitating selection and confidence scoring of the best feature candidate for each peptide. This approach also enables our algorithm to estimate the false discovery rate (FDR) of the feature selection step. We validated FFId based on a public benchmark data set, comprising a yeast cell lysate spiked with protein standards
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Chemical proteomics for target discovery of head-to-tail cyclized mini-proteins
NASA Astrophysics Data System (ADS)
Hellinger, Roland; Thell, Kathrin; Vasileva, Mina; Muhammad, Taj; Gunasekera, Sunithi; Kümmel, Daniel; Göransson, Ulf; Becker, Christian W.; Gruber, Christian W.
2017-10-01
Target deconvolution is one of the most challenging tasks in drug discovery, but a key step in drug development. In contrast to small molecules, there is a lack of validated and robust methodologies for target elucidation of peptides. In particular, it is difficult to apply these methods to cyclic and cysteine-stabilized peptides since they exhibit reduced amenability to chemical modification and affinity capture; however, such ribosomal synthesized and post-translationally modified peptide natural products are rich sources of promising drug candidates. For example, plant-derived circular peptides called cyclotides have recently attracted much attention due to their immunosuppressive effects and oral activity in the treatment of multiple sclerosis in mice, but their molecular target has hitherto not been reported. In this study a chemical proteomics approach using photo-affinity crosslinking was developed to determine a target of the circular peptide [T20K]kalata B1. Using this prototypic nature-derived peptide enabled the identification of a possible modulation of 14-3-3 proteins. This biochemical interaction was validated via competition pull down assays as well as a cellular reporter assay indicating an effect on 14-3-3-dependent transcriptional activity. As proof of concept, the presented approach may be applicable for target elucidation of various cyclic peptides and mini-proteins, in particular cyclotides, which represent a promising class of molecules in drug discovery and development.
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Time-course human urine proteomics in space-flight simulation experiments.
Binder, Hans; Wirth, Henry; Arakelyan, Arsen; Lembcke, Kathrin; Tiys, Evgeny S; Ivanisenko, Vladimir A; Kolchanov, Nikolay A; Kononikhin, Alexey; Popov, Igor; Nikolaev, Evgeny N; Pastushkova, Lyudmila; Larina, Irina M
2014-01-01
Long-term space travel simulation experiments enabled to discover different aspects of human metabolism such as the complexity of NaCl salt balance. Detailed proteomics data were collected during the Mars105 isolation experiment enabling a deeper insight into the molecular processes involved. We studied the abundance of about two thousand proteins extracted from urine samples of six volunteers collected weekly during a 105-day isolation experiment under controlled dietary conditions including progressive reduction of salt consumption. Machine learning using Self Organizing maps (SOM) in combination with different analysis tools was applied to describe the time trajectories of protein abundance in urine. The method enables a personalized and intuitive view on the physiological state of the volunteers. The abundance of more than one half of the proteins measured clearly changes in the course of the experiment. The trajectory splits roughly into three time ranges, an early (week 1-6), an intermediate (week 7-11) and a late one (week 12-15). Regulatory modes associated with distinct biological processes were identified using previous knowledge by applying enrichment and pathway flow analysis. Early protein activation modes can be related to immune response and inflammatory processes, activation at intermediate times to developmental and proliferative processes and late activations to stress and responses to chemicals. The protein abundance profiles support previous results about alternative mechanisms of salt storage in an osmotically inactive form. We hypothesize that reduced NaCl consumption of about 6 g/day presumably will reduce or even prevent the activation of inflammatory processes observed in the early time range of isolation. SOM machine learning in combination with analysis methods of class discovery and functional annotation enable the straightforward analysis of complex proteomics data sets generated by means of mass spectrometry.
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Ellis, Matthew J; Gillette, Michael; Carr, Steven A; Paulovich, Amanda G; Smith, Richard D; Rodland, Karin K; Townsend, R Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel C
2013-10-01
The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Weckwerth, Wolfram; Baginsky, Sacha; Van Wijk, Klass
2009-12-01
In the past 10 years, we have witnessed remarkable advances in the field of plant molecular biology. The rapid development of proteomic technologies and the speed with which these techniques have been applied to the field have altered our perception of how we can analyze proteins in complex systems. At nearly the same time, the availability of the complete genome for the model plant Arabidopsis thaliana was released; this effort provides an unsurpassed resource for the identification of proteins when researchers use MS to analyze plant samples. Recognizing the growth in this area, the Multinational Arabidopsis Steering Committee (MASC) establishedmore » a subcommittee for A. thaliana proteomics in 2006 with the objective of consolidating databases, technique standards, and experimentally validated candidate genes and functions. Since the establishment of the Multinational Arabidopsis Steering Subcommittee for Proteomics (MASCP), many new approaches and resources have become available. Recently, the subcommittee established a webpage to consolidate this information (www.masc-proteomics.org). It includes links to plant proteomic databases, general information about proteomic techniques, meeting information, a summary of proteomic standards, and other relevant resources. Altogether, this website provides a useful resource for the Arabidopsis proteomics community. In the future, the website will host discussions and investigate the cross-linking of databases. The subcommittee members have extensive experience in arabidopsis proteomics and collectively have produced some of the most extensive proteomics data sets for this model plant (Table S1 in the Supporting Information has a list of resources). The largest collection of proteomics data from a single study in A. thaliana was assembled into an accessible database (AtProteome; http://fgcz-atproteome.unizh.ch/index.php) and was recently published by the Baginsky lab.1 The database provides links to major Arabidopsis
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Comparative and Quantitative Global Proteomics Approaches: An Overview
Deracinois, Barbara; Flahaut, Christophe; Duban-Deweer, Sophie; Karamanos, Yannis
2013-01-01
Proteomics became a key tool for the study of biological systems. The comparison between two different physiological states allows unravelling the cellular and molecular mechanisms involved in a biological process. Proteomics can confirm the presence of proteins suggested by their mRNA content and provides a direct measure of the quantity present in a cell. Global and targeted proteomics strategies can be applied. Targeted proteomics strategies limit the number of features that will be monitored and then optimise the methods to obtain the highest sensitivity and throughput for a huge amount of samples. The advantage of global proteomics strategies is that no hypothesis is required, other than a measurable difference in one or more protein species between the samples. Global proteomics methods attempt to separate quantify and identify all the proteins from a given sample. This review highlights only the different techniques of separation and quantification of proteins and peptides, in view of a comparative and quantitative global proteomics analysis. The in-gel and off-gel quantification of proteins will be discussed as well as the corresponding mass spectrometry technology. The overview is focused on the widespread techniques while keeping in mind that each approach is modular and often recovers the other. PMID:28250403
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Pedreschi, Romina; Nørgaard, Jørgen; Maquet, Alain
2012-01-01
There is a need for selective and sensitive methods to detect the presence of food allergens at trace levels in highly processed food products. In this work, a combination of non-targeted and targeted proteomics approaches are used to illustrate the difficulties encountered in the detection of the major peanut allergens Ara h 1, Ara h 2 and Ara h 3 from a representative processed food matrix. Shotgun proteomics was employed for selection of the proteotypic peptides for targeted approaches via selective reaction monitoring. Peanut presence through detection of the proteotypic Ara h 3/4 peptides AHVQVVDSNGNR (m/z 432.5, 3+) and SPDIYNPQAGSLK (m/z 695.4, 2+) was confirmed and the developed method was able to detect peanut presence at trace levels (≥10 μg peanut g−1 matrix) in baked cookies. PMID:22413066
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Maryáš, Josef; Faktor, Jakub; Dvořáková, Monika; Struhárová, Iva; Grell, Peter; Bouchal, Pavel
2014-03-01
Metastases are responsible for most of the cases of death in patients with solid tumors. There is thus an urgent clinical need of better understanding the exact molecular mechanisms and finding novel therapeutics targets and biomarkers of metastatic disease of various tumors. Metastases are formed in a complicated biological process called metastatic cascade. Up to now, proteomics has enabled the identification of number of metastasis-associated proteins and potential biomarkers in cancer tissues, microdissected cells, model systems, and secretomes. Expression profiles and biological role of key proteins were confirmed in verification and functional experiments. This communication reviews these observations and analyses the methodological aspects of the proteomics approaches used. Moreover, it reviews contribution of current proteomics in the field of functional characterization and interactome analysis of proteins involved in various events in metastatic cascade. It is evident that ongoing technical progress will further increase proteome coverage and sample capacity of proteomics technologies, giving complex answers to clinical and functional questions asked. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Li, Guo-Chun; Zhang, Lina; Yu, Ming; Jia, Haiyu; Tian, Ting; Wang, Junqin; Wang, Fuqiang; Zhou, Ling
2017-01-01
The systematic mechanisms of acute intracerebral hemorrhage are still unknown and unverified, although many recent researches have indicated the secondary insults. This study was aimed to disclose the pathological mechanism and identify novel biomarker and therapeutic target candidates by plasma proteome. Patients with AICH (n = 8) who demographically matched healthy controls (n = 4) were prospectively enrolled, and their plasma samples were obtained. The TMT-LC-MS/MS-based proteomics approach was used to quantify the differential proteome across plasma samples, and the results were analyzed by Ingenuity Pathway Analysis to explore canonical pathways and the relationship involved in the uploaded data. Compared with healthy controls, there were 31 differentially expressed proteins in the ICH group ( P < 0.05), of which 21 proteins increased while 10 proteins decreased in abundance. These proteins are involved in 21 canonical pathways. One network with high confidence level was selected by the function network analysis, in which 23 proteins, P38MAPK and NFκB signaling pathways participated. Upstream regulator analysis found two regulators, IL6 and TNF, with an activation z -score. Seven biomarker candidates: APCS, FGB, LBP, MGMT, IGFBP2, LYZ, and APOA4 were found. Six candidate proteins were selected to assess the validity of the results by subsequent Western blotting analysis. Our analysis provided several intriguing pathways involved in ICH, like LXR/RXR activation, acute phase response signaling, and production of NO and ROS in macrophages pathways. The three upstream regulators: IL-6, TNF, LPS, and seven biomarker candidates: APCS, APOA4, FGB, IGFBP2, LBP, LYZ, and MGMT were uncovered. LPS, APOA4, IGFBP2, LBP, LYZ, and MGMT are novel potential biomarkers in ICH development. The identified proteins and pathways provide new perspectives to the potential pathological mechanism and therapeutic targets underlying ICH.
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Effects of Hypertension and Exercise on Cardiac Proteome Remodelling
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
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In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line.
Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R; Shen, Han-Ming; Lin, Qingsong
2016-02-26
To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQ(TM) quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway Analysis(TM) (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death.
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In situ Proteomic Profiling of Curcumin Targets in HCT116 Colon Cancer Cell Line
Wang, Jigang; Zhang, Jianbin; Zhang, Chong-Jing; Wong, Yin Kwan; Lim, Teck Kwang; Hua, Zi-Chun; Liu, Bin; Tannenbaum, Steven R.; Shen, Han-Ming; Lin, Qingsong
2016-01-01
To date, the exact targets and mechanism of action of curcumin, a natural product with anti-inflammatory and anti-cancer properties, remain elusive. Here we synthesized a cell permeable curcumin probe (Cur-P) with an alkyne moiety, which can be tagged with biotin for affinity enrichment, or with a fluorescent dye for visualization of the direct-binding protein targets of curcumin in situ. iTRAQTM quantitative proteomics approach was applied to distinguish the specific binding targets from the non-specific ones. In total, 197 proteins were confidently identified as curcumin binding targets from HCT116 colon cancer cell line. Gene Ontology analysis showed that the targets are broadly distributed and enriched in the nucleus, mitochondria and plasma membrane, and they are involved in various biological functions including metabolic process, regulation, response to stimulus and cellular process. Ingenuity Pathway AnalysisTM (IPA) suggested that curcumin may exert its anticancer effects over multiple critical biological pathways including the EIF2, eIF4/p70S6K, mTOR signaling and mitochondrial dysfunction pathways. Functional validations confirmed that curcumin downregulates cellular protein synthesis, and induces autophagy, lysosomal activation and increased ROS production, thus leading to cell death. PMID:26915414
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Proteomics Analysis of Nucleolar SUMO-1 Target Proteins upon Proteasome Inhibition*
Matafora, Vittoria; D'Amato, Alfonsina; Mori, Silvia; Blasi, Francesco; Bachi, Angela
2009-01-01
Many cellular processes are regulated by the coordination of several post-translational modifications that allow a very fine modulation of substrates. Recently it has been reported that there is a relationship between sumoylation and ubiquitination. Here we propose that the nucleolus is the key organelle in which SUMO-1 conjugates accumulate in response to proteasome inhibition. We demonstrated that, upon proteasome inhibition, the SUMO-1 nuclear dot localization is redirected to nucleolar structures. To better understand this process we investigated, by quantitative proteomics, the effect of proteasome activity on endogenous nucleolar SUMO-1 targets. 193 potential SUMO-1 substrates were identified, and interestingly in several purified SUMO-1 conjugates ubiquitin chains were found to be present, confirming the coordination of these two modifications. 23 SUMO-1 targets were confirmed by an in vitro sumoylation reaction performed on nuclear substrates. They belong to protein families such as small nuclear ribonucleoproteins, heterogeneous nuclear ribonucleoproteins, ribosomal proteins, histones, RNA-binding proteins, and transcription factor regulators. Among these, histone H1, histone H3, and p160 Myb-binding protein 1A were further characterized as novel SUMO-1 substrates. The analysis of the nature of the SUMO-1 targets identified in this study strongly indicates that sumoylation, acting in coordination with the ubiquitin-proteasome system, regulates the maintenance of nucleolar integrity. PMID:19596686
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Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin
Dai, Shao-Xing; Li, Wen-Xing
2016-01-01
Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view. PMID:26989626
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Dai, Shao-Xing; Li, Wen-Xing; Li, Gong-Hua; Huang, Jing-Fei
2016-01-01
Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view.
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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.
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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
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Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi
2012-01-01
Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive
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Tetrazine ligation for chemical proteomics.
Kang, Kyungtae; Park, Jongmin; Kim, Eunha
2016-01-01
Determining small molecule-target protein interaction is essential for the chemical proteomics. One of the most important keys to explore biological system in chemical proteomics field is finding first-class molecular tools. Chemical probes can provide great spatiotemporal control to elucidate biological functions of proteins as well as for interrogating biological pathways. The invention of bioorthogonal chemistry has revolutionized the field of chemical biology by providing superior chemical tools and has been widely used for investigating the dynamics and function of biomolecules in live condition. Among 20 different bioorthogonal reactions, tetrazine ligation has been spotlighted as the most advanced bioorthogonal chemistry because of their extremely faster kinetics and higher specificity than others. Therefore, tetrazine ligation has a tremendous potential to enhance the proteomic research. This review highlights the current status of tetrazine ligation reaction as a molecular tool for the chemical proteomics.
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Pressurized Pepsin Digestion in Proteomics
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
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A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets.
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
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Pérez-Bercoff, Lena; Valentini, Davide; Gaseitsiwe, Simani; Mahdavifar, Shahnaz; Schutkowski, Mike; Poiret, Thomas; Pérez-Bercoff, Åsa; Ljungman, Per; Maeurer, Markus J.
2014-01-01
Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution. PMID:24740411
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Proteogenomics Dashboard for the Human Proteome Project.
Tabas-Madrid, Daniel; Alves-Cruzeiro, Joao; Segura, Victor; Guruceaga, Elizabeth; Vialas, Vital; Prieto, Gorka; García, Carlos; Corrales, Fernando J; Albar, Juan Pablo; Pascual-Montano, Alberto
2015-09-04
dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.
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Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM).
Demeure, Kevin; Fack, Fred; Duriez, Elodie; Tiemann, Katja; Bernard, Amandine; Golebiewska, Anna; Bougnaud, Sébastien; Bjerkvig, Rolf; Domon, Bruno; Niclou, Simone P
2016-02-01
Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future
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Targeted Proteomics to Assess the Response to Anti-Angiogenic Treatment in Human Glioblastoma (GBM)*
Demeure, Kevin; Fack, Fred; Duriez, Elodie; Tiemann, Katja; Bernard, Amandine; Golebiewska, Anna; Bougnaud, Sébastien; Bjerkvig, Rolf; Domon, Bruno; Niclou, Simone P.
2016-01-01
Glioblastoma (GBM) is a highly aggressive primary brain tumor with dismal outcome for affected patients. Because of the significant neo-angiogenesis exhibited by GBMs, anti-angiogenic therapies have been intensively evaluated during the past years. Recent clinical studies were however disappointing, although a subpopulation of patients may benefit from such treatment. We have previously shown that anti-angiogenic targeting in GBM increases hypoxia and leads to a metabolic adaptation toward glycolysis, suggesting that combination treatments also targeting the glycolytic phenotype may be effective in GBM patients. The aim of this study was to identify marker proteins that are altered by treatment and may serve as a short term readout of anti-angiogenic therapy. Ultimately such proteins could be tested as markers of efficacy able to identify patient subpopulations responsive to the treatment. We applied a proteomics approach based on selected reaction monitoring (SRM) to precisely quantify targeted protein candidates, selected from pathways related to metabolism, apoptosis and angiogenesis. The workflow was developed in the context of patient-derived intracranial GBM xenografts developed in rodents and ensured the specific identification of human tumor versus rodent stroma-derived proteins. Quality control experiments were applied to assess sample heterogeneity and reproducibility of SRM assays at different levels. The data demonstrate that tumor specific proteins can be precisely quantified within complex biological samples, reliably identifying small concentration differences induced by the treatment. In line with previous work, we identified decreased levels of TCA cycle enzymes, including isocitrate dehydrogenase, whereas malectin, calnexin, and lactate dehydrogenase A were augmented after treatment. We propose the most responsive proteins of our subset as potential novel biomarkers to assess treatment response after anti-angiogenic therapy that warrant future
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Proteomics in the genome engineering era.
Vandemoortele, Giel; Gevaert, Kris; Eyckerman, Sven
2016-01-01
Genome engineering experiments used to be lengthy, inefficient, and often expensive, preventing a widespread adoption of such experiments for the full assessment of endogenous protein functions. With the revolutionary clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 technology, genome engineering became accessible to the broad life sciences community and is now implemented in several research areas. One particular field that can benefit significantly from this evolution is proteomics where a substantial impact on experimental design and general proteome biology can be expected. In this review, we describe the main applications of genome engineering in proteomics, including the use of engineered disease models and endogenous epitope tagging. In addition, we provide an overview on current literature and highlight important considerations when launching genome engineering technologies in proteomics workflows. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Pan, Sheng; Rush, John; Peskind, Elaine R; Galasko, Douglas; Chung, Kathryn; Quinn, Joseph; Jankovic, Joseph; Leverenz, James B; Zabetian, Cyrus; Pan, Catherine; Wang, Yan; Oh, Jung Hun; Gao, Jean; Zhang, Jianpeng; Montine, Thomas; Zhang, Jing
2008-02-01
Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.
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Genomes2Drugs: Identifies Target Proteins and Lead Drugs from Proteome Data
Toomey, David; Hoppe, Heinrich C.; Brennan, Marian P.; Nolan, Kevin B.; Chubb, Anthony J.
2009-01-01
Background Genome sequencing and bioinformatics have provided the full hypothetical proteome of many pathogenic organisms. Advances in microarray and mass spectrometry have also yielded large output datasets of possible target proteins/genes. However, the challenge remains to identify new targets for drug discovery from this wealth of information. Further analysis includes bioinformatics and/or molecular biology tools to validate the findings. This is time consuming and expensive, and could fail to yield novel drugs if protein purification and crystallography is impossible. To pre-empt this, a researcher may want to rapidly filter the output datasets for proteins that show good homology to proteins that have already been structurally characterised or proteins that are already targets for known drugs. Critically, those researchers developing novel antibiotics need to select out the proteins that show close homology to any human proteins, as future inhibitors are likely to cross-react with the host protein, causing off-target toxicity effects later in clinical trials. Methodology/Principal Findings To solve many of these issues, we have developed a free online resource called Genomes2Drugs which ranks sequences to identify proteins that are (i) homologous to previously crystallized proteins or (ii) targets of known drugs, but are (iii) not homologous to human proteins. When tested using the Plasmodium falciparum malarial genome the program correctly enriched the ranked list of proteins with known drug target proteins. Conclusions/Significance Genomes2Drugs rapidly identifies proteins that are likely to succeed in drug discovery pipelines. This free online resource helps in the identification of potential drug targets. Importantly, the program further highlights proteins that are likely to be inhibited by FDA-approved drugs. These drugs can then be rapidly moved into Phase IV clinical studies under ‘change-of-application’ patents. PMID:19593435
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PatternLab for proteomics 4.0: A one-stop shop for analyzing shotgun proteomic data
Carvalho, Paulo C; Lima, Diogo B; Leprevost, Felipe V; Santos, Marlon D M; Fischer, Juliana S G; Aquino, Priscila F; Moresco, James J; Yates, John R; Barbosa, Valmir C
2017-01-01
PatternLab for proteomics is an integrated computational environment that unifies several previously published modules for analyzing shotgun proteomic data. PatternLab contains modules for formatting sequence databases, performing peptide spectrum matching, statistically filtering and organizing shotgun proteomic data, extracting quantitative information from label-free and chemically labeled data, performing statistics for differential proteomics, displaying results in a variety of graphical formats, performing similarity-driven studies with de novo sequencing data, analyzing time-course experiments, and helping with the understanding of the biological significance of data in the light of the Gene Ontology. Here we describe PatternLab for proteomics 4.0, which closely knits together all of these modules in a self-contained environment, covering the principal aspects of proteomic data analysis as a freely available and easily installable software package. All updates to PatternLab, as well as all new features added to it, have been tested over the years on millions of mass spectra. PMID:26658470
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Akala, Hoseah M.; Macharia, Rosaline W.; Juma, Dennis W.; Cheruiyot, Agnes C.; Andagalu, Ben; Brown, Mathew L.; El-Shemy, Hany A.; Nyanjom, Steven G.
2017-01-01
Malaria causes about half a million deaths annually, with Plasmodium falciparum being responsible for 90% of all the cases. Recent reports on artemisinin resistance in Southeast Asia warrant urgent discovery of novel drugs for the treatment of malaria. However, most bioactive compounds fail to progress to treatments due to safety concerns. Drug repositioning offers an alternative strategy where drugs that have already been approved as safe for other diseases could be used to treat malaria. This study screened approved drugs for antimalarial activity using an in silico chemogenomics approach prior to in vitro verification. All the P. falciparum proteins sequences available in NCBI RefSeq were mined and used to perform a similarity search against DrugBank, TTD and STITCH databases to identify similar putative drug targets. Druggability indices of the potential P. falciparum drug targets were obtained from TDR targets database. Functional amino acid residues of the drug targets were determined using ConSurf server which was used to fine tune the similarity search. This study predicted 133 approved drugs that could target 34 P. falciparum proteins. A literature search done at PubMed and Google Scholar showed 105 out of the 133 drugs to have been previously tested against malaria, with most showing activity. For further validation, drug susceptibility assays using SYBR Green I method were done on a representative group of 10 predicted drugs, eight of which did show activity against P. falciparum 3D7 clone. Seven had IC50 values ranging from 1 μM to 50 μM. This study also suggests drug-target association and hence possible mechanisms of action of drugs that did show antiplasmodial activity. The study results validate the use of proteome-wide target similarity approach in identifying approved drugs with activity against P. falciparum and could be adapted for other pathogens. PMID:29088219
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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
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Monneuse, Jean-Marc; Sugano, Madeleine; Becue, Thierry; Santoni, Véronique; Hem, Sonia; Rossignol, Michel
2011-05-01
Plant membranes bear a variety of transporters belonging to multigene families that are affected by environmental and nutritional conditions. In addition, they often display high-sequence identity, making difficult in-depth investigation by current shot-gun strategies. In this study, we set up a targeted proteomics approach aimed at identifying and quantifying within single experiments the five major proton pumps of the autoinhibited H(+) ATPases (AHA) family, the 13 plasma membrane intrinsic proteins (PIP) water channels (PIPs), and ten members of ammonium transporters (AMTs) and nitrate transporter (NRT) families. Proteotypic peptides were selected and isotopically labeled heavy versions were used for technical optimization and for quantification of the corresponding light version in biological samples. This approach allowed to quantify simultaneously nine PIPs in leaf membranes and 13 PIPs together with three autoinhibited H(+) ATPases, two ammonium transporters, and two NRTs in root membranes. Similarly, it was used to investigate the effect of a salt stress on the expression of these latter 20 transporters in roots. These novel isoform-specific data were compared with published transcriptome information and revealed a close correlation between PIP isoforms and transcripts levels. The obtained resource is reusable and can be expanded to other transporter families for large-scale profiling of membrane transporters. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Litou, Zoi I.; Konstandi, Ourania A.; Giannopoulou, Aikaterini F.; Anastasiadou, Ema; Voutsinas, Gerassimos E.; Tsangaris, George Th.; Stravopodis, Dimitrios J.
2017-01-01
Cutaneous melanoma is a malignant tumor of skin melanocytes that are pigment-producing cells located in the basal layer (stratum basale) of epidermis. Accumulation of genetic mutations within their oncogenes or tumor-suppressor genes compels melanocytes to aberrant proliferation and spread to distant organs of the body, thereby resulting in severe and/or lethal malignancy. Metastatic melanoma’s heavy mutational load, molecular heterogeneity and resistance to therapy necessitate the development of novel biomarkers and drug-based protocols that target key proteins involved in perpetuation of the disease. To this direction, we have herein employed a nano liquid chromatography-tandem mass spectrometry (nLC-MS/MS) proteomics technology to profile the deep-proteome landscape of WM-266-4 human metastatic melanoma cells. Our advanced melanoma-specific catalogue proved to contain 6,681 unique proteins, which likely constitute the hitherto largest single cell-line-derived proteomic collection of the disease. Through engagement of UNIPROT, DAVID, KEGG, PANTHER, INTACT, CYTOSCAPE, dbEMT and GAD bioinformatics resources, WM-266-4 melanoma proteins were categorized according to their sub-cellular compartmentalization, function and tumorigenicity, and successfully reassembled in molecular networks and interactomes. The obtained data dictate the presence of plastically inter-converted sub-populations of non-cancer and cancer stem cells, and also indicate the oncoproteomic resemblance of melanoma to glioma and lung cancer. Intriguingly, WM-266-4 cells seem to be subjected to both epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial (MET) programs, with 1433G and ADT3 proteins being identified in the EMT/MET molecular interface. Oncogenic addiction of WM-266-4 cells to autocrine/paracrine signaling of IL17-, DLL3-, FGF(2/13)- and OSTP-dependent sub-routines suggests their critical contribution to the metastatic melanoma chemotherapeutic refractoriness. Interestingly, the
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Xu, Feifei; Yang, Ting; Sheng, Yuan; Zhong, Ting; Yang, Mi; Chen, Yun
2014-12-05
As one of the most studied post-translational modifications (PTM), protein phosphorylation plays an essential role in almost all cellular processes. Current methods are able to predict and determine thousands of phosphorylation sites, whereas stoichiometric quantification of these sites is still challenging. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted proteomics is emerging as a promising technique for site-specific quantification of protein phosphorylation using proteolytic peptides as surrogates of proteins. However, several issues may limit its application, one of which relates to the phosphopeptides with different phosphorylation sites and the same mass (i.e., isobaric phosphopeptides). While employment of site-specific product ions allows for these isobaric phosphopeptides to be distinguished and quantified, site-specific product ions are often absent or weak in tandem mass spectra. In this study, linear algebra algorithms were employed as an add-on to targeted proteomics to retrieve information on individual phosphopeptides from their common spectra. To achieve this simultaneous quantification, a LC-MS/MS-based targeted proteomics assay was first developed and validated for each phosphopeptide. Given the slope and intercept of calibration curves of phosphopeptides in each transition, linear algebraic equations were developed. Using a series of mock mixtures prepared with varying concentrations of each phosphopeptide, the reliability of the approach to quantify isobaric phosphopeptides containing multiple phosphorylation sites (≥ 2) was discussed. Finally, we applied this approach to determine the phosphorylation stoichiometry of heat shock protein 27 (HSP27) at Ser78 and Ser82 in breast cancer cells and tissue samples.
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Zougman, Alexandre; Banks, Rosamonde E
2015-01-01
Recently we introduced the concept of Suspension Trapping (STrap) for bottom-up proteomics sample processing that is based upon SDS-mediated protein extraction, swift detergent removal and rapid reactor-type protein digestion in a quartz depth filter trap. As the depth filter surface is made of silica, it is readily modifiable with various functional groups using the silane coupling chemistries. Thus, during the digest, peptides possessing specific features could be targeted for enrichment by the functionalized depth filter material while non-targeted peptides could be collected as an unbound distinct fraction after the digest. In the example presented here the quartz depth filter surface is functionalized with the pyridyldithiol group therefore enabling reversible in-situ capture of the cysteine-containing peptides generated during the STrap-based digest. The described C-STrap method retains all advantages of the original STrap methodology and provides robust foundation for the conception of the targeted in-situ peptide fractionation in the STrap format for bottom-up proteomics. The presented data support the method's use in qualitative and semi-quantitative proteomics experiments.
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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.
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Levitt, Joseph E.; Rogers, Angela J.
2017-01-01
The acute respiratory distress syndrome (ARDS) is a common cause of acute respiratory failure, and is associated with substantial mortality and morbidity. Dozens of clinical trials targeting ARDS have failed, with no drug specifically targeting lung injury in widespread clinical use. Thus, the need for drug development in ARDS is great. Targeted proteomic studies in ARDS have identified many key pathways in the disease, including inflammation, epithelial injury, endothelial injury or activation, and disordered coagulation and repair. Recent studies reveal the potential for proteomic changes to identify novel subphenotypes of ARDS patients who may be most likely to respond to therapy and could thus be targeted for enrollment in clinical trials. Nontargeted studies of proteomics in ARDS are just beginning and have the potential to identify novel drug targets and key pathways in the disease. Proteomics will play an important role in phenotyping of patients and developing novel therapies for ARDS in the future. PMID:27031735
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ProCon - PROteomics CONversion tool.
Mayer, Gerhard; Stephan, Christian; Meyer, Helmut E; Kohl, Michael; Marcus, Katrin; Eisenacher, Martin
2015-11-03
With the growing amount of experimental data produced in proteomics experiments and the requirements/recommendations of journals in the proteomics field to publicly make available data described in papers, a need for long-term storage of proteomics data in public repositories arises. For such an upload one needs proteomics data in a standardized format. Therefore, it is desirable, that the proprietary vendor's software will integrate in the future such an export functionality using the standard formats for proteomics results defined by the HUPO-PSI group. Currently not all search engines and analysis tools support these standard formats. In the meantime there is a need to provide user-friendly free-to-use conversion tools that can convert the data into such standard formats in order to support wet-lab scientists in creating proteomics data files ready for upload into the public repositories. ProCon is such a conversion tool written in Java for conversion of proteomics identification data into standard formats mzIdentML and Pride XML. It allows the conversion of Sequest™/Comet .out files, of search results from the popular and often used ProteomeDiscoverer® 1.x (x=versions 1.1 to1.4) software and search results stored in the LIMS systems ProteinScape® 1.3 and 2.1 into mzIdentML and PRIDE XML. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.
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Progress on the HUPO Draft Human Proteome: 2017 Metrics of the Human Proteome Project.
Omenn, Gilbert S; Lane, Lydie; Lundberg, Emma K; Overall, Christopher M; Deutsch, Eric W
2017-12-01
The Human Proteome Organization (HUPO) Human Proteome Project (HPP) continues to make progress on its two overall goals: (1) completing the protein parts list, with an annual update of the HUPO draft human proteome, and (2) making proteomics an integrated complement to genomics and transcriptomics throughout biomedical and life sciences research. neXtProt version 2017-01-23 has 17 008 confident protein identifications (Protein Existence [PE] level 1) that are compliant with the HPP Guidelines v2.1 ( https://hupo.org/Guidelines ), up from 13 664 in 2012-12 and 16 518 in 2016-04. Remaining to be found by mass spectrometry and other methods are 2579 "missing proteins" (PE2+3+4), down from 2949 in 2016. PeptideAtlas 2017-01 has 15 173 canonical proteins, accounting for nearly all of the 15 290 PE1 proteins based on MS data. These resources have extensive data on PTMs, single amino acid variants, and splice isoforms. The Human Protein Atlas v16 has 10 492 highly curated protein entries with tissue and subcellular spatial localization of proteins and transcript expression. Organ-specific popular protein lists have been generated for broad use in quantitative targeted proteomics using SRM-MS or DIA-SWATH-MS studies of biology and disease.
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Proteomic approaches in cancer risk and response assessment.
Petricoin, Emanuel F; Liotta, Lance A
2004-02-01
Proteomics is more than just a list-generating exercise where increases or decreases in protein expression are identified. Proteomic technologies will ultimately characterize information-flow through the protein circuitry that interconnects the extracellular microenvironment to the serum or plasma macroenvironment through intracellular signaling systems and their control of gene transcription. The nature of this information can be a cause or a consequence of disease processes and how patients respond to therapy. Analysis of human cancer as a model for how proteomics can have an impact at the bedside can take advantage of several promising new proteomic technologies. These technologies are being developed for early detection and risk assessment, therapeutic targeting and patient-tailored therapy.
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Quantitative proteomics in biological research.
Wilm, Matthias
2009-10-01
Proteomics has enabled the direct investigation of biological material, at first through the analysis of individual proteins, then of lysates from cell cultures, and finally of extracts from tissues and biopsies from entire organisms. Its latest manifestation - quantitative proteomics - allows deeper insight into biological systems. This article reviews the different methods used to extract quantitative information from mass spectra. It follows the technical developments aimed toward global proteomics, the attempt to characterize every expressed protein in a cell by at least one peptide. When applications of the technology are discussed, the focus is placed on yeast biology. In particular, differential quantitative proteomics, the comparison between an experiment and its control, is very discriminating for proteins involved in the process being studied. When trying to understand biological processes on a molecular level, differential quantitative proteomics tends to give a clearer picture than global transcription analyses. As a result, MS has become an even more indispensable tool for biochemically motivated biological research.
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Zhou, Weixian; Xu, Feifei; Li, Danni; Chen, Yun
2018-03-01
Human epidermal growth factor receptor 2 (HER2)-positive breast cancer is a particularly aggressive type of the disease. To date, much evidence has indicated that accurate HER2 status detection is crucial for prognosis and treatment strategy selection. Thus, bioanalytical techniques for early and accurate detection of HER2 have the potential to improve patient care. Currently, the widely used immunohistochemical staining normally has problems with reproducibility and lack of standardization, resulting in poor concordance between laboratories. Aptamers are a good alternative, but the extent of their use in quantitative analysis of HER2 is limited because of the lack of effective detection methods. We developed a quasi-targeted proteomics assay and converted the HER2 signal into the mass response of reporter peptide by a combination of aptamer-peptide probe and LC-MS/MS. The selected aptamer-peptide probe consisted of aptamer HB5 and the substrate peptide GDKAVLGVDPFR that contained the reporter peptide AVLGVDPFR. After characterization of this newly synthesized probe (e.g., conjugation efficiency, stability, binding affinity, specificity, and digestion efficiency), probe binding and trypsin shaving conditions were optimized. The resulting limit of quantification for HER2 was 25 pmol/L. Then, the quasi-targeted proteomics assay was applied to determine the HER2 concentrations in the HER2-positive breast cancer cells BT474 and SK-BR-3, the HER2-negative breast cancer cells MDA-MB-231 and MCF-7, and 36 pairs of human breast primary tumors and adjacent normal tissue samples. The results were highly concordant with those obtained by immunohistochemistry with reflex testing by fluorescent in situ hybridization. Quasi-targeted proteomics can be a quantitative alternative for HER2 detection. © 2017 American Association for Clinical Chemistry.
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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
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A Proteomics View of the Molecular Mechanisms and Biomarkers of Glaucomatous Neurodegeneration
Tezel, Gülgün
2013-01-01
Despite improving understanding of glaucoma, key molecular players of neurodegeneration that can be targeted for treatment of glaucoma, or molecular biomarkers that can be useful for clinical testing, remain unclear. Proteomics technology offers a powerful toolbox to accomplish these important goals of the glaucoma research and is increasingly being applied to identify molecular mechanisms and biomarkers of glaucoma. Recent studies of glaucoma using proteomics analysis techniques have resulted in the lists of differentially expressed proteins in human glaucoma and animal models. The global analysis of protein expression in glaucoma has been followed by cell-specific proteome analysis of retinal ganglion cells and astrocytes. The proteomics data have also guided targeted studies to identify post-translational modifications and protein-protein interactions during glaucomatous neurodegeneration. In addition, recent applications of proteomics have provided a number of potential biomarker candidates. Proteomics technology holds great promise to move glaucoma research forward toward new treatment strategies and biomarker discovery. By reviewing the major proteomics approaches and their applications in the field of glaucoma, this article highlights the power of proteomics in translational and clinical research related to glaucoma and also provides a framework for future research to functionally test the importance of specific molecular pathways and validate candidate biomarkers. PMID:23396249
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Identification of BAG3 target proteins in anaplastic thyroid cancer cells by proteomic analysis.
Galdiero, Francesca; Bello, Anna Maria; Spina, Anna; Capiluongo, Anna; Liuu, Sophie; De Marco, Margot; Rosati, Alessandra; Capunzo, Mario; Napolitano, Maria; Vuttariello, Emilia; Monaco, Mario; Califano, Daniela; Turco, Maria Caterina; Chiappetta, Gennaro; Vinh, Joëlle; Chiappetta, Giovanni
2018-01-30
BAG3 protein is an apoptosis inhibitor and is highly expressed in Anaplastic Thyroid Cancer. We investigated the entire set of proteins modulated by BAG3 silencing in the human anaplastic thyroid 8505C cancer cells by using the Stable-Isotope Labeling by Amino acids in Cell culture strategy combined with mass spectrometry analysis. By this approach we identified 37 up-regulated and 54 down-regulated proteins in BAG3-silenced cells. Many of these proteins are reportedly involved in tumor progression, invasiveness and resistance to therapies. We focused our attention on an oncogenic protein, CAV1, and a tumor suppressor protein, SERPINB2, that had not previously been reported to be modulated by BAG3. Their expression levels in BAG3-silenced cells were confirmed by qRT-PCR and western blot analyses, disclosing two novel targets of BAG3 pro-tumor activity. We also examined the dataset of proteins obtained by the quantitative proteomics analysis using two tools, Downstream Effect Analysis and Upstream Regulator Analysis of the Ingenuity Pathways Analysis software. Our analyses confirm the association of the proteome profile observed in BAG3-silenced cells with an increase in cell survival and a decrease in cell proliferation and invasion, and highlight the possible involvement of four tumor suppressor miRNAs and TP53/63 proteins in BAG3 activity.
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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
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Ziegler, Yvonne S.; Moresco, James J.; Tu, Patricia G.; Yates, John R.; Nardulli, Ann M.
