Sample records for quantitative discovery proteomics

  1. Determination of burn patient outcome by large-scale quantitative discovery proteomics

    PubMed Central

    Finnerty, Celeste C.; Jeschke, Marc G.; Qian, Wei-Jun; Kaushal, Amit; Xiao, Wenzhong; Liu, Tao; Gritsenko, Marina A.; Moore, Ronald J.; Camp, David G.; Moldawer, Lyle L.; Elson, Constance; Schoenfeld, David; Gamelli, Richard; Gibran, Nicole; Klein, Matthew; Arnoldo, Brett; Remick, Daniel; Smith, Richard D.; Davis, Ronald; Tompkins, Ronald G.; Herndon, David N.

    2013-01-01

    Objective Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and multiplex cytokine analysis to profile the plasma proteome of survivors and non-survivors of massive burn injury to determine the proteomic survival signature following a major burn injury. Design Proteomic discovery study. Setting Five burn hospitals across the U.S. Patients Thirty-two burn patients (16 non-survivors and 16 survivors), 19–89 years of age, were admitted within 96 h of injury to the participating hospitals with burns covering >20% of the total body surface area and required at least one surgical intervention. Interventions None. Measurements and Main Results We found differences in circulating levels of 43 proteins involved in the acute phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. IL-4, IL-8, GM-CSF, MCP-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. Conclusions These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale LC-MS-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma or critical illness. PMID:23507713

  2. Experimental Null Method to Guide the Development of Technical Procedures and to Control False-Positive Discovery in Quantitative Proteomics.

    PubMed

    Shen, Xiaomeng; Hu, Qiang; Li, Jun; Wang, Jianmin; Qu, Jun

    2015-10-02

    Comprehensive and accurate evaluation of data quality and false-positive biomarker discovery is critical to direct the method development/optimization for quantitative proteomics, which nonetheless remains challenging largely due to the high complexity and unique features of proteomic data. Here we describe an experimental null (EN) method to address this need. Because the method experimentally measures the null distribution (either technical or biological replicates) using the same proteomic samples, the same procedures and the same batch as the case-vs-contol experiment, it correctly reflects the collective effects of technical variability (e.g., variation/bias in sample preparation, LC-MS analysis, and data processing) and project-specific features (e.g., characteristics of the proteome and biological variation) on the performances of quantitative analysis. To show a proof of concept, we employed the EN method to assess the quantitative accuracy and precision and the ability to quantify subtle ratio changes between groups using different experimental and data-processing approaches and in various cellular and tissue proteomes. It was found that choices of quantitative features, sample size, experimental design, data-processing strategies, and quality of chromatographic separation can profoundly affect quantitative precision and accuracy of label-free quantification. The EN method was also demonstrated as a practical tool to determine the optimal experimental parameters and rational ratio cutoff for reliable protein quantification in specific proteomic experiments, for example, to identify the necessary number of technical/biological replicates per group that affords sufficient power for discovery. Furthermore, we assessed the ability of EN method to estimate levels of false-positives in the discovery of altered proteins, using two concocted sample sets mimicking proteomic profiling using technical and biological replicates, respectively, where the true

  3. Quantitative proteomics in cardiovascular research: global and targeted strategies

    PubMed Central

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

    2014-01-01

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

  4. Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry*

    PubMed Central

    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

  5. Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

    PubMed

    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.

  6. Simulated linear test applied to quantitative proteomics.

    PubMed

    Pham, T V; Jimenez, C R

    2016-09-01

    Omics studies aim to find significant changes due to biological or functional perturbation. However, gene and protein expression profiling experiments contain inherent technical variation. In discovery proteomics studies where the number of samples is typically small, technical variation plays an important role because it contributes considerably to the observed variation. Previous methods place both technical and biological variations in tightly integrated mathematical models that are difficult to adapt for different technological platforms. Our aim is to derive a statistical framework that allows the inclusion of a wide range of technical variability. We introduce a new method called the simulated linear test, or the s-test, that is easy to implement and easy to adapt for different models of technical variation. It generates virtual data points from the observed values according to a pre-defined technical distribution and subsequently employs linear modeling for significance analysis. We demonstrate the flexibility of the proposed approach by deriving a new significance test for quantitative discovery proteomics for which missing values have been a major issue for traditional methods such as the t-test. We evaluate the result on two label-free (phospho) proteomics datasets based on ion-intensity quantitation. Available at http://www.oncoproteomics.nl/software/stest.html : t.pham@vumc.nl. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  7. Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry

    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

  8. Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

    PubMed

    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.

  9. Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

    PubMed Central

    Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. Leigh; Liebler, Daniel C.; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L.; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Boja, Emily S.

    2014-01-01

    Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

  10. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

    PubMed

    Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

    2013-12-06

    Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

  11. Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

    PubMed

    Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

    2015-11-01

    Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. [Methods of quantitative proteomics].

    PubMed

    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.

  13. To label or not to label: applications of quantitative proteomics in neuroscience research.

    PubMed

    Filiou, Michaela D; Martins-de-Souza, Daniel; Guest, Paul C; Bahn, Sabine; Turck, Christoph W

    2012-02-01

    Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Quantitative proteomics in biological research.

    PubMed

    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.

  15. Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

    PubMed Central

    Brusniak, Mi-Youn; Bodenmiller, Bernd; Campbell, David; Cooke, Kelly; Eddes, James; Garbutt, Andrew; Lau, Hollis; Letarte, Simon; Mueller, Lukas N; Sharma, Vagisha; Vitek, Olga; Zhang, Ning; Aebersold, Ruedi; Watts, Julian D

    2008-01-01

    Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to

  16. [Progress in stable isotope labeled quantitative proteomics methods].

    PubMed

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

    2013-06-01

    Quantitative proteomics is an important research field in post-genomics era. There are two strategies for proteome quantification: label-free methods and stable isotope labeling methods which have become the most important strategy for quantitative proteomics at present. In the past few years, a number of quantitative methods have been developed, which support the fast development in biology research. In this work, we discuss the progress in the stable isotope labeling methods for quantitative proteomics including relative and absolute quantitative proteomics, and then give our opinions on the outlook of proteome quantification methods.

  17. Proteomic profiling of human plasma for cancer biomarker discovery.

    PubMed

    Huang, Zhao; Ma, Linguang; Huang, Canhua; Li, Qifu; Nice, Edouard C

    2017-03-01

    Over the past decades, substantial advances have been made in both the early diagnosis and accurate prognosis of many cancers because of the impressive development of novel proteomic strategies. However, it remains difficult to standardize proteomic approaches. In addition, the heterogeneity of proteins in distinct tissues results in incomplete population of the whole proteome, which inevitably limits its clinical practice. As one of the most complex proteomes in the human body, the plasma proteome contains secreted proteins originating from multiple organs and tissues, making it a favorable matrix for comprehensive biomarker discovery. Here, we will discuss the roles of plasma proteome profiling in cancer biomarker discovery and validation, and highlight both the inherent advantages and disadvantages. Although several hurdles lay ahead, further advances in this technology will greatly increase our understanding of cancer biology, reveal new biomarkers and biomarker panels, and open a new avenue for more efficient early diagnosis and surveillance of cancer, leading toward personalized medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Analysis of high accuracy, quantitative proteomics data in the MaxQB database.

    PubMed

    Schaab, Christoph; Geiger, Tamar; Stoehr, Gabriele; Cox, Juergen; Mann, Matthias

    2012-03-01

    MS-based proteomics generates rapidly increasing amounts of precise and quantitative information. Analysis of individual proteomic experiments has made great strides, but the crucial ability to compare and store information across different proteome measurements still presents many challenges. For example, it has been difficult to avoid contamination of databases with low quality peptide identifications, to control for the inflation in false positive identifications when combining data sets, and to integrate quantitative data. Although, for example, the contamination with low quality identifications has been addressed by joint analysis of deposited raw data in some public repositories, we reasoned that there should be a role for a database specifically designed for high resolution and quantitative data. Here we describe a novel database termed MaxQB that stores and displays collections of large proteomics projects and allows joint analysis and comparison. We demonstrate the analysis tools of MaxQB using proteome data of 11 different human cell lines and 28 mouse tissues. The database-wide false discovery rate is controlled by adjusting the project specific cutoff scores for the combined data sets. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted. We used MaxQB to calculate the signal reproducibility of the detected peptides for the same proteins across different proteomes. Spearman rank correlation between peptide intensity and detection probability of identified proteins was greater than 0.8 for 64% of the proteome, whereas a minority of proteins have negative correlation. This information can be used to pinpoint false protein identifications, independently of peptide database

  19. Toward improved peptide feature detection in quantitative proteomics using stable isotope labeling.

    PubMed

    Nilse, Lars; Sigloch, Florian Christoph; Biniossek, Martin L; Schilling, Oliver

    2015-08-01

    Reliable detection of peptides in LC-MS data is a key algorithmic step in the analysis of quantitative proteomics experiments. While highly abundant peptides can be detected reliably by most modern software tools, there is much less agreement on medium and low-intensity peptides in a sample. The choice of software tools can have a big impact on the quantification of proteins, especially for proteins that appear in lower concentrations. However, in many experiments, it is precisely this region of less abundant but substantially regulated proteins that holds the biggest potential for discoveries. This is particularly true for discovery proteomics in the pharmacological sector with a specific interest in key regulatory proteins. In this viewpoint article, we discuss how the development of novel software algorithms allows us to study this region of the proteome with increased confidence. Reliable results are one of many aspects to be considered when deciding on a bioinformatics software platform. Deployment into existing IT infrastructures, compatibility with other software packages, scalability, automation, flexibility, and support need to be considered and are briefly addressed in this viewpoint article. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

    PubMed Central

    Cohen Freue, Gabriela V.; Meredith, Anna; Smith, Derek; Bergman, Axel; Sasaki, Mayu; Lam, Karen K. Y.; Hollander, Zsuzsanna; Opushneva, Nina; Takhar, Mandeep; Lin, David; Wilson-McManus, Janet; Balshaw, Robert; Keown, Paul A.; Borchers, Christoph H.; McManus, Bruce; Ng, Raymond T.; McMaster, W. Robert

    2013-01-01

    Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac

  1. Quantitative proteomics in the field of microbiology.

    PubMed

    Otto, Andreas; Becher, Dörte; Schmidt, Frank

    2014-03-01

    Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    PubMed

    Hawkridge, Adam M; Muddiman, David C

    2009-01-01

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

  3. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    PubMed

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

    2010-12-07

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

  4. Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

    PubMed

    Megger, Dominik Andre; Rosowski, Kristin; Ahrens, Maike; Bracht, Thilo; Eisenacher, Martin; Schlaak, Jörg F; Weber, Frank; Hoffmann, Andreas-Claudius; Meyer, Helmut E; Baba, Hideo A; Sitek, Barbara

    2017-03-01

    Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. RAB1A was verified to be a potent biomarker candidate for HCC.

  5. MOPED enables discoveries through consistently processed proteomics data

    PubMed Central

    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

  6. A Statistical Framework for Protein Quantitation in Bottom-Up MS-Based Proteomics

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

    Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas

    2009-08-15

    Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate themore » methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives. Availability: The software has been made available in the opensource proteomics platform DAnTE (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu Supplementary information: Supplementary data are available at Bioinformatics online.« less

  7. Design and analysis issues in quantitative proteomics studies.

    PubMed

    Karp, Natasha A; Lilley, Kathryn S

    2007-09-01

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

  8. Current trends in quantitative proteomics - an update.

    PubMed

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

    2017-05-01

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

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

    PubMed

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

    2013-05-01

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

  10. Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

    DTIC Science & Technology

    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

  11. Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

    PubMed Central

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

    2010-01-01

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

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

    PubMed

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

    2017-09-01

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

  13. Benchmarking quantitative label-free LC-MS data processing workflows using a complex spiked proteomic standard dataset.

    PubMed

    Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Van Dorssaeler, Alain; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

    2016-01-30

    Proteomic workflows based on nanoLC-MS/MS data-dependent-acquisition analysis have progressed tremendously in recent years. High-resolution and fast sequencing instruments have enabled the use of label-free quantitative methods, based either on spectral counting or on MS signal analysis, which appear as an attractive way to analyze differential protein expression in complex biological samples. However, the computational processing of the data for label-free quantification still remains a challenge. Here, we used a proteomic standard composed of an equimolar mixture of 48 human proteins (Sigma UPS1) spiked at different concentrations into a background of yeast cell lysate to benchmark several label-free quantitative workflows, involving different software packages developed in recent years. This experimental design allowed to finely assess their performances in terms of sensitivity and false discovery rate, by measuring the number of true and false-positive (respectively UPS1 or yeast background proteins found as differential). The spiked standard dataset has been deposited to the ProteomeXchange repository with the identifier PXD001819 and can be used to benchmark other label-free workflows, adjust software parameter settings, improve algorithms for extraction of the quantitative metrics from raw MS data, or evaluate downstream statistical methods. Bioinformatic pipelines for label-free quantitative analysis must be objectively evaluated in their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. This can be done through the use of complex spiked samples, for which the "ground truth" of variant proteins is known, allowing a statistical evaluation of the performances of the data processing workflow. We provide here such a controlled standard dataset and used it to evaluate the performances of several label-free bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in

  14. Proteomic profiling in MPTP monkey model for early Parkinson disease biomarker discovery

    PubMed Central

    Lin, Xiangmin; Shi, Min; Gunasingh Masilamoni, Jeyaraj; Dator, Romel; Movius, James; Aro, Patrick; Smith, Yoland; Zhang, Jing

    2015-01-01

    Identification of reliable and robust biomarkers is crucial to enable early diagnosis of Parkinson disease (PD) and monitoring disease progression. While imperfect, the slow, chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced non-human primate animal model system of parkinsonism is an abundant source of pre-motor or early stage PD biomarker discovery. Here, we present a study of a MPTP rhesus monkey model of PD that utilizes complementary quantitative iTRAQ-based proteomic, glycoproteomics and phosphoproteomics approaches. We compared the glycoprotein, non-glycoprotein, and phosphoprotein profiles in the putamen of asymptomatic and symptomatic MPTP-treated monkeys as well as saline injected controls. We identified 86 glycoproteins, 163 non-glycoproteins, and 71 phosphoproteins differentially expressed in the MPTP-treated groups. Functional analysis of the data sets inferred the biological processes and pathways that link to neurodegeneration in PD and related disorders. Several potential biomarkers identified in this study have already been translated for their usefulness in PD diagnosis in human subjects and further validation investigations are currently under way. In addition to providing potential early PD biomarkers, this comprehensive quantitative proteomic study may also shed insights regarding the mechanisms underlying early PD development. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology. PMID:25617661

  15. Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

    PubMed

    Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

    2015-06-06

    There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

  16. Quantitative proteomics in Giardia duodenalis-Achievements and challenges.

    PubMed

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

    2016-08-01

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

  17. Liquid Chromatography-Mass Spectrometry-based Quantitative Proteomics

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

    Xie, Fang; Liu, Tao; Qian, Weijun

    2011-07-22

    Liquid chromatography-mass spectrometry (LC-MS)-based quantitative proteomics has become increasingly applied for a broad range of biological applications due to growing capabilities for broad proteome coverage and good accuracy in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations, and highlight their potential applications.

  18. Quantitative proteomics of bronchoalveolar lavage fluid in lung adenocarcinoma.

    PubMed

    Almatroodi, Saleh A; McDonald, Christine F; Collins, Allison L; Darby, Ian A; Pouniotis, Dodie S

    2015-01-01

    The most commonly reported primary lung cancer subtype is adenocarcinoma, which is associated with a poor prognosis and short survival. Proteomic studies on human body fluids such as bronchoalveolar lavage fluid (BALF) have become essential methods for biomarker discovery, examination of tumor pathways and investigation of potential treatments. This study used quantitative proteomics to investigate the up-regulation of novel proteins in BALF from patients with primary lung adenocarcinoma in order to identify potential biomarkers. BALF samples from individuals with and without primary lung adenocarcinoma were analyzed using liquid chromatography-mass spectrometry. One thousand and one hundred proteins were identified, 33 of which were found to be consistently overexpressed in all lung adenocarcinoma samples compared to non-cancer controls. A number of overexpressed proteins have been previously shown to be related to lung cancer progression including S100-A8, annexin A1, annexin A2, thymidine phosphorylase and transglutaminase 2. The overexpression of a number of specific proteins in BALF from patients with primary lung adenocarcinoma may be used as a potential biomarker for lung adenocarcinoma. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

  19. Quantitative proteomics to study carbapenem resistance in Acinetobacter baumannii

    PubMed Central

    Tiwari, Vishvanath; Tiwari, Monalisa

    2014-01-01

    Acinetobacter baumannii is an opportunistic pathogen causing pneumonia, respiratory infections and urinary tract infections. The prevalence of this lethal pathogen increases gradually in the clinical setup where it can grow on artificial surfaces, utilize ethanol as a carbon source. Moreover it resists desiccation. Carbapenems, a β-lactam, are the most commonly prescribed drugs against A. baumannii. Resistance against carbapenem has emerged in Acinetobacter baumannii which can create significant health problems and is responsible for high morbidity and mortality. With the development of quantitative proteomics, a considerable progress has been made in the study of carbapenem resistance of Acinetobacter baumannii. Recent updates showed that quantitative proteomics has now emerged as an important tool to understand the carbapenem resistance mechanism in Acinetobacter baumannii. Present review also highlights the complementary nature of different quantitative proteomic methods used to study carbapenem resistance and suggests to combine multiple proteomic methods for understanding the response to antibiotics by Acinetobacter baumannii. PMID:25309531

  20. QPROT: Statistical method for testing differential expression using protein-level intensity data in label-free quantitative proteomics.

    PubMed

    Choi, Hyungwon; Kim, Sinae; Fermin, Damian; Tsou, Chih-Chiang; Nesvizhskii, Alexey I

    2015-11-03

    We introduce QPROT, a statistical framework and computational tool for differential protein expression analysis using protein intensity data. QPROT is an extension of the QSPEC suite, originally developed for spectral count data, adapted for the analysis using continuously measured protein-level intensity data. QPROT offers a new intensity normalization procedure and model-based differential expression analysis, both of which account for missing data. Determination of differential expression of each protein is based on the standardized Z-statistic based on the posterior distribution of the log fold change parameter, guided by the false discovery rate estimated by a well-known Empirical Bayes method. We evaluated the classification performance of QPROT using the quantification calibration data from the clinical proteomic technology assessment for cancer (CPTAC) study and a recently published Escherichia coli benchmark dataset, with evaluation of FDR accuracy in the latter. QPROT is a statistical framework with computational software tool for comparative quantitative proteomics analysis. It features various extensions of QSPEC method originally built for spectral count data analysis, including probabilistic treatment of missing values in protein intensity data. With the increasing popularity of label-free quantitative proteomics data, the proposed method and accompanying software suite will be immediately useful for many proteomics laboratories. This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Proteomic Approaches in Biomarker Discovery: New Perspectives in Cancer Diagnostics

    PubMed Central

    Kocevar, Nina; Komel, Radovan

    2014-01-01

    Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697

  2. Advances in Quantitative Proteomics of Microbes and Microbial Communities

    NASA Astrophysics Data System (ADS)

    Waldbauer, J.; Zhang, L.; Rizzo, A. I.

    2015-12-01

    Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

  3. Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

    PubMed

    Ma, Hongyan; Delafield, Daniel G; Wang, Zhe; You, Jianlan; Wu, Si

    2017-04-01

    The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion. Graphical Abstract ᅟ.

  4. Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP)

    NASA Astrophysics Data System (ADS)

    Ma, Hongyan; Delafield, Daniel G.; Wang, Zhe; You, Jianlan; Wu, Si

    2017-04-01

    The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion.

  5. Guidelines for reporting quantitative mass spectrometry based experiments in proteomics.

    PubMed

    Martínez-Bartolomé, Salvador; Deutsch, Eric W; Binz, Pierre-Alain; Jones, Andrew R; Eisenacher, Martin; Mayer, Gerhard; Campos, Alex; Canals, Francesc; Bech-Serra, Joan-Josep; Carrascal, Montserrat; Gay, Marina; Paradela, Alberto; Navajas, Rosana; Marcilla, Miguel; Hernáez, María Luisa; Gutiérrez-Blázquez, María Dolores; Velarde, Luis Felipe Clemente; Aloria, Kerman; Beaskoetxea, Jabier; Medina-Aunon, J Alberto; Albar, Juan P

    2013-12-16

    Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML [1]. The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and

  6. EBprot: Statistical analysis of labeling-based quantitative proteomics data.

    PubMed

    Koh, Hiromi W L; Swa, Hannah L F; Fermin, Damian; Ler, Siok Ghee; Gunaratne, Jayantha; Choi, Hyungwon

    2015-08-01

    Labeling-based proteomics is a powerful method for detection of differentially expressed proteins (DEPs). The current data analysis platform typically relies on protein-level ratios, which is obtained by summarizing peptide-level ratios for each protein. In shotgun proteomics, however, some proteins are quantified with more peptides than others, and this reproducibility information is not incorporated into the differential expression (DE) analysis. Here, we propose a novel probabilistic framework EBprot that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides. To evaluate its performance with known DE states, we conducted a simulation study to show that the peptide-level analysis of EBprot provides better receiver-operating characteristic and more accurate estimation of the false discovery rates than the methods based on protein-level ratios. We also demonstrate superior classification performance of peptide-level EBprot analysis in a spike-in dataset. To illustrate the wide applicability of EBprot in different experimental designs, we applied EBprot to a dataset for lung cancer subtype analysis with biological replicates and another dataset for time course phosphoproteome analysis of EGF-stimulated HeLa cells with multiplexed labeling. Through these examples, we show that the peptide-level analysis of EBprot is a robust alternative to the existing statistical methods for the DE analysis of labeling-based quantitative datasets. The software suite is freely available on the Sourceforge website http://ebprot.sourceforge.net/. All MS data have been deposited in the ProteomeXchange with identifier PXD001426 (http://proteomecentral.proteomexchange.org/dataset/PXD001426/). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples

    PubMed Central

    Licier, Rígel; Miranda, Eric; Serrano, Horacio

    2016-01-01

    The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine. PMID:28248241

  8. A Quantitative Proteomics Approach to Clinical Research with Non-Traditional Samples.

    PubMed

    Licier, Rígel; Miranda, Eric; Serrano, Horacio

    2016-10-17

    The proper handling of samples to be analyzed by mass spectrometry (MS) can guarantee excellent results and a greater depth of analysis when working in quantitative proteomics. This is critical when trying to assess non-traditional sources such as ear wax, saliva, vitreous humor, aqueous humor, tears, nipple aspirate fluid, breast milk/colostrum, cervical-vaginal fluid, nasal secretions, bronco-alveolar lavage fluid, and stools. We intend to provide the investigator with relevant aspects of quantitative proteomics and to recognize the most recent clinical research work conducted with atypical samples and analyzed by quantitative proteomics. Having as reference the most recent and different approaches used with non-traditional sources allows us to compare new strategies in the development of novel experimental models. On the other hand, these references help us to contribute significantly to the understanding of the proportions of proteins in different proteomes of clinical interest and may lead to potential advances in the emerging field of precision medicine.

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

    PubMed

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

    2016-01-01

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

  10. Proteome-wide covalent ligand discovery in native biological systems

    PubMed Central

    Backus, Keriann M.; Correia, Bruno E.; Lum, Kenneth M.; Forli, Stefano; Horning, Benjamin D.; González-Páez, Gonzalo E.; Chatterjee, Sandip; Lanning, Bryan R.; Teijaro, John R.; Olson, Arthur J.; Wolan, Dennis W.; Cravatt, Benjamin F.

    2016-01-01

    Small molecules are powerful tools for investigating protein function and can serve as leads for new therapeutics. Most human proteins, however, lack small-molecule ligands, and entire protein classes are considered “undruggable” 1,2. Fragment-based ligand discovery (FBLD) can identify small-molecule probes for proteins that have proven difficult to target using high-throughput screening of complex compound libraries 1,3. Although reversibly binding ligands are commonly pursued, covalent fragments provide an alternative route to small-molecule probes 4–10, including those that can access regions of proteins that are difficult to access through binding affinity alone 5,10,11. In this manuscript, we report a quantitative analysis of cysteine-reactive small-molecule fragments screened against thousands of proteins. Covalent ligands were identified for >700 cysteines found in both druggable proteins and proteins deficient in chemical probes, including transcription factors, adaptor/scaffolding proteins, and uncharacterized proteins. Among the atypical ligand-protein interactions discovered were compounds that react preferentially with pro- (inactive) caspases. We used these ligands to distinguish extrinsic apoptosis pathways in human cell lines versus primary human T-cells, showing that the former is largely mediated by caspase-8 while the latter depends on both caspase-8 and −10. Fragment-based covalent ligand discovery provides a greatly expanded portrait of the ligandable proteome and furnishes compounds that can illuminate protein functions in native biological systems. PMID:27309814

  11. Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics.

    PubMed

    Gao, Yan; Lim, Teck Kwang; Lin, Qingsong; Li, Sam Fong Yau

    2016-04-29

    Cypermethrin (CYP) is one of the most widely used pesticides in large scale for agricultural and domestic purpose and the residue often seriously affects aquatic system. Environmental pollutant-induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of action. While proteomics investigations of CYP stress in some animal models have been well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001μg/L, 0.01μg/L and 1μg/L) of CYP on green algae Chlorella vulgaris for 24h and 96h was investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrate metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticide-exposed plant and algae. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Statistical design of quantitative mass spectrometry-based proteomic experiments.

    PubMed

    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.

  13. Missing Value Monitoring Enhances the Robustness in Proteomics Quantitation.

    PubMed

    Matafora, Vittoria; Corno, Andrea; Ciliberto, Andrea; Bachi, Angela

    2017-04-07

    In global proteomic analysis, it is estimated that proteins span from millions to less than 100 copies per cell. The challenge of protein quantitation by classic shotgun proteomic techniques relies on the presence of missing values in peptides belonging to low-abundance proteins that lowers intraruns reproducibility affecting postdata statistical analysis. Here, we present a new analytical workflow MvM (missing value monitoring) able to recover quantitation of missing values generated by shotgun analysis. In particular, we used confident data-dependent acquisition (DDA) quantitation only for proteins measured in all the runs, while we filled the missing values with data-independent acquisition analysis using the library previously generated in DDA. We analyzed cell cycle regulated proteins, as they are low abundance proteins with highly dynamic expression levels. Indeed, we found that cell cycle related proteins are the major components of the missing values-rich proteome. Using the MvM workflow, we doubled the number of robustly quantified cell cycle related proteins, and we reduced the number of missing values achieving robust quantitation for proteins over ∼50 molecules per cell. MvM allows lower quantification variance among replicates for low abundance proteins with respect to DDA analysis, which demonstrates the potential of this novel workflow to measure low abundance, dynamically regulated proteins.

  14. Standardization approaches in absolute quantitative proteomics with mass spectrometry.

    PubMed

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

    2017-07-31

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

  15. Comparative and Quantitative Global Proteomics Approaches: An Overview

    PubMed Central

    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

  16. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Applications in Quantitative Proteomics.

    PubMed

    Chahrour, Osama; Malone, John

    2017-01-01

    Recent advances in inductively coupled plasma mass spectrometry (ICP-MS) hyphenated to different separation techniques have promoted it as a valuable tool in protein/peptide quantification. These emerging ICP-MS applications allow absolute quantification by measuring specific elemental responses. One approach quantifies elements already present in the structure of the target peptide (e.g. phosphorus and sulphur) as natural tags. Quantification of these natural tags allows the elucidation of the degree of protein phosphorylation in addition to absolute protein quantification. A separate approach is based on utilising bi-functional labelling substances (those containing ICP-MS detectable elements), that form a covalent chemical bond with the protein thus creating analogs which are detectable by ICP-MS. Based on the previously established stoichiometries of the labelling reagents, quantification can be achieved. This technique is very useful for the design of precise multiplexed quantitation schemes to address the challenges of biomarker screening and discovery. This review discusses the capabilities and different strategies to implement ICP-MS in the field of quantitative proteomics. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  17. Quantitative targeted proteomics for understanding the blood-brain barrier: towards pharmacoproteomics.

    PubMed

    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.

  18. GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

    PubMed

    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.

  19. GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data*

    PubMed Central

    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

  20. Urine Sample Preparation in 96-Well Filter Plates for Quantitative Clinical Proteomics

    PubMed Central

    2015-01-01

    Urine is an important, noninvasively collected body fluid source for the diagnosis and prognosis of human diseases. Liquid chromatography mass spectrometry (LC-MS) based shotgun proteomics has evolved as a sensitive and informative technique to discover candidate disease biomarkers from urine specimens. Filter-aided sample preparation (FASP) generates peptide samples from protein mixtures of cell lysate or body fluid origin. Here, we describe a FASP method adapted to 96-well filter plates, named 96FASP. Soluble urine concentrates containing ∼10 μg of total protein were processed by 96FASP and LC-MS resulting in 700–900 protein identifications at a 1% false discovery rate (FDR). The experimental repeatability, as assessed by label-free quantification and Pearson correlation analysis for shared proteins among replicates, was high (R ≥ 0.97). Application to urinary pellet lysates which is of particular interest in the context of urinary tract infection analysis was also demonstrated. On average, 1700 proteins (±398) were identified in five experiments. In a pilot study using 96FASP for analysis of eight soluble urine samples, we demonstrated that protein profiles of technical replicates invariably clustered; the protein profiles for distinct urine donors were very different from each other. Robust, highly parallel methods to generate peptide mixtures from urine and other body fluids are critical to increase cost-effectiveness in clinical proteomics projects. This 96FASP method has potential to become a gold standard for high-throughput quantitative clinical proteomics. PMID:24797144

  1. Data from quantitative label free proteomics analysis of rat spleen.

    PubMed

    Dudekula, Khadar; Le Bihan, Thierry

    2016-09-01

    The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

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

    PubMed

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

    2017-08-01

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

  3. A complete mass spectrometric map for the analysis of the yeast proteome and its application to quantitative trait analysis

    PubMed Central

    Picotti, Paola; Clement-Ziza, Mathieu; Lam, Henry; Campbell, David S.; Schmidt, Alexander; Deutsch, Eric W.; Röst, Hannes; Sun, Zhi; Rinner, Oliver; Reiter, Lukas; Shen, Qin; Michaelson, Jacob J.; Frei, Andreas; Alberti, Simon; Kusebauch, Ulrike; Wollscheid, Bernd; Moritz, Robert; Beyer, Andreas; Aebersold, Ruedi

    2013-01-01

    Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways. PMID:23334424

  4. Proteomics in bone research

    PubMed Central

    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

  5. Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

    DTIC Science & Technology

    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

  6. UNiquant, a program for quantitative proteomics analysis using stable isotope labeling.

    PubMed

    Huang, Xin; Tolmachev, Aleksey V; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A; Smith, Richard D; Chan, Wing C; Hinrichs, Steven H; Fu, Kai; Ding, Shi-Jian

    2011-03-04

    Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.

  7. UNiquant, a Program for Quantitative Proteomics Analysis Using Stable Isotope Labeling

    PubMed Central

    Huang, Xin; Tolmachev, Aleksey V.; Shen, Yulei; Liu, Miao; Huang, Lin; Zhang, Zhixin; Anderson, Gordon A.; Smith, Richard D.; Chan, Wing C.; Hinrichs, Steven H.; Fu, Kai; Ding, Shi-Jian

    2011-01-01

    Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for post-measurement normalization of peptide ratios, which is required by the other programs. PMID:21158445

  8. Response of Human Osteoblast to n-HA/PEEK—Quantitative Proteomic Study of Bio-effects of Nano-Hydroxyapatite Composite

    NASA Astrophysics Data System (ADS)

    Zhao, Minzhi; Li, Haiyun; Liu, Xiaochen; Wei, Jie; Ji, Jianguo; Yang, Shu; Hu, Zhiyuan; Wei, Shicheng

    2016-03-01

    Nano-sized hydroxyapatite (n-HA) is considered as a bio-active material, which is often mixed into bone implant material, polyetheretherketone (PEEK). To reveal the global protein expression modulations of osteoblast in response to direct contact with the PEEK composite containing high level (40%) nano-sized hydroxyapatite (n-HA/PEEK) and explain its comprehensive bio-effects, quantitative proteomic analysis was conducted on human osteoblast-like cells MG-63 cultured on n-HA/PEEK in comparison with pure PEEK. Results from quantitative proteomic analysis showed that the most enriched categories in the up-regulated proteins were related to calcium ion processes and associated functions while the most enriched categories in the down-regulated proteins were related to RNA process. This enhanced our understanding to the molecular mechanism of the promotion of the cell adhesion and differentiation with the inhibition of the cell proliferation on n-HA/PEEK composite. It also exhibited that although the calcium ion level of incubate environment hadn’t increased, merely the calcium fixed on the surface of material had influence to intracellular calcium related processes, which was also reflect by the higher intracellular Ca2+ concentration of n-HA/PEEK. This study could lead to more comprehensive cognition to the versatile biocompatibility of composite materials. It further proves that proteomics is useful in new bio-effect discovery.

  9. Response of Human Osteoblast to n-HA/PEEK--Quantitative Proteomic Study of Bio-effects of Nano-Hydroxyapatite Composite.

    PubMed

    Zhao, Minzhi; Li, Haiyun; Liu, Xiaochen; Wei, Jie; Ji, Jianguo; Yang, Shu; Hu, Zhiyuan; Wei, Shicheng

    2016-03-09

    Nano-sized hydroxyapatite (n-HA) is considered as a bio-active material, which is often mixed into bone implant material, polyetheretherketone (PEEK). To reveal the global protein expression modulations of osteoblast in response to direct contact with the PEEK composite containing high level (40%) nano-sized hydroxyapatite (n-HA/PEEK) and explain its comprehensive bio-effects, quantitative proteomic analysis was conducted on human osteoblast-like cells MG-63 cultured on n-HA/PEEK in comparison with pure PEEK. Results from quantitative proteomic analysis showed that the most enriched categories in the up-regulated proteins were related to calcium ion processes and associated functions while the most enriched categories in the down-regulated proteins were related to RNA process. This enhanced our understanding to the molecular mechanism of the promotion of the cell adhesion and differentiation with the inhibition of the cell proliferation on n-HA/PEEK composite. It also exhibited that although the calcium ion level of incubate environment hadn't increased, merely the calcium fixed on the surface of material had influence to intracellular calcium related processes, which was also reflect by the higher intracellular Ca(2+) concentration of n-HA/PEEK. This study could lead to more comprehensive cognition to the versatile biocompatibility of composite materials. It further proves that proteomics is useful in new bio-effect discovery.

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

    PubMed

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

    2014-07-01

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

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

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

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

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

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

    PubMed

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

    2016-01-01

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

  13. Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome.

    PubMed

    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.

  14. Will Quantitative Proteomics Redefine Some of the Key Concepts in Skeletal Muscle Physiology?

    PubMed

    Gizak, Agnieszka; Rakus, Dariusz

    2016-01-11

    Molecular and cellular biology methodology is traditionally based on the reasoning called "the mechanistic explanation". In practice, this means identifying and selecting correlations between biological processes which result from our manipulation of a biological system. In theory, a successful application of this approach requires precise knowledge about all parameters of a studied system. However, in practice, due to the systems' complexity, this requirement is rarely, if ever, accomplished. Typically, it is limited to a quantitative or semi-quantitative measurements of selected parameters (e.g., concentrations of some metabolites), and a qualitative or semi-quantitative description of expression/post-translational modifications changes within selected proteins. A quantitative proteomics approach gives a possibility of quantitative characterization of the entire proteome of a biological system, in the context of the titer of proteins as well as their post-translational modifications. This enables not only more accurate testing of novel hypotheses but also provides tools that can be used to verify some of the most fundamental dogmas of modern biology. In this short review, we discuss some of the consequences of using quantitative proteomics to verify several key concepts in skeletal muscle physiology.

  15. Proteomics-driven Antigen Discovery for Development of Vaccines Against Gonorrhea*

    PubMed Central

    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

  16. iTRAQ Quantitative Proteomic Comparison of Metastatic and Non-Metastatic Uveal Melanoma Tumors

    PubMed Central

    Crabb, John W.; Hu, Bo; Crabb, John S.; Triozzi, Pierre; Saunthararajah, Yogen; Singh, Arun D.

    2015-01-01

    Background Uveal melanoma is the most common malignancy of the adult eye. The overall mortality rate is high because this aggressive cancer often metastasizes before ophthalmic diagnosis. Quantitative proteomic analysis of primary metastasizing and non-metastasizing tumors was pursued for insights into mechanisms and biomarkers of uveal melanoma metastasis. Methods Eight metastatic and 7 non-metastatic human primary uveal melanoma tumors were analyzed by LC MS/MS iTRAQ technology with Bruch’s membrane/choroid complex from normal postmortem eyes as control tissue. Tryptic peptides from tumor and control proteins were labeled with iTRAQ tags, fractionated by cation exchange chromatography, and analyzed by LC MS/MS. Protein identification utilized the Mascot search engine and the human Uni-Prot/Swiss-Protein database with false discovery ≤ 1%; protein quantitation utilized the Mascot weighted average method. Proteins designated differentially expressed exhibited quantitative differences (p ≤ 0.05, t-test) in a training set of five metastatic and five non-metastatic tumors. Logistic regression models developed from the training set were used to classify the metastatic status of five independent tumors. Results Of 1644 proteins identified and quantified in 5 metastatic and 5 non-metastatic tumors, 12 proteins were found uniquely in ≥ 3 metastatic tumors, 28 were found significantly elevated and 30 significantly decreased only in metastatic tumors, and 31 were designated differentially expressed between metastatic and non-metastatic tumors. Logistic regression modeling of differentially expressed collagen alpha-3(VI) and heat shock protein beta-1 allowed correct prediction of metastasis status for each of five independent tumor specimens. Conclusions The present data provide new clues to molecular differences in metastatic and non-metastatic uveal melanoma tumors. While sample size is limited and validation required, the results support collagen alpha-3(VI) and

  17. Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

    PubMed Central

    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

  18. A Critical Appraisal of Techniques, Software Packages, and Standards for Quantitative Proteomic Analysis

    PubMed Central

    Lawless, Craig; Hubbard, Simon J.; Fan, Jun; Bessant, Conrad; Hermjakob, Henning; Jones, Andrew R.

    2012-01-01

    Abstract New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool (http://www.proteosuite.org/?q=other_resources) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology. PMID:22804616

  19. Science, marketing and wishful thinking in quantitative proteomics.

    PubMed

    Hackett, Murray

    2008-11-01

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

  20. Design and analysis of quantitative differential proteomics investigations using LC-MS technology.

    PubMed

    Bukhman, Yury V; Dharsee, Moyez; Ewing, Rob; Chu, Peter; Topaloglou, Thodoros; Le Bihan, Thierry; Goh, Theo; Duewel, Henry; Stewart, Ian I; Wisniewski, Jacek R; Ng, Nancy F

    2008-02-01

    Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is becoming an increasingly important tool in characterizing the abundance of proteins in biological samples of various types and across conditions. Effects of disease or drug treatments on protein abundance are of particular interest for the characterization of biological processes and the identification of biomarkers. Although state-of-the-art instrumentation is available to make high-quality measurements and commercially available software is available to process the data, the complexity of the technology and data presents challenges for bioinformaticians and statisticians. Here, we describe a pipeline for the analysis of quantitative LC-MS data. Key components of this pipeline include experimental design (sample pooling, blocking, and randomization) as well as deconvolution and alignment of mass chromatograms to generate a matrix of molecular abundance profiles. An important challenge in LC-MS-based quantitation is to be able to accurately identify and assign abundance measurements to members of protein families. To address this issue, we implement a novel statistical method for inferring the relative abundance of related members of protein families from tryptic peptide intensities. This pipeline has been used to analyze quantitative LC-MS data from multiple biomarker discovery projects. We illustrate our pipeline here with examples from two of these studies, and show that the pipeline constitutes a complete workable framework for LC-MS-based differential quantitation. Supplementary material is available at http://iec01.mie.utoronto.ca/~thodoros/Bukhman/.