2014-01-01
The use of broad spectrum chemotherapeutic agents to treat breast cancer results in substantial and debilitating side effects, necessitating the development of targeted therapies to limit tumor proliferation and prevent metastasis. In recent years, the list of approved targeted therapies has expanded, and it includes both monoclonal antibodies and small molecule inhibitors that interfere with key proteins involved in the uncontrolled growth and migration of cancer cells. The targeting of plasma membrane proteins has been most successful to date, and this is reflected in the large representation of these proteins as targets of newer therapies. In view of these facts, experiments were designed to investigate the plasma membrane proteome of a variety of human breast cancer cell lines representing hormone-responsive, ErbB2 over-expressing and triple negative cell types, as well as a benign control. Plasma membranes were isolated by using an aqueous two-phase system, and the resulting proteins were subjected to mass spectrometry analysis. Overall, each of the cell lines expressed some unique proteins, and a number of proteins were expressed in multiple cell lines, but in patterns that did not always follow traditional clinical definitions of breast cancer type. From our data, it can be deduced that most cancer cells possess multiple strategies to promote uncontrolled growth, reflected in aberrant expression of tyrosine kinases, cellular adhesion molecules, and structural proteins. Our data set provides a very rich and complex picture of plasma membrane proteins present on breast cancer cells, and the sorting and categorizing of this data provides interesting insights into the biology, classification, and potential treatment of this prevalent and debilitating disease. PMID:25029196
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Friedman, David B
2012-01-01
All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.
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Proteomics of effector-triggered immunity (ETI) in plants.
Hurley, Brenden; Subramaniam, Rajagopal; Guttman, David S; Desveaux, Darrell
2014-01-01
Effector-triggered immunity (ETI) was originally termed gene-for-gene resistance and dates back to fundamental observations of flax resistance to rust fungi by Harold Henry Flor in the 1940s. Since then, genetic and biochemical approaches have defined our current understanding of how plant "resistance" proteins recognize microbial effectors. More recently, proteomic approaches have expanded our view of the protein landscape during ETI and contributed significant advances to our mechanistic understanding of ETI signaling. Here we provide an overview of proteomic techniques that have been used to study plant ETI including both global and targeted approaches. We discuss the challenges associated with ETI proteomics and highlight specific examples from the literature, which demonstrate how proteomics is advancing the ETI research field.
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Proteomics for understanding miRNA biology
Huang, Tai-Chung; Pinto, Sneha M.; Pandey, Akhilesh
2013-01-01
MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. PMID:23125164
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Schilmiller, Anthony L; Miner, Dennis P; Larson, Matthew; McDowell, Eric; Gang, David R; Wilkerson, Curtis; Last, Robert L
2010-07-01
Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces beta-caryophyllene and alpha-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells.
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Dal Piaz, Fabrizio; Cotugno, Roberta; Lepore, Laura; Vassallo, Antonio; Malafronte, Nicola; Lauro, Gianluigi; Bifulco, Giuseppe; Belisario, Maria Antonietta; De Tommasi, Nunziatina
2013-04-26
Oridonin, an ent-kaurane diterpene isolated from well known Chinese medicinal plant Isodon rubescens, has been shown to have multiple biological activities. Among them, the anticancer activity has been repeatedly reported by many research groups. The chemopreventive and antitumor effects of oridonin have been related to its ability to interfere with several pathways which are involved in cell proliferation, cell cycle arrest, apoptosis and/or autophagy. Despite the number of studies performed on this diterpene, the molecular mechanism underlying its cellular activity remains to be elucidated. Hence, we tried to mine target protein(s) of oridonin by employing a mass spectrometry-based chemical proteomics approach, providing evidences that oridonin is able to directly bind the multifunctional, stress-inducible heat shock protein 70 1A (HSP70 1A). Oridonin/HSP70 complex formation was confirmed in leukemia-derived Jurkat cells. The characterization of HSP70 inhibition by oridonin was performed using chemical and biological approaches. Moreover, the binding site of oridonin on the chaperone was identified by a mass-based approach combined with Molecular Dynamics simulations. Although natural products showed high efficiency and several of these agents have now entered in clinical trials, information concerning the mechanisms of action at a molecular level of many of them is very poor or completely missed. Nevertheless, the identification of the molecular target of a drug candidate has several advantages. The most significant is the ability to set up target-based assays and to allow structure-activity relationship studies to guide medicinal chemistry efforts towards lead optimization. The knowledge of drug targets can also facilitate the identification of potential toxicities or side effects, if there is any precedent of toxicities for the identified target. Achieving this in an effective, unbiased and efficient manner subsists as a significant challenge for the new era
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Shepherd, Danielle L; Hathaway, Quincy A; Nichols, Cody E; Durr, Andrya J; Pinti, Mark V; Hughes, Kristen M; Kunovac, Amina; Stine, Seth M; Hollander, John M
2018-06-01
>99% of the mitochondrial proteome is nuclear-encoded. The mitochondrion relies on a coordinated multi-complex process for nuclear genome-encoded mitochondrial protein import. Mitochondrial heat shock protein 70 (mtHsp70) is a key component of this process and a central constituent of the protein import motor. Type 2 diabetes mellitus (T2DM) disrupts mitochondrial proteomic signature which is associated with decreased protein import efficiency. The goal of this study was to manipulate the mitochondrial protein import process through targeted restoration of mtHsp70, in an effort to restore proteomic signature and mitochondrial function in the T2DM heart. A novel line of cardiac-specific mtHsp70 transgenic mice on the db/db background were generated and cardiac mitochondrial subpopulations were isolated with proteomic evaluation and mitochondrial function assessed. MicroRNA and epigenetic regulation of the mtHsp70 gene during T2DM were also evaluated. MtHsp70 overexpression restored cardiac function and nuclear-encoded mitochondrial protein import, contributing to a beneficial impact on proteome signature and enhanced mitochondrial function during T2DM. Further, transcriptional repression at the mtHsp70 genomic locus through increased localization of H3K27me3 during T2DM insult was observed. Our results suggest that restoration of a key protein import constituent, mtHsp70, provides therapeutic benefit through attenuation of mitochondrial and contractile dysfunction in T2DM. Copyright © 2018 Elsevier Ltd. All rights reserved.
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2015-01-01
Background Meningitis is the inflammation of the meninges in response to infection or chemical agents. While aseptic meningitis, most frequently caused by enteroviruses, is usually benign with a self-limiting course, bacterial meningitis remains associated with high morbidity and mortality rates, despite advances in antimicrobial therapy and intensive care. Fast and accurate differential diagnosis is crucial for assertive choice of the appropriate therapeutic approach for each form of meningitis. Methods We used 2D-PAGE and mass spectrometry to identify the cerebrospinal fluid proteome specifically related to the host response to pneumococcal, meningococcal, and enteroviral meningitis. The disease-specific proteome signatures were inspected by pathway analysis. Results Unique cerebrospinal fluid proteome signatures were found to the three aetiological forms of meningitis investigated, and a qualitative predictive model with four protein markers was developed for the differential diagnosis of these diseases. Nevertheless, pathway analysis of the disease-specific proteomes unveiled that Kallikrein-kinin system may play a crucial role in the pathophysiological mechanisms leading to brain damage in bacterial meningitis. Proteins taking part in this cellular process are proposed as putative targets to novel adjunctive therapies. Conclusions Comparative proteomics of cerebrospinal fluid disclosed candidate biomarkers, which were combined in a qualitative and sequential predictive model with potential to improve the differential diagnosis of pneumococcal, meningococcal and enteroviral meningitis. Moreover, we present the first evidence of the possible implication of Kallikrein-kinin system in the pathophysiology of bacterial meningitis. PMID:26040285
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Cordeiro, Ana Paula; Silva Pereira, Rosiane Aparecida; Chapeaurouge, Alex; Coimbra, Clarice Semião; Perales, Jonas; Oliveira, Guilherme; Sanchez Candiani, Talitah Michel; Coimbra, Roney Santos
2015-01-01
Meningitis is the inflammation of the meninges in response to infection or chemical agents. While aseptic meningitis, most frequently caused by enteroviruses, is usually benign with a self-limiting course, bacterial meningitis remains associated with high morbidity and mortality rates, despite advances in antimicrobial therapy and intensive care. Fast and accurate differential diagnosis is crucial for assertive choice of the appropriate therapeutic approach for each form of meningitis. We used 2D-PAGE and mass spectrometry to identify the cerebrospinal fluid proteome specifically related to the host response to pneumococcal, meningococcal, and enteroviral meningitis. The disease-specific proteome signatures were inspected by pathway analysis. Unique cerebrospinal fluid proteome signatures were found to the three aetiological forms of meningitis investigated, and a qualitative predictive model with four protein markers was developed for the differential diagnosis of these diseases. Nevertheless, pathway analysis of the disease-specific proteomes unveiled that Kallikrein-kinin system may play a crucial role in the pathophysiological mechanisms leading to brain damage in bacterial meningitis. Proteins taking part in this cellular process are proposed as putative targets to novel adjunctive therapies. Comparative proteomics of cerebrospinal fluid disclosed candidate biomarkers, which were combined in a qualitative and sequential predictive model with potential to improve the differential diagnosis of pneumococcal, meningococcal and enteroviral meningitis. Moreover, we present the first evidence of the possible implication of Kallikrein-kinin system in the pathophysiology of bacterial meningitis.
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Kawahara, Rebeca; Bollinger, James G.; Rivera, César; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Paes Leme, Adriana F.; MacCoss, Michael J.
2015-01-01
Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC. PMID:26552850
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What is proteomics? Proteomics is a highly automated and rapid method for measuring all the proteins in a biological sample. Proteins are the molecules that actually do most of the work inside a cell. When researchers develop cancer drugs, those drugs typically target proteins, so scientists and clinicians really have to understand what the proteins are doing. Proteomics researchers are now able to measure up to 10,000 proteins per tumor sample.
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Affinity Proteomics in the mountains: Alpbach 2015.
Taussig, Michael J
2016-09-25
The 2015 Alpbach Workshop on Affinity Proteomics, organised by the EU AFFINOMICS consortium, was the 7th workshop in this series. As in previous years, the focus of the event was the current state of affinity methods for proteome analysis, including complementarity with mass spectrometry, progress in recombinant binder production methods, alternatives to classical antibodies as affinity reagents, analysis of proteome targets, industry focus on biomarkers, and diagnostic and clinical applications. The combination of excellent science with Austrian mountain scenery and winter sports engender an atmosphere that makes this series of workshops exceptional. The articles in this Special Issue represent a cross-section of the presentations at the 2015 meeting. Copyright © 2016 Elsevier B.V. All rights reserved.
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Jackson, David; Bramwell, David
2013-12-16
Proteomics technologies can be effective for the discovery and assay of protein forms altered with disease. However, few examples of successful biomarker discovery yet exist. Critical to addressing this is the widespread implementation of appropriate QC (quality control) methodology. Such QC should combine the rigour of clinical laboratory assays with a suitable treatment of the complexity of the proteome by targeting separate assignable causes of variation. We demonstrate an approach, metric and example workflow for users to develop such targeted QC rules systematically and objectively, using a publicly available plasma DIGE data set. Hierarchical clustering analysis of standard channels is first used to discover correlated groups of features corresponding to specific assignable sources of technical variation. These effects are then quantified using a statistical distance metric, and followed on control charts. This allows measurement of process drift and the detection of runs that outlie for any given effect. A known technical issue on originally rejected gels was detected validating this approach, and relevant novel effects were also detected and classified effectively. Our approach was effective for 2-DE QC. Whilst we demonstrated this in a retrospective DIGE experiment, the principles would apply to ongoing QC and other proteomic technologies. This work asserts that properly carried out QC is essential to proteomics discovery experiments. Its significance is that it provides one possible novel framework for applying such methods, with a particular consideration of how to handle the complexity of the proteome. It not only focusses on 2DE-based methodology but also demonstrates general principles. A combination of results and discussion based upon a publicly available data set is used to illustrate the approach and allows a structured discussion of factors that experimenters may wish to bear in mind in other situations. The demonstration is on retrospective data
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Proteomics: a new approach to the study of disease.
Chambers, G; Lawrie, L; Cash, P; Murray, G I
2000-11-01
The global analysis of cellular proteins has recently been termed proteomics and is a key area of research that is developing in the post-genome era. Proteomics uses a combination of sophisticated techniques including two-dimensional (2D) gel electrophoresis, image analysis, mass spectrometry, amino acid sequencing, and bio-informatics to resolve comprehensively, to quantify, and to characterize proteins. The application of proteomics provides major opportunities to elucidate disease mechanisms and to identify new diagnostic markers and therapeutic targets. This review aims to explain briefly the background to proteomics and then to outline proteomic techniques. Applications to the study of human disease conditions ranging from cancer to infectious diseases are reviewed. Finally, possible future advances are briefly considered, especially those which may lead to faster sample throughput and increased sensitivity for the detection of individual proteins. Copyright 2000 John Wiley & Sons, Ltd.
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A proteomic landscape of diffuse-type gastric cancer.
Ge, Sai; Xia, Xia; Ding, Chen; Zhen, Bei; Zhou, Quan; Feng, Jinwen; Yuan, Jiajia; Chen, Rui; Li, Yumei; Ge, Zhongqi; Ji, Jiafu; Zhang, Lianhai; Wang, Jiayuan; Li, Zhongwu; Lai, Yumei; Hu, Ying; Li, Yanyan; Li, Yilin; Gao, Jing; Chen, Lin; Xu, Jianming; Zhang, Chunchao; Jung, Sung Yun; Choi, Jong Min; Jain, Antrix; Liu, Mingwei; Song, Lei; Liu, Wanlin; Guo, Gaigai; Gong, Tongqing; Huang, Yin; Qiu, Yang; Huang, Wenwen; Shi, Tieliu; Zhu, Weimin; Wang, Yi; He, Fuchu; Shen, Lin; Qin, Jun
2018-03-08
The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of 11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1-3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.
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Gunawardena, Harsha P.; Feltcher, Meghan E.; Wrobel, John A.; Gu, Sheng; Braunstein, Miriam; Chen, Xian
2015-01-01
The Mycobacterium tuberculosis (MTB) membrane is rich in antigens that are potential targets for diagnostics and the development of new vaccines. To better understand the mechanisms underlying MTB virulence and identify new targets for therapeutic intervention we investigated the differential composition of membrane proteomes between virulent M. tuberculosis H37Rv (MTB) and the Mycobacterium bovis BCG vaccine strain. To compare the membrane proteomes, we used LC-MS/MS analysis in combination with label-free quantitative (LFQ) proteomics, utilizing the area-under-curve (AUC) of the extracted ion chromatograms (XIC) of peptides obtained from m/z and retention time alignment of MS1 features. With this approach, we obtained relative abundance ratios for 2,203 identified membrane-associated proteins in high confidence. Of these proteins, 294 showed statistically significant differences of at least 2 fold, in relative abundance between MTB and BCG membrane fractions. Our comparative analysis detected several proteins associated with known genomic regions of difference between MTB and BCG as being absent, which validated the accuracy of our approach. In further support of our label-free quantitative data, we verified select protein differences by immunoblotting. To our knowledge we have generated the first comprehensive and high coverage profile of comparative membrane proteome changes between virulent MTB and its attenuated relative BCG, which helps elucidate the proteomic basis of the intrinsic virulence of the MTB pathogen. PMID:24093440
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Proteomics for understanding miRNA biology.
Huang, Tai-Chung; Pinto, Sneha M; Pandey, Akhilesh
2013-02-01
MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in posttranscriptional regulation of gene expression. Mature miRNAs associate with the RNA interference silencing complex to repress mRNA translation and/or degrade mRNA transcripts. Mass spectrometry-based proteomics has enabled identification of several core components of the canonical miRNA processing pathway and their posttranslational modifications which are pivotal in miRNA regulatory mechanisms. The use of quantitative proteomic strategies has also emerged as a key technique for experimental identification of miRNA targets by allowing direct determination of proteins whose levels are altered because of translational suppression. This review focuses on the role of proteomics and labeling strategies to understand miRNA biology. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Schmidlin, Thierry; Garrigues, Luc; Lane, Catherine S; Mulder, T Celine; van Doorn, Sander; Post, Harm; de Graaf, Erik L; Lemeer, Simone; Heck, Albert J R; Altelaar, A F Maarten
2016-08-01
Hypothesis-driven MS-based targeted proteomics has gained great popularity in a relatively short timespan. Next to the widely established selected reaction monitoring (SRM) workflow, data-independent acquisition (DIA), also referred to as sequential window acquisition of all theoretical spectra (SWATH) was introduced as a high-throughput targeted proteomics method. DIA facilitates increased proteome coverage, however, does not yet reach the sensitivity obtained with SRM. Therefore, a well-informed method selection is crucial for designing a successful targeted proteomics experiment. This is especially the case when targeting less conventional peptides such as those that contain PTMs, as these peptides do not always adhere to the optimal fragmentation considerations for targeted assays. Here, we provide insight into the performance of DIA, SRM, and MRM cubed (MRM(3) ) in the analysis of phosphorylation dynamics throughout the phosphoinositide 3-kinase mechanistic target of rapamycin (PI3K-mTOR) and mitogen-activated protein kinase (MAPK) signaling network. We observe indeed that DIA is less sensitive when compared to SRM, however demonstrates increased flexibility, by postanalysis selection of alternative phosphopeptide precursors. Additionally, we demonstrate the added benefit of MRM(3) , allowing the quantification of two poorly accessible phosphosites. In total, targeted proteomics enabled the quantification of 42 PI3K-mTOR and MAPK phosphosites, gaining a so far unachieved in-depth view mTOR signaling events linked to tyrosine kinase inhibitor resistance in non-small cell lung cancer. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Proteomic-based identification of Apg-2 as a therapeutic target for chronic myeloid leukemia.
Li, Yajuan; Chen, Xi; Shi, Meng; Wang, Haixia; Cao, Weixi; Wang, Xiaozhong; Li, Chunli; Feng, Wenli
2013-12-01
The oncogenic BCR/ABL tyrosine kinase induces constitutive enhanced "spontaneous" DNA damage and unfaithful repair in Philadelphia chromosome positive leukemia cells. Here, we investigated the changes of protein profile in H2O2-induced DNA damage/repair in BaF3-MIGR1 and BaF3-BCR/ABL cells through a proteomic strategy consisting of two-dimensional gel electrophoresis (2-DE) coupled with MALDI-TOF mass spectrometry. In total, 41 spots were differentially expressed and 13 proteins were identified with further MS analysis. Two essential proteins, Proto-oncogene tyrosine-protein kinase ABL1 (c-ABL) and Heat shock 70kDa protein 4 (Apg-2), were confirmed by Western blot and showed consistent changes with proteomic results. Moreover, functional analysis demonstrated that inhibition of Apg-2 not only decreased cell proliferation, but also induced cell apoptosis in BCR/ABL positive cells (BaF3-BCR/ABL, BaF3-BCR/ABL(T315I)). We also proved that Apg-2 inhibition aggravated H2O2 induced damage in BCR/ABL positive cells, and enhanced the sensitivity of BaF3-BCR/ABL(T315I) to STI571. Taken together, the findings in this work provide us with some clues to a better understanding of the molecular mechanisms underlying BCR/ABL in the DNA damage/repair processes and demonstrated that Apg-2 would be a valid target for anti-leukemia drug development. © 2013.
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Selective Targeting of the Cysteine Proteome by Thioredoxin and Glutathione Redox Systems
Go, Young-Mi; Roede, James R.; Walker, Douglas I.; Duong, Duc M.; Seyfried, Nicholas T.; Orr, Michael; Liang, Yongliang; Pennell, Kurt D.; Jones, Dean P.
2013-01-01
Thioredoxin (Trx) and GSH are the major thiol antioxidants protecting cells from oxidative stress-induced cytotoxicity. Redox states of Trx and GSH have been used as indicators of oxidative stress. Accumulating studies suggest that Trx and GSH redox systems regulate cell signaling and metabolic pathways differently and independently during diverse stressful conditions. In the current study, we used a mass spectrometry-based redox proteomics approach to test responses of the cysteine (Cys) proteome to selective disruption of the Trx- and GSH-dependent systems. Auranofin (ARF) was used to inhibit Trx reductase without detectable oxidation of the GSH/GSSG couple, and buthionine sulfoximine (BSO) was used to deplete GSH without detectable oxidation of Trx1. Results for 606 Cys-containing peptides (peptidyl Cys) showed that 36% were oxidized more than 1.3-fold by ARF, whereas BSO-induced oxidation of peptidyl Cys was only 10%. Mean fold oxidation of these peptides was also higher by ARF than BSO treatment. Analysis of potential functional pathways showed that ARF oxidized peptides associated with glycolysis, cytoskeleton remodeling, translation and cell adhesion. Of 60 peptidyl Cys oxidized due to depletion of GSH, 41 were also oxidized by ARF and included proteins of translation and cell adhesion but not glycolysis or cytoskeletal remodeling. Studies to test functional correlates showed that pyruvate kinase activity and lactate levels were decreased with ARF but not BSO, confirming the effects on glycolysis-associated proteins are sensitive to oxidation by ARF. These data show that the Trx system regulates a broader range of proteins than the GSH system, support distinct function of Trx and GSH in cellular redox control, and show for the first time in mammalian cells selective targeting peptidyl Cys and biological pathways due to deficient function of the Trx system. PMID:23946468
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Zhang, Hengwei; Recker, Robert; Lee, Wai-Nang Paul; Xiao, Gary Guishan
2010-01-01
Osteoporosis is prevalent among the elderly and is a major cause of bone fracture in this population. Bone integrity is maintained by the dynamic processes of bone resorption and bone formation (bone remodeling). Osteoporosis results when there is an imbalance of the two counteracting processes. Bone mineral density, measured by dual-energy x-ray absorptiometry has been the primary method to assess fracture risk for decades. Recent studies demonstrated that measurement of bone turnover markers allows for a dynamic assessment of bone remodeling, while imaging techniques, such as dual-energy x-ray absorptiometry, do not. The application of proteomics has permitted discoveries of new, sensitive, bone turnover markers, which provide unique information for clinical diagnosis and treatment of patients with bone diseases. This review summarizes the recent findings of proteomic studies on bone diseases, properties of mesenchymal stem cells with high expansion rates and osteoblast and osteoclast differentiation, with emphasis on the role of quantitative proteomics in the study of signaling dynamics, biomarkers and discovery of therapeutic targets. PMID:20121480
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Mass spectrometry based proteomics: existing capabilities and future directions
Angel, Thomas E.; Aryal, Uma K.; Hengel, Shawna M.; Baker, Erin S.; Kelly, Ryan T.; Robinson, Errol W.; Smith, Richard D.
2012-01-01
Mass spectrometry (MS)-based proteomics is emerging as a broadly effective means for identification, characterization, and quantification of proteins that are integral components of the processes essential for life. Characterization of proteins at the proteome and sub-proteome (e.g., the phosphoproteome, proteoglycome, or degradome/peptidome) levels provides a foundation for understanding fundamental aspects of biology. Emerging technologies such as ion mobility separations coupled with MS and microchip-based-proteome measurements combined with MS instrumentation and chromatographic separation techniques, such as nanoscale reversed phase liquid chromatography and capillary electrophoresis, show great promise for both broad undirected and targeted highly sensitive measurements. MS-based proteomics is increasingly contribute to our understanding of the dynamics, interactions, and roles that proteins and peptides play, advancing our understanding of biology on a systems wide level for a wide range of applications including investigations of microbial communities, bioremediation, and human health. PMID:22498958
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Proteomics of Plant Pathogenic Fungi
González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V.
2010-01-01
Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection. PMID:20589070
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Proteomics of plant pathogenic fungi.
González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V
2010-01-01
Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.
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Gregorich, Zachery R; Peng, Ying; Cai, Wenxuan; Jin, Yutong; Wei, Liming; Chen, Albert J; McKiernan, Susan H; Aiken, Judd M; Moss, Richard L; Diffee, Gary M; Ge, Ying
2016-08-05
Sarcopenia, the loss of skeletal muscle mass and function with advancing age, is a significant cause of disability and loss of independence in the elderly and thus, represents a formidable challenge for the aging population. Nevertheless, the molecular mechanism(s) underlying sarcopenia-associated muscle dysfunction remain poorly understood. In this study, we employed an integrated approach combining top-down targeted proteomics with mechanical measurements to dissect the molecular mechanism(s) in age-related muscle dysfunction. Top-down targeted proteomic analysis uncovered a progressive age-related decline in the phosphorylation of myosin regulatory light chain (RLC), a critical protein involved in the modulation of muscle contractility, in the skeletal muscle of aging rats. Top-down tandem mass spectrometry analysis identified a previously unreported bis-phosphorylated proteoform of fast skeletal RLC and localized the sites of decreasing phosphorylation to Ser14/15. Of these sites, Ser14 phosphorylation represents a previously unidentified site of phosphorylation in RLC from fast-twitch skeletal muscle. Subsequent mechanical analysis of single fast-twitch fibers isolated from the muscles of rats of different ages revealed that the observed decline in RLC phosphorylation can account for age-related decreases in the contractile properties of sarcopenic fast-twitch muscles. These results strongly support a role for decreasing RLC phosphorylation in sarcopenia-associated muscle dysfunction and suggest that therapeutic modulation of RLC phosphorylation may represent a new avenue for the treatment of sarcopenia.
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A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets
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
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Hamzeiy, Hamid; Cox, Jürgen
2017-02-01
Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.
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Platelet proteomics: from discovery to diagnosis.
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.
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Peckner, Ryan; Myers, Samuel A; Jacome, Alvaro Sebastian Vaca; Egertson, Jarrett D; Abelin, Jennifer G; MacCoss, Michael J; Carr, Steven A; Jaffe, Jacob D
2018-05-01
Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.
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Ghiraldi-Lopes, Luciana D; Campanerut-Sá, Paula Az; Meneguello, Jean E; Seixas, Flávio Av; Lopes-Ortiz, Mariana A; Scodro, Regiane Bl; Pires, Claudia Ta; da Silva, Rosi Z; Siqueira, Vera Ld; Nakamura, Celso V; Cardoso, Rosilene F
2017-08-01
We investigated a proteome profile, protein-protein interaction and morphological changes of Mycobacterium tuberculosis after different times of eupomatenoid-5 (EUP-5) induction to evaluate the cellular response to the drug-induced damages. The bacillus was induced to sub-minimal inhibitory concentration of EUP-5 at 12 h, 24 h and 48 h. The proteins were separated by 2D gel electrophoresis, identified by LC/MS-MS. Scanning electron microscopy and Search Tool for the Retrieval of Interacting Genes/Proteins analyses were performed. EUP-5 impacts mainly in M. tuberculosis proteins of intermediary metabolism and interactome suggests a multisite disturbance that contributes to bacilli death. Scanning electron microscopy revealed the loss of bacillary form. Some of the differentially expressed proteins have the potential to be drug targets such as citrate synthase (Rv0896), phosphoglycerate kinase (Rv1437), ketol-acid reductoisomerase (Rv3001c) and ATP synthase alpha chain (Rv1308).
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Mühlhaus, Timo; Weiss, Julia; Hemme, Dorothea; Sommer, Frederik; Schroda, Michael
2011-01-01
Crop-plant-yield safety is jeopardized by temperature stress caused by the global climate change. To take countermeasures by breeding and/or transgenic approaches it is essential to understand the mechanisms underlying plant acclimation to heat stress. To this end proteomics approaches are most promising, as acclimation is largely mediated by proteins. Accordingly, several proteomics studies, mainly based on two-dimensional gel-tandem MS approaches, were conducted in the past. However, results often were inconsistent, presumably attributable to artifacts inherent to the display of complex proteomes via two-dimensional-gels. We describe here a new approach to monitor proteome dynamics in time course experiments. This approach involves full 15N metabolic labeling and mass spectrometry based quantitative shotgun proteomics using a uniform 15N standard over all time points. It comprises a software framework, IOMIQS, that features batch job mediated automated peptide identification by four parallelized search engines, peptide quantification and data assembly for the processing of large numbers of samples. We have applied this approach to monitor proteome dynamics in a heat stress time course using the unicellular green alga Chlamydomonas reinhardtii as model system. We were able to identify 3433 Chlamydomonas proteins, of which 1116 were quantified in at least three of five time points of the time course. Statistical analyses revealed that levels of 38 proteins significantly increased, whereas levels of 206 proteins significantly decreased during heat stress. The increasing proteins comprise 25 (co-)chaperones and 13 proteins involved in chromatin remodeling, signal transduction, apoptosis, photosynthetic light reactions, and yet unknown functions. Proteins decreasing during heat stress were significantly enriched in functional categories that mediate carbon flux from CO2 and external acetate into protein biosynthesis, which also correlated with a rapid, but fully
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Knowledge Translation: Moving Proteomics Science to Innovation in Society.
Holmes, Christina; McDonald, Fiona; Jones, Mavis; Graham, Janice
2016-06-01
Proteomics is one of the pivotal next-generation biotechnologies in the current "postgenomics" era. Little is known about the ways in which innovative proteomics science is navigating the complex socio-political space between laboratory and society. It cannot be assumed that the trajectory between proteomics laboratory and society is linear and unidirectional. Concerned about public accountability and hopes for knowledge-based innovations, funding agencies and citizens increasingly expect that emerging science and technologies, such as proteomics, are effectively translated and disseminated as innovation in society. Here, we describe translation strategies promoted in the knowledge translation (KT) and science communication literatures and examine the use of these strategies within the field of proteomics. Drawing on data generated from qualitative interviews with proteomics scientists and ethnographic observation of international proteomics conferences over a 5-year period, we found that proteomics science incorporates a variety of KT strategies to reach knowledge users outside the field. To attain the full benefit of KT, however, proteomics scientists must challenge their own normative assumptions and approaches to innovation dissemination-beyond the current paradigm relying primarily on publication for one's scientific peers within one's field-and embrace the value of broader (interdisciplinary) KT strategies in promoting the uptake of their research. Notably, the Human Proteome Organization (HUPO) is paying increasing attention to a broader range of KT strategies, including targeted dissemination, integrated KT, and public outreach. We suggest that increasing the variety of KT strategies employed by proteomics scientists is timely and would serve well the omics system sciences community.
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Computer applications making rapid advances in high throughput microbial proteomics (HTMP).
Anandkumar, Balakrishna; Haga, Steve W; Wu, Hui-Fen
2014-02-01
The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.
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Faccidomo, Sara; Swaim, Katarina S; Saunders, Briana L; Santanam, Taruni S; Taylor, Seth M; Kim, Michelle; Reid, Grant T; Eastman, Vallari R; Hodge, Clyde W
2018-06-01
There is a clear need for discovery of effective medications to treat behavioral pathologies associated with alcohol addiction, such as chronic drinking. The goal of this preclinical study was to assess effects of chronic alcohol drinking on the nucleus accumbens (NAcb) proteome to identify and validate novel targets for medications development. Two-dimensional difference in-gel electrophoresis (2D-DIGE) with matrix-assisted laser desorption ionization tandem time-of-flight (MALDI-TOF/TOF) was used to assess effects of chronic voluntary home-cage (24-h access) alcohol drinking on the NAcb proteome of C57BL/6J mice. To extend these findings to a model of alcohol self-administration and reinforcement, we investigated potential regulation of the positive reinforcing effects of alcohol by the target protein glutathione S-transferase Pi 1 (GSTP1) using a pharmacological inhibition strategy in mice trained to self-administer alcohol or sucrose. Expression of 52 unique proteins in the NAcb was changed by chronic alcohol drinking relative to water control (23 upregulated, 29 downregulated). Ingenuity Pathway Analysis showed that alcohol drinking altered an array of protein networks associated with neurological and psychological disorders, molecular and cellular functions, and physiological systems and development. DAVID functional annotation analysis identified 9 proteins (SNCA, GSTP1, PRDX3, PPP3R1, EIF5A, PHB, PEBP1/RKIP, GAPDH, AND SOD1) that were significantly overrepresented in a functional cluster that included the Gene Ontology categories "response to alcohol" and "aging." Immunoblots confirmed changes in Pebp1 (RKIP) and GSTP1 in NAcb with no change in amygdala or frontal cortex, suggesting anatomical specificity. Systemic inhibition of GSTP1 with Ezatiostat (0-30 mg/kg, i.p.) dose-dependently reduced the reinforcing effects of alcohol as measured by operant self-administration, in the absence of motor effects. Sucrose self-administration was also reduced but in a
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Yang, Zhaoshou; Hou, Yongheng; Hao, Taofang; Rho, Hee-Sool; Wan, Jun; Luan, Yizhao; Gao, Xin; Yao, Jianping; Pan, Aihua; Xie, Zhi; Qian, Jiang; Liao, Wanqin; Zhu, Heng; Zhou, Xingwang
2017-01-01
Toxoplasma kinase ROP18 is a key molecule responsible for the virulence of Toxoplasma gondii; however, the mechanisms by which ROP18 exerts parasite virulence via interaction with host proteins remain limited to a small number of identified substrates. To identify a broader array of ROP18 substrates, we successfully purified bioactive mature ROP18 and used it to probe a human proteome array. Sixty eight new putative host targets were identified. Functional annotation analysis suggested that these proteins have a variety of functions, including metabolic process, kinase activity and phosphorylation, cell growth, apoptosis and cell death, and immunity, indicating a pleiotropic role of ROP18 kinase. Among these proteins, four candidates, p53, p38, UBE2N, and Smad1, were further validated. We demonstrated that ROP18 targets p53, p38, UBE2N, and Smad1 for degradation. Importantly, we demonstrated that ROP18 phosphorylates Smad1 Ser-187 to trigger its proteasome-dependent degradation. Further functional characterization of the substrates of ROP18 may enhance understanding of the pathogenesis of Toxoplasma infection and provide new therapeutic targets. Similar strategies could be used to identify novel host targets for other microbial kinases functioning at the pathogen-host interface. PMID:28087594
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A proteomic approach to obesity and type 2 diabetes
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
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Head and neck cancer: proteomic advances and biomarker achievements.
Rezende, Taia Maria Berto; de Souza Freire, Mirna; Franco, Octávio Luiz
2010-11-01
Tumors of the head and neck comprise an important neoplasia group, the incidence of which is increasing in many parts of the world. Recent advances in diagnostic and therapeutic techniques for these lesions have yielded novel molecular targets, uncovered signal pathway dominance, and advanced early cancer detection. Proteomics is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the analysis of different types of samples. The proteomic profiles of different types of cancer have been studied, and this has provided remarkable advances in cancer understanding. This review covers recent advances for head and neck cancer; it encompasses the risk factors, pathogenesis, proteomic tools that can help in understanding cancer, and new proteomic findings in this type of cancer. Copyright © 2010 American Cancer Society.
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Chen, Xiulan; Wei, Shasha; Ma, Ying; Lu, Jie; Niu, Gang; Xue, Yanhong; Chen, Xiaoyuan; Yang, Fuquan
2014-01-01
Doxorubicin is a widely used chemotherapeutic agent for the treatment of a variety of solid tumors. However, resistance to this anticancer drug is a major obstacle to the effective treatment of tumors. As mitochondria play important roles in cell life and death, we anticipate that mitochondria may be related to drug resistance. Here, stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomic strategy was applied to compare mitochondrial protein expression in doxorubicin sensitive OVCAR8 cells and its doxorubicin-resistant variant NCI_ADR/RES cells. A total of 2085 proteins were quantified, of which 122 proteins displayed significant changes in the NCI_ADR/RES cells. These proteins participated in a variety of cell processes including cell apoptosis, substance metabolism, transport, detoxification and drug metabolism. Then qRT-PCR and western blot were applied to validate the differentially expressed proteins quantified by SILAC. Further functional studies with RNAi demonstrated TOP1MT, a mitochondrial protein participated in DNA repair, was involved in doxorubicin resistance in NCI_ADR/RES cells. Besides the proteomic study, electron microscopy and fluorescence analysis also observed that mitochondrial morphology and localization were greatly altered in NCI_ADR/RES cells. Mitochondrial membrane potential was also decreased in NCI_ADR/RES cells. All these results indicate that mitochondrial function is impaired in doxorubicin-resistant cells and mitochondria play an important role in doxorubicin resistance. This research provides some new information about doxorubicin resistance, indicating that mitochondria could be therapeutic targets of doxorubicin resistance in ovarian cancer cells. PMID:25285166
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Analyzing large-scale proteomics projects with latent semantic indexing.
Klie, Sebastian; Martens, Lennart; Vizcaíno, Juan Antonio; Côté, Richard; Jones, Phil; Apweiler, Rolf; Hinneburg, Alexander; Hermjakob, Henning
2008-01-01
Since the advent of public data repositories for proteomics data, readily accessible results from high-throughput experiments have been accumulating steadily. Several large-scale projects in particular have contributed substantially to the amount of identifications available to the community. Despite the considerable body of information amassed, very few successful analyses have been performed and published on this data, leveling off the ultimate value of these projects far below their potential. A prominent reason published proteomics data is seldom reanalyzed lies in the heterogeneous nature of the original sample collection and the subsequent data recording and processing. To illustrate that at least part of this heterogeneity can be compensated for, we here apply a latent semantic analysis to the data contributed by the Human Proteome Organization's Plasma Proteome Project (HUPO PPP). Interestingly, despite the broad spectrum of instruments and methodologies applied in the HUPO PPP, our analysis reveals several obvious patterns that can be used to formulate concrete recommendations for optimizing proteomics project planning as well as the choice of technologies used in future experiments. It is clear from these results that the analysis of large bodies of publicly available proteomics data by noise-tolerant algorithms such as the latent semantic analysis holds great promise and is currently underexploited.
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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.
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Advances in Proteomics of Mycobacterium leprae.
Parkash, O; Singh, B P
2012-04-01
Although Mycobacterium leprae was the first bacterial pathogen identified causing human disease, it remains one of the few that is non-cultivable. Understanding the biology of M. leprae is one of the primary challenges in current leprosy research. Genomics has been extremely valuable, nonetheless, functional proteins are ultimately responsible for controlling most aspects of cellular functions, which in turn could facilitate parasitizing the host. Furthermore, bacterial proteins provide targets for most of the vaccines and immunodiagnostic tools. Better understanding of the proteomics of M. leprae could also help in developing new drugs against M. leprae. During the past nearly 15 years, there have been several developments towards the identification of M. leprae proteins employing contemporary proteomics tools. In this review, we discuss the knowledge gained on the biology and pathogenesis of M. leprae from current proteomic studies. © 2012 The Authors. Scandinavian Journal of Immunology © 2012 Blackwell Publishing Ltd.
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Banerjee, Anirban; Silliman, Christopher C; Moore, Ernest E; Dzieciatkowska, Monika; Kelher, Marguerite; Sauaia, Angela; Jones, Kenneth; Chapman, Michael P; Gonzalez, Eduardo; Moore, Hunter B; D'Alessandro, Angelo; Peltz, Erik; Huebner, Benjamin E; Einerson, Peter; Chandler, James; Ghasabayan, Arsen; Hansen, Kirk
2018-06-01
Viscoelastic measurements of hemostasis indicate that 20% of seriously injured patients exhibit systemic hyperfibrinolysis, with increased early mortality. These patients have normal clot formation with rapid clot lysis. Targeted proteomics was applied to quantify plasma proteins from hyperfibrinolytic (HF) patients to elucidate potential pathophysiology. Blood samples were collected in the field or at emergency department arrival and thrombelastography (TEG) was used to characterize in vitro clot formation under native and tissue plasminogen activator (tPA)-stimulated conditions. Ten samples were taken from injured patients exhibiting normal lysis time at 30 min (Ly30), "eufibrinolytic" (EF), 10 from HF patients, defined as tPA-stimulated TEG Ly30 >50%, and 10 from healthy controls. Trauma patient samples were analyzed by targeted proteomics and ELISA assays for specific coagulation proteins. HF patients exhibited increased plasminogen activation. Thirty-three proteins from the HF patients were significantly decreased compared with healthy controls and EF patients; 17 were coagulation proteins with anti-protease consumption (p < 0.005). The other 16 decreased proteins indicate activation of the alternate complement pathway, depletion of carrier proteins, and four glycoproteins. CXC7 was elevated in all injured patients versus healthy controls (p < 0.005), and 35 proteins were unchanged across all groups (p > 0.1 and fold change of concentrations of 0.75-1.3). HF patients had significant decreases in specific proteins and support mechanisms known in trauma-induced hyperfibrinolysis and also unexpected decreases in coagulation factors, factors II, X, and XIII, without changes in clot formation (SP, R times, or angle). Decreased clot stability in HF patients was corroborated with tPA-stimulated TEGs. Prognostic, level III.