  1. Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

    PubMed

    Pursiheimo, Anna; Vehmas, Anni P; Afzal, Saira; Suomi, Tomi; Chand, Thaman; Strauss, Leena; Poutanen, Matti; Rokka, Anne; Corthals, Garry L; Elo, Laura L

    2015-10-02

    As tools for quantitative label-free mass spectrometry (MS) rapidly develop, a consensus about the best practices is not apparent. In the work described here we compared popular statistical methods for detecting differential protein expression from quantitative MS data using both controlled experiments with known quantitative differences for specific proteins used as standards as well as "real" experiments where differences in protein abundance are not known a priori. Our results suggest that data-driven reproducibility-optimization can consistently produce reliable differential expression rankings for label-free proteome tools and are straightforward in their application.

  2. Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients.

    PubMed

    Mu, Jun; Yang, Yongtao; Chen, Jin; Cheng, Ke; Li, Qi; Wei, Yongdong; Zhu, Dan; Shao, Weihua; Zheng, Peng; Xie, Peng

    2015-10-30

    Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology and proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2011-01-01

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

  4. PIQMIe: a web server for semi-quantitative proteomics data management and analysis

    PubMed Central

    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

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

    PubMed

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

    2008-09-01

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

  6. Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

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

    Mu, Jun; Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing; Chongqing Key Laboratory of Neurobiology, Chongqing

    Purpose: Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). Methods: CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology andmore » proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Results: Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. Conclusions: CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. - Highlights: • The first proteomic study on the cerebrospinal fluid of tuberculous meningitis patients using iTRAQ. • Identify 4 differential proteins invloved in the lipid metabolism. • Elevated expression of Apo

  7. Label-free quantitative proteomics to investigate strawberry fruit proteome changes under controlled atmosphere and low temperature storage.

    PubMed

    Li, Li; Luo, Zisheng; Huang, Xinhong; Zhang, Lu; Zhao, Pengyu; Ma, Hongyuan; Li, Xihong; Ban, Zhaojun; Liu, Xia

    2015-04-29

    To elucidate the mechanisms contributing to fruit responses to senescence and stressful environmental stimuli under low temperature (LT) and controlled atmosphere (CA) storage, a label-free quantitative proteomic investigation was conducted in strawberry (Fragaria ananassa, Duch. cv. 'Akihime'). Postharvest physiological quality traits including firmness, total soluble solids, total acidity, ascorbic acid and volatile production were characterized following storage under different conditions. The observed post-storage protein expression profiles may be associated with delayed senescence features in strawberry. A total of 454 proteins were identified in differentially treated strawberry fruits. Quantitative analysis, using normalized spectral counts, revealed 73 proteins common to all treatments, which formed three clusters in a hierarchical clustering analysis. The proteins spanned a range of functions in various metabolic pathways and networks involved in carbohydrate and energy metabolism, volatile biosynthesis, phenylpropanoid activity, stress response and protein synthesis, degradation and folding. After CA and LT storage, 16 (13) and 11 (17) proteins, respectively, were significantly increased (decreased) in abundance, while expression profile of 12 proteins was significantly changed by both CA and LT. To summarize, the differential variability of abundance in strawberry proteome, working in a cooperative manner, provided an overview of the biological processes that occurred during CA and LT storage. Controlled atmosphere storage at an optimal temperature is regarded to be an effective postharvest technology to delay fruit senescence and maintain fruit quality during shelf life. Nonetheless, little information on fruit proteomic changes under controlled atmosphere and/or low temperature storage is available. The significance of this paper is that it is the first study employing a label-free approach in the investigation of strawberry fruit response to

  8. Proteomics of gliomas: Initial biomarker discovery and evolution of technology

    PubMed Central

    Kalinina, Juliya; Peng, Junmin; Ritchie, James C.; Van Meir, Erwin G.

    2011-01-01

    Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers. PMID:21852429

  9. Quantitative proteomics reveals the kinetics of trypsin-catalyzed protein digestion.

    PubMed

    Pan, Yanbo; Cheng, Kai; Mao, Jiawei; Liu, Fangjie; Liu, Jing; Ye, Mingliang; Zou, Hanfa

    2014-10-01

    Trypsin is the popular protease to digest proteins into peptides in shotgun proteomics, but few studies have attempted to systematically investigate the kinetics of trypsin-catalyzed protein digestion in proteome samples. In this study, we applied quantitative proteomics via triplex stable isotope dimethyl labeling to investigate the kinetics of trypsin-catalyzed cleavage. It was found that trypsin cleaves the C-terminal to lysine (K) and arginine (R) residues with higher rates for R. And the cleavage sites surrounded by neutral residues could be quickly cut, while those with neighboring charged residues (D/E/K/R) or proline residue (P) could be slowly cut. In a proteome sample, a huge number of proteins with different physical chemical properties coexists. If any type of protein could be preferably digested, then limited digestion could be applied to reduce the sample complexity. However, we found that protein abundance and other physicochemical properties, such as molecular weight (Mw), grand average of hydropathicity (GRAVY), aliphatic index, and isoelectric point (pI) have no notable correlation with digestion priority of proteins.

  10. Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis.

    PubMed

    Clark, David J; Fondrie, William E; Liao, Zhongping; Hanson, Phyllis I; Fulton, Amy; Mao, Li; Yang, Austin J

    2015-10-20

    Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

  11. A review on recent developments in mass spectrometry instrumentation and quantitative tools advancing bacterial proteomics.

    PubMed

    Van Oudenhove, Laurence; Devreese, Bart

    2013-06-01

    Proteomics has evolved substantially since its early days, some 20 years ago. In this mini-review, we aim to provide an overview of general methodologies and more recent developments in mass spectrometric approaches used for relative and absolute quantitation of proteins. Enhancement of sensitivity of the mass spectrometers as well as improved sample preparation and protein fractionation methods are resulting in a more comprehensive analysis of proteomes. We also document some upcoming trends for quantitative proteomics such as the use of label-free quantification methods. Hopefully, microbiologists will continue to explore proteomics as a tool in their research to understand the adaptation of microorganisms to their ever changing environment. We encourage them to incorporate some of the described new developments in mass spectrometry to facilitate their analyses and improve the general knowledge of the fascinating world of microorganisms.

  12. Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

    PubMed

    Morris, Jeffrey S

    2012-01-01

    In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods

  13. Method and platform standardization in MRM-based quantitative plasma proteomics.

    PubMed

    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

  14. MRM as a discovery tool?

    PubMed

    Rudnick, Paul A

    2015-04-01

    Multiple-reaction monitoring (MRM) of peptides has been recognized as a promising technology because it is sensitive and robust. Borrowed from stable-isotope dilution (SID) methodologies in the field of small molecules, MRM is now routinely used in proteomics laboratories. While its usefulness validating candidate targets is widely accepted, it has not been established as a discovery tool. Traditional thinking has been that MRM workflows cannot be multiplexed high enough to efficiently profile. This is due to slower instrument scan rates and the complexities of developing increasingly large scheduling methods. In this issue, Colangelo et al. (Proteomics 2015, 15, 1202-1214) describe a pipeline (xMRM) for discovery-style MRM using label-free methods (i.e. relative quantitation). Label-free comes with cost benefits as does MRM, where data are easier to analyze than full-scan. Their paper offers numerous improvements in method design and data analysis. The robustness of their pipeline was tested on rodent postsynaptic density fractions. There, they were able to accurately quantify 112 proteins at a CV% of 11.4, with only 2.5% of the 1697 transitions requiring user intervention. Colangelo et al. aim to extend the reach of MRM deeper into the realm of discovery proteomics, an area that is currently dominated by data-dependent and data-independent workflows. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. PIQMIe: a web server for semi-quantitative proteomics data management and analysis.

    PubMed

    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.

  16. Stable isotope dimethyl labelling for quantitative proteomics and beyond

    PubMed Central

    Hsu, Jue-Liang; Chen, Shu-Hui

    2016-01-01

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

  17. Characterization of the liver tissue interstitial fluid (TIF) proteome indicates potential for application in liver disease biomarker discovery.

    PubMed

    Sun, Wei; Ma, Jie; Wu, Songfeng; Yang, Dong; Yan, Yujuan; Liu, Kehui; Wang, Jinglan; Sun, Longqin; Chen, Ning; Wei, Handong; Zhu, Yunping; Xing, Baocai; Zhao, Xiaohang; Qian, Xiaohong; Jiang, Ying; He, Fuchu

    2010-02-05

    Tissue interstitial fluid (TIF) forms the interface between circulating body fluids and intracellular fluid. Pathological alterations of liver cells could be reflected in TIF, making it a promising source of liver disease biomarkers. Mouse liver TIF was extracted, separated by SDS-PAGE, analyzed by linear ion trap mass spectrometer, and 1450 proteins were identified. These proteins may be secreted, shed from membrane vesicles, or represent cellular breakdown products. They show different profiling patterns, quantities, and possibly modification/cleavage of intracellular proteins. The high solubility and even distribution of liver TIF supports its suitability for proteome analysis. Comparison of mouse liver TIF data with liver tissue and plasma proteome data identified major proteins that might be released from liver to plasma and serve as blood biomarkers of liver origin. This result was partially supported by comparison of human liver TIF data with human liver and plasma proteome data. Paired TIFs from tumor and nontumor liver tissues of a hepatocellular carcinoma patient were analyzed and the profile of subtracted differential proteins supports the potential for biomarker discovery in TIF. This study is the first analysis of the liver TIF proteome and provides a foundation for further application of TIF in liver disease biomarker discovery.

  18. The speciation of the proteome

    PubMed Central

    Jungblut, Peter R; Holzhütter, Hermann G; Apweiler, Rolf; Schlüter, Hartmut

    2008-01-01

    Introduction In proteomics a paradox situation developed in the last years. At one side it is basic knowledge that proteins are post-translationally modified and occur in different isoforms. At the other side the protein expression concept disclaims post-translational modifications by connecting protein names directly with function. Discussion Optimal proteome coverage is today reached by bottom-up liquid chromatography/mass spectrometry. But quantification at the peptide level in shotgun or bottom-up approaches by liquid chromatography and mass spectrometry is completely ignoring that a special peptide may exist in an unmodified form and in several-fold modified forms. The acceptance of the protein species concept is a basic prerequisite for meaningful quantitative analyses in functional proteomics. In discovery approaches only top-down analyses, separating the protein species before digestion, identification and quantification by two-dimensional gel electrophoresis or protein liquid chromatography, allow the correlation between changes of a biological situation and function. Conclusion To obtain biological relevant information kinetics and systems biology have to be performed at the protein species level, which is the major challenge in proteomics today. PMID:18638390

  19. Using PeptideAtlas, SRMAtlas and PASSEL – Comprehensive Resources for discovery and targeted proteomics

    PubMed Central

    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

  20. Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics.

    PubMed

    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.

  1. Improved False Discovery Rate Estimation Procedure for Shotgun Proteomics

    PubMed Central

    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

  2. Quantitative Proteomic Analysis of the Hfq-Regulon in Sinorhizobium meliloti 2011

    PubMed Central

    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

  3. Quantitative proteomic analysis of the Hfq-regulon in Sinorhizobium meliloti 2011.

    PubMed

    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.

  4. Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

    PubMed

    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

  5. Mining for Microbial Gems: Integrating Proteomics in the Postgenomic Natural Product Discovery Pipeline.

    PubMed

    Du, Chao; van Wezel, Gilles P

    2018-04-30

    Natural products (NPs) are a major source of compounds for medical, agricultural, and biotechnological industries. Many of these compounds are of microbial origin, and, in particular, from Actinobacteria or filamentous fungi. To successfully identify novel compounds that correlate to a bioactivity of interest, or discover new enzymes with desired functions, systematic multiomics approaches have been developed over the years. Bioinformatics tools harness the rapidly expanding wealth of genome sequence information, revealing previously unsuspected biosynthetic diversity. Varying growth conditions or application of elicitors are applied to activate cryptic biosynthetic gene clusters, and metabolomics provide detailed insights into the NPs they specify. Combining these technologies with proteomics-based approaches to profile the biosynthetic enzymes provides scientists with insights into the full biosynthetic potential of microorganisms. The proteomics approaches include enrichment strategies such as employing activity-based probes designed by chemical biology, as well as unbiased (quantitative) proteomics methods. In this review, the opportunities and challenges in microbial NP research are discussed, and, in particular, the application of proteomics to link biosynthetic enzymes to the molecules they produce, and vice versa. © 2018 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Magnetoresistive biosensors for quantitative proteomics

    NASA Astrophysics Data System (ADS)

    Zhou, Xiahan; Huang, Chih-Cheng; Hall, Drew A.

    2017-08-01

    Quantitative proteomics, as a developing method for study of proteins and identification of diseases, reveals more comprehensive and accurate information of an organism than traditional genomics. A variety of platforms, such as mass spectrometry, optical sensors, electrochemical sensors, magnetic sensors, etc., have been developed for detecting proteins quantitatively. The sandwich immunoassay is widely used as a labeled detection method due to its high specificity and flexibility allowing multiple different types of labels. While optical sensors use enzyme and fluorophore labels to detect proteins with high sensitivity, they often suffer from high background signal and challenges in miniaturization. Magnetic biosensors, including nuclear magnetic resonance sensors, oscillator-based sensors, Hall-effect sensors, and magnetoresistive sensors, use the specific binding events between magnetic nanoparticles (MNPs) and target proteins to measure the analyte concentration. Compared with other biosensing techniques, magnetic sensors take advantage of the intrinsic lack of magnetic signatures in biological samples to achieve high sensitivity and high specificity, and are compatible with semiconductor-based fabrication process to have low-cost and small-size for point-of-care (POC) applications. Although still in the development stage, magnetic biosensing is a promising technique for in-home testing and portable disease monitoring.

  7. An Overview of Advanced SILAC-Labeling Strategies for Quantitative Proteomics.

    PubMed

    Terzi, F; Cambridge, S

    2017-01-01

    Comparative, quantitative mass spectrometry of proteins provides great insight to protein abundance and function, but some molecular characteristics related to protein dynamics are not so easily obtained. Because the metabolic incorporation of stable amino acid isotopes allows the extraction of distinct temporal and spatial aspects of protein dynamics, the SILAC methodology is uniquely suited to be adapted for advanced labeling strategies. New SILAC strategies have emerged that allow deeper foraging into the complexity of cellular proteomes. Here, we review a few advanced SILAC-labeling strategies that have been published during last the years. Among them, different subsaturating-labeling as well as dual-labeling schemes are most prominent for a range of analyses including those of neuronal proteomes, secretion, or cell-cell-induced stimulations. These recent developments suggest that much more information can be gained from proteomic analyses if the labeling strategies are specifically tailored toward the experimental design. © 2017 Elsevier Inc. All rights reserved.

  8. Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics

    PubMed Central

    Lavallée-Adam, Mathieu

    2017-01-01

    PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. PMID:27010334

  9. Comparison of the Membrane Proteome of Virulent Mycobacterium tuberculosis and the Attenuated Mycobacterium bovis BCG Vaccine Strain by Label-free Quantitative Proteomics

    PubMed Central

    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

  10. Comparative quantitative proteomics analysis of the ABA response of roots of drought-sensitive and drought-tolerant wheat varieties identifies proteomic signatures of drought adaptability.

    PubMed

    Alvarez, Sophie; Roy Choudhury, Swarup; Pandey, Sona

    2014-03-07

    Wheat is one of the most highly cultivated cereals in the world. Like other cultivated crops, wheat production is significantly affected by abiotic stresses such as drought. Multiple wheat varieties suitable for different geographical regions of the world have been developed that are adapted to different environmental conditions; however, the molecular basis of such adaptations remains unknown in most cases. We have compared the quantitative proteomics profile of the roots of two different wheat varieties, Nesser (drought-tolerant) and Opata (drought-sensitive), in the absence and presence of abscisic acid (ABA, as a proxy for drought). A labeling LC-based quantitative proteomics approach using iTRAQ was applied to elucidate the changes in protein abundance levels. Quantitative differences in protein levels were analyzed for the evaluation of inherent differences between the two varieties as well as the overall and variety-specific effect of ABA on the root proteome. This study reveals the most elaborate ABA-responsive root proteome identified to date in wheat. A large number of proteins exhibited inherently different expression levels between Nesser and Opata. Additionally, significantly higher numbers of proteins were ABA-responsive in Nesser roots compared with Opata roots. Furthermore, several proteins showed variety-specific regulation by ABA, suggesting their role in drought adaptation.

  11. Targeted proteomics guided by label-free global proteome analysis in saliva reveal transition signatures from health to periodontal disease.

    PubMed

    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

  12. False-positive rate determination of protein target discovery using a covalent modification- and mass spectrometry-based proteomics platform.

    PubMed

    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.

  13. How to talk about protein-level false discovery rates in shotgun proteomics.

    PubMed

    The, Matthew; Tasnim, Ayesha; Käll, Lukas

    2016-09-01

    A frequently sought output from a shotgun proteomics experiment is a list of proteins that we believe to have been present in the analyzed sample before proteolytic digestion. The standard technique to control for errors in such lists is to enforce a preset threshold for the false discovery rate (FDR). Many consider protein-level FDRs a difficult and vague concept, as the measurement entities, spectra, are manifestations of peptides and not proteins. Here, we argue that this confusion is unnecessary and provide a framework on how to think about protein-level FDRs, starting from its basic principle: the null hypothesis. Specifically, we point out that two competing null hypotheses are used concurrently in today's protein inference methods, which has gone unnoticed by many. Using simulations of a shotgun proteomics experiment, we show how confusing one null hypothesis for the other can lead to serious discrepancies in the FDR. Furthermore, we demonstrate how the same simulations can be used to verify FDR estimates of protein inference methods. In particular, we show that, for a simple protein inference method, decoy models can be used to accurately estimate protein-level FDRs for both competing null hypotheses. © 2016 The Authors. Proteomics Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Quantitative proteomic characterization of redox-dependent post-translational modifications on protein cysteines

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

    Duan, Jicheng; Gaffrey, Matthew J.; Qian, Wei-Jun

    Protein cysteine thiols play a crucial role in redox signaling, regulation of enzymatic activity and protein function, and maintaining redox homeostasis in living systems. The unique chemical reactivity of thiol groups makes cysteine susceptible to oxidative modifications by reactive oxygen and nitrogen species to form a broad array of reversible and irreversible protein post-translational modifications (PTMs). The reversible modifications in particular are one of the major components of redox signaling and are involved in regulation of various cellular processes under physiological and pathological conditions. The biological significance of these redox PTMs in health and diseases has been increasingly recognized. Herein,more » we review the recent advances of quantitative proteomic approaches for investigating redox PTMs in complex biological systems, including the general considerations of sample processing, various chemical or affinity enrichment strategies, and quantitative approaches. We also highlight a number of redox proteomic approaches that enable effective profiling of redox PTMs for addressing specific biological questions. Although some technological limitations remain, redox proteomics is paving the way towards a better understanding of redox signaling and regulation in human health and diseases.« less

  15. Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

    PubMed

    Parker, Carol E; Borchers, Christoph H

    2014-06-01

    In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  16. A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells*

    PubMed Central

    Boisvert, François-Michel; Ahmad, Yasmeen; Gierliński, Marek; Charrière, Fabien; Lamont, Douglas; Scott, Michelle; Barton, Geoff; Lamond, Angus I.

    2012-01-01

    Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization, and turnover rates, on a whole proteome level remains a major challenge in the postgenome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labeling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation, and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and stable isotope labeling with amino acids in cell culture, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualized using specialized software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear, and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was ∼20 h. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxyl terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multiprotein complexes, suggesting a general

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

    PubMed

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

    2013-02-01

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

  18. Using PSEA-Quant for Protein Set Enrichment Analysis of Quantitative Mass Spectrometry-Based Proteomics.

    PubMed

    Lavallée-Adam, Mathieu; Yates, John R

    2016-03-24

    PSEA-Quant analyzes quantitative mass spectrometry-based proteomics datasets to identify enrichments of annotations contained in repositories such as the Gene Ontology and Molecular Signature databases. It allows users to identify the annotations that are significantly enriched for reproducibly quantified high abundance proteins. PSEA-Quant is available on the Web and as a command-line tool. It is compatible with all label-free and isotopic labeling-based quantitative proteomics methods. This protocol describes how to use PSEA-Quant and interpret its output. The importance of each parameter as well as troubleshooting approaches are also discussed. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

  19. Quantitative proteomic characterization of the lung extracellular matrix in chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis.

    PubMed

    Åhrman, Emma; Hallgren, Oskar; Malmström, Lars; Hedström, Ulf; Malmström, Anders; Bjermer, Leif; Zhou, Xiao-Hong; Westergren-Thorsson, Gunilla; Malmström, Johan

    2018-03-01

    Remodeling of the extracellular matrix (ECM) is a common feature in lung diseases such as chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). Here, we applied a sequential tissue extraction strategy to describe disease-specific remodeling of human lung tissue in disease, using end-stages of COPD and IPF. Our strategy was based on quantitative comparison of the disease proteomes, with specific focus on the matrisome, using data-independent acquisition and targeted data analysis (SWATH-MS). Our work provides an in-depth proteomic characterization of human lung tissue during impaired tissue remodeling. In addition, we show important quantitative and qualitative effects of the solubility of matrisome proteins. COPD was characterized by a disease-specific increase in ECM regulators, metalloproteinase inhibitor 3 (TIMP3) and matrix metalloproteinase 28 (MMP-28), whereas for IPF, impairment in cell adhesion proteins, such as collagen VI and laminins, was most prominent. For both diseases, we identified increased levels of proteins involved in the regulation of endopeptidase activity, with several proteins belonging to the serpin family. The established human lung quantitative proteome inventory and the construction of a tissue-specific protein assay library provides a resource for future quantitative proteomic analyses of human lung tissues. We present a sequential tissue extraction strategy to determine changes in extractability of matrisome proteins in end-stage COPD and IPF compared to healthy control tissue. Extensive quantitative analysis of the proteome changes of the disease states revealed altered solubility of matrisome proteins involved in ECM regulators and cell-ECM communication. The results highlight disease-specific remodeling mechanisms associated with COPD and IPF. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Analytical performance of reciprocal isotope labeling of proteome digests for quantitative proteomics and its application for comparative studies of aerobic and anaerobic Escherichia coli proteomes.

    PubMed

    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.

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

    PubMed

    Pfammatter, Sibylle; Bonneil, Eric; Thibault, Pierre

    2016-12-02

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

  2. Experimental design and data-analysis in label-free quantitative LC/MS proteomics: A tutorial with MSqRob.

    PubMed

    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.

  3. A tutorial for software development in quantitative proteomics using PSI standard formats☆

    PubMed Central

    Gonzalez-Galarza, Faviel F.; Qi, Da; Fan, Jun; Bessant, Conrad; Jones, Andrew R.

    2014-01-01

    The Human Proteome Organisation — Proteomics Standards Initiative (HUPO-PSI) has been working for ten years on the development of standardised formats that facilitate data sharing and public database deposition. In this article, we review three HUPO-PSI data standards — mzML, mzIdentML and mzQuantML, which can be used to design a complete quantitative analysis pipeline in mass spectrometry (MS)-based proteomics. In this tutorial, we briefly describe the content of each data model, sufficient for bioinformaticians to devise proteomics software. We also provide guidance on the use of recently released application programming interfaces (APIs) developed in Java for each of these standards, which makes it straightforward to read and write files of any size. We have produced a set of example Java classes and a basic graphical user interface to demonstrate how to use the most important parts of the PSI standards, available from http://code.google.com/p/psi-standard-formats-tutorial. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23584085

  4. Quantitative analysis of cellular proteome alterations in human influenza A virus-infected mammalian cell lines.

    PubMed

    Vester, Diana; Rapp, Erdmann; Gade, Dörte; Genzel, Yvonne; Reichl, Udo

    2009-06-01

    Over the last years virus-host cell interactions were investigated in numerous studies. Viral strategies for evasion of innate immune response, inhibition of cellular protein synthesis and permission of viral RNA and protein production were disclosed. With quantitative proteome technology, comprehensive studies concerning the impact of viruses on the cellular machinery of their host cells at protein level are possible. Therefore, 2-D DIGE and nanoHPLC-nanoESI-MS/MS analysis were used to qualitatively and quantitatively determine the dynamic cellular proteome responses of two mammalian cell lines to human influenza A virus infection. A cell line used for vaccine production (MDCK) was compared with a human lung carcinoma cell line (A549) as a reference model. Analyzing 2-D gels of the proteomes of uninfected and influenza-infected host cells, 16 quantitatively altered protein spots (at least +/-1.7-fold change in relative abundance, p<0.001) were identified for both cell lines. Most significant changes were found for keratins, major components of the cytoskeleton system, and for Mx proteins, interferon-induced key components of the host cell defense. Time series analysis of infection processes allowed the identification of further proteins that are described to be involved in protein synthesis, signal transduction and apoptosis events. Most likely, these proteins are required for supporting functions during influenza viral life cycle or host cell stress response. Quantitative proteome-wide profiling of virus infection can provide insights into complexity and dynamics of virus-host cell interactions and may accelerate antiviral research and support optimization of vaccine manufacturing processes.

  5. Quantitative proteomic analysis of human lung tumor xenografts treated with the ectopic ATP synthase inhibitor citreoviridin.

    PubMed

    Wu, Yi-Hsuan; Hu, Chia-Wei; Chien, Chih-Wei; Chen, Yu-Ju; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

    2013-01-01

    ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy.

  6. Quantitative Proteomic Analysis of Human Lung Tumor Xenografts Treated with the Ectopic ATP Synthase Inhibitor Citreoviridin

    PubMed Central

    Wu, Yi-Hsuan; Hu, Chia-Wei; Chien, Chih-Wei; Chen, Yu-Ju; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

    2013-01-01

    ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy. PMID:23990911

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

    PubMed Central

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

    2013-01-01

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

  8. Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

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

    Li, Zhou; Adams, Rachel M; Chourey, Karuna

    2012-01-01

    A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification. Isobaricmore » chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. Based on the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.« less

  9. Quantitative proteome analysis using isobaric peptide termini labeling (IPTL).

    PubMed

    Arntzen, Magnus O; Koehler, Christian J; Treumann, Achim; Thiede, Bernd

    2011-01-01

    The quantitative comparison of proteome level changes across biological samples has become an essential feature in proteomics that remains challenging. We have recently introduced isobaric peptide termini labeling (IPTL), a novel strategy for isobaric quantification based on the derivatization of peptide termini with complementary isotopically labeled reagents. Unlike non-isobaric quantification methods, sample complexity at the MS level is not increased, providing improved sensitivity and protein coverage. The distinguishing feature of IPTL when comparing it to more established isobaric labeling methods (iTRAQ and TMT) is the presence of quantification signatures in all sequence-determining ions in MS/MS spectra, not only in the low mass reporter ion region. This makes IPTL a quantification method that is accessible to mass spectrometers with limited capabilities in the low mass range. Also, the presence of several quantification points in each MS/MS spectrum increases the robustness of the quantification procedure.

  10. A statistical framework for protein quantitation in bottom-up MS-based proteomics

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

    Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas

    2009-08-15

    ABSTRACT Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and confidence measures. Challenges include the presence of low-quality or incorrectly identified peptides and widespread, informative, missing data. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model for protein abundance in terms of peptide peak intensities, applicable to both label-based and label-free quantitation experiments. The model allows for both random and censoring missingness mechanisms and provides naturally for protein-level estimates and confidence measures. The model is also used to derive automated filtering and imputation routines. Three LC-MS datasets are used tomore » illustrate the methods. Availability: The software has been made available in the open-source proteomics platform DAnTE (Polpitiya et al. (2008)) (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu« less

  11. Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.

    PubMed

    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.

  12. Strigolactone-regulated proteins revealed by iTRAQ-based quantitative proteomics in Arabidopsis.

    PubMed

    Li, Zhou; Czarnecki, Olaf; Chourey, Karuna; Yang, Jun; Tuskan, Gerald A; Hurst, Gregory B; Pan, Chongle; Chen, Jin-Gui

    2014-03-07

    Strigolactones (SLs) are a new class of plant hormones. In addition to acting as a key inhibitor of shoot branching, SLs stimulate seed germination of root parasitic plants and promote hyphal branching and root colonization of symbiotic arbuscular mycorrhizal fungi. They also regulate many other aspects of plant growth and development. At the transcription level, SL-regulated genes have been reported. However, nothing is known about the proteome regulated by this new class of plant hormones. A quantitative proteomics approach using an isobaric chemical labeling reagent, iTRAQ, to identify the proteome regulated by SLs in Arabidopsis seedlings is presented. It was found that SLs regulate the expression of about three dozen proteins that have not been previously assigned to SL pathways. These findings provide a new tool to investigate the molecular mechanism of action of SLs.

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

    PubMed

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

    2012-06-20

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

  14. Top-Down Quantitative Proteomics Identified Phosphorylation of Cardiac Troponin I as a Candidate Biomarker for Chronic Heart Failure

    PubMed Central

    Zhang, Jiang; Guy, Moltu J.; Norman, Holly S.; Chen, Yi-Chen; Xu, Qingge; Dong, Xintong; Guner, Huseyin; Wang, Sijian; Kohmoto, Takushi; Young, Ken H.; Moss, Richard L.; Ge, Ying

    2011-01-01

    The rapid increase in the prevalence of chronic heart failure (CHF) worldwide underscores an urgent need to identify biomarkers for the early detection of CHF. Post-translational modifications (PTMs) are associated with many critical signaling events during disease progression and thus offer a plethora of candidate biomarkers. We have employed top-down quantitative proteomics methodology for comprehensive assessment of PTMs in whole proteins extracted from normal and diseased tissues. We have systematically analyzed thirty-six clinical human heart tissue samples and identified phosphorylation of cardiac troponin I (cTnI) as a candidate biomarker for CHF. The relative percentages of the total phosphorylated cTnI forms over the entire cTnI populations (%Ptotal) were 56.4±3.5%, 36.9±1.6%, 6.1±2.4%, and 1.0±0.6% for postmortem hearts with normal cardiac function (n=7), early-stage of mild hypertrophy (n=5), severe hypertrophy/dilation (n=4), and end-stage CHF (n=6), respectively. In fresh transplant samples, the %Ptotal of cTnI from non-failing donor (n=4), and end-stage failing hearts (n=10) were 49.5±5.9% and 18.8±2.9%, respectively. Top-down MS with electron capture dissociation unequivocally localized the altered phosphorylation sites to Ser22/23 and determined the order of phosphorylation/dephosphorylation. This study represents the first clinical application of top-down MS-based quantitative proteomics for biomarker discovery from tissues, highlighting the potential of PTM as disease biomarkers. PMID:21751783

  15. Platelet proteomics: from discovery to diagnosis.

    PubMed

    Looße, Christina; Swieringa, Frauke; Heemskerk, Johan W M; Sickmann, Albert; Lorenz, Christin

    2018-05-22

    Platelets are the smallest cells within the circulating blood with key roles in physiological haemostasis and pathological thrombosis regulated by the onset of activating/inhibiting processes via receptor responses and signalling cascades. Areas covered: Proteomics as well as genomic approaches have been fundamental in identifying and quantifying potential targets for future diagnostic strategies in the prevention of bleeding and thrombosis, and uncovering the complexity of platelet functions in health and disease. In this article, we provide a critical overview on current functional tests used in diagnostics and the future perspectives for platelet proteomics in clinical applications. Expert commentary: Proteomics represents a valuable tool for the identification of patients with diverse platelet associated defects. In-depth validation of identified biomarkers, e.g. receptors, signalling proteins, post-translational modifications, in large cohorts is decisive for translation into routine clinical diagnostics.

  16. Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis*

    PubMed Central

    Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

    2014-01-01

    Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the

  17. Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis.

    PubMed

    Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

    2014-06-01

    Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the

  18. IsobariQ: software for isobaric quantitative proteomics using IPTL, iTRAQ, and TMT.

    PubMed

    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.

  19. AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

    PubMed

    Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

    2011-01-01

    Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method

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

    PubMed

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

    2013-12-16

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

  1. Less is More: Membrane Protein Digestion Beyond Urea-Trypsin Solution for Next-level Proteomics.

    PubMed

    Zhang, Xi

    2015-09-01

    The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea-trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting-not destroying-structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  2. Less is More: Membrane Protein Digestion Beyond Urea–Trypsin Solution for Next-level Proteomics*

    PubMed Central

    Zhang, Xi

    2015-01-01

    The goal of next-level bottom-up membrane proteomics is protein function investigation, via high-coverage high-throughput peptide-centric quantitation of expression, modifications and dynamic structures at systems scale. Yet efficient digestion of mammalian membrane proteins presents a daunting barrier, and prevalent day-long urea–trypsin in-solution digestion proved insufficient to reach this goal. Many efforts contributed incremental advances over past years, but involved protein denaturation that disconnected measurement from functional states. Beyond denaturation, the recent discovery of structure/proteomics omni-compatible detergent n-dodecyl-β-d-maltopyranoside, combined with pepsin and PNGase F columns, enabled breakthroughs in membrane protein digestion: a 2010 DDM-low-TCEP (DLT) method for H/D-exchange (HDX) using human G protein-coupled receptor, and a 2015 flow/detergent-facilitated protease and de-PTM digestions (FDD) for integrative deep sequencing and quantitation using full-length human ion channel complex. Distinguishing protein solubilization from denaturation, protease digestion reliability from theoretical specificity, and reduction from alkylation, these methods shifted day(s)-long paradigms into minutes, and afforded fully automatable (HDX)-protein-peptide-(tandem mass tag)-HPLC pipelines to instantly measure functional proteins at deep coverage, high peptide reproducibility, low artifacts and minimal leakage. Promoting—not destroying—structures and activities harnessed membrane proteins for the next-level streamlined functional proteomics. This review analyzes recent advances in membrane protein digestion methods and highlights critical discoveries for future proteomics. PMID:26081834

  3. Placental Proteomics: A Shortcut to Biological Insight

    PubMed Central

    Robinson, John M.; Vandré, Dale D.; Ackerman, William E.

    2012-01-01

    Proteomics analysis of biological samples has the potential to identify novel protein expression patterns and/or changes in protein expression patterns in different developmental or disease states. An important component of successful proteomics research, at least in its present form, is to reduce the complexity of the sample if it is derived from cells or tissues. One method to simplify complex tissues is to focus on a specific, highly purified sub-proteome. Using this approach we have developed methods to prepare highly enriched fractions of the apical plasma membrane of the syncytiotrophoblast. Through proteomics analysis of this fraction we have identified over five hundred proteins several of which were previously not known to reside in the syncytiotrophoblast. Herein, we focus on two of these, dysferlin and myoferlin. These proteins, largely known from studies of skeletal muscle, may not have been found in the human placenta were it not for discovery-based proteomics analysis. This new knowledge, acquired through a discovery-driven approach, can now be applied for the generation of hypothesis-based experimentation. Thus discovery-based and hypothesis-based research are complimentary approaches that when coupled together can hasten scientific discoveries. PMID:19070895

  4. Characterization of the human aqueous humour proteome: A comparison of the genders.

    PubMed

    Perumal, Natarajan; Manicam, Caroline; Steinicke, Matthias; Funke, Sebastian; Pfeiffer, Norbert; Grus, Franz H

    2017-01-01

    Aqueous humour (AH) is an important biologic fluid that maintains normal intraocular pressure and contains proteins that regulate the homeostasis of ocular tissues. Any alterations in the protein compositions are correlated to the pathogenesis of various ocular disorders. In recent years, gender-based medicine has emerged as an important research focus considering the prevalence of certain diseases, which are higher in a particular sex. Nevertheless, the inter-gender variations in the AH proteome are unknown. Therefore, this study endeavoured to characterize the AH proteome to assess the differences between genders. Thirty AH samples of patients who underwent cataract surgery were categorized according to their gender. Label-free quantitative discovery mass spectrometry-based proteomics strategy was employed to characterize the AH proteome. A total of 147 proteins were identified with a false discovery rate of less than 1% and only the top 10 major AH proteins make up almost 90% of the total identified proteins. A large number of proteins identified were correlated to defence, immune and inflammatory mechanisms, and response to wounding. Four proteins were found to be differentially abundant between the genders, comprising SERPINF1, SERPINA3, SERPING1 and PTGDS. The findings emerging from our study provide the first insight into the gender-based proteome differences in the AH and also highlight the importance in considering potential sex-dependent changes in the proteome of ocular pathologies in future studies employing the AH.

  5. Plasma proteomics for biomarker discovery: a study in blue.

    PubMed

    Di Girolamo, Francesco; Righetti, Pier Giorgio

    2011-12-01

    The performance of Cibacron Blue dye (HiTrapBlue or Affigel Blue) in depleting albumin from plasma, as a pre-treatment for biomarker searching in the low-abundance proteome, is here assessed. It is shown that (i) co-depletion of non-albumin species is an ever-present hazard; (ii) the only proper eluant able to release quantitatively the proteins bound to the dye is boiling 4% SDS-25 mM DTT, an ion shock (2 M NaCl) being quite ineffective in releasing the low-abundance species tightly bound to the dye moiety; (iii) the mechanism of dye-protein interaction, after an initial ion-ion docking, is a robust hydrophobic interaction, which progressively augments at lower and lower pH values; (iv) at pH 2.2 in the presence of 0.1% TFA, the blue resin behaves, for all practical purposes, just as a reverse-phase chromatography column, since all residual proteins present in plasma are completely harvested. However Cibacron Blue technology should not necessarily be discarded: As long as also the plasma fraction adsorbed is properly released and analyzed, together with the flow through, one should be able to perform a viable analysis of the low-abundance proteome. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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

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

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

  7. Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics

    PubMed Central

    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

  8. Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset.

    PubMed

    Metz, Thomas O; Qian, Wei-Jun; Jacobs, Jon M; Gritsenko, Marina A; Moore, Ronald J; Polpitiya, Ashoka D; Monroe, Matthew E; Camp, David G; Mueller, Patricia W; Smith, Richard D

    2008-02-01

    Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

  9. Recent 5-year Findings and Technological Advances in the Proteomic Study of HIV-associated Disorders.

    PubMed

    Zhang, Lijun; Jia, Xiaofang; Jin, Jun-O; Lu, Hongzhou; Tan, Zhimi

    2017-04-01

    Human immunodeficiency virus-1 (HIV-1) mainly relies on host factors to complete its life cycle. Hence, it is very important to identify HIV-regulated host proteins. Proteomics is an excellent technique for this purpose because of its high throughput and sensitivity. In this review, we summarized current technological advances in proteomics, including general isobaric tags for relative and absolute quantitation (iTRAQ) and stable isotope labeling by amino acids in cell culture (SILAC), as well as subcellular proteomics and investigation of posttranslational modifications. Furthermore, we reviewed the applications of proteomics in the discovery of HIV-related diseases and HIV infection mechanisms. Proteins identified by proteomic studies might offer new avenues for the diagnosis and treatment of HIV infection and the related diseases. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

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

    PubMed Central

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

    2015-01-01

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

  11. Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum—Phytophthora capsici Phytopathosystem

    PubMed Central

    Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G.; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

    2016-01-01

    Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset

  12. Transcriptome- Assisted Label-Free Quantitative Proteomics Analysis Reveals Novel Insights into Piper nigrum-Phytophthora capsici Phytopathosystem.

    PubMed

    Mahadevan, Chidambareswaren; Krishnan, Anu; Saraswathy, Gayathri G; Surendran, Arun; Jaleel, Abdul; Sakuntala, Manjula

    2016-01-01

    Black pepper (Piper nigrum L.), a tropical spice crop of global acclaim, is susceptible to Phytophthora capsici, an oomycete pathogen which causes the highly destructive foot rot disease. A systematic understanding of this phytopathosystem has not been possible owing to lack of genome or proteome information. In this study, we explain an integrated transcriptome-assisted label-free quantitative proteomics pipeline to study the basal immune components of black pepper when challenged with P. capsici. We report a global identification of 532 novel leaf proteins from black pepper, of which 518 proteins were functionally annotated using BLAST2GO tool. A label-free quantitation of the protein datasets revealed 194 proteins common to diseased and control protein datasets of which 22 proteins showed significant up-regulation and 134 showed significant down-regulation. Ninety-three proteins were identified exclusively on P. capsici infected leaf tissues and 245 were expressed only in mock (control) infected samples. In-depth analysis of our data gives novel insights into the regulatory pathways of black pepper which are compromised during the infection. Differential down-regulation was observed in a number of critical pathways like carbon fixation in photosynthetic organism, cyano-amino acid metabolism, fructose, and mannose metabolism, glutathione metabolism, and phenylpropanoid biosynthesis. The proteomics results were validated with real-time qRT-PCR analysis. We were also able to identify the complete coding sequences for all the proteins of which few selected genes were cloned and sequence characterized for further confirmation. Our study is the first report of a quantitative proteomics dataset in black pepper which provides convincing evidence on the effectiveness of a transcriptome-based label-free proteomics approach for elucidating the host response to biotic stress in a non-model spice crop like P. nigrum, for which genome information is unavailable. Our dataset

  13. Synovial fluid proteomics in the pursuit of arthritis mediators: An evolving field of novel biomarker discovery.

    PubMed

    Mahendran, Shalini M; Oikonomopoulou, Katerina; Diamandis, Eleftherios P; Chandran, Vinod

    Synovial fluid (SF) is a protein-rich fluid produced into the joint cavity by cells of the synovial membrane. Due to its direct contact with articular cartilage, surfaces of the bone, and the synoviocytes of the inner membrane, it provides a promising reflection of the biochemical state of the joint under varying physiological and pathophysiological conditions. This property of SF has been exploited within numerous studies in search of unique biomarkers of joint pathologies with the ultimate goal of developing minimally invasive clinical assays to detect and/or monitor disease states. Several proteomic methodologies have been employed to mine the SF proteome. From elementary immunoassays to high-throughput analyses using mass spectrometry-based techniques, each has demonstrated distinct advantages and disadvantages in the identification and quantification of SF proteins. This review will explore the role of SF in the elucidation of the arthritis proteome and the extent to which high-throughput techniques have facilitated the discovery and validation of protein biomarkers from osteoarthritis (OA), rheumatoid arthritis (RA), psoriatic arthritis (PsA), and juvenile idiopathic arthritis (JIA) patients.

  14. The proteomic landscape of triple-negative breast cancer.

    PubMed

    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.

  15. How to talk about protein‐level false discovery rates in shotgun proteomics

    PubMed Central

    The, Matthew; Tasnim, Ayesha

    2016-01-01

    A frequently sought output from a shotgun proteomics experiment is a list of proteins that we believe to have been present in the analyzed sample before proteolytic digestion. The standard technique to control for errors in such lists is to enforce a preset threshold for the false discovery rate (FDR). Many consider protein‐level FDRs a difficult and vague concept, as the measurement entities, spectra, are manifestations of peptides and not proteins. Here, we argue that this confusion is unnecessary and provide a framework on how to think about protein‐level FDRs, starting from its basic principle: the null hypothesis. Specifically, we point out that two competing null hypotheses are used concurrently in today's protein inference methods, which has gone unnoticed by many. Using simulations of a shotgun proteomics experiment, we show how confusing one null hypothesis for the other can lead to serious discrepancies in the FDR. Furthermore, we demonstrate how the same simulations can be used to verify FDR estimates of protein inference methods. In particular, we show that, for a simple protein inference method, decoy models can be used to accurately estimate protein‐level FDRs for both competing null hypotheses. PMID:27503675

  16. Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

    PubMed Central

    Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

    2011-01-01

    The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID

  17. The quantitative and condition-dependent Escherichia coli proteome

    PubMed Central

    Schmidt, Alexander; Kochanowski, Karl; Vedelaar, Silke; Ahrné, Erik; Volkmer, Benjamin; Callipo, Luciano; Knoops, Kèvin; Bauer, Manuel; Aebersold, Ruedi; Heinemann, Matthias

    2016-01-01

    Measuring precise concentrations of proteins can provide insights into biological processes. Here, we use efficient protein extraction and sample fractionation and state-of-the-art quantitative mass spectrometry techniques to generate a comprehensive, condition-dependent protein abundance map of Escherichia coli. We measure cellular protein concentrations for 55% of predicted E. coli genes (>2300 proteins) under 22 different experimental conditions and identify methylation and N-terminal protein acetylations previously not known to be prevalent in bacteria. We uncover system-wide proteome allocation, expression regulation, and post-translational adaptations. These data provide a valuable resource for the systems biology and broader E. coli research communities. PMID:26641532

  18. Mining the human urine proteome for monitoring renal transplant injury

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

    Sigdel, Tara K.; Gao, Yuqian; He, Jintang

    The human urinary proteome reflects systemic and inherent renal injury perturbations and can be analyzed to harness specific biomarkers for different kidney transplant injury states. 396 unique urine samples were collected contemporaneously with an allograft biopsy from 396 unique kidney transplant recipients. Centralized, blinded histology on the graft was used to classify matched urine samples into categories of acute rejection (AR), chronic allograft nephropathy (CAN), BK virus nephritis (BKVN), and stable graft (STA). Liquid chromatography–mass spectrometry (LC-MS) based proteomics using iTRAQ based discovery (n=108) and global label-free LC-MS analyses of individual samples (n=137) for quantitative proteome assessment were used inmore » the discovery step. Selected reaction monitoring (SRM) was applied to identify and validate minimal urine protein/peptide biomarkers to accurately segregate organ injury causation and pathology on unique urine samples (n=151). A total of 958 proteins were initially quantified by iTRAQ, 87% of which were also identified among 1574 urine proteins detected in LC-MS validation. 103 urine proteins were significantly (p<0.05) perturbed in injury and enriched for humoral immunity, complement activation, and lymphocyte trafficking. A set of 131 peptides corresponding to 78 proteins were assessed by SRM for their significance in an independent sample cohort. A minimal set of 35 peptides mapping to 33 proteins, were modeled to segregate different injury groups (AUC =93% for AR, 99% for CAN, 83% for BKVN). Urinary proteome discovery and targeted validation identified urine protein fingerprints for non-invasive differentiation of kidney transplant injuries, thus opening the door for personalized immune risk assessment and therapy.« less

  19. Proteomic and transcriptional analysis of Lactobacillus johnsonii PF01 during bile salt exposure by iTRAQ shotgun proteomics and quantitative RT-PCR.

    PubMed

    Lee, Ji Yoon; Pajarillo, Edward Alain B; Kim, Min Jeong; Chae, Jong Pyo; Kang, Dae-Kyung

    2013-01-04

    Lactobacillus johnsonii PF01 has been reported to be highly resistant to bile, a key property of probiotic microorganisms. Here, we examine the nature of the bile-salt tolerance of L. johnsonii PF01. Growth inhibition and surface morphology and physiology aberrations were observed after overnight exposure to bile stress. Quantitative proteomic profiles using iTRAQ-LC-MS/MS technology identified 8307 peptides from both untreated PF01 cells and those exposed to 0.1%, 0.2%, and 0.3% bile salts. Some 215 proteins exhibited changed levels in response to bile stress; of these, levels of 94 peptides increased while those of 121 decreased. These were classified into the following categories: stress responses, cell division, transcription, translation, nucleotide metabolism, carbohydrate transport and metabolism, cell wall biosynthesis, and amino acid biosynthesis, and 16 of unidentified function. Analysis of the mRNA expression of selected genes by quantitative reverse transcriptase-PCR verified the proteomic data. Both proteomic and mRNA data provided evidence for increased phosphotransferase activity and cell wall biosynthesis. In addition, three bile salt hydrolases were significantly upregulated by bile exposure. These findings provide a basis for future evaluations of the tolerance of potential probiotic strains toward the various gastrointestinal challenges, including bile stress.

  20. How molecular profiling could revolutionize drug discovery.

    PubMed

    Stoughton, Roland B; Friend, Stephen H

    2005-04-01

    Information from genomic, proteomic and metabolomic measurements has already benefited target discovery and validation, assessment of efficacy and toxicity of compounds, identification of disease subgroups and the prediction of responses of individual patients. Greater benefits can be expected from the application of these technologies on a significantly larger scale; by simultaneously collecting diverse measurements from the same subjects or cell cultures; by exploiting the steadily improving quantitative accuracy of the technologies; and by interpreting the emerging data in the context of underlying biological models of increasing sophistication. The benefits of applying molecular profiling to drug discovery and development will include much lower failure rates at all stages of the drug development pipeline, faster progression from discovery through to clinical trials and more successful therapies for patient subgroups. Upheavals in existing organizational structures in the current 'conveyor belt' models of drug discovery might be required to take full advantage of these methods.

  1. Quantitative Proteomic Analysis of Mouse Embryonic Fibroblasts and Induced Pluripotent Stem Cells Using 16O /18O labeling

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

    Huang, Xin; Tian, Changhai; Liu, Miao

    2012-04-06

    Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC. This platform consists of 16O/18O labeling, multidimensional peptide separation coupled with tandem mass spectrometry, and data analysis with UNiquant software. Using thismore » platform a total of 2,481 proteins were identified and quantified from the 16O/18O-labeled MEF-iPSC proteome mixtures with a false discovery rate of 0.01. Among them, 218 proteins were significantly upregulated, while 247 proteins were significantly downregulated in iPSC compared to MEF. Many nuclear proteins, including Hdac1, Dnmt1, Pcna, Ccnd1, Smarcc1, and subunits in DNA replication and RNA polymerase II complex were found to be enhanced in iPSC. Protein network analysis revealed that Pcna functions as a hub orchestrating complicated mechanisms including DNA replication, epigenetic inheritance (Dnmt1) and chromatin remodeling (Smarcc1) to reprogram MEF and maintain stemness of iPSC.« less

  2. Final Report: Proteomic study of brassinosteroid responses in Arabidopsis

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

    Wang, Zhiyong; Burlingame, Alma

    2017-11-29

    The steroid hormone brassinosteroid (BR) is a major growth-promoting phytohormone. The specific aim of the current project is to identify BR-regulated proteins and characterize their functions in various aspects of plant growth, development, and adaptation. Our research has significantly advanced our understanding of how BR signal is transduced from the receptor at the cell surface to changes of nuclear gene expression and other cellular responses such as vesicle trafficking, as well as developmental transitions such as seed germination and flowering. We have also developed effective proteomic methods for quantitative analysis of protein phosphorylation and for identification of glycosylated proteins. Throughmore » this DOE funding, we have performed several proteomic experiments and made major discoveries.« less

  3. Proteome-wide Light/Dark Modulation of Thiol Oxidation in Cyanobacteria Revealed by Quantitative Site-specific Redox Proteomics*

    PubMed Central

    Guo, Jia; Nguyen, Amelia Y.; Dai, Ziyu; Su, Dian; Gaffrey, Matthew J.; Moore, Ronald J.; Jacobs, Jon M.; Monroe, Matthew E.; Smith, Richard D.; Koppenaal, David W.; Pakrasi, Himadri B.; Qian, Wei-Jun

    2014-01-01

    Reversible protein thiol oxidation is an essential regulatory mechanism of photosynthesis, metabolism, and gene expression in photosynthetic organisms. Herein, we present proteome-wide quantitative and site-specific profiling of in vivo thiol oxidation modulated by light/dark in the cyanobacterium Synechocystis sp. PCC 6803, an oxygenic photosynthetic prokaryote, using a resin-assisted thiol enrichment approach. Our proteomic approach integrates resin-assisted enrichment with isobaric tandem mass tag labeling to enable site-specific and quantitative measurements of reversibly oxidized thiols. The redox dynamics of ∼2,100 Cys-sites from 1,060 proteins under light, dark, and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (a photosystem II inhibitor) conditions were quantified. In addition to relative quantification, the stoichiometry or percentage of oxidation (reversibly oxidized/total thiols) for ∼1,350 Cys-sites was also quantified. The overall results revealed broad changes in thiol oxidation in many key biological processes, including photosynthetic electron transport, carbon fixation, and glycolysis. Moreover, the redox sensitivity along with the stoichiometric data enabled prediction of potential functional Cys-sites for proteins of interest. The functional significance of redox-sensitive Cys-sites in NADP-dependent glyceraldehyde-3-phosphate dehydrogenase, peroxiredoxin (AhpC/TSA family protein Sll1621), and glucose 6-phosphate dehydrogenase was further confirmed with site-specific mutagenesis and biochemical studies. Together, our findings provide significant insights into the broad redox regulation of photosynthetic organisms. PMID:25118246

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

    PubMed

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

    2016-12-16

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

  5. PeptideDepot: flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information.

    PubMed

    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.

  6. Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program (DASP) sample subset

    PubMed Central

    Metz, Thomas O.; Qian, Wei-Jun; Jacobs, Jon M.; Gritsenko, Marina A.; Moore, Ronald J.; Polpitiya, Ashoka D.; Monroe, Matthew E.; Camp, David G.; Mueller, Patricia W.; Smith, Richard D.

    2009-01-01

    Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted “-omics” approaches are under-utilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. Alpha-2-glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples. PMID:18092746

  7. System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

    PubMed

    Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

    2017-02-03

    Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

  8. A Proteomic Analysis of Eccrine Sweat: Implications for the Discovery of Schizophrenia Biomarker Proteins

    PubMed Central

    Raiszadeh, Michelle M.; Ross, Mark M.; Russo, Paul S.; Schaepper, Mary Ann H.; Zhou, Weidong; Deng, Jianghong; Ng, Daniel; Dickson, April; Dickson, Cindy; Strom, Monica; Osorio, Carolina; Soeprono, Thomas; Wulfkuhle, Julia D.; Kabbani, Nadine; Petricoin, Emanuel F.; Liotta, Lance A.; Kirsch, Wolff M.

    2012-01-01

    Liquid chromatography tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate, and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately two-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers. PMID:22256890

  9. Mass spectrometry-based targeted quantitative proteomics: achieving sensitive and reproducible detection of proteins.

    PubMed

    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.

  10. Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

    PubMed Central

    Orton, Dennis J.; Doucette, Alan A.

    2013-01-01

    Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

  11. Quantitative Analysis of Global Proteome and Lysine Acetylome Reveal the Differential Impacts of VPA and SAHA on HL60 Cells.

    PubMed

    Zhu, Xiaoyu; Liu, Xin; Cheng, Zhongyi; Zhu, Jun; Xu, Lei; Wang, Fengsong; Qi, Wulin; Yan, Jiawei; Liu, Ning; Sun, Zimin; Liu, Huilan; Peng, Xiaojun; Hao, Yingchan; Zheng, Nan; Wu, Quan

    2016-01-29

    Valproic acid (VPA) and suberoylanilide hydroxamic acid (SAHA) are both HDAC inhibitors (HDACi). Previous studies indicated that both inhibitors show therapeutic effects on acute myeloid leukaemia (AML), while the differential impacts of the two different HDACi on AML treatment still remains elusive. In this study, using 3-plex SILAC based quantitative proteomics technique, anti-acetyllysine antibody based affinity enrichment, high resolution LC-MS/MS and intensive bioinformatic analysis, the quantitative proteome and acetylome in SAHA and VPA treated AML HL60 cells were extensively studied. In total, 5,775 proteins and 1,124 lysine acetylation sites were successfully obtained in response to VAP and SAHA treatment. It is found that VPA and SAHA treatment differently induced proteome and acetylome profiling in AML HL60 cells. This study revealed the differential impacts of VPA and SAHA on proteome/acetylome in AML cells, deepening our understanding of HDAC inhibitor mediated AML therapeutics.

  12. Quantitative estimation of pesticide-likeness for agrochemical discovery.

    PubMed

    Avram, Sorin; Funar-Timofei, Simona; Borota, Ana; Chennamaneni, Sridhar Rao; Manchala, Anil Kumar; Muresan, Sorel

    2014-12-01

    The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. The aim of this study is to develop quantitative estimates of herbicide- (QEH), insecticide- (QEI), fungicide- (QEF), and, finally, pesticide-likeness (QEP). In the assessment of these definitions, we relied on the concept of desirability functions. We found a simple function, shared by the three classes of pesticides, parameterized particularly, for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings. Subsequently, we describe the scoring of each pesticide class by the corresponding quantitative estimate. In a comparative study, we assessed the performance of the scoring functions using extensive datasets of patented pesticides. The hereby-established quantitative assessment has the ability to rank compounds whether they fail well-established pesticide-likeness rules or not, and offer an efficient way to prioritize (class-specific) pesticides. These findings are valuable for the efficient estimation of pesticide-likeness of vast chemical libraries in the field of agrochemical discovery. Graphical AbstractQuantitative models for pesticide-likeness were derived using the concept of desirability functions parameterized for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings.

  13. Quantitative Proteomics of the Infectious and Replicative Forms of Chlamydia trachomatis

    PubMed Central

    Skipp, Paul J. S.; Hughes, Chris; McKenna, Thérèse; Edwards, Richard; Langridge, James; Thomson, Nicholas R.; Clarke, Ian N.

    2016-01-01

    The obligate intracellular developmental cycle of Chlamydia trachomatis presents significant challenges in defining its proteome. In this study we have applied quantitative proteomics to both the intracellular reticulate body (RB) and the extracellular elementary body (EB) from C. trachomatis. We used C. trachomatis L2 as a model chlamydial isolate for our study since it has a high infectivity:particle ratio and there is an excellent quality genome sequence. EBs and RBs (>99% pure) were quantified by chromosomal and plasmid copy number using PCR, from which the concentrations of chlamydial proteins per bacterial cell/genome were determined. RBs harvested at 15h post infection (PI) were purified by three successive rounds of gradient centrifugation. This is the earliest possible time to obtain purified RBs, free from host cell components in quantity, within the constraints of the technology. EBs were purified at 48h PI. We then used two-dimensional reverse phase UPLC to fractionate RB or EB peptides before mass spectroscopic analysis, providing absolute amount estimates of chlamydial proteins. The ability to express the data as molecules per cell gave ranking in both abundance and energy requirements for synthesis, allowing meaningful identification of rate-limiting components. The study assigned 562 proteins with high confidence and provided absolute estimates of protein concentration for 489 proteins. Interestingly, the data showed an increase in TTS capacity at 15h PI. Most of the enzymes involved in peptidoglycan biosynthesis were detected along with high levels of muramidase (in EBs) suggesting breakdown of peptidoglycan occurs in the non-dividing form of the microorganism. All the genome-encoded enzymes for glycolysis, pentose phosphate pathway and tricarboxylic acid cycle were identified and quantified; these data supported the observation that the EB is metabolically active. The availability of detailed, accurate quantitative proteomic data will be

  14. Quantitative Proteomics Analysis of Inborn Errors of Cholesterol Synthesis

    PubMed Central

    Jiang, Xiao-Sheng; Backlund, Peter S.; Wassif, Christopher A.; Yergey, Alfred L.; Porter, Forbes D.

    2010-01-01

    Smith-Lemli-Opitz syndrome (SLOS) and lathosterolosis are malformation syndromes with cognitive deficits caused by mutations of 7-dehydrocholesterol reductase (DHCR7) and lathosterol 5-desaturase (SC5D), respectively. DHCR7 encodes the last enzyme in the Kandutsch-Russel cholesterol biosynthetic pathway, and impaired DHCR7 activity leads to a deficiency of cholesterol and an accumulation of 7-dehydrocholesterol. SC5D catalyzes the synthesis of 7-dehydrocholesterol from lathosterol. Impaired SC5D activity leads to a similar deficiency of cholesterol but an accumulation of lathosterol. Although the genetic and biochemical causes underlying both syndromes are known, the pathophysiological processes leading to the developmental defects remain unclear. To study the pathophysiological mechanisms underlying SLOS and lathosterolosis neurological symptoms, we performed quantitative proteomics analysis of SLOS and lathosterolosis mouse brain tissue and identified multiple biological pathways affected in Dhcr7Δ3–5/Δ3–5 and Sc5d−/− E18.5 embryos. These include alterations in mevalonate metabolism, apoptosis, glycolysis, oxidative stress, protein biosynthesis, intracellular trafficking, and cytoskeleton. Comparison of proteome alterations in both Dhcr7Δ3–5/Δ3–5 and Sc5d−/− brain tissues helps elucidate whether perturbed protein expression was due to decreased cholesterol or a toxic effect of sterol precursors. Validation of the proteomics results confirmed increased expression of isoprenoid and cholesterol synthetic enzymes. This alteration of isoprenoid synthesis may underlie the altered posttranslational modification of Rab7, a small GTPase that is functionally dependent on prenylation with geranylgeranyl, that we identified and validated in this study. These data suggested that although cholesterol synthesis is impaired in both Dhcr7Δ3–5/Δ3–5 and Sc5d−/− embryonic brain tissues the synthesis of nonsterol isoprenoids may be increased and thus

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

    PubMed

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

    2015-09-01

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

  16. Quantitative Proteomics of Sleep-Deprived Mouse Brains Reveals Global Changes in Mitochondrial Proteins

    PubMed Central

    Li, Tie-Mei; Zhang, Ju-en; Lin, Rui; Chen, She; Luo, Minmin; Dong, Meng-Qiu

    2016-01-01

    Sleep is a ubiquitous, tightly regulated, and evolutionarily conserved behavior observed in almost all animals. Prolonged sleep deprivation can be fatal, indicating that sleep is a physiological necessity. However, little is known about its core function. To gain insight into this mystery, we used advanced quantitative proteomics technology to survey the global changes in brain protein abundance. Aiming to gain a comprehensive profile, our proteomics workflow included filter-aided sample preparation (FASP), which increased the coverage of membrane proteins; tandem mass tag (TMT) labeling, for relative quantitation; and high resolution, high mass accuracy, high throughput mass spectrometry (MS). In total, we obtained the relative abundance ratios of 9888 proteins encoded by 6070 genes. Interestingly, we observed significant enrichment for mitochondrial proteins among the differentially expressed proteins. This finding suggests that sleep deprivation strongly affects signaling pathways that govern either energy metabolism or responses to mitochondrial stress. Additionally, the differentially-expressed proteins are enriched in pathways implicated in age-dependent neurodegenerative diseases, including Parkinson’s, Huntington’s, and Alzheimer’s, hinting at possible connections between sleep loss, mitochondrial stress, and neurodegeneration. PMID:27684481

  17. Quantitative Proteomics Identifies Activation of Hallmark Pathways of Cancer in Patient Melanoma.

    PubMed

    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.

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

    PubMed Central

    Yu, Kebing; Salomon, Arthur R.

    2010-01-01

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

  19. Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

    PubMed

    Magdalinou, N K; Noyce, A J; Pinto, R; Lindstrom, E; Holmén-Larsson, J; Holtta, M; Blennow, K; Morris, H R; Skillbäck, T; Warner, T T; Lees, A J; Pike, I; Ward, M; Zetterberg, H; Gobom, J

    2017-04-01

    Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as

  20. A multiplexed quantitative proteomics approach for investigating protein expression in the developing central nervous system.

    PubMed

    Orme, Rowan P; Gates, Monte A; Fricker-Gates, Rosemary A

    2010-08-15

    Cell transplantation using stem cell-derived neurons is commonly viewed as a candidate therapy for neurodegenerative diseases. However, methods for differentiating stem cells into homogenous populations of neurons suitable for transplant remain elusive. This suggests that there are as yet unknown signalling factors working in vivo to specify neuronal cell fate during development. These factors could be manipulated to better differentiate stem cells into neural populations useful for therapeutic transplantation. Here a quantitative proteomics approach is described for investigating cell signalling in the developing central nervous system (CNS), using the embryonic ventral mesencephalon as a model. Briefly, total protein was extracted from embryonic ventral midbrain tissue before, during and after the birth of dopaminergic neurons, and digested using trypsin. Two-dimensional liquid chromatography, coupled with tandem mass spectrometry, was then used to identify proteins from the tryptic peptides. Isobaric tagging for relative and absolute quantification (iTRAQ) reagents were used to label the tryptic peptides and facilitate relative quantitative analysis. The success of the experiment was confirmed by the identification of proteins known to be expressed in the developing ventral midbrain, as well as by Western blotting, and immunolabelling of embryonic tissue sections. This method of protein discovery improves upon previous attempts to identify novel signalling factors through microarray analysis. Importantly, the methods described here could be applied to virtually any aspect of development. (c) 2010 Elsevier B.V. All rights reserved.

  1. Quantitative mass spectrometry of human reticulocytes reveal proteome-wide modifications during maturation.

    PubMed

    Chu, Trang T T; Sinha, Ameya; Malleret, Benoit; Suwanarusk, Rossarin; Park, Jung E; Naidu, Renugah; Das, Rupambika; Dutta, Bamaprasad; Ong, Seow Theng; Verma, Navin K; Chan, Jerry K; Nosten, François; Rénia, Laurent; Sze, Siu K; Russell, Bruce; Chandramohanadas, Rajesh

    2018-01-01

    Erythropoiesis is marked by progressive changes in morphological, biochemical and mechanical properties of erythroid precursors to generate red blood cells (RBC). The earliest enucleated forms derived in this process, known as reticulocytes, are multi-lobular and spherical. As reticulocytes mature, they undergo a series of dynamic cytoskeletal re-arrangements and the expulsion of residual organelles, resulting in highly deformable biconcave RBCs (normocytes). To understand the significant, yet neglected proteome-wide changes associated with reticulocyte maturation, we undertook a quantitative proteomics approach. Immature reticulocytes (marked by the presence of surface transferrin receptor, CD71) and mature RBCs (devoid of CD71) were isolated from human cord blood using a magnetic separation procedure. After sub-fractionation into triton-extracted membrane proteins and luminal samples (isobaric tags for relative and absolute quantitation), quantitative mass spectrometry was conducted to identify more than 1800 proteins with good confidence and coverage. While most structural proteins (such as Spectrins, Ankyrin and Band 3) as well as surface glycoproteins were conserved, proteins associated with microtubule structures, such as Talin-1/2 and ß-Tubulin, were detected only in immature reticulocytes. Atomic force microscopy (AFM)-based imaging revealed an extended network of spectrin filaments in reticulocytes (with an average length of 48 nm), which shortened during reticulocyte maturation (average spectrin length of 41 nm in normocytes). The extended nature of cytoskeletal network may partly account for increased deformability and shape changes, as reticulocytes transform to normocytes. © 2017 John Wiley & Sons Ltd.

  2. Quantitative proteomics reveals the central changes of wheat in response to powdery mildew.

    PubMed

    Fu, Ying; Zhang, Hong; Mandal, Siddikun Nabi; Wang, Changyou; Chen, Chunhuan; Ji, Wanquan

    2016-01-01

    Powdery mildew (Pm), caused by Blumeria graminis f. sp. tritici (Bgt), is one of the most important crop diseases, causing severe economic losses to wheat production worldwide. However, there are few reports about the proteomic response to Bgt infection in resistant wheat. Hence, quantitative proteomic analysis of N9134, a resistant wheat line, was performed to explore the molecular mechanism of wheat in defense against Bgt. Comparing the leaf proteins of Bgt-inoculated N9134 with that of mock-inoculated controls, a total of 2182 protein-species were quantified by iTRAQ at 24, 48 and 72h postinoculation (hpi) with Bgt, of which 394 showed differential accumulation. These differentially accumulated protein-species (DAPs) mainly included pathogenesis-related (PR) polypeptides, oxidative stress responsive proteins and components involved in primary metabolic pathways. KEGG enrichment analysis showed that phenylpropanoid biosynthesis, phenylalanine metabolism and photosynthesis-antenna proteins were the key pathways in response to Bgt infection. InterProScan 5 and the Gibbs Motif Sampler cluster 394 DAPs into eight conserved motifs, which shared leucine repeats and histidine sites in the sequence motifs. Moreover, eight separate protein-protein interaction (PPI) networks were predicted from STRING database. This study provides a powerful platform for further exploration of the molecular mechanism underlying resistant wheat responding to Bgt. Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive pathogenic disease in wheat-producing regions worldwide, resulting in severe yield reductions. Although many resistant wheat varieties have been cultivated, there are few reports about the proteomic response to Bgt infection in resistant wheat. Therefore, an iTRAQ-based quantitative proteomic analysis of a resistant wheat line (N9134) in response to Bgt infection has been performed. This paper provides new insights into the underlying molecular

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

    PubMed

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

    2012-05-01

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

  4. Quantitative and temporal proteome analysis of butyrate-treated colorectal cancer cells.

    PubMed

    Tan, Hwee Tong; Tan, Sandra; Lin, Qingsong; Lim, Teck Kwang; Hew, Choy Leong; Chung, Maxey C M

    2008-06-01

    Colorectal cancer is one of the most common cancers in developed countries, and its incidence is negatively associated with high dietary fiber intake. Butyrate, a short-chain fatty acid fermentation by-product of fiber induces cell maturation with the promotion of growth arrest, differentiation, and/or apoptosis of cancer cells. The stimulation of cell maturation by butyrate in colonic cancer cells follows a temporal progression from the early phase of growth arrest to the activation of apoptotic cascades. Previously we performed two-dimensional DIGE to identify differentially expressed proteins induced by 24-h butyrate treatment of HCT-116 colorectal cancer cells. Herein we used quantitative proteomics approaches using iTRAQ (isobaric tags for relative and absolute quantitation), a stable isotope labeling methodology that enables multiplexing of four samples, for a temporal study of HCT-116 cells treated with butyrate. In addition, cleavable ICAT, which selectively tags cysteine-containing proteins, was also used, and the results complemented those obtained from the iTRAQ strategy. Selected protein targets were validated by real time PCR and Western blotting. A model is proposed to illustrate our findings from this temporal analysis of the butyrate-responsive proteome that uncovered several integrated cellular processes and pathways involved in growth arrest, apoptosis, and metastasis. These signature clusters of butyrate-regulated pathways are potential targets for novel chemopreventive and therapeutic drugs for treatment of colorectal cancer.

  5. Quantitation of peptides from non-invasive skin tapings using isotope dilution and tandem mass spectrometry.

    PubMed

    Reisdorph, Nichole; Armstrong, Michael; Powell, Roger; Quinn, Kevin; Legg, Kevin; Leung, Donald; Reisdorph, Rick

    2018-05-01

    Previous work from our laboratories utilized a novel skin taping method and mass spectrometry-based proteomics to discover clinical biomarkers of skin conditions; these included atopic dermatitis, Staphylococcus aureus colonization, and eczema herpeticum. While suitable for discovery purposes, semi-quantitative proteomics is generally time-consuming and expensive. Furthermore, depending on the method used, discovery-based proteomics can result in high variation and inadequate sensitivity to detect low abundant peptides. Therefore, we strove to develop a rapid, sensitive, and reproducible method to quantitate disease-related proteins from skin tapings. We utilized isotopically-labeled peptides and tandem mass spectrometry to obtain absolute quantitation values on 14 peptides from 7 proteins; these proteins had shown previous importance in skin disease. The method demonstrated good reproducibility, dynamic range, and linearity (R 2  > 0.993) when n = 3 standards were analyzed across 0.05-2.5 pmol. The method was used to determine if differences exist between skin proteins in a small group of atopic versus non-atopic individuals (n = 12). While only minimal differences were found, peptides were detected in all samples and exhibited good correlation between peptides for 5 of the 7 proteins (R 2  = 0.71-0.98). This method can be applied to larger cohorts to further establish the relationships of these proteins to skin disease. Copyright © 2017. Published by Elsevier B.V.

  6. CPTAC Accelerates Precision Proteomics Biomedical Research | Office of Cancer Clinical Proteomics Research

    Cancer.gov

    The accurate quantitation of proteins or peptides using Mass Spectrometry (MS) is gaining prominence in the biomedical research community as an alternative method for analyte measurement. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigators have been at the forefront in the promotion of reproducible MS techniques, through the development and application of standardized proteomic methods for protein quantitation on biologically relevant samples.

  7. Differential quantitative proteomics of Porphyromonas gingivalis by linear ion trap mass spectrometry: non-label methods comparison, q-values and LOWESS curve fitting

    PubMed Central

    Xia, Qiangwei; Wang, Tiansong; Park, Yoonsuk; Lamont, Richard J.; Hackett, Murray

    2009-01-01

    Differential analysis of whole cell proteomes by mass spectrometry has largely been applied using various forms of stable isotope labeling. While metabolic stable isotope labeling has been the method of choice, it is often not possible to apply such an approach. Four different label free ways of calculating expression ratios in a classic “two-state” experiment are compared: signal intensity at the peptide level, signal intensity at the protein level, spectral counting at the peptide level, and spectral counting at the protein level. The quantitative data were mined from a dataset of 1245 qualitatively identified proteins, about 56% of the protein encoding open reading frames from Porphyromonas gingivalis, a Gram-negative intracellular pathogen being studied under extracellular and intracellular conditions. Two different control populations were compared against P. gingivalis internalized within a model human target cell line. The q-value statistic, a measure of false discovery rate previously applied to transcription microarrays, was applied to proteomics data. For spectral counting, the most logically consistent estimate of random error came from applying the locally weighted scatter plot smoothing procedure (LOWESS) to the most extreme ratios generated from a control technical replicate, thus setting upper and lower bounds for the region of experimentally observed random error. PMID:19337574

  8. PANDA-view: An easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.

    PubMed

    Chang, Cheng; Xu, Kaikun; Guo, Chaoping; Wang, Jinxia; Yan, Qi; Zhang, Jian; He, Fuchu; Zhu, Yunping

    2018-05-22

    Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. 1987ccpacer@163.com and zhuyunping@gmail.com. Supplementary data are available at Bioinformatics online.

  9. A Targeted MRM Approach for Tempo-Spatial Proteomics Analyses.

    PubMed

    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.

  10. Comparative analysis of Staphylococcus epidermidis strains utilizing quantitative and cell surface shaving proteomics.

    PubMed

    Solis, Nestor; Cain, Joel A; Cordwell, Stuart J

    2016-01-01

    Staphylococcus epidermidis is an opportunistic pathogen that is an emerging risk factor in hospitals worldwide and is often difficult to eradicate as virulent strains produce a protective biofilm matrix. We utilized cell shaving proteomics to profile surface-exposed proteins from two fully genome sequenced S. epidermidis strains: the avirulent, non-biofilm forming ATCC12228 and the virulent, strongly adherent biofilm forming ATCC35984 (RP62A). A false positive control strategy was employed to calculate the probabilities of proteins being truly surface-exposed. A total of 78 surface-exposed proteins were identified, of which only 19 proteins were common to ATCC12228 and RP62A, and which thus represents the core surfaceome. S. epidermidis RP62A displayed additional proteins involved in biofilm formation (cell wall-associated Bhp and intercellular adhesion protein IcaB), surface antigenicity, peptidoglycan biosynthesis and antibiotic resistance. We concurrently profiled whole cell proteomes of the two strains using iTRAQ quantitation and LC-MS/MS. A total of 1610 proteins were confidently identified (representing 64% of the theoretical S. epidermidis proteome). One hundred and ninety one proteins were differentially abundant between strains. Proteins associated with RP62A were clustered into functions including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-mediated defense, sulfate assimilation, antibiotic resistance and biofilm formation. Validation of the sulfate assimilation and cysteine/methionine biosynthesis pathways showed RP62A contained elevated levels (~25% increase) of methionine that are likely linked to biofilm formation. Cell shaving and quantitative proteomics identified proteins associated with a biofilm-forming, virulent strain of S. epidermidis (RP62A). These proteins show RP62A maintains an active CRISPR-mediated defense, as well as heightened antibiotic resistance in comparison to a non-virulent, non-biofilm forming strain

  11. Quantitative Proteomic Analysis of Mosquito C6/36 Cells Reveals Host Proteins Involved in Zika Virus Infection.

    PubMed

    Xin, Qi-Lin; Deng, Cheng-Lin; Chen, Xi; Wang, Jun; Wang, Shao-Bo; Wang, Wei; Deng, Fei; Zhang, Bo; Xiao, Gengfu; Zhang, Lei-Ke

    2017-06-15

    Zika virus (ZIKV) is an emerging arbovirus belonging to the genus Flavivirus of the family Flaviviridae During replication processes, flavivirus manipulates host cell systems to facilitate its replication, while the host cells activate antiviral responses. Identification of host proteins involved in the flavivirus replication process may lead to the discovery of antiviral targets. The mosquitoes Aedes aegypti and Aedes albopictus are epidemiologically important vectors for ZIKV, and effective restrictions of ZIKV replication in mosquitoes will be vital in controlling the spread of virus. In this study, an iTRAQ-based quantitative proteomic analysis of ZIKV-infected Aedes albopictus C6/36 cells was performed to investigate host proteins involved in the ZIKV infection process. A total of 3,544 host proteins were quantified, with 200 being differentially regulated, among which CHCHD2 can be upregulated by ZIKV infection in both mosquito C6/36 and human HeLa cells. Our further study indicated that CHCHD2 can promote ZIKV replication and inhibit beta interferon (IFN-β) production in HeLa cells, suggesting that ZIKV infection may upregulate CHCHD2 to inhibit IFN-I production and thus promote virus replication. Bioinformatics analysis of regulated host proteins highlighted several ZIKV infection-regulated biological processes. Further study indicated that the ubiquitin proteasome system (UPS) plays roles in the ZIKV entry process and that an FDA-approved inhibitor of the 20S proteasome, bortezomib, can inhibit ZIKV infection in vivo Our study illustrated how host cells respond to ZIKV infection and also provided a candidate drug for the control of ZIKV infection in mosquitoes and treatment of ZIKV infection in patients. IMPORTANCE ZIKV infection poses great threats to human health, and there is no FDA-approved drug available for the treatment of ZIKV infection. During replication, ZIKV manipulates host cell systems to facilitate its replication, while host cells activate

  12. iTRAQ-Based Quantitative Proteomics of Developing and Ripening Muscadine Grape Berry

    PubMed Central

    Kambiranda, Devaiah; Katam, Ramesh; Basha, Sheikh M.; Siebert, Shalom

    2014-01-01

    Grapes are among the widely cultivated fruit crops in the world. Grape berries like other nonclimacteric fruits undergo a complex set of dynamic, physical, physiological, and biochemical changes during ripening. Muscadine grapes are widely cultivated in the southern United States for fresh fruit and wine. To date, changes in the metabolites composition of muscadine grapes have been well documented; however, the molecular changes during berry development and ripening are not fully known. The aim of this study was to investigate changes in the berry proteome during ripening in muscadine grape cv. Noble. Isobaric tags for relative and absolute quantification (iTRAQ) MS/MS was used to detect statistically significant changes in the berry proteome. A total of 674 proteins were detected, and 76 were differentially expressed across four time points in muscadine berry. Proteins obtained were further analyzed to provide information about its potential functions during ripening. Several proteins involved in abiotic and biotic stimuli and sucrose and hexose metabolism were upregulated during berry ripening. Quantitative real-time PCR analysis validated the protein expression results for nine proteins. Identification of vicilin-like antimicrobial peptides indicates additional disease tolerance proteins are present in muscadines for berry protection during ripening. The results provide new information for characterization and understanding muscadine berry proteome and grape ripening. PMID:24251720

  13. The Functional Network of the Arabidopsis Plastoglobule Proteome Based on Quantitative Proteomics and Genome-Wide Coexpression Analysis1[C][W][OA

    PubMed Central

    Lundquist, Peter K.; Poliakov, Anton; Bhuiyan, Nazmul H.; Zybailov, Boris; Sun, Qi; van Wijk, Klaas J.