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Costenoble, Roeland; Picotti, Paola; Reiter, Lukas; Stallmach, Robert; Heinemann, Matthias; Sauer, Uwe; Aebersold, Ruedi
2011-01-01
Decades of biochemical research have identified most of the enzymes that catalyze metabolic reactions in the yeast Saccharomyces cerevisiae. The adaptation of metabolism to changing nutritional conditions, in contrast, is much less well understood. As an important stepping stone toward such understanding, we exploit the power of proteomics assays based on selected reaction monitoring (SRM) mass spectrometry to quantify abundance changes of the 228 proteins that constitute the central carbon and amino-acid metabolic network in the yeast Saccharomyces cerevisiae, at five different metabolic steady states. Overall, 90% of the targeted proteins, including families of isoenzymes, were consistently detected and quantified in each sample, generating a proteomic data set that represents a nutritionally perturbed biological system at high reproducibility. The data set is near comprehensive because we detect 95–99% of all proteins that are required under a given condition. Interpreted through flux balance modeling, the data indicate that S. cerevisiae retains proteins not necessarily used in a particular environment. Further, the data suggest differential functionality for several metabolic isoenzymes. PMID:21283140
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Proteome | Office of Cancer Clinical Proteomics Research
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.
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Kustatscher, Georg; Grabowski, Piotr; Rappsilber, Juri
2016-02-01
Subcellular localization is an important aspect of protein function, but the protein composition of many intracellular compartments is poorly characterized. For example, many nuclear bodies are challenging to isolate biochemically and thus remain inaccessible to proteomics. Here, we explore covariation in proteomics data as an alternative route to subcellular proteomes. Rather than targeting a structure of interest biochemically, we target it by machine learning. This becomes possible by taking data obtained for one organelle and searching it for traces of another organelle. As an extreme example and proof-of-concept we predict mitochondrial proteins based on their covariation in published interphase chromatin data. We detect about ⅓ of the known mitochondrial proteins in our chromatin data, presumably most as contaminants. However, these proteins are not present at random. We show covariation of mitochondrial proteins in chromatin proteomics data. We then exploit this covariation by multiclassifier combinatorial proteomics to define a list of mitochondrial proteins. This list agrees well with different databases on mitochondrial composition. This benchmark test raises the possibility that, in principle, covariation proteomics may also be applicable to structures for which no biochemical isolation procedures are available. © 2015 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Confetti: A Multiprotease Map of the HeLa Proteome for Comprehensive Proteomics*
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
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Pre-fractionation strategies to resolve pea (Pisum sativum) sub-proteomes
Meisrimler, Claudia-Nicole; Menckhoff, Ljiljana; Kukavica, Biljana M.; Lüthje, Sabine
2015-01-01
Legumes are important crop plants and pea (Pisum sativum L.) has been investigated as a model with respect to several physiological aspects. The sequencing of the pea genome has not been completed. Therefore, proteomic approaches are currently limited. Nevertheless, the increasing numbers of available EST-databases as well as the high homology of the pea and medicago genome (Medicago truncatula Gaertner) allow the successful identification of proteins. Due to the un-sequenced pea genome, pre-fractionation approaches have been used in pea proteomic surveys in the past. Aside from a number of selective proteome studies on crude extracts and the chloroplast, few studies have targeted other components such as the pea secretome, an important sub-proteome of interest due to its role in abiotic and biotic stress processes. The secretome itself can be further divided into different sub-proteomes (plasma membrane, apoplast, cell wall proteins). Cell fractionation in combination with different gel-electrophoresis, chromatography methods and protein identification by mass spectrometry are important partners to gain insight into pea sub-proteomes, post-translational modifications and protein functions. Overall, pea proteomics needs to link numerous existing physiological and biochemical data to gain further insight into adaptation processes, which play important roles in field applications. Future developments and directions in pea proteomics are discussed. PMID:26539198
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Csősz, É; Emri, G; Kalló, G; Tsaprailis, G; Tőzsér, J
2015-10-01
The healthy human skin with its effective antimicrobial defense system forms an efficient barrier against invading pathogens. There is evidence suggesting that the composition of this chemical barrier varies between diseases, making the easily collected sweat an ideal candidate for biomarker discoveries. Our aim was to provide information about the normal composition of the sweat, and to study the chemical barrier found at the surface of skin. Sweat samples from healthy individuals were collected during sauna bathing, and the global protein panel was analysed by label-free mass spectrometry. SRM-based targeted proteomic methods were designed and stable isotope labelled reference peptides were used for method validation. Ninety-five sweat proteins were identified, 20 of them were novel proteins. It was shown that dermcidin is the most abundant sweat protein, and along with apolipoprotein D, clusterin, prolactin-inducible protein and serum albumin, they make up 91% of secreted sweat proteins. The roles of these highly abundant proteins were reviewed; all of which have protective functions, highlighting the importance of sweat glands in composing the first line of innate immune defense system, and maintaining the epidermal barrier integrity. Our findings with regard to the proteins forming the chemical barrier of the skin as determined by label-free quantification and targeted proteomics methods are in accordance with previous studies, and can be further used as a starting point for non-invasive sweat biomarker research. © 2015 European Academy of Dermatology and Venereology.
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Schilmiller, Anthony L.; Miner, Dennis P.; Larson, Matthew; McDowell, Eric; Gang, David R.; Wilkerson, Curtis; Last, Robert L.
2010-01-01
Shotgun proteomics analysis allows hundreds of proteins to be identified and quantified from a single sample at relatively low cost. Extensive DNA sequence information is a prerequisite for shotgun proteomics, and it is ideal to have sequence for the organism being studied rather than from related species or accessions. While this requirement has limited the set of organisms that are candidates for this approach, next generation sequencing technologies make it feasible to obtain deep DNA sequence coverage from any organism. As part of our studies of specialized (secondary) metabolism in tomato (Solanum lycopersicum) trichomes, 454 sequencing of cDNA was combined with shotgun proteomics analyses to obtain in-depth profiles of genes and proteins expressed in leaf and stem glandular trichomes of 3-week-old plants. The expressed sequence tag and proteomics data sets combined with metabolite analysis led to the discovery and characterization of a sesquiterpene synthase that produces β-caryophyllene and α-humulene from E,E-farnesyl diphosphate in trichomes of leaf but not of stem. This analysis demonstrates the utility of combining high-throughput cDNA sequencing with proteomics experiments in a target tissue. These data can be used for dissection of other biochemical processes in these specialized epidermal cells. PMID:20431087
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Mapping Proteome-Wide Interactions of Reactive Chemicals Using Chemoproteomic Platforms
Counihan, Jessica L.; Ford, Breanna; Nomura, Daniel K.
2015-01-01
A large number of pharmaceuticals, endogenous metabolites, and environmental chemicals act through covalent mechanisms with protein targets. Yet, their specific interactions with the proteome still remain poorly defined for most of these reactive chemicals. Deciphering direct protein targets of reactive small-molecules is critical in understanding their biological action, off-target effects, potential toxicological liabilities, and development of safer and more selective agents. Chemoproteomic technologies have arisen as a powerful strategy that enable the assessment of proteome-wide interactions of these irreversible agents directly in complex biological systems. We review here several chemoproteomic strategies that have facilitated our understanding of specific protein interactions of irreversibly-acting pharmaceuticals, endogenous metabolites, and environmental electrophiles to reveal novel pharmacological, biological, and toxicological mechanisms. PMID:26647369
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Villers, Jennifer; Savocco, Jérôme; Szopinska, Aleksandra; Degand, Hervé; Nootens, Sylvain; Morsomme, Pierre
2017-09-01
Yeast cells, to be able to grow on a wide variety of nitrogen sources, regulate the set of nitrogen transporters present at their plasma membrane. Such regulation relies on both transcriptional and post-translational events. Although microarray studies have identified most nitrogen-sensitive genes, nitrogen-induced post-translational regulation has only been studied for very few proteins among which the general amino acid permease Gap1. Adding a preferred nitrogen source to proline-grown cells triggers Gap1 endocytosis and vacuolar degradation in an Rsp5-Bul1/2-dependent manner. Here, we used a proteomic approach to follow the dynamics of the plasma membrane proteome after addition of a preferred nitrogen source. We identified new targets of the nitrogen regulation and four transporters of poor nitrogen sources-Put4, Opt2, Dal5, and Ptr2-that rapidly decrease in abundance. Although the kinetics is different for each transporter, we found that three of them-Put4, Dal5, and Ptr2-are endocytosed, like Gap1, in an Rsp5-dependent manner and degraded in the vacuole. Finally, we showed that Gap1 stabilization at the plasma membrane, through deletion of Bul proteins, regulates the abundance of Put4, Dal5 and Ptr2. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
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Sys-BodyFluid: a systematical database for human body fluid proteome research
Li, Su-Jun; Peng, Mao; Li, Hong; Liu, Bo-Shu; Wang, Chuan; Wu, Jia-Rui; Li, Yi-Xue; Zeng, Rong
2009-01-01
Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10 000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/. PMID:18978022
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Sys-BodyFluid: a systematical database for human body fluid proteome research.
Li, Su-Jun; Peng, Mao; Li, Hong; Liu, Bo-Shu; Wang, Chuan; Wu, Jia-Rui; Li, Yi-Xue; Zeng, Rong
2009-01-01
Recently, body fluids have widely become an important target for proteomic research and proteomic study has produced more and more body fluid related protein data. A database is needed to collect and analyze these proteome data. Thus, we developed this web-based body fluid proteome database Sys-BodyFluid. It contains eleven kinds of body fluid proteomes, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, seminal fluid, human milk and amniotic fluid. Over 10,000 proteins are presented in the Sys-BodyFluid. Sys-BodyFluid provides the detailed protein annotations, including protein description, Gene Ontology, domain information, protein sequence and involved pathways. These proteome data can be retrieved by using protein name, protein accession number and sequence similarity. In addition, users can query between these different body fluids to get the different proteins identification information. Sys-BodyFluid database can facilitate the body fluid proteomics and disease proteomics research as a reference database. It is available at http://www.biosino.org/bodyfluid/.
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Zhao, Jing; Xie, Ming; Liu, Jin-Na; Wang, Bang-Zhong
2018-04-11
Ethnopharmacology relevance Based on basic theories of Chinese medicine, Yi-Qi-Yang-Yin-Hua-Tan-Qu-Yu (YQYYHTQY) recipe was constituted by eleven kinds of Chinese herbs and effective in treatment of type 2 diabetes (T2DM). But the therapy target was unclear. In this study, we used the serum proteome labeled by iTRAQ to find therapy target of YQYYHTQY recipe on T2DM. The rat model was induced by high-fat diet (HFD) and streptozotocin (STZ, 30mg/kg). Drugs were administered to rats once daily for 14 days. Related laboratory parameters were observed. Serum proteome were compared between T2DM and YQYYHTQY group using the iTRAQ labeling quantitative proteomics technique. Functional differential proteins were analysis by STRING software. Target proteins were confirmed by ELISA kits. Hyperglycemia, hyperinsulinemia, insulin resistance, decrease of glucose transporter, depilation, less activity, flock together, depression, ecchymosis of tongue and tail appearance, the typical diabetic patients "a little more than three" symptoms, as well as the decrease of grip strength, serum cyclic adenosine monophosphate (cAMP)/ cyclic guanosine monophosphate (cGMP) ratio, serum high density lipoprotein-cholesterol (HDL-C) and the increase of serum triglyceride (TG), total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C), thromboxane B 2 (TXB 2 )/ 6-keto prostaglandin F1α (6-keto PGF1α) ratio, endothelin-1 (ET-1) levels were found in T2DM group. After drugs treatment, all the above indexes almost were improved in different degrees and effect of YQYYHTQY recipe was superior to pioglitazone hydrochloride. In addition, there were 23 differential proteins, 5 up-regulated and 18 down-regulated proteins. Of them, there were 4 proteins related with diabetes, blood and behavior. Cell division control protein 42 homolog (CDC42) and Ras homolog gene family member A (RhoA) were the therapy targets of YQYYHTQY recipe on T2DM. YQYYHTQY recipe showed therapy effect on T2DM. CDC42 and
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[ProteoСat: a tool for planning of proteomic experiments].
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.
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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
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The Use of Proteomics in Assisted Reproduction.
Kosteria, Ioanna; Anagnostopoulos, Athanasios K; Kanaka-Gantenbein, Christina; Chrousos, George P; Tsangaris, George T
2017-01-01
Despite the explosive increase in the use of Assisted Reproductive Technologies (ART) over the last 30 years, their success rates remain suboptimal. Proteomics is a rapidly-evolving technology-driven science that has already been widely applied in the exploration of human reproduction and fertility, providing useful insights into its physiology and leading to the identification of numerous proteins that may be potential biomarkers and/or treatment targets of a successful ART pregnancy. Here we present a brief overview of the techniques used in proteomic analyses and attempt a comprehensive presentation of recent data from mass spectrometry-based proteomic studies in humans, regarding all components of ARTs, including the male and female gamete, the derived zygote and embryo, the endometrium and, finally, the ART offspring both pre- and postnatally. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
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Controlled vocabularies and ontologies in proteomics: Overview, principles and practice☆
Mayer, Gerhard; Jones, Andrew R.; Binz, Pierre-Alain; Deutsch, Eric W.; Orchard, Sandra; Montecchi-Palazzi, Luisa; Vizcaíno, Juan Antonio; Hermjakob, Henning; Oveillero, David; Julian, Randall; Stephan, Christian; Meyer, Helmut E.; Eisenacher, Martin
2014-01-01
This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the “mapping files” used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23429179
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Application of proteomics in research on traditional Chinese medicine.
Suo, Tongchuan; Wang, Haixia; Li, Zheng
2016-09-01
Traditional Chinese medicine (TCM) is a widely used complementary alternative medicine approach. Although many aspects of its effectiveness have been approved clinically, rigorous scientific techniques are highly required to translate the promises from TCM into powerful modern therapies. In this respect, proteomics is useful because of its ability to unveil the underlying target proteins and/or protein biomarkers. In this review, we summarize the recent interplay between proteomics and research on TCM, ranging from exploration of the medicinal materials to the biological basis of TCM concepts, and from pathological studies to pharmacological investigations. We show that proteomic analyses provide preliminary biological evidence of the promises in TCM, and the integration of proteomics with other omics and bioinformatics offers a comprehensive methodology to address the complications of TCM. Expert commentary: Currently, only limited information can be obtained regarding TCM issues and thus more work is required to resolve the ambiguity. As such, more collaborations between proteomics and other techniques (other omics, network pharmacology, etc.) are essential for deciphering the underlying biological basis in TCM topics.
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Swaney, Danielle L; Rodríguez-Mias, Ricard A; Villén, Judit
2015-01-01
Ubiquitylation is an essential post-translational modification that regulates numerous cellular processes, most notably protein degradation. Ubiquitin can itself be phosphorylated at nearly every serine, threonine, and tyrosine residue. However, the effect of this modification on ubiquitin function is largely unknown. Here, we characterized the effects of phosphorylation of yeast ubiquitin at serine 65 in vivo and in vitro. We find this post-translational modification to be regulated under oxidative stress, occurring concomitantly with the restructuring of the ubiquitin landscape into a highly polymeric state. Phosphomimetic mutation of S65 recapitulates the oxidative stress phenotype, causing a dramatic accumulation of ubiquitylated proteins and a proteome-wide reduction of protein turnover rates. Importantly, this mutation impacts ubiquitin chain disassembly, chain linkage distribution, ubiquitin interactions, and substrate targeting. These results demonstrate that phosphorylation is an additional mode of ubiquitin regulation with broad implications in cellular physiology. PMID:26142280
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The Escherichia coli Peripheral Inner Membrane Proteome*
Papanastasiou, Malvina; Orfanoudaki, Georgia; Koukaki, Marina; Kountourakis, Nikos; Sardis, Marios Frantzeskos; Aivaliotis, Michalis; Karamanou, Spyridoula; Economou, Anastassios
2013-01-01
Biological membranes are essential for cell viability. Their functional characteristics strongly depend on their protein content, which consists of transmembrane (integral) and peripherally associated membrane proteins. Both integral and peripheral inner membrane proteins mediate a plethora of biological processes. Whereas transmembrane proteins have characteristic hydrophobic stretches and can be predicted using bioinformatics approaches, peripheral inner membrane proteins are hydrophilic, exist in equilibria with soluble pools, and carry no discernible membrane targeting signals. We experimentally determined the cytoplasmic peripheral inner membrane proteome of the model organism Escherichia coli using a multidisciplinary approach. Initially, we extensively re-annotated the theoretical proteome regarding subcellular localization using literature searches, manual curation, and multi-combinatorial bioinformatics searches of the available databases. Next we used sequential biochemical fractionations coupled to direct identification of individual proteins and protein complexes using high resolution mass spectrometry. We determined that the proposed cytoplasmic peripheral inner membrane proteome occupies a previously unsuspected ∼19% of the basic E. coli BL21(DE3) proteome, and the detected peripheral inner membrane proteome occupies ∼25% of the estimated expressed proteome of this cell grown in LB medium to mid-log phase. This value might increase when fleeting interactions, not studied here, are taken into account. Several proteins previously regarded as exclusively cytoplasmic bind membranes avidly. Many of these proteins are organized in functional or/and structural oligomeric complexes that bind to the membrane with multiple interactions. Identified proteins cover the full spectrum of biological activities, and more than half of them are essential. Our data suggest that the cytoplasmic proteome displays remarkably dynamic and extensive communication with
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Ko, Chia-Chen; Chen, Yun-Ju; Chen, Chih-Ta; Liu, Yu-Chih; Cheng, Fong-Chi; Hsu, Kai-Chao; Chow, Lu-Ping
2014-01-01
Quercetin, a flavonoid abundantly present in plants, is widely used as a phytotherapy in prostatitis and prostate cancer. Although quercetin has been reported to have a number of therapeutic effects, the cellular target(s) responsible for its anti-cancer action has not yet been clearly elucidated. Here, employing affinity chromatography and mass spectrometry, we identified heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) as a direct target of quercetin. A specific interaction between quercetin and hnRNPA1 was validated by immunoblotting and in vitro binding experiments. We found that quercetin bound the C-terminal region of hnRNPA1, impairing the ability of hnRNPA1 to shuttle between the nucleus and cytoplasm and ultimately resulting in its cytoplasmic retention. In addition, hnRNPA1 was recruited to stress granules after treatment of cells with quercetin for up to 48 h, and the levels of cIAP1 (cellular inhibitor of apoptosis), an internal ribosome entry site translation-dependent protein, were reduced by hnRNPA1 regulation. This is the first report that anti-cancer effects of quercetin are mediated, in part, by impairing functions of hnRNPA1, insights that were obtained using a chemical proteomics strategy. PMID:24962584
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Proteomics of industrial fungi: trends and insights for biotechnology.
de Oliveira, José Miguel P Ferreira; de Graaff, Leo H
2011-01-01
Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis.
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Proteomics of industrial fungi: trends and insights for biotechnology
de Oliveira, José Miguel P. Ferreira
2010-01-01
Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis. PMID:20922379
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A New Mass Spectrometry-compatible Degradable Surfactant for Tissue Proteomics
Chang, Ying-Hua; Gregorich, Zachery R.; Chen, Albert J.; Hwang, Leekyoung; Guner, Huseyin; Yu, Deyang; Zhang, Jianyi; Ge, Ying
2015-01-01
Tissue proteomics is increasingly recognized for its role in biomarker discovery and disease mechanism investigation. However, protein solubility remains a significant challenge in mass spectrometry (MS)-based tissue proteomics. Conventional surfactants such as sodium dodecyl sulfate (SDS), the preferred surfactant for protein solubilization, are not compatible with MS. Herein, we have screened a library of surfactant-like compounds and discovered an MS-compatible degradable surfactant (MaSDeS) for tissue proteomics that solubilizes all categories of proteins with performance comparable to SDS. The use of MaSDeS in the tissue extraction significantly improves the total number of protein identifications from commonly used tissues, including tissue from the heart, liver, and lung. Notably, MaSDeS significantly enriches membrane proteins, which are often under-represented in proteomics studies. The acid degradable nature of MaSDeS makes it amenable for high-throughput mass spectrometry-based proteomics. In addition, the thermostability of MaSDeS allows for its use in experiments requiring high temperature to facilitate protein extraction and solubilization. Furthermore, we have shown that MaSDeS outperforms the other MS-compatible surfactants in terms of overall protein solubility and the total number of identified proteins in tissue proteomics. Thus, the use of MaSDeS will greatly advance tissue proteomics and realize its potential in basic biomedical and clinical research. MaSDeS could be utilized in a variety of proteomics studies as well as general biochemical and biological experiments that employ surfactants for protein solubilization. PMID:25589168
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Zhang, Yaoyang; Xu, Tao; Shan, Bing; Hart, Jonathan; Aslanian, Aaron; Han, Xuemei; Zong, Nobel; Li, Haomin; Choi, Howard; Wang, Dong; Acharya, Lipi; Du, Lisa; Vogt, Peter K; Ping, Peipei; Yates, John R
2015-11-03
Shotgun proteomics generates valuable information from large-scale and target protein characterizations, including protein expression, protein quantification, protein post-translational modifications (PTMs), protein localization, and protein-protein interactions. Typically, peptides derived from proteolytic digestion, rather than intact proteins, are analyzed by mass spectrometers because peptides are more readily separated, ionized and fragmented. The amino acid sequences of peptides can be interpreted by matching the observed tandem mass spectra to theoretical spectra derived from a protein sequence database. Identified peptides serve as surrogates for their proteins and are often used to establish what proteins were present in the original mixture and to quantify protein abundance. Two major issues exist for assigning peptides to their originating protein. The first issue is maintaining a desired false discovery rate (FDR) when comparing or combining multiple large datasets generated by shotgun analysis and the second issue is properly assigning peptides to proteins when homologous proteins are present in the database. Herein we demonstrate a new computational tool, ProteinInferencer, which can be used for protein inference with both small- or large-scale data sets to produce a well-controlled protein FDR. In addition, ProteinInferencer introduces confidence scoring for individual proteins, which makes protein identifications evaluable. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015. Published by Elsevier B.V.
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Virtual Labs in proteomics: new E-learning tools.
Ray, Sandipan; Koshy, Nicole Rachel; Reddy, Panga Jaipal; Srivastava, Sanjeeva
2012-05-17
Web-based educational resources have gained enormous popularity recently and are increasingly becoming a part of modern educational systems. Virtual Labs are E-learning platforms where learners can gain the experience of practical experimentation without any direct physical involvement on real bench work. They use computerized simulations, models, videos, animations and other instructional technologies to create interactive content. Proteomics being one of the most rapidly growing fields of the biological sciences is now an important part of college and university curriculums. Consequently, many E-learning programs have started incorporating the theoretical and practical aspects of different proteomic techniques as an element of their course work in the form of Video Lectures and Virtual Labs. To this end, recently we have developed a Virtual Proteomics Lab at the Indian Institute of Technology Bombay, which demonstrates different proteomics techniques, including basic and advanced gel and MS-based protein separation and identification techniques, bioinformatics tools and molecular docking methods, and their applications in different biological samples. This Tutorial will discuss the prominent Virtual Labs featuring proteomics content, including the Virtual Proteomics Lab of IIT-Bombay, and E-resources available for proteomics study that are striving to make proteomic techniques and concepts available and accessible to the student and research community. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 14). Details can be found at: http://www.proteomicstutorials.org/. Copyright © 2012 Elsevier B.V. All rights reserved.
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Integrative FourD omics approach profiles the target network of the carbon storage regulatory system
Sowa, Steven W.; Gelderman, Grant; Leistra, Abigail N.; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A.; Romeo, Tony; Baldea, Michael
2017-01-01
Abstract Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. PMID:28126921
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SPS' Digest: the Swiss Proteomics Society selection of proteomics articles.
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.
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Plasticity in the proteome of Emiliania huxleyi CCMP 1516 to extremes of light is highly targeted.
McKew, Boyd A; Lefebvre, Stephane C; Achterberg, Eric P; Metodieva, Gergana; Raines, Christine A; Metodiev, Metodi V; Geider, Richard J
2013-10-01
Optimality principles are often applied in theoretical studies of microalgal ecophysiology to predict changes in allocation of resources to different metabolic pathways, and optimal acclimation is likely to involve changes in the proteome, which typically accounts for > 50% of cellular nitrogen (N). We tested the hypothesis that acclimation of the microalga Emiliania huxleyi CCMP 1516 to suboptimal vs supraoptimal light involves large changes in the proteome as cells rebalance the capacities to absorb light, fix CO2 , perform biosynthesis and resist photooxidative stress. Emiliania huxleyi was grown in nutrient-replete continuous culture at 30 (LL) and 1000 μmol photons m(-2) s(-1) (HL), and changes in the proteome were assessed by LC-MS/MS shotgun proteomics. Changes were most evident in proteins involved in the light reactions of photosynthesis; the relative abundance of photosystem I (PSI) and PSII proteins was 70% greater in LL, light-harvesting fucoxanthin-chlorophyll proteins (Lhcfs) were up to 500% greater in LL and photoprotective LI818 proteins were 300% greater in HL. The marked changes in the abundances of Lhcfs and LI818s, together with the limited plasticity in the bulk of the E. huxleyi proteome, probably reflect evolutionary pressures to provide energy to maintain metabolic capabilities in stochastic light environments encountered by this species in nature. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
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Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir
2018-05-15
Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several
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Basisty, Nathan; Dai, Dao-Fu; Gagnidze, Arni; Gitari, Lemuel; Fredrickson, Jeanne; Maina, Yvonne; Beyer, Richard P; Emond, Mary J; Hsieh, Edward J; MacCoss, Michael J; Martin, George M; Rabinovitch, Peter S
2016-08-01
Reactive oxygen species (ROS) are highly reactive oxygen-containing molecules associated with aging and a broad spectrum of pathologies. We have previously shown that transgenic expression of the antioxidant enzyme catalase targeted to the mitochondria (mCAT) in mice reduces ROS, attenuates age-related disease, and increases lifespan. However, it has been increasingly recognized that ROS also has beneficial roles in signaling, hormesis, stress response, and immunity. We therefore hypothesized that mCAT might be beneficial only when ROS approaches pathological levels in older age and might not be advantageous at a younger age when basal ROS is low. We analyzed abundance and turnover of the global proteome in hearts and livers of young (4 month) and old (20 month) mCAT and wild-type (WT) mice. In old hearts and livers of WT mice, protein half-lives were reduced compared to young, while in mCAT mice the reverse was observed; the longest half-lives were seen in old mCAT mice and the shortest in young mCAT. Protein abundance of old mCAT hearts recapitulated a more youthful proteomic expression profile (P-value < 0.01). However, young mCAT mice partially phenocopied the older wild-type proteome (P-value < 0.01). Age strongly interacts with mCAT, consistent with antagonistic pleiotropy in the reverse of the typical direction. These findings underscore the contrasting roles of ROS in young vs. old mice and indicate the need for better understanding of the interaction between dose and age in assessing the efficacy of therapeutic interventions in aging, including mitochondrial antioxidants. © 2016 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
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Kim, Jong-Seo; Fillmore, Thomas L; Liu, Tao; Robinson, Errol; Hossain, Mahmud; Champion, Boyd L; Moore, Ronald J; Camp, David G; Smith, Richard D; Qian, Wei-Jun
2011-12-01
Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.
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The path to enlightenment: making sense of genomic and proteomic information.
Maurer, Martin H
2004-05-01
Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.
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The Gel Electrophoresis Markup Language (GelML) from the Proteomics Standards Initiative
Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J. Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R
2011-01-01
The Human Proteome Organisation’s Proteomics Standards Initiative (HUPO-PSI) has developed the GelML data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for mass spectrometry data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications. PMID:20677327
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The gel electrophoresis markup language (GelML) from the Proteomics Standards Initiative.
Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R
2010-09-01
The Human Proteome Organisation's Proteomics Standards Initiative has developed the GelML (gel electrophoresis markup language) data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for MS data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications.
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2017-01-01
Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704
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Redox proteomics and drug development.
D'Alessandro, Angelo; Rinalducci, Sara; Zolla, Lello
2011-11-18
As alterations of the redox homeostasis lie at the root of many pathophysiological processes in human health, redox proteomics holds the promise to shed further light on fundamental biological processes. In this review, the mechanisms of reactive oxygen species (ROS) and reactive nitrogen species (RNS) production are reviewed, mainly addressing those chemical phenomena which have already been associated with pathological conditions (of the central nervous system, cardiovascular system, or simply related to aging and altered-cell cycle regulation). From Alzheimer's to Parkinson's and Hungtinton's disease, from ageing to cancer, oxidative stress (OS) appears to represent a common trait in so many relevant biological aspects of human health, that further investments in the field of redox proteomics ought to be mandatory. For the foreseeable future, redox proteomics will likely play a pivotal role in the quest for new therapeutical targets and their validation, in the process of determining OS-triggered cellular alteration upon drug treatments and thus in the very heart of the design and testing of new drugs and their metabolites against those pathologies relying on altered redox homeostasis. Copyright © 2011 Elsevier B.V. All rights reserved.
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[Application progress of proteomic in pharmacological study of Chinese medicinal formulae].
Liu, Yu-Qian; Zhan, Shu-Yu; Ruan, Yu-Er; Zuo, Zhi-Yan; Ji, Xiao-Ming; Wang, Shuai-Jie; Ding, Bao-Yue
2017-10-01
Chinese medicinal formulae are the important means of clinical treatment in traditional Chinese medicine. It is urgent to use modern advanced scientific and technological means to reveal the complicated mechanism of Chinese medicinal formulae because they have the function characteristics of multiple components, multiple targets and integrated regulation. The systematic and comprehensive research model of proteomic is in line with the function characteristics of Chinese medicinal formulae, and proteomic has been widely used in the study of pharmacological mechanism of Chinese medicinal formulae. The recent applications of proteomic in pharmacological study of Chinese medicinal formulae in anti-cardiovascular and cerebrovascular diseases, anti-liver disease, antidiabetic, anticancer, anti-rheumatoid arthritis and other diseases were reviewed in this paper, and then the future development direction of proteomic in pharmacological study of Chinese medicinal formulae was put forward. This review is to provide the ideas and method for proteomic research on function mechanism of Chinese medicinal formulae. Copyright© by the Chinese Pharmaceutical Association.
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Ballistic Experiments with Titanium and Aluminum Targets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gogolewski, R.; Morgan, B.R.
1999-11-23
During the course of the project we conducted two sets of fundamental experiments in penetration mechanics in the LLNL Terminal Ballistics Laboratory of the Physics Directorate. The first set of full-scale experiments was conducted with a 14.5mm air propelled launcher. The object of the experiments was to determine the ballistic limit speed of 6Al-4V-alloy titanium, low fineness ratio projectiles centrally impacting 2024-T3 alloy aluminum flat plates and the failure modes of the projectiles and the targets. The second set of one-third scale experiments was conducted with a 14.5mm powder launcher. The object of these experiments was to determine the ballisticmore » limit speed of 6Al-4V alloy titanium high fineness ratio projectiles centrally impacting 6Al-4V alloy titanium flat plates and the failure modes of the projectiles and the target. We employed radiography to observe a projectile just before and after interaction with a target plate. Early on, we employed a non-damaging ''soft-catch'' technique to capture projectiles after they perforated targets. Once we realized that a projectile was not damaged during interaction with a target, we used a 4-inch thick 6061-T6-alloy aluminum witness block with a 6.0-inch x 6.0-inch cross-section to measure projectile residual penetration. We have recorded and tabulated below projectile impact speed, projectile residual (post-impact) speed, projectile failure mode, target failure mode, and pertinent comments for the experiments. The ballistic techniques employed for the experiments are similar to those employed in an earlier study.« less
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Proteome alteration induced by hTERT transfection of human fibroblast cells.
Mazzucchelli, Gabriel D; Gabelica, Valérie; Smargiasso, Nicolas; Fléron, Maximilien; Ashimwe, Wilson; Rosu, Frédéric; De Pauw-Gillet, Marie-Claire; Riou, Jean-François; De Pauw, Edwin
2008-04-17
Telomerase confers cellular immortality by elongating telomeres, thereby circumventing the Hayflick limit. Extended-life-span cells have been generated by transfection with the human telomerase reverse transcriptase (hTERT) gene. hTERT transfected cell lines may be of outstanding interest to monitor the effect of drugs targeting the telomerase activity. The incidence of hTERT gene transfection at the proteome level is a prerequisite to that purpose. The effect of the transfection has been studied on the proteome of human fibroblast (WI38). Cytosolic and nuclear fractions of WI38 cells, empty vector transfected WI38 (WI38-HPV) and hTERT WI38 cells were submitted to a 2D-DIGE (Two-Dimensional Differential In-Gel Electrophoresis) analysis. Only spots that had a similar abundance in WI38 and WI38-HPV, but were differentially expressed in WI38 hTERT were selected for MS identification. This method directly points to the proteins linked with the hTERT expression. Number of false positive differentially expressed proteins has been excluded by using control WI38-HPV cells. The proteome alteration induced by hTERT WI38 transfection should be taken into account in subsequent use of the cell line for anti-telomerase drugs evaluation. 2D-DIGE experiment shows that 57 spots out of 2246 are significantly differentially expressed in the cytosolic fraction due to hTERT transfection, and 38 were confidently identified. In the nuclear fraction, 44 spots out of 2172 were selected in the differential proteome analysis, and 14 were identified. The results show that, in addition to elongating telomeres, hTERT gene transfection has other physiological roles, among which an enhanced ER capacity and a potent cell protection against apoptosis. We show that the methodology reduces the complexity of the proteome analysis and highlights proteins implicated in other processes than telomere elongation. hTERT induced proteome changes suggest that telomerase expression enhances natural cell repair
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A proteomic approach to obesity and type 2 diabetes.
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.
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Global profiling of lysine reactivity and ligandability in the human proteome
NASA Astrophysics Data System (ADS)
Hacker, Stephan M.; Backus, Keriann M.; Lazear, Michael R.; Forli, Stefano; Correia, Bruno E.; Cravatt, Benjamin F.
2017-12-01
Nucleophilic amino acids make important contributions to protein function, including performing key roles in catalysis and serving as sites for post-translational modification. Electrophilic groups that target amino-acid nucleophiles have been used to create covalent ligands and drugs, but have, so far, been mainly limited to cysteine and serine. Here, we report a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems. We have quantified, in total, more than 9,000 lysines in human cell proteomes and have identified several hundred residues with heightened reactivity that are enriched at protein functional sites and can frequently be targeted by electrophilic small molecules. We have also discovered lysine-reactive fragment electrophiles that inhibit enzymes by active site and allosteric mechanisms, as well as disrupt protein-protein interactions in transcriptional regulatory complexes, emphasizing the broad potential and diverse functional consequences of liganding lysine residues throughout the human proteome.
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Global profiling of lysine reactivity and ligandability in the human proteome.
Hacker, Stephan M; Backus, Keriann M; Lazear, Michael R; Forli, Stefano; Correia, Bruno E; Cravatt, Benjamin F
2017-12-01
Nucleophilic amino acids make important contributions to protein function, including performing key roles in catalysis and serving as sites for post-translational modification. Electrophilic groups that target amino-acid nucleophiles have been used to create covalent ligands and drugs, but have, so far, been mainly limited to cysteine and serine. Here, we report a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems. We have quantified, in total, more than 9,000 lysines in human cell proteomes and have identified several hundred residues with heightened reactivity that are enriched at protein functional sites and can frequently be targeted by electrophilic small molecules. We have also discovered lysine-reactive fragment electrophiles that inhibit enzymes by active site and allosteric mechanisms, as well as disrupt protein-protein interactions in transcriptional regulatory complexes, emphasizing the broad potential and diverse functional consequences of liganding lysine residues throughout the human proteome.
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Deswal, Renu; Abat, Jasmeet Kaur; Sehrawat, Ankita; Gupta, Ravi; Kashyap, Prakriti; Sharma, Shruti; Sharma, Bhavana; Chaurasia, Satya Prakash; Chanu, Sougrakpam Yaiphabi; Masi, Antonio; Agrawal, Ganesh Kumar; Sarkar, Abhijit; Agrawal, Raj; Dunn, Michael J; Renaut, Jenny; Rakwal, Randeep
2014-07-01
International Plant Proteomics Organization (INPPO) outlined ten initiatives to promote plant proteomics in each and every country. With greater emphasis in developing countries, one of those was to "organize workshops at national and international levels to train manpower and exchange information". This third INPPO highlights covers the workshop organized for the very first time in a developing country, India, at the Department of Botany in University of Delhi on December 26-30, 2013 titled - "1(st) Plant Proteomics Workshop / Training Program" under the umbrella of INPPO India-Nepal chapter. Selected 20 participants received on-hand training mainly on gel-based proteomics approach along with manual booklet and parallel lectures on this and associated topics. In house, as well as invited experts drawn from other Universities and Institutes (national and international), delivered talks on different aspects of gel-based and gel-free proteomics. Importance of gel-free proteomics approach, translational proteomics, and INPPO roles were presented and interactively discussed by a group of three invited speakers Drs. Ganesh Kumar Agrawal (Nepal), Randeep Rakwal (Japan), and Antonio Masi (Italy). Given the output of this systematic workshop, it was proposed and thereafter decided to be organized every alternate year; the next workshop will be held in 2015. Furthermore, possibilities on providing advanced training to those students / researchers / teachers with basic knowledge in proteomics theory and experiments at national and international levels were discussed. INPPO is committed to generating next-generation trained manpower in proteomics, and it would only happen by the firm determination of scientists to come forward and do it. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Quantitative Proteomic Analysis of the Hfq-Regulon in Sinorhizobium meliloti 2011
Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio
2012-01-01
Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with 15N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti. PMID:23119037
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Quantitative proteomic analysis of the Hfq-regulon in Sinorhizobium meliloti 2011.
Sobrero, Patricio; Schlüter, Jan-Philip; Lanner, Ulrike; Schlosser, Andreas; Becker, Anke; Valverde, Claudio
2012-01-01
Riboregulation stands for RNA-based control of gene expression. In bacteria, small non-coding RNAs (sRNAs) are a major class of riboregulatory elements, most of which act at the post-transcriptional level by base-pairing target mRNA genes. The RNA chaperone Hfq facilitates antisense interactions between target mRNAs and regulatory sRNAs, thus influencing mRNA stability and/or translation rate. In the α-proteobacterium Sinorhizobium meliloti strain 2011, the identification and detection of multiple sRNAs genes and the broadly pleitropic phenotype associated to the absence of a functional Hfq protein both support the existence of riboregulatory circuits controlling gene expression to ensure the fitness of this bacterium in both free living and symbiotic conditions. In order to identify target mRNAs subject to Hfq-dependent riboregulation, we have compared the proteome of an hfq mutant and the wild type S. meliloti by quantitative proteomics following protein labelling with (15)N. Among 2139 univocally identified proteins, a total of 195 proteins showed a differential abundance between the Hfq mutant and the wild type strain; 65 proteins accumulated ≥2-fold whereas 130 were downregulated (≤0.5-fold) in the absence of Hfq. This profound proteomic impact implies a major role for Hfq on regulation of diverse physiological processes in S. meliloti, from transport of small molecules to homeostasis of iron and nitrogen. Changes in the cellular levels of proteins involved in transport of nucleotides, peptides and amino acids, and in iron homeostasis, were confirmed with phenotypic assays. These results represent the first quantitative proteomic analysis in S. meliloti. The comparative analysis of the hfq mutant proteome allowed identification of novel strongly Hfq-regulated genes in S. meliloti.