    2012-01-01

    Plastoglobules (PGs) in chloroplasts are thylakoid-associated monolayer lipoprotein particles containing prenyl and neutral lipids and several dozen proteins mostly with unknown functions. An integrated view of the role of the PG is lacking. Here, we better define the PG proteome and provide a conceptual framework for further studies. The PG proteome from Arabidopsis (Arabidopsis thaliana) leaf chloroplasts was determined by mass spectrometry of isolated PGs and quantitative comparison with the proteomes of unfractionated leaves, thylakoids, and stroma. Scanning electron microscopy showed the purity and size distribution of the isolated PGs. Compared with previous PG proteome analyses, we excluded several proteins and identified six new PG proteins, including an M48 metallopeptidase and two Absence of bc1 complex (ABC1) atypical kinases, confirmed by immunoblotting. This refined PG proteome consisted of 30 proteins, including six ABC1 kinases and seven fibrillins together comprising more than 70% of the PG protein mass. Other fibrillins were located predominantly in the stroma or thylakoid and not in PGs; we discovered that this partitioning can be predicted by their isoelectric point and hydrophobicity. A genome-wide coexpression network for the PG genes was then constructed from mRNA expression data. This revealed a modular network with four distinct modules that each contained at least one ABC1K and/or fibrillin gene. Each module showed clear enrichment in specific functions, including chlorophyll degradation/senescence, isoprenoid biosynthesis, plastid proteolysis, and redox regulators and phosphoregulators of electron flow. We propose a new testable model for the PGs, in which sets of genes are associated with specific PG functions. PMID:22274653

  14. Multidimensional electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) for quantitative analysis of the proteome and phosphoproteome in clinical and biomedical research.

    PubMed

    Loroch, Stefan; Schommartz, Tim; Brune, Wolfram; Zahedi, René Peiman; Sickmann, Albert

    2015-05-01

    Quantitative proteomics and phosphoproteomics have become key disciplines in understanding cellular processes. Fundamental research can be done using cell culture providing researchers with virtually infinite sample amounts. In contrast, clinical, pre-clinical and biomedical research is often restricted to minute sample amounts and requires an efficient analysis with only micrograms of protein. To address this issue, we generated a highly sensitive workflow for combined LC-MS-based quantitative proteomics and phosphoproteomics by refining an ERLIC-based 2D phosphoproteomics workflow into an ERLIC-based 3D workflow covering the global proteome as well. The resulting 3D strategy was successfully used for an in-depth quantitative analysis of both, the proteome and the phosphoproteome of murine cytomegalovirus-infected mouse fibroblasts, a model system for host cell manipulation by a virus. In a 2-plex SILAC experiment with 150 μg of a tryptic digest per condition, the 3D strategy enabled the quantification of ~75% more proteins and even ~134% more peptides compared to the 2D strategy. Additionally, we could quantify ~50% more phosphoproteins by non-phosphorylated peptides, concurrently yielding insights into changes on the levels of protein expression and phosphorylation. Beside its sensitivity, our novel three-dimensional ERLIC-strategy has the potential for semi-automated sample processing rendering it a suitable future perspective for clinical, pre-clinical and biomedical research. Copyright © 2015. Published by Elsevier B.V.

  15. Immunodepletion Plasma Proteomics by TripleTOF 5600 and Orbitrap Elite/LTQ-Orbitrap Velos/Q Exactive Mass Spectrometers

    PubMed Central

    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

  16. Stable isotope labelling methods in mass spectrometry-based quantitative proteomics.

    PubMed

    Chahrour, Osama; Cobice, Diego; Malone, John

    2015-09-10

    Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. The Application of SILAC Mouse in Human Body Fluid Proteomics Analysis Reveals Protein Patterns Associated with IgA Nephropathy.

    PubMed

    Zhao, Shilin; Li, Rongxia; Cai, Xiaofan; Chen, Wanjia; Li, Qingrun; Xing, Tao; Zhu, Wenjie; Chen, Y Eugene; Zeng, Rong; Deng, Yueyi

    2013-01-01

    Body fluid proteome is the most informative proteome from a medical viewpoint. But the lack of accurate quantitation method for complicated body fluid limited its application in disease research and biomarker discovery. To address this problem, we introduced a novel strategy, in which SILAC-labeled mouse serum was used as internal standard for human serum and urine proteome analysis. The SILAC-labeled mouse serum was mixed with human serum and urine, and multidimensional separation coupled with tandem mass spectrometry (IEF-LC-MS/MS) analysis was performed. The shared peptides between two species were quantified by their SILAC pairs, and the human-only peptides were quantified by mouse peptides with coelution. The comparison for the results from two replicate experiments indicated the high repeatability of our strategy. Then the urine from Immunoglobulin A nephropathy patients treated and untreated was compared by this quantitation strategy. Fifty-three peptides were found to be significantly changed between two groups, including both known diagnostic markers for IgAN and novel candidates, such as Complement C3, Albumin, VDBP, ApoA,1 and IGFBP7. In conclusion, we have developed a practical and accurate quantitation strategy for comparison of complicated human body fluid proteome. The results from such strategy could provide potential disease-related biomarkers for evaluation of treatment.

  18. Quantitative Dynamics of Proteome, Acetylome, and Succinylome during Stem-Cell Differentiation into Hepatocyte-like Cells.

    PubMed

    Liu, Zekun; Zhang, Qing-Bin; Bu, Chen; Wang, Dawei; Yu, Kai; Gan, Zhixue; Chang, Jianfeng; Cheng, Zhongyi; Liu, Zexian

    2018-06-21

    Stem-cell differentiation is a complex biological process controlled by a series of functional protein clusters and signaling transductions, especially metabolism-related pathways. Although previous studies have quantified the proteome and phosphoproteome for stem-cell differentiation, the investigation of acylation-mediated regulation is still absent. In this study, we quantitatively profiled the proteome, acetylome, and succinylome in pluripotent human embryonic stem cells (hESCs) and differentiated hepatocyte-like cells (HLCs). In total, 3843 proteins, 185 acetylation sites in 103 proteins, and 602 succinylation sites in 391 proteins were quantified. The quantitative proteome showed that in differentiated HLCs the TGF-β, JAK-STAT, and RAS signaling pathways were activated, whereas ECM-related processes such as sulfates and leucine degradation were depressed. Interestingly, it was observed that the acetylation and succinylation were more intensive in hESCs, whereas protein processing in endoplasmic reticulum and the carbon metabolic pathways were especially highly succinylated. Because the metabolism patterns in pluripotent hESCs and the differentiated HLCs were different, we proposed that the dynamic acylations, especially succinylation, might regulate the Warburg-like effect and TCA cycle during differentiation. Taken together, we systematically profiled the protein and acylation levels of regulation in pluripotent hESCs and differentiated HLCs, and the results indicated the important roles of acylation in pluripotency maintenance and differentiation.

  19. Compensatory islet response to insulin resistance revealed by quantitative proteomics

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

    El Ouaamari, Abdelfattah; Zhou, Jian -Ying; Liew, Chong Wee

    Compensatory islet response is a distinct feature of the pre-diabetic insulin resistant state in humans and rodents. To identify alterations in the islet proteome that characterize the adaptive response, we analyzed islets from five-month-old male control, high-fat diet fed (HFD) or obese ob/ob mice by LC-MS(/MS) and quantified ~1,100 islet proteins (at least two peptides) with a false discovery rate <1%. Significant alterations in abundance were observed for ~350 proteins between groups. A majority of alterations were common to both models, and the changes of a subset of ~40 proteins and 12 proteins were verified by targeted quantification using selectedmore » reaction monitoring and Western blots, respectively. The insulin resistant islets in both groups exhibited reduced expression of proteins controlling energy metabolism, oxidative phosphorylation, hormone processing, and secretory pathways. Conversely, an increased expression of molecules involved in protein synthesis and folding suggested effects in endoplasmic reticulum stress response, cell survival, and proliferation in both insulin resistant models. In conclusion, we report a unique comparison of the islet proteome that is focused on the compensatory response in two insulin resistant rodent models that are not overtly diabetic. In conclusion, these data provide a valuable resource of candidate proteins to the scientific community to undertake further studies aimed at enhancing β-cell mass in patients with diabetes. The data are available via the MassIVE repository, with accession MSV000079093.« less

  20. Compensatory islet response to insulin resistance revealed by quantitative proteomics

    DOE PAGES

    El Ouaamari, Abdelfattah; Zhou, Jian -Ying; Liew, Chong Wee; ...

    2015-07-07

    Compensatory islet response is a distinct feature of the pre-diabetic insulin resistant state in humans and rodents. To identify alterations in the islet proteome that characterize the adaptive response, we analyzed islets from five-month-old male control, high-fat diet fed (HFD) or obese ob/ob mice by LC-MS(/MS) and quantified ~1,100 islet proteins (at least two peptides) with a false discovery rate <1%. Significant alterations in abundance were observed for ~350 proteins between groups. A majority of alterations were common to both models, and the changes of a subset of ~40 proteins and 12 proteins were verified by targeted quantification using selectedmore » reaction monitoring and Western blots, respectively. The insulin resistant islets in both groups exhibited reduced expression of proteins controlling energy metabolism, oxidative phosphorylation, hormone processing, and secretory pathways. Conversely, an increased expression of molecules involved in protein synthesis and folding suggested effects in endoplasmic reticulum stress response, cell survival, and proliferation in both insulin resistant models. In conclusion, we report a unique comparison of the islet proteome that is focused on the compensatory response in two insulin resistant rodent models that are not overtly diabetic. In conclusion, these data provide a valuable resource of candidate proteins to the scientific community to undertake further studies aimed at enhancing β-cell mass in patients with diabetes. The data are available via the MassIVE repository, with accession MSV000079093.« less

  1. Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

    PubMed

    Park, Gun Wook; Hwang, Heeyoun; Kim, Kwang Hoe; Lee, Ju Yeon; Lee, Hyun Kyoung; Park, Ji Yeong; Ji, Eun Sun; Park, Sung-Kyu Robin; Yates, John R; Kwon, Kyung-Hoon; Park, Young Mok; Lee, Hyoung-Joo; Paik, Young-Ki; Kim, Jin Young; Yoo, Jong Shin

    2016-11-04

    In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

  2. High-coverage quantitative proteomics using amine-specific isotopic labeling.

    PubMed

    Melanson, Jeremy E; Avery, Steven L; Pinto, Devanand M

    2006-08-01

    Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.

  3. Integrative Analysis of Subcellular Quantitative Proteomics Studies Reveals Functional Cytoskeleton Membrane-Lipid Raft Interactions in Cancer.

    PubMed

    Shah, Anup D; Inder, Kerry L; Shah, Alok K; Cristino, Alexandre S; McKie, Arthur B; Gabra, Hani; Davis, Melissa J; Hill, Michelle M

    2016-10-07

    Lipid rafts are dynamic membrane microdomains that orchestrate molecular interactions and are implicated in cancer development. To understand the functions of lipid rafts in cancer, we performed an integrated analysis of quantitative lipid raft proteomics data sets modeling progression in breast cancer, melanoma, and renal cell carcinoma. This analysis revealed that cancer development is associated with increased membrane raft-cytoskeleton interactions, with ∼40% of elevated lipid raft proteins being cytoskeletal components. Previous studies suggest a potential functional role for the raft-cytoskeleton in the action of the putative tumor suppressors PTRF/Cavin-1 and Merlin. To extend the observation, we examined lipid raft proteome modulation by an unrelated tumor suppressor opioid binding protein cell-adhesion molecule (OPCML) in ovarian cancer SKOV3 cells. In agreement with the other model systems, quantitative proteomics revealed that 39% of OPCML-depleted lipid raft proteins are cytoskeletal components, with microfilaments and intermediate filaments specifically down-regulated. Furthermore, protein-protein interaction network and simulation analysis showed significantly higher interactions among cancer raft proteins compared with general human raft proteins. Collectively, these results suggest increased cytoskeleton-mediated stabilization of lipid raft domains with greater molecular interactions as a common, functional, and reversible feature of cancer cells.

  4. The application of absolute quantitative (1)H NMR spectroscopy in drug discovery and development.

    PubMed

    Singh, Suruchi; Roy, Raja

    2016-07-01

    The identification of a drug candidate and its structural determination is the most important step in the process of the drug discovery and for this, nuclear magnetic resonance (NMR) is one of the most selective analytical techniques. The present review illustrates the various perspectives of absolute quantitative (1)H NMR spectroscopy in drug discovery and development. It deals with the fundamentals of quantitative NMR (qNMR), the physiochemical properties affecting qNMR, and the latest referencing techniques used for quantification. The precise application of qNMR during various stages of drug discovery and development, namely natural product research, drug quantitation in dosage forms, drug metabolism studies, impurity profiling and solubility measurements is elaborated. To achieve this, the authors explore the literature of NMR in drug discovery and development between 1963 and 2015. It also takes into account several other reviews on the subject. qNMR experiments are used for drug discovery and development processes as it is a non-destructive, versatile and robust technique with high intra and interpersonal variability. However, there are several limitations also. qNMR of complex biological samples is incorporated with peak overlap and a low limit of quantification and this can be overcome by using hyphenated chromatographic techniques in addition to NMR.

  5. How well can morphology assess cell death modality? A proteomics study

    PubMed Central

    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

  6. Proteomic technology for biomarker profiling in cancer: an update*

    PubMed Central

    Alaoui-Jamali, Moulay A.; Xu, Ying-jie

    2006-01-01

    The progress in the understanding of cancer progression and early detection has been slow and frustrating due to the complex multifactorial nature and heterogeneity of the cancer syndrome. To date, no effective treatment is available for advanced cancers, which remain a major cause of morbidity and mortality. Clearly, there is urgent need to unravel novel biomarkers for early detection. Most of the functional information of the cancer-associated genes resides in the proteome. The later is an exceptionally complex biological system involving several proteins that function through posttranslational modifications and dynamic intermolecular collisions with partners. These protein complexes can be regulated by signals emanating from cancer cells, their surrounding tissue microenvironment, and/or from the host. Some proteins are secreted and/or cleaved into the extracellular milieu and may represent valuable serum biomarkers for diagnosis purpose. It is estimated that the cancer proteome may include over 1.5 million proteins as a result of posttranslational processing and modifications. Such complexity clearly highlights the need for ultra-high resolution proteomic technology for robust quantitative protein measurements and data acquisition. This review is to update the current research efforts in high-resolution proteomic technology for discovery and monitoring cancer biomarkers. PMID:16625706

  7. PSSMSearch: a server for modeling, visualization, proteome-wide discovery and annotation of protein motif specificity determinants.

    PubMed

    Krystkowiak, Izabella; Manguy, Jean; Davey, Norman E

    2018-06-05

    There is a pressing need for in silico tools that can aid in the identification of the complete repertoire of protein binding (SLiMs, MoRFs, miniMotifs) and modification (moiety attachment/removal, isomerization, cleavage) motifs. We have created PSSMSearch, an interactive web-based tool for rapid statistical modeling, visualization, discovery and annotation of protein motif specificity determinants to discover novel motifs in a proteome-wide manner. PSSMSearch analyses proteomes for regions with significant similarity to a motif specificity determinant model built from a set of aligned motif-containing peptides. Multiple scoring methods are available to build a position-specific scoring matrix (PSSM) describing the motif specificity determinant model. This model can then be modified by a user to add prior knowledge of specificity determinants through an interactive PSSM heatmap. PSSMSearch includes a statistical framework to calculate the significance of specificity determinant model matches against a proteome of interest. PSSMSearch also includes the SLiMSearch framework's annotation, motif functional analysis and filtering tools to highlight relevant discriminatory information. Additional tools to annotate statistically significant shared keywords and GO terms, or experimental evidence of interaction with a motif-recognizing protein have been added. Finally, PSSM-based conservation metrics have been created for taxonomic range analyses. The PSSMSearch web server is available at http://slim.ucd.ie/pssmsearch/.

  8. Large-scale label-free quantitative proteomics of the pea aphid-Buchnera symbiosis.

    PubMed

    Poliakov, Anton; Russell, Calum W; Ponnala, Lalit; Hoops, Harold J; Sun, Qi; Douglas, Angela E; van Wijk, Klaas J

    2011-06-01

    Many insects are nutritionally dependent on symbiotic microorganisms that have tiny genomes and are housed in specialized host cells called bacteriocytes. The obligate symbiosis between the pea aphid Acyrthosiphon pisum and the γ-proteobacterium Buchnera aphidicola (only 584 predicted proteins) is particularly amenable for molecular analysis because the genomes of both partners have been sequenced. To better define the symbiotic relationship between this aphid and Buchnera, we used large-scale, high accuracy tandem mass spectrometry (nanoLC-LTQ-Orbtrap) to identify aphid and Buchnera proteins in the whole aphid body, purified bacteriocytes, isolated Buchnera cells and the residual bacteriocyte fraction. More than 1900 aphid and 400 Buchnera proteins were identified. All enzymes in amino acid metabolism annotated in the Buchnera genome were detected, reflecting the high (68%) coverage of the proteome and supporting the core function of Buchnera in the aphid symbiosis. Transporters mediating the transport of predicted metabolites were present in the bacteriocyte. Label-free spectral counting combined with hierarchical clustering, allowed to define the quantitative distribution of a subset of these proteins across both symbiotic partners, yielding no evidence for the selective transfer of protein among the partners in either direction. This is the first quantitative proteome analysis of bacteriocyte symbiosis, providing a wealth of information about molecular function of both the host cell and bacterial symbiont.

  9. Quantitative proteomic view associated with resistance to clinically important antibiotics in Gram-positive bacteria: a systematic review

    PubMed Central

    Lee, Chang-Ro; Lee, Jung Hun; Park, Kwang Seung; Jeong, Byeong Chul; Lee, Sang Hee

    2015-01-01

    The increase of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) poses a worldwide and serious health threat. Although new antibiotics, such as daptomycin and linezolid, have been developed for the treatment of infections of Gram-positive pathogens, the emergence of daptomycin-resistant and linezolid-resistant strains during therapy has now increased clinical treatment failures. In the past few years, studies using quantitative proteomic methods have provided a considerable progress in understanding antibiotic resistance mechanisms. In this review, to understand the resistance mechanisms to four clinically important antibiotics (methicillin, vancomycin, linezolid, and daptomycin) used in the treatment of Gram-positive pathogens, we summarize recent advances in studies on resistance mechanisms using quantitative proteomic methods, and also examine proteins playing an important role in the bacterial mechanisms of resistance to the four antibiotics. Proteomic researches can identify proteins whose expression levels are changed in the resistance mechanism to only one antibiotic, such as LiaH in daptomycin resistance and PrsA in vancomycin resistance, and many proteins simultaneously involved in resistance mechanisms to various antibiotics. Most of resistance-related proteins, which are simultaneously associated with resistance mechanisms to several antibiotics, play important roles in regulating bacterial envelope biogenesis, or compensating for the fitness cost of antibiotic resistance. Therefore, proteomic data confirm that antibiotic resistance requires the fitness cost and the bacterial envelope is an important factor in antibiotic resistance. PMID:26322035

  10. Involvement of GABA Transporters in Atropine-Treated Myopic Retina As Revealed by iTRAQ Quantitative Proteomics

    PubMed Central

    2015-01-01

    Atropine, a muscarinic antagonist, is known to inhibit myopia progression in several animal models and humans. However, the mode of action is not established yet. In this study, we compared quantitative iTRAQ proteomic analysis in the retinas collected from control and lens-induced myopic (LIM) mouse eyes treated with atropine. The myopic group received a (−15D) spectacle lens over the right eye on postnatal day 10 with or without atropine eye drops starting on postnatal day 24. Axial length was measured by optical low coherence interferometry (OLCI), AC-Master, and refraction was measured by automated infrared photorefractor at postnatal 24, 38, and 52 days. Retinal tissue samples were pooled from six eyes for each group. The experiments were repeated twice, and technical replicates were also performed for liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis. MetaCore was used to perform protein profiling for pathway analysis. We identified a total of 3882 unique proteins with <1% FDR by analyzing the samples in replicates for two independent experiments. This is the largest number of mouse retina proteome reported to date. Thirty proteins were found to be up-regulated (ratio for myopia/control > global mean ratio + 1 standard deviation), and 28 proteins were down-regulated (ratio for myopia/control < global mean ratio - 1 standard deviation) in myopic eyes as compared with control retinas. Pathway analysis using MetaCore revealed regulation of γ-aminobutyric acid (GABA) levels in the myopic eyes. Detailed analysis of the quantitative proteomics data showed that the levels of GABA transporter 1 (GAT-1) were elevated in myopic retina and significantly reduced after atropine treatment. These results were further validated with immunohistochemistry and Western blot analysis. In conclusion, this study provides a comprehensive quantitative proteomic analysis of atropine-treated mouse retina and suggests the involvement of GABAergic signaling in the

  11. iTRAQ-Based Quantitative Proteomic Analysis of the Initiation of Head Regeneration in Planarians.

    PubMed

    Geng, Xiaofang; Wang, Gaiping; Qin, Yanli; Zang, Xiayan; Li, Pengfei; Geng, Zhi; Xue, Deming; Dong, Zimei; Ma, Kexue; Chen, Guangwen; Xu, Cunshuan

    2015-01-01

    The planarian Dugesia japonica has amazing ability to regenerate a head from the anterior ends of the amputated stump with maintenance of the original anterior-posterior polarity. Although planarians present an attractive system for molecular investigation of regeneration and research has focused on clarifying the molecular mechanism of regeneration initiation in planarians at transcriptional level, but the initiation mechanism of planarian head regeneration (PHR) remains unclear at the protein level. Here, a global analysis of proteome dynamics during the early stage of PHR was performed using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy, and our data are available via ProteomeXchange with identifier PXD002100. The results showed that 162 proteins were differentially expressed at 2 h and 6 h following amputation. Furthermore, the analysis of expression patterns and functional enrichment of the differentially expressed proteins showed that proteins involved in muscle contraction, oxidation reduction and protein synthesis were up-regulated in the initiation of PHR. Moreover, ingenuity pathway analysis showed that predominant signaling pathways such as ILK, calcium, EIF2 and mTOR signaling which were associated with cell migration, cell proliferation and protein synthesis were likely to be involved in the initiation of PHR. The results for the first time demonstrated that muscle contraction and ILK signaling might played important roles in the initiation of PHR at the global protein level. The findings of this research provide a molecular basis for further unraveling the mechanism of head regeneration initiation in planarians.

  12. Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma.

    PubMed

    O'Grady, John P; Meyer, Kevin W; Poe, Derrick N

    2017-01-01

    The improving efficacy of many biological therapeutics and identification of low-level biomarkers are driving the analytical proteomics community to deal with extremely high levels of sample complexity relative to their analytes. Many protein quantitation and biomarker validation procedures utilize an immunoaffinity enrichment step to purify the sample and maximize the sensitivity of the corresponding liquid chromatography tandem mass spectrometry measurements. In order to generate surrogate peptides with better mass spectrometric properties, protein enrichment is followed by a proteolytic cleavage step. This is often a time-consuming multistep process. Presented here is a workflow which enables rapid protein enrichment and proteolytic cleavage to be performed in a single, easy-to-use reactor. Using this strategy Klotho, a low-abundance biomarker found in plasma, can be accurately quantitated using a protocol that takes under 5 h from start to finish.

  13. NCI Launches Proteomics Assay Portal | Office of Cancer Clinical Proteomics Research

    Cancer.gov

    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

  14. Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction.

    PubMed

    Ortea, I; Rodríguez-Ariza, A; Chicano-Gálvez, E; Arenas Vacas, M S; Jurado Gámez, B

    2016-04-14

    Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF

  15. Quantitative Proteomics Uncovers Novel Factors Involved in Developmental Differentiation of Trypanosoma brucei

    PubMed Central

    Dejung, Mario; Subota, Ines; Bucerius, Ferdinand; Dindar, Gülcin; Freiwald, Anja; Engstler, Markus; Boshart, Michael; Butter, Falk; Janzen, Christian J.

    2016-01-01

    Developmental differentiation is a universal biological process that allows cells to adapt to different environments to perform specific functions. African trypanosomes progress through a tightly regulated life cycle in order to survive in different host environments when they shuttle between an insect vector and a vertebrate host. Transcriptomics has been useful to gain insight into RNA changes during stage transitions; however, RNA levels are only a moderate proxy for protein abundance in trypanosomes. We quantified 4270 protein groups during stage differentiation from the mammalian-infective to the insect form and provide classification for their expression profiles during development. Our label-free quantitative proteomics study revealed previously unknown components of the differentiation machinery that are involved in essential biological processes such as signaling, posttranslational protein modifications, trafficking and nuclear transport. Furthermore, guided by our proteomic survey, we identified the cause of the previously observed differentiation impairment in the histone methyltransferase DOT1B knock-out strain as it is required for accurate karyokinesis in the first cell division during differentiation. This epigenetic regulator is likely involved in essential chromatin restructuring during developmental differentiation, which might also be important for differentiation in higher eukaryotic cells. Our proteome dataset will serve as a resource for detailed investigations of cell differentiation to shed more light on the molecular mechanisms of this process in trypanosomes and other eukaryotes. PMID:26910529

  16. 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.

  17. Quantitative proteome analysis of barley seeds using ruthenium(II)-tris-(bathophenanthroline-disulphonate) staining.

    PubMed

    Witzel, Katja; Surabhi, Giridara-Kumar; Jyothsnakumari, Gottimukkala; Sudhakar, Chinta; Matros, Andrea; Mock, Hans-Peter

    2007-04-01

    This paper describes the application of the recently introduced fluorescence stain Ruthenium(II)-tris-(bathophenanthroline-disulphonate) (RuBP) on a comparative proteome analysis of two phenotypically different barley lines. We carried out an analysis of protein patterns from 2-D gels of the parental lines of the Oregon Wolfe Barley mapping population DOM and REC and stained with either the conventional colloidal Coomassie Brilliant Blue (cCBB) or with the novel RuBP solution. We wished to experimentally verify the usefulness of such a stain in evaluating the complex pattern of a seed proteome, in comparison to the previously used cCBB staining technique. To validate the efficiency of visualization by both stains, we first compared the overall number of detected protein spots. On average, 790 spots were visible by cCBB staining and 1200 spots by RuBP staining. Then, the intensity of a set of spots was assessed, and changes in relative abundance were determined using image analysis software. As expected, staining with RuBP performed better in quantitation in terms of sensitivity and dynamic range. Furthermore, spots from a cultivar-specific region in the protein map were chosen for identification to asses the gain of biological information due to the staining procedure. From this particular region, eight spots were visualized exclusively by RuBP and identification was successful for all spots, proving the ability to identify even very low abundant proteins. Performance in MS analysis was comparable for both protein stains. Proteins were identified by MALDI-TOF MS peptide mass fingerprinting. This approach was not successful for all spots, due to the restricted entry number for barley in the database. Therefore, we subsequently used LC-ESI-Q-TOF MS/MS and de novo sequencing for identification. Because only an insufficient number of proteins from barley is annotated, an EST-based identification strategy was chosen for our experiment. We wished to test whether under

  18. Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

    PubMed

    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.

  19. Comparative Testis Tissue Proteomics Using 2-Dye Versus 3-Dye DIGE Analysis.

    PubMed

    Holland, Ashling

    2018-01-01

    Comparative tissue proteomics aims to analyze alterations of the proteome in response to a stimulus. Two-dimensional difference gel electrophoresis (2D-DIGE) is a modified and advanced form of 2D gel electrophoresis. DIGE is a powerful biochemical method that compares two or three protein samples on the same analytical gel, and can be used to establish differentially expressed protein levels between healthy normal and diseased pathological tissue sample groups. Minimal DIGE labeling can be used via a 2-dye system with Cy3 and Cy5 or a 3-dye system with Cy2, Cy3, and Cy5 to fluorescently label samples with CyDye flours pre-electrophoresis. DIGE circumvents gel-to-gel variability by multiplexing samples to a single gel and through the use of a pooled internal standard for normalization. This form of quantitative high-resolution proteomics facilitates the comparative analysis and evaluation of tissue protein compositions. Comparing tissue groups under different conditions is crucially important for advancing the biomedical field by characterization of cellular processes, understanding pathophysiological development and tissue biomarker discovery. This chapter discusses 2D-DIGE as a comparative tissue proteomic technique and describes in detail the experimental steps required for comparative proteomic analysis employing both options of 2-dye and 3-dye DIGE minimal labeling.

  20. Quantitative proteomic analysis of bacterial enzymes released in cheese during ripening.

    PubMed

    Jardin, Julien; Mollé, Daniel; Piot, Michel; Lortal, Sylvie; Gagnaire, Valérie

    2012-04-02

    Due to increasingly available bacterial genomes in databases, proteomic tools have recently been used to screen proteins expressed by micro-organisms in food in order to better understand their metabolism in situ. While the main objective is the systematic identification of proteins, the next step will be to bridge the gap between identification and quantification of these proteins. For that purpose, a new mass spectrometry-based approach was applied, using isobaric tagging reagent for quantitative proteomic analysis (iTRAQ), which are amine specific and yield labelled peptides identical in mass. Experimental Swiss-type cheeses were manufactured from microfiltered milk using Streptococcus thermophilus ITG ST20 and Lactobacillus helveticus ITG LH1 as lactic acid starters. At three ripening times (7, 20 and 69 days), cheese aqueous phases were extracted and enriched in bacterial proteins by fractionation. Each sample, standardised in protein amount prior to proteomic analyses, was: i) analysed by 2D-electrophoresis for qualitative analysis and ii) submitted to trypsinolysis, and labelled with specific iTRAQ tag, one per ripening time. The three labelled samples were mixed together and analysed by nano-LC coupled on-line with ESI-QTOF mass spectrometer. Thirty proteins, both from bacterial or bovine origin, were identified and efficiently quantified. The free bacterial proteins detected were enzymes from the central carbon metabolism as well as stress proteins. Depending on the protein considered, the quantity of these proteins in the cheese aqueous extract increased from 2.5 to 20 fold in concentration from day 7 to day 69 of ripening. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline

    PubMed Central

    Schilling, Birgit; Rardin, Matthew J.; MacLean, Brendan X.; Zawadzka, Anna M.; Frewen, Barbara E.; Cusack, Michael P.; Sorensen, Dylan J.; Bereman, Michael S.; Jing, Enxuan; Wu, Christine C.; Verdin, Eric; Kahn, C. Ronald; MacCoss, Michael J.; Gibson, Bradford W.

    2012-01-01

    Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models. PMID:22454539

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    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.

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

    PubMed Central

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

    2017-01-01

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

  5. Proteomic analysis of cow, yak, buffalo, goat and camel milk whey proteins: quantitative differential expression patterns.

    PubMed

    Yang, Yongxin; Bu, Dengpan; Zhao, Xiaowei; Sun, Peng; Wang, Jiaqi; Zhou, Lingyun

    2013-04-05

    To aid in unraveling diverse genetic and biological unknowns, a proteomic approach was used to analyze the whey proteome in cow, yak, buffalo, goat, and camel milk based on the isobaric tag for relative and absolute quantification (iTRAQ) techniques. This analysis is the first to produce proteomic data for the milk from the above-mentioned animal species: 211 proteins have been identified and 113 proteins have been categorized according to molecular function, cellular components, and biological processes based on gene ontology annotation. The results of principal component analysis showed significant differences in proteomic patterns among goat, camel, cow, buffalo, and yak milk. Furthermore, 177 differentially expressed proteins were submitted to advanced hierarchical clustering. The resulting clustering pattern included three major sample clusters: (1) cow, buffalo, and yak milk; (2) goat, cow, buffalo, and yak milk; and (3) camel milk. Certain proteins were chosen as characterization traits for a given species: whey acidic protein and quinone oxidoreductase for camel milk, biglycan for goat milk, uncharacterized protein (Accession Number: F1MK50 ) for yak milk, clusterin for buffalo milk, and primary amine oxidase for cow milk. These results help reveal the quantitative milk whey proteome pattern for analyzed species. This provides information for evaluating adulteration of specific specie milk and may provide potential directions for application of specific milk protein production based on physiological differences among animal species.

  6. Liver proteomics for therapeutic drug discovery: inhibition of the cyclophilin receptor CD147 attenuates sepsis-induced acute renal failure

    PubMed Central

    Dear, James W.; Leelahavanichkul, Asada; Aponte, Angel; Hu, Xuzhen; Constant, Stephanie L.; Hewitt, Stephen M.; Yuen, Peter S.T.; Star, Robert A.

    2008-01-01

    Objective Sepsis-induced multi-organ failure continues to have a high mortality. The liver is an organ central to the disease pathogenesis. The objective of this study was to identify the liver proteins that change in abundance with sepsis and, therefore, identify new drug targets. Design Proteomic discovery study and drug target validation Setting Research institute laboratory Subjects Three month old C57BL/6 mice Interventions We used a mouse model of sepsis based on cecal ligation and puncture (CLP) but with fluid and antibiotic resuscitation. Liver proteins that changed in abundance were identified by difference in-gel electrophoresis (DIGE). We compared liver proteins from 6 hr post-CLP to sham-operated mice (‘early proteins’) and 24 hr post-CLP with 6 hr post-CLP (‘late proteins’). Proteins that changed in abundance were identified by tandem mass spectrometry. We then inhibited the receptor for one protein and determined the effect on sepsis-induced organ dysfunction. Results The liver proteins that changed in abundance after sepsis had a range of functions such as acute phase proteins, coagulation, ER stress, oxidative stress, apoptosis, mitochondrial proteins and nitric oxide metabolism. We found that cyclophilin increased in abundance after CLP. When the receptor for this protein, CD147, was inhibited sepsis-induced renal dysfunction was reduced. There was also a significant reduction in serum cytokine production when CD147 was inhibited. Conclusion By applying proteomics to a clinically relevant mouse model of sepsis we identified a number of novel proteins that changed in abundance. The inhibition of the receptor for one of these proteins, cyclophilin, attenuated sepsis-induced acute renal failure. The application of proteomics to sepsis research can facilitate the discovery of new therapeutic targets. PMID:17944020

  7. Quantitative proteomics-based analysis supports a significant role of GTG proteins in regulation of ABA response in Arabidopsis roots.

    PubMed

    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.

  8. NCI's Proteome Characterization Centers Announced | Office of Cancer Clinical Proteomics Research

    Cancer.gov

    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.

  9. Label free quantitative proteomics analysis on the cisplatin resistance in ovarian cancer cells.

    PubMed

    Wang, F; Zhu, Y; Fang, S; Li, S; Liu, S

    2017-05-20

    Quantitative proteomics has been made great progress in recent years. Label free quantitative proteomics analysis based on the mass spectrometry is widely used. Using this technique, we determined the differentially expressed proteins in the cisplatin-sensitive ovarian cancer cells COC1 and cisplatin-resistant cells COC1/DDP before and after the application of cisplatin. Using the GO analysis, we classified those proteins into different subgroups bases on their cellular component, biological process, and molecular function. We also used KEGG pathway analysis to determine the key signal pathways that those proteins were involved in. There are 710 differential proteins between COC1 and COC1/DDP cells, 783 between COC1 and COC1/DDP cells treated with cisplatin, 917 between the COC1/DDP cells and COC1/DDP cells treated with LaCl3, 775 between COC1/DDP cells treated with cisplatin and COC1/DDP cells treated with cisplatin and LaCl3. Among the same 411 differentially expressed proteins in cisplatin-sensitive COC1 cells and cisplain-resistant COC1/DDP cells before and after cisplatin treatment, 14% of them were localized on the cell membrane. According to the KEGG results, differentially expressed proteins were classified into 21 groups. The most abundant proteins were involved in spliceosome. This study lays a foundation for deciphering the mechanism for drug resistance in ovarian tumor.

  10. The hemolymph proteome of fed and starved Drosophila larvae.

    PubMed

    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.

  11. The Hemolymph Proteome of Fed and Starved Drosophila Larvae

    PubMed Central

    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

  12. Quantitative proteomics of synaptic and nonsynaptic mitochondria: insights for synaptic mitochondrial vulnerability.

    PubMed

    Stauch, Kelly L; Purnell, Phillip R; Fox, Howard S

    2014-05-02

    Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage.

  13. Quantitative Proteomics of Synaptic and Nonsynaptic Mitochondria: Insights for Synaptic Mitochondrial Vulnerability

    PubMed Central

    2015-01-01

    Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage. PMID:24708184

  14. Quantitative changes in proteins responsible for flavonoid and anthocyanin biosynthesis in strawberry fruit at different ripening stages: A targeted quantitative proteomic investigation employing multiple reaction monitoring.

    PubMed

    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

  15. Human body fluid proteome analysis

    PubMed Central

    Hu, Shen; Loo, Joseph A.; Wong, David T.

    2010-01-01

    The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future. PMID:17083142

  16. Human body fluid proteome analysis.

    PubMed

    Hu, Shen; Loo, Joseph A; Wong, David T

    2006-12-01

    The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

  17. The proteome of Hypobaric Induced Hypoxic Lung: Insights from Temporal Proteomic Profiling for Biomarker Discovery

    PubMed Central

    Ahmad, Yasmin; Sharma, Narendra K.; Ahmad, Mohammad Faiz; Sharma, Manish; Garg, Iti; Srivastava, Mousami; Bhargava, Kalpana

    2015-01-01

    Exposure to high altitude induces physiological responses due to hypoxia. Lungs being at the first level to face the alterations in oxygen levels are critical to counter and balance these changes. Studies have been done analysing pulmonary proteome alterations in response to exposure to hypobaric hypoxia. However, such studies have reported the alterations at specific time points and do not reflect the gradual proteomic changes. These studies also identify the various biochemical pathways and responses induced after immediate exposure and the resolution of these effects in challenge to hypobaric hypoxia. In the present study, using 2-DE/MS approach, we attempt to resolve these shortcomings by analysing the proteome alterations in lungs in response to different durations of exposure to hypobaric hypoxia. Our study thus highlights the gradual and dynamic changes in pulmonary proteome following hypobaric hypoxia. For the first time, we also report the possible consideration of SULT1A1, as a biomarker for the diagnosis of high altitude pulmonary edema (HAPE). Higher SULT1A1 levels were observed in rats as well as in humans exposed to high altitude, when compared to sea-level controls. This study can thus form the basis for identifying biomarkers for diagnostic and prognostic purposes in responses to hypobaric hypoxia. PMID:26022216

  18. Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics.

    PubMed

    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.

  19. Proteomics of the Lysosome

    PubMed Central

    Lübke, Torben; Lobel, Peter; Sleat, David

    2009-01-01

    Defects in lysosomal function have been associated with numerous monogenic human diseases typically classified as lysosomal storage diseases. However, there is increasing evidence that lysosomal proteins are also involved in more widespread human diseases including cancer and Alzheimer disease. Thus, there is a continuing interest in understanding the cellular functions of the lysosome and an emerging approach to this is the identification of its constituent proteins by proteomic analyses. To date, the mammalian lysosome has been shown to contain ~ 60 soluble luminal proteins and ~25 transmembrane proteins. However, recent proteomic studies based upon affinity purification of soluble components or subcellular fractionation to obtain both soluble and membrane components suggest that there may be many more of both classes of protein resident within this organelle than previously appreciated. Discovery of such proteins has important implications for understanding the function and the dynamics of the lysosome but can also lead the way towards the discovery of the genetic basis for human diseases of hitherto unknown etiology. Here, we describe current approaches to lysosomal proteomics and data interpretation and review the new lysosomal proteins that have recently emerged from such studies. PMID:18977398

  20. Interaction Analysis through Proteomic Phage Display

    PubMed Central

    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

  1. Quantitative Temporal in Vivo Proteomics Deciphers the Transition of Virus-Driven Myeloid Cells into M2 Macrophages

    PubMed Central

    2017-01-01

    Myeloid cells play a central role in the context of viral eradication, yet precisely how these cells differentiate throughout the course of acute infections is poorly understood. In this study, we have developed a novel quantitative temporal in vivo proteomics (QTiPs) platform to capture proteomic signatures of temporally transitioning virus-driven myeloid cells directly in situ, thus taking into consideration host–virus interactions throughout the course of an infection. QTiPs, in combination with phenotypic, functional, and metabolic analyses, elucidated a pivotal role for inflammatory CD11b+, Ly6G–, Ly6Chigh-low cells in antiviral immune response and viral clearance. Most importantly, the time-resolved QTiPs data set showed the transition of CD11b+, Ly6G–, Ly6Chigh-low cells into M2-like macrophages, which displayed increased antigen-presentation capacities and bioenergetic demands late in infection. We elucidated the pivotal role of myeloid cells in virus clearance and show how these cells phenotypically, functionally, and metabolically undergo a timely transition from inflammatory to M2-like macrophages in vivo. With respect to the growing appreciation for in vivo examination of viral–host interactions and for the role of myeloid cells, this study elucidates the use of quantitative proteomics to reveal the role and response of distinct immune cell populations throughout the course of virus infection. PMID:28768414

  2. Multiple reaction monitoring (MRM) of plasma proteins in cardiovascular proteomics.

    PubMed

    Dardé, Verónica M; Barderas, Maria G; Vivanco, Fernando

    2013-01-01

    Different methodologies have been used through years to discover new potential biomarkers related with cardiovascular risk. The conventional proteomic strategy involves a discovery phase that requires the use of mass spectrometry (MS) and a validation phase, usually on an alternative platform such as immunoassays that can be further implemented in clinical practice. This approach is suitable for a single biomarker, but when large panels of biomarkers must be validated, the process becomes inefficient and costly. Therefore, it is essential to find an alternative methodology to perform the biomarker discovery, validation, and -quantification. The skills provided by quantitative MS turn it into an extremely attractive alternative to antibody-based technologies. Although it has been traditionally used for quantification of small molecules in clinical chemistry, MRM is now emerging as an alternative to traditional immunoassays for candidate protein biomarker validation.

  3. A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data

    PubMed Central

    Chen, Yi-Hau

    2017-01-01

    Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https

  4. A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.

    PubMed

    Lai, En-Yu; Chen, Yi-Hau; Wu, Kun-Pin

    2017-06-01

    Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https

  5. Low Mass Blood Peptides Discriminative of Inflammatory Bowel Disease (IBD) Severity: A Quantitative Proteomic Perspective*

    PubMed Central

    Yau, Yunki; Duo, Xizi; Zeng, Ming; Campbell, Beth; Shin, Sean; Luber, Raphael; Redmond, Diane; Leong, Rupert W. L.

    2016-01-01

    Breakdown of the protective gut barrier releases effector molecules and degradation products into the blood stream making serum and plasma ideal as a diagnostic medium. The enriched low mass proteome is unexplored as a source of differentiators for diagnosing and monitoring inflammatory bowel disease (IBD) activity, that is less invasive than colonoscopy. Differences in the enriched low mass plasma proteome (<25 kDa) were assessed by label-free quantitative mass-spectrometry. A panel of marker candidates were progressed to validation phase and “Tier-2” FDA-level validated quantitative assay. Proteins important in maintaining gut barrier function and homeostasis at the epithelial interface have been quantitated by multiple reaction monitoring in plasma and serum including both inflammatory; rheumatoid arthritis controls, and non-inflammatory healthy controls; ulcerative colitis (UC), and Crohn's disease (CD) patients. Detection by immunoblot confirmed presence at the protein level in plasma. Correlation analysis and receiver operator characteristics were used to report the sensitivity and specificity. Peptides differentiating controls from IBD originate from secreted phosphoprotein 24 (SPP24, p = 0.000086, 0.009); whereas those in remission and healthy can be differentiated in UC by SPP24 (p = 0.00023, 0.001), α-1-microglobulin (AMBP, p = 0.006) and CD by SPP24 (p = 0.019, 0.05). UC and CD can be differentiated by Guanylin (GUC2A, p = 0.001), and Secretogranin-1 (CHGB p = 0.035). Active and quiescent disease can also be differentiated in UC and CD by CHGB (p ≤ 0.023) SPP24 (p ≤ 0.023) and AMBP (UC p = 0.046). Five peptides discriminating IBD activity and severity had very little-to-no correlation to erythrocyte sedimentation rate, C-reactive protein, white cell or platelet counts. Three of these peptides were found to be binding partners to SPP24 protein alongside other known matrix proteins. These proteins have the potential to improve diagnosis and

  6. Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

    PubMed

    Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

    2004-01-01

    The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

  7. Candidate-based proteomics in the search for biomarkers of cardiovascular disease

    PubMed Central

    Anderson, Leigh

    2005-01-01

    The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

  8. Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers

    PubMed Central

    Schilling, Birgit; Gibson, Bradford W.; Hunter, Christie L.

    2017-01-01

    Data-independent acquisition is a powerful mass spectrometry technique that enables comprehensive MS and MS/MS analysis of all detectable species, providing an information rich data file that can be mined deeply. Here, we describe how to acquire high-quality SWATH® Acquisition data to be used for large quantitative proteomic studies. We specifically focus on using variable sized Q1 windows for acquisition of MS/MS data for generating higher specificity quantitative data. PMID:28188533

  9. Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

    PubMed Central

    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

  10. Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields.

    PubMed

    Kuzniar, Arnold; Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A Peter M; Demmers, Jeroen; Lebbink, Joyce H G; Kanaar, Roland

    2017-01-01

    The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture.

  11. Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields

    PubMed Central

    Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A. Peter M.; Demmers, Jeroen; Lebbink, Joyce H. G.; Kanaar, Roland

    2017-01-01

    The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture. PMID:28234898

  12. Proteome-wide detection and quantitative analysis of irreversible cysteine oxidation using long column UPLC-pSRM.

    PubMed

    Lee, Chia-Fang; Paull, Tanya T; Person, Maria D

    2013-10-04

    Reactive oxygen species (ROS) play an important role in normal biological functions and pathological processes. ROS is one of the driving forces for oxidizing proteins, especially on cysteine thiols. The labile, transient, and dynamic nature of oxidative modifications poses enormous technical challenges for both accurate modification site determination and quantitation of cysteine thiols. The present study describes a mass spectrometry-based approach that allows effective discovery and quantification of irreversible cysteine modifications. The utilization of a long reverse phase column provides high-resolution chromatography to separate different forms of modified cysteine thiols from protein complexes or cell lysates. This Fourier transform mass spectrometry (FT-MS) approach enabled detection and quantitation of ataxia telangiectasia mutated (ATM) complex cysteine sulfoxidation states using Skyline MS1 filtering. When we applied the long column ultra high pressure liquid chromatography (UPLC)-MS/MS analysis, 61 and 44 peptides from cell lysates and cells were identified with cysteine modifications in response to in vitro and in vivo H2O2 oxidation, respectively. Long column ultra high pressure liquid chromatography pseudo selected reaction monitoring (UPLC-pSRM) was then developed to monitor the oxidative level of cysteine thiols in cell lysate under varying concentrations of H2O2 treatment. From UPLC-pSRM analysis, the dynamic conversion of sulfinic (S-O2H) and sulfonic acid (S-O3H) was observed within nucleoside diphosphate kinase (Nm23-H1) and heat shock 70 kDa protein 8 (Hsc70). These methods are suitable for proteome-wide studies, providing a highly sensitive, straightforward approach to identify proteins containing redox-sensitive cysteine thiols in biological systems.

  13. Comparative and quantitative proteomic analysis of normal and degenerated human annulus fibrosus cells.

    PubMed

    Ye, Dongping; Liang, Weiguo; Dai, Libing; Zhou, Longqiang; Yao, Yicun; Zhong, Xin; Chen, Honghui; Xu, Jiake

    2015-05-01

    Degeneration of the intervertebral disc (IVD) is a major chronic medical condition associated with back pain. To better understand the pathogenesis of IVD degeneration, we performed comparative and quantitative proteomic analyses of normal and degenerated human annulus fibrosus (AF) cells and identified proteins that are differentially expressed between them. Annulus fibrosus cells were isolated and cultured from patients with lumbar disc herniation (the experimental group, degenerated AF cells) and scoliosis patients who underwent orthopaedic surgery (the control group, normal AF cells). Comparative proteomic analyses of normal and degenerated cultured AF cells were carried out using 2-D electrophoresis, mass spectrometric analyses, and database searching. Quantitative analyses of silver-stained 2-D electrophoresis gels of normal and degenerated cultured AF cells identified 10 protein spots that showed the most altered differential expression levels between the two groups. Among these, three proteins were decreased, including heat shock cognate 71-kDa protein, glucose-6-phosphate 1-dehydrogenase, and protocadherin-23, whereas seven proteins were increased, including guanine nucleotide-binding protein G(i) subunit α-2, superoxide dismutase, transmembrane protein 51, adenosine receptor A3, 26S protease regulatory subunit 8, lipid phosphate phosphatase-related protein, and fatty acyl-crotonic acid reductase 1. These differentially expressed proteins might be involved in the pathophysiological process of IVD degeneration and have potential values as biomarkers of the degeneration of IVD. © 2015 Wiley Publishing Asia Pty Ltd.

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

    PubMed

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

    2016-05-01

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

  15. Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

    PubMed Central

    Feist, Peter; Hummon, Amanda B.

    2015-01-01

    Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed. PMID:25664860

  16. Statistical Analysis of Variation in the Human Plasma Proteome

    DOE PAGES

    Corzett, Todd H.; Fodor, Imola K.; Choi, Megan W.; ...

    2010-01-01

    Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where onemore » human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.« less

  17. Statistical analysis of variation in the human plasma proteome.

    PubMed

    Corzett, Todd H; Fodor, Imola K; Choi, Megan W; Walsworth, Vicki L; Turteltaub, Kenneth W; McCutchen-Maloney, Sandra L; Chromy, Brett A

    2010-01-01

    Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

  18. Recent advances in mass spectrometry-based proteomics of gastric cancer.

    PubMed

    Kang, Changwon; Lee, Yejin; Lee, J Eugene

    2016-10-07

    The last decade has witnessed remarkable technological advances in mass spectrometry-based proteomics. The development of proteomics techniques has enabled the reliable analysis of complex proteomes, leading to the identification and quantification of thousands of proteins in gastric cancer cells, tissues, and sera. This quantitative information has been used to profile the anomalies in gastric cancer and provide insights into the pathogenic mechanism of the disease. In this review, we mainly focus on the advances in mass spectrometry and quantitative proteomics that were achieved in the last five years and how these up-and-coming technologies are employed to track biochemical changes in gastric cancer cells. We conclude by presenting a perspective on quantitative proteomics and its future applications in the clinic and translational gastric cancer research.

  19. Comparative analysis of cerebrospinal fluid from the meningo-encephalitic stage of T. b. gambiense and rhodesiense sleeping sickness patients using TMT quantitative proteomics.

    PubMed

    Tiberti, Natalia; Sanchez, Jean-Charles

    2015-09-01

    The quantitative proteomics data here reported are part of a research article entitled "Increased acute immune response during the meningo-encephalitic stage of Trypanosoma brucei rhodesiense sleeping sickness compared to Trypanosoma brucei gambiense", published by Tiberti et al., 2015. Transl. Proteomics 6, 1-9. Sleeping sickness (human African trypanosomiasis - HAT) is a deadly neglected tropical disease affecting mainly rural communities in sub-Saharan Africa. This parasitic disease is caused by the Trypanosoma brucei (T. b.) parasite, which is transmitted to the human host through the bite of the tse-tse fly. Two parasite sub-species, T. b. rhodesiense and T. b. gambiense, are responsible for two clinically different and geographically separated forms of sleeping sickness. The objective of the present study was to characterise and compare the cerebrospinal fluid (CSF) proteome of stage 2 (meningo-encephalitic stage) HAT patients suffering from T. b. gambiense or T. b. rhodesiense disease using high-throughput quantitative proteomics and the Tandem Mass Tag (TMT(®)) isobaric labelling. In order to evaluate the CSF proteome in the context of HAT pathophysiology, the protein dataset was then submitted to gene ontology and pathway analysis. Two significantly differentially expressed proteins (C-reactive protein and orosomucoid 1) were further verified on a larger population of patients (n=185) by ELISA, confirming the mass spectrometry results. By showing a predominant involvement of the acute immune response in rhodesiense HAT, the proteomics results obtained in this work will contribute to further understand the mechanisms of pathology occurring in HAT and to propose new biomarkers of potential clinical utility. The mass spectrometry raw data are available in the Pride Archive via ProteomeXchange through the identifier PXD001082.

  20. Quantitative proteomics and dynamic imaging of the nucleolus reveal distinct responses to UV and ionizing radiation.

    PubMed

    Moore, Henna M; Bai, Baoyan; Boisvert, François-Michel; Latonen, Leena; Rantanen, Ville; Simpson, Jeremy C; Pepperkok, Rainer; Lamond, Angus I; Laiho, Marikki

    2011-10-01

    The nucleolus is a nuclear organelle that coordinates rRNA transcription and ribosome subunit biogenesis. Recent proteomic analyses have shown that the nucleolus contains proteins involved in cell cycle control, DNA processing and DNA damage response and repair, in addition to the many proteins connected with ribosome subunit production. Here we study the dynamics of nucleolar protein responses in cells exposed to stress and DNA damage caused by ionizing and ultraviolet (UV) radiation in diploid human fibroblasts. We show using a combination of imaging and quantitative proteomics methods that nucleolar substructure and the nucleolar proteome undergo selective reorganization in response to UV damage. The proteomic responses to UV include alterations of functional protein complexes such as the SSU processome and exosome, and paraspeckle proteins, involving both decreases and increases in steady state protein ratios, respectively. Several nonhomologous end-joining proteins (NHEJ), such as Ku70/80, display similar fast responses to UV. In contrast, nucleolar proteomic responses to IR are both temporally and spatially distinct from those caused by UV, and more limited in terms of magnitude. With the exception of the NHEJ and paraspeckle proteins, where IR induces rapid and transient changes within 15 min of the damage, IR does not alter the ratios of most other functional nucleolar protein complexes. The rapid transient decrease of NHEJ proteins in the nucleolus indicates that it may reflect a response to DNA damage. Our results underline that the nucleolus is a specific stress response organelle that responds to different damage and stress agents in a unique, damage-specific manner.

  1. High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics

    PubMed Central

    2015-01-01

    Multiplex isobaric tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantification (iTRAQ)) are a valuable tool for high-throughput mass spectrometry based quantitative proteomics. We have developed our own multiplex isobaric tags, DiLeu, that feature quantitative performance on par with commercial offerings but can be readily synthesized in-house as a cost-effective alternative. In this work, we achieve a 3-fold increase in the multiplexing capacity of the DiLeu reagent without increasing structural complexity by exploiting mass defects that arise from selective incorporation of 13C, 15N, and 2H stable isotopes in the reporter group. The inclusion of eight new reporter isotopologues that differ in mass from the existing four reporters by intervals of 6 mDa yields a 12-plex isobaric set that preserves the synthetic simplicity and quantitative performance of the original implementation. We show that the new reporter variants can be baseline-resolved in high-resolution higher-energy C-trap dissociation (HCD) spectra, and we demonstrate accurate 12-plex quantitation of a DiLeu-labeled Saccharomyces cerevisiae lysate digest via high-resolution nano liquid chromatography–tandem mass spectrometry (nanoLC–MS2) analysis on an Orbitrap Elite mass spectrometer. PMID:25405479

  2. A proteomics performance standard to support measurement quality in proteomics.

    PubMed

    Beasley-Green, Ashley; Bunk, David; Rudnick, Paul; Kilpatrick, Lisa; Phinney, Karen

    2012-04-01

    The emergence of MS-based proteomic platforms as a prominent technology utilized in biochemical and biomedical research has increased the need for high-quality MS measurements. To address this need, National Institute of Standards and Technology (NIST) reference material (RM) 8323 yeast protein extract is introduced as a proteomics quality control material for benchmarking the preanalytical and analytical performance of proteomics-based experimental workflows. RM 8323 yeast protein extract is based upon the well-characterized eukaryote Saccharomyces cerevisiae and can be utilized in the design and optimization of proteomics-based methodologies from sample preparation to data analysis. To demonstrate its utility as a proteomics quality control material, we coupled LC-MS/MS measurements of RM 8323 with the NIST MS Quality Control (MSQC) performance metrics to quantitatively assess the LC-MS/MS instrumentation parameters that influence measurement accuracy, repeatability, and reproducibility. Due to the complexity of the yeast proteome, we also demonstrate how NIST RM 8323, along with the NIST MSQC performance metrics, can be used in the evaluation and optimization of proteomics-based sample preparation methods. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. An introduction to statistical process control in research proteomics.

    PubMed

    Bramwell, David

    2013-12-16

    Statistical process control is a well-established and respected method which provides a general purpose, and consistent framework for monitoring and improving the quality of a process. It is routinely used in many industries where the quality of final products is critical and is often required in clinical diagnostic laboratories [1,2]. To date, the methodology has been little utilised in research proteomics. It has been shown to be capable of delivering quantitative QC procedures for qualitative clinical assays [3] making it an ideal methodology to apply to this area of biological research. To introduce statistical process control as an objective strategy for quality control and show how it could be used to benefit proteomics researchers and enhance the quality of the results they generate. We demonstrate that rules which provide basic quality control are easy to derive and implement and could have a major impact on data quality for many studies. Statistical process control is a powerful tool for investigating and improving proteomics research work-flows. The process of characterising measurement systems and defining control rules forces the exploration of key questions that can lead to significant improvements in performance. This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 The Author. Published by Elsevier

  4. Quantitative proteomics analysis using 2D-PAGE to investigate the effects of cigarette smoke and aerosol of a prototypic modified risk tobacco product on the lung proteome in C57BL/6 mice.

    PubMed

    Elamin, Ashraf; Titz, Bjoern; Dijon, Sophie; Merg, Celine; Geertz, Marcel; Schneider, Thomas; Martin, Florian; Schlage, Walter K; Frentzel, Stefan; Talamo, Fabio; Phillips, Blaine; Veljkovic, Emilija; Ivanov, Nikolai V; Vanscheeuwijck, Patrick; Peitsch, Manuel C; Hoeng, Julia

    2016-08-11

    Smoking is associated with several serious diseases, such as lung cancer and chronic obstructive pulmonary disease (COPD). Within our systems toxicology framework, we are assessing whether potential modified risk tobacco products (MRTP) can reduce smoking-related health risks compared to conventional cigarettes. In this article, we evaluated to what extent 2D-PAGE/MALDI MS/MS (2D-PAGE) can complement the iTRAQ LC-MS/MS results from a previously reported mouse inhalation study, in which we assessed a prototypic MRTP (pMRTP). Selected differentially expressed proteins identified by both LC-MS/MS and 2D-PAGE approaches were further verified using reverse-phase protein microarrays. LC-MS/MS captured the effects of cigarette smoke (CS) on the lung proteome more comprehensively than 2D-PAGE. However, an integrated analysis of both proteomics data sets showed that 2D-PAGE data complement the LC-MS/MS results by supporting the overall trend of lower effects of pMRTP aerosol than CS on the lung proteome. Biological effects of CS exposure supported by both methods included increases in immune-related, surfactant metabolism, proteasome, and actin cytoskeleton protein clusters. Overall, while 2D-PAGE has its value, especially as a complementary method for the analysis of effects on intact proteins, LC-MS/MS approaches will likely be the method of choice for proteome analysis in systems toxicology investigations. Quantitative proteomics is anticipated to play a growing role within systems toxicology assessment frameworks in the future. To further understand how different proteomics technologies can contribute to toxicity assessment, we conducted a quantitative proteomics analysis using 2D-PAGE and isobaric tag-based LC-MS/MS approaches and compared the results produced from the 2 approaches. Using a prototypic modified risk tobacco product (pMRTP) as our test item, we show compared with cigarette smoke, how 2D-PAGE results can complement and support LC-MS/MS data, demonstrating

  5. Optimization of quantitative proteomic analysis of clots generated from plasma of patients with venous thromboembolism.

    PubMed

    Stachowicz, Aneta; Siudut, Jakub; Suski, Maciej; Olszanecki, Rafał; Korbut, Ryszard; Undas, Anetta; Wiśniewski, Jacek R

    2017-01-01

    It is well known that fibrin network binds a large variety of proteins, including inhibitors and activators of fibrinolysis, which may affect clot properties, such as stability and susceptibility to fibrinolysis. Specific plasma clot composition differs between individuals and may change in disease states. However, the plasma clot proteome has not yet been in-depth analyzed, mainly due to technical difficulty related to the presence of a highly abundant protein-fibrinogen and fibrin that forms a plasma clot. The aim of our study was to optimize quantitative proteomic analysis of fibrin clots prepared ex vivo from citrated plasma of the peripheral blood drawn from patients with prior venous thromboembolism (VTE). We used a multiple enzyme digestion filter aided sample preparation, a multienzyme digestion (MED) FASP method combined with LC-MS/MS analysis performed on a Proxeon Easy-nLC System coupled to the Q Exactive HF mass spectrometer. We also evaluated the impact of peptide fractionation with pipet-tip strong anion exchange (SAX) method on the obtained results. Our proteomic approach revealed 476 proteins repeatedly identified in the plasma fibrin clots from patients with VTE including extracellular vesicle-derived proteins, lipoproteins, fibrinolysis inhibitors, and proteins involved in immune responses. The MED FASP method using three different enzymes: LysC, trypsin and chymotrypsin increased the number of identified peptides and proteins and their sequence coverage as compared to a single step digestion. Peptide fractionation with a pipet-tip strong anion exchange (SAX) protocol increased the depth of proteomic analyses, but also extended the time needed for sample analysis with LC-MS/MS. The MED FASP method combined with a label-free quantification is an excellent proteomic approach for the analysis of fibrin clots prepared ex vivo from citrated plasma of patients with prior VTE.

  6. Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

    PubMed Central

    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

  7. Postmenopausal estrogen and progestin effects on the serum proteome

    PubMed Central

    2009-01-01

    Background Women's Health Initiative randomized trials of postmenopausal hormone therapy reported intervention effects on several clinical outcomes, with some important differences between estrogen alone and estrogen plus progestin. The biologic mechanisms underlying these effects, and these differences, have yet to be fully elucidated. Methods Baseline serum samples were compared with samples drawn 1 year later for 50 women assigned to active hormone therapy in both the estrogen-plus-progestin and estrogen-alone randomized trials, by applying an in-depth proteomic discovery platform to serum pools from 10 women per pool. Results In total, 378 proteins were quantified in two or more of the 10 pooled serum comparisons, by using strict identification criteria. Of these, 169 (44.7%) showed evidence (nominal P < 0.05) of change in concentration between baseline and 1 year for one or both of estrogen-plus-progestin and estrogen-alone groups. Quantitative changes were highly correlated between the two hormone-therapy preparations. A total of 98 proteins had false discovery rates < 0.05 for change with estrogen plus progestin, compared with 94 for estrogen alone. Of these, 84 had false discovery rates <0.05 for both preparations. The observed changes included multiple proteins relevant to coagulation, inflammation, immune response, metabolism, cell adhesion, growth factors, and osteogenesis. Evidence of differential changes also was noted between the hormone preparations, with the strongest evidence in growth factor and inflammation pathways. Conclusions Serum proteomic analyses yielded a large number of proteins similarly affected by estrogen plus progestin and by estrogen alone and identified some proteins and pathways that appear to be differentially affected between the two hormone preparations; this may explain their distinct clinical effects. PMID:20034393

  8. Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics

    PubMed Central

    Bennett, Eric J.; Rush, John; Gygi, Steven P.; Harper, J. Wade

    2010-01-01

    Dynamic reorganization of signaling systems frequently accompany pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex Absolute Quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules while only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. PMID:21145461

  9. Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm

    PubMed Central

    Burillo, Elena; Jorge, Inmaculada; Martínez-López, Diego; Camafeita, Emilio; Blanco-Colio, Luis Miguel; Trevisan-Herraz, Marco; Ezkurdia, Iakes; Egido, Jesús; Michel, Jean-Baptiste; Meilhac, Olivier; Vázquez, Jesús; Martin-Ventura, Jose Luis

    2016-01-01

    High-density lipoproteins (HDLs) are complex protein and lipid assemblies whose composition is known to change in diverse pathological situations. Analysis of the HDL proteome can thus provide insight into the main mechanisms underlying abdominal aortic aneurysm (AAA) and potentially detect novel systemic biomarkers. We performed a multiplexed quantitative proteomics analysis of HDLs isolated from plasma of AAA patients (N = 14) and control study participants (N = 7). Validation was performed by western-blot (HDL), immunohistochemistry (tissue), and ELISA (plasma). HDL from AAA patients showed elevated expression of peroxiredoxin-6 (PRDX6), HLA class I histocompatibility antigen (HLA-I), retinol-binding protein 4, and paraoxonase/arylesterase 1 (PON1), whereas α-2 macroglobulin and C4b-binding protein were decreased. The main pathways associated with HDL alterations in AAA were oxidative stress and immune-inflammatory responses. In AAA tissue, PRDX6 colocalized with neutrophils, vascular smooth muscle cells, and lipid oxidation. Moreover, plasma PRDX6 was higher in AAA (N = 47) than in controls (N = 27), reflecting increased systemic oxidative stress. Finally, a positive correlation was recorded between PRDX6 and AAA diameter. The analysis of the HDL proteome demonstrates that redox imbalance is a major mechanism in AAA, identifying the antioxidant PRDX6 as a novel systemic biomarker of AAA. PMID:27934969

  10. Mathematical biodescriptors of proteomics maps: background and applications.

    PubMed

    Basak, Subhash C; Gute, Brian D

    2008-05-01

    This article reviews recent developments in the formulation and application of biodescriptors to characterize proteomics maps. Such biodescriptors can be derived by applying techniques from discrete mathematics (graph theory, linear algebra and information theory). This review focuses on the development of biodescriptors for proteomics maps derived from 2D gel electrophoresis. Preliminary results demonstrated that such descriptors have a reasonable ability to differentiate between proteomics patterns that result from exposure to closely related individual chemicals and complex mixtures, such as the jet fuel JP-8. Further research is required to evaluate the utility of these proteomics-based biodescriptors for drug discovery and predictive toxicology.

  11. A Proteomic View on the Role of Legume Symbiotic Interactions

    PubMed Central

    Larrainzar, Estíbaliz; Wienkoop, Stefanie

    2017-01-01

    Legume plants are key elements in sustainable agriculture and represent a significant source of plant-based protein for humans and animal feed worldwide. One specific feature of the family is the ability to establish nitrogen-fixing symbiosis with Rhizobium bacteria. Additionally, like most vascular flowering plants, legumes are able to form a mutualistic endosymbiosis with arbuscular mycorrhizal (AM) fungi. These beneficial associations can enhance the plant resistance to biotic and abiotic stresses. Understanding how symbiotic interactions influence and increase plant stress tolerance are relevant questions toward maintaining crop yield and food safety in the scope of climate change. Proteomics offers numerous tools for the identification of proteins involved in such responses, allowing the study of sub-cellular localization and turnover regulation, as well as the discovery of post-translational modifications (PTMs). The current work reviews the progress made during the last decades in the field of proteomics applied to the study of the legume-Rhizobium and -AM symbioses, and highlights their influence on the plant responses to pathogens and abiotic stresses. We further discuss future perspectives and new experimental approaches that are likely to have a significant impact on the field including peptidomics, mass spectrometric imaging, and quantitative proteomics. PMID:28769967

  12. Evaluation of a High Intensity Focused Ultrasound-Immobilized Trypsin Digestion and 18O-Labeling Method for Quantitative Proteomics

    PubMed Central

    López-Ferrer, Daniel; Hixson, Kim K.; Smallwood, Heather; Squier, Thomas C.; Petritis, Konstantinos; Smith, Richard D.

    2009-01-01

    A new method that uses immobilized trypsin concomitant with ultrasonic irradiation results in ultra-rapid digestion and thorough 18O labeling for quantitative protein comparisons. The reproducible and highly efficient method provided effective digestions in <1 min with a minimized amount of enzyme required compared to traditional methods. This method was demonstrated for digestion of both simple and complex protein mixtures, including bovine serum albumin, a global proteome extract from the bacteria Shewanella oneidensis, and mouse plasma, as well as 18O labeling of such complex protein mixtures, which validated the application of this method for differential proteomic measurements. This approach is simple, reproducible, cost effective, rapid, and thus well-suited for automation. PMID:19555078

  13. Overgrazing induces alterations in the hepatic proteome of sheep (Ovis aries): an iTRAQ-based quantitative proteomic analysis.

    PubMed

    Ren, Weibo; Hou, Xiangyang; Wang, Yuqing; Badgery, Warwick; Li, Xiliang; Ding, Yong; Guo, Huiqin; Wu, Zinian; Hu, Ningning; Kong, Lingqi; Chang, Chun; Jiang, Chao; Zhang, Jize

    2016-01-01

    The degradation of the steppe of Inner Mongolia, due to overgrazing, has resulted in ecosystem damage as well as extensive reductions in sheep production. The growth performance of sheep is greatly reduced because of overgrazing, which triggers massive economic losses every year. The liver is an essential organ that has very important roles in multiple functions, such as nutrient metabolism, immunity and others, which are closely related to animal growth. However, to our knowledge, no detailed studies have evaluated hepatic metabolism adaption in sheep due to overgrazing. The molecular mechanisms that underlie these effects remain unclear. In the present study, our group applied isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic analysis to investigate changes in the protein profiles of sheep hepatic tissues when nutrition was reduced due to overgrazing (12.0 sheep/ha), with the goal of characterizing the molecular mechanisms of hepatic metabolism adaption in sheep in an overgrazing condition. The body weight daily gain of sheep was greatly decreased due to overgrazing. Overall, 41 proteins were found to be differentially abundant in the hepatic tissue between a light grazing group and an overgrazing group. Most of the differentially expressed proteins identified are involved in protein metabolism, transcriptional and translational regulation, and immune response. In particular, the altered abundance of kynureninase (KYNU) and HAL (histidine ammonia-lyase) involved in protein metabolic function, integrated with the changes of serum levels of blood urea nitrogen (BUN) and glucose (GLU), suggest that overgrazing triggers a shift in energy resources from carbohydrates to proteins, causing poorer nitrogen utilization efficiency. Altogether, these results suggest that the reductions in animal growth induced by overgrazing are associated with liver proteomic changes, especially the proteins involved in nitrogen compounds metabolism

  14. SILAC-based proteomics of human primary endothelial cell morphogenesis unveils tumor angiogenic markers.

    PubMed

    Zanivan, Sara; Maione, Federica; Hein, Marco Y; Hernández-Fernaud, Juan Ramon; Ostasiewicz, Pawel; Giraudo, Enrico; Mann, Matthias

    2013-12-01

    Proteomics has been successfully used for cell culture on dishes, but more complex cellular systems have proven to be challenging and so far poorly approached with proteomics. Because of the complexity of the angiogenic program, we still do not have a complete understanding of the molecular mechanisms involved in this process, and there have been no in depth quantitative proteomic studies. Plating endothelial cells on matrigel recapitulates aspects of vessel growth, and here we investigate this mechanism by using a spike-in SILAC quantitative proteomic approach. By comparing proteomic changes in primary human endothelial cells morphogenesis on matrigel to general adhesion mechanisms in cells spreading on culture dish, we pinpoint pathways and proteins modulated by endothelial cells. The cell-extracellular matrix adhesion proteome depends on the adhesion substrate, and a detailed proteomic profile of the extracellular matrix secreted by endothelial cells identified CLEC14A as a matrix component, which binds to MMRN2. We verify deregulated levels of these proteins during tumor angiogenesis in models of multistage carcinogenesis. This is the most in depth quantitative proteomic study of endothelial cell morphogenesis, which shows the potential of applying high accuracy quantitative proteomics to in vitro models of vessel growth to shed new light on mechanisms that accompany pathological angiogenesis. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000359.

  15. iTRAQ-Based Quantitative Proteomic Analysis of Spirulina platensis in Response to Low Temperature Stress

    PubMed Central

    Li, Qingye; Chang, Rong; Sun, Yijun; Li, Bosheng

    2016-01-01

    Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance. PMID:27902743

  16. Quantitative proteomics and terminomics to elucidate the role of ubiquitination and proteolysis in adaptive immunity.

    PubMed

    Klein, Theo; Viner, Rosa I; Overall, Christopher M

    2016-10-28

    Adaptive immunity is the specialized defence mechanism in vertebrates that evolved to eliminate pathogens. Specialized lymphocytes recognize specific protein epitopes through antigen receptors to mount potent immune responses, many of which are initiated by nuclear factor-kappa B activation and gene transcription. Most, if not all, pathways in adaptive immunity are further regulated by post-translational modification (PTM) of signalling proteins, e.g. phosphorylation, citrullination, ubiquitination and proteolytic processing. The importance of PTMs is reflected by genetic or acquired defects in these pathways that lead to a dysfunctional immune response. Here we discuss the state of the art in targeted proteomics and systems biology approaches to dissect the PTM landscape specifically regarding ubiquitination and proteolysis in B- and T-cell activation. Recent advances have occurred in methods for specific enrichment and targeted quantitation. Together with improved instrument sensitivity, these advances enable the accurate analysis of often rare PTM events that are opaque to conventional proteomics approaches, now rendering in-depth analysis and pathway dissection possible. We discuss published approaches, including as a case study the profiling of the N-terminome of lymphocytes of a rare patient with a genetic defect in the paracaspase protease MALT1, a key regulator protease in antigen-driven signalling, which was manifested by elevated linear ubiquitination.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Authors.

  17. iTRAQ-Based Quantitative Proteomic Analysis of Spirulina platensis in Response to Low Temperature Stress.

    PubMed

    Li, Qingye; Chang, Rong; Sun, Yijun; Li, Bosheng

    2016-01-01

    Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance.

  18. Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications.

    PubMed

    Jimenez, Connie R; Verheul, Henk M W

    2014-01-01

    Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

  19. Quantitative proteome analysis of plasma microparticles for the characterization of HCV-induced hepatic cirrhosis and hepatocellular carcinoma.

    PubMed

    Taleb, Raghda Saad Zaghloul; Moez, Pacint; Younan, Doreen; Eisenacher, Martin; Tenbusch, Matthias; Sitek, Barbara; Bracht, Thilo

    2017-12-01

    Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor and a leading cause of cancer-related deaths worldwide. Cirrhosis induced by hepatitis-C virus (HCV) infection is the most critical risk factor for HCC. However, the mechanism of HCV-induced carcinogenesis is not fully understood. Plasma microparticles (PMP) contribute to numerous physiological and pathological processes and contain proteins whose composition correlates to the respective pathophysiological conditions. We analyzed PMP from 22 HCV-induced cirrhosis patients, 16 HCV-positive HCC patients with underlying cirrhosis and 18 healthy controls. PMP were isolated using ultracentrifugation and analyzed via label-free LC-MS/MS. We identified 840 protein groups and quantified 507 proteins. 159 proteins were found differentially abundant between the three experimental groups. PMP in both disease entities displayed remarkable differences in the proteome composition compared to healthy controls. Conversely, the proteome difference between both diseases was minimal. GO analysis revealed that PMP isolated from both diseases were significantly enriched in proteins involved in complement activation, while endopeptidase activity was downregulated exclusively in HCC patients. This study reports for the first time a quantitative proteome analysis for PMP from patients with HCV-induced cirrhosis and HCC. Data are available via ProteomeXchange with identifier PXD005777. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Deciphering the molecular mechanisms underlying sea urchin reversible adhesion: A quantitative proteomics approach.

    PubMed

    Lebesgue, Nicolas; da Costa, Gonçalo; Ribeiro, Raquel Mesquita; Ribeiro-Silva, Cristina; Martins, Gabriel G; Matranga, Valeria; Scholten, Arjen; Cordeiro, Carlos; Heck, Albert J R; Santos, Romana

    2016-04-14

    Marine bioadhesives have unmatched performances in wet environments, being an inspiration for biomedical applications. In sea urchins specialized adhesive organs, tube feet, mediate reversible adhesion, being composed by a disc, producing adhesive and de-adhesive secretions, and a motile stem. After tube foot detachment, the secreted adhesive remains bound to the substratum as a footprint. Sea urchin adhesive is composed by proteins and sugars, but so far only one protein, Nectin, was shown to be over-expressed as a transcript in tube feet discs, suggesting its involvement in sea urchin adhesion. Here we use high-resolution quantitative mass-spectrometry to perform the first study combining the analysis of the differential proteome of an adhesive organ, with the proteome of its secreted adhesive. This strategy allowed us to identify 163 highly over-expressed disc proteins, specifically involved in sea urchin reversible adhesion; to find that 70% of the secreted adhesive components fall within five protein groups, involved in exocytosis and microbial protection; and to provide evidences that Nectin is not only highly expressed in tube feet discs but is an actual component of the adhesive. These results give an unprecedented insight into the molecular mechanisms underlying sea urchin adhesion, and opening new doors to develop wet-reliable, reversible, and ecological biomimetic adhesives. Sea urchins attach strongly but in a reversible manner to substratum, being a valuable source of inspiration for industrial and biomedical applications. Yet, the molecular mechanisms governing reversible adhesion are still poorly studied delaying the engineering of biomimetic adhesives. We used the latest mass spectrometry techniques to analyze the differential proteome of an adhesive organ and the proteome of its secreted adhesive, allowing us to uncover the key players in sea urchin reversible adhesion. We demonstrate, that Nectin, a protein previously pointed out as potentially

  1. Quantitative proteomics links metabolic pathways to specific developmental stages of the plant-pathogenic oomycete Phytophthora capsici.

    PubMed

    Pang, Zhili; Srivastava, Vaibhav; Liu, Xili; Bulone, Vincent

    2017-04-01

    The oomycete Phytophthora capsici is a plant pathogen responsible for important losses to vegetable production worldwide. Its asexual reproduction plays an important role in the rapid propagation and spread of the disease in the field. A global proteomics study was conducted to compare two key asexual life stages of P. capsici, i.e. the mycelium and cysts, to identify stage-specific biochemical processes. A total of 1200 proteins was identified using qualitative and quantitative proteomics. The transcript abundance of some of the enriched proteins was also analysed by quantitative real-time polymerase chain reaction. Seventy-three proteins exhibited different levels of abundance between the mycelium and cysts. The proteins enriched in the mycelium are mainly associated with glycolysis, the tricarboxylic acid (or citric acid) cycle and the pentose phosphate pathway, providing the energy required for the biosynthesis of cellular building blocks and hyphal growth. In contrast, the proteins that are predominant in cysts are essentially involved in fatty acid degradation, suggesting that the early infection stage of the pathogen relies primarily on fatty acid degradation for energy production. The data provide a better understanding of P. capsici biology and suggest potential metabolic targets at the two different developmental stages for disease control. © 2016 BSPP AND JOHN WILEY & SONS LTD.

  2. Global response of Acidithiobacillus ferrooxidans ATCC 53993 to high concentrations of copper: A quantitative proteomics approach.

    PubMed

    Martínez-Bussenius, Cristóbal; Navarro, Claudio A; Orellana, Luis; Paradela, Alberto; Jerez, Carlos A

    2016-08-11

    Acidithiobacillus ferrooxidans is used in industrial bioleaching of minerals to extract valuable metals. A. ferrooxidans strain ATCC 53993 is much more resistant to copper than other strains of this microorganism and it has been proposed that genes present in an exclusive genomic island (GI) of this strain would contribute to its extreme copper tolerance. ICPL (isotope-coded protein labeling) quantitative proteomics was used to study in detail the response of this bacterium to copper. A high overexpression of RND efflux systems and CusF copper chaperones, both present in the genome and the GI of strain ATCC 53993 was found. Also, changes in the levels of the respiratory system proteins such as AcoP and Rus copper binding proteins and several proteins with other predicted functions suggest that numerous metabolic changes are apparently involved in controlling the effects of the toxic metal on this acidophile. Using quantitative proteomics we overview the adaptation mechanisms that biomining acidophiles use to stand their harsh environment. The overexpression of several genes present in an exclusive genomic island strongly suggests the importance of the proteins coded in this DNA region in the high tolerance of A. ferrooxidans ATCC 53993 to metals. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Plant proteome analysis: a 2006 update.

    PubMed

    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

  4. NCI, NHLBI, FDA, AACC, and CMS Collaborate in Advancing Proteomics Regulatory Science | Office of Cancer Clinical Proteomics Research

    Cancer.gov

    Despite great strides in proteomics and the growing number of articles citing the discovery of potential biomarkers, the actual rate of introduction of Food and Drug Administration (FDA) approved protein analytes has been relatively unchanged over the past 10 years. One of reasons for the lack of new protein-based biomarkers approved has been a lack of information and understanding by the proteomics research community to the regulatory process used by the FDA. To address this issue, Dr.