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Proteomics and syndrome of Chinese medicine
Lu, Chuan-Li; Qv, Xiao-Ying; Jiang, Jian-Guo
2010-01-01
Abstract Syndrome of Chinese medicine is an understanding of the regularity of disease occurrence and development and its performance of symptoms. Syndrome is the key to recognize diseases and the foundation to treat them. However, because of the complexity of the concept and the limitation of present investigations, the research of syndrome is hard to go further. Proteomics has been received extensive attention in the area of medical diagnosis and drug development. In the holistic and systemic context, proteomics have a convergence with traditional Chinese medicine (TCM) syndrome, which could overcome the one-sidedness and singleness of TCM and avoid the complication and tedious processes. Chinese medicine has a wealth of experience and proteomics has a substantial research potential, the integration of the two aspects will bring a great enhancement of our knowledge of disease. PMID:20874721
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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
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Defining the wheat gluten peptide fingerprint via a discovery and targeted proteomics approach.
Martínez-Esteso, María José; Nørgaard, Jørgen; Brohée, Marcel; Haraszi, Reka; Maquet, Alain; O'Connor, Gavin
2016-09-16
Accurate, reliable and sensitive detection methods for gluten are required to support current EU regulations. The enforcement of legislative levels requires that measurement results are comparable over time and between methods. This is not a trivial task for gluten which comprises a large number of protein targets. This paper describes a strategy for defining a set of specific analytical targets for wheat gluten. A comprehensive proteomic approach was applied by fractionating wheat gluten using RP-HPLC (reversed phase high performance liquid chromatography) followed by a multi-enzymatic digestion (LysC, trypsin and chymotrypsin) with subsequent mass spectrometric analysis. This approach identified 434 peptide sequences from gluten. Peptides were grouped based on two criteria: unique to a single gluten protein sequence; contained known immunogenic and toxic sequences in the context of coeliac disease. An LC-MS/MS method based on selected reaction monitoring (SRM) was developed on a triple quadrupole mass spectrometer for the specific detection of the target peptides. The SRM based screening approach was applied to gluten containing cereals (wheat, rye, barley and oats) and non-gluten containing flours (corn, soy and rice). A unique set of wheat gluten marker peptides were identified and are proposed as wheat specific markers. The measurement of gluten in processed food products in support of regulatory limits is performed routinely. Mass spectrometry is emerging as a viable alternative to ELISA based methods. Here we outline a set of peptide markers that are representative of gluten and consider the end user's needs in protecting those with coeliac disease. The approach taken has been applied to wheat but can be easily extended to include other species potentially enabling the MS quantification of different gluten containing species from the identified markers. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
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Overview of proteomics studies in obstructive sleep apnea
Feliciano, Amélia; Torres, Vukosava Milic; Vaz, Fátima; Carvalho, Ana Sofia; Matthiesen, Rune; Pinto, Paula; Malhotra, Atul; Bárbara, Cristina; Penque, Deborah
2015-01-01
Obstructive sleep apnea (OSA) is an underdiagnosed common public health concern causing deleterious effects on metabolic and cardiovascular health. Although much has been learned regarding the pathophysiology and consequences of OSA in the past decades, the molecular mechanisms associated with such processes remain poorly defined. The advanced high-throughput proteomics-based technologies have become a fundamental approach for identifying novel disease mediators as potential diagnostic and therapeutic targets for many diseases, including OSA. Here, we briefly review OSA pathophysiology and the technological advances in proteomics and the first results of its application to address critical issues in the OSA field. PMID:25770042
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Yu, Su Jong; Kim, Hyunsoo; Min, Hophil; Sohn, Areum; Cho, Young Youn; Yoo, Jeong-Ju; Lee, Dong Hyeon; Cho, Eun Ju; Lee, Jeong-Hoon; Gim, Jungsoo; Park, Taesung; Kim, Yoon Jun; Kim, Chung Yong; Yoon, Jung-Hwan; Kim, Youngsoo
2017-03-03
This study was aimed to identify blood-based biomarkers to predict a sustained complete response (CR) after transarterial chemoembolization (TACE) using targeted proteomics. Consecutive patients with HCC who had undergone TACE were prospectively enrolled (training (n = 100) and validation set (n = 80)). Serum samples were obtained before and 6 months after TACE. Treatment responses were evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST). In the training set, the MRM-MS assay identified five marker candidate proteins (LRG1, APCS, BCHE, C7, and FCN3). When this five-marker panel was combined with the best-performing clinical variables (tumor number, baseline PIVKA, and baseline AFP), the resulting ensemble model had the highest area under the receiver operating curve (AUROC) value in predicting a sustained CR after TACE in the training and validation sets (0.881 and 0.813, respectively). Furthermore, the ensemble model was an independent predictor of rapid progression (hazard ratio (HR), 2.889; 95% confidence interval (CI), 1.612-5.178; P value < 0.001) and overall an unfavorable survival rate (HR, 1.985; 95% CI, 1.024-3.848; P value = 0.042) in the entire population by multivariate analysis. Targeted proteomics-based ensemble model can predict clinical outcomes after TACE. Therefore, this model can aid in determining the best candidates for TACE and the need for adjuvant therapy.
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Proteomics Analysis of the Nucleolus in Adenovirus-infected Cells
Lam, Yun W.; Evans, Vanessa C.; Heesom, Kate J.; Lamond, Angus I.; Matthews, David A.
2010-01-01
Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined. PMID:19812395
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Proteomics analysis of the nucleolus in adenovirus-infected cells.
Lam, Yun W; Evans, Vanessa C; Heesom, Kate J; Lamond, Angus I; Matthews, David A
2010-01-01
Adenoviruses replicate primarily in the host cell nucleus, and it is well established that adenovirus infection affects the structure and function of host cell nucleoli in addition to coding for a number of nucleolar targeted viral proteins. Here we used unbiased proteomics methods, including high throughput mass spectrometry coupled with stable isotope labeling by amino acids in cell culture (SILAC) and traditional two-dimensional gel electrophoresis, to identify quantitative changes in the protein composition of the nucleolus during adenovirus infection. Two-dimensional gel analysis revealed changes in six proteins. By contrast, SILAC-based approaches identified 351 proteins with 24 proteins showing at least a 2-fold change after infection. Of those, four were previously reported to have aberrant localization and/or functional relevance during adenovirus infection. In total, 15 proteins identified as changing in amount by proteomics methods were examined in infected cells using confocal microscopy. Eleven of these proteins showed altered patterns of localization in adenovirus-infected cells. Comparing our data with the effects of actinomycin D on the nucleolar proteome revealed that adenovirus infection apparently specifically targets a relatively small subset of nucleolar antigens at the time point examined.
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Song, Jun; Du, Lina; Li, Li; Kalt, Wilhelmina; Palmer, Leslie Campbell; Fillmore, Sherry; Zhang, Ying; Zhang, ZhaoQi; Li, XiHong
2015-06-03
To better understand the regulation of flavonoid and anthocyanin biosynthesis, a targeted quantitative proteomic investigation employing LC-MS with multiple reaction monitoring was conducted on two strawberry cultivars at three ripening stages. This quantitative proteomic workflow was improved through an OFFGEL electrophoresis to fractionate peptides from total protein digests. A total of 154 peptide transitions from 47 peptides covering 21 proteins and isoforms related to anthocyanin biosynthesis were investigated. The normalized protein abundance, which was measured using isotopically-labeled standards, was significantly changed concurrently with increased anthocyanin content and advanced fruit maturity. The protein abundance of phenylalanine ammonia-lyase; anthocyanidin synthase, chalcone isomerase; flavanone 3-hydroxylase; dihydroflavonol 4-reductase, UDP-glucose:flavonoid-3-O-glucosyltransferase, cytochrome c and cytochrome C oxidase subunit 2, was all significantly increased in fruit of more advanced ripeness. An interaction between cultivar and maturity was also shown with respect to chalcone isomerase. The good correlation between protein abundance and anthocyanin content suggested that a metabolic control point may exist for anthocyanin biosynthesis. This research provides insights into the process of anthocyanin formation in strawberry fruit at the level of protein concentration and reveals possible candidates in the regulation of anthocyanin formation during fruit ripening. To gain insight into the molecular mechanisms contributing to flavonoids and anthocyanin biosynthesis and regulation of strawberry fruit during ripening is challenging due to limited molecular biology tools and established hypothesis. Our targeted proteomic approach employing LC-MS/MS analysis and MRM technique to quantify proteins in relation to flavonoids and anthocyanin biosynthesis and regulation in strawberry fruit during fruit ripening is novel. The identification of peptides
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Jarnuczak, Andrew F; Lee, Dave C H; Lawless, Craig; Holman, Stephen W; Eyers, Claire E; Hubbard, Simon J
2016-09-02
Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.
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Technical advances in proteomics: new developments in data-independent acquisition.
Hu, Alex; Noble, William S; Wolf-Yadlin, Alejandro
2016-01-01
The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low‑abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various
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Top-down Proteomics: Technology Advancements and Applications to Heart Diseases
Cai, Wenxuan; Tucholski, Trisha M.; Gregorich, Zachery R.; Ge, Ying
2016-01-01
Introduction Diseases of the heart are a leading cause of morbidity and mortality for both men and women worldwide, and impose significant economic burdens on the healthcare systems. Despite substantial effort over the last several decades, the molecular mechanisms underlying diseases of the heart remain poorly understood. Areas covered Altered protein post-translational modifications (PTMs) and protein isoform switching are increasingly recognized as important disease mechanisms. Top-down high-resolution mass spectrometry (MS)-based proteomics has emerged as the most powerful method for the comprehensive analysis of PTMs and protein isoforms. Here, we will review recent technology developments in the field of top-down proteomics, as well as highlight recent studies utilizing top-down proteomics to decipher the cardiac proteome for the understanding of the molecular mechanisms underlying diseases of the heart. Expert commentary Top-down proteomics is a premier method for the global and comprehensive study of protein isoforms and their PTMs, enabling the identification of novel protein isoforms and PTMs, characterization of sequence variations, and quantification of disease-associated alterations. Despite significant challenges, continuous development of top-down proteomics technology will greatly aid the dissection of the molecular mechanisms underlying diseases of the hearts for the identification of novel biomarkers and therapeutic targets. PMID:27448560
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Building ProteomeTools based on a complete synthetic human proteome
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
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Proteomic identification of E6AP as a molecular target of tamoxifen in MCF7 cells.
Lochab, Savita; Pal, Pooja; Kanaujiya, Jitendra K; Tripathi, Shashi B; Kapoor, Isha; Bhatt, Madan L B; Sanyal, Sabyasachi; Behre, Gerhard; Trivedi, Arun K
2012-05-01
Tamoxifen (Tam) is most widely used selective estrogen receptor modulator (SERM) for treatment of hormone-responsive breast cancer. Despite being regularly used in clinical therapy for breast cancer since 1971, the mechanism of Tam action remains largely unclear. In order to gain insights into Tam-mediated antibreast cancer actions, we applied 2DE and MS based proteomics approach to identify target proteins of Tam. We identified E6-associated protein, i.e. E6AP (UBE3A) among others to be regulated by Tam that otherwise is upregulated in breast tumors. We confirmed our 2DE finding by immunoblotting and further show that Tam leads to inhibition of E6AP expression presumably by promoting its autoubiquitination, which is coupled with nuclear export and subsequent proteasome-mediated degradation. Furthermore, we show that Tam- and siE6AP-mediated inhibition of E6AP leads to enhanced G0-G1 growth arrest and apoptosis, which is also evident from significant upregulation of cytochrome-c, Bax, p21, and PARP cleavage. Taken together, our data suggest that, Tam-targeted E6AP inhibition is in fact required for Tam-mediated antibreast cancer actions. Thus, E6AP may be a therapeutic target in breast cancer. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Britton, David; Zen, Yoh; Quaglia, Alberto; Selzer, Stefan; Mitra, Vikram; Löβner, Christopher; Jung, Stephan; Böhm, Gitte; Schmid, Peter; Prefot, Petra; Hoehle, Claudia; Koncarevic, Sasa; Gee, Julia; Nicholson, Robert; Ward, Malcolm; Castellano, Leandro; Stebbing, Justin; Zucht, Hans Dieter; Sarker, Debashis; Heaton, Nigel; Pike, Ian
2014-01-01
LC-MS/MS phospho-proteomics is an essential technology to help unravel the complex molecular events that lead to and propagate cancer. We have developed a global phospho-proteomic workflow to determine activity of signaling pathways and drug targets in pancreatic cancer tissue for clinical application. Peptides resulting from tryptic digestion of proteins extracted from frozen tissue of pancreatic ductal adenocarcinoma and background pancreas (n = 12), were labelled with tandem mass tags (TMT 8-plex), separated by strong cation exchange chromatography, then were analysed by LC-MS/MS directly or first enriched for phosphopeptides using IMAC and TiO2, prior to analysis. In-house, commercial and freeware bioinformatic platforms were used to identify relevant biological events from the complex dataset. Of 2,101 proteins identified, 152 demonstrated significant difference in abundance between tumor and non-tumor tissue. They included proteins that are known to be up-regulated in pancreatic cancer (e.g. Mucin-1), but the majority were new candidate markers such as HIPK1 & MLCK. Of the 6,543 unique phosphopeptides identified (6,284 unique phosphorylation sites), 635 showed significant regulation, particularly those from proteins involved in cell migration (Rho guanine nucleotide exchange factors & MRCKα) and formation of focal adhesions. Activator phosphorylation sites on FYN, AKT1, ERK2, HDAC1 and other drug targets were found to be highly modulated (≥2 fold) in different cases highlighting their predictive power. Here we provided critical information enabling us to identify the common and unique molecular events likely contributing to cancer in each case. Such information may be used to help predict more bespoke therapy suitable for an individual case.
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Beauty and charm production at fixed-target experiments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Erik E. Gottschalk
Fixed-target experiments continue to provide insights into the physics of particle production in strong interactions. The experiments are performed with different types of beam particles of varying energies, and many different target materials. Studies of beauty and charm production are of particular interest, since experimental results can be compared to perturbative QCD calculations. It is in this context that recent results from fixed-target experiments on beauty and charm production will be reviewed.
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MOPED enables discoveries through consistently processed proteomics data
Higdon, Roger; Stewart, Elizabeth; Stanberry, Larissa; Haynes, Winston; Choiniere, John; Montague, Elizabeth; Anderson, Nathaniel; Yandl, Gregory; Janko, Imre; Broomall, William; Fishilevich, Simon; Lancet, Doron; Kolker, Natali; Kolker, Eugene
2014-01-01
The Model Organism Protein Expression Database (MOPED, http://moped.proteinspire.org), is an expanding proteomics resource to enable biological and biomedical discoveries. MOPED aggregates simple, standardized and consistently processed summaries of protein expression and metadata from proteomics (mass spectrometry) experiments from human and model organisms (mouse, worm and yeast). The latest version of MOPED adds new estimates of protein abundance and concentration, as well as relative (differential) expression data. MOPED provides a new updated query interface that allows users to explore information by organism, tissue, localization, condition, experiment, or keyword. MOPED supports the Human Proteome Project’s efforts to generate chromosome and diseases specific proteomes by providing links from proteins to chromosome and disease information, as well as many complementary resources. MOPED supports a new omics metadata checklist in order to harmonize data integration, analysis and use. MOPED’s development is driven by the user community, which spans 90 countries guiding future development that will transform MOPED into a multi-omics resource. MOPED encourages users to submit data in a simple format. They can use the metadata a checklist generate a data publication for this submission. As a result, MOPED will provide even greater insights into complex biological processes and systems and enable deeper and more comprehensive biological and biomedical discoveries. PMID:24350770
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Wang, Xijun; Zhang, Aihua; Wang, Ping; Sun, Hui; Wu, Gelin; Sun, Wenjun; Lv, Haitao; Jiao, Guozheng; Xu, Hongying; Yuan, Ye; Liu, Lian; Zou, Dixin; Wu, Zeming; Han, Ying; Yan, Guangli; Dong, Wei; Wu, Fangfang; Dong, Tianwei; Yu, Yang; Zhang, Shuxiang; Wu, Xiuhong; Tong, Xin; Meng, Xiangcai
2013-01-01
To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/additive effect, and activates both intrinsic and extrinsic pathways. PMID:23362329
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Wang, Xijun; Zhang, Aihua; Wang, Ping; Sun, Hui; Wu, Gelin; Sun, Wenjun; Lv, Haitao; Jiao, Guozheng; Xu, Hongying; Yuan, Ye; Liu, Lian; Zou, Dixin; Wu, Zeming; Han, Ying; Yan, Guangli; Dong, Wei; Wu, Fangfang; Dong, Tianwei; Yu, Yang; Zhang, Shuxiang; Wu, Xiuhong; Tong, Xin; Meng, Xiangcai
2013-05-01
To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/additive effect, and activates both intrinsic and extrinsic pathways.
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Lee, Hangyeore; Mun, Dong-Gi; So, Jeong Eun; Bae, Jingi; Kim, Hokeun; Masselon, Christophe; Lee, Sang-Won
2016-12-06
Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.
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Sowa, Steven W; Gelderman, Grant; Leistra, Abigail N; Buvanendiran, Aishwarya; Lipp, Sarah; Pitaktong, Areen; Vakulskas, Christopher A; Romeo, Tony; Baldea, Michael; Contreras, Lydia M
2017-02-28
Multi-target regulators represent a largely untapped area for metabolic engineering and anti-bacterial development. These regulators are complex to characterize because they often act at multiple levels, affecting proteins, transcripts and metabolites. Therefore, single omics experiments cannot profile their underlying targets and mechanisms. In this work, we used an Integrative FourD omics approach (INFO) that consists of collecting and analyzing systems data throughout multiple time points, using multiple genetic backgrounds, and multiple omics approaches (transcriptomics, proteomics and high throughput sequencing crosslinking immunoprecipitation) to evaluate simultaneous changes in gene expression after imposing an environmental stress that accentuates the regulatory features of a network. Using this approach, we profiled the targets and potential regulatory mechanisms of a global regulatory system, the well-studied carbon storage regulatory (Csr) system of Escherichia coli, which is widespread among bacteria. Using 126 sets of proteomics and transcriptomics data, we identified 136 potential direct CsrA targets, including 50 novel ones, categorized their behaviors into distinct regulatory patterns, and performed in vivo fluorescence-based follow up experiments. The results of this work validate 17 novel mRNAs as authentic direct CsrA targets and demonstrate a generalizable strategy to integrate multiple lines of omics data to identify a core pool of regulator targets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
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A proteomics performance standard to support measurement quality in proteomics.
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.
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Design and analysis issues in quantitative proteomics studies.
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.
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2013-01-01
Proteomics has opened a new horizon in biological sciences. Global proteomic analysis is a promising technology for the discovery of thousands of proteins, post-translational modifications, polymorphisms, and molecular interactions in a variety of biological systems. The activities and roles of the identified proteins must also be elucidated, but this is complicated by the inability of conventional proteomic methods to yield quantitative information for protein expression. Thus, a variety of biological systems remain “black boxes”. Quantitative targeted absolute proteomics (QTAP) enables the determination of absolute expression levels (mol) of any target protein, including low-abundance functional proteins, such as transporters and receptors. Therefore, QTAP will be useful for understanding the activities and roles of individual proteins and their differences, including normal/disease, human/animal, or in vitro/in vivo. Here, we describe the study protocols and precautions for QTAP experiments including in silico target peptide selection, determination of peptide concentration by amino acid analysis, setup of selected/multiple reaction monitoring (SRM/MRM) analysis in liquid chromatography–tandem mass spectrometry, preparation of protein samples (brain capillaries and plasma membrane fractions) followed by the preparation of peptide samples, simultaneous absolute quantification of target proteins by SRM/MRM analysis, data analysis, and troubleshooting. An application of QTAP in biological sciences was introduced that utilizes data from inter-strain differences in the protein expression levels of transporters, receptors, tight junction proteins and marker proteins at the blood–brain barrier in ddY, FVB, and C57BL/6J mice. Among 18 molecules, 13 (abcb1a/mdr1a/P-gp, abcc4/mrp4, abcg2/bcrp, slc2a1/glut1, slc7a5/lat1, slc16a1/mct1, slc22a8/oat3, insr, lrp1, tfr1, claudin-5, Na+/K+-ATPase, and γ-gtp) were detected in the isolated brain capillaries, and their
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Severi, Leda; Losi, Lorena; Fonda, Sergio; Taddia, Laura; Gozzi, Gaia; Marverti, Gaetano; Magni, Fulvio; Chinello, Clizia; Stella, Martina; Sheouli, Jalid; Braicu, Elena I; Genovese, Filippo; Lauriola, Angela; Marraccini, Chiara; Gualandi, Alessandra; D'Arca, Domenico; Ferrari, Stefania; Costi, Maria P
2018-01-01
Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuest™ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.
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Microchip-Based Single-Cell Functional Proteomics for Biomedical Applications
Lu, Yao; Yang, Liu; Wei, Wei; Shi, Qihui
2017-01-01
Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that fail to be addressed by traditional population-based methods. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical framework to extract new biology. In this review article, we highlight a few biological and clinical applications in which the microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating well-contolled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies. PMID:28280819
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Matsuda, Fumio; Kinoshita, Syohei; Nishino, Shunsuke; Tomita, Atsumi; Shimizu, Hiroshi
2017-01-01
Central carbon metabolism is controlled by modulating the protein abundance profiles of enzymes that maintain the essential systems in living organisms. In this study, metabolic adaptation mechanisms in the model organism Saccharomyces cerevisiae were investigated by direct determination of enzyme abundance levels in 30 wild type and mutant strains. We performed a targeted proteome analysis using S. cerevisiae strains that lack genes encoding the enzymes responsible for central carbon metabolism. Our analysis revealed that at least 30% of the observed variations in enzyme abundance levels could be explained by global regulatory mechanisms. A enzyme-enzyme co-abundance analysis revealed that the abundances of enzyme proteins involved in the trehalose metabolism and glycolysis changed in a coordinated manner under the control of the transcription factors for global regulation. The remaining variations were derived from local mechanisms such as a mutant-specific increase in the abundances of remote enzymes. The proteome data also suggested that, although the functional compensation of the deficient enzyme was attained by using more resources for protein biosynthesis, available resources for the biosynthesis of the enzymes responsible for central metabolism were not abundant in S. cerevisiae cells. These results showed that global and local regulation of enzyme abundance levels shape central carbon metabolism in S. cerevisiae by using a limited resource for protein biosynthesis.
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Marzano, Valeria; Santini, Simonetta; Rossi, Claudia; Zucchelli, Mirco; D'Alessandro, Annamaria; Marchetti, Carlo; Mingardi, Michele; Stagni, Venturina; Barilà, Daniela; Urbani, Andrea
2012-01-01
Ataxia Telangiectasia Mutated (ATM) protein kinase is a key effector in the modulation of the functionality of some important stress responses, including DNA damage and oxidative stress response, and its deficiency is the hallmark of Ataxia Telangiectasia (A-T), a rare genetic disorder. ATM modulates the activity of hundreds of target proteins, essential for the correct balance between proliferation and cell death. The aim of this study is to evaluate the phenotypic adaptation at the protein level both in basal condition and in presence of proteasome blockage in order to identify the molecules whose level and stability are modulated through ATM expression. We pursued a comparative analysis of ATM deficient and proficient lymphoblastoid cells by label-free shotgun proteomic experiments comparing the panel of proteins differentially expressed. Through a non-supervised comparative bioinformatic analysis these data provided an insight on the functional role of ATM deficiency in cellular carbohydrate metabolism's regulation. This hypothesis has been demonstrated by targeted metabolic fingerprint analysis SRM (Selected Reaction Monitoring) on specific thermodynamic checkpoints of glycolysis. This article is part of a Special Issue entitled: Translational Proteomics. PMID:22641158
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The emergence of top-down proteomics in clinical research
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
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jPOSTrepo: an international standard data repository for proteomes
Okuda, Shujiro; Watanabe, Yu; Moriya, Yuki; Kawano, Shin; Yamamoto, Tadashi; Matsumoto, Masaki; Takami, Tomoyo; Kobayashi, Daiki; Araki, Norie; Yoshizawa, Akiyasu C.; Tabata, Tsuyoshi; Sugiyama, Naoyuki; Goto, Susumu; Ishihama, Yasushi
2017-01-01
Major advancements have recently been made in mass spectrometry-based proteomics, yielding an increasing number of datasets from various proteomics projects worldwide. In order to facilitate the sharing and reuse of promising datasets, it is important to construct appropriate, high-quality public data repositories. jPOSTrepo (https://repository.jpostdb.org/) has successfully implemented several unique features, including high-speed file uploading, flexible file management and easy-to-use interfaces. This repository has been launched as a public repository containing various proteomic datasets and is available for researchers worldwide. In addition, our repository has joined the ProteomeXchange consortium, which includes the most popular public repositories such as PRIDE in Europe for MS/MS datasets and PASSEL for SRM datasets in the USA. Later MassIVE was introduced in the USA and accepted into the ProteomeXchange, as was our repository in July 2016, providing important datasets from Asia/Oceania. Accordingly, this repository thus contributes to a global alliance to share and store all datasets from a wide variety of proteomics experiments. Thus, the repository is expected to become a major repository, particularly for data collected in the Asia/Oceania region. PMID:27899654
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The quest of the human proteome and the missing proteins: digging deeper.
Reddy, Panga Jaipal; Ray, Sandipan; Srivastava, Sanjeeva
2015-05-01
view was to study the wider tissue range with multiple digesting enzymes and follow targeted proteomics workflow in particular. On the innovation trajectory from the proteomics laboratory to novel proteomics diagnostics and therapeutics in society, we will also need new conceptual frames for translation science and innovation strategy in proteomics. These will embody both technical as well as rigorous social science and humanities considerations to understand the correlates of the proteome from cell to society.
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Architecture Mapping of the Inner Mitochondrial Membrane Proteome by Chemical Tools in Live Cells.
Lee, Song-Yi; Kang, Myeong-Gyun; Shin, Sanghee; Kwak, Chulhwan; Kwon, Taejoon; Seo, Jeong Kon; Kim, Jong-Seo; Rhee, Hyun-Woo
2017-03-15
The inner mitochondrial membrane (IMM) proteome plays a central role in maintaining mitochondrial physiology and cellular metabolism. Various important biochemical reactions such as oxidative phosphorylation, metabolite production, and mitochondrial biogenesis are conducted by the IMM proteome, and mitochondria-targeted therapeutics have been developed for IMM proteins, which is deeply related for various human metabolic diseases including cancer and neurodegenerative diseases. However, the membrane topology of the IMM proteome remains largely unclear because of the lack of methods to evaluate it in live cells in a high-throughput manner. In this article, we reveal the in vivo topological direction of 135 IMM proteins, using an in situ-generated radical probe with genetically targeted peroxidase (APEX). Owing to the short lifetime of phenoxyl radicals generated in situ by submitochondrial targeted APEX and the impermeability of the IMM to small molecules, the solvent-exposed tyrosine residues of both the matrix and intermembrane space (IMS) sides of IMM proteins were exclusively labeled with the radical probe in live cells by Matrix-APEX and IMS-APEX, respectively and identified by mass spectrometry. From this analysis, we confirmed 58 IMM protein topologies and we could determine the topological direction of 77 IMM proteins whose topology at the IMM has not been fully characterized. We also found several IMM proteins (e.g., LETM1 and OXA1) whose topological information should be revised on the basis of our results. Overall, our identification of structural information on the mitochondrial inner-membrane proteome can provide valuable insights for the architecture and connectome of the IMM proteome in live cells.
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van Vlijmen, Bart J.; Yang, Juncong; Percy, Andrew J.
2017-01-01
The plasma levels of pro- and anticoagulant proteins are important markers for venous thrombosis (VT) risk and can be affected by both genetic and acquired factors, including cancer. Generally, these markers are measured using activity- or antibody-based assays. Targeted proteomics with stable-isotope–labeled internal standards has proven adept at the rapid, multiplex, and precise quantification of proteins in complex biological samples such as plasma. We used liquid chromatography coupled to multiple reaction monitoring (MRM) mass spectrometry to evaluate the concentrations of 31 coagulation- and fibrinolysis-related proteins in plasma from 25 healthy controls, 25 patients with VT, and 25 patients with VT who were also diagnosed with cancer. The concentration level of 1 to 3 proteotypic peptides per protein was determined, and all samples were previously characterized using traditional antibody- or activity-based methods. When comparing the conventional and the MRM strategies, the mean Pearson correlation for the 13 proteins (covered by 36 target peptides) shared between the 2 approaches was 0.77, indicating a good correlation. Additionally, MRM offers higher sensitivity (mean regression slope, 0.81), higher multiplicity in a single run, and good ability to leverage all measurements to discriminate groups using unsupervised clustering, which identified vitamin K antagonist users as well as patients with VT and cancer. The data collected using MRM show that the combination of coagulation factor levels yields signature information on VT and cancer, which was not obvious from a single measurement. These results encourage the further validation and investigation of MRM in profiling protein signature of disease. PMID:29296750
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Architecture of a Host-Parasite Interface: Complex Targeting Mechanisms Revealed Through Proteomics.
Gadelha, Catarina; Zhang, Wenzhu; Chamberlain, James W; Chait, Brian T; Wickstead, Bill; Field, Mark C
2015-07-01
Surface membrane organization and composition is key to cellular function, and membrane proteins serve many essential roles in endocytosis, secretion, and cell recognition. The surface of parasitic organisms, however, is a double-edged sword; this is the primary interface between parasites and their hosts, and those crucial cellular processes must be carried out while avoiding elimination by the host immune defenses. For extracellular African trypanosomes, the surface is partitioned such that all endo- and exocytosis is directed through a specific membrane region, the flagellar pocket, in which it is thought the majority of invariant surface proteins reside. However, very few of these proteins have been identified, severely limiting functional studies, and hampering the development of potential treatments. Here we used an integrated biochemical, proteomic and bioinformatic strategy to identify surface components of the human parasite Trypanosoma brucei. This surface proteome contains previously known flagellar pocket proteins as well as multiple novel components, and is significantly enriched in proteins that are essential for parasite survival. Molecules with receptor-like properties are almost exclusively parasite-specific, whereas transporter-like proteins are conserved in model organisms. Validation shows that the majority of surface proteome constituents are bona fide surface-associated proteins and, as expected, most present at the flagellar pocket. Moreover, the largest systematic analysis of trypanosome surface molecules to date provides evidence that the cell surface is compartmentalized into three distinct domains with free diffusion of molecules in each, but selective, asymmetric traffic between. This work provides a paradigm for the compartmentalization of a cell surface and a resource for its analysis. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
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Use of proteomic methods in the analysis of human body fluids in Alzheimer research.
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.
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Lata, Manju; Sharma, Divakar; Kumar, Bhavnesh; Deo, Nirmala; Tiwari, Pramod Kumar; Bisht, Deepa; Venkatesan, Krishnamurthy
2015-01-01
Ofloxacin (OFX) and moxifloxacin (MOX) are the most promising second line drugs for tuberculosis treatment. Although the primary mechanism of action of OFX and MOX is gyrase inhibition, other possible mechanisms cannot be ruled out. Being the functional moiety of cell, the proteins act as primary targets for developing drugs, diagnostics and therapeutics. In this study we have investigated the proteomic changes of Mycobacterium tuberculosis isolates induced by OFX and MOX by applying comparative proteomic approaches based on two-dinensional gel electrophoresis (2DE) along with matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI TOF/TOF-MS) and bioinformatic tools. The findings are likely to provide new understanding of OFX and MOX mechanisms that might be helpful in exploring new diagnostics and drug targets. Our study explored eleven proteins (Rv2889c, Rv2623, Rv0952, Rv1827, Rv1932, Rv0054, Rv1080c, Rv3418c, Rv3914, Rv1636 and Rv0009) that were overexpressed in the presence of drugs. Among them, Rv2623, Rv1827 and Rv1636 were identified as proteins with unknown function. InterProScan and molecular docking revealed that the conserved domain of hypothetical proteins interact with OFX and MOX which indicate a probable inhibition/modulation of the functioning of these proteins by both drugs, which might be overexpressed to overcome this effect.
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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.
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Characterization, design, and function of the mitochondrial proteome: from organs to organisms.
Lotz, Christopher; Lin, Amanda J; Black, Caitlin M; Zhang, Jun; Lau, Edward; Deng, Ning; Wang, Yueju; Zong, Nobel C; Choi, Jeong H; Xu, Tao; Liem, David A; Korge, Paavo; Weiss, James N; Hermjakob, Henning; Yates, John R; Apweiler, Rolf; Ping, Peipei
2014-02-07
Mitochondria are a common energy source for organs and organisms; their diverse functions are specialized according to the unique phenotypes of their hosting environment. Perturbation of mitochondrial homeostasis accompanies significant pathological phenotypes. However, the connections between mitochondrial proteome properties and function remain to be experimentally established on a systematic level. This uncertainty impedes the contextualization and translation of proteomic data to the molecular derivations of mitochondrial diseases. We present a collection of mitochondrial features and functions from four model systems, including two cardiac mitochondrial proteomes from distinct genomes (human and mouse), two unique organ mitochondrial proteomes from identical genetic codons (mouse heart and mouse liver), as well as a relevant metazoan out-group (drosophila). The data, composed of mitochondrial protein abundance and their biochemical activities, capture the core functionalities of these mitochondria. This investigation allowed us to redefine the core mitochondrial proteome from organs and organisms, as well as the relevant contributions from genetic information and hosting milieu. Our study has identified significant enrichment of disease-associated genes and their products. Furthermore, correlational analyses suggest that mitochondrial proteome design is primarily driven by cellular environment. Taken together, these results connect proteome feature with mitochondrial function, providing a prospective resource for mitochondrial pathophysiology and developing novel therapeutic targets in medicine.
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Omenn, Gilbert S; Lane, Lydie; Lundberg, Emma K; Beavis, Ronald C; Overall, Christopher M; Deutsch, Eric W
2016-11-04
variants (SAAVSs), and splice isoforms. Meanwhile, the Biology- and Disease-driven (B/D)-HPP has created comprehensive SRM resources, generated popular protein lists to guide targeted proteomics assays for specific diseases, and launched an Early Career Researchers initiative.
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The unique peptidome: Taxon-specific tryptic peptides as biomarkers for targeted metaproteomics.
Mesuere, Bart; Van der Jeugt, Felix; Devreese, Bart; Vandamme, Peter; Dawyndt, Peter
2016-09-01
The Unique Peptide Finder (http://unipept.ugent.be/peptidefinder) is an interactive web application to quickly hunt for tryptic peptides that are unique to a particular species, genus, or any other taxon. Biodiversity within the target taxon is represented by a set of proteomes selected from a monthly updated list of complete and nonredundant UniProt proteomes, supplemented with proprietary proteomes loaded into persistent local browser storage. The software computes and visualizes pan and core peptidomes as unions and intersections of tryptic peptides occurring in the selected proteomes. In addition, it also computes and displays unique peptidomes as the set of all tryptic peptides that occur in all selected proteomes but not in any UniProt record not assigned to the target taxon. As a result, the unique peptides can serve as robust biomarkers for the target taxon, for example, in targeted metaproteomics studies. Computations are extremely fast since they are underpinned by the Unipept database, the lowest common ancestor algorithm implemented in Unipept and modern web technologies that facilitate in-browser data storage and parallel processing. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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The proteomic landscape of triple-negative breast cancer.
Lawrence, Robert T; Perez, Elizabeth M; Hernández, Daniel; Miller, Chris P; Haas, Kelsey M; Irie, Hanna Y; Lee, Su-In; Blau, C Anthony; Villén, Judit
2015-04-28
Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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Probing the Proteome on Earth and Beyond
NASA Astrophysics Data System (ADS)
Ostrom, P.
2008-12-01
Less than a decade ago, protein sequencing was the bane of paleobiology. Since that time researchers have completely sequenced proteins in >50 Ka fossils, been dazzled by reports of collagen peptides in dinosaur bones, and witnessed the development of phylogenetic trees from ancient protein sequences. Enlisting proteomics as biosignature is now in our grasp. In this talk the pitfalls and challenges of mass spectrometric approaches to protein sequencing will be illustrated and phylogenetic applications will be discussed. Work on extinct organisms at Michigan State University, University of Michigan and York University will provide a vantage point to assess methodologies, explore diagenetic alterations, evaluate mass spectra and illustrate issues associated with data base searching. Challenges encountered in the study of paleoproteomics, such as the absence of sequences for extinct organisms in commercially available databases, protein diagenesis and low concentrations of target are parallel to those that will be encountered when protein sequencing is extended to extreme and extraterrestrial environments. Thus, lessons learned from interrogating the ancient proteome are important and necessary step in developing proteomics as a biosignature tools.
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Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J.; Chatterjee, Aditi; Prasad, T. S. Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva
2015-01-01
Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division. PMID:25874956
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Reddy, Panga Jaipal; Sinha, Sneha; Ray, Sandipan; Sathe, Gajanan J; Chatterjee, Aditi; Prasad, T S Keshava; Dhali, Snigdha; Srikanth, Rapole; Panda, Dulal; Srivastava, Sanjeeva
2015-01-01
Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division.
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Redox Proteomics: A Key Tool for New Insights into Protein Modification with Relevance to Disease.
Butterfield, D Allan; Perluigi, Marzia
2017-03-01
Oxidatively modified proteins are characterized by elevations in protein-resident carbonyls or 3-nitrotyrosine, measures of protein oxidation, or protein bound reactive alkenals such as 4-hydroxy-2-nonenal, a measure of lipid peroxidation. Oxidatively modified proteins nearly always have altered structure and function. Redox proteomics is that branch of proteomics used to identify oxidized proteins and determine the extent and location of oxidative modifications in the proteomes of interest. This technique nearly always employs mass spectrometry as the major platform to achieve the goals of identifying the target proteins. Once identified, oxidatively modified proteins can be placed in specific molecular pathways to provide insights into protein oxidation and human disease. Both original research and review articles are included in this Forum on Redox Proteomics. The topics related to redox proteomics range from basic chemistry of sulfur radical-induced redox modifications in proteins, to the thiol secretome and inflammatory network, to reversible thiol oxidation in proteomes, to the role of glutamine synthetase in peripheral and central environments on inflammation and insulin resistance, to bioanalytical aspects of tyrosine nitrated proteins, to protein oxidation in human smokers and models thereof, and to Alzheimer disease, including articles on the brain ubiquitinylome and the "triangle of death" composed of oxidatively modified proteins involved in energy metabolism, mammalian target of rampamycin activation, and the proteostasis network. This Forum on Redox Proteomics is both timely and a critically important resource to highlight one of the key tools needed to better understand protein structure and function in oxidative environments in health and disease. Antioxid. Redox Signal. 26, 277-279.