  5. The Proteome of Native Adult Müller Glial Cells From Murine Retina*

    PubMed Central

    Hauser, Alexandra; Lepper, Marlen Franziska; Mayo, Rebecca

    2016-01-01

    To date, the proteomic profiling of Müller cells, the dominant macroglia of the retina, has been hampered because of the absence of suitable enrichment methods. We established a novel protocol to isolate native, intact Müller cells from adult murine retinae at excellent purity which retain in situ morphology and are well suited for proteomic analyses. Two different strategies of sample preparation - an in StageTips (iST) and a subcellular fractionation approach including cell surface protein profiling were used for quantitative liquid chromatography-mass spectrometry (LC-MSMS) comparing Müller cell-enriched to depleted neuronal fractions. Pathway enrichment analyses on both data sets enabled us to identify Müller cell-specific functions which included focal adhesion kinase signaling, signal transduction mediated by calcium as second messenger, transmembrane neurotransmitter transport and antioxidant activity. Pathways associated with RNA processing, cellular respiration and phototransduction were enriched in the neuronal subpopulation. Proteomic results were validated for selected Müller cell genes by quantitative real time PCR, confirming the high expression levels of numerous members of the angiogenic and anti-inflammatory annexins and antioxidant enzymes (e.g. paraoxonase 2, peroxiredoxin 1, 4 and 6). Finally, the significant enrichment of antioxidant proteins in Müller cells was confirmed by measurements on vital retinal cells using the oxidative stress indicator CM-H2DCFDA. In contrast to photoreceptors or bipolar cells, Müller cells were most efficiently protected against H2O2-induced reactive oxygen species formation, which is in line with the protein repertoire identified in the proteomic profiling. Our novel approach to isolate intact glial cells from adult retina in combination with proteomic profiling enabled the identification of novel Müller glia specific proteins, which were validated as markers and for their functional impact in glial

  6. Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics.

    PubMed

    Bennett, Eric J; Rush, John; Gygi, Steven P; Harper, J Wade

    2010-12-10

    Dynamic reorganization of signaling systems frequently accompanies pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex absolute quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules, whereas only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. Copyright © 2010 Elsevier Inc. All rights reserved.

  7. Comprehensive and Quantitative Proteomic Analysis of Metamorphosis-Related Proteins in the Veined Rapa Whelk, Rapana venosa.

    PubMed

    Song, Hao; Wang, Hai-Yan; Zhang, Tao

    2016-06-15

    Larval metamorphosis of the veined rapa whelk (Rapana venosa) is a pelagic to benthic transition that involves considerable structural and physiological changes. Because metamorphosis plays a pivotal role in R. venosa commercial breeding and natural populations, the endogenous proteins that drive this transition attract considerable interest. This study is the first to perform a comprehensive and quantitative proteomic analysis related to metamorphosis in a marine gastropod. We analyzed the proteomes of competent R. venosa larvae and post-larvae, resulting in the identification of 5312 proteins, including 470 that were downregulated and 668 that were upregulated after metamorphosis. The differentially expressed proteins reflected multiple processes involved in metamorphosis, including cytoskeleton and cell adhesion, ingestion and digestion, stress response and immunity, as well as specific tissue development. Our data improve understanding of the physiological traits controlling R. venosa metamorphosis and provide a solid basis for further study.

  8. Determining protein complex connectivity using a probabilistic deletion network derived from quantitative proteomics.

    PubMed

    Sardiu, Mihaela E; Gilmore, Joshua M; Carrozza, Michael J; Li, Bing; Workman, Jerry L; Florens, Laurence; Washburn, Michael P

    2009-10-06

    Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.

  9. Condenser: a statistical aggregation tool for multi-sample quantitative proteomic data from Matrix Science Mascot Distiller™.

    PubMed

    Knudsen, Anders Dahl; Bennike, Tue; Kjeldal, Henrik; Birkelund, Svend; Otzen, Daniel Erik; Stensballe, Allan

    2014-05-30

    We describe Condenser, a freely available, comprehensive open-source tool for merging multidimensional quantitative proteomics data from the Matrix Science Mascot Distiller Quantitation Toolbox into a common format ready for subsequent bioinformatic analysis. A number of different relative quantitation technologies, such as metabolic (15)N and amino acid stable isotope incorporation, label-free and chemical-label quantitation are supported. The program features multiple options for curative filtering of the quantified peptides, allowing the user to choose data quality thresholds appropriate for the current dataset, and ensure the quality of the calculated relative protein abundances. Condenser also features optional global normalization, peptide outlier removal, multiple testing and calculation of t-test statistics for highlighting and evaluating proteins with significantly altered relative protein abundances. Condenser provides an attractive addition to the gold-standard quantitative workflow of Mascot Distiller, allowing easy handling of larger multi-dimensional experiments. Source code, binaries, test data set and documentation are available at http://condenser.googlecode.com/. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

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

    Zhou, Jian-Ying; Chen, Lijun; Zhang, Bai

    The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assessmore » the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.« less

  11. Quantitative structure-activity relationship: promising advances in drug discovery platforms.

    PubMed

    Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

    2015-12-01

    Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

  12. Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics.

    PubMed

    Mudaliar, Manikhandan; Tassi, Riccardo; Thomas, Funmilola C; McNeilly, Tom N; Weidt, Stefan K; McLaughlin, Mark; Wilson, David; Burchmore, Richard; Herzyk, Pawel; Eckersall, P David; Zadoks, Ruth N

    2016-08-16

    Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously.

  13. Quantitative proteomic view on secreted, cell surface-associated, and cytoplasmic proteins of the methicillin-resistant human pathogen Staphylococcus aureus under iron-limited conditions.

    PubMed

    Hempel, Kristina; Herbst, Florian-Alexander; Moche, Martin; Hecker, Michael; Becher, Dörte

    2011-04-01

    Staphylococcus aureus is capable of colonizing and infecting humans by its arsenal of surface-exposed and secreted proteins. Iron-limited conditions in mammalian body fluids serve as a major environmental signal to bacteria to express virulence determinants. Here we present a comprehensive, gel-free, and GeLC-MS/MS-based quantitative proteome profiling of S. aureus under this infection-relevant situation. (14)N(15)N metabolic labeling and three complementing approaches were combined for relative quantitative analyses of surface-associated proteins. The surface-exposed and secreted proteome profiling approaches comprise trypsin shaving, biotinylation, and precipitation of the supernatant. By analysis of the outer subproteomic and cytoplasmic protein fraction, 1210 proteins could be identified including 221 surface-associated proteins. Thus, access was enabled to 70% of the predicted cell wall-associated proteins, 80% of the predicted sortase substrates, two/thirds of lipoproteins and more than 50% of secreted and cytoplasmic proteins. For iron-deficiency, 158 surface-associated proteins were quantified. Twenty-nine proteins were found in altered amounts showing particularly surface-exposed proteins strongly induced, such as the iron-regulated surface determinant proteins IsdA, IsdB, IsdC and IsdD as well as lipid-anchored iron compound-binding proteins. The work presents a crucial subject for understanding S. aureus pathophysiology by the use of methods that allow quantitative surface proteome profiling.

  14. Investigation of Pokemon-regulated proteins in hepatocellular carcinoma using mass spectrometry-based multiplex quantitative proteomics.

    PubMed

    Bi, Xin; Jin, Yibao; Gao, Xiang; Liu, Feng; Gao, Dan; Jiang, Yuyang; Liu, Hongxia

    2013-01-01

    Pokemon is a transcription regulator involved in embryonic development, cellular differentiation and oncogenesis. It is aberrantly overexpressed in multiple human cancers including Hepatocellular carcinoma (HCC) and is considered as a promising biomarker for HCC. In this work, the isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy was used to investigate the proteomic profile associated with Pokemon in human HCC cell line QGY7703 and human hepatocyte line HL7702. Samples were labeled with four-plex iTRAQ reagents followed by two-dimensional liquid chromatography coupled with tandem mass spectrometry analysis. A total of 24 differentially expressed proteins were selected as significant. Nine proteins were potentially up-regulated by Pokemon while 15 proteins were potentially down-regulated and many proteins were previously identified as potential biomarkers for HCC. Gene ontology (GO) term enrichment revealed that the listed proteins were mainly involved in DNA metabolism and biosynthesis process. The changes of glucose-6-phosphate 1-dehydrogenase (G6PD, up-regulated) and ribonucleoside-diphosphate reductase large sub-unit (RIM1, down-regulated) were validated by Western blotting analysis and denoted as Pokemon's function of oncogenesis. We also found that Pokemon potentially repressed the expression of highly clustered proteins (MCM3, MCM5, MCM6, MCM7) which played key roles in promoting DNA replication. Altogether, our results may help better understand the role of Pokemon in HCC and promote the clinical applications.

  15. Discovery and Targeted Proteomics on Cutaneous Biopsies Infected by Borrelia to Investigate Lyme Disease*

    PubMed Central

    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

  16. Quantitative proteomics reveals a role of JAZ7 in plant defense response to Pseudomonas syringae DC3000.

    PubMed

    Zhang, Tong; Meng, Li; Kong, Wenwen; Yin, Zepeng; Wang, Yang; Schneider, Jacqueline D; Chen, Sixue

    2018-03-20

    Jasmonate ZIM-domain (JAZ) proteins are key transcriptional repressors regulating various biological processes. Although many studies have studied JAZ proteins by genetic and biochemical analyses, little is known about JAZ7-associated global protein networks and how JAZ7 contributes to bacterial pathogen defense. In this study, we aim to fill this knowledge gap by conducting unbiased large-scale quantitative proteomics using tandem mass tags (TMT). We compared the proteomes of a JAZ7 knock-out line, a JAZ7 overexpression line, as well as the wild type Arabidopsis plants in the presence and absence of Pseudomonas syringae DC3000 infection. Both pairwise comparison and multi-factor analysis of variance reveal that differential proteins are enriched in biological processes such as primary and secondary metabolism, redox regulation, and response to stress. The differential regulation in these pathways may account for the alterations in plant size, redox homeostasis and accumulation of glucosinolates. In addition, possible interplay between genotype and environment is suggested as the abundance of seven proteins is influenced by the interaction of the two factors. Collectively, we demonstrate a role of JAZ7 in pathogen defense and provide a list of proteins that are uniquely responsive to genetic disruption, pathogen infection, or the interaction between genotypes and environmental factors. We report proteomic changes as a result of genetic perturbation of JAZ7, and the contribution of JAZ7 in plant immunity. Specifically, the similarity between the proteomes of a JAZ7 knockout mutant and the wild type plants confirmed the functional redundancy of JAZs. In contrast, JAZ7 overexpression plants were much different, and proteomic analysis of the JAZ7 overexpression plants under Pst DC3000 infection revealed that JAZ7 may regulate plant immunity via ROS modulation, energy balance and glucosinolate biosynthesis. Multiple variate analysis for this two-factor proteomics

  17. Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human.

    PubMed

    Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

    2016-04-13

    Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish.

  18. Comprehensive and quantitative proteomic analyses of zebrafish plasma reveals conserved protein profiles between genders and between zebrafish and human

    PubMed Central

    Li, Caixia; Tan, Xing Fei; Lim, Teck Kwang; Lin, Qingsong; Gong, Zhiyuan

    2016-01-01

    Omic approaches have been increasingly used in the zebrafish model for holistic understanding of molecular events and mechanisms of tissue functions. However, plasma is rarely used for omic profiling because of the technical challenges in collecting sufficient blood. In this study, we employed two mass spectrometric (MS) approaches for a comprehensive characterization of zebrafish plasma proteome, i.e. conventional shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS) for an overview study and quantitative SWATH (Sequential Window Acquisition of all THeoretical fragment-ion spectra) for comparison between genders. 959 proteins were identified in the shotgun profiling with estimated concentrations spanning almost five orders of magnitudes. Other than the presence of a few highly abundant female egg yolk precursor proteins (vitellogenins), the proteomic profiles of male and female plasmas were very similar in both number and abundance and there were basically no other highly gender-biased proteins. The types of plasma proteins based on IPA (Ingenuity Pathway Analysis) classification and tissue sources of production were also very similar. Furthermore, the zebrafish plasma proteome shares significant similarities with human plasma proteome, in particular in top abundant proteins including apolipoproteins and complements. Thus, the current study provided a valuable dataset for future evaluation of plasma proteins in zebrafish. PMID:27071722

  19. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.

    PubMed

    Lazar, Cosmin; Gatto, Laurent; Ferro, Myriam; Bruley, Christophe; Burger, Thomas

    2016-04-01

    Missing values are a genuine issue in label-free quantitative proteomics. Recent works have surveyed the different statistical methods to conduct imputation and have compared them on real or simulated data sets and recommended a list of missing value imputation methods for proteomics application. Although insightful, these comparisons do not account for two important facts: (i) depending on the proteomics data set, the missingness mechanism may be of different natures and (ii) each imputation method is devoted to a specific type of missingness mechanism. As a result, we believe that the question at stake is not to find the most accurate imputation method in general but instead the most appropriate one. We describe a series of comparisons that support our views: For instance, we show that a supposedly "under-performing" method (i.e., giving baseline average results), if applied at the "appropriate" time in the data-processing pipeline (before or after peptide aggregation) on a data set with the "appropriate" nature of missing values, can outperform a blindly applied, supposedly "better-performing" method (i.e., the reference method from the state-of-the-art). This leads us to formulate few practical guidelines regarding the choice and the application of an imputation method in a proteomics context.

  20. Quantitative Analysis of the Human Milk Whey Proteome Reveals Developing Milk and Mammary-Gland Functions across the First Year of Lactation

    PubMed Central

    Zhang, Qiang; Cundiff, Judy K.; Maria, Sarah D.; McMahon, Robert J.; Woo, Jessica G.; Davidson, Barbara S.; Morrow, Ardythe L.

    2013-01-01

    In-depth understanding of the changing functions of human milk (HM) proteins and the corresponding physiological adaptions of the lactating mammary gland has been inhibited by incomplete knowledge of the HM proteome. We analyzed the HM whey proteome (n = 10 women with samples at 1 week and 1, 3, 6, 9 and 12 months) using a quantitative proteomic approach. One thousand three hundred and thirty three proteins were identified with 615 being quantified. Principal component analysis revealed a transition in the HM whey proteome-throughout the first year of lactation. Abundance changes in IgG, sIgA and sIgM display distinct features during the first year. Complement components and other acute-phase proteins are generally at higher levels in early lactation. Proteomic analysis further suggests that the sources of milk fatty acids (FA) shift from more direct blood influx to more de novo mammary synthesis over lactation. The abundances of the majority of glycoproteins decline over lactation, which is consistent with increased enzyme expression in glycoprotein degradation and decreased enzyme expression in glycoprotein synthesis. Cellular detoxification machinery may be transformed as well, thereby accommodating increased metabolic activities in late lactation. The multiple developing functions of HM proteins and the corresponding mammary adaption become more apparent from this study. PMID:28250401

  1. Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

    PubMed Central

    Kuo, Kung-Kai; Kuo, Chao-Jen; Chiu, Chiang-Yen; Liang, Shih-Shin; Huang, Chun-Hao; Chi, Shu-Wen; Tsai, Kun-Bow; Chen, Chiao-Yun; Hsi, Edward; Cheng, Kuang-Hung; Chiou, Shyh-Horng

    2016-01-01

    Objectives The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling. Methods Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion. Results Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining. Conclusions The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC. PMID:26262590

  2. Quantitative proteomic analysis of the Salmonella-lettuce interaction

    PubMed Central

    Zhang, Yuping; Nandakumar, Renu; Bartelt-Hunt, Shannon L; Snow, Daniel D; Hodges, Laurie; Li, Xu

    2014-01-01

    Human pathogens can internalize food crops through root and surface uptake and persist inside crop plants. The goal of the study was to elucidate the global modulation of bacteria and plant protein expression after Salmonella internalizes lettuce. A quantitative proteomic approach was used to analyse the protein expression of Salmonella enterica serovar Infantis and lettuce cultivar Green Salad Bowl 24 h after infiltrating S. Infantis into lettuce leaves. Among the 50 differentially expressed proteins identified by comparing internalized S. Infantis against S. Infantis grown in Luria Broth, proteins involved in glycolysis were down-regulated, while one protein involved in ascorbate uptake was up-regulated. Stress response proteins, especially antioxidant proteins, were up-regulated. The modulation in protein expression suggested that internalized S. Infantis might utilize ascorbate as a carbon source and require multiple stress response proteins to cope with stresses encountered in plants. On the other hand, among the 20 differentially expressed lettuce proteins, proteins involved in defense response to bacteria were up-regulated. Moreover, the secreted effector PipB2 of S. Infantis and R proteins of lettuce were induced after bacterial internalization into lettuce leaves, indicating human pathogen S. Infantis triggered the defense mechanisms of lettuce, which normally responds to plant pathogens. PMID:24512637

  3. Quantitation of heat-shock proteins in clinical samples using mass spectrometry.

    PubMed

    Kaur, Punit; Asea, Alexzander

    2011-01-01

    Mass spectrometry (MS) is a powerful analytical tool for proteomics research and drug and biomarker discovery. MS enables identification and quantification of known and unknown compounds by revealing their structural and chemical properties. Proper sample preparation for MS-based analysis is a critical step in the proteomics workflow because the quality and reproducibility of sample extraction and preparation for downstream analysis significantly impact the separation and identification capabilities of mass spectrometers. The highly expressed proteins represent potential biomarkers that could aid in diagnosis, therapy, or drug development. Because the proteome is so complex, there is no one standard method for preparing protein samples for MS analysis. Protocols differ depending on the type of sample, source, experiment, and method of analysis. Molecular chaperones play significant roles in almost all biological functions due to their capacity for detecting intracellular denatured/unfolded proteins, initiating refolding or denaturation of such malfolded protein sequences and more recently for their role in the extracellular milieu as chaperokines. In this chapter, we describe the latest techniques for quantitating the expression of molecular chaperones in human clinical samples.

  4. Label-free protein quantification using LC-coupled ion trap or FT mass spectrometry: Reproducibility, linearity, and application with complex proteomes.

    PubMed

    Wang, Guanghui; Wu, Wells W; Zeng, Weihua; Chou, Chung-Lin; Shen, Rong-Fong

    2006-05-01

    A critical step in protein biomarker discovery is the ability to contrast proteomes, a process referred generally as quantitative proteomics. While stable-isotope labeling (e.g., ICAT, 18O- or 15N-labeling, or AQUA) remains the core technology used in mass spectrometry-based proteomic quantification, increasing efforts have been directed to the label-free approach that relies on direct comparison of peptide peak areas between LC-MS runs. This latter approach is attractive to investigators for its simplicity as well as cost effectiveness. In the present study, the reproducibility and linearity of using a label-free approach to highly complex proteomes were evaluated. Various amounts of proteins from different proteomes were subjected to repeated LC-MS analyses using an ion trap or Fourier transform mass spectrometer. Highly reproducible data were obtained between replicated runs, as evidenced by nearly ideal Pearson's correlation coefficients (for ion's peak areas or retention time) and average peak area ratios. In general, more than 50% and nearly 90% of the peptide ion ratios deviated less than 10% and 20%, respectively, from the average in duplicate runs. In addition, the multiplicity ratios of the amounts of proteins used correlated nicely with the observed averaged ratios of peak areas calculated from detected peptides. Furthermore, the removal of abundant proteins from the samples led to an improvement in reproducibility and linearity. A computer program has been written to automate the processing of data sets from experiments with groups of multiple samples for statistical analysis. Algorithms for outlier-resistant mean estimation and for adjusting statistical significance threshold in multiplicity of testing were incorporated to minimize the rate of false positives. The program was applied to quantify changes in proteomes of parental and p53-deficient HCT-116 human cells and found to yield reproducible results. Overall, this study demonstrates an alternative

  5. Quantitative proteome profile of water deficit stress responses in eastern cottonwood ( Populus deltoides) leaves

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

    Abraham, Paul E.; Garcia, Benjamin J.; Gunter, Lee E.

    Drought stress is a recurring feature of world climate and the single most important factor influencing agricultural yield worldwide. Plants display highly variable, species-specific responses to drought and these responses are multifaceted, requiring physiological and morphological changes influenced by genetic and molecular mechanisms. Moreover, the reproducibility of water deficit studies is very cumbersome, which significantly impedes research on drought tolerance, because how a plant responds is highly influenced by the timing, duration, and intensity of the water deficit. Despite progress in the identification of drought-related mechanisms in many plants, the molecular basis of drought resistance remains to be fully understoodmore » in trees, particularly in poplar species because their wide geographic distribution results in varying tolerances to drought. Herein, we aimed to better understand this complex phenomenon in eastern cottonwood ( Populus deltoides) by performing a detailed contrast of the proteome changes between two different water deficit experiments to identify functional intersections and divergences in proteome responses. We investigated plants subjected to cyclic water deficit and compared these responses to plants subjected to prolonged acute water deficit. In total, we identified 108,012 peptide sequences across both experiments that provided insight into the quantitative state of 22,737 Populus gene models and 8,199 functional protein groups in response to drought. Together, these datasets provide the most comprehensive insight into proteome drought responses in poplar to date and a direct proteome comparison between short period dehydration shock and cyclic, post-drought re-watering. Altogether, this investigation provides novel insights into drought avoidance mechanisms that are distinct from progressive drought stress. Additionally, we identified proteins that have been associated as drought-relevant in previous studies. Importantly

  6. Quantitative proteome profile of water deficit stress responses in eastern cottonwood ( Populus deltoides) leaves

    DOE PAGES

    Abraham, Paul E.; Garcia, Benjamin J.; Gunter, Lee E.; ...

    2018-02-15

    Drought stress is a recurring feature of world climate and the single most important factor influencing agricultural yield worldwide. Plants display highly variable, species-specific responses to drought and these responses are multifaceted, requiring physiological and morphological changes influenced by genetic and molecular mechanisms. Moreover, the reproducibility of water deficit studies is very cumbersome, which significantly impedes research on drought tolerance, because how a plant responds is highly influenced by the timing, duration, and intensity of the water deficit. Despite progress in the identification of drought-related mechanisms in many plants, the molecular basis of drought resistance remains to be fully understoodmore » in trees, particularly in poplar species because their wide geographic distribution results in varying tolerances to drought. Herein, we aimed to better understand this complex phenomenon in eastern cottonwood ( Populus deltoides) by performing a detailed contrast of the proteome changes between two different water deficit experiments to identify functional intersections and divergences in proteome responses. We investigated plants subjected to cyclic water deficit and compared these responses to plants subjected to prolonged acute water deficit. In total, we identified 108,012 peptide sequences across both experiments that provided insight into the quantitative state of 22,737 Populus gene models and 8,199 functional protein groups in response to drought. Together, these datasets provide the most comprehensive insight into proteome drought responses in poplar to date and a direct proteome comparison between short period dehydration shock and cyclic, post-drought re-watering. Altogether, this investigation provides novel insights into drought avoidance mechanisms that are distinct from progressive drought stress. Additionally, we identified proteins that have been associated as drought-relevant in previous studies. Importantly

  7. Proteomics: from hypothesis to quantitative assay on a single platform. Guidelines for developing MRM assays using ion trap mass spectrometers.

    PubMed

    Han, Bomie; Higgs, Richard E

    2008-09-01

    High-throughput HPLC-mass spectrometry (HPLC-MS) is routinely used to profile biological samples for potential protein markers of disease, drug efficacy and toxicity. The discovery technology has advanced to the point where translating hypotheses from proteomic profiling studies into clinical use is the bottleneck to realizing the full potential of these approaches. The first step in this translation is the development and analytical validation of a higher throughput assay with improved sensitivity and selectivity relative to typical profiling assays. Multiple reaction monitoring (MRM) assays are an attractive approach for this stage of biomarker development given their improved sensitivity and specificity, the speed at which the assays can be developed and the quantitative nature of the assay. While the profiling assays are performed with ion trap mass spectrometers, MRM assays are traditionally developed in quadrupole-based mass spectrometers. Development of MRM assays from the same instrument used in the profiling analysis enables a seamless and rapid transition from hypothesis generation to validation. This report provides guidelines for rapidly developing an MRM assay using the same mass spectrometry platform used for profiling experiments (typically ion traps) and reviews methodological and analytical validation considerations. The analytical validation guidelines presented are drawn from existing practices on immunological assays and are applicable to any mass spectrometry platform technology.

  8. Proteomic analyses of host and pathogen responses during bovine mastitis.

    PubMed

    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.

  9. ABRF-PRG07: advanced quantitative proteomics study.

    PubMed

    Falick, Arnold M; Lane, William S; Lilley, Kathryn S; MacCoss, Michael J; Phinney, Brett S; Sherman, Nicholas E; Weintraub, Susan T; Witkowska, H Ewa; Yates, Nathan A

    2011-04-01

    A major challenge for core facilities is determining quantitative protein differences across complex biological samples. Although there are numerous techniques in the literature for relative and absolute protein quantification, the majority is nonroutine and can be challenging to carry out effectively. There are few studies comparing these technologies in terms of their reproducibility, accuracy, and precision, and no studies to date deal with performance across multiple laboratories with varied levels of expertise. Here, we describe an Association of Biomolecular Resource Facilities (ABRF) Proteomics Research Group (PRG) study based on samples composed of a complex protein mixture into which 12 known proteins were added at varying but defined ratios. All of the proteins were present at the same concentration in each of three tubes that were provided. The primary goal of this study was to allow each laboratory to evaluate its capabilities and approaches with regard to: detection and identification of proteins spiked into samples that also contain complex mixtures of background proteins and determination of relative quantities of the spiked proteins. The results returned by 43 participants were compiled by the PRG, which also collected information about the strategies used to assess overall performance and as an aid to development of optimized protocols for the methodologies used. The most accurate results were generally reported by the most experienced laboratories. Among laboratories that used the same technique, values that were closer to the expected ratio were obtained by more experienced groups.

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

    PubMed

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

    2013-01-04

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

  11. Assay Portal | Office of Cancer Clinical Proteomics Research

    Cancer.gov

    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.

  12. The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard.

    PubMed

    Qi, Da; Zhang, Huaizhong; Fan, Jun; Perkins, Simon; Pisconti, Addolorata; Simpson, Deborah M; Bessant, Conrad; Hubbard, Simon; Jones, Andrew R

    2015-09-01

    The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)-level quantification values from peptide-level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC-MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in-built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq-lib/. © 2015 The Authors. PROTEOMICS Published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. PatternLab for proteomics 4.0: A one-stop shop for analyzing shotgun proteomic data

    PubMed Central

    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

  14. Quantitative Proteomic Profiling of Prostate Cancer Reveals a Role for miR-128 in Prostate Cancer*

    PubMed Central

    Khan, Amjad P.; Poisson, Laila M.; Bhat, Vadiraja B.; Fermin, Damian; Zhao, Rong; Kalyana-Sundaram, Shanker; Michailidis, George; Nesvizhskii, Alexey I.; Omenn, Gilbert S.; Chinnaiyan, Arul M.; Sreekumar, Arun

    2010-01-01

    Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of biomarkers of cancer invasion and disease aggressiveness. Although alterations in gene expression have been extensively quantified during neoplastic progression, complementary analyses of proteomic changes have been limited. Here we interrogate the proteomic alterations in a cohort of 15 prostate-derived tissues that included five each from adjacent benign prostate, clinically localized prostate cancer, and metastatic disease from distant sites. The experimental strategy couples isobaric tags for relative and absolute quantitation with multidimensional liquid phase peptide fractionation followed by tandem mass spectrometry. Over 1000 proteins were quantified across the specimens and delineated into clinically localized and metastatic prostate cancer-specific signatures. Included in these class-specific profiles were both proteins that were known to be dysregulated during prostate cancer progression and new ones defined by this study. Enrichment analysis of the prostate cancer-specific proteomic signature, to gain insight into the functional consequences of these alterations, revealed involvement of miR-128-a/b regulation during prostate cancer progression. This finding was validated using real time PCR analysis for microRNA transcript levels in an independent set of 15 clinical specimens. miR-128 levels were elevated in benign prostate epithelial cell lines compared with invasive prostate cancer cells. Knockdown of miR-128 induced invasion in benign prostate epithelial cells, whereas its overexpression attenuated invasion in prostate cancer cells. Taken together, our profiles of the proteomic alterations of prostate cancer progression revealed miR-128 as a potentially important negative regulator of prostate cancer cell invasion. PMID:19955085

  15. Infrared Multiphoton Dissociation for Quantitative Shotgun Proteomics

    PubMed Central

    Ledvina, Aaron R.; Lee, M. Violet; McAlister, Graeme C.; Westphall, Michael S.; Coon, Joshua J.

    2012-01-01

    We modified a dual-cell linear ion trap mass spectrometer to perform infrared multiphoton dissociation (IRMPD) in the low pressure trap of a dual-cell quadrupole linear ion trap (dual cell QLT) and perform large-scale IRMPD analyses of complex peptide mixtures. Upon optimization of activation parameters (precursor q-value, irradiation time, and photon flux), IRMPD subtly, but significantly outperforms resonant excitation CAD for peptides identified at a 1% false-discovery rate (FDR) from a yeast tryptic digest (95% confidence, p = 0.019). We further demonstrate that IRMPD is compatible with the analysis of isobaric-tagged peptides. Using fixed QLT RF amplitude allows for the consistent retention of reporter ions, but necessitates the use of variable IRMPD irradiation times, dependent upon precursor mass-to-charge (m/z). We show that IRMPD activation parameters can be tuned to allow for effective peptide identification and quantitation simultaneously. We thus conclude that IRMPD performed in a dual-cell ion trap is an effective option for the large-scale analysis of both unmodified and isobaric-tagged peptides. PMID:22480380

  16. Coatomer subunit beta 2 (COPB2), identified by label-free quantitative proteomics, regulates cell proliferation and apoptosis in human prostate carcinoma cells.

    PubMed

    Mi, Yuanyuan; Sun, Chuanyu; Wei, Bingbing; Sun, Feiyu; Guo, Yijun; Hu, Qingfeng; Ding, Weihong; Zhu, Lijie; Xia, Guowei

    2018-01-01

    Label-free quantitative proteomics has broad applications in the identification of differentially expressed proteins. Here, we applied this method to identify differentially expressed proteins (such as coatomer subunit beta 2 [COPB2]) and evaluated the functions and molecular mechanisms of these proteins in prostate cancer (PCA) cell proliferation. Proteins extracted from surgically resected PCA tissues and adjacent tissues of 3 patients were analyzed by label-free quantitative proteomics. The target protein was confirmed by bioinformatics and GEO dataset analyses. To investigate the role of the target protein in PCA, we used lentivirus-mediated small-interfering RNA (siRNA) to knockdown protein expression in the prostate carcinoma cell line, CWR22RV1 cells and assessed gene and protein expression by reverse transcription quantitative polymerase chain reaction and western blotting. CCK8 and colony formation assays were conducted to evaluate cell proliferation. Cell cycle distributions and apoptosis were assayed by flow cytometry. We selected the differentiation-related protein COPB2 as our target protein based on the results of label-free quantitative proteomics. High expression of COPB2 was found in PCA tissue and was related to poor overall survival based on a public dataset. Cell proliferation was significantly inhibited in COPB2-knockdown CWR22RV1 cells, as demonstrated by CCK8 and colony formation assays. Additionally, the apoptosis rate and percentage of cells in the G 1 phase were increased in COPB2-knockdown cells compared with those in control cells. CDK2, CDK4, and cyclin D1 were downregulated, whereas p21 Waf1/Cip1 and p27 Kip1 were upregulated, affecting the cell cycle signaling pathway. COPB2 significantly promoted CWR22RV1 cell proliferation through the cell cycle signaling pathway. Thus, silencing of COPB2 may have therapeutic applications in PCA. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Proteomic and N-glycoproteomic quantification reveal aberrant changes in the human saliva of oral ulcer patients.

    PubMed

    Zhang, Ying; Wang, Xi; Cui, Dan; Zhu, Jun

    2016-12-01

    Human whole saliva is a vital body fluid for studying the physiology and pathology of the oral cavity. As a powerful technique for biomarker discovery, MS-based proteomic strategies have been introduced for saliva analysis and identified hundreds of proteins and N-glycosylation sites. However, there is still a lack of quantitative analysis, which is necessary for biomarker screening and biological research. In this study, we establish an integrated workflow by the combination of stable isotope dimethyl labeling, HILIC enrichment, and high resolution MS for both quantification of the global proteome and N-glycoproteome of human saliva from oral ulcer patients. With the help of advanced bioinformatics, we comprehensively studied oral ulcers at both protein and glycoprotein scales. Bioinformatics analyses revealed that starch digestion and protein degradation activities are inhibited while the immune response is promoted in oral ulcer saliva. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Quantitative profiling of drug-associated proteomic alterations by combined 2-nitrobenzenesulfenyl chloride (NBS) isotope labeling and 2DE/MS identification.

    PubMed

    Ou, Keli; Kesuma, Djohan; Ganesan, Kumaresan; Yu, Kun; Soon, Sou Yen; Lee, Suet Ying; Goh, Xin Pei; Hooi, Michelle; Chen, Wei; Jikuya, Hiroyuki; Ichikawa, Tetsuo; Kuyama, Hiroki; Matsuo, Ei-ichi; Nishimura, Osamu; Tan, Patrick

    2006-09-01

    The identification of drug-responsive biomarkers in complex protein mixtures is an important goal of quantitative proteomics. Here, we describe a novel approach for identifying such drug-induced protein alterations, which combines 2-nitrobenzenesulfenyl chloride (NBS) tryptophan labeling with two-dimensional gel electrophoresis (2DE)/mass spectrometry (MS). Lysates from drug-treated and control samples are labeled with light or heavy NBS moiety and separated on a common 2DE gel, and protein alterations are identified by MS through the differential intensity of paired NBS peptide peaks. Using NBS/2DE/MS, we profiled the proteomic alterations induced by tamoxifen (TAM) in the estrogen receptor (ER) positive MCF-7 breast cancer cell line. Of 88 protein spots that significantly changed upon TAM treatment, 44 spots representing 23 distinct protein species were successfully identified with NBS-paired peptides. Of these 23 TAM-altered proteins, 16 (70%) have not been previously associated with TAM or ER activity. We found the NBS labeling procedure to be both technically and biologically reproducible, and the NBS/2DE/MS alterations exhibited good concordance with conventional 2DE differential protein quantitation, with discrepancies largely due to the comigration of distinct proteins in the regular 2DE gels. To validate the NBS/2DE/MS results, we used immunoblotting to confirm GRP78, CK19, and PA2G4 as bona fide TAM-regulated proteins. Furthermore, we demonstrate that PA2G4 expression can serve as a novel prognostic factor for disease-free survival in two independent breast cancer patient cohorts. To our knowledge, this is the first report describing the proteomic changes in breast cancer cells induced by TAM, the most commonly used selective estrogen receptor modulator (SERM). Our results indicate that NBS/2DE/MS may represent a more reliable approach for cellular protein quantitation than conventional 2DE approaches.

  19. Label-free Quantitative Proteomics of Mouse Cerebrospinal Fluid Detects β-Site APP Cleaving Enzyme (BACE1) Protease Substrates In Vivo*

    PubMed Central

    Dislich, Bastian; Wohlrab, Felix; Bachhuber, Teresa; Müller, Stephan A.; Kuhn, Peer-Hendrik; Hogl, Sebastian; Meyer-Luehmann, Melanie; Lichtenthaler, Stefan F.

    2015-01-01

    Analysis of murine cerebrospinal fluid (CSF) by quantitative mass spectrometry is challenging because of low CSF volume, low total protein concentration, and the presence of highly abundant proteins such as albumin. We demonstrate that the CSF proteome of individual mice can be analyzed in a quantitative manner to a depth of several hundred proteins in a robust and simple workflow consisting of single ultra HPLC runs on a benchtop mass spectrometer. The workflow is validated by a comparative analysis of BACE1−/− and wild-type mice using label-free quantification. The protease BACE1 cleaves the amyloid precursor protein (APP) as well as several other substrates and is a major drug target in Alzheimer's disease. We identified a total of 715 proteins with at least 2 unique peptides and quantified 522 of those proteins in CSF from BACE1−/− and wild-type mice. Several proteins, including the known BACE1 substrates APP, APLP1, CHL1 and contactin-2 showed lower abundance in the CSF of BACE1−/− mice, demonstrating that BACE1 substrate identification is possible from CSF. Additionally, ectonucleotide pyrophosphatase 5 was identified as a novel BACE1 substrate and validated in cells using immunoblots and by an in vitro BACE1 protease assay. Likewise, receptor-type tyrosine-protein phosphatase N2 and plexin domain-containing 2 were confirmed as BACE1 substrates by in vitro assays. Taken together, our study shows the deepest characterization of the mouse CSF proteome to date and the first quantitative analysis of the CSF proteome of individual mice. The BACE1 substrates identified in CSF may serve as biomarkers to monitor BACE1 activity in Alzheimer patients treated with BACE inhibitors. PMID:26139848

  20. Serum quantitative proteomic analysis reveals potential zinc-associated biomarkers for nonbacterial prostatitis.

    PubMed

    Yang, Xiaoli; Li, Hongtao; Zhang, Chengdong; Lin, Zhidi; Zhang, Xinhua; Zhang, Youjie; Yu, Yanbao; Liu, Kun; Li, Muyan; Zhang, Yuening; Lv, Wenxin; Xie, Yuanliang; Lu, Zheng; Wu, Chunlei; Teng, Ruobing; Lu, Shaoming; He, Min; Mo, Zengnan

    2015-10-01

    Prostatitis is one of the most common urological problems afflicting adult men. The etiology and pathogenesis of nonbacterial prostatitis, which accounts for 90-95% of cases, is largely unknown. As serum proteins often indicate the overall pathologic status of patients, we hypothesized that protein biomarkers of prostatitis might be identified by comparing the serum proteomes of patients with and without nonbacterial prostatitis. All untreated samples were collected from subjects attending the Fangchenggang Area Male Health and Examination Survey (FAMHES). We profiled pooled serum samples from four carefully selected groups of patients (n = 10/group) representing the various categories of nonbacterial prostatitis (IIIa, IIIb, and IV) and matched healthy controls using a mass spectrometry-based 4-plex iTRAQ proteomic approach. More than 160 samples were validated by ELISA. Overall, 69 proteins were identified. Among them, 42, 52, and 37 proteins were identified with differential expression in Category IIIa, IIIb, and IV prostatitis, respectively. The 19 common proteins were related to immunity and defense, ion binding, transport, and proteolysis. Two zinc-binding proteins, superoxide dismutase 3 (SOD3), and carbonic anhydrase I (CA1), were significantly higher in all types of prostatitis than in the control. A receiver operating characteristic curve estimated sensitivities of 50.4 and 68.1% and specificities of 92.1 and 83.8% for CA1 and SOD3, respectively, in detecting nonbacterial prostatitis. The serum CA1 concentration was inversely correlated to the zinc concentration in expressed-prostatic secretions. Our findings suggest that SOD3 and CA1 are potential diagnostic markers of nonbacterial prostatitis, although further large-scale studies are required. The molecular profiles of nonbacterial prostatitis pathogenesis may lay a foundation for discovery of new therapies. © 2015 Wiley Periodicals, Inc.

  1. Quantitative Proteomics by Metabolic Labeling of Model Organisms*

    PubMed Central

    Gouw, Joost W.; Krijgsveld, Jeroen; Heck, Albert J. R.

    2010-01-01

    In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life. PMID:19955089

  2. A comparative proteomics method for multiple samples based on a 18O-reference strategy and a quantitation and identification-decoupled strategy.

    PubMed

    Wang, Hongbin; Zhang, Yongqian; Gui, Shuqi; Zhang, Yong; Lu, Fuping; Deng, Yulin

    2017-08-15

    Comparisons across large numbers of samples are frequently necessary in quantitative proteomics. Many quantitative methods used in proteomics are based on stable isotope labeling, but most of these are only useful for comparing two samples. For up to eight samples, the iTRAQ labeling technique can be used. For greater numbers of samples, the label-free method has been used, but this method was criticized for low reproducibility and accuracy. An ingenious strategy has been introduced, comparing each sample against a 18 O-labeled reference sample that was created by pooling equal amounts of all samples. However, it is necessary to use proportion-known protein mixtures to investigate and evaluate this new strategy. Another problem for comparative proteomics of multiple samples is the poor coincidence and reproducibility in protein identification results across samples. In present study, a method combining 18 O-reference strategy and a quantitation and identification-decoupled strategy was investigated with proportion-known protein mixtures. The results obviously demonstrated that the 18 O-reference strategy had greater accuracy and reliability than other previously used comparison methods based on transferring comparison or label-free strategies. By the decoupling strategy, the quantification data acquired by LC-MS and the identification data acquired by LC-MS/MS are matched and correlated to identify differential expressed proteins, according to retention time and accurate mass. This strategy made protein identification possible for all samples using a single pooled sample, and therefore gave a good reproducibility in protein identification across multiple samples, and allowed for optimizing peptide identification separately so as to identify more proteins. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. The developmental proteome of Drosophila melanogaster

    PubMed Central

    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

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

    PubMed

    Zauber, Henrik; Schulze, Waltraud X

    2012-11-02

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

  5. iTRAQ Quantitative Proteomic Analysis of Vitreous from Patients with Retinal Detachment.

    PubMed

    Santos, Fátima Milhano; Gaspar, Leonor Mesquita; Ciordia, Sergio; Rocha, Ana Sílvia; Castro E Sousa, João Paulo; Paradela, Alberto; Passarinha, Luís António; Tomaz, Cândida Teixeira

    2018-04-11

    Rhegmatogenous retinal detachment (RRD) is a potentially blinding condition characterized by a physical separation between neurosensory retina and retinal pigment epithelium. Quantitative proteomics can help to understand the changes that occur at the cellular level during RRD, providing additional information about the molecular mechanisms underlying its pathogenesis. In the present study, iTRAQ labeling was combined with two-dimensional LC-ESI-MS/MS to find expression changes in the proteome of vitreous from patients with RRD when compared to control samples. A total of 150 proteins were found differentially expressed in the vitreous of patients with RRD, including 96 overexpressed and 54 underexpressed. Several overexpressed proteins, several such as glycolytic enzymes (fructose-bisphosphate aldolase A, gamma-enolase, and phosphoglycerate kinase 1), glucose transporters (GLUT-1), growth factors (metalloproteinase inhibitor 1), and serine protease inhibitors (plasminogen activator inhibitor 1) are regulated by HIF-1, which suggests that HIF-1 signaling pathway can be triggered in response to RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Nevertheless, the differentially expressed proteins found in this study suggest that different mechanisms are activated after RRD to promote the survival of retinal cells through complex cellular responses.

  6. iTRAQ Quantitative Proteomic Analysis of Vitreous from Patients with Retinal Detachment

    PubMed Central

    Gaspar, Leonor Mesquita; Ciordia, Sergio; Rocha, Ana Sílvia; Castro e Sousa, João Paulo; Paradela, Alberto

    2018-01-01

    Rhegmatogenous retinal detachment (RRD) is a potentially blinding condition characterized by a physical separation between neurosensory retina and retinal pigment epithelium. Quantitative proteomics can help to understand the changes that occur at the cellular level during RRD, providing additional information about the molecular mechanisms underlying its pathogenesis. In the present study, iTRAQ labeling was combined with two-dimensional LC-ESI-MS/MS to find expression changes in the proteome of vitreous from patients with RRD when compared to control samples. A total of 150 proteins were found differentially expressed in the vitreous of patients with RRD, including 96 overexpressed and 54 underexpressed. Several overexpressed proteins, several such as glycolytic enzymes (fructose-bisphosphate aldolase A, gamma-enolase, and phosphoglycerate kinase 1), glucose transporters (GLUT-1), growth factors (metalloproteinase inhibitor 1), and serine protease inhibitors (plasminogen activator inhibitor 1) are regulated by HIF-1, which suggests that HIF-1 signaling pathway can be triggered in response to RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Also, the accumulation of photoreceptor proteins, including phosducin, rhodopsin, and s-arrestin, and vimentin in vitreous may indicate that photoreceptor degeneration occurs in RRD. Nevertheless, the differentially expressed proteins found in this study suggest that different mechanisms are activated after RRD to promote the survival of retinal cells through complex cellular responses. PMID:29641463

  7. Quantitative Proteomics Analysis of the cAMP/Protein Kinase A Signaling Pathway

    PubMed Central

    2012-01-01

    To define the proteins whose expression is regulated by cAMP and protein kinase A (PKA), we used a quantitative proteomics approach in studies of wild-type (WT) and kin- (PKA-null) S49 murine T lymphoma cells. We also compared the impact of endogenous increases in the level of cAMP [by forskolin (Fsk) and the phosphodiesterase inhibitor isobutylmethylxanthine (IBMX)] or by a cAMP analogue (8-CPT-cAMP). We identified 1056 proteins in WT and kin- S49 cells and found that 8-CPT-cAMP and Fsk with IBMX produced differences in protein expression. WT S49 cells had a correlation coefficient of 0.41 between DNA microarray data and the proteomics analysis in cells incubated with 8-CPT-cAMP for 24 h and a correlation coefficient of 0.42 between the DNA microarray data obtained at 6 h and the changes in protein expression after incubation with 8-CPT-cAMP for 24 h. Glutathione reductase (Gsr) had a higher level of basal expression in kin- S49 cells than in WT cells. Consistent with this finding, kin- cells are less sensitive to cell killing and generation of malondialdehyde than are WT cells incubated with H2O2. Cyclic AMP acting via PKA thus has a broad impact on protein expression in mammalian cells, including in the regulation of Gsr and oxidative stress. PMID:23110364

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

    PubMed

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

    2008-04-01

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

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

    PubMed

    Tyanova, Stefka; Temu, Tikira; Cox, Juergen

    2016-12-01

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

  10. Integration of cardiac proteome biology and medicine by a specialized knowledgebase.

    PubMed

    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.

  11. Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues*

    PubMed Central

    Bruderer, Roland; Bernhardt, Oliver M.; Gandhi, Tejas; Miladinović, Saša M.; Cheng, Lin-Yang; Messner, Simon; Ehrenberger, Tobias; Zanotelli, Vito; Butscheid, Yulia; Escher, Claudia; Vitek, Olga; Rinner, Oliver; Reiter, Lukas

    2015-01-01

    The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics. We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics. Utilizing HRM, we profiled acetaminophen (APAP)1-treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD). Our findings imply that DIA should be the preferred method for quantitative protein profiling. PMID:25724911

  12. Proteomics of the Human Placenta: Promises and Realities

    PubMed Central

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

    2015-01-01

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

  13. Cell death proteomics database: consolidating proteomics data on cell death.

    PubMed

    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.

  14. Statistical issues in the design and planning of proteomic profiling experiments.

    PubMed

    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.

  15. Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

    PubMed

    Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

    2018-01-10

    Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

  16. Reproducible Tissue Homogenization and Protein Extraction for Quantitative Proteomics Using MicroPestle-Assisted Pressure-Cycling Technology.

    PubMed

    Shao, Shiying; Guo, Tiannan; Gross, Vera; Lazarev, Alexander; Koh, Ching Chiek; Gillessen, Silke; Joerger, Markus; Jochum, Wolfram; Aebersold, Ruedi

    2016-06-03

    The reproducible and efficient extraction of proteins from biopsy samples for quantitative analysis is a critical step in biomarker and translational research. Recently, we described a method consisting of pressure-cycling technology (PCT) and sequential windowed acquisition of all theoretical fragment ions-mass spectrometry (SWATH-MS) for the rapid quantification of thousands of proteins from biopsy-size tissue samples. As an improvement of the method, we have incorporated the PCT-MicroPestle into the PCT-SWATH workflow. The PCT-MicroPestle is a novel, miniaturized, disposable mechanical tissue homogenizer that fits directly into the microTube sample container. We optimized the pressure-cycling conditions for tissue lysis with the PCT-MicroPestle and benchmarked the performance of the system against the conventional PCT-MicroCap method using mouse liver, heart, brain, and human kidney tissues as test samples. The data indicate that the digestion of the PCT-MicroPestle-extracted proteins yielded 20-40% more MS-ready peptide mass from all tissues tested with a comparable reproducibility when compared to the conventional PCT method. Subsequent SWATH-MS analysis identified a higher number of biologically informative proteins from a given sample. In conclusion, we have developed a new device that can be seamlessly integrated into the PCT-SWATH workflow, leading to increased sample throughput and improved reproducibility at both the protein extraction and proteomic analysis levels when applied to the quantitative proteomic analysis of biopsy-level samples.

  17. Quantitative Proteomic Analysis of Duck Ovarian Follicles Infected with Duck Tembusu Virus by Label-Free LC-MS

    PubMed Central

    Han, Kaikai; Zhao, Dongmin; Liu, Yuzhuo; Liu, Qingtao; Huang, Xinmei; Yang, Jing; An, Fengjiao; Li, Yin

    2016-01-01

    Duck Tembusu virus (DTMUV) is a newly emerging pathogenic flavivirus that has caused massive economic losses to the duck industry in China. DTMUV infection mainly results in significant decreases in egg production in egg-laying ducks within 1–2 weeks post infection. However, information on the comparative protein expression of host tissues in response to DTMUV infection is limited. In the present study, the cellular protein response to DTMUV infection in duck ovarian follicles was analyzed using nano-flow high-performance liquid chromatography-electrospray tandem mass spectrometry. Quantitative proteomic analysis revealed 131 differentially expressed proteins, among which 53 were up regulated and 78 were down regulated. The identified proteins were involved in the regulation of essential processes such as cellular structure and integrity, RNA processing, protein biosynthesis and modification, vesicle transport, signal transduction, and mitochondrial pathway. Some selected proteins that were found to be regulated in DTMUV-infected tissues were screened by quantitative real-time PCR to examine their regulation at the transcriptional level, western blot analysis was used to validate the changes of some selected proteins on translational level. To our knowledge, this study is the first to analyze the proteomic changes in duck ovarian follicles following DTMUV infection. The protein-related information obtained in this study may be useful to understand the host response to DTMUV infection and the inherent mechanism of DTMUV replication and pathogenicity. PMID:27066001

  18. ITRAQ-based quantitative proteomic analysis of Cynops orientalis limb regeneration.

    PubMed

    Tang, Jie; Yu, Yuan; Zheng, Hanxue; Yin, Lu; Sun, Mei; Wang, Wenjun; Cui, Jihong; Liu, Wenguang; Xie, Xin; Chen, Fulin

    2017-09-22

    Salamanders regenerate their limbs after amputation. However, the molecular mechanism of this unique regeneration remains unclear. In this study, isobaric tags for relative and absolute quantification (iTRAQ) coupled with liquid chromatography tandem mass spectrometry (LC-MS/MS) was employed to quantitatively identify differentially expressed proteins in regenerating limbs 3, 7, 14, 30 and 42 days post amputation (dpa). Of 2636 proteins detected in total, 253 proteins were differentially expressed during different regeneration stages. Among these proteins, Asporin, Cadherin-13, Keratin, Collagen alpha-1(XI) and Titin were down-regulated. CAPG, Coronin-1A, AnnexinA1, Cathepsin B were up-regulated compared with the control. The identified proteins were further analyzed to obtain information about their expression patterns and functions in limb regeneration. Functional analysis indicated that the differentially expressed proteins were associated with wound healing, immune response, cellular process, metabolism and binding. This work indicated that significant proteome alternations occurred during salamander limb regeneration. The results may provide fundamental knowledge to understand the mechanism of limb regeneration.

  19. Proteomics in the investigation of HIV-1 interactions with host proteins.

    PubMed

    Li, Ming

    2015-02-01

    Productive HIV-1 infection depends on host machinery, including a broad array of cellular proteins. Proteomics has played a significant role in the discovery of HIV-1 host proteins. In this review, after a brief survey of the HIV-1 host proteins that were discovered by proteomic analyses, I focus on analyzing the interactions between the virion and host proteins, as well as the technologies and strategies used in those proteomic studies. With the help of proteomics, the identification and characterization of HIV-1 host proteins can be translated into novel antiretroviral therapeutics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

    PubMed

    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.

  1. Quantitative Shotgun Proteomics Using a Uniform 15N-Labeled Standard to Monitor Proteome Dynamics in Time Course Experiments Reveals New Insights into the Heat Stress Response of Chlamydomonas reinhardtii*

    PubMed Central

    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

  2. Derivative component analysis for mass spectral serum proteomic profiles.

    PubMed

    Han, Henry

    2014-01-01

    As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate

  3. Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

    PubMed

    Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

    2015-08-03

    Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Mixed-mode ion exchange-based integrated proteomics technology for fast and deep plasma proteome profiling.

    PubMed

    Xue, Lu; Lin, Lin; Zhou, Wenbin; Chen, Wendong; Tang, Jun; Sun, Xiujie; Huang, Peiwu; Tian, Ruijun

    2018-06-09

    Plasma proteome profiling by LC-MS based proteomics has drawn great attention recently for biomarker discovery from blood liquid biopsy. Due to standard multi-step sample preparation could potentially cause plasma protein degradation and analysis variation, integrated proteomics sample preparation technologies became promising solution towards this end. Here, we developed a fully integrated proteomics sample preparation technology for both fast and deep plasma proteome profiling under its native pH. All the sample preparation steps, including protein digestion and two-dimensional fractionation by both mixed-mode ion exchange and high-pH reversed phase mechanism were integrated into one spintip device for the first time. The mixed-mode ion exchange beads design achieved the sample loading at neutral pH and protein digestion within 30 min. Potential sample loss and protein degradation by pH changing could be voided. 1 μL of plasma sample with depletion of high abundant proteins was processed by the developed technology with 12 equally distributed fractions and analyzed with 12 h of LC-MS gradient time, resulting in the identification of 862 proteins. The combination of the Mixed-mode-SISPROT and data-independent MS method achieved fast plasma proteome profiling in 2 h with high identification overlap and quantification precision for a proof-of-concept study of plasma samples from 5 healthy donors. We expect that the Mixed-mode-SISPROT become a generally applicable sample preparation technology for clinical oriented plasma proteome profiling. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Comprehensive genome-wide proteomic analysis of human placental tissue for the Chromosome-Centric Human Proteome Project.

    PubMed

    Lee, Hyoung-Joo; Jeong, Seul-Ki; Na, Keun; Lee, Min Jung; Lee, Sun Hee; Lim, Jong-Sun; Cha, Hyun-Jeong; Cho, Jin-Young; Kwon, Ja-Young; Kim, Hoguen; Song, Si Young; Yoo, Jong Shin; Park, Young Mok; Kim, Hail; Hancock, William S; Paik, Young-Ki

    2013-06-07

    As a starting point of the Chromosome-Centric Human Proteome Project (C-HPP), we established strategies of genome-wide proteomic analysis, including protein identification, quantitation of disease-specific proteins, and assessment of post-translational modifications, using paired human placental tissues from healthy and preeclampsia patients. This analysis resulted in identification of 4239 unique proteins with high confidence (two or more unique peptides with a false discovery rate less than 1%), covering 21% of approximately 20, 059 (Ensembl v69, Oct 2012) human proteins, among which 28 proteins exhibited differentially expressed preeclampsia-specific proteins. When these proteins are assigned to all human chromosomes, the pattern of the newly identified placental protein population is proportional to that of the gene count distribution of each chromosome. We also identified 219 unique N-linked glycopeptides, 592 unique phosphopeptides, and 66 chromosome 13-specific proteins. In particular, protein evidence of 14 genes previously known to be specifically up-regulated in human placenta was verified by mass spectrometry. With respect to the functional implication of these proteins, 38 proteins were found to be involved in regulatory factor biosynthesis or the immune system in the placenta, but the molecular mechanism of these proteins during pregnancy warrants further investigation. As far as we know, this work produced the highest number of proteins identified in the placenta and will be useful for annotating and mapping all proteins encoded in the human genome.

  6. Analysis of disease-associated protein expression using quantitative proteomics—fibulin-5 is expressed in association with hepatic fibrosis.

    PubMed

    Bracht, Thilo; Schweinsberg, Vincent; Trippler, Martin; Kohl, Michael; Ahrens, Maike; Padden, Juliet; Naboulsi, Wael; Barkovits, Katalin; Megger, Dominik A; Eisenacher, Martin; Borchers, Christoph H; Schlaak, Jörg F; Hoffmann, Andreas-Claudius; Weber, Frank; Baba, Hideo A; Meyer, Helmut E; Sitek, Barbara

    2015-05-01

    Hepatic fibrosis and cirrhosis are major health problems worldwide. Until now, highly invasive biopsy remains the diagnostic gold standard despite many disadvantages. To develop noninvasive diagnostic assays for the assessment of liver fibrosis, it is urgently necessary to identify molecules that are robustly expressed in association with the disease. We analyzed biopsied tissue samples from 95 patients with HBV/HCV-associated hepatic fibrosis using three different quantification methods. We performed a label-free proteomics discovery study to identify novel disease-associated proteins using a subset of the cohort (n = 27). Subsequently, gene expression data from all available clinical samples were analyzed (n = 77). Finally, we performed a targeted proteomics approach, multiple reaction monitoring (MRM), to verify the disease-associated expression in samples independent from the discovery approach (n = 68). We identified fibulin-5 (FBLN5) as a novel protein expressed in relation to hepatic fibrosis. Furthermore, we confirmed the altered expression of microfibril-associated glycoprotein 4 (MFAP4), lumican (LUM), and collagen alpha-1(XIV) chain (COL14A1) in association to hepatic fibrosis. To our knowledge, no tissue-based quantitative proteomics study for hepatic fibrosis has been performed using a cohort of comparable size. By this means, we add substantial evidence for the disease-related expression of the proteins examined in this study.

  7. Quantitative Proteomic Profiling of Low-Dose Ionizing Radiation Effects in a Human Skin Model

    PubMed Central

    Hengel, Shawna M.; Aldrich, Joshua T.; Waters, Katrina M.; Pasa-Tolic, Ljiljana; Stenoien, David L.

    2014-01-01

    To assess responses to low-dose ionizing radiation (LD-IR) exposures potentially encountered during medical diagnostic procedures, nuclear accidents or terrorist acts, a quantitative proteomic approach was used to identify changes in protein abundance in a reconstituted human skin tissue model treated with 0.1 Gy of ionizing radiation. To improve the dynamic range of the assay, subcellular fractionation was employed to remove highly abundant structural proteins and to provide insight into radiation-induced alterations in protein localization. Relative peptide quantification across cellular fractions, control and irradiated samples was performing using 8-plex iTRAQ labeling followed by online two-dimensional nano-scale liquid chromatography and high resolution MS/MS analysis. A total of 107 proteins were detected with statistically significant radiation-induced change in abundance (>1.5 fold) and/or subcellular localization compared to controls. The top biological pathways identified using bioinformatics include organ development, anatomical structure formation and the regulation of actin cytoskeleton. From the proteomic data, a change in proteolytic processing and subcellular localization of the skin barrier protein, filaggrin, was identified, and the results were confirmed by western blotting. This data indicate post-transcriptional regulation of protein abundance, localization and proteolytic processing playing an important role in regulating radiation response in human tissues. PMID:28250387

  8. Quantitative Proteomics Reveals Membrane Protein-Mediated Hypersaline Sensitivity and Adaptation in Halophilic Nocardiopsis xinjiangensis.

    PubMed

    Zhang, Yao; Li, Yanchang; Zhang, Yongguang; Wang, Zhiqiang; Zhao, Mingzhi; Su, Na; Zhang, Tao; Chen, Lingsheng; Wei, Wei; Luo, Jing; Zhou, Yanxia; Xu, Yongru; Xu, Ping; Li, Wenjun; Tao, Yong

    2016-01-04

    The genus Nocardiopsis is one of the most dominant Actinobacteria that survives in hypersaline environments. However, the adaptation mechanisms for halophilism are still unclear. Here, we performed isobaric tags for relative and absolute quantification based quantitative proteomics to investigate the functions of the membrane proteome after salt stress. A total of 683 membrane proteins were identified and quantified, of which 126 membrane proteins displayed salt-induced changes in abundance. Intriguingly, bioinformatics analyses indicated that these differential proteins showed two expression patterns, which were further validated by phenotypic changes and functional differences. The majority of ABC transporters, secondary active transporters, cell motility proteins, and signal transduction kinases were up-regulated with increasing salt concentration, whereas cell differentiation, small molecular transporter (ions and amino acids), and secondary metabolism proteins were significantly up-regulated at optimum salinity, but down-regulated or unchanged at higher salinity. The small molecule transporters and cell differentiation-related proteins acted as sensing proteins that played a more important biological role at optimum salinity. However, the ABC transporters for compatible solutes, Na(+)-dependent transporters, and cell motility proteins acted as adaptive proteins that actively counteracted higher salinity stress. Overall, regulation of membrane proteins may provide a major protection strategy against hyperosmotic stress.

  9. Proteomics in pharmaceutical research and development.

    PubMed

    Cutler, Paul; Voshol, Hans

    2015-08-01

    In the 20 years since its inception, the evolution of proteomics in pharmaceutical industry has mirrored the developments within academia and indeed other industries. From initial enthusiasm and subsequent disappointment in global protein expression profiling, pharma research saw the biggest impact when relating to more focused approaches, such as those exploring the interaction between proteins and drugs. Nowadays, proteomics technologies have been integrated in many areas of pharmaceutical R&D, ranging from the analysis of therapeutic proteins to the monitoring of clinical trials. Here, we review the development of proteomics in the drug discovery process, placing it in a historical context as well as reviewing the current status in light of the contributions to this special issue, which reflect some of the diverse demands of the drug and biomarker pipelines. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Uncaria rhynchophylla Ameliorates Parkinson's Disease by Inhibiting HSP90 Expression: Insights from Quantitative Proteomics.

    PubMed

    Lan, Yu-Long; Zhou, Jun-Jun; Liu, Jing; Huo, Xiao-Kui; Wang, Ya-Li; Liang, Jia-Hao; Zhao, Jian-Chao; Sun, Cheng-Peng; Yu, Zhen-Long; Fang, Lin-Lin; Tian, Xiang-Ge; Feng, Lei; Ning, Jing; Zhang, Bao-Jing; Wang, Chao; Zhao, Xin-Yu; Ma, Xiao-Chi

    2018-06-21

    Uncaria rhynchophylla, known as "Gou-teng", is a traditional Chinese medicine (TCM) used to extinguish wind, clear heat, arrest convulsions, and pacify the liver. Although U. rhynchophylla has a long history of being often used to treat central nervous system (CNS) diseases, its efficacy and potential mechanism are still uncertain. This study investigated neuroprotective effect and the underlying mechanism of U. rhynchophylla extract (URE) in MPP+-induced SH-SY5Y cells and MPTP-induced mice. MPP+-induced SH-SY5Y cells and MPTP-induced mice were used to established Parkinson's disease (PD) models. Quantitative proteomics and bioinformatics were used to uncover proteomics changes of URE. Western blotting was used to validate main differentially expressed proteins and test HSP90 client proteins (apoptosis-related, autophagy-related, MAPKs, PI3K, and AKT proteins). Flow cytometry and JC-1 staining assay were further used to confirm the effect of URE on MPP+-induced apoptosis in SH-SY5Y cells. Gait analysis was used to detect the behavioral changes in MPTP-induced mice. The levels of dopamine (DA) and their metabolites were examined in striatum (STR) by HPLC-EC. The positive expression of tyrosine hydroxylase (TH) was detected by immunohischemical staining and Western blotting. URE dose-dependently increased the cell viability in MPP+-induced SH-SY5Y cells. Quantitative proteomics and bioinformatics results confirmed that HSP90 was an important differentially expressed protein of URE. URE inhibited the expression of HSP90, which further reversed MPP+-induced cell apoptosis and autophagy by increasing the expressions of Bcl-2, Cyclin D1, p-ERK, p-PI3K p85, PI3K p110α, p-AKT, and LC3-I and decreasing cleaved caspase 3, Bax, p-JNK, p-p38, and LC3-II. URE also markedly decreased the apoptotic ratio and elevated mitochondrial transmembrane potential (DΨm). Furthermore, URE treatment ameliorated behavioral impairments, increased the contents of DA and its metabolites and

  11. Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation.

    PubMed

    Schilling, Birgit; Rardin, Matthew J; MacLean, Brendan X; Zawadzka, Anna M; Frewen, Barbara E; Cusack, Michael P; Sorensen, Dylan J; Bereman, Michael S; Jing, Enxuan; Wu, Christine C; Verdin, Eric; Kahn, C Ronald; Maccoss, Michael J; Gibson, Bradford W

    2012-05-01

    Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

  12. Transcriptomic and Quantitative Proteomic Analyses Provide Insights Into the Phagocytic Killing of Hemocytes in the Oyster Crassostrea gigas

    PubMed Central

    Jiang, Shuai; Qiu, Limei; Wang, Lingling; Jia, Zhihao; Lv, Zhao; Wang, Mengqiang; Liu, Conghui; Xu, Jiachao; Song, Linsheng

    2018-01-01

    As invertebrates lack an adaptive immune system, they depend to a large extent on their innate immune system to recognize and clear invading pathogens. Although phagocytes play pivotal roles in invertebrate innate immunity, the molecular mechanisms underlying this killing remain unclear. Cells of this type from the Pacific oyster Crassostrea gigas were classified efficiently in this study via fluorescence-activated cell sorting (FACS) based on their phagocytosis of FITC-labeled latex beads. Transcriptomic and quantitative proteomic analyses revealed a series of differentially expressed genes (DEGs) and proteins present in phagocytes; of the 352 significantly high expressed proteins identified here within the phagocyte proteome, 262 corresponding genes were similarly high expressed in the transcriptome, while 140 of 205 significantly low expressed proteins within the proteome were transcriptionally low expressed. A pathway crosstalk network analysis of these significantly high expressed proteins revealed that phagocytes were highly activated in a number of antimicrobial-related biological processes, including oxidation–reduction and lysosomal proteolysis processes. A number of DEGs, including oxidase, lysosomal protease, and immune receptors, were also validated in this study using quantitative PCR, while seven lysosomal cysteine proteases, referred to as cathepsin Ls, were significantly high expressed in phagocytes. Results show that the expression level of cathepsin L protein in phagocytes [mean fluorescence intensity (MFI): 327 ± 51] was significantly higher (p < 0.01) than that in non-phagocytic hemocytes (MFI: 83 ± 26), while the cathepsin L protein was colocalized with the phagocytosed Vibrio splendidus in oyster hemocytes during this process. The results of this study collectively suggest that oyster phagocytes possess both potent oxidative killing and microbial disintegration capacities; these findings provide important insights into hemocyte

  13. Quantitative proteomic analyses of the microbial degradation of estrone under various background nitrogen and carbon conditions.

    PubMed

    Du, Zhe; Chen, Yinguang; Li, Xu

    2017-10-15

    Microbial degradation of estrogenic compounds can be affected by the nitrogen source and background carbon in the environment. However, the underlying mechanisms are not well understood. The objective of this study was to elucidate the molecular mechanisms of estrone (E1) biodegradation at the protein level under various background nitrogen (nitrate or ammonium) and carbon conditions (no background carbon, acetic acid, or humic acid as background carbon) by a newly isolated bacterial strain. The E1 degrading bacterial strain, Hydrogenophaga atypica ZD1, was isolated from river sediments and its proteome was characterized under various experimental conditions using quantitative proteomics. Results show that the E1 degradation rate was faster when ammonium was used as the nitrogen source than with nitrate. The degradation rate was also faster when either acetic acid or humic acid was present in the background. Proteomics analyses suggested that the E1 biodegradation products enter the tyrosine metabolism pathway. Compared to nitrate, ammonium likely promoted E1 degradation by increasing the activities of the branched-chain-amino-acid aminotransferase (IlvE) and enzymes involved in the glutamine synthetase-glutamine oxoglutarate aminotransferase (GS-GOGAT) pathway. The increased E1 degradation rate with acetic acid or humic acid in the background can also be attributed to the up-regulation of IlvE. Results from this study can help predict and explain E1 biodegradation kinetics under various environmental conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Characterization of individual mouse cerebrospinal fluid proteomes

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

    Smith, Jeffrey S.; Angel, Thomas E.; Chavkin, Charles

    2014-03-20

    Analysis of cerebrospinal fluid (CSF) offers key insight into the status of the central nervous system. Characterization of murine CSF proteomes can provide a valuable resource for studying central nervous system injury and disease in animal models. However, the small volume of CSF in mice has thus far limited individual mouse proteome characterization. Through non-terminal CSF extractions in C57Bl/6 mice and high-resolution liquid chromatography-mass spectrometry analysis of individual murine samples, we report the most comprehensive proteome characterization of individual murine CSF to date. Utilizing stringent protein inclusion criteria that required the identification of at least two unique peptides (1% falsemore » discovery rate at the peptide level) we identified a total of 566 unique proteins, including 128 proteins from three individual CSF samples that have been previously identified in brain tissue. Our methods and analysis provide a mechanism for individual murine CSF proteome analysis.« less

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

    PubMed

    Mardamshina, Mariya; Geiger, Tamar

    2017-10-01

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

  16. Integrated Proteomic Approaches for Understanding Toxicity of Environmental Chemicals

    EPA Science Inventory

    To apply quantitative proteomic analysis to the evaluation of toxicity of environmental chemicals, we have developed an integrated proteomic technology platform. This platform has been applied to the analysis of the toxic effects and pathways of many important environmental chemi...

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

    PubMed

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

    2009-06-01

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

  18. Dynamic quantitative proteomics characterization of TNF-α-induced necroptosis.

    PubMed

    Wang, Yang; Huang, Zhi-Hao; Li, Yang-Jia; He, Gui-Wei; Yu, Ru-Yuan; Yang, Jie; Liu, Wan-Ting; Li, Bin; He, Qing-Yu

    2016-12-01

    Emerging evidence suggested that necroptosis has essential functions in many human inflammatory diseases, but the molecular mechanisms of necroptosis remain unclear. Here, we employed SILAC quantitatively dynamic proteomics to compare the protein changes during TNF-α-induced necroptosis at different time points in murine fibrosarcoma L929 cells with caspase-8 deficiency, and then performed the systematical analysis on the signaling networks involved in the progress using bioinformatics methods. Our results showed that a total of 329, 421 and 378 differentially expressed proteins were detected at three stages of necroptosis, respectively. Gene ontology and ingenuity pathway analysis (IPA) revealed that the proteins regulated at early stages of necroptosis (2, 6 h) were mainly involved in mitochondria dysfunction, oxidative phosphorylation and Nrf-2 signaling, while the expression levels of the proteins related to ubiquitin, Nrf-2, and NF-κB pathways were found to have changes at last stages of necroptosis (6, 18 h). Taken together, we demonstrated for the first time that dysfunction of mitochondria and ubiquitin-proteasome signaling contributed to the initiation and execution of necroptosis. These findings may provide clues for the identification of important regulators in necroptosis and the development of novel therapeutic strategies for the related diseases.

  19. Quantitative Proteomics Reveal Distinct Protein Regulations Caused by Aggregatibacter actinomycetemcomitans within Subgingival Biofilms

    PubMed Central

    Bao, Kai; Bostanci, Nagihan; Selevsek, Nathalie; Thurnheer, Thomas; Belibasakis, Georgios N.

    2015-01-01

    Periodontitis is an infectious disease that causes the inflammatory destruction of the tooth-supporting (periodontal) tissues, caused by polymicrobial biofilm communities growing on the tooth surface. Aggressive periodontitis is strongly associated with the presence of Aggregatibacter actinomycetemcomitans in the subgingival biofilms. Nevertheless, whether and how A. actinomycetemcomitans orchestrates molecular changes within the biofilm is unclear. The aim of this work was to decipher the interactions between A. actinomycetemcomitans and other bacterial species in a multi-species biofilm using proteomic analysis. An in vitro 10-species “subgingival” biofilm model, or its derivative that included additionally A. actinomycetemcomitans, were anaerobically cultivated on hydroxyapatite discs for 64 h. When present, A. actinomycetemcomitans formed dense intra-species clumps within the biofilm mass, and did not affect the numbers of the other species in the biofilm. Liquid chromatography-tandem mass spectrometry was used to identify the proteomic content of the biofilm lysate. A total of 3225 and 3352 proteins were identified in the biofilm, in presence or absence of A. actinomycetemcomitans, respectively. Label-free quantitative proteomics revealed that 483 out of the 728 quantified bacterial proteins (excluding those of A. actinomycetemcomitans) were accordingly regulated. Interestingly, all quantified proteins from Prevotella intermedia were up-regulated, and most quantified proteins from Campylobacter rectus, Streptococcus anginosus, and Porphyromonas gingivalis were down-regulated in presence of A. actinomycetemcomitans. Enrichment of Gene Ontology pathway analysis showed that the regulated groups of proteins were responsible primarily for changes in the metabolic rate, the ferric iron-binding, and the 5S RNA binding capacities, on the universal biofilm level. While the presence of A. actinomycetemcomitans did not affect the numeric composition or absolute

  20. mapDIA: Preprocessing and statistical analysis of quantitative proteomics data from data independent acquisition mass spectrometry.

    PubMed

    Teo, Guoshou; Kim, Sinae; Tsou, Chih-Chiang; Collins, Ben; Gingras, Anne-Claude; Nesvizhskii, Alexey I; Choi, Hyungwon

    2015-11-03

    Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3β dynamic interaction network and prostate cancer glycoproteome. The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis.

    PubMed

    Falter, Christian; Ellinger, Dorothea; von Hülsen, Behrend; Heim, René; Voigt, Christian A

    2015-01-01

    The outwardly directed cell wall and associated plasma membrane of epidermal cells represent the first layers of plant defense against intruding pathogens. Cell wall modifications and the formation of defense structures at sites of attempted pathogen penetration are decisive for plant defense. A precise isolation of these stress-induced structures would allow a specific analysis of regulatory mechanism and cell wall adaption. However, methods for large-scale epidermal tissue preparation from the model plant Arabidopsis thaliana, which would allow proteome and cell wall analysis of complete, laser-microdissected epidermal defense structures, have not been provided. We developed the adhesive tape - liquid cover glass technique (ACT) for simple leaf epidermis preparation from A. thaliana, which is also applicable on grass leaves. This method is compatible with subsequent staining techniques to visualize stress-related cell wall structures, which were precisely isolated from the epidermal tissue layer by laser microdissection (LM) coupled to laser pressure catapulting. We successfully demonstrated that these specific epidermal tissue samples could be used for quantitative downstream proteome and cell wall analysis. The development of the ACT for simple leaf epidermis preparation and the compatibility to LM and downstream quantitative analysis opens new possibilities in the precise examination of stress- and pathogen-related cell wall structures in epidermal cells. Because the developed tissue processing is also applicable on A. thaliana, well-established, model pathosystems that include the interaction with powdery mildews can be studied to determine principal regulatory mechanisms in plant-microbe interaction with their potential outreach into crop breeding.

  2. Quantitative high-throughput profiling of snake venom gland transcriptomes and proteomes (Ovophis okinavensis and Protobothrops flavoviridis)

    PubMed Central

    2013-01-01

    Background Advances in DNA sequencing and proteomics have facilitated quantitative comparisons of snake venom composition. Most studies have employed one approach or the other. Here, both Illumina cDNA sequencing and LC/MS were used to compare the transcriptomes and proteomes of two pit vipers, Protobothrops flavoviridis and Ovophis okinavensis, which differ greatly in their biology. Results Sequencing of venom gland cDNA produced 104,830 transcripts. The Protobothrops transcriptome contained transcripts for 103 venom-related proteins, while the Ovophis transcriptome contained 95. In both, transcript abundances spanned six orders of magnitude. Mass spectrometry identified peptides from 100% of transcripts that occurred at higher than contaminant (e.g. human keratin) levels, including a number of proteins never before sequenced from snakes. These transcriptomes reveal fundamentally different envenomation strategies. Adult Protobothrops venom promotes hemorrhage, hypotension, incoagulable blood, and prey digestion, consistent with mammalian predation. Ovophis venom composition is less readily interpreted, owing to insufficient pharmacological data for venom serine and metalloproteases, which comprise more than 97.3% of Ovophis transcripts, but only 38.0% of Protobothrops transcripts. Ovophis venom apparently represents a hybrid strategy optimized for frogs and small mammals. Conclusions This study illustrates the power of cDNA sequencing combined with MS profiling. The former quantifies transcript composition, allowing detection of novel proteins, but cannot indicate which proteins are actually secreted, as does MS. We show, for the first time, that transcript and peptide abundances are correlated. This means that MS can be used for quantitative, non-invasive venom profiling, which will be beneficial for studies of endangered species. PMID:24224955

  3. Simple preparation of plant epidermal tissue for laser microdissection and downstream quantitative proteome and carbohydrate analysis

    PubMed Central

    Falter, Christian; Ellinger, Dorothea; von Hülsen, Behrend; Heim, René; Voigt, Christian A.

    2015-01-01

    The outwardly directed cell wall and associated plasma membrane of epidermal cells represent the first layers of plant defense against intruding pathogens. Cell wall modifications and the formation of defense structures at sites of attempted pathogen penetration are decisive for plant defense. A precise isolation of these stress-induced structures would allow a specific analysis of regulatory mechanism and cell wall adaption. However, methods for large-scale epidermal tissue preparation from the model plant Arabidopsis thaliana, which would allow proteome and cell wall analysis of complete, laser-microdissected epidermal defense structures, have not been provided. We developed the adhesive tape – liquid cover glass technique (ACT) for simple leaf epidermis preparation from A. thaliana, which is also applicable on grass leaves. This method is compatible with subsequent staining techniques to visualize stress-related cell wall structures, which were precisely isolated from the epidermal tissue layer by laser microdissection (LM) coupled to laser pressure catapulting. We successfully demonstrated that these specific epidermal tissue samples could be used for quantitative downstream proteome and cell wall analysis. The development of the ACT for simple leaf epidermis preparation and the compatibility to LM and downstream quantitative analysis opens new possibilities in the precise examination of stress- and pathogen-related cell wall structures in epidermal cells. Because the developed tissue processing is also applicable on A. thaliana, well-established, model pathosystems that include the interaction with powdery mildews can be studied to determine principal regulatory mechanisms in plant–microbe interaction with their potential outreach into crop breeding. PMID:25870605

  4. Quantitative proteomics reveal a feedforward mechanism for mitochondrial PARKIN translocation and ubiquitin chain synthesis.

    PubMed

    Ordureau, Alban; Sarraf, Shireen A; Duda, David M; Heo, Jin-Mi; Jedrychowski, Mark P; Sviderskiy, Vladislav O; Olszewski, Jennifer L; Koerber, James T; Xie, Tiao; Beausoleil, Sean A; Wells, James A; Gygi, Steven P; Schulman, Brenda A; Harper, J Wade

    2014-11-06

    Phosphorylation is often used to promote protein ubiquitylation, yet we rarely understand quantitatively how ligase activation and ubiquitin (UB) chain assembly are integrated with phosphoregulation. Here we employ quantitative proteomics and live-cell imaging to dissect individual steps in the PINK1 kinase-PARKIN UB ligase mitochondrial control pathway disrupted in Parkinson's disease. PINK1 plays a dual role by phosphorylating PARKIN on its UB-like domain and poly-UB chains on mitochondria. PARKIN activation by PINK1 produces canonical and noncanonical UB chains on mitochondria, and PARKIN-dependent chain assembly is required for accumulation of poly-phospho-UB (poly-p-UB) on mitochondria. In vitro, PINK1 directly activates PARKIN's ability to assemble canonical and noncanonical UB chains and promotes association of PARKIN with both p-UB and poly-p-UB. Our data reveal a feedforward mechanism that explains how PINK1 phosphorylation of both PARKIN and poly-UB chains synthesized by PARKIN drives a program of PARKIN recruitment and mitochondrial ubiquitylation in response to mitochondrial damage. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Translational Research and Plasma Proteomic in Cancer.