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Proteomics of Skeletal Muscle: Focus on Insulin Resistance and Exercise Biology
Deshmukh, Atul S.
2016-01-01
Skeletal muscle is the largest tissue in the human body and plays an important role in locomotion and whole body metabolism. It accounts for ~80% of insulin stimulated glucose disposal. Skeletal muscle insulin resistance, a primary feature of Type 2 diabetes, is caused by a decreased ability of muscle to respond to circulating insulin. Physical exercise improves insulin sensitivity and whole body metabolism and remains one of the most promising interventions for the prevention of Type 2 diabetes. Insulin resistance and exercise adaptations in skeletal muscle might be a cause, or consequence, of altered protein expressions profiles and/or their posttranslational modifications (PTMs). Mass spectrometry (MS)-based proteomics offer enormous promise for investigating the molecular mechanisms underlying skeletal muscle insulin resistance and exercise-induced adaptation; however, skeletal muscle proteomics are challenging. This review describes the technical limitations of skeletal muscle proteomics as well as emerging developments in proteomics workflow with respect to samples preparation, liquid chromatography (LC), MS and computational analysis. These technologies have not yet been fully exploited in the field of skeletal muscle proteomics. Future studies that involve state-of-the-art proteomics technology will broaden our understanding of exercise-induced adaptations as well as molecular pathogenesis of insulin resistance. This could lead to the identification of new therapeutic targets. PMID:28248217
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A Method for Label-Free, Differential Top-Down Proteomics.
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.
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CIG-P: Circular Interaction Graph for Proteomics.
Hobbs, Christopher K; Leung, Michelle; Tsang, Herbert H; Ebhardt, H Alexander
2014-10-31
A typical affinity purification coupled to mass spectrometry (AP-MS) experiment includes the purification of a target protein (bait) using an antibody and subsequent mass spectrometry analysis of all proteins co-purifying with the bait (aka prey proteins). Like any other systems biology approach, AP-MS experiments generate a lot of data and visualization has been challenging, especially when integrating AP-MS experiments with orthogonal datasets. We present Circular Interaction Graph for Proteomics (CIG-P), which generates circular diagrams for visually appealing final representation of AP-MS data. Through a Java based GUI, the user inputs experimental and reference data as file in csv format. The resulting circular representation can be manipulated live within the GUI before exporting the diagram as vector graphic in pdf format. The strength of CIG-P is the ability to integrate orthogonal datasets with each other, e.g. affinity purification data of kinase PRPF4B in relation to the functional components of the spliceosome. Further, various AP-MS experiments can be compared to each other. CIG-P aids to present AP-MS data to a wider audience and we envision that the tool finds other applications too, e.g. kinase - substrate relationships as a function of perturbation. CIG-P is available under: http://sourceforge.net/projects/cig-p/
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Lancaster, T S; Jefferson, S J; Hunter, J Craig; Lopez, Veronica; Van Eyk, J E; Lakatta, E G; Korzick, D H
2012-10-17
The incidence of myocardial infarction rises sharply at menopause, implicating a potential role for estrogen (E(2)) loss in age-related increases in ischemic injury. We aimed to identify quantitative changes to the cardiac mitochondrial proteome of aging females, based on the hypothesis that E(2) deficiency exacerbates age-dependent disruptions in mitochondrial proteins. Mitochondria isolated from left ventricles of adult (6 mo) and aged (24 mo) F344 ovary-intact or ovariectomized (OVX) rats were labeled with 8plex isobaric tags for relative and absolute quantification (iTRAQ; n = 5-6/group). Groups studied were adult, adult OVX, aged, and aged OVX. In vivo coronary artery ligation and in vitro mitochondrial respiration studies were also performed in a subset of rats. We identified 965 proteins across groups and significant directional changes in 67 proteins of aged and/or aged OVX; 32 proteins were unique to aged OVX. Notably, only six proteins were similarly altered in adult OVX (voltage-dependent ion channel 1, adenine nucleotide translocator 1, cytochrome c oxidase subunits VIIc and VIc, catalase, and myosin binding protein C). Proteins affected by aging were primarily related to cellular metabolism, oxidative stress, and cell death. The largest change occurred in monoamine oxidase-A (MAO-A), a source of oxidative stress. While acute MAO-A inhibition induced mild uncoupling in aged mitochondria, reductions in infarct size were not observed. Age-dependent alterations in mitochondrial signaling indicate a highly selective myocardial response to E(2) deficiency. The combined proteomic and functional approaches described here offer possibility of new protein targets for experimentation and therapeutic intervention in the aged female population.
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Domazet, Barbara; MacLennan, Gregory T.; Lopez-Beltran, Antonio; Montironi, Rodolfo; Cheng, Liang
2008-01-01
The advent of new technologies has enabled deeper insight into processes atsubcellular levels, which will ultimately improve diagnostic procedures and patient outcome. Thanks to cell enrichment methods, it is now possible to study cells in their native environment. This has greatly contributed to a rapid growth in several areas, such as gene expression analysis, proteomics, and metabolonomics. Laser capture microdissection (LCM) as a method of procuring subpopulations of cells under direct visual inspection is playing an important role in these areas. This review provides an overview of existing LCM technology and its downstream applications in genomics, proteomics, diagnostics and therapy. PMID:18787684
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Domazet, Barbara; Maclennan, Gregory T; Lopez-Beltran, Antonio; Montironi, Rodolfo; Cheng, Liang
2008-03-15
The advent of new technologies has enabled deeper insight into processes at subcellular levels, which will ultimately improve diagnostic procedures and patient outcome. Thanks to cell enrichment methods, it is now possible to study cells in their native environment. This has greatly contributed to a rapid growth in several areas, such as gene expression analysis, proteomics, and metabolonomics. Laser capture microdissection (LCM) as a method of procuring subpopulations of cells under direct visual inspection is playing an important role in these areas. This review provides an overview of existing LCM technology and its downstream applications in genomics, proteomics, diagnostics and therapy.
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Proteomics research in India: an update.
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.
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Proteomic analyses of host and pathogen responses during bovine mastitis.
Boehmer, Jamie L
2011-12-01
The pursuit of biomarkers for use as clinical screening tools, measures for early detection, disease monitoring, and as a means for assessing therapeutic responses has steadily evolved in human and veterinary medicine over the past two decades. Concurrently, advances in mass spectrometry have markedly expanded proteomic capabilities for biomarker discovery. While initial mass spectrometric biomarker discovery endeavors focused primarily on the detection of modulated proteins in human tissues and fluids, recent efforts have shifted to include proteomic analyses of biological samples from food animal species. Mastitis continues to garner attention in veterinary research due mainly to affiliated financial losses and food safety concerns over antimicrobial use, but also because there are only a limited number of efficacious mastitis treatment options. Accordingly, comparative proteomic analyses of bovine milk have emerged in recent years. Efforts to prevent agricultural-related food-borne illness have likewise fueled an interest in the proteomic evaluation of several prominent strains of bacteria, including common mastitis pathogens. The interest in establishing biomarkers of the host and pathogen responses during bovine mastitis stems largely from the need to better characterize mechanisms of the disease, to identify reliable biomarkers for use as measures of early detection and drug efficacy, and to uncover potentially novel targets for the development of alternative therapeutics. The following review focuses primarily on comparative proteomic analyses conducted on healthy versus mastitic bovine milk. However, a comparison of the host defense proteome of human and bovine milk and the proteomic analysis of common veterinary pathogens are likewise introduced.
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The Proteome Folding Project: Proteome-scale prediction of structure and function
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
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Chimeric origins of ochrophytes and haptophytes revealed through an ancient plastid proteome
Dorrell, Richard G; Gile, Gillian; McCallum, Giselle; Méheust, Raphaël; Bapteste, Eric P; Klinger, Christen M; Brillet-Guéguen, Loraine; Freeman, Katalina D; Richter, Daniel J; Bowler, Chris
2017-01-01
Plastids are supported by a wide range of proteins encoded within the nucleus and imported from the cytoplasm. These plastid-targeted proteins may originate from the endosymbiont, the host, or other sources entirely. Here, we identify and characterise 770 plastid-targeted proteins that are conserved across the ochrophytes, a major group of algae including diatoms, pelagophytes and kelps, that possess plastids derived from red algae. We show that the ancestral ochrophyte plastid proteome was an evolutionary chimera, with 25% of its phylogenetically tractable nucleus-encoded proteins deriving from green algae. We additionally show that functional mixing of host and plastid proteomes, such as through dual-targeting, is an ancestral feature of plastid evolution. Finally, we detect a clear phylogenetic signal from one ochrophyte subgroup, the lineage containing pelagophytes and dictyochophytes, in plastid-targeted proteins from another major algal lineage, the haptophytes. This may represent a possible serial endosymbiosis event deep in eukaryotic evolutionary history. DOI: http://dx.doi.org/10.7554/eLife.23717.001 PMID:28498102
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NASA Astrophysics Data System (ADS)
Vasaturo, Michele; Fiengo, Lorenzo; de Tommasi, Nunziatina; Sabatino, Lina; Ziccardi, Pamela; Colantuoni, Vittorio; Bruno, Maurizio; Cerchia, Carmen; Novellino, Ettore; Lupo, Angelo; Lavecchia, Antonio; Piaz, Fabrizio Dal
2017-01-01
Proteomics based approaches are emerging as useful tools to identify the targets of bioactive compounds and elucidate their molecular mechanisms of action. Here, we applied a chemical proteomic strategy to identify the peroxisome proliferator-activated receptor γ (PPARγ) as a molecular target of the pro-apoptotic agent 15-ketoatractyligenin methyl ester (compound 1). We demonstrated that compound 1 interacts with PPARγ, forms a covalent bond with the thiol group of C285 and occupies the sub-pocket between helix H3 and the β-sheet of the ligand-binding domain (LBD) of the receptor by Surface Plasmon Resonance (SPR), mass spectrometry-based studies and docking experiments. 1 displayed partial agonism of PPARγ in cell-based transactivation assays and was found to inhibit the AKT pathway, as well as its downstream targets. Consistently, a selective PPARγ antagonist (GW9662) greatly reduced the anti-proliferative and pro-apoptotic effects of 1, providing the molecular basis of its action. Collectively, we identified 1 as a novel PPARγ partial agonist and elucidated its mode of action, paving the way for therapeutic strategies aimed at tailoring novel PPARγ ligands with reduced undesired harmful side effects.
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Vasaturo, Michele; Fiengo, Lorenzo; De Tommasi, Nunziatina; Sabatino, Lina; Ziccardi, Pamela; Colantuoni, Vittorio; Bruno, Maurizio; Cerchia, Carmen; Novellino, Ettore; Lupo, Angelo; Lavecchia, Antonio; Piaz, Fabrizio Dal
2017-01-01
Proteomics based approaches are emerging as useful tools to identify the targets of bioactive compounds and elucidate their molecular mechanisms of action. Here, we applied a chemical proteomic strategy to identify the peroxisome proliferator-activated receptor γ (PPARγ) as a molecular target of the pro-apoptotic agent 15-ketoatractyligenin methyl ester (compound 1). We demonstrated that compound 1 interacts with PPARγ, forms a covalent bond with the thiol group of C285 and occupies the sub-pocket between helix H3 and the β-sheet of the ligand-binding domain (LBD) of the receptor by Surface Plasmon Resonance (SPR), mass spectrometry-based studies and docking experiments. 1 displayed partial agonism of PPARγ in cell-based transactivation assays and was found to inhibit the AKT pathway, as well as its downstream targets. Consistently, a selective PPARγ antagonist (GW9662) greatly reduced the anti-proliferative and pro-apoptotic effects of 1, providing the molecular basis of its action. Collectively, we identified 1 as a novel PPARγ partial agonist and elucidated its mode of action, paving the way for therapeutic strategies aimed at tailoring novel PPARγ ligands with reduced undesired harmful side effects. PMID:28117438
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Vasaturo, Michele; Fiengo, Lorenzo; De Tommasi, Nunziatina; Sabatino, Lina; Ziccardi, Pamela; Colantuoni, Vittorio; Bruno, Maurizio; Cerchia, Carmen; Novellino, Ettore; Lupo, Angelo; Lavecchia, Antonio; Piaz, Fabrizio Dal
2017-01-24
Proteomics based approaches are emerging as useful tools to identify the targets of bioactive compounds and elucidate their molecular mechanisms of action. Here, we applied a chemical proteomic strategy to identify the peroxisome proliferator-activated receptor γ (PPARγ) as a molecular target of the pro-apoptotic agent 15-ketoatractyligenin methyl ester (compound 1). We demonstrated that compound 1 interacts with PPARγ, forms a covalent bond with the thiol group of C285 and occupies the sub-pocket between helix H3 and the β-sheet of the ligand-binding domain (LBD) of the receptor by Surface Plasmon Resonance (SPR), mass spectrometry-based studies and docking experiments. 1 displayed partial agonism of PPARγ in cell-based transactivation assays and was found to inhibit the AKT pathway, as well as its downstream targets. Consistently, a selective PPARγ antagonist (GW9662) greatly reduced the anti-proliferative and pro-apoptotic effects of 1, providing the molecular basis of its action. Collectively, we identified 1 as a novel PPARγ partial agonist and elucidated its mode of action, paving the way for therapeutic strategies aimed at tailoring novel PPARγ ligands with reduced undesired harmful side effects.
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Di Girolamo, Francesco; Righetti, Pier Giorgio; Soste, Martin; Feng, Yuehan; Picotti, Paola
2013-08-26
Systems biology studies require the capability to quantify with high precision proteins spanning a broad range of abundances across multiple samples. However, the broad range of protein expression in cells often precludes the detection of low-abundance proteins. Different sample processing techniques can be applied to increase proteome coverage. Among these, combinatorial (hexa)peptide ligand libraries (CPLLs) bound to solid matrices have been used to specifically capture and detect low-abundance proteins in complex samples. To assess whether CPLL capture can be applied in systems biology studies involving the precise quantitation of proteins across a multitude of samples, we evaluated its performance across the whole range of protein abundances in Saccharomyces cerevisiae. We used selected reaction monitoring assays for a set of target proteins covering a broad abundance range to quantitatively evaluate the precision of the approach and its capability to detect low-abundance proteins. Replicated CPLL-isolates showed an average variability of ~10% in the amount of the isolated proteins. The high reproducibility of the technique was not dependent on the abundance of the protein or the amount of beads used for the capture. However, the protein-to-bead ratio affected the enrichment of specific proteins. We did not observe a normalization effect of CPLL beads on protein abundances. However, CPLLs enriched for and depleted specific sets of proteins and thus changed the abundances of proteins from a whole proteome extract. This allowed the identification of ~400 proteins otherwise undetected in an untreated sample, under the experimental conditions used. CPLL capture is thus a useful tool to increase protein identifications in proteomic experiments, but it should be coupled to the analysis of untreated samples, to maximize proteome coverage. Our data also confirms that CPLL capture is reproducible and can be confidently used in quantitative proteomic experiments
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El-Rami, Fadi; Nelson, Kristina; Xu, Ping
2017-01-01
Streptococcus sanguinis is a commensal and early colonizer of oral cavity as well as an opportunistic pathogen of infectious endocarditis. Extracting the soluble proteome of this bacterium provides deep insights about the physiological dynamic changes under different growth and stress conditions, thus defining “proteomic signatures” as targets for therapeutic intervention. In this protocol, we describe an experimentally verified approach to extract maximal cytoplasmic proteins from Streptococcus sanguinis SK36 strain. A combination of procedures was adopted that broke the thick cell wall barrier and minimized denaturation of the intracellular proteome, using optimized buffers and a sonication step. Extracted proteome was quantitated using Pierce BCA Protein Quantitation assay and protein bands were macroscopically assessed by Coomassie Blue staining. Finally, a high resolution detection of the extracted proteins was conducted through Synapt G2Si mass spectrometer, followed by label-free relative quantification via Progenesis QI. In conclusion, this pipeline for proteomic extraction and analysis of soluble proteins provides a fundamental tool in deciphering the biological complexity of Streptococcus sanguinis. PMID:29152022
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Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics
Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang
2013-01-01
Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026
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Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1
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
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Development of proteome-wide binding reagents for research and diagnostics.
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.
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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
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The online Tabloid Proteome: an annotated database of protein associations
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
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Williamson, Nicholas A
2018-03-01
This paper discusses the successful adoption of a subscription-based, open-access model of service delivery for a mass spectrometry and proteomics facility. In 2009, the Mass Spectrometry and Proteomics Facility at the University of Melbourne (Australia) moved away from the standard fee for service model of service provision. Instead, the facility adopted a subscription- or membership-based, open-access model of service delivery. For a low fixed yearly cost, users could directly operate the instrumentation but, more importantly, there were no limits on usage other than the necessity to share available instrument time with all other users. All necessary training from platform staff and many of the base reagents were also provided as part of the membership cost. These changes proved to be very successful in terms of financial outcomes for the facility, instrument access and usage, and overall research output. This article describes the systems put in place as well as the overall successes and challenges associated with the operation of a mass spectrometry/proteomics core in this manner. Graphical abstract ᅟ.
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NASA Astrophysics Data System (ADS)
Williamson, Nicholas A.
2018-03-01
This paper discusses the successful adoption of a subscription-based, open-access model of service delivery for a mass spectrometry and proteomics facility. In 2009, the Mass Spectrometry and Proteomics Facility at the University of Melbourne (Australia) moved away from the standard fee for service model of service provision. Instead, the facility adopted a subscription- or membership-based, open-access model of service delivery. For a low fixed yearly cost, users could directly operate the instrumentation but, more importantly, there were no limits on usage other than the necessity to share available instrument time with all other users. All necessary training from platform staff and many of the base reagents were also provided as part of the membership cost. These changes proved to be very successful in terms of financial outcomes for the facility, instrument access and usage, and overall research output. This article describes the systems put in place as well as the overall successes and challenges associated with the operation of a mass spectrometry/proteomics core in this manner. [Figure not available: see fulltext.
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Wheat proteomics: proteome modulation and abiotic stress acclimation
Komatsu, Setsuko; Kamal, Abu H. M.; Hossain, Zahed
2014-01-01
Cellular mechanisms of stress sensing and signaling represent the initial plant responses to adverse conditions. The development of high-throughput “Omics” techniques has initiated a new era of the study of plant molecular strategies for adapting to environmental changes. However, the elucidation of stress adaptation mechanisms in plants requires the accurate isolation and characterization of stress-responsive proteins. Because the functional part of the genome, namely the proteins and their post-translational modifications, are critical for plant stress responses, proteomic studies provide comprehensive information about the fine-tuning of cellular pathways that primarily involved in stress mitigation. This review summarizes the major proteomic findings related to alterations in the wheat proteomic profile in response to abiotic stresses. Moreover, the strengths and weaknesses of different sample preparation techniques, including subcellular protein extraction protocols, are discussed in detail. The continued development of proteomic approaches in combination with rapidly evolving bioinformatics tools and interactive databases will facilitate understanding of the plant mechanisms underlying stress tolerance. PMID:25538718
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Lakra, Nita; Kaur, Charanpreet; Anwar, Khalid; Singla-Pareek, Sneh Lata; Pareek, Ashwani
2018-05-01
High salinity is one of the major problems in crop productivity, affecting seed germination as well as yield. In order to enhance tolerance of crops towards salinity, it is essential to understand the underlying physiological and molecular mechanisms. In this endeavor, study of contrasting genotypes of the same species differing in their response towards salinity stress can be very useful. In the present study, we have investigated temporal differences in morphological, physiological and proteome profiles of two contrasting genotypes of rice to understand the basis of salt tolerance. When compared to IR64 rice, Pokkali, the salt-tolerant wild genotype, has enhanced capacity to cope with stress, better growth rate and possesses efficient antioxidant system, as well as better photosynthetic machinery. Our proteome studies revealed a higher and an early abundance of proteins involved in stress tolerance and photosynthesis in Pokkali in comparison with IR64, which, in contrast, showed greater changes in metabolic machinery even during early duration of stress. Our findings suggest important differences in physicochemical and proteome profiles of the two genotypes, which may be the basis of observed stress tolerance in the salt-tolerant Pokkali. © 2017 John Wiley & Sons Ltd.
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James, Peter
2011-09-01
The most critical functions of the various proteomics organisations are the training of young scientists and the dissemination of information to the general scientific community. The education committees of the Human Proteome Organisation (HUPO) and the European Proteomics Association (EuPA) together with their national counterparts are therefore launching the International Proteomics Tutorial Programme to meet these needs. The programme is being led by Peter James (Sweden), Thierry Rabilloud (France) and Kazuyuki Nakamura (Japan). It involves collaboration between the leading proteomics journals: Journal of Proteome Research, Journal of Proteomics, Molecular and Cellular Proteomics, and Proteomics. The overall level is aimed at Masters/PhD level students who are starting out their research and who would benefit from a solid grounding in the techniques used in modern protein-based research. The tutorial program will cover core techniques and basics as an introduction to scientists new to the field. At a later stage the programme may be expanded with a series of more advanced topics focussing on the application of proteomics techniques to biological problem solving. The entire series of articles and slides will be made freely available for teaching use at the Journals and Organisations homepages and at a special website, www.proteomicstutorials.org. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Helgeland, Erik; Breivik, Lars Ertesvåg; Vaudel, Marc; Svendsen, Øyvind Sverre; Garberg, Hilde; Nordrehaug, Jan Erik; Berven, Frode Steingrimsen; Jonassen, Anne Kristine
2014-01-01
Despite major advances in early revascularization techniques, cardiovascular diseases are still the leading cause of death worldwide, and myocardial infarctions contribute heavily to this. Over the past decades, it has become apparent that reperfusion of blood to a previously ischemic area of the heart causes damage in and of itself, and that this ischemia reperfusion induced injury can be reduced by up to 50% by mechanical manipulation of the blood flow to the heart. The recent discovery of remote ischemic preconditioning (RIPC) provides a non-invasive approach of inducing this cardioprotection at a distance. Finding its endogenous mediators and their operative mode is an important step toward increasing the ischemic tolerance. The release of humoral factor(s) upon RIPC was recently demonstrated and several candidate proteins were published as possible mediators of the cardioprotection. Before clinical applicability, these potential biomarkers and their efficiency must be validated, a task made challenging by the large heterogeneity in reported data and results. Here, in an attempt to reproduce and provide more experimental data on these mediators, we conducted an unbiased in-depth analysis of the human plasma proteome before and after RIPC. From the 68 protein markers reported in the literature, only 28 could be mapped to manually reviewed (Swiss-Prot) protein sequences. 23 of them were monitored in our untargeted experiment. However, their significant regulation could not be reproducibly estimated. In fact, among the 394 plasma proteins we accurately quantified, no significant regulation could be confidently and reproducibly assessed. This indicates that it is difficult to both monitor and reproduce published data from experiments exploring for RIPC induced plasma proteomic regulations, and suggests that further work should be directed towards small humoral factors. To simplify this task, we made our proteomic dataset available via ProteomeXchange, where
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Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation
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
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Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.
Rivero-Hinojosa, Samuel; Lau, Ling San; Stampar, Mojca; Staal, Jerome; Zhang, Huizhen; Gordish-Dressman, Heather; Northcott, Paul A; Pfister, Stefan M; Taylor, Michael D; Brown, Kristy J; Rood, Brian R
2018-06-07
Genomic characterization has begun to redefine diagnostic classifications of cancers. However, it remains a challenge to infer disease phenotypes from genomic alterations alone. To help realize the promise of genomics, we have performed a quantitative proteomics investigation using Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and 41 tissue samples spanning the 4 genomically based subgroups of medulloblastoma and control cerebellum. We have identified and quantitated thousands of proteins across these groups and find that we are able to recapitulate the genomic subgroups based upon subgroup restricted and differentially abundant proteins while also identifying subgroup specific protein isoforms. Integrating our proteomic measurements with genomic data, we calculate a poor correlation between mRNA and protein abundance. Using EPIC 850 k methylation array data on the same tissues, we also investigate the influence of copy number alterations and DNA methylation on the proteome in an attempt to characterize the impact of these genetic features on the proteome. Reciprocally, we are able to use the proteome to identify which genomic alterations result in altered protein abundance and thus are most likely to impact biology. Finally, we are able to assemble protein-based pathways yielding potential avenues for clinical intervention. From these, we validate the EIF4F cap-dependent translation pathway as a novel druggable pathway in medulloblastoma. Thus, quantitative proteomics complements genomic platforms to yield a more complete understanding of functional tumor biology and identify novel therapeutic targets for medulloblastoma.
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Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi
2008-08-01
In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.
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Investigating RAS Signaling in Cancer | Office of Cancer Clinical Proteomics Research
CPTAC expertise has been charged to develop RAS specific targeted proteomic assays to study the important pathways of human cancer. The oncogene RAS is linked to 30 percent of human cancers, but the search for a targeted therapy for RAS has remained elusive. To advance our understanding of this oncogene and to develop improved targeted therapies against RAS pathway, the National Cancer Institute (NCI) has launched a RAS Initiative.
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Assay Characterization Guidance Documents | Office of Cancer Clinical Proteomics Research
CPTAC characterized assays are defined as those that meet the criteria described in the Assay Characterization Guidance Document. This guidance document aligns with recommendations by the research community as “fit-for-purpose” validation requirements of targeted proteomics assays.
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IsobariQ: software for isobaric quantitative proteomics using IPTL, iTRAQ, and TMT.
Arntzen, Magnus Ø; Koehler, Christian J; Barsnes, Harald; Berven, Frode S; Treumann, Achim; Thiede, Bernd
2011-02-04
Isobaric peptide labeling plays an important role in relative quantitative comparisons of proteomes. Isobaric labeling techniques utilize MS/MS spectra for relative quantification, which can be either based on the relative intensities of reporter ions in the low mass region (iTRAQ and TMT) or on the relative intensities of quantification signatures throughout the spectrum due to isobaric peptide termini labeling (IPTL). Due to the increased quantitative information found in MS/MS fragment spectra generated by the recently developed IPTL approach, new software was required to extract the quantitative information. IsobariQ was specifically developed for this purpose; however, support for the reporter ion techniques iTRAQ and TMT is also included. In addition, to address recently emphasized issues about heterogeneity of variance in proteomics data sets, IsobariQ employs the statistical software package R and variance stabilizing normalization (VSN) algorithms available therein. Finally, the functionality of IsobariQ is validated with data sets of experiments using 6-plex TMT and IPTL. Notably, protein substrates resulting from cleavage by proteases can be identified as shown for caspase targets in apoptosis.
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Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms.
Jaffe, Jacob D; Feeney, Caitlin M; Patel, Jinal; Lu, Xiaodong; Mani, D R
2016-11-01
Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques. Graphical Abstract ᅟ.
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Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms
NASA Astrophysics Data System (ADS)
Jaffe, Jacob D.; Feeney, Caitlin M.; Patel, Jinal; Lu, Xiaodong; Mani, D. R.
2016-11-01
Targeted proteomic assays are becoming increasingly popular because of their robust quantitative applications enabled by internal standardization, and they can be routinely executed on high performance mass spectrometry instrumentation. However, these assays are typically limited to 100s of analytes per experiment. Considerable time and effort are often expended in obtaining and preparing samples prior to targeted analyses. It would be highly desirable to detect and quantify 1000s of analytes in such samples using comprehensive mass spectrometry techniques (e.g., SWATH and DIA) while retaining a high degree of quantitative rigor for analytes with matched internal standards. Experimentally, it is facile to port a targeted assay to a comprehensive data acquisition technique. However, data analysis challenges arise from this strategy concerning agreement of results from the targeted and comprehensive approaches. Here, we present the use of genetic algorithms to overcome these challenges in order to configure hybrid targeted/comprehensive MS assays. The genetic algorithms are used to select precursor-to-fragment transitions that maximize the agreement in quantification between the targeted and the comprehensive methods. We find that the algorithm we used provided across-the-board improvement in the quantitative agreement between the targeted assay data and the hybrid comprehensive/targeted assay that we developed, as measured by parameters of linear models fitted to the results. We also found that the algorithm could perform at least as well as an independently-trained mass spectrometrist in accomplishing this task. We hope that this approach will be a useful tool in the development of quantitative approaches for comprehensive proteomics techniques.
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Comparing Simplification Strategies for the Skeletal Muscle Proteome
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
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Chimeric plastid proteome in the Florida "red tide" dinoflagellate Karenia brevis.
Nosenko, Tetyana; Lidie, Kristy L; Van Dolah, Frances M; Lindquist, Erika; Cheng, Jan-Fang; Bhattacharya, Debashish
2006-11-01
Current understanding of the plastid proteome comes almost exclusively from studies of plants and red algae. The proteome in these taxa has a relatively simple origin via integration of proteins from a single cyanobacterial primary endosymbiont and the host. However, the most successful algae in marine environments are the chlorophyll c-containing chromalveolates such as diatoms and dinoflagellates that contain a plastid of red algal origin derived via secondary or tertiary endosymbiosis. Virtually nothing is known about the plastid proteome in these taxa. We analyzed expressed sequence tag data from the toxic "Florida red tide" dinoflagellate Karenia brevis that has undergone a tertiary plastid endosymbiosis. Comparative analyses identified 30 nuclear-encoded plastid-targeted proteins in this chromalveolate that originated via endosymbiotic or horizontal gene transfer (HGT) from multiple different sources. We identify a fundamental divide between plant/red algal and chromalveolate plastid proteomes that reflects a history of mixotrophy in the latter group resulting in a highly chimeric proteome. Loss of phagocytosis in the "red" and "green" clades effectively froze their proteomes, whereas chromalveolate lineages retain the ability to engulf prey allowing them to continually recruit new, potentially adaptive genes through subsequent endosymbioses and HGT. One of these genes is an electron transfer protein (plastocyanin) of green algal origin in K. brevis that likely allows this species to thrive under conditions of iron depletion.
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Schizophrenia proteomics: biomarkers on the path to laboratory medicine?
Lakhan, Shaheen Emmanuel
2006-01-01
Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science. PMID:16846510
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ZHANG, YAFANG; CROFTON, ELIZABETH J.; FAN, XIUZHEN; LI, DINGGE; KONG, FANPING; SINHA, MALA; LUXON, BRUCE A.; SPRATT, HEIDI M.; LICHTI, CHERYL F.; GREEN, THOMAS A.
2016-01-01
Transcriptomic and proteomic approaches have separately proven effective at identifying novel mechanisms affecting addiction-related behavior; however, it is difficult to prioritize the many promising leads from each approach. A convergent secondary analysis of proteomic and transcriptomic results can glean additional information to help prioritize promising leads. The current study is a secondary analysis of the convergence of recently published separate transcriptomic and proteomic analyses of nucleus accumbens (NAc) tissue from rats subjected to environmental enrichment vs. isolation and cocaine self-administration vs. saline. Multiple bioinformatics approaches (e.g. Gene Ontology (GO) analysis, Ingenuity Pathway Analysis (IPA), and Gene Set Enrichment Analysis (GSEA)) were used to interrogate these rich data sets. Although there was little correspondence between mRNA vs. protein at the individual target level, good correspondence was found at the level of gene/protein sets, particularly for the environmental enrichment manipulation. These data identify gene sets where there is a positive relationship between changes in mRNA and protein (e.g. glycolysis, ATP synthesis, translation elongation factor activity, etc.) and gene sets where there is an inverse relationship (e.g. ribosomes, Rho GTPase signaling, protein ubiquitination, etc.). Overall environmental enrichment produced better correspondence than cocaine self-administration. The individual targets contributing to mRNA and protein effects were largely not overlapping. As a whole, these results confirm that robust transcriptomic and proteomic data sets can provide similar results at the gene/protein set level even when there is little correspondence at the individual target level and little overlap in the targets contributing to the effects. PMID:27717806
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Diversification of the muscle proteome through alternative splicing.
Nakka, Kiran; Ghigna, Claudia; Gabellini, Davide; Dilworth, F Jeffrey
2018-03-06
Skeletal muscles express a highly specialized proteome that allows the metabolism of energy sources to mediate myofiber contraction. This muscle-specific proteome is partially derived through the muscle-specific transcription of a subset of genes. Surprisingly, RNA sequencing technologies have also revealed a significant role for muscle-specific alternative splicing in generating protein isoforms that give specialized function to the muscle proteome. In this review, we discuss the current knowledge with respect to the mechanisms that allow pre-mRNA transcripts to undergo muscle-specific alternative splicing while identifying some of the key trans-acting splicing factors essential to the process. The importance of specific splicing events to specialized muscle function is presented along with examples in which dysregulated splicing contributes to myopathies. Though there is now an appreciation that alternative splicing is a major contributor to proteome diversification, the emergence of improved "targeted" proteomic methodologies for detection of specific protein isoforms will soon allow us to better appreciate the extent to which alternative splicing modifies the activity of proteins (and their ability to interact with other proteins) in the skeletal muscle. In addition, we highlight a continued need to better explore the signaling pathways that contribute to the temporal control of trans-acting splicing factor activity to ensure specific protein isoforms are expressed in the proper cellular context. An understanding of the signal-dependent and signal-independent events driving muscle-specific alternative splicing has the potential to provide us with novel therapeutic strategies to treat different myopathies.
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A statistical approach to selecting and confirming validation targets in -omics experiments
2012-01-01
Background Genomic technologies are, by their very nature, designed for hypothesis generation. In some cases, the hypotheses that are generated require that genome scientists confirm findings about specific genes or proteins. But one major advantage of high-throughput technology is that global genetic, genomic, transcriptomic, and proteomic behaviors can be observed. Manual confirmation of every statistically significant genomic result is prohibitively expensive. This has led researchers in genomics to adopt the strategy of confirming only a handful of the most statistically significant results, a small subset chosen for biological interest, or a small random subset. But there is no standard approach for selecting and quantitatively evaluating validation targets. Results Here we present a new statistical method and approach for statistically validating lists of significant results based on confirming only a small random sample. We apply our statistical method to show that the usual practice of confirming only the most statistically significant results does not statistically validate result lists. We analyze an extensively validated RNA-sequencing experiment to show that confirming a random subset can statistically validate entire lists of significant results. Finally, we analyze multiple publicly available microarray experiments to show that statistically validating random samples can both (i) provide evidence to confirm long gene lists and (ii) save thousands of dollars and hundreds of hours of labor over manual validation of each significant result. Conclusions For high-throughput -omics studies, statistical validation is a cost-effective and statistically valid approach to confirming lists of significant results. PMID:22738145
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The HUPO proteomics standards initiative--overcoming the fragmentation of proteomics data.
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.
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Sabidó, Eduard; Wu, Yibo; Bautista, Lucia; Porstmann, Thomas; Chang, Ching-Yun; Vitek, Olga; Stoffel, Markus; Aebersold, Ruedi
2013-07-16
The metabolic syndrome is a collection of risk factors including obesity, insulin resistance and hepatic steatosis, which occur together and increase the risk of diseases such as diabetes, cardiovascular disease and cancer. In spite of intense research, the complex etiology of insulin resistance and its association with the accumulation of triacylglycerides in the liver and with hepatic steatosis remains not completely understood. Here, we performed quantitative measurements of 144 proteins involved in the insulin-signaling pathway and central metabolism in liver homogenates of two genetically well-defined mouse strains C57BL/6J and 129Sv that were subjected to a sustained high-fat diet. We used targeted mass spectrometry by selected reaction monitoring (SRM) to generate accurate and reproducible quantitation of the targeted proteins across 36 different samples (12 conditions and 3 biological replicates), generating one of the largest quantitative targeted proteomics data sets in mammalian tissues. Our results revealed rapid response to high-fat diet that diverged early in the feeding regimen, and evidenced a response to high-fat diet dominated by the activation of peroxisomal β-oxidation in C57BL/6J and by lipogenesis in 129Sv mice.
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Rigbolt, Kristoffer T G; Vanselow, Jens T; Blagoev, Blagoy
2011-08-01
Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)(1). The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.
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Rigbolt, Kristoffer T. G.; Vanselow, Jens T.; Blagoev, Blagoy
2011-01-01
Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net. PMID:21602510
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Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.
Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József
2017-02-05
Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.
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The proteomic profile of hair damage.
Sinclair, R; Flagler, M J; Jones, L; Rufaut, N; Davis, M G
2012-06-01
Monilethrix is a congenital hair shaft disorder with associated fragility. Many of the changes seen in monilethrix hair on light microscopy and scanning electron microscopy are also seen in hair weathering and cosmetic damage to hair. We used monilethrix as a model to investigate the relationship between hair protein structure and hair strength and resistance to cosmetic insult. We applied proteomic techniques to identify novel peptide damage markers for chemical oxidative damage to hair. The findings suggest that specific sites in the protein structure of hair are targeted during oxidative damage from bleaching, a unique insight into how chemical damage compromises the structural integrity of the hair shaft at the molecular level. Applying proteomics to the study of congenital and acquired hair shaft disorders can deliver new insights into hair damage and novel strategies to strengthen hair. © 2012 The Authors. BJD © 2012 British Association of Dermatologists.
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Utility, Limitations, and Promise of Proteomics in Animal Science
USDA-ARS?s Scientific Manuscript database
Proteomics experiments have the ability to simultaneously identify and quantify thousands of proteins in one experiment. The use of this technology in veterinary/animal science is still in its infancy, yet it holds significant promise as a method for advancing veterinary/animal science research. E...
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Method and platform standardization in MRM-based quantitative plasma proteomics.
Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H
2013-12-16
There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This
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Proteomic analysis of protein phosphatase Z1 from Candida albicans
Pfliegler, Walter P.; Petrényi, Katalin; Boros, Enikő; Pócsi, István; Tőzsér, József; Dombrádi, Viktor
2017-01-01
Protein phosphatase Z is a “novel type” fungus specific serine/threonine protein phosphatase. Previously our research group identified the CaPPZ1 gene in the opportunistic pathogen Candida albicans and reported that the gene deletion had several important physiological consequences. In order to reveal the protein targets and the associated mechanisms behind the functions of the phosphatase a proteomic method was adopted for the comparison of the cappz1 deletion mutant and the genetically matching QMY23 control strain. Proteins extracted from the control and deletion mutant strains were separated by two-dimensional gel electrophoresis and the protein spots were stained with RuBPS and Pro-Q Diamond in order to visualize the total proteome and the phosphoproteome, respectively. The alterations in spot intensities were determined by densitometry and were analysed with the Delta2D (Decodon) software. Spots showing significantly different intensities between the mutant and control strains were excised from the gels and were digested with trypsin. The resulting peptides were identified by LC-MS/MS mass spectrometry. As many as 15 protein spots were found that exhibited significant changes in their intensity upon the deletion of the phosphatase and 20 phosphoproteins were identified in which the level of phosphorylation was modified significantly in the mutant. In agreement with previous findings we found that the affected proteins function in protein synthesis, oxidative stress response, regulation of morphology and metabolism. Among these proteins we identified two potential CaPpz1 substrates (Eft2 and Rpp0) that may regulate the elongation step of translation. RT-qPCR experiments revealed that the expression of the genes coding for the affected proteins was not altered significantly. Thus, the absence of CaPpz1 exerted its effects via protein synthesis/degradation and phosphorylation/dephosphorylation. In addition, our proteomics data strongly suggested a role for
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QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories
Chiva, Cristina; Olivella, Roger; Borràs, Eva; Espadas, Guadalupe; Pastor, Olga; Solé, Amanda
2018-01-01
The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0. PMID:29324744
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Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva
2017-01-01
No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as
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Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study
Sun, Su; Xie, Shangxian; Cheng, Yanbing; ...
2017-09-12
Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level formore » the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.« less
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Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study.