    PubMed

    Santini, Annamaria Chiara; Giovane, Giancarlo; Auletta, Adelaide; Di Carlo, Angelina; Fiorelli, Alfonso; Cito, Letizia; Astarita, Carlo; Giordano, Antonio; Alfano, Roberto; Feola, Antonia; Di Domenico, Marina

    2016-04-01

    Proteomics is a recent field of research in molecular biology that can help in the fight against cancer through the search for biomarkers that can detect this disease in the early stages of its development. Proteomic is a speedily growing technology, also thanks to the development of even more sensitive and fast mass spectrometry analysis. Although this technique is the most widespread for the discovery of new cancer biomarkers, it still suffers of a poor sensitivity and insufficient reproducibility, essentially due to the tumor heterogeneity. Common technical shortcomings include limitations in the sensitivity of detecting low abundant biomarkers and possible systematic biases in the observed data. Current research attempts are trying to develop high-resolution proteomic instrumentation for high-throughput monitoring of protein changes that occur in cancer. In this review, we describe the basic features of the proteomic tools which have proven to be useful in cancer research, showing their advantages and disadvantages. The application of these proteomic tools could provide early biomarkers detection in various cancer types and could improve the understanding the mechanisms of tumor growth and dissemination. © 2015 Wiley Periodicals, Inc.

  6. iTRAQ-based Quantitative Proteomics Study in Patients with Refractory Mycoplasma pneumoniae Pneumonia.

    PubMed

    Yu, Jia-Lu; Song, Qi-Fang; Xie, Zhi-Wei; Jiang, Wen-Hui; Chen, Jia-Hui; Fan, Hui-Feng; Xie, Ya-Ping; Lu, Gen

    2017-09-25

    Mycoplasma pneumoniae (MP) is a leading cause of community-acquired pneumonia in children and young adults. Although MP pneumonia is usually benign and self-limited, in some cases it can develop into life-threating refractory MP pneumonia (RMPP). However, the pathogenesis of RMPP is poorly understood. The identification and characterization of proteins related to RMPP could provide a proof of principle to facilitate appropriate diagnostic and therapeutic strategies for treating paients with MP. In this study, we used a quantitative proteomic technique (iTRAQ) to analyze MP-related proteins in serum samples from 5 patients with RMPP, 5 patients with non-refractory MP pneumonia (NRMPP), and 5 healthy children. Functional classification, sub-cellular localization, and protein interaction network analysis were carried out based on protein annotation through evolutionary relationship (PANTHER) and Cytoscape analysis. A total of 260 differentially expressed proteins were identified in the RMPP and NRMPP groups. Compared to the control group, the NRMPP and RMPP groups showed 134 (70 up-regulated and 64 down-regulated) and 126 (63 up-regulated and 63 down-regulated) differentially expressed proteins, respectively. The complex functional classification and protein interaction network of the identified proteins reflected the complex pathogenesis of RMPP. Our study provides the first comprehensive proteome map of RMPP-related proteins from MP pneumonia. These profiles may be useful as part of a diagnostic panel, and the identified proteins provide new insights into the pathological mechanisms underlying RMPP.

  7. Isobaric Tags for Relative and Absolute Quantitation-Based Proteomic Analysis of Patent and Constricted Ductus Arteriosus Tissues Confirms the Systemic Regulation of Ductus Arteriosus Closure.

    PubMed

    Hong, Haifa; Ye, Lincai; Chen, Huiwen; Xia, Yu; Liu, Yue; Liu, Jinfen; Lu, Yanan; Zhang, Haibo

    2015-08-01

    We aimed to evaluate global changes in protein expression associated with patency by undertaking proteomic analysis of human constricted and patent ductus arteriosus (DA). Ten constricted and 10 patent human DAs were excised from infants with ductal-dependent heart disease during surgery. Using isobaric tags for relative and absolute quantitation-based quantitative proteomics, 132 differentially expressed proteins were identified. Of 132 proteins, voltage-gated sodium channel 1.3 (SCN3A), myosin 1d (Myo1d), Rho GTPase activating protein 26 (ARHGAP26), and retinitis pigmentosa 1 (RP1) were selected for validation by Western blot and quantitative real-time polymerase chain reaction analyses. Significant upregulation of SCN3A, Myo1d, and RP1 messenger RNA, and protein levels was observed in the patent DA group (all P ≤ 0.048). ARHGAP26 messenger RNA and protein levels were decreased in patent DA tissue (both P ≤ 0.018). Immunohistochemistry analysis revealed that Myo1d, ARHGAP26, and RP1 were specifically expressed in the subendothelial region of constricted DAs; however, diffuse expression of these proteins was noted in the patent group. Proteomic analysis revealed global changes in the expression of proteins that regulate oxygen sensing, ion channels, smooth muscle cell migration, nervous system, immune system, and metabolism, suggesting a basis for the systemic regulation of DA patency by diverse signaling pathways, which will be confirmed in further studies.

  8. Proteomic landscape in Central and Eastern Europe: the 9th Central and Eastern European Proteomic Conference, Poznań, Poland.

    PubMed

    Gadher, Suresh Jivan; Marczak, Łukasz; Łuczak, Magdalena; Stobiecki, Maciej; Widlak, Piotr; Kovarova, Hana

    2016-01-01

    Every year since 2007, the Central and Eastern European Proteomic Conference (CEEPC) has excelled in representing state-of-the-art proteomics in and around Central and Eastern Europe, and linking it to international institutions worldwide. Its mission remains to contribute to all approaches of proteomics including traditional and often-revisited methodologies as well as the latest technological achievements in clinical, quantitative and structural proteomics with a view to systems biology of a variety of processes. The 9th CEEPC was held from June 15th to 18th, 2015, at the Institute of Bioorganic Chemistry, Polish Academy of Sciences in Poznań, Poland. The scientific program stimulated exchange of proteomic knowledge whilst the spectacular venue of the conference allowed participants to enjoy the cobblestoned historical city of Poznań.

  9. Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

    PubMed

    Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

    2016-08-18

    A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (<7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model

  10. Statistical Model to Analyze Quantitative Proteomics Data Obtained by 18O/16O Labeling and Linear Ion Trap Mass Spectrometry

    PubMed Central

    Jorge, Inmaculada; Navarro, Pedro; Martínez-Acedo, Pablo; Núñez, Estefanía; Serrano, Horacio; Alfranca, Arántzazu; Redondo, Juan Miguel; Vázquez, Jesús

    2009-01-01

    Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16O/18O labeling. Besides large scale test experiments to validate the null hypothesis are lacking. Although the study of mechanisms underlying biological actions promoted by vascular endothelial growth factor (VEGF) on endothelial cells is of considerable interest, quantitative proteomics studies on this subject are scarce and have been performed after exposing cells to the factor for long periods of time. In this work we present the largest quantitative proteomics study to date on the short term effects of VEGF on human umbilical vein endothelial cells by 18O/16O labeling. Current statistical models based on normality and variance homogeneity were found unsuitable to describe the null hypothesis in a large scale test experiment performed on these cells, producing false expression changes. A random effects model was developed including four different sources of variance at the spectrum-fitting, scan, peptide, and protein levels. With the new model the number of outliers at scan and peptide levels was negligible in three large scale experiments, and only one false protein expression change was observed in the test experiment among more than 1000 proteins. The new model allowed the detection of significant protein expression changes upon VEGF stimulation for 4 and 8 h. The consistency of the changes observed at 4 h was confirmed by a replica at a smaller scale and further validated by Western blot analysis of some proteins. Most of the observed changes have not been described previously and are consistent with a pattern of protein expression that dynamically changes over time following the evolution of the angiogenic response. With this statistical model the 18O labeling approach emerges as a very promising and robust alternative to perform quantitative proteomics studies at a depth of several thousand proteins

  11. The membrane proteome of Medicago truncatula roots displays qualitative and quantitative changes in response to arbuscular mycorrhizal symbiosis.

    PubMed

    Abdallah, Cosette; Valot, Benoit; Guillier, Christelle; Mounier, Arnaud; Balliau, Thierry; Zivy, Michel; van Tuinen, Diederik; Renaut, Jenny; Wipf, Daniel; Dumas-Gaudot, Eliane; Recorbet, Ghislaine

    2014-08-28

    Arbuscular mycorrhizal (AM) symbiosis that associates roots of most land plants with soil-borne fungi (Glomeromycota), is characterized by reciprocal nutritional benefits. Fungal colonization of plant roots induces massive changes in cortical cells where the fungus differentiates an arbuscule, which drives proliferation of the plasma membrane. Despite the recognized importance of membrane proteins in sustaining AM symbiosis, the root microsomal proteome elicited upon mycorrhiza still remains to be explored. In this study, we first examined the qualitative composition of the root membrane proteome of Medicago truncatula after microsome enrichment and subsequent in depth analysis by GeLC-MS/MS. The results obtained highlighted the identification of 1226 root membrane protein candidates whose cellular and functional classifications predispose plastids and protein synthesis as prevalent organelle and function, respectively. Changes at the protein abundance level between the membrane proteomes of mycorrhizal and nonmycorrhizal roots were further monitored by spectral counting, which retrieved a total of 96 proteins that displayed a differential accumulation upon AM symbiosis. Besides the canonical markers of the periarbuscular membrane, new candidates supporting the importance of membrane trafficking events during mycorrhiza establishment/functioning were identified, including flotillin-like proteins. The data have been deposited to the ProteomeXchange with identifier PXD000875. During arbuscular mycorrhizal symbiosis, one of the most widespread mutualistic associations in nature, the endomembrane system of plant roots is believed to undergo qualitative and quantitative changes in order to sustain both the accommodation process of the AM fungus within cortical cells and the exchange of nutrients between symbionts. Large-scale GeLC-MS/MS proteomic analysis of the membrane fractions from mycorrhizal and nonmycorrhizal roots of M. truncatula coupled to spectral counting

  12. Proteomic analysis of Medulloblastoma reveals functional biology with translational potential.

    PubMed

    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.

  13. Label-free proteome of water buffalo (Bubalus bubalis) seminal plasma.

    PubMed

    Brito, Mayara F; Auler, Patrícia A; Tavares, Guilherme C; Rezende, Cristiana P; Almeida, Gabriel M F; Pereira, Felipe L; Leal, Carlos A G; Moura, Arlindo de Alencar; Figueiredo, Henrique C P; Henry, Marc

    2018-06-11

    The study aimed to describe the Bubalus bubalis seminal plasma proteome using a label-free shotgun UDMS E approach. A total of 859 nonredundant proteins were identified across five biological replicates with stringent identification. Proteins specifically related to sperm maturation and protection, capacitation, fertilization and metabolic activity were detected in the buffalo seminal fluid. In conclusion, we provide a comprehensive proteomic profile of buffalo seminal plasma, which establishes a foundation for further studies designed to understand regulation of sperm function and discovery of novel biomarkers for fertility. MS data are available in the ProteomeXchange with identifier PXD003728. © 2018 Blackwell Verlag GmbH.

  14. Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

    PubMed Central

    Higgs, Richard E.; Butler, Jon P.; Han, Bomie; Knierman, Michael D.

    2013-01-01

    Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference. PMID:23710359

  15. A Targeted Quantitative Proteomics Strategy for Global Kinome Profiling of Cancer Cells and Tissues*

    PubMed Central

    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

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

    PubMed

    Arntzen, Magnus Ø; Thiede, Bernd

    2012-02-01

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

  17. Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

    PubMed

    Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

    2012-08-01

    Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

  18. SWATH™- and iTRAQ-based quantitative proteomic analyses reveal an overexpression and biological relevance of CD109 in advanced NSCLC.

    PubMed

    Zhang, Fanglin; Lin, Hechun; Gu, Aiqin; Li, Jing; Liu, Lei; Yu, Tao; Cui, Yongqi; Deng, Wei; Yan, Mingxia; Li, Jinjun; Yao, Ming

    2014-05-06

    To identify cancer-related proteins, we used isobaric tags in a relative and absolute quantitation (iTRAQ) proteomic approach and SWATH™ quantification approach to analyze the secretome of an isogenic pair of highly metastatic and low metastatic non-small-cell lung cancer (NSCLC) cell lines. In addition, we compared two groups of pooled serum samples (12 early-stage and 12 late-stage patients) to mine data for candidates screened by iTRAQ-labeled proteomic analysis. A total of 110 proteins and 71 proteins were observed to be significantly differentially expressed in the cell line secretome and NSCLC sera, respectively. Among these proteins, CD109 was found to be highly expressed in both the highly metastatic cell line secretome and the group of late-stage patients. A sandwich ELISA assay also demonstrated an elevation of serum CD109 levels in individual NSCLC patients (n=30) compared with healthy subjects (n=19). Furthermore, CD109 displayed higher expression in lung cancer tissues compared with their matched noncancerous lung tissues (n=72). In addition, the knockdown of CD109 influenced several NSCLC cell bio-functions, for instance, depressing cell growth, affecting cell cycle phases. These phenomena suggest that CD109 plays a critical role in NSCLC progression. We simultaneously applied two quantitative proteomic approaches-iTRAQ-labeling and SWATH™-to analyze the secretome of metastatic cell lines, in order to explore the cancer-associated proteins in conditioned media. In this study, our results indicate that CD109 plays a critical role in non-small-cell lung cancer (NSCLC) progression, and is overexpressed in advanced NSCLC. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria

    PubMed Central

    Hui, Sheng; Silverman, Josh M; Chen, Stephen S; Erickson, David W; Basan, Markus; Wang, Jilong; Hwa, Terence; Williamson, James R

    2015-01-01

    A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies. PMID:25678603

  20. Quantitative analysis of oyster larval proteome provides new insights into the effects of multiple climate change stressors.

    PubMed

    Dineshram, Ramadoss; Chandramouli, Kondethimmanahalli; Ko, Ginger Wai Kuen; Zhang, Huoming; Qian, Pei-Yuan; Ravasi, Timothy; Thiyagarajan, Vengatesen

    2016-06-01

    The metamorphosis of planktonic larvae of the Pacific oyster (Crassostrea gigas) underpins their complex life-history strategy by switching on the molecular machinery required for sessile life and building calcite shells. Metamorphosis becomes a survival bottleneck, which will be pressured by different anthropogenically induced climate change-related variables. Therefore, it is important to understand how metamorphosing larvae interact with emerging climate change stressors. To predict how larvae might be affected in a future ocean, we examined changes in the proteome of metamorphosing larvae under multiple stressors: decreased pH (pH 7.4), increased temperature (30 °C), and reduced salinity (15 psu). Quantitative protein expression profiling using iTRAQ-LC-MS/MS identified more than 1300 proteins. Decreased pH had a negative effect on metamorphosis by down-regulating several proteins involved in energy production, metabolism, and protein synthesis. However, warming switched on these down-regulated pathways at pH 7.4. Under multiple stressors, cell signaling, energy production, growth, and developmental pathways were up-regulated, although metamorphosis was still reduced. Despite the lack of lethal effects, significant physiological responses to both individual and interacting climate change related stressors were observed at proteome level. The metamorphosing larvae of the C. gigas population in the Yellow Sea appear to have adequate phenotypic plasticity at the proteome level to survive in future coastal oceans, but with developmental and physiological costs. © 2016 John Wiley & Sons Ltd.

  1. Quantitative proteomic analysis of whey proteins in the colostrum and mature milk of yak (Bos grunniens).

    PubMed

    Yang, Yongxin; Zhao, Xiaowei; Yu, Shumin; Cao, Suizhong

    2015-02-01

    Yak (Bos grunniens) is an important natural resource in mountainous regions. To date, few studies have addressed the differences in the protein profiles of yak colostrum and milk. We used quantitative proteomics to compare the protein profiles of whey from yak colostrum and milk. Milk samples were collected from 21 yaks after calving (1 and 28 d). Whey protein profiles were generated through isobaric tag for relative and absolute quantification (iTRAQ)-labelled proteomics. We identified 183 proteins in milk whey; of these, the expression levels of 86 proteins differed significantly between the whey from colostrum and milk. Haemoglobin expression showed the greatest change; its levels were significantly higher in the whey from colostrum than in mature milk whey. Functional analysis revealed that many of the differentially expressed proteins were associated with biological regulation and response to stimuli. Further, eight differentially expressed proteins involved in the complement and coagulation cascade pathway were enriched in milk whey. These findings add to the general understanding of the protein composition of yak milk, suggest potential functions of the differentially expressed proteins, and provide novel information on the role of colostral components in calf survival. © 2014 Society of Chemical Industry.

  2. Quantitative proteomics reveals the mechanism and consequence of gliotoxin-mediated dysregulation of the methionine cycle in Aspergillus niger.

    PubMed

    Manzanares-Miralles, Lara; Sarikaya-Bayram, Özlem; Smith, Elizabeth B; Dolan, Stephen K; Bayram, Özgür; Jones, Gary W; Doyle, Sean

    2016-01-10

    Gliotoxin (GT) is a redox-active metabolite, produced by Aspergillus fumigatus, which inhibits the growth of other fungi. Here we demonstrate how Aspergillus niger responds to GT exposure. Quantitative proteomics revealed that GT dysregulated the abundance of 378 proteins including those involved in methionine metabolism and induced de novo abundance of two S-adenosylmethionine (SAM)-dependent methyltransferases. Increased abundance of enzymes S-adenosylhomocysteinase (p=0.0018) required for homocysteine generation from S-adenosylhomocysteine (SAH), and spermidine synthase (p=0.0068), involved in the recycling of Met, was observed. Analysis of Met-related metabolites revealed significant increases in the levels of Met and adenosine, in correlation with proteomic data. Methyltransferase MT-II is responsible for bisthiobis(methylthio)gliotoxin (BmGT) formation, deletion of MT-II abolished BmGT formation and led to increased GT sensitivity in A. niger. Proteomic analysis also revealed that GT exposure also significantly (p<0.05) increased hydrolytic enzyme abundance, including glycoside hydrolases (n=22) and peptidases (n=16). We reveal that in an attempt to protect against the detrimental affects of GT, methyltransferase-mediated GT thiomethylation alters cellular pathways involving Met and SAM, with consequential dysregulation of hydrolytic enzyme abundance in A. niger. Thus, it provides new opportunities to exploit the response of GT-naïve fungi to GT. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective.

    PubMed

    Findeisen, Peter; Neumaier, Michael

    2009-01-01

    Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

  4. Insights into the virulence of oral biofilms: discoveries from proteomics.

    PubMed

    Kuboniwa, Masae; Tribble, Gena D; Hendrickson, Erik L; Amano, Atsuo; Lamont, Richard J; Hackett, Murray

    2012-06-01

    This review covers developments in the study of polymicrobial communities, biofilms and selected areas of host response relevant to dental plaque and related areas of oral biology. The emphasis is on recent studies in which proteomic methods, particularly those using mass spectrometry as a readout, have played a major role in the investigation. The last 5-10 years have seen a transition of such methods from the periphery of oral biology to the mainstream, as in other areas of biomedical science. For reasons of focus and space, the authors do not discuss biomarker studies relevant to improved diagnostics for oral health, as this literature is rather substantial in its own right and deserves a separate treatment. Here, global gene regulation studies of plaque-component organisms, biofilm formation, multispecies interactions and host-microbe interactions are discussed. Several aspects of proteomics methodology that are relevant to the studies of multispecies systems are commented upon.

  5. Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis.

    PubMed

    Dai, Peng; Wang, Qin; Wang, Weihua; Jing, Ruirui; Wang, Wei; Wang, Fengqin; Azadzoi, Kazem M; Yang, Jing-Hua; Yan, Zhen

    2016-01-21

    Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients' tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

  6. Quantitative proteomic analysis for high-throughput screening of differential glycoproteins in hepatocellular carcinoma serum

    PubMed Central

    Gao, Hua-Jun; Chen, Ya-Jing; Zuo, Duo; Xiao, Ming-Ming; Li, Ying; Guo, Hua; Zhang, Ning; Chen, Rui-Bing

    2015-01-01

    Objective Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths. Novel serum biomarkers are required to increase the sensitivity and specificity of serum screening for early HCC diagnosis. This study employed a quantitative proteomic strategy to analyze the differential expression of serum glycoproteins between HCC and normal control serum samples. Methods Lectin affinity chromatography (LAC) was used to enrich glycoproteins from the serum samples. Quantitative mass spectrometric analysis combined with stable isotope dimethyl labeling and 2D liquid chromatography (LC) separations were performed to examine the differential levels of the detected proteins between HCC and control serum samples. Western blot was used to analyze the differential expression levels of the three serum proteins. Results A total of 2,280 protein groups were identified in the serum samples from HCC patients by using the 2D LC-MS/MS method. Up to 36 proteins were up-regulated in the HCC serum, whereas 19 proteins were down-regulated. Three differential glycoproteins, namely, fibrinogen gamma chain (FGG), FOS-like antigen 2 (FOSL2), and α-1,6-mannosylglycoprotein 6-β-N-acetylglucosaminyltransferase B (MGAT5B) were validated by Western blot. All these three proteins were up-regulated in the HCC serum samples. Conclusion A quantitative glycoproteomic method was established and proven useful to determine potential novel biomarkers for HCC. PMID:26487969

  7. Embryology in the era of proteomics.

    PubMed

    Katz-Jaffe, Mandy G; McReynolds, Susanna

    2013-03-15

    Proteomic technologies have begun providing evidence that viable embryos possess unique protein profiles. Some of these potential protein biomarkers have been identified as extracellular and could be used in the development of a noninvasive quantitative method for embryo assessment. The field of assisted reproductive technologies would benefit from defining the human embryonic proteome and secretome, thereby expanding our current knowledge of embryonic cellular processes. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  8. CSF proteomic fingerprints for HIV-associated cognitive impairment.

    PubMed

    Laspiur, Juliana Pérez; Anderson, Eric R; Ciborowski, Pawel; Wojna, Valerie; Rozek, Wojciech; Duan, Fenghai; Mayo, Raul; Rodríguez, Elaine; Plaud-Valentín, Marinés; Rodríguez-Orengo, José; Gendelman, Howard E; Meléndez, Loyda M

    2007-12-01

    Cognitive impairment remains a major complication of advanced human immunodeficiency virus (HIV) infection despite the widespread use of anti-retroviral therapy. Diagnosis is made by exclusion making biomarkers of great potential use. Thus, we used an integrated proteomics platform to assess cerebrospinal fluid protein profiles from 50 HIV-1 seropositive Hispanic women. Nine of 38 proteins identified were unique in those patients with cognitive impairment (CI). These proteins were linked to cell signaling, structural function, and antioxidant activities. This work highlights, in a preliminary manner, the utility of proteomic profiling for biomarker discovery for HIV-1 associated cognitive dysfunction.

  9. CSF proteomic fingerprints for HIV- associated cognitive impairment

    PubMed Central

    Laspiur, Juliana Pérez; Anderson, Eric R.; Ciborowski, Pawel; Wojna, Valerie; Rozek, Wojciech; Duan, Fenghai; Mayo, Raul; Rodríguez, Elaine; Plaud-Valentín, Marinés; Rodríguez-Orengo, José; Gendelman, Howard E.; Meléndez, Loyda M.

    2008-01-01

    Cognitive impairment remains a major complication of advanced human immunodeficiency virus (HIV) infection despite the wide spread use of anti-retroviral therapy. Diagnosis is made by exclusion making biomarkers of great potential use. Thus, we used an integrated proteomics platform to assess cerebrospinal fluid protein profiles from 50 HIV-1 seropositive Hispanic women. Nine of 38 proteins identified were unique in those patients with cognitive impairment. These proteins were linked to cell signaling, structural function, and antioxidant activities. This work highlights, in a preliminary manner, the utility of proteomic profiling for biomarker discovery for HIV-1 associated cognitive dysfunction. PMID:17950469

  10. Integrated omics dissection of proteome dynamics during cardiac remodeling.

    PubMed

    Lau, Edward; Cao, Quan; Lam, Maggie P Y; Wang, Jie; Ng, Dominic C M; Bleakley, Brian J; Lee, Jessica M; Liem, David A; Wang, Ding; Hermjakob, Henning; Ping, Peipei

    2018-01-09

    Transcript abundance and protein abundance show modest correlation in many biological models, but how this impacts disease signature discovery in omics experiments is rarely explored. Here we report an integrated omics approach, incorporating measurements of transcript abundance, protein abundance, and protein turnover to map the landscape of proteome remodeling in a mouse model of pathological cardiac hypertrophy. Analyzing the hypertrophy signatures that are reproducibly discovered from each omics data type across six genetic strains of mice, we find that the integration of transcript abundance, protein abundance, and protein turnover data leads to 75% gain in discovered disease gene candidates. Moreover, the inclusion of protein turnover measurements allows discovery of post-transcriptional regulations across diverse pathways, and implicates distinct disease proteins not found in steady-state transcript and protein abundance data. Our results suggest that multi-omics investigations of proteome dynamics provide important insights into disease pathogenesis in vivo.

  11. Detergents: Friends not foes for high-performance membrane proteomics toward precision medicine.

    PubMed

    Zhang, Xi

    2017-02-01

    Precision medicine, particularly therapeutics, emphasizes the atomic-precise, dynamic, and systems visualization of human membrane proteins and their endogenous modifiers. For years, bottom-up proteomics has grappled with removing and avoiding detergents, yet faltered at the therapeutic-pivotal membrane proteins, which have been tackled by classical approaches and are known for decades refractory to single-phase aqueous or organic denaturants. Hydrophobicity and aggregation commonly challenge tissue and cell lysates, biofluids, and enriched samples. Frequently, expected membrane proteins and peptides are not identified by shotgun bottom-up proteomics, let alone robust quantitation. This review argues the cause of this proteomic crisis is not detergents per se, but the choice of detergents. Recently, inclusion of compatible detergents for membrane protein extraction and digestion has revealed stark improvements in both quantitative and structural proteomics. This review analyzes detergent properties behind recent proteomic advances, and proposes that rational use of detergents may reconcile outstanding membrane proteomics dilemmas, enabling ultradeep coverage and minimal artifacts for robust protein and endogenous PTM measurements. The simplicity of detergent tools confers bottom-up membrane proteomics the sophistication toward precision medicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    PubMed Central

    Arntzen, Magnus Ø.; Thiede, Bernd

    2012-01-01

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

  13. Comparative iTRAQ-Based Quantitative Proteomic Analysis of Pelteobagrus vachelli Liver under Acute Hypoxia: Implications in Metabolic Responses.

    PubMed

    Zhang, Guosong; Zhang, Jiajia; Wen, Xin; Zhao, Cheng; Zhang, Hongye; Li, Xinru; Yin, Shaowu

    2017-09-01

    More and more frequently these days, aquatic ecosystems are being stressed by nutrient enrichment, pollutants, and global warming, leading to a serious depletion in oxygen concentrations. Although a sudden, significant lack of oxygen will result in mortality, fishes can have an acute behavior (e.g., an increase in breathing rate, reduction in swimming frequency) and physiology responses (e.g., increase in oxygen delivery, and reduction in oxygen consumption) to hypoxia, which allows them to maintain normal physical activity. Therefore, in order to shed further light on the molecular mechanisms of hypoxia adaptation in fishes, the authors conduct comparative quantitative proteomics on Pelteobagrus vachelli livers using iTRAQ. The research identifies 511 acute hypoxia-responsive proteins in P. vachelli. Furthermore, comparison of several of the diverse key pathways studied (e.g., peroxisome pathway, PPAR signaling pathway, lipid metabolism, glycolysis/gluco-neogenesis, and amino acid metabolism) help to articulate the different mechanisms involved in the hypoxia response of P. vachelli. Data from proteome analysis shows that P. vachelli can have an acute reaction to hypoxia, including detoxification of metabolic by-products and oxidative stress in light of continued metabolic activity (e.g., peroxisomes), an activation in the capacity of catabolism to get more energy (e.g., lipolysis and amino acid catabolism), a depression in the capacity of biosynthesis to reduce energy consumption (e.g., biosynthesis of amino acids and lipids), and a shift in the aerobic and anaerobic contributions to total metabolism. The observed hypoxia-related changes in the liver proteome of the fish can help to understand or can be related to the hypoxia-related response that takes place in similar conditions in the liver or other proteomes of mammals. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. iTRAQ-based quantitative proteomic analysis of midgut in silkworm infected with Bombyx mori cytoplasmic polyhedrosis virus.

    PubMed

    Gao, Kun; Deng, Xiang-Yuan; Shang, Meng-Ke; Qin, Guang-Xing; Hou, Cheng-Xiang; Guo, Xi-Jie

    2017-01-30

    Bombyx mori cytoplasmic polyhedrosis virus (BmCPV) specifically infects the epithelial cells in the midgut of silkworm and causes them to death, which negatively affects the sericulture industry. In order to determine the midgut response at the protein levels to the virus infection, differential proteomes of the silkworm midgut responsive to BmCPV infection were identified with isobaric tags for relative and absolute quantitation (iTRAQ) labeling followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). 193, 408, 189 differentially expressed proteins (DEPs) were reliably quantified by iTRAQ analysis in the midgut of BmCPV-infected and control larvae at 24, 48, 72h post infection (hpi) respectively. KEGG enrichment analysis showed that Oxidative phosphorylation, amyotrophic lateral sclerosis, Toll-like receptor signaling pathway, steroid hormone biosynthesis were the significant pathways (Q value≤0.05) both at 24 and 48hpi. qRT-PCR was used to further verify gene transcription of 30 DEPs from iTRAQ, showing that the regulations of 24 genes at the transcript level were consistent with those at the proteomic level. Moreover, the cluster analysis of the three time groups showed that there were seven co-regulated DEPs including BGIBMGA002620-PA, which was a putative p62/sequestosome-1 protein in silkworm. It was upregulated at both the mRNA level and the proteomic level and may play an important role in regulating the autophagy and apoptosis (especially apoptosis) induced by BmCPV infection. This was the first report using an iTRAQ approach to analyze proteomes of the silkworm midgut against BmCPV infection, which contributes to understanding the defense mechanisms of silkworm midgut to virus infection. The domesticated silkworm, Bombyx mori, is renowned for silk production as well as being a traditional lepidopteron model insect served as a subject for morphological, genetic, physiological, and developmental studies. Bombyx mori cytoplasmic polyhedrosis

  15. The role of proteomics in studies of protein moonlighting.

    PubMed

    Beynon, Robert J; Hammond, Dean; Harman, Victoria; Woolerton, Yvonne

    2014-12-01

    The increasing acceptance that proteins may exert multiple functions in the cell brings with it new analytical challenges that will have an impact on the field of proteomics. Many proteomics workflows begin by destroying information about the interactions between different proteins, and the reduction of a complex protein mixture to constituent peptides also scrambles information about the combinatorial potential of post-translational modifications. To bring the focus of proteomics on to the domain of protein moonlighting will require novel analytical and quantitative approaches.

  16. Quantitative nucleolar proteomics reveals nuclear re-organization during stress- induced senescence in mouse fibroblast

    PubMed Central

    2011-01-01

    Background Nucleolus is the most prominent mammalian organelle within the nucleus which is also the site for ribosomal biogenesis. There have been many reports indicating the involvement of nucleolus in the process of aging. Several proteins related to aging have been shown to localize in the nucleolus, which suggests the role of this organelle in senescence. Results In this study, we used quantitative mass spectrometry to map the flux of proteins into and out of the nucleolus during the induction of senescence in cultured mammalian cells. Changes in the abundance of 344 nucleolar proteins in sodium butyrate-induced senescence in NIH3T3 cells were studied by SILAC (stable isotope labeling by amino acids in cell culture)-based mass spectrometry. Biochemically, we have validated the proteomic results and confirmed that B23 (nucleophosmin) protein was down-regulated, while poly (ADP-ribose) polymerase (PARP) and nuclear DNA helicase II (NDH II/DHX9/RHA) were up-regulated in the nucleolus upon treatment with sodium butyrate. Accumulation of chromatin in the nucleolus was also observed, by both proteomics and microscopy, in sodium butyrate-treated cells. Similar observations were found in other models of senescence, namely, in mitoxantrone- (MTX) treated cells and primary fibroblasts from the Lamin A knockout mice. Conclusion Our data indicate an extensive nuclear organization during senescence and suggest that the redistribution of B23 protein and chromatin can be used as an important marker for senescence. PMID:21835027

  17. Computational modeling approaches to quantitative structure-binding kinetics relationships in drug discovery.

    PubMed

    De Benedetti, Pier G; Fanelli, Francesca

    2018-03-21

    Simple comparative correlation analyses and quantitative structure-kinetics relationship (QSKR) models highlight the interplay of kinetic rates and binding affinity as an essential feature in drug design and discovery. The choice of the molecular series, and their structural variations, used in QSKR modeling is fundamental to understanding the mechanistic implications of ligand and/or drug-target binding and/or unbinding processes. Here, we discuss the implications of linear correlations between kinetic rates and binding affinity constants and the relevance of the computational approaches to QSKR modeling. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2008-02-01

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

  19. Intraluminal proteome and peptidome of human urinary extracellular vesicles.

    PubMed

    Liu, Xinyu; Chinello, Clizia; Musante, Luca; Cazzaniga, Marta; Tataruch, Dorota; Calzaferri, Giulio; James Smith, Andrew; De Sio, Gabriele; Magni, Fulvio; Zou, Hequn; Holthofer, Harry

    2015-06-01

    Urinary extracellular vesicles (UEVs) are a novel source for disease biomarker discovery. However, Tamm-Horsfall protein (THP) is still a challenge for proteomic analysis since it can inhibit detection of low-abundance proteins. Here, we introduce a new approach that does not involve an ultracentrifugation step to enrich vesicles and that reduces the amount of THP to manageable levels. UEVs were dialyzed and ultrafiltered after reduction and alkylation. The retained fraction was digested with trypsin to reduce the remaining THP and incubated with deoxycholate (DOC). The internal peptidome and internal proteome were analyzed by LC-ESI-MS. A total of 942 different proteins and 3115 unique endogenous peptide fragments deriving from 973 different protein isoforms were identified. Around 82% of the key endosomal sorting complex required for transport components of UEVs generation could be detected from the intraluminal content. Our UEVs preparation protocol provides a simplified way to investigate the intraluminal proteome and peptidome, in particular the subpopulation of UEVs of the trypsin-resistant class of exosomes (positive for tumor susceptibility gene101) and eliminates the majority of interfering proteins such as THP. This method allows the possibility to study endoproteome and endopeptidome of UEVs, thus greatly facilitating biomarker discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Activity-based protein profiling: from enzyme chemistry to proteomic chemistry.

    PubMed

    Cravatt, Benjamin F; Wright, Aaron T; Kozarich, John W

    2008-01-01

    Genome sequencing projects have provided researchers with a complete inventory of the predicted proteins produced by eukaryotic and prokaryotic organisms. Assignment of functions to these proteins represents one of the principal challenges for the field of proteomics. Activity-based protein profiling (ABPP) has emerged as a powerful chemical proteomic strategy to characterize enzyme function directly in native biological systems on a global scale. Here, we review the basic technology of ABPP, the enzyme classes addressable by this method, and the biological discoveries attributable to its application.

  1. Quantitative proteomics reveals the importance of nitrogen source to control glucosinolate metabolism in Arabidopsis thaliana and Brassica oleracea

    PubMed Central

    Marino, Daniel; Ariz, Idoia; Lasa, Berta; Santamaría, Enrique; Fernández-Irigoyen, Joaquín; González-Murua, Carmen; Aparicio Tejo, Pedro M.

    2016-01-01

    Accessing different nitrogen (N) sources involves a profound adaptation of plant metabolism. In this study, a quantitative proteomic approach was used to further understand how the model plant Arabidopsis thaliana adjusts to different N sources when grown exclusively under nitrate or ammonium nutrition. Proteome data evidenced that glucosinolate metabolism was differentially regulated by the N source and that both TGG1 and TGG2 myrosinases were more abundant under ammonium nutrition, which is generally considered to be a stressful situation. Moreover, Arabidopsis plants displayed glucosinolate accumulation and induced myrosinase activity under ammonium nutrition. Interestingly, these results were also confirmed in the economically important crop broccoli (Brassica oleracea var. italica). Moreover, these metabolic changes were correlated in Arabidopsis with the differential expression of genes from the aliphatic glucosinolate metabolic pathway. This study underlines the importance of nitrogen nutrition and the potential of using ammonium as the N source in order to stimulate glucosinolate metabolism, which may have important applications not only in terms of reducing pesticide use, but also for increasing plants’ nutritional value. PMID:27085186

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

    PubMed

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

    2015-09-01

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

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

    PubMed

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

    2007-12-01

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

  4. Oestrus synchronisation and superovulation alter the cervicovaginal mucus proteome of the ewe.

    PubMed

    Maddison, Jessie W; Rickard, Jessica P; Bernecic, Naomi C; Tsikis, Guillaume; Soleilhavoup, Clement; Labas, Valerie; Combes-Soia, Lucie; Harichaux, Gregoire; Druart, Xavier; Leahy, Tamara; de Graaf, Simon P

    2017-02-23

    Although essential for artificial insemination (AI) and MOET (multiple ovulation and embryo transfer), oestrus synchronisation and superovulation are associated with increased female reproductive tract mucus production and altered sperm transport. The effects of such breeding practices on the ovine cervicovaginal (CV) mucus proteome have not been detailed. The aim of this study was to qualitatively and quantitatively investigate the Merino CV mucus proteome in naturally cycling (NAT) ewes at oestrus and mid-luteal phase, and quantitatively compare CV oestrus mucus proteomes of NAT, progesterone synchronised (P4) and superovulated (SOV) ewes. Quantitative analysis revealed 60 proteins were more abundant during oestrus and 127 were more abundant during the luteal phase, with 27 oestrus specific and 40 luteal specific proteins identified. The oestrus proteins most disparate in abundance compared to mid-luteal phase were ceruloplasmin (CP), chitinase-3-like protein 1 (CHI3L1), clusterin (CLU), alkaline phosphatase (ALPL) and mucin-16 (MUC16). Exogenous hormones greatly altered the proteome with 51 and 32 proteins more abundant and 98 and 53 proteins less abundant, in P4 and SOV mucus, respectively when compared to NAT mucus. Investigation of the impact of these proteomic changes on sperm motility and longevity within mucus may help improve sperm transport and fertility following cervical AI. This manuscript is the first to detail the proteome of ovine cervicovaginal mucus using qualitative and quantitative proteomic methods over the oestrous cycle in naturally cycling ewes, and also after application of common oestrus synchronisation and superovulation practices. The investigation of the mucus proteome throughout both the follicular and luteal periods of the oestrous cycle, and also after oestrous synchronisation and superovulation provides information about the endocrine control and the effects that exogenous hormones have on protein expression in the female

  5. A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline

    PubMed Central

    Rudnick, Paul A.; Markey, Sanford P.; Roth, Jeri; Mirokhin, Yuri; Yan, Xinjian; Tchekhovskoi, Dmitrii V.; Edwards, Nathan J.; Thangudu, Ratna R.; Ketchum, Karen A.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Stephen E.

    2016-01-01

    The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics datasets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and non-reference markers of cancer. The CPTAC labs have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these datasets were produced from 2D LC-MS/MS analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) Peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false discovery rate (FDR)-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the datasets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level (“rolled-up”) precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ™. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data, enabling comparisons between different samples and cancer types as well as across the major ‘omics fields. PMID:26860878

  6. A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline.

    PubMed

    Rudnick, Paul A; Markey, Sanford P; Roth, Jeri; Mirokhin, Yuri; Yan, Xinjian; Tchekhovskoi, Dmitrii V; Edwards, Nathan J; Thangudu, Ratna R; Ketchum, Karen A; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Stein, Stephen E

    2016-03-04

    The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics data sets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and nonreference markers of cancer. The CPTAC laboratories have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these data sets were produced from 2D liquid chromatography-tandem mass spectrometry analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false-discovery rate-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the data sets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level ("rolled-up") precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data to enable comparisons between different samples and cancer types as well as across the major omics fields.

  7. Trends in mass spectrometry instrumentation for proteomics

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

    Smith, Richard D.

    2002-12-01

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

  8. Progress on the HUPO Draft Human