Sun, Su; Xie, Shangxian; Cheng, Yanbing; Yu, Hongbo; Zhao, Honglu; Li, Muzi; Li, Xiaotong; Zhang, Xiaoyu; Yuan, Joshua S; Dai, Susie Y
2017-09-12
Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level for the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.
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Enhancement of Environmental Hazard Degradation in the Presence of Lignin: a Proteomics Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Su; Xie, Shangxian; Cheng, Yanbing
Proteomics studies of fungal systems have progressed dramatically based on the availability of more fungal genome sequences in recent years. Different proteomics strategies have been applied toward characterization of fungal proteome and revealed important gene functions and proteome dynamics. Presented here is the application of shot-gun proteomic technology to study the bio-remediation of environmental hazards by white-rot fungus. Lignin, a naturally abundant component of the plant biomass, is discovered to promote the degradation of Azo dye by white-rot fungus Irpex lacteus CD2 in the lignin/dye/fungus system. Shotgun proteomics technique was used to understand degradation mechanism at the protein level formore » the lignin/dye/fungus system. Our proteomics study can identify about two thousand proteins (one third of the predicted white-rot fungal proteome) in a single experiment, as one of the most powerful proteomics platforms to study the fungal system to date. The study shows a significant enrichment of oxidoreduction functional category under the dye/lignin combined treatment. An in vitro validation is performed and supports our hypothesis that the synergy of Fenton reaction and manganese peroxidase might play an important role in DR5B dye degradation. The results could guide the development of effective bioremediation strategies and efficient lignocellulosic biomass conversion.« less
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Proteomics Standards Initiative: Fifteen Years of Progress and Future Work
2017-01-01
The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI. PMID:28849660
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Proteomics Standards Initiative: Fifteen Years of Progress and Future Work.
Deutsch, Eric W; Orchard, Sandra; Binz, Pierre-Alain; Bittremieux, Wout; Eisenacher, Martin; Hermjakob, Henning; Kawano, Shin; Lam, Henry; Mayer, Gerhard; Menschaert, Gerben; Perez-Riverol, Yasset; Salek, Reza M; Tabb, David L; Tenzer, Stefan; Vizcaíno, Juan Antonio; Walzer, Mathias; Jones, Andrew R
2017-12-01
The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.
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Beauty and charm production in fixed target experiments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kidonakis, Nikolaos; Vogt, Ramona
We present calculations of NNLO threshold corrections for beauty and charm production in {pi}{sup -} p and pp interactions at fixed-target experiments. Recent calculations for heavy quark hadroproduction have included next-to-next-to-leading-order (NNLO) soft-gluon corrections [1] to the double differential cross section from threshold resummation techniques [2]. These corrections are important for near-threshold beauty and charm production at fixed-target experiments, including HERA-B and some of the current and future heavy ion experiments.
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Recent advances in proteomic applications for schistosomiasis research: potential clinical impact.
Sotillo, Javier; Doolan, Denise; Loukas, Alex
2017-02-01
Schistosomiasis is a neglected tropical disease affecting hundreds of millions of people worldwide. Recent advances in the field of proteomics and the development of new and highly sensitive mass spectrometers and quantitative techniques have provided new tools for advancing the molecular biology, cell biology, diagnosis and vaccine development for public health threats such as schistosomiasis. Areas covered: In this review we describe the latest advances in research that utilizes proteomics-based tools to address some of the key challenges to developing effective interventions against schistosomiasis. We also provide information about the potential of extracellular vesicles to advance the fight against this devastating disease. Expert commentary: Different proteins are already being tested as vaccines against schistosomiasis with promising results. The re-analysis of the Schistosoma spp. proteomes using new and more sensitive mass spectrometers as well as better separation approaches will help identify more vaccine targets in a rational and informed manner. In addition, the recent development of new proteome microarrays will facilitate characterisation of novel markers of infection as well as new vaccine and diagnostic candidate antigens.
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The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory colon study data. The goal of the study is to analyze the proteomes of approximately 100 confirmatory colon tumor patients, which includes tumor and adjacent normal samples, with liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic and phosphoproteomic profiling.
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Proteomics in medical microbiology.
Cash, P
2000-04-01
The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.
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NCI Launches Proteomics Assay Portal | Office of Cancer Clinical Proteomics Research
In a paper recently published by the journal Nature Methods, Investigators from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (NCI-CPTAC) announced the launch of a proteomics Assay Portal for multiple reaction monitoring-mass spectrometry (MRM-MS) assays. This community web-based repository for well-characterized quantitative proteomic assays currently consists of 456 unique peptide assays to 282 unique proteins and ser
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Standardization approaches in absolute quantitative proteomics with mass spectrometry.
Calderón-Celis, Francisco; Encinar, Jorge Ruiz; Sanz-Medel, Alfredo
2017-07-31
Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and
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Proteomic Analyses of the Unexplored Sea Anemone Bunodactis verrucosa
Campos, Alexandre; Turkina, Maria V.; Ribeiro, Tiago; Osorio, Hugo; Vasconcelos, Vítor; Antunes, Agostinho
2018-01-01
Cnidarian toxic products, particularly peptide toxins, constitute a promising target for biomedicine research. Indeed, cnidarians are considered as the largest phylum of generally toxic animals. However, research on peptides and toxins of sea anemones is still limited. Moreover, most of the toxins from sea anemones have been discovered by classical purification approaches. Recently, high-throughput methodologies have been used for this purpose but in other Phyla. Hence, the present work was focused on the proteomic analyses of whole-body extract from the unexplored sea anemone Bunodactis verrucosa. The proteomic analyses applied were based on two methods: two-dimensional gel electrophoresis combined with MALDI-TOF/TOF and shotgun proteomic approach. In total, 413 proteins were identified, but only eight proteins were identified from gel-based analyses. Such proteins are mainly involved in basal metabolism and biosynthesis of antibiotics as the most relevant pathways. In addition, some putative toxins including metalloproteinases and neurotoxins were also identified. These findings reinforce the significance of the production of antimicrobial compounds and toxins by sea anemones, which play a significant role in defense and feeding. In general, the present study provides the first proteome map of the sea anemone B. verrucosa stablishing a reference for future studies in the discovery of new compounds. PMID:29364843
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Proteomic Analyses of the Unexplored Sea Anemone Bunodactis verrucosa.
Domínguez-Pérez, Dany; Campos, Alexandre; Alexei Rodríguez, Armando; Turkina, Maria V; Ribeiro, Tiago; Osorio, Hugo; Vasconcelos, Vítor; Antunes, Agostinho
2018-01-24
Cnidarian toxic products, particularly peptide toxins, constitute a promising target for biomedicine research. Indeed, cnidarians are considered as the largest phylum of generally toxic animals. However, research on peptides and toxins of sea anemones is still limited. Moreover, most of the toxins from sea anemones have been discovered by classical purification approaches. Recently, high-throughput methodologies have been used for this purpose but in other Phyla. Hence, the present work was focused on the proteomic analyses of whole-body extract from the unexplored sea anemone Bunodactis verrucosa . The proteomic analyses applied were based on two methods: two-dimensional gel electrophoresis combined with MALDI-TOF/TOF and shotgun proteomic approach. In total, 413 proteins were identified, but only eight proteins were identified from gel-based analyses. Such proteins are mainly involved in basal metabolism and biosynthesis of antibiotics as the most relevant pathways. In addition, some putative toxins including metalloproteinases and neurotoxins were also identified. These findings reinforce the significance of the production of antimicrobial compounds and toxins by sea anemones, which play a significant role in defense and feeding. In general, the present study provides the first proteome map of the sea anemone B. verrucosa stablishing a reference for future studies in the discovery of new compounds.
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Cryogenic Target-Implosion Experiments on OMEGA
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harding, D.R.; Meyerhofer, D.D.; Sangster, T.C.
The University of Rochester’s Laboratory for Laser Energetics has been imploding thick cryogenic targets for six years. Improvements in the Cryogenic Target Handling System and the ability to accurately design laser pulse shapes that properly time shocks and minimize electron preheat, produced high fuel areal densities in deuterium cryogenic targets (202+/-7 mg/cm^2). The areal density was inferred from the energy loss of secondary protons in the fuel (D2) shell. Targets were driven on a low final adiabat (alpha = 2) employing techniques to radially grade the adiabat (the highest adiabat at the ablation surface). The ice layer meets the target-designmore » toughness specification for DT ice of 1-um rms (all modes), while D2 ice layers average 3.0-um-rms roughness. The implosion experiments and the improvements in the quality and understanding of cryogenic targets are presented.« less
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Understanding Cullin-RING E3 Biology through Proteomics-based Substrate Identification*
Harper, J. Wade; Tan, Meng-Kwang Marcus
2012-01-01
Protein turnover through the ubiquitin-proteasome pathway controls numerous developmental decisions and biochemical processes in eukaryotes. Central to protein ubiquitylation are ubiquitin ligases, which provide specificity in targeted ubiquitylation. With more than 600 ubiquitin ligases encoded by the human genome, many of which remain to be studied, considerable effort is being placed on the development of methods for identifying substrates of specific ubiquitin ligases. In this review, we describe proteomic technologies for the identification of ubiquitin ligase targets, with a particular focus on members of the cullin-RING E3 class of ubiquitin ligases, which use F-box proteins as substrate specific adaptor proteins. Various proteomic methods are described and are compared with genetic approaches that are available. The continued development of such methods is likely to have a substantial impact on the ubiquitin-proteasome field. PMID:22962057
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Understanding cullin-RING E3 biology through proteomics-based substrate identification.
Harper, J Wade; Tan, Meng-Kwang Marcus
2012-12-01
Protein turnover through the ubiquitin-proteasome pathway controls numerous developmental decisions and biochemical processes in eukaryotes. Central to protein ubiquitylation are ubiquitin ligases, which provide specificity in targeted ubiquitylation. With more than 600 ubiquitin ligases encoded by the human genome, many of which remain to be studied, considerable effort is being placed on the development of methods for identifying substrates of specific ubiquitin ligases. In this review, we describe proteomic technologies for the identification of ubiquitin ligase targets, with a particular focus on members of the cullin-RING E3 class of ubiquitin ligases, which use F-box proteins as substrate specific adaptor proteins. Various proteomic methods are described and are compared with genetic approaches that are available. The continued development of such methods is likely to have a substantial impact on the ubiquitin-proteasome field.
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Alvarez, Sophie; Roy Choudhury, Swarup; Hicks, Leslie M; Pandey, Sona
2013-03-01
Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in Arabidopsis thaliana. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and gtg1gtg2 were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in Arabidopsis. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus gtg1gtg2 provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk.
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Debiasing affective forecasting errors with targeted, but not representative, experience narratives.
Shaffer, Victoria A; Focella, Elizabeth S; Scherer, Laura D; Zikmund-Fisher, Brian J
2016-10-01
To determine whether representative experience narratives (describing a range of possible experiences) or targeted experience narratives (targeting the direction of forecasting bias) can reduce affective forecasting errors, or errors in predictions of experiences. In Study 1, participants (N=366) were surveyed about their experiences with 10 common medical events. Those who had never experienced the event provided ratings of predicted discomfort and those who had experienced the event provided ratings of actual discomfort. Participants making predictions were randomly assigned to either the representative experience narrative condition or the control condition in which they made predictions without reading narratives. In Study 2, participants (N=196) were again surveyed about their experiences with these 10 medical events, but participants making predictions were randomly assigned to either the targeted experience narrative condition or the control condition. Affective forecasting errors were observed in both studies. These forecasting errors were reduced with the use of targeted experience narratives (Study 2) but not representative experience narratives (Study 1). Targeted, but not representative, narratives improved the accuracy of predicted discomfort. Public collections of patient experiences should favor stories that target affective forecasting biases over stories representing the range of possible experiences. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Santamaría, Enrique; Avila, Matías A.; Latasa, M. Ujue; Rubio, Angel; Martín-Duce, Antonio; Lu, Shelly C.; Mato, José M.; Corrales, Fernando J.
2003-01-01
Recent work shows that S-adenosylmethionine (AdoMet) helps maintain normal liver function as chronic hepatic deficiency results in spontaneous development of steatohepatitis and hepatocellular carcinoma. The mechanisms by which these nontraditional functions of AdoMet occur are unknown. Here, we use knockout mice deficient in hepatic AdoMet synthesis (MAT1A−/−) to study the proteome of the liver during the development of steatohepatitis. One hundred and seventeen protein spots, differentially expressed during the development of steatohepatitis, were selected and identified by peptide mass fingerprinting. Among them, 12 proteins were found to be affected from birth, when MAT1A−/− expression is switched on in WT mouse liver, to the rise of histological lesions, which occurs at ≈8 months. Of the 12 proteins, 4 [prohibitin 1 (PHB1), cytochrome c oxidase I and II, and ATPase β-subunit] have known roles in mitochondrial function. We show that the alteration in expression of PHB1 correlates with a loss of mitochondrial function. Experiments in isolated rat hepatocytes indicate that AdoMet regulates PHB1 content, thus suggesting ways by which steatohepatitis may be induced. Importantly, we found the expression of these mitochondrial proteins was abnormal in ob/ob mice and obese patients who are at risk for nonalcoholic steatohepatitis. PMID:12631701
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Dr. Henry Rodriguez, director of the Office of Cancer Clinical Proteomics Research (OCCPR) at NCI, speaks with ecancer television at WIN 2017 about the translation of the proteins expressed in a patient's tumor into a map for druggable targets. By combining genomic and proteomic information (proteogenomics), leading scientists are gaining new insights into ways to detect and treat cancer due to a more complete and unified understanding of complex biological processes.
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Fixed-target hadron production experiments
NASA Astrophysics Data System (ADS)
Popov, Boris A.
2015-08-01
Results from fixed-target hadroproduction experiments (HARP, MIPP, NA49 and NA61/SHINE) as well as their implications for cosmic ray and neutrino physics are reviewed. HARP measurements have been used for predictions of neutrino beams in K2K and MiniBooNE/SciBooNE experiments and are also being used to improve predictions of the muon yields in EAS and of the atmospheric neutrino fluxes as well as to help in the optimization of neutrino factory and super-beam designs. Recent measurements released by the NA61/SHINE experiment are of significant importance for a precise prediction of the J-PARC neutrino beam used for the T2K experiment and for interpretation of EAS data. These hadroproduction experiments provide also a large amount of input for validation and tuning of hadron production models in Monte-Carlo generators.
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A Routine 'Top-Down' Approach to Analysis of the Human Serum Proteome.
D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R
2017-06-06
Serum provides a rich source of potential biomarker proteoforms. One of the major obstacles in analysing serum proteomes is detecting lower abundance proteins owing to the presence of hyper-abundant species (e.g., serum albumin and immunoglobulins). Although depletion methods have been used to address this, these can lead to the concomitant removal of non-targeted protein species, and thus raise issues of specificity, reproducibility, and the capacity for meaningful quantitative analyses. Altering the native stoichiometry of the proteome components may thus yield a more complex series of issues than dealing directly with the inherent complexity of the sample. Hence, here we targeted method refinements so as to ensure optimum resolution of serum proteomes via a top down two-dimensional gel electrophoresis (2DE) approach that enables the routine assessment of proteoforms and is fully compatible with subsequent mass spectrometric analyses. Testing included various fractionation and non-fractionation approaches. The data show that resolving 500 µg protein on 17 cm 3-10 non-linear immobilised pH gradient strips in the first dimension followed by second dimension resolution on 7-20% gradient gels with a combination of lithium dodecyl sulfate (LDS) and sodium dodecyl sulfate (SDS) detergents markedly improves the resolution and detection of proteoforms in serum. In addition, well established third dimension electrophoretic separations in combination with deep imaging further contributed to the best available resolution, detection, and thus quantitative top-down analysis of serum proteomes.
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Quantitative Proteomics Identifies Activation of Hallmark Pathways of Cancer in Patient Melanoma.
Byrum, Stephanie D; Larson, Signe K; Avaritt, Nathan L; Moreland, Linley E; Mackintosh, Samuel G; Cheung, Wang L; Tackett, Alan J
2013-03-01
Molecular pathways regulating melanoma initiation and progression are potential targets of therapeutic development for this aggressive cancer. Identification and molecular analysis of these pathways in patients has been primarily restricted to targeted studies on individual proteins. Here, we report the most comprehensive analysis of formalin-fixed paraffin-embedded human melanoma tissues using quantitative proteomics. From 61 patient samples, we identified 171 proteins varying in abundance among benign nevi, primary melanoma, and metastatic melanoma. Seventy-three percent of these proteins were validated by immunohistochemistry staining of malignant melanoma tissues from the Human Protein Atlas database. Our results reveal that molecular pathways involved with tumor cell proliferation, motility, and apoptosis are mis-regulated in melanoma. These data provide the most comprehensive proteome resource on patient melanoma and reveal insight into the molecular mechanisms driving melanoma progression.
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Target charging in short-pulse-laser-plasma experiments.
Dubois, J-L; Lubrano-Lavaderci, F; Raffestin, D; Ribolzi, J; Gazave, J; Compant La Fontaine, A; d'Humières, E; Hulin, S; Nicolaï, Ph; Poyé, A; Tikhonchuk, V T
2014-01-01
Interaction of high-intensity laser pulses with solid targets results in generation of large quantities of energetic electrons that are the origin of various effects such as intense x-ray emission, ion acceleration, and so on. Some of these electrons are escaping the target, leaving behind a significant positive electric charge and creating a strong electromagnetic pulse long after the end of the laser pulse. We propose here a detailed model of the target electric polarization induced by a short and intense laser pulse and an escaping electron bunch. A specially designed experiment provides direct measurements of the target polarization and the discharge current in the function of the laser energy, pulse duration, and target size. Large-scale numerical simulations describe the energetic electron generation and their emission from the target. The model, experiment, and numerical simulations demonstrate that the hot-electron ejection may continue long after the laser pulse ends, enhancing significantly the polarization charge.
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Bacterial membrane proteomics.
Poetsch, Ansgar; Wolters, Dirk
2008-10-01
About one quarter to one third of all bacterial genes encode proteins of the inner or outer bacterial membrane. These proteins perform essential physiological functions, such as the import or export of metabolites, the homeostasis of metal ions, the extrusion of toxic substances or antibiotics, and the generation or conversion of energy. The last years have witnessed completion of a plethora of whole-genome sequences of bacteria important for biotechnology or medicine, which is the foundation for proteome and other functional genome analyses. In this review, we discuss the challenges in membrane proteome analysis, starting from sample preparation and leading to MS-data analysis and quantification. The current state of available proteomics technologies as well as their advantages and disadvantages will be described with a focus on shotgun proteomics. Then, we will briefly introduce the most abundant proteins and protein families present in bacterial membranes before bacterial membrane proteomics studies of the last years will be presented. It will be shown how these works enlarged our knowledge about the physiological adaptations that take place in bacteria during fine chemical production, bioremediation, protein overexpression, and during infections. Furthermore, several examples from literature demonstrate the suitability of membrane proteomics for the identification of antigens and different pathogenic strains, as well as the elucidation of membrane protein structure and function.
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Consolidation of proteomics data in the Cancer Proteomics database.
Arntzen, Magnus Ø; Boddie, Paul; Frick, Rahel; Koehler, Christian J; Thiede, Bernd
2015-11-01
Cancer is a class of diseases characterized by abnormal cell growth and one of the major reasons for human deaths. Proteins are involved in the molecular mechanisms leading to cancer, furthermore they are affected by anti-cancer drugs, and protein biomarkers can be used to diagnose certain cancer types. Therefore, it is important to explore the proteomics background of cancer. In this report, we developed the Cancer Proteomics database to re-interrogate published proteome studies investigating cancer. The database is divided in three sections related to cancer processes, cancer types, and anti-cancer drugs. Currently, the Cancer Proteomics database contains 9778 entries of 4118 proteins extracted from 143 scientific articles covering all three sections: cell death (cancer process), prostate cancer (cancer type) and platinum-based anti-cancer drugs including carboplatin, cisplatin, and oxaliplatin (anti-cancer drugs). The detailed information extracted from the literature includes basic information about the articles (e.g., PubMed ID, authors, journal name, publication year), information about the samples (type, study/reference, prognosis factor), and the proteomics workflow (Subcellular fractionation, protein, and peptide separation, mass spectrometry, quantification). Useful annotations such as hyperlinks to UniProt and PubMed were included. In addition, many filtering options were established as well as export functions. The database is freely available at http://cancerproteomics.uio.no. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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SUMO-Enriched Proteome for Drosophila Innate Immune Response
Handu, Mithila; Kaduskar, Bhagyashree; Ravindranathan, Ramya; Soory, Amarendranath; Giri, Ritika; Elango, Vijay Barathi; Gowda, Harsha; Ratnaparkhi, Girish S.
2015-01-01
Small ubiquitin-like modifier (SUMO) modification modulates the expression of defense genes in Drosophila, activated by the Toll/nuclear factor-κB and immune-deficient/nuclear factor-κB signaling networks. We have, however, limited understanding of the SUMO-modulated regulation of the immune response and lack information on SUMO targets in the immune system. In this study, we measured the changes to the SUMO proteome in S2 cells in response to a lipopolysaccharide challenge and identified 1619 unique proteins in SUMO-enriched lysates. A confident set of 710 proteins represents the immune-induced SUMO proteome and analysis suggests that specific protein domains, cellular pathways, and protein complexes respond to immune stress. A small subset of the confident set was validated by in-bacto SUMOylation and shown to be bona-fide SUMO targets. These include components of immune signaling pathways such as Caspar, Jra, Kay, cdc42, p38b, 14-3-3ε, as well as cellular proteins with diverse functions, many being components of protein complexes, such as prosß4, Rps10b, SmD3, Tango7, and Aats-arg. Caspar, a human FAF1 ortholog that negatively regulates immune-deficient signaling, is SUMOylated at K551 and responds to treatment with lipopolysaccharide in cultured cells. Our study is one of the first to describe SUMO proteome for the Drosophila immune response. Our data and analysis provide a global framework for the understanding of SUMO modification in the host response to pathogens. PMID:26290570
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SUMO-Enriched Proteome for Drosophila Innate Immune Response.
Handu, Mithila; Kaduskar, Bhagyashree; Ravindranathan, Ramya; Soory, Amarendranath; Giri, Ritika; Elango, Vijay Barathi; Gowda, Harsha; Ratnaparkhi, Girish S
2015-08-18
Small ubiquitin-like modifier (SUMO) modification modulates the expression of defense genes in Drosophila, activated by the Toll/nuclear factor-κB and immune-deficient/nuclear factor-κB signaling networks. We have, however, limited understanding of the SUMO-modulated regulation of the immune response and lack information on SUMO targets in the immune system. In this study, we measured the changes to the SUMO proteome in S2 cells in response to a lipopolysaccharide challenge and identified 1619 unique proteins in SUMO-enriched lysates. A confident set of 710 proteins represents the immune-induced SUMO proteome and analysis suggests that specific protein domains, cellular pathways, and protein complexes respond to immune stress. A small subset of the confident set was validated by in-bacto SUMOylation and shown to be bona-fide SUMO targets. These include components of immune signaling pathways such as Caspar, Jra, Kay, cdc42, p38b, 14-3-3ε, as well as cellular proteins with diverse functions, many being components of protein complexes, such as prosß4, Rps10b, SmD3, Tango7, and Aats-arg. Caspar, a human FAF1 ortholog that negatively regulates immune-deficient signaling, is SUMOylated at K551 and responds to treatment with lipopolysaccharide in cultured cells. Our study is one of the first to describe SUMO proteome for the Drosophila immune response. Our data and analysis provide a global framework for the understanding of SUMO modification in the host response to pathogens. Copyright © 2015 Handu et al.
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Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations
Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; ...
2015-07-03
Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Finally, herein, we report on applications illustrating increased sensitivity, throughput,more » and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.« less
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PIQMIe: a web server for semi-quantitative proteomics data management and analysis
Kuzniar, Arnold; Kanaar, Roland
2014-01-01
We present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations from multiple experiments with additional biological information on the protein entries, and makes the linked data available in the form of a light-weight relational database, which enables dedicated data analyses (e.g. in R) and user-driven queries. Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. The web server not only provides data access through a web interface but also supports programmatic access through RESTful web service. The web server is available at http://piqmie.semiqprot-emc.cloudlet.sara.nl or http://www.bioinformatics.nl/piqmie. This website is free and open to all users and there is no login requirement. PMID:24861615
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Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics.
Klont, Frank; Bras, Linda; Wolters, Justina C; Ongay, Sara; Bischoff, Rainer; Halmos, Gyorgy B; Horvatovich, Péter
2018-04-17
For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.
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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
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The Scottish Structural Proteomics Facility: targets, methods and outputs.
Oke, Muse; Carter, Lester G; Johnson, Kenneth A; Liu, Huanting; McMahon, Stephen A; Yan, Xuan; Kerou, Melina; Weikart, Nadine D; Kadi, Nadia; Sheikh, Md Arif; Schmelz, Stefan; Dorward, Mark; Zawadzki, Michal; Cozens, Christopher; Falconer, Helen; Powers, Helen; Overton, Ian M; van Niekerk, C A Johannes; Peng, Xu; Patel, Prakash; Garrett, Roger A; Prangishvili, David; Botting, Catherine H; Coote, Peter J; Dryden, David T F; Barton, Geoffrey J; Schwarz-Linek, Ulrich; Challis, Gregory L; Taylor, Garry L; White, Malcolm F; Naismith, James H
2010-06-01
The Scottish Structural Proteomics Facility was funded to develop a laboratory scale approach to high throughput structure determination. The effort was successful in that over 40 structures were determined. These structures and the methods harnessed to obtain them are reported here. This report reflects on the value of automation but also on the continued requirement for a high degree of scientific and technical expertise. The efficiency of the process poses challenges to the current paradigm of structural analysis and publication. In the 5 year period we published ten peer-reviewed papers reporting structural data arising from the pipeline. Nevertheless, the number of structures solved exceeded our ability to analyse and publish each new finding. By reporting the experimental details and depositing the structures we hope to maximize the impact of the project by allowing others to follow up the relevant biology.
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Translational plant proteomics: a perspective.
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.
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Alberio, Tiziana; Pieroni, Luisa; Ronci, Maurizio; Banfi, Cristina; Bongarzone, Italia; Bottoni, Patrizia; Brioschi, Maura; Caterino, Marianna; Chinello, Clizia; Cormio, Antonella; Cozzolino, Flora; Cunsolo, Vincenzo; Fontana, Simona; Garavaglia, Barbara; Giusti, Laura; Greco, Viviana; Lucacchini, Antonio; Maffioli, Elisa; Magni, Fulvio; Monteleone, Francesca; Monti, Maria; Monti, Valentina; Musicco, Clara; Petrosillo, Giuseppe; Porcelli, Vito; Saletti, Rosaria; Scatena, Roberto; Soggiu, Alessio; Tedeschi, Gabriella; Zilocchi, Mara; Roncada, Paola; Urbani, Andrea; Fasano, Mauro
2017-12-01
The Mitochondrial Human Proteome Project aims at understanding the function of the mitochondrial proteome and its crosstalk with the proteome of other organelles. Being able to choose a suitable and validated enrichment protocol of functional mitochondria, based on the specific needs of the downstream proteomics analysis, would greatly help the researchers in the field. Mitochondrial fractions from ten model cell lines were prepared using three enrichment protocols and analyzed on seven different LC-MS/MS platforms. All data were processed using neXtProt as reference database. The data are available for the Human Proteome Project purposes through the ProteomeXchange Consortium with the identifier PXD007053. The processed data sets were analyzed using a suite of R routines to perform a statistical analysis and to retrieve subcellular and submitochondrial localizations. Although the overall number of identified total and mitochondrial proteins was not significantly dependent on the enrichment protocol, specific line to line differences were observed. Moreover, the protein lists were mapped to a network representing the functional mitochondrial proteome, encompassing mitochondrial proteins and their first interactors. More than 80% of the identified proteins resulted in nodes of this network but with a different ability in coisolating mitochondria-associated structures for each enrichment protocol/cell line pair.
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Principles of proteome allocation are revealed using proteomic data and genome-scale models
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
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Fadda, Silvina; Almeida, André M
2015-11-01
Argentina is one of the most relevant countries in Latin America, playing a major role in regional economics, culture and science. Over the last 80 years, Argentinean history has been characterized by several upward and downward phases that had major consequences on the development of science in the country and most recently on proteomics. In this article, we characterize the evolution of Proteomics sciences in Argentina over the last decade and a half. We describe the proteomics publication output of the country in the framework of the regional and international contexts, demonstrating that Argentina is solidly anchored in a regional context, showing results similar to other emergent and Latin American countries, albeit still far from the European, American or Australian realities. We also provide a case-study on the importance of Proteomics to a specific sector in the area of food science: the use of bacteria of technological interest, highlighting major achievements obtained by Argentinean proteomics scientists. Finally, we provide a general picture of the endeavors being undertaken by Argentinean Proteomics scientists and their international collaborators to promote the Proteomics-based research with the new generation of scientists and PhD students in both Argentina and other countries in the Southern cone. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Proteomics reveals the effects of sustained weight loss on the human plasma proteome.
Geyer, Philipp E; Wewer Albrechtsen, Nicolai J; Tyanova, Stefka; Grassl, Niklas; Iepsen, Eva W; Lundgren, Julie; Madsbad, Sten; Holst, Jens J; Torekov, Signe S; Mann, Matthias
2016-12-22
Sustained weight loss is a preferred intervention in a wide range of metabolic conditions, but the effects on an individual's health state remain ill-defined. Here, we investigate the plasma proteomes of a cohort of 43 obese individuals that had undergone 8 weeks of 12% body weight loss followed by a year of weight maintenance. Using mass spectrometry-based plasma proteome profiling, we measured 1,294 plasma proteomes. Longitudinal monitoring of the cohort revealed individual-specific protein levels with wide-ranging effects of losing weight on the plasma proteome reflected in 93 significantly affected proteins. The adipocyte-secreted SERPINF1 and apolipoprotein APOF1 were most significantly regulated with fold changes of -16% and +37%, respectively (P < 10 -13 ), and the entire apolipoprotein family showed characteristic differential regulation. Clinical laboratory parameters are reflected in the plasma proteome, and eight plasma proteins correlated better with insulin resistance than the known marker adiponectin. Nearly all study participants benefited from weight loss regarding a ten-protein inflammation panel defined from the proteomics data. We conclude that plasma proteome profiling broadly evaluates and monitors intervention in metabolic diseases. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.
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Principles of proteome allocation are revealed using proteomic data and genome-scale models
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
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Identification and validation nucleolin as a target of curcumol in nasopharyngeal carcinoma cells.
Wang, Juan; Wu, Jiacai; Li, Xumei; Liu, Haowei; Qin, Jianli; Bai, Zhun; Chi, Bixia; Chen, Xu
2018-06-30
Identification of the specific protein target(s) of a drug is a critical step in unraveling its mechanisms of action (MOA) in many natural products. Curcumol, isolated from well known Chinese medicinal plant Curcuma zedoary, has been shown to possess multiple biological activities. It can inhibit nasopharyngeal carcinoma (NPC) proliferation and induce apoptosis, but its target protein(s) in NPC cells remains unclear. In this study, we employed a mass spectrometry-based chemical proteomics approach reveal the possible protein targets of curcumol in NPC cells. Cellular thermal shift assay (CETSA), molecular docking and cell-based assay was used to validate the binding interactions. Chemical proteomics capturing uncovered that NCL is a target of curcumol in NPC cells, Molecular docking showed that curcumol bound to NCL with an -7.8 kcal/mol binding free energy. Cell function analysis found that curcumol's treatment leads to a degradation of NCL in NPC cells, and it showed slight effects on NP69 cells. In conclusion, our results providing evidences that NCL is a target protein of curcumol. We revealed that the anti-cancer effects of curcumol in NPC cells are mediated, at least in part, by NCL inhibition. Many natural products showed high bioactivity, while their mechanisms of action (MOA) are very poor or completely missed. Understanding the MOA of natural drugs can thoroughly exploit their therapeutic potential and minimize their adverse side effects. Identification of the specific protein target(s) of a drug is a critical step in unraveling its MOA. Compound-centric chemical proteomics is a classic chemical proteomics approach which integrates chemical synthesis with cell biology and mass spectrometry (MS) to identify protein targets of natural products determine the drug mechanism of action, describe its toxicity, and figure out the possible cause of off-target. It is an affinity-based chemical proteomics method to identify small molecule-protein interactions
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Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics
Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent
2016-01-01
Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778
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Lo, Andy; Weiner, Joel H; Li, Liang
2013-09-17
Due to limited sample amounts, instrument time considerations, and reagent costs, only a small number of replicate experiments are typically performed for quantitative proteome analyses. Generation of reproducible data that can be readily assessed for consistency within a small number of datasets is critical for accurate quantification. We report our investigation of a strategy using reciprocal isotope labeling of two comparative samples as a tool for determining proteome changes. Reciprocal labeling was evaluated to determine the internal consistency of quantified proteome changes from Escherichia coli grown under aerobic and anaerobic conditions. Qualitatively, the peptide overlap between replicate analyses of the same sample and reverse labeled samples were found to be within 8%. Quantitatively, reciprocal analyses showed only a slight increase in average overall inconsistency when compared with replicate analyses (1.29 vs. 1.24-fold difference). Most importantly, reverse labeling was successfully used to identify spurious values resulting from incorrect peptide identifications and poor peak fitting. After removal of 5% of the peptide data with low reproducibility, a total of 275 differentially expressed proteins (>1.50-fold difference) were consistently identified and were then subjected to bioinformatics analysis. General considerations and guidelines for reciprocal labeling experimental design and biological significance of obtained results are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.
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Buron-Moles, Gemma; Wisniewski, Michael; Viñas, Inmaculada; Teixidó, Neus; Usall, Josep; Droby, Samir; Torres, Rosario
2015-01-30
Apples are subjected to both abiotic and biotic stresses during the postharvest period, which lead to large economic losses worldwide. To obtain biochemical insights into apple defense response, we monitored the protein abundance changes (proteome), as well as the protein carbonyls (oxi-proteome) formed by reactive oxygen species (ROS) in 'Golden Smoothee' apple in response to wounding, Penicillium expansum (host) and Penicillium digitatum (non-host) pathogens with select transcriptional studies. To examine the biological relevance of the results, we described quantitative and oxidative protein changes into the gene ontology functional categories, as well as into de KEGG pathways. We identified 26 proteins that differentially changed in abundance in response to wounding, P. expansum or P. digitatum infection. While these changes showed some similarities between the apple responses and abiotic and biotic stresses, Mal d 1.03A case, other proteins as Mal d 1.03E and EF-Tu were specifically induced in response to P. digitatum infection. Using a protein carbonyl detection method based on fluorescent Bodipy, we detected and identified 27 oxidized proteins as sensitive ROS targets. These ROS target proteins were related to metabolism processes, suggesting that this process plays a leading role in apple fruit defense response against abiotic and biotic stresses. ACC oxidase and two glutamine synthetases showed the highest protein oxidation level in response to P. digitatum infection. Documenting changes in the proteome and, specifically in oxi-proteome of apple can provide information that can be used to better understand how impaired protein functions may affect apple defense mechanisms. Possible mechanisms by which these modified proteins are involved in fruit defense response are discussed. Mechanical damage in apple fruits is linked annually to large economic losses due to opportunistic infection by postharvest pathogens, such as P. expansum. Despite the current use
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Lubin, Alexandra S; Rueda-Zubiaurre, Ainoa; Matthews, Holly; Baumann, Hella; Fisher, Fabio R; Morales-Sanfrutos, Julia; Hadavizadeh, Kate S; Nardella, Flore; Tate, Edward W; Baum, Jake; Scherf, Artur; Fuchter, Matthew J
2018-04-13
Diaminoquinazolines represent a privileged scaffold for antimalarial discovery, including use as putative Plasmodium histone lysine methyltransferase inhibitors. Despite this, robust evidence for their molecular targets is lacking. Here we report the design and development of a small-molecule photo-cross-linkable probe to investigate the targets of our diaminoquinazoline series. We demonstrate the effectiveness of our designed probe for photoaffinity labeling of Plasmodium lysates and identify similarities between the target profiles of the probe and the representative diaminoquinazoline BIX-01294. Initial pull-down proteomics experiments identified 104 proteins from different classes, many of which are essential, highlighting the suitability of the developed probe as a valuable tool for target identification in Plasmodium falciparum.
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Megajoule Dense Plasma Focus Solid Target Experiments
NASA Astrophysics Data System (ADS)
Podpaly, Y. A.; Falabella, S.; Link, A.; Povilus, A.; Higginson, D. P.; Shaw, B. H.; Cooper, C. M.; Chapman, S.; Bennett, N.; Sipe, N.; Olson, R.; Schmidt, A. E.
2016-10-01
Dense plasma focus (DPF) devices are plasma sources that can produce significant neutron yields from beam into gas interactions. Yield increases, up to approximately a factor of five, have been observed previously on DPFs using solid targets, such as CD2 and D2O ice. In this work, we report on deuterium solid-target experiments at the Gemini DPF. A rotatable target holder and baffle arrangement were installed in the Gemini device which allowed four targets to be deployed sequentially without breaking vacuum. Solid targets of titanium deuteride were installed and systematically studied at a variety of fill pressures, bias voltages, and target positions. Target holder design, experimental results, and comparison to simulations will be presented. Prepared by LLNL under Contract DE-AC52-07NA27344.
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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.
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Cell death proteomics database: consolidating proteomics data on cell death.
Arntzen, Magnus Ø; Bull, Vibeke H; Thiede, Bernd
2013-05-03
Programmed cell death is a ubiquitous process of utmost importance for the development and maintenance of multicellular organisms. More than 10 different types of programmed cell death forms have been discovered. Several proteomics analyses have been performed to gain insight in proteins involved in the different forms of programmed cell death. To consolidate these studies, we have developed the cell death proteomics (CDP) database, which comprehends data from apoptosis, autophagy, cytotoxic granule-mediated cell death, excitotoxicity, mitotic catastrophe, paraptosis, pyroptosis, and Wallerian degeneration. The CDP database is available as a web-based database to compare protein identifications and quantitative information across different experimental setups. The proteomics data of 73 publications were integrated and unified with protein annotations from UniProt-KB and gene ontology (GO). Currently, more than 6,500 records of more than 3,700 proteins are included in the CDP. Comparing apoptosis and autophagy using overrepresentation analysis of GO terms, the majority of enriched processes were found in both, but also some clear differences were perceived. Furthermore, the analysis revealed differences and similarities of the proteome between autophagosomal and overall autophagy. The CDP database represents a useful tool to consolidate data from proteome analyses of programmed cell death and is available at http://celldeathproteomics.uio.no.
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The Utility, Limitations, and Promise of Proteomics in Animal Science
USDA-ARS?s Scientific Manuscript database
Proteomics experiments have the ability to simultaneously identify and quantify potentially thousands of proteins in one experiment. The use of this technology in animal science is still in its infancy, yet it holds significant promise as a method for advancing animal science research. Examples of...
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Perez-Riverol, Yasset; Xu, Qing-Wei; Wang, Rui; Uszkoreit, Julian; Griss, Johannes; Sanchez, Aniel; Reisinger, Florian; Csordas, Attila; Ternent, Tobias; del-Toro, Noemi; Dianes, Jose A.; Eisenacher, Martin; Hermjakob, Henning; Vizcaíno, Juan Antonio
2016-01-01
The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE. The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX “complete” submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/. PMID:26545397
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Recent advances and opportunities in proteomic analyses of tumour heterogeneity.
Bateman, Nicholas W; Conrads, Thomas P
2018-04-01
Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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Identification of new intrinsic proteins in Arabidopsis plasma membrane proteome.
Marmagne, Anne; Rouet, Marie-Aude; Ferro, Myriam; Rolland, Norbert; Alcon, Carine; Joyard, Jacques; Garin, Jérome; Barbier-Brygoo, Hélène; Ephritikhine, Geneviève
2004-07-01
Identification and characterization of anion channel genes in plants represent a goal for a better understanding of their central role in cell signaling, osmoregulation, nutrition, and metabolism. Though channel activities have been well characterized in plasma membrane by electrophysiology, the corresponding molecular entities are little documented. Indeed, the hydrophobic protein equipment of plant plasma membrane still remains largely unknown, though several proteomic approaches have been reported. To identify new putative transport systems, we developed a new proteomic strategy based on mass spectrometry analyses of a plasma membrane fraction enriched in hydrophobic proteins. We produced from Arabidopsis cell suspensions a highly purified plasma membrane fraction and characterized it in detail by immunological and enzymatic tests. Using complementary methods for the extraction of hydrophobic proteins and mass spectrometry analyses on mono-dimensional gels, about 100 proteins have been identified, 95% of which had never been found in previous proteomic studies. The inventory of the plasma membrane proteome generated by this approach contains numerous plasma membrane integral proteins, one-third displaying at least four transmembrane segments. The plasma membrane localization was confirmed for several proteins, therefore validating such proteomic strategy. An in silico analysis shows a correlation between the putative functions of the identified proteins and the expected roles for plasma membrane in transport, signaling, cellular traffic, and metabolism. This analysis also reveals 10 proteins that display structural properties compatible with transport functions and will constitute interesting targets for further functional studies.
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A chemical proteomics approach reveals Hsp27 as a target for proapoptotic clerodane diterpenes.
Faiella, Laura; Piaz, Fabrizio Dal; Bisio, Angela; Tosco, Alessandra; De Tommasi, Nunziatina
2012-10-01
Clerodane diterpenoids are a class of naturally occurring molecules widely distributed in the Lamiaceae family. Neo-clerodane diterpenoids from Salvia ssp were recently described as compounds inhibiting the proliferation of human cancer cell lines. To gain new insights into molecular mechanism(s) underlying the antitumor potential of this class of compounds, we used a chemical proteomics approach to analyse the cellular interactome of hardwickiic acid (HAA) selected as a representative molecule. HAA was linked to an opportune 1,1'-carbonyldiimidazole modified by 1,12-dodecanediamine and then immobilized on a matrix support. The modified beads were then used as bait for fishing the potential partners of HAA in a U937 cell lysate. We identified heat shock protein 27 (Hsp27), an ATP-independent antiapoptotic chaperone characterized for its tumorigenic and metastatic properties and now referenced as a major therapeutic target in many types of cancer, as a major HAA partner. Here, we also report the study of HAA-Hsp27 interaction by means of a panel of chemical and biological approaches, including surface plasmon resonance measurements limited proteolysis, and biochemical assays. Our data suggest that HAA could provide a potential tool to develop strategies for the discovery of Hsp27 chemical inhibitors.
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Advancing Proteomics Research through Collaboration | Office of Cancer Clinical Proteomics Research
The National Cancer Institute (NCI), through the Office of Cancer Clinical Proteomics Research (OCCPR), has signed two Memorandums of Understanding (MOUs) in the areas of sharing proteomics reagents and protocols and also in regulatory science.
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Kockmann, Tobias; Trachsel, Christian; Panse, Christian; Wahlander, Asa; Selevsek, Nathalie; Grossmann, Jonas; Wolski, Witold E; Schlapbach, Ralph
2016-08-01
Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*
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
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Completed | Office of Cancer Clinical Proteomics Research
Prior to the current Clinical Proteomic Tumor Analysis Consortium (CPTAC), previously funded initiatives associated with clinical proteomics research included: Clinical Proteomic Tumor Analysis Consortium (CPTAC 2.0) Clinical Proteomic Technologies for Cancer Initiative (CPTC) Mouse Proteomic Technologies Initiative
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Zhang, Bao; Qin, Yuxuan; Han, Yuzhu; Dong, Chunjuan; Li, Pinglan; Shang, Qingmao
2016-09-01
Bacillomycin L, a natural iturinic lipopeptide produced by Bacillus amyloliquefaciens, is characterized by strong antifungal activity against a variety of agronomically important filamentous fungi including Rhizoctonia solani Kühn. To further understand its antifungal actions, proteomes were comparatively studied within R. solani hyphal cells treated with or without bacillomycin L. The results show that 39 proteins were alternatively expressed within cells in response to this lipopeptide, which are involved in stress response, carbohydrate, amino acid and nucleotide metabolism, cellular component organization, calcium homeostasis, protein degradation, RNA processing, gene transcription, and others, suggesting that, in addition to inducing cell membrane permeabilization, iturin exhibits antibiotic activities by targeting intracellular molecules. Based on these results, a model of action of bacillomycin L against R. solani hyphal cells was proposed. Our study provides new insight into the antibiotic mechanisms of iturins. Copyright © 2016 Elsevier B.V. All rights reserved.
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Proteomic snapshot of the EGF-induced ubiquitin network
Argenzio, Elisabetta; Bange, Tanja; Oldrini, Barbara; Bianchi, Fabrizio; Peesari, Raghunath; Mari, Sara; Di Fiore, Pier Paolo; Mann, Matthias; Polo, Simona
2011-01-01
The activity, localization and fate of many cellular proteins are regulated through ubiquitination, a process whereby one or more ubiquitin (Ub) monomers or chains are covalently attached to target proteins. While Ub-conjugated and Ub-associated proteomes have been described, we lack a high-resolution picture of the dynamics of ubiquitination in response to signaling. In this study, we describe the epidermal growth factor (EGF)-regulated Ubiproteome, as obtained by two complementary purification strategies coupled to quantitative proteomics. Our results unveil the complex impact of growth factor signaling on Ub-based intracellular networks to levels that extend well beyond what might have been expected. In addition to endocytic proteins, the EGF-regulated Ubiproteome includes a large number of signaling proteins, ubiquitinating and deubiquitinating enzymes, transporters and proteins involved in translation and transcription. The Ub-based signaling network appears to intersect both housekeeping and regulatory circuitries of cellular physiology. Finally, as proof of principle of the biological relevance of the EGF-Ubiproteome, we demonstrated that EphA2 is a novel, downstream ubiquitinated target of epidermal growth factor receptor (EGFR), critically involved in EGFR biological responses. PMID:21245847
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The hemolymph proteome of fed and starved Drosophila larvae.
Handke, Björn; Poernbacher, Ingrid; Goetze, Sandra; Ahrens, Christian H; Omasits, Ulrich; Marty, Florian; Simigdala, Nikiana; Meyer, Imke; Wollscheid, Bernd; Brunner, Erich; Hafen, Ernst; Lehner, Christian F
2013-01-01
The co-operation of specialized organ systems in complex multicellular organisms depends on effective chemical communication. Thus, body fluids (like blood, lymph or intraspinal fluid) contain myriads of signaling mediators apart from metabolites. Moreover, these fluids are also of crucial importance for immune and wound responses. Compositional analyses of human body fluids are therefore of paramount diagnostic importance. Further improving their comprehensiveness should increase our understanding of inter-organ communication. In arthropods, which have trachea for gas exchange and an open circulatory system, the single dominating interstitial fluid is the hemolymph. Accordingly, a detailed analysis of hemolymph composition should provide an especially comprehensive picture of chemical communication and defense in animals. Therefore we used an extensive protein fractionation workflow in combination with a discovery-driven proteomic approach to map out the detectable protein composition of hemolymph isolated from Drosophila larvae. Combined mass spectrometric analysis revealed more than 700 proteins extending far beyond the previously known Drosophila hemolymph proteome. Moreover, by comparing hemolymph isolated from either fed or starved larvae, we provide initial provisional insights concerning compositional changes in response to nutritional state. Storage proteins in particular were observed to be strongly reduced by starvation. Our hemolymph proteome catalog provides a rich basis for data mining, as exemplified by our identification of potential novel cytokines, as well as for future quantitative analyses by targeted proteomics.
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The Hemolymph Proteome of Fed and Starved Drosophila Larvae
Goetze, Sandra; Ahrens, Christian H.; Omasits, Ulrich; Marty, Florian; Simigdala, Nikiana; Meyer, Imke; Wollscheid, Bernd; Brunner, Erich; Hafen, Ernst; Lehner, Christian F.
2013-01-01
The co-operation of specialized organ systems in complex multicellular organisms depends on effective chemical communication. Thus, body fluids (like blood, lymph or intraspinal fluid) contain myriads of signaling mediators apart from metabolites. Moreover, these fluids are also of crucial importance for immune and wound responses. Compositional analyses of human body fluids are therefore of paramount diagnostic importance. Further improving their comprehensiveness should increase our understanding of inter-organ communication. In arthropods, which have trachea for gas exchange and an open circulatory system, the single dominating interstitial fluid is the hemolymph. Accordingly, a detailed analysis of hemolymph composition should provide an especially comprehensive picture of chemical communication and defense in animals. Therefore we used an extensive protein fractionation workflow in combination with a discovery-driven proteomic approach to map out the detectable protein composition of hemolymph isolated from Drosophila larvae. Combined mass spectrometric analysis revealed more than 700 proteins extending far beyond the previously known Drosophila hemolymph proteome. Moreover, by comparing hemolymph isolated from either fed or starved larvae, we provide initial provisional insights concerning compositional changes in response to nutritional state. Storage proteins in particular were observed to be strongly reduced by starvation. Our hemolymph proteome catalog provides a rich basis for data mining, as exemplified by our identification of potential novel cytokines, as well as for future quantitative analyses by targeted proteomics. PMID:23840627
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Choudhary, Indu; Lee, Hyunkyoung; Pyo, Min Jung; Heo, Yunwi; Chae, Jinho; Yum, Seung Shic; Kang, Changkeun; Kim, Euikyung
2018-01-01
Nemopilema nomurai is a giant jellyfish that blooms in East Asian seas. Recently, N. nomurai venom (NnV) was characterized from a toxicological and pharmacological point of view. A mild dose of NnV inhibits the growth of various kinds of cancer cells, mainly hepatic cancer cells. The present study aims to identify the potential therapeutic targets and mechanism of NnV in the growth inhibition of cancer cells. Human hepatocellular carcinoma (HepG2) cells were treated with NnV, and its proteome was analyzed using two-dimensional gel electrophoresis, followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI/TOF/MS). The quantity of twenty four proteins in NnV-treated HepG2 cells varied compared to non-treated control cells. Among them, the amounts of fourteen proteins decreased and ten proteins showed elevated levels. We also found that the amounts of several cancer biomarkers and oncoproteins, which usually increase in various types of cancer cells, decreased after NnV treatment. The representative proteins included proliferating cell nuclear antigen (PCNA), glucose-regulated protein 78 (GRP78), glucose-6-phosphate dehydrogenase (G6PD), elongation factor 1γ (EF1γ), nucleolar and spindle-associated protein (NuSAP), and activator of 90 kDa heat shock protein ATPase homolog 1 (AHSA1). Western blotting also confirmed altered levels of PCNA, GRP78, and G6PD in NnV-treated HepG2 cells. In summary, the proteomic approach explains the mode of action of NnV as an anticancer agent. Further characterization of NnV may help to unveil novel therapeutic agents in cancer treatment. PMID:29748501
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Unraveling the resistance of microbial biofilms: has proteomics been helpful?
Seneviratne, C Jayampath; Wang, Yu; Jin, Lijian; Wong, Sarah S W; Herath, Thanuja D K; Samaranayake, Lakshman P
2012-02-01
Biofilms are surface-attached, matrix-encased, structured microbial communities which display phenotypic features that are dramatically different from those of their free-floating, or planktonic, counterparts. Biofilms seem to be the preferred mode of growth of microorganisms in nature, and at least 65% of all human infections are associated with biofilms. The most notable and clinically relevant property of biofilms is their greater resistance to antimicrobials compared with their planktonic counterparts. Although both bacterial and fungal biofilms display this phenotypic feature, the exact mechanisms underlying their increased drug resistance are yet to be determined. Advances in proteomics techniques during the past decade have facilitated in-depth analysis of the possible mechanisms underpinning increased drug resistance in biofilms. These studies have demonstrated the ability of proteomics techniques to unravel new targets for combating microbial biofilms. In this review, we discuss the putative drug resistance mechanisms of microbial biofilms that have been uncovered by proteomics and critically evaluate the possible contribution of the new knowledge to future development in the field. We also summarize strategic uses of novel proteomics technologies in studies related to drug resistance mechanisms of microbial biofilms. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Goeminne, Ludger J E; Gevaert, Kris; Clement, Lieven
2018-01-16
Label-free shotgun proteomics is routinely used to assess proteomes. However, extracting relevant information from the massive amounts of generated data remains difficult. This tutorial provides a strong foundation on analysis of quantitative proteomics data. We provide key statistical concepts that help researchers to design proteomics experiments and we showcase how to analyze quantitative proteomics data using our recent free and open-source R package MSqRob, which was developed to implement the peptide-level robust ridge regression method for relative protein quantification described by Goeminne et al. MSqRob can handle virtually any experimental proteomics design and outputs proteins ordered by statistical significance. Moreover, its graphical user interface and interactive diagnostic plots provide easy inspection and also detection of anomalies in the data and flaws in the data analysis, allowing deeper assessment of the validity of results and a critical review of the experimental design. Our tutorial discusses interactive preprocessing, data analysis and visualization of label-free MS-based quantitative proteomics experiments with simple and more complex designs. We provide well-documented scripts to run analyses in bash mode on GitHub, enabling the integration of MSqRob in automated pipelines on cluster environments (https://github.com/statOmics/MSqRob). The concepts outlined in this tutorial aid in designing better experiments and analyzing the resulting data more appropriately. The two case studies using the MSqRob graphical user interface will contribute to a wider adaptation of advanced peptide-based models, resulting in higher quality data analysis workflows and more reproducible results in the proteomics community. We also provide well-documented scripts for experienced users that aim at automating MSqRob on cluster environments. Copyright © 2017 Elsevier B.V. All rights reserved.
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[Methods of quantitative proteomics].
Kopylov, A T; Zgoda, V G
2007-01-01
In modern science proteomic analysis is inseparable from other fields of systemic biology. Possessing huge resources quantitative proteomics operates colossal information on molecular mechanisms of life. Advances in proteomics help researchers to solve complex problems of cell signaling, posttranslational modification, structure and functional homology of proteins, molecular diagnostics etc. More than 40 various methods have been developed in proteomics for quantitative analysis of proteins. Although each method is unique and has certain advantages and disadvantages all these use various isotope labels (tags). In this review we will consider the most popular and effective methods employing both chemical modifications of proteins and also metabolic and enzymatic methods of isotope labeling.
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Proteomics of filamentous fungi.
Kim, Yonghyun; Nandakumar, M P; Marten, Mark R
2007-09-01
Proteomic analysis, defined here as the global assessment of cellular proteins expressed in a particular biological state, is a powerful tool that can provide a systematic understanding of events at the molecular level. Proteomic studies of filamentous fungi have only recently begun to appear in the literature, despite the prevalence of these organisms in the biotechnology industry, and their importance as both human and plant pathogens. Here, we review recent publications that have used a proteomic approach to develop a better understanding of filamentous fungi, highlighting sample preparation methods and whole-cell cytoplasmic proteomics, as well as subproteomics of cell envelope, mitochondrial and secreted proteins.
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ProteoSign: an end-user online differential proteomics statistical analysis platform.
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.
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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.
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Proteomic identification of fat-browning markers in cultured white adipocytes treated with curcumin.
Kim, Sang Woo; Choi, Jae Heon; Mukherjee, Rajib; Hwang, Ki-Chul; Yun, Jong Won
2016-04-01
We previously reported that curcumin induces browning of primary white adipocytes via enhanced expression of brown adipocyte-specific genes. In this study, we attempted to identify target proteins responsible for this fat-browning effect by analyzing proteomic changes in cultured white adipocytes in response to curcumin treatment. To elucidate the role of curcumin in fat-browning, we conducted comparative proteomic analysis of primary adipocytes between control and curcumin-treated cells using two-dimensional electrophoresis combined with MALDI-TOF-MS. We also investigated fatty acid metabolic targets, mitochondrial biogenesis, and fat-browning-associated proteins using combined proteomic and network analyses. Proteomic analysis revealed that 58 protein spots from a total of 325 matched spots showed differential expression between control and curcumin-treated adipocytes. Using network analysis, most of the identified proteins were proven to be involved in various metabolic and cellular processes based on the PANTHER classification system. One of the most striking findings is that hormone-sensitive lipase (HSL) was highly correlated with main browning markers based on the STRING database. HSL and two browning markers (UCP1, PGC-1α) were co-immunoprecipitated with these markers, suggesting that HSL possibly plays a role in fat-browning of white adipocytes. Our results suggest that curcumin increased HSL levels and other browning-specific markers, suggesting its possible role in augmentation of lipolysis and suppression of lipogenesis by trans-differentiation from white adipocytes into brown adipocytes (beige).
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Plant proteome analysis: a 2006 update.
Jorrín, Jesús V; Maldonado, Ana M; Castillejo, Ma Angeles
2007-08-01
This 2006 'Plant Proteomics Update' is a continuation of the two previously published in 'Proteomics' by 2004 (Canovas et al., Proteomics 2004, 4, 285-298) and 2006 (Rossignol et al., Proteomics 2006, 6, 5529-5548) and it aims to bring up-to-date the contribution of proteomics to plant biology on the basis of the original research papers published throughout 2006, with references to those appearing last year. According to the published papers and topics addressed, we can conclude that, as observed for the three previous years, there has been a quantitative, but not qualitative leap in plant proteomics. The full potential of proteomics is far from being exploited in plant biology research, especially if compared to other organisms, mainly yeast and humans, and a number of challenges, mainly technological, remain to be tackled. The original papers published last year numbered nearly 100 and deal with the proteome of at least 26 plant species, with a high percentage for Arabidopsis thaliana (28) and rice (11). Scientific objectives ranged from proteomic analysis of organs/tissues/cell suspensions (57) or subcellular fractions (29), to the study of plant development (12), the effect of hormones and signalling molecules (8) and response to symbionts (4) and stresses (27). A small number of contributions have covered PTMs (8) and protein interactions (4). 2-DE (specifically IEF-SDS-PAGE) coupled to MS still constitutes the almost unique platform utilized in plant proteome analysis. The application of gel-free protein separation methods and 'second generation' proteomic techniques such as multidimensional protein identification technology (MudPIT), and those for quantitative proteomics including DIGE, isotope-coded affinity tags (ICAT), iTRAQ and stable isotope labelling by amino acids in cell culture (SILAC) still remains anecdotal. This review is divided into seven sections: Introduction, Methodology, Subcellular proteomes, Development, Responses to biotic and abiotic
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Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.
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.
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Proteomic Profiling of the Pituitary Gland in Studies of Psychiatric Disorders.
Krishnamurthy, Divya; Rahmoune, Hassan; Guest, Paul C
2017-01-01
Psychiatric disorders have been associated with perturbations of the hypothalamic-pituitary-adrenal axis. Therefore, proteomic studies of the pituitary gland have the potential to provide new insights into the underlying pathways affected in these conditions as well as identify new biomarkers or targets for use in developing improved medications. This chapter describes a protocol for preparation of pituitary protein extracts followed by characterization of the pituitary proteome by label-free liquid chromatography-tandem mass spectrometry in expression mode (LC-MS E ). The main focus was on establishing a method for identifying the major pituitary hormones and accessory proteins as many of these have already been implicated in psychiatric diseases.
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Proteomic Assessment of Poultry Spermatozoa
USDA-ARS?s Scientific Manuscript database
Fully characterizing the protein composition of spermatozoa is the first step in utilizing proteomics to delineate the function of sperm proteins. To date, sperm proteome maps have been partially developed for the human, mouse, rat, bull and several invertebrates. Here we report the first proteomic...
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Recent advances in stable isotope labeling based techniques for proteome relative quantification.
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.
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Highlights of the Biology and Disease-driven Human Proteome Project, 2015-2016.
Van Eyk, Jennifer E; Corrales, Fernando J; Aebersold, Ruedi; Cerciello, Ferdinando; Deutsch, Eric W; Roncada, Paola; Sanchez, Jean-Charles; Yamamoto, Tadashi; Yang, Pengyuan; Zhang, Hui; Omenn, Gilbert S
2016-11-04
The Biology and Disease-driven Human Proteome Project (B/D-HPP) is aimed at supporting and enhancing the broad use of state-of-the-art proteomic methods to characterize and quantify proteins for in-depth understanding of the molecular mechanisms of biological processes and human disease. Based on a foundation of the pre-existing HUPO initiatives begun in 2002, the B/D-HPP is designed to provide standardized methods and resources for mass spectrometry and specific protein affinity reagents and facilitate accessibility of these resources to the broader life sciences research and clinical communities. Currently there are 22 B/D-HPP initiatives and 3 closely related HPP resource pillars. The B/D-HPP groups are working to define sets of protein targets that are highly relevant to each particular field to deliver relevant assays for the measurement of these selected targets and to disseminate and make publicly accessible the information and tools generated. Major developments are the 2016 publications of the Human SRM Atlas and of "popular protein sets" for six organ systems. Here we present the current activities and plans of the BD-HPP initiatives as highlighted in numerous B/D-HPP workshops at the 14th annual HUPO 2015 World Congress of Proteomics in Vancouver, Canada.
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PIQMIe: a web server for semi-quantitative proteomics data management and analysis.
Kuzniar, Arnold; Kanaar, Roland
2014-07-01
We present the Proteomics Identifications and Quantitations Data Management and Integration Service or PIQMIe that aids in reliable and scalable data management, analysis and visualization of semi-quantitative mass spectrometry based proteomics experiments. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations from multiple experiments with additional biological information on the protein entries, and makes the linked data available in the form of a light-weight relational database, which enables dedicated data analyses (e.g. in R) and user-driven queries. Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. The web server not only provides data access through a web interface but also supports programmatic access through RESTful web service. The web server is available at http://piqmie.semiqprot-emc.cloudlet.sara.nl or http://www.bioinformatics.nl/piqmie. This website is free and open to all users and there is no login requirement. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Perez-Riverol, Yasset; Xu, Qing-Wei; Wang, Rui; Uszkoreit, Julian; Griss, Johannes; Sanchez, Aniel; Reisinger, Florian; Csordas, Attila; Ternent, Tobias; Del-Toro, Noemi; Dianes, Jose A; Eisenacher, Martin; Hermjakob, Henning; Vizcaíno, Juan Antonio
2016-01-01
The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE.The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX "complete" submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
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Shteynberg, David; Deutsch, Eric W.; Lam, Henry; Eng, Jimmy K.; Sun, Zhi; Tasman, Natalie; Mendoza, Luis; Moritz, Robert L.; Aebersold, Ruedi; Nesvizhskii, Alexey I.
2011-01-01
The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments
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Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.
2015-01-01
Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240
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Deutsch, Eric W; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L
2015-08-01
Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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P2P proteomics -- data sharing for enhanced protein identification
2012-01-01
Background In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that
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Bensaddek, Dalila; Narayan, Vikram; Nicolas, Armel; Murillo, Alejandro Brenes; Gartner, Anton; Kenyon, Cynthia J; Lamond, Angus I
2016-02-01
Proteomics studies typically analyze proteins at a population level, using extracts prepared from tens of thousands to millions of cells. The resulting measurements correspond to average values across the cell population and can mask considerable variation in protein expression and function between individual cells or organisms. Here, we report the development of micro-proteomics for the analysis of Caenorhabditis elegans, a eukaryote composed of 959 somatic cells and ∼1500 germ cells, measuring the worm proteome at a single organism level to a depth of ∼3000 proteins. This includes detection of proteins across a wide dynamic range of expression levels (>6 orders of magnitude), including many chromatin-associated factors involved in chromosome structure and gene regulation. We apply the micro-proteomics workflow to measure the global proteome response to heat-shock in individual nematodes. This shows variation between individual animals in the magnitude of proteome response following heat-shock, including variable induction of heat-shock proteins. The micro-proteomics pipeline thus facilitates the investigation of stochastic variation in protein expression between individuals within an isogenic population of C. elegans. All data described in this study are available online via the Encyclopedia of Proteome Dynamics (http://www.peptracker.com/epd), an open access, searchable database resource. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Weckwerth, Wolfram; Wienkoop, Stefanie; Hoehenwarter, Wolfgang; Egelhofer, Volker; Sun, Xiaoliang
2014-01-01
Genome sequencing and systems biology are revolutionizing life sciences. Proteomics emerged as a fundamental technique of this novel research area as it is the basis for gene function analysis and modeling of dynamic protein networks. Here a complete proteomics platform suited for functional genomics and systems biology is presented. The strategy includes MAPA (mass accuracy precursor alignment; http://www.univie.ac.at/mosys/software.html ) as a rapid exploratory analysis step; MASS WESTERN for targeted proteomics; COVAIN ( http://www.univie.ac.at/mosys/software.html ) for multivariate statistical analysis, data integration, and data mining; and PROMEX ( http://www.univie.ac.at/mosys/databases.html ) as a database module for proteogenomics and proteotypic peptides for targeted analysis. Moreover, the presented platform can also be utilized to integrate metabolomics and transcriptomics data for the analysis of metabolite-protein-transcript correlations and time course analysis using COVAIN. Examples for the integration of MAPA and MASS WESTERN data, proteogenomic and metabolic modeling approaches for functional genomics, phosphoproteomics by integration of MOAC (metal-oxide affinity chromatography) with MAPA, and the integration of metabolomics, transcriptomics, proteomics, and physiological data using this platform are presented. All software and step-by-step tutorials for data processing and data mining can be downloaded from http://www.univie.ac.at/mosys/software.html.
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Integrating cell biology and proteomic approaches in plants.
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
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The developmental proteome of Drosophila melanogaster
Casas-Vila, Nuria; Bluhm, Alina; Sayols, Sergi; Dinges, Nadja; Dejung, Mario; Altenhein, Tina; Kappei, Dennis; Altenhein, Benjamin; Roignant, Jean-Yves; Butter, Falk
2017-01-01
Drosophila melanogaster is a widely used genetic model organism in developmental biology. While this model organism has been intensively studied at the RNA level, a comprehensive proteomic study covering the complete life cycle is still missing. Here, we apply label-free quantitative proteomics to explore proteome remodeling across Drosophila’s life cycle, resulting in 7952 proteins, and provide a high temporal-resolved embryogenesis proteome of 5458 proteins. Our proteome data enabled us to monitor isoform-specific expression of 34 genes during development, to identify the pseudogene Cyp9f3Ψ as a protein-coding gene, and to obtain evidence of 268 small proteins. Moreover, the comparison with available transcriptomic data uncovered examples of poor correlation between mRNA and protein, underscoring the importance of proteomics to study developmental progression. Data integration of our embryogenesis proteome with tissue-specific data revealed spatial and temporal information for further functional studies of yet uncharacterized proteins. Overall, our high resolution proteomes provide a powerful resource and can be explored in detail in our interactive web interface. PMID:28381612
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The wheat chloroplastic proteome.
Kamal, Abu Hena Mostafa; Cho, Kun; Choi, Jong-Soon; Bae, Kwang-Hee; Komatsu, Setsuko; Uozumi, Nobuyuki; Woo, Sun Hee
2013-11-20
With the availability of plant genome sequencing, analysis of plant proteins with mass spectrometry has become promising and admired. Determining the proteome of a cell is still a challenging assignment, which is convoluted by proteome dynamics and convolution. Chloroplast is fastidious curiosity for plant biologists due to their intricate biochemical pathways for indispensable metabolite functions. In this review, an overview on proteomic studies conducted in wheat with a special focus on subcellular proteomics of chloroplast, salt and water stress. In recent years, we and other groups have attempted to understand the photosynthesis in wheat and abiotic stress under salt imposed and water deficit during vegetative stage. Those studies provide interesting results leading to better understanding of the photosynthesis and identifying the stress-responsive proteins. Indeed, recent studies aimed at resolving the photosynthesis pathway in wheat. Proteomic analysis combining two complementary approaches such as 2-DE and shotgun methods couple to high through put mass spectrometry (LTQ-FTICR and MALDI-TOF/TOF) in order to better understand the responsible proteins in photosynthesis and abiotic stress (salt and water) in wheat chloroplast will be focused. In this review we discussed the identification of the most abundant protein in wheat chloroplast and stress-responsive under salt and water stress in chloroplast of wheat seedlings, thus providing the proteomic view of the events during the development of this seedling under stress conditions. Chloroplast is fastidious curiosity for plant biologists due to their intricate biochemical pathways for indispensable metabolite functions. An overview on proteomic studies conducted in wheat with a special focus on subcellular proteomics of chloroplast, salt and water stress. We have attempted to understand the photosynthesis in wheat and abiotic stress under salt imposed and water deficit during seedling stage. Those studies
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Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth
Law, Kai P.; Han, Ting-Li; Tong, Chao; Baker, Philip N.
2015-01-01
Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered. PMID:26006232
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[Proteomics and its application to determine mechanism of action of traditional Chinese medicine].
Xin, Ping; Kuang, Hai-Xue; Li, Xiao-Liang; Wang, Yu; Zhang, Ben-Mei; Bu, He; Wang, Zhi-Bin; Meng, Yong-Hai; Wang, Yan-Hong; Wang, Qiu-Hong
2018-03-01
There is no doubt that the traditional Chinese medicine(TCM) is effective, practical and scientific after it was used for thousands of years. However, the mechanisms of action of many TCM are still unclear because of their multi-component, multi-target and multi-level features, which hinder the modernization and internationalization of the TCM. Proteomics is to analyze the composition and activity of intracellular proteins which are changing dynamically from a holistic perspective. It is consistent with the holistic and dynamic views of the TCM and brings about the hope of clarifying the mechanism of action of the TCM. In recent years, great progress has been made in the application of proteomics to determine the mechanism of the TCM. This article introduced the core technologies of proteomics and systematically summarized the applications of proteomics in the study of the mechanism of the Chinese medicinal formulae, single Chinese medicine and monomeric compounds from the TCM to provide innovative ideas and methods for reference. Copyright© by the Chinese Pharmaceutical Association.
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Tyrosine-Nitrated Proteins: Proteomic and Bioanalytical Aspects.
Batthyány, Carlos; Bartesaghi, Silvina; Mastrogiovanni, Mauricio; Lima, Analía; Demicheli, Verónica; Radi, Rafael
2017-03-01
"Nitroproteomic" is under active development, as 3-nitrotyrosine in proteins constitutes a footprint left by the reactions of nitric oxide-derived oxidants that are usually associated to oxidative stress conditions. Moreover, protein tyrosine nitration can cause structural and functional changes, which may be of pathophysiological relevance for human disease conditions. Biological protein tyrosine nitration is a free radical process involving the intermediacy of tyrosyl radicals; in spite of being a nonenzymatic process, nitration is selectively directed toward a limited subset of tyrosine residues. Precise identification and quantitation of 3-nitrotyrosine in proteins has represented a "tour de force" for researchers. Recent Advances: A small number of proteins are preferential targets of nitration (usually less than 100 proteins per proteome), contrasting with the large number of proteins modified by other post-translational modifications such as phosphorylation, acetylation, and, notably, S-nitrosation. Proteomic approaches have revealed key features of tyrosine nitration both in vivo and in vitro, including selectivity, site specificity, and effects in protein structure and function. Identification of 3-nitrotyrosine-containing proteins and mapping nitrated residues is challenging, due to low abundance of this oxidative modification in biological samples and its unfriendly behavior in mass spectrometry (MS)-based technologies, that is, MALDI, electrospray ionization, and collision-induced dissociation. The use of (i) classical two-dimensional electrophoresis with immunochemical detection of nitrated proteins followed by protein ID by regular MS/MS in combination with (ii) immuno-enrichment of tyrosine-nitrated peptides and (iii) identification of nitrated peptides by a MIDAS™ experiment is arising as a potent methodology to unambiguously map and quantitate tyrosine-nitrated proteins in vivo. Antioxid. Redox Signal. 26, 313-328.
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Proteomics-driven Antigen Discovery for Development of Vaccines Against Gonorrhea*
Zielke, Ryszard A.; Wierzbicki, Igor H.; Baarda, Benjamin I.; Gafken, Philip R.; Soge, Olusegun O.; Holmes, King K.; Jerse, Ann E.; Unemo, Magnus
2016-01-01
Expanding efforts to develop preventive gonorrhea vaccines is critical because of the dire possibility of untreatable gonococcal infections. Reverse vaccinology, which includes genome and proteome mining, has proven very successful in the discovery of vaccine candidates against many pathogenic bacteria. However, progress with this approach for a gonorrhea vaccine remains in its infancy. Accordingly, we applied a comprehensive proteomic platform—isobaric tagging for absolute quantification coupled with two-dimensional liquid chromatography and mass spectrometry—to identify potential gonococcal vaccine antigens. Our previous analyses focused on cell envelopes and naturally released membrane vesicles derived from four different Neisseria gonorrhoeae strains. Here, we extended these studies to identify cell envelope proteins of N. gonorrhoeae that are ubiquitously expressed and specifically induced by physiologically relevant environmental stimuli: oxygen availability, iron deprivation, and the presence of human serum. Together, these studies enabled the identification of numerous potential gonorrhea vaccine targets. Initial characterization of five novel vaccine candidate antigens that were ubiquitously expressed under these different growth conditions demonstrated that homologs of BamA (NGO1801), LptD (NGO1715), and TamA (NGO1956), and two uncharacterized proteins, NGO2054 and NGO2139, were surface exposed, secreted via naturally released membrane vesicles, and elicited bactericidal antibodies that cross-reacted with a panel of temporally and geographically diverse isolates. In addition, analysis of polymorphisms at the nucleotide and amino acid levels showed that these vaccine candidates are highly conserved among N. gonorrhoeae strains. Finally, depletion of BamA caused a loss of N. gonorrhoeae viability, suggesting it may be an essential target. Together, our data strongly support the use of proteomics-driven discovery of potential vaccine targets as a sound
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Large-scale Proteomics Analysis of the Human Kinome
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
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Allmer, Jens; Kuhlgert, Sebastian; Hippler, Michael
2008-07-07
The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed. In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application. We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling
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Jeong, Seul-Ki; Hancock, William S; Paik, Young-Ki
2015-09-04
Since the launch of the Chromosome-centric Human Proteome Project (C-HPP) in 2012, the number of "missing" proteins has fallen to 2932, down from ∼5932 since the number was first counted in 2011. We compared the characteristics of missing proteins with those of already annotated proteins with respect to transcriptional expression pattern and the time periods in which newly identified proteins were annotated. We learned that missing proteins commonly exhibit lower levels of transcriptional expression and less tissue-specific expression compared with already annotated proteins. This makes it more difficult to identify missing proteins as time goes on. One of the C-HPP goals is to identify alternative spliced product of proteins (ASPs), which are usually difficult to find by shot-gun proteomic methods due to their sequence similarities with the representative proteins. To resolve this problem, it may be necessary to use a targeted proteomics approach (e.g., selected and multiple reaction monitoring [S/MRM] assays) and an innovative bioinformatics platform that enables the selection of target peptides for rarely expressed missing proteins or ASPs. Given that the success of efforts to identify missing proteins may rely on more informative public databases, it was necessary to upgrade the available integrative databases. To this end, we attempted to improve the features and utility of GenomewidePDB by integrating transcriptomic information (e.g., alternatively spliced transcripts), annotated peptide information, and an advanced search interface that can find proteins of interest when applying a targeted proteomics strategy. This upgraded version of the database, GenomewidePDB 2.0, may not only expedite identification of the remaining missing proteins but also enhance the exchange of information among the proteome community. GenomewidePDB 2.0 is available publicly at http://genomewidepdb.proteomix.org/.
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Proteomic Analysis of Kveim Reagent Identifies Targets of Cellular Immunity in Sarcoidosis
Parker, Robert; Siddiqui, Nazneen; Potiphar, Lee; Goldin, Rob; Timms, John F.; Wells, Athol U.; Kon, Onn M.; Wickremasinghe, Melissa; Mitchell, Donald; Weeks, Mark E.; Lalvani, Ajit
2017-01-01
Background Kveim-reagent (Kv) skin testing was a historical method of diagnosing sarcoidosis. Intradermal injection of treated sarcoidosis spleen tissue resulted in a granuloma response at injection site by 4–6 weeks. Previous work indicates proteins as the possible trigger of this reaction. We aimed to identify Kv-specific proteins and characterise the ex vivo response of Peripheral Blood Mononuclear Cells (PBMCs) from sarcoidosis, tuberculosis and healthy control patients when stimulated with both Kv and selected Kv-specific proteins. Methods Kv extracts were separated by 1D-SDS-PAGE and 2D-DIGE and then underwent mass spectrometric analysis for protein identification. Sarcoidosis and control PBMCs were first stimulated with Kv and then with three selected recombinant protein candidates which were identified from the proteomic analysis. PBMC secreted cytokines were subsequently measured by Multiplex Cytokine Assay. Results We observed significantly increased IFN-γ and TNF-α secretion from Kv-stimulated PBMCs of sarcoidosis patients vs. PBMCs from healthy volunteers (IFN-γ: 207.2 pg/mL vs. 3.86 pg/mL, p = 0.0018; TNF-α: 2375 pg/mL vs. 42.82 pg/mL, p = 0.0003). Through proteomic approaches we then identified 74 sarcoidosis tissue-specific proteins. Of these, 3 proteins (vimentin, tubulin and alpha-actinin-4) were identified using both 1D-SDS-PAGE and 2D-DIGE. Data are available via ProteomeXchange with identifier PXD005150. Increased cytokine secretion was subsequently observed with vimentin stimulation of sarcoidosis PBMCs vs. tuberculosis PBMCs (IFN-γ: 396.6 pg/mL vs 0.1 pg/mL, p = 0.0009; TNF-α: 1139 pg/mL vs 0.1 pg/mL, p<0.0001). This finding was also observed in vimentin stimulation of sarcoidosis PBMCs compared to PBMCs from healthy controls (IFN-γ: 396.6 pg/mL vs. 0.1 pg/mL, p = 0.014; TNF-α: 1139 pg/mL vs 42.29 pg/mL, p = 0.027). No difference was found in cytokine secretion between sarcoidosis and control PBMCs when stimulated with either tubulin
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Science, marketing and wishful thinking in quantitative proteomics.
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.
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Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin
2017-01-01
There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed. PMID:28912895
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HTAPP: High-Throughput Autonomous Proteomic Pipeline
Yu, Kebing; Salomon, Arthur R.
2011-01-01
Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic datasets is critically important. The high-throughput autonomous proteomic pipeline (HTAPP) described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is comprised of software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of HTAPP focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples. PMID:20336676
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Proteomic Analysis of the Cell Cycle of Procylic Form Trypanosoma brucei.
Crozier, Thomas W M; Tinti, Michele; Wheeler, Richard J; Ly, Tony; Ferguson, Michael A J; Lamond, Angus I
2018-06-01
We describe a single-step centrifugal elutriation method to produce synchronous Gap1 (G1)-phase procyclic trypanosomes at a scale amenable for proteomic analysis of the cell cycle. Using ten-plex tandem mass tag (TMT) labeling and mass spectrometry (MS)-based proteomics technology, the expression levels of 5325 proteins were quantified across the cell cycle in this parasite. Of these, 384 proteins were classified as cell-cycle regulated and subdivided into nine clusters with distinct temporal regulation. These groups included many known cell cycle regulators in trypanosomes, which validates the approach. In addition, we identify 40 novel cell cycle regulated proteins that are essential for trypanosome survival and thus represent potential future drug targets for the prevention of trypanosomiasis. Through cross-comparison to the TrypTag endogenous tagging microscopy database, we were able to validate the cell-cycle regulated patterns of expression for many of the proteins of unknown function detected in our proteomic analysis. A convenient interface to access and interrogate these data is also presented, providing a useful resource for the scientific community. Data are available via ProteomeXchange with identifier PXD008741 (https://www.ebi.ac.uk/pride/archive/). © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.
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Comprehensive prediction of drug-protein interactions and side effects for the human proteome
Zhou, Hongyi; Gao, Mu; Skolnick, Jeffrey
2015-01-01
Identifying unexpected drug-protein interactions is crucial for drug repurposing. We develop a comprehensive proteome scale approach that predicts human protein targets and side effects of drugs. For drug-protein interaction prediction, FINDSITEcomb, whose average precision is ~30% and recall ~27%, is employed. For side effect prediction, a new method is developed with a precision of ~57% and a recall of ~24%. Our predictions show that drugs are quite promiscuous, with the average (median) number of human targets per drug of 329 (38), while a given protein interacts with 57 drugs. The result implies that drug side effects are inevitable and existing drugs may be useful for repurposing, with only ~1,000 human proteins likely causing serious side effects. A killing index derived from serious side effects has a strong correlation with FDA approved drugs being withdrawn. Therefore, it provides a pre-filter for new drug development. The methodology is free to the academic community on the DR. PRODIS (DRugome, PROteome, and DISeasome) webserver at http://cssb.biology.gatech.edu/dr.prodis/. DR. PRODIS provides protein targets of drugs, drugs for a given protein target, associated diseases and side effects of drugs, as well as an interface for the virtual target screening of new compounds. PMID:26057345
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NCI's Proteome Characterization Centers Announced | Office of Cancer Clinical Proteomics Research
The National Cancer Institute (NCI), part of the National Institutes of Health, announces the launch of a Clinical Proteomic Tumor Analysis Consortium (CPTAC). CPTAC is a comprehensive, coordinated team effort to accelerate the understanding of the molecular basis of cancer through the application of robust, quantitative, proteomic technologies and workflows.
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Target selection biases from recent experience transfer across effectors.
Moher, Jeff; Song, Joo-Hyun
2016-02-01
Target selection is often biased by an observer's recent experiences. However, not much is known about whether these selection biases influence behavior across different effectors. For example, does looking at a red object make it easier to subsequently reach towards another red object? In the current study, we asked observers to find the uniquely colored target object on each trial. Randomly intermixed pre-trial cues indicated the mode of action: either an eye movement or a visually guided reach movement to the target. In Experiment 1, we found that priming of popout, reflected in faster responses following repetition of the target color on consecutive trials, occurred regardless of whether the effector was repeated from the previous trial or not. In Experiment 2, we examined whether an inhibitory selection bias away from a feature could transfer across effectors. While priming of popout reflects both enhancement of the repeated target features and suppression of the repeated distractor features, the distractor previewing effect isolates a purely inhibitory component of target selection in which a previewed color is presented in a homogenous display and subsequently inhibited. Much like priming of popout, intertrial suppression biases in the distractor previewing effect transferred across effectors. Together, these results suggest that biases for target selection driven by recent trial history transfer across effectors. This indicates that representations in memory that bias attention towards or away from specific features are largely independent from their associated actions.
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Mammalian plasma membrane proteins as potential biomarkers and drug targets.
Rucevic, Marijana; Hixson, Douglas; Josic, Djuro
2011-06-01
Defining the plasma membrane proteome is crucial to understand the role of plasma membrane in fundamental biological processes. Change in membrane proteins is one of the first events that take place under pathological conditions, making plasma membrane proteins a likely source of potential disease biomarkers with prognostic or diagnostic potential. Membrane proteins are also potential targets for monoclonal antibodies and other drugs that block receptors or inhibit enzymes essential to the disease progress. Despite several advanced methods recently developed for the analysis of hydrophobic proteins and proteins with posttranslational modifications, integral membrane proteins are still under-represented in plasma membrane proteome. Recent advances in proteomic investigation of plasma membrane proteins, defining their roles as diagnostic and prognostic disease biomarkers and as target molecules in disease treatment, are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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The Succinated Proteome of FH-Mutant Tumours
Yang, Ming; Ternette, Nicola; Su, Huizhong; Dabiri, Raliat; Kessler, Benedikt M.; Adam, Julie; Teh, Bin Tean; Pollard, Patrick J.
2014-01-01
Inherited mutations in the Krebs cycle enzyme fumarate hydratase (FH) predispose to hereditary leiomyomatosis and renal cell cancer (HLRCC). Loss of FH activity in HLRCC tumours causes accumulation of the Krebs cycle intermediate fumarate to high levels, which may act as an oncometabolite through various, but not necessarily mutually exclusive, mechanisms. One such mechanism, succination, is an irreversible non-enzymatic modification of cysteine residues by fumarate, to form S-(2-succino)cysteine (2SC). Previous studies have demonstrated that succination of proteins including glyceraldehyde 3-phosphate dehydrogenase (GAPDH), kelch-like ECH-associated protein 1 (KEAP1) and mitochondrial aconitase (ACO2) can have profound effects on cellular metabolism. Furthermore, immunostaining for 2SC is a sensitive and specific biomarker for HLRCC tumours. Here, we performed a proteomic screen on an FH-mutant tumour and two HLRCC-derived cancer cell lines and identified 60 proteins where one or more cysteine residues were succinated; 10 of which were succinated at cysteine residues either predicted, or experimentally proven, to be functionally significant. Bioinformatic enrichment analyses identified most succinated targets to be involved in redox signaling. To our knowledge, this is the first proteomic-based succination screen performed in human tumours and cancer-derived cells and has identified novel 2SC targets that may be relevant to the pathogenesis of HLRCC. PMID:25105836
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Agrawal, Ganesh Kumar; Sarkar, Abhijit; Agrawal, Raj; Ndimba, Bongani Kaiser; Tanou, Georgia; Dunn, Michael J; Kieselbach, Thomas; Cramer, Rainer; Wienkoop, Stefanie; Chen, Sixue; Rafudeen, Mohammed Suhail; Deswal, Renu; Barkla, Bronwyn J; Weckwerth, Wolfram; Heazlewood, Joshua L; Renaut, Jenny; Job, Dominique; Chakraborty, Niranjan; Rakwal, Randeep
2012-02-01
The International Plant Proteomics Organization (INPPO) is a non-profit-organization consisting of people who are involved or interested in plant proteomics. INPPO is constantly growing in volume and activity, which is mostly due to the realization among plant proteomics researchers worldwide for the need of such a global platform. Their active participation resulted in the rapid growth within the first year of INPPO's official launch in 2011 via its website (www.inppo.com) and publication of the 'Viewpoint paper' in a special issue of PROTEOMICS (May 2011). Here, we will be highlighting the progress achieved in the year 2011 and the future targets for the year 2012 and onwards. INPPO has achieved a successful administrative structure, the Core Committee (CC; composed of President, Vice-President, and General Secretaries), Executive Council (EC), and General Body (GB) to achieve INPPO objectives. Various committees and subcommittees are in the process of being functionalized via discussion amongst scientists around the globe. INPPO's primary aim to popularize the plant proteomics research in biological sciences has also been recognized by PROTEOMICS where a section dedicated to plant proteomics has been introduced starting January 2012, following the very first issue of this journal devoted to plant proteomics in May 2011. To disseminate organizational activities to the scientific community, INPPO has launched a biannual (in January and July) newsletter entitled 'INPPO Express: News & Views' with the first issue published in January 2012. INPPO is also planning to have several activities in 2012, including programs within the Education Outreach committee in different countries, and the development of research ideas and proposals with priority on crop and horticultural plants, while keeping tight interactions with proteomics programs on model plants such as Arabidopsis thaliana, rice, and Medicago truncatula. Altogether, the INPPO progress and upcoming activities
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Yu, Kebing; Salomon, Arthur R
2009-12-01
Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post-acquisition analysis of proteomic data.
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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 .
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de Bernonville, Thomas Dugé; Albenne, Cécile; Arlat, Matthieu; Hoffmann, Laurent; Lauber, Emmanuelle; Jamet, Elisabeth
2014-01-01
Proteomic analysis of xylem sap has recently become a major field of interest to understand several biological questions related to plant development and responses to environmental clues. The xylem sap appears as a dynamic fluid undergoing changes in its proteome upon abiotic and biotic stresses. Unlike cell compartments which are amenable to purification in sufficient amount prior to proteomic analysis, the xylem sap has to be collected in particular conditions to avoid contamination by intracellular proteins and to obtain enough material. A model plant like Arabidopsis thaliana is not suitable for such an analysis because efficient harvesting of xylem sap is difficult. The analysis of the xylem sap proteome also requires specific procedures to concentrate proteins and to focus on proteins predicted to be secreted. Indeed, xylem sap proteins appear to be synthesized and secreted in the root stele or to originate from dying differentiated xylem cells. This chapter describes protocols to collect xylem sap from Brassica species and to prepare total and N-glycoprotein extracts for identification of proteins by mass spectrometry analyses and bioinformatics.
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Sarnyai, Zoltán; Guest, Paul C
2017-01-01
Modelling psychiatric disorders in animals has been hindered by several challenges related to our poor understanding of the disease causes. This chapter describes recent advances in translational research which may lead to animal models and relevant proteomic biomarkers that can be informative about disease mechanisms and potential new therapeutic targets. The review focuses on the behavioural and molecular correlates in models of schizophrenia and major depressive disorder, as guided by recently established Research Domain Criteria (RDoC). This approach is based on providing proteomic data for aetiologically driven, behaviourally well-characterised animal models to link discovered biomarker candidates with the human disease.
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NDCX-II target experiments and simulations
Barnard, J. J.; More, R. M.; Terry, M.; ...
2013-06-13
The ion accelerator NDCX-II is undergoing commissioning at Lawrence Berkeley National Laboratory (LBNL). Its principal mission is to explore ion-driven High Energy Density Physics (HEDP) relevant to Inertial Fusion Energy (IFE) especially in the Warm Dense Matter (WDM) regime. We have carried out hydrodynamic simulations of beam-heated targets for parameters expected for the initial configuration of NDCX-II. For metal foils of order one micron thick (thin targets), the beam is predicted to heat the target in a timescale comparable to the hydrodynamic expansion time for experiments that infer material properties from measurements of the resulting rarefaction wave. We have alsomore » carried out hydrodynamic simulations of beam heating of metallic foam targets several tens of microns thick (thick targets) in which the ion range is shorter than the areal density of the material. In this case shock waves will form and we derive simple scaling laws for the efficiency of conversion of ion energy into kinetic energy of fluid flow. Geometries with a tamping layer may also be used to study the merging of a tamper shock with the end-of-range shock. As a result, this process can occur in tamped, direct drive IFE targets.« less
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How well can morphology assess cell death modality? A proteomics study
Chernobrovkin, Alexey L; Zubarev, Roman A
2016-01-01
While the focus of attempts to classify cell death programs has finally shifted in 2010s from microscopy-based morphological characteristics to biochemical assays, more recent discoveries have put the underlying assumptions of many such assays under severe stress, mostly because of the limited specificity of the assays. On the other hand, proteomics can quantitatively measure the abundances of thousands of proteins in a single experiment. Thus proteomics could develop a modern alternative to both semiquantitative morphology assessment as well as single-molecule biochemical assays. Here we tested this hypothesis by analyzing the proteomes of cells dying after been treated with various chemical agents. The most striking finding is that, for a multivariate model based on the proteome changes in three cells lines, the regulation patterns of the 200–500 most abundant proteins typically attributed to household type more accurately reflect that of the proteins directly interacting with the drug than any other protein subset grouped by common function or biological process, including cell death. This is in broad agreement with the 'rigid cell death mechanics' model where drug action mechanism and morphological changes caused by it are bijectively linked. This finding, if confirmed, will open way for a broad use of proteomics in death modality assessment. PMID:27752363
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Integration of cardiac proteome biology and medicine by a specialized knowledgebase.
Zong, Nobel C; Li, Haomin; Li, Hua; Lam, Maggie P Y; Jimenez, Rafael C; Kim, Christina S; Deng, Ning; Kim, Allen K; Choi, Jeong Ho; Zelaya, Ivette; Liem, David; Meyer, David; Odeberg, Jacob; Fang, Caiyun; Lu, Hao-Jie; Xu, Tao; Weiss, James; Duan, Huilong; Uhlen, Mathias; Yates, John R; Apweiler, Rolf; Ge, Junbo; Hermjakob, Henning; Ping, Peipei
2013-10-12
Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.
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Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tabb, David L.; Wang, Xia; Carr, Steven A.
2016-03-04
The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilarmore » workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation. From these assessments we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61-93% of the time. When comparing across different instruments and quantitative technologies, differential genes were reproduced by other data sets from 67-99% of the time. Projecting gene differences to biological pathways and networks increased the similarities. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.« less
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Hauck, Stefanie M; Lepper, Marlen F; Hertl, Michael; Sekundo, Walter; Deeg, Cornelia A
2017-10-01
Equine recurrent uveitis is the only spontaneous model for recurrent autoimmune uveitis in humans, where T cells target retinal proteins. Differences between normal and autoaggressive lymphocytes were identified in this study by analyzing peripheral blood derived lymphocytes (PBL) proteomes from the same case with interphotoreceptor retinoid binding protein induced uveitis sampled before (Day 0), during (Day 15), and after uveitic attack (Day 23). Relative protein abundances of PBL were investigated in a quantitative, label-free differential proteome analysis in cells that were kept frozen for 14 years since the initial experiment. Quantitative data could be acquired for 2632 proteins at all three time points. Profound changes (≥2-fold change) in PBL protein abundance were observed when comparing Day 0 with 15, representing acute inflammation (1070 regulated proteins) and Day 0 with 23 (cessation; 1571 regulated). Significant differences applied to proteins with functions in integrin signaling during active uveitis, involving "Erk and pi-3 kinase are necessary for collagen binding in corneal epithelia," "integrins in angiogenesis," and "integrin-linked kinase signaling" pathways. In contrast, at cessation of uveitic attack, significantly changed proteins belonged to pathways of "nongenotropic androgen signaling," "classical complement pathway," and "Amb2 integrin signaling." Several members of respective pathways were earlier shown to be changed in naturally occurring uveitis, underscoring the significance of these findings here and proofing the value of the induced model in mimicking spontaneous autoimmune uveitis. All MS data have been deposited to the ProteomeXchange consortium via the PRIDE partner repository (dataset identifier PXD005580). © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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PROTEOMICS OF THE AMNIOTIC FLUID IN ASSESSMENT OF THE PLACENTA – RELEVANCE FOR PRETERM BIRTH
Buhimschi, Irina A.; Buhimschi, Catalin S.
2008-01-01
Proteomics is the study of expressed proteins and has emerged as a complement to genomic research. The major advantage of proteomics over DNA-RNA based technologies is that it more closely relates to phenotype and not the source code. Proteomics thus holds the promise of providing direct insight into the true mechanisms of human disease. Historically, examination of the placenta was the first modality to subclassify pathogenetical entities responsible for preterm birth. Because placenta is a key pathophysiological participant in several major obstetrical syndromes (preterm birth, preeclampsia, intrauterine growth restriction) identification of relevant biomarkers of placental function can profoundly impact on the prediction of fetal outcome and treatment efficacy. Proteomics is a young science and studies that associate proteomic patterns with long-term outcome require follow-up of children up to school age. In the interim, placental pathological footprints of cellular injury can be useful as intermediate outcomes. Furthermore, knowledge of the identity of the dys-regulated proteins may provide the necessary insight into novel pathophysiological pathways and unravel possible targets for therapeutic intervention that could not have been envisioned through hypothesis-driven approaches. PMID:18191197
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Targeted Approach for Proteomic Analysis of a Hidden Membrane Protein.
Martins-Marques, Tania; Anjo, Sandra I; Ribeiro-Rodrigues, Teresa; Manadas, Bruno; Girao, Henrique
2017-01-01
Given the properties of plasma membrane proteins, namely, their hydrophobicity, low solubility, and high resistance to digestion and extraction, their identification by traditional mass spectrometry (MS) has been a challenging task. Hence, proteomic studies involving the transmembrane protein connexin43 (Cx43) are scarce. Additionally, studies demonstrating the presence of proteins embedded in the lipid bilayer of extracellular vesicles (EVs) are difficult to perform and require specific changes and fine adjustments in the experimental and technical procedure to allow their detection by MS. In this review, we provide a detailed description of the protocol we have used to detect Cx43 in EVs of human peripheral blood. This includes some of the modifications that we have introduced in order to improve the detection of Cx43 in EVs, including an optimization of vesicle isolation, Cx43 purification, MS acquisition data, and further analysis.
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Computational clustering for viral reference proteomes
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
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Yano, Hiroyuki; Kuroda, Masaharu
2006-01-01
Accumulating evidence suggests that redox regulations play important roles in a broad spectrum of biological processes. Recently, Yano et al. developed a disulfide proteome technique that comprehensively visualizes redox change in proteins. In this paper, using the disulfide proteome, we examined rice bran and identified fragments of embryo-specific protein and dienelactone hydrolase as putative targets of thioredoxin. Also, monitoring of the endogenous and recombinant effects of thioredoxin on rice bran proteins and supporting in vivo observations propose a mechanism of redox regulation in seed germination, in which thioredoxin activates cysteine protease with a concurrent unfolding of its substrate, the embryo-specific protein. Our findings suggest that thioredoxin controls the lifetime of specific proteins effectively by regulating the redox reactions coordinately. The model study demonstrates that the disulfide proteome technique is useful not only for identifying targets of thioredoxin, but also for clarify the detailed mechanism of redox regulation.
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Advances of Proteomic Sciences in Dentistry
Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur
2016-01-01
Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed. PMID:27187379
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Advances of Proteomic Sciences in Dentistry.
Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur
2016-05-13
Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.
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An introduction to statistical process control in research proteomics.
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
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Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi
2017-06-23
The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from
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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.
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Schwarz, Jennifer Jasmin; Wiese, Heike; Tölle, Regine Charlotte; Zarei, Mostafa; Dengjel, Jörn; Warscheid, Bettina; Thedieck, Kathrin
2015-01-01
The serine/threonine kinase mammalian target of rapamycin (mTOR) governs growth, metabolism, and aging in response to insulin and amino acids (aa), and is often activated in metabolic disorders and cancer. Much is known about the regulatory signaling network that encompasses mTOR, but surprisingly few direct mTOR substrates have been established to date. To tackle this gap in our knowledge, we took advantage of a combined quantitative phosphoproteomic and interactomic strategy. We analyzed the insulin- and aa-responsive phosphoproteome upon inhibition of the mTOR complex 1 (mTORC1) component raptor, and investigated in parallel the interactome of endogenous mTOR. By overlaying these two datasets, we identified acinus L as a potential novel mTORC1 target. We confirmed acinus L as a direct mTORC1 substrate by co-immunoprecipitation and MS-enhanced kinase assays. Our study delineates a triple proteomics strategy of combined phosphoproteomics, interactomics, and MS-enhanced kinase assays for the de novo-identification of mTOR network components, and provides a rich source of potential novel mTOR interactors and targets for future investigation. PMID:25907765
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Alkylation Damage by Lipid Electrophiles Targets Functional Protein Systems*
Codreanu, Simona G.; Ullery, Jody C.; Zhu, Jing; Tallman, Keri A.; Beavers, William N.; Porter, Ned A.; Marnett, Lawrence J.; Zhang, Bing; Liebler, Daniel C.
2014-01-01
Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions. PMID:24429493
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Chen, Shun-Li; Wu, Shiaw-Lin; Huang, Li-Juan; Huang, Jia-Bao; Chen, Shu-Hui
2013-06-01
Liquid chromatography-tandem mass spectrometry-based proteomics for peptide mapping and sequencing was used to characterize the marketed monoclonal antibody trastuzumab and compare it with two biosimilar products, mAb A containing D359E and L361M variations at the Fc site and mAb B without variants. Complete sequence coverage (100%) including disulfide linkages, glycosylations and other commonly occurring modifications (i.e., deamidation, oxidation, dehydration and K-clipping) were identified using maps generated from multi-enzyme digestions. In addition to the targeted comparison for the relative populations of targeted modification forms, a non-targeted approach was used to globally compare ion intensities in tryptic maps. The non-targeted comparison provided an extra-dimensional view to examine any possible differences related to variants or modifications. A peptide containing the two variants in mAb A, D359E and L361M, was revealed using the non-targeted comparison of the tryptic maps. In contrast, no significant differences were observed when trastuzumab was self-compared or compared with mAb B. These results were consistent with the data derived from peptide sequencing via collision induced dissociation/electron transfer dissociation. Thus, combined targeted and non-targeted approaches using powerful mass spectrometry-based proteomic tools hold great promise for the structural characterization of biosimilar products. Copyright © 2013 Elsevier B.V. All rights reserved.
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The Scottish Structural Proteomics Facility: targets, methods and outputs
Oke, Muse; Carter, Lester G.; Johnson, Kenneth A.; Liu, Huanting; McMahon, Stephen A.; Yan, Xuan; Kerou, Melina; Weikart, Nadine D.; Kadi, Nadia; Sheikh, Md. Arif; Schmelz, Stefan; Dorward, Mark; Zawadzki, Michal; Cozens, Christopher; Falconer, Helen; Powers, Helen; Overton, Ian M.; van Niekerk, C. A. Johannes; Peng, Xu; Patel, Prakash; Garrett, Roger A.; Prangishvili, David; Botting, Catherine H.; Coote, Peter J.; Dryden, David T. F.; Barton, Geoffrey J.; Schwarz-Linek, Ulrich; Challis, Gregory L.; Taylor, Garry L.; White, Malcolm F.
2010-01-01
The Scottish Structural Proteomics Facility was funded to develop a laboratory scale approach to high throughput structure determination. The effort was successful in that over 40 structures were determined. These structures and the methods harnessed to obtain them are reported here. This report reflects on the value of automation but also on the continued requirement for a high degree of scientific and technical expertise. The efficiency of the process poses challenges to the current paradigm of structural analysis and publication. In the 5 year period we published ten peer-reviewed papers reporting structural data arising from the pipeline. Nevertheless, the number of structures solved exceeded our ability to analyse and publish each new finding. By reporting the experimental details and depositing the structures we hope to maximize the impact of the project by allowing others to follow up the relevant biology. Electronic supplementary material The online version of this article (doi:10.1007/s10969-010-9090-y) contains supplementary material, which is available to authorized users. PMID:20419351
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Proteome studies of filamentous fungi.
Baker, Scott E; Panisko, Ellen A
2011-01-01
The continued fast pace of fungal genome sequence generation has enabled proteomic analysis of a wide variety of organisms that span the breadth of the Kingdom Fungi. There is some phylogenetic bias to the current catalog of fungi with reasonable DNA sequence databases (genomic or EST) that could be analyzed at a global proteomic level. However, the rapid development of next generation sequencing platforms has lowered the cost of genome sequencing such that in the near future, having a genome sequence will no longer be a time or cost bottleneck for downstream proteomic (and transcriptomic) analyses. High throughput, nongel-based proteomics offers a snapshot of proteins present in a given sample at a single point in time. There are a number of variations on the general methods and technologies for identifying peptides in a given sample. We present a method that can serve as a "baseline" for proteomic studies of fungi.
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Jiang, Xiao-Sheng; Dai, Jie; Sheng, Quan-Hu; Zhang, Lei; Xia, Qi-Chang; Wu, Jia-Rui; Zeng, Rong
2005-01-01
Subcellular proteomics, as an important step to functional proteomics, has been a focus in proteomic research. However, the co-purification of "contaminating" proteins has been the major problem in all the subcellular proteomic research including all kinds of mitochondrial proteome research. It is often difficult to conclude whether these "contaminants" represent true endogenous partners or artificial associations induced by cell disruption or incomplete purification. To solve such a problem, we applied a high-throughput comparative proteome experimental strategy, ICAT approach performed with two-dimensional LC-MS/MS analysis, coupled with combinational usage of different bioinformatics tools, to study the proteome of rat liver mitochondria prepared with traditional centrifugation (CM) or further purified with a Nycodenz gradient (PM). A total of 169 proteins were identified and quantified convincingly in the ICAT analysis, in which 90 proteins have an ICAT ratio of PM:CM>1.0, while another 79 proteins have an ICAT ratio of PM:CM<1.0. Almost all the proteins annotated as mitochondrial according to Swiss-Prot annotation, bioinformatics prediction, and literature reports have a ratio of PM:CM>1.0, while proteins annotated as extracellular or secreted, cytoplasmic, endoplasmic reticulum, ribosomal, and so on have a ratio of PM:CM<1.0. Catalase and AP endonuclease 1, which have been known as peroxisomal and nuclear, respectively, have shown a ratio of PM:CM>1.0, confirming the reports about their mitochondrial location. Moreover, the 125 proteins with subcellular location annotation have been used as a testing dataset to evaluate the efficiency for ascertaining mitochondrial proteins by ICAT analysis and the bioinformatics tools such as PSORT, TargetP, SubLoc, MitoProt, and Predotar. The results indicated that ICAT analysis coupled with combinational usage of different bioinformatics tools could effectively ascertain mitochondrial proteins and distinguish contaminant
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An estimated 252,710 new cases of female breast cancer, accounting for 15% of all new cancer cases, occurred in 2017. To better understand proteogenomic abnormalities in breast cancer, the National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory breast study data. The goal of the study was to comprehensively characterize the proteome and phosphoproteome on approximately 100 prospectively collected breast tumor and adjacent normal tissues.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Matzke, Melissa M.; Brown, Joseph N.; Gritsenko, Marina A.
2013-02-01
Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred frommore » one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.« less
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Beri, Joshua; Rosenblatt, Michael M; Strauss, Ethan; Urh, Marjeta; Bereman, Michael S
2015-12-01
We present a novel proteomic standard for assessing liquid chromatography-tandem mass spectrometry (LC-MS/MS) instrument performance, in terms of chromatographic reproducibility and dynamic range within a single LC-MS/MS injection. The peptide mixture standard consists of six peptides that were specifically synthesized to cover a wide range of hydrophobicities (grand average hydropathy (GRAVY) scores of -0.6 to 1.9). A combination of stable isotope labeled amino acids ((13)C and (15)N) were inserted to create five isotopologues. By combining these isotopologues at different ratios, they span four orders of magnitude within each distinct peptide sequence. Each peptide, from lightest to heaviest, increases in abundance by a factor of 10. We evaluate several metrics on our quadrupole orbitrap instrument using the 6 × 5 LC-MS/MS reference mixture spiked into a complex lysate background as a function of dynamic range, including mass measurement accuracy (MMA) and the linear range of quantitation of MS1 and parallel reaction monitoring experiments. Detection and linearity of the instrument routinely spanned three orders of magnitude across the gradient (500 fmol to 0.5 fmol on column) and no systematic trend was observed for MMA of targeted peptides as a function of abundance by analysis of variance analysis (p = 0.17). Detection and linearity of the fifth isotopologue (i.e., 0.05 fmol on column) was dependent on the peptide and instrument scan type (MS1 vs PRM). We foresee that this standard will serve as a powerful method to conduct both intra-instrument performance monitoring/evaluation, technology development, and inter-instrument comparisons.
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An Experiment Quantifying The Effect Of Clutter On Target Detection
NASA Astrophysics Data System (ADS)
Weathersby, Marshall R.; Schmieder, David E.
1985-01-01
Experiments were conducted to determine the influence of background clutter on target detection criteria. The experiment consisted of placing observers in front of displayed images on a TV monitor. Observer ability to detect military targets embedded in simulated natural and manmade background clutter was measured when there was unlimited viewing time. Results were described in terms of detection probability versus target resolution for various signal to clutter ratios (SCR). The experiments were preceded by a search for a meaningful clutter definition. The selected definition was a statistical measure computed by averaging the standard deviation of contiguous scene cells over the whole scene. The cell size was comparable to the target size. Observer test results confirmed the expectation that the resolution required for a given detection probability was a continuum function of the clutter level. At the lower SCRs the resolution required for a high probability of detection was near 6 lines pairs per target (LP/TGT), while at the higher SCRs it was found that a resolution of less than 0.25 LP/TGT would yield a high probability of detection. These results are expected to aid in target acquisition performance modeling and to lead to improved specifications for imaging automatic target screeners.
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Bursomanno, Sara; Beli, Petra; Khan, Asif M; Minocherhomji, Sheroy; Wagner, Sebastian A; Bekker-Jensen, Simon; Mailand, Niels; Choudhary, Chunaram; Hickson, Ian D; Liu, Ying
2015-01-01
SUMOylation is a form of post-translational modification involving covalent attachment of SUMO (Small Ubiquitin-like Modifier) polypeptides to specific lysine residues in the target protein. In human cells, there are four SUMO proteins, SUMO1-4, with SUMO2 and SUMO3 forming a closely related subfamily. SUMO2/3, in contrast to SUMO1, are predominantly involved in the cellular response to certain stresses, including heat shock. Substantial evidence from studies in yeast has shown that SUMOylation plays an important role in the regulation of DNA replication and repair. Here, we report a proteomic analysis of proteins modified by SUMO2 in response to DNA replication stress in S phase in human cells. We have identified a panel of 22 SUMO2 targets with increased SUMOylation during DNA replication stress, many of which play key functions within the DNA replication machinery and/or in the cellular response to DNA damage. Interestingly, POLD3 was found modified most significantly in response to a low dose aphidicolin treatment protocol that promotes common fragile site (CFS) breakage. POLD3 is the human ortholog of POL32 in budding yeast, and has been shown to act during break-induced recombinational repair. We have also shown that deficiency of POLD3 leads to an increase in RPA-bound ssDNA when cells are under replication stress, suggesting that POLD3 plays a role in the cellular response to DNA replication stress. Considering that DNA replication stress is a source of genome instability, and that excessive replication stress is a hallmark of pre-neoplastic and tumor cells, our characterization of SUMO2 targets during a perturbed S-phase should provide a valuable resource for future functional studies in the fields of DNA metabolism and cancer biology. Copyright © 2014 Elsevier B.V. All rights reserved.
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Marondedze, Claudius; Wong, Aloysius; Groen, Arnoud; Serrano, Natalia; Jankovic, Boris; Lilley, Kathryn; Gehring, Christoph; Thomas, Ludivine
2014-12-31
The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins.
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Exploring the Arabidopsis Proteome: Influence of Protein Solubilization Buffers on Proteome Coverage
Marondedze, Claudius; Wong, Aloysius; Groen, Arnoud; Serrano, Natalia; Jankovic, Boris; Lilley, Kathryn; Gehring, Christoph; Thomas, Ludivine
2014-01-01
The study of proteomes provides new insights into stimulus-specific responses of protein synthesis and turnover, and the role of post-translational modifications at the systems level. Due to the diverse chemical nature of proteins and shortcomings in the analytical techniques used in their study, only a partial display of the proteome is achieved in any study, and this holds particularly true for plant proteomes. Here we show that different solubilization and separation methods have profound effects on the resulting proteome. In particular, we observed that the type of detergents employed in the solubilization buffer preferentially enriches proteins in different functional categories. These include proteins with a role in signaling, transport, response to temperature stimuli and metabolism. This data may offer a functional bias on comparative analysis studies. In order to obtain a broader coverage, we propose a two-step solubilization protocol with first a detergent-free buffer and then a second step utilizing a combination of two detergents to solubilize proteins. PMID:25561235
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Patel, Bhavinkumar B.; Kelsen, Steven G.; Braverman, Alan; Swinton, Derrick J.; Gafken, Philip R.; Jones, Lisa A.; Lane, William S.; Neveu, John M.; Leung, Hon-Chiu E.; Shaffer, Scott A.; Leszyk, John D.; Stanley, Bruce A.; Fox, Todd E.; Stanley, Anne; Hall, Michael J.; Hampel, Heather; South, Christopher D.; de la Chapelle, Albert; Burt, Randall W.; Jones, David A.; Kopelovich, Levy; Yeung, Anthony T.
2013-01-01
Plasma proteomic experiments performed rapidly and economically using several of the latest high-resolution mass spectrometers were compared. Four quantitative hyperfractionated plasma proteomics experiments were analyzed in replicates by two AB SCIEX TripleTOF 5600 and three Thermo Scientific Orbitrap (Elite/LTQ-Orbitrap Velos/Q Exactive) instruments. Each experiment compared two iTRAQ isobaric-labeled immunodepleted plasma proteomes, provided as 30 labeled peptide fractions. 480 LC-MS/MS runs delivered >250 GB of data in two months. Several analysis algorithms were compared. At 1 % false discovery rate, the relative comparative findings concluded that the Thermo Scientific Q Exactive Mass Spectrometer resulted in the highest number of identified proteins and unique sequences with iTRAQ quantitation. The confidence of iTRAQ fold-change for each protein is dependent on the overall ion statistics (Mascot Protein Score) attainable by each instrument. The benchmarking also suggested how to further improve the mass spectrometry parameters and HPLC conditions. Our findings highlight the special challenges presented by the low abundance peptide ions of iTRAQ plasma proteome because the dynamic range of plasma protein abundance is uniquely high compared with cell lysates, necessitating high instrument sensitivity. PMID:24004147
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The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature
Gonzalez‐Freire, Marta; Semba, Richard D.; Ubaida‐Mohien, Ceereena; Fabbri, Elisa; Scalzo, Paul; Højlund, Kurt; Dufresne, Craig; Lyashkov, Alexey
2016-01-01
Abstract Skeletal muscle is a large organ that accounts for up to half the total mass of the human body. A progressive decline in muscle mass and strength occurs with ageing and in some individuals configures the syndrome of ‘sarcopenia’, a condition that impairs mobility, challenges autonomy, and is a risk factor for mortality. The mechanisms leading to sarcopenia as well as myopathies are still little understood. The Human Skeletal Muscle Proteome Project was initiated with the aim to characterize muscle proteins and how they change with ageing and disease. We conducted an extensive review of the literature and analysed publically available protein databases. A systematic search of peer‐reviewed studies was performed using PubMed. Search terms included ‘human’, ‘skeletal muscle’, ‘proteome’, ‘proteomic(s)’, and ‘mass spectrometry’, ‘liquid chromatography‐mass spectrometry (LC‐MS/MS)’. A catalogue of 5431 non‐redundant muscle proteins identified by mass spectrometry‐based proteomics from 38 peer‐reviewed scientific publications from 2002 to November 2015 was created. We also developed a nosology system for the classification of muscle proteins based on localization and function. Such inventory of proteins should serve as a useful background reference for future research on changes in muscle proteome assessed by quantitative mass spectrometry‐based proteomic approaches that occur with ageing and diseases. This classification and compilation of the human skeletal muscle proteome can be used for the identification and quantification of proteins in skeletal muscle to discover new mechanisms for sarcopenia and specific muscle diseases that can be targeted for the prevention and treatment. PMID:27897395
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Colangelo, Christopher M.; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L.; Carriero, Nicholas J.; Gulcicek, Erol E.; Lam, TuKiet T.; Wu, Terence; Bjornson, Robert D.; Bruce, Can; Nairn, Angus C.; Rinehart, Jesse; Miller, Perry L.; Williams, Kenneth R.
2015-01-01
We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. PMID:25712262
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Colangelo, Christopher M; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L; Carriero, Nicholas J; Gulcicek, Erol E; Lam, TuKiet T; Wu, Terence; Bjornson, Robert D; Bruce, Can; Nairn, Angus C; Rinehart, Jesse; Miller, Perry L; Williams, Kenneth R
2015-02-01
We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.
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Proteome-wide Subcellular Topologies of E. coli Polypeptides Database (STEPdb)*
Orfanoudaki, Georgia; Economou, Anastassios
2014-01-01
Cell compartmentalization serves both the isolation and the specialization of cell functions. After synthesis in the cytoplasm, over a third of all proteins are targeted to other subcellular compartments. Knowing how proteins are distributed within the cell and how they interact is a prerequisite for understanding it as a whole. Surface and secreted proteins are important pathogenicity determinants. Here we present the STEP database (STEPdb) that contains a comprehensive characterization of subcellular localization and topology of the complete proteome of Escherichia coli. Two widely used E. coli proteomes (K-12 and BL21) are presented organized into thirteen subcellular classes. STEPdb exploits the wealth of genetic, proteomic, biochemical, and functional information on protein localization, secretion, and targeting in E. coli, one of the best understood model organisms. Subcellular annotations were derived from a combination of bioinformatics prediction, proteomic, biochemical, functional, topological data and extensive literature re-examination that were refined through manual curation. Strong experimental support for the location of 1553 out of 4303 proteins was based on 426 articles and some experimental indications for another 526. Annotations were provided for another 320 proteins based on firm bioinformatic predictions. STEPdb is the first database that contains an extensive set of peripheral IM proteins (PIM proteins) and includes their graphical visualization into complexes, cellular functions, and interactions. It also summarizes all currently known protein export machineries of E. coli K-12 and pairs them, where available, with the secretory proteins that use them. It catalogs the Sec- and TAT-utilizing secretomes and summarizes their topological features such as signal peptides and transmembrane regions, transmembrane topologies and orientations. It also catalogs physicochemical and structural features that influence topology such as abundance
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Cerna, Hana; Černý, Martin; Habánová, Hana; Šafářová, Dana; Abushamsiya, Kifah; Navrátil, Milan; Brzobohatý, Břetislav
2017-02-05
Pea seed-borne mosaic virus (PSbMV) significantly reduces yields in a broad spectra of legumes. The eukaryotic translation initiation factor has been shown to confer resistance to this pathogen, thus implying that translation and proteome dynamics play a role in resistance. This study presents the results of a proteome-wide analysis of Pisum sativum L. response to PSbMV infection. LC-MS profiling of two contrasting pea cultivars, resistant (B99) and susceptible (Raman) to PSbMV infection, detected >2300 proteins, 116 of which responded to PSbMV ten and/or twenty days post-inoculation. These differentially abundant proteins are involved in number of processes that have previously been reported in the plant-pathogen response, including protein and amino acid metabolism, stress signaling, redox homeostasis, carbohydrate metabolism, and lipid metabolism. We complemented our proteome-wide analysis work with targeted analyses of free amino acids and selected small molecules, fatty acid profiling, and enzyme activity assays. Data from these additional experiments support our findings and validate the biological relevance of the observed proteome changes. We found surprising similarities in the resistant and susceptible cultivars, which implies that a seemingly unaffected plant, with no detectable levels of PSbMV, actively suppresses viral replication. Plant resistance to PSbMV is connected to translation initiation factors, yet the processes involved are still poorly understood at the proteome level. To the best of our knowledge, this is the first survey of the global proteomic response to PSbMV in plants. The combination of label-free LC-MS profiling and two contrasting cultivars (resistant and susceptible) provided highly sensitive snapshots of protein abundance in response to PSbMV infection. PSbMV is a member of the largest family of plant viruses and our results are in accordance with previously characterized potyvirus-responsive proteomes. Hence, the results of this
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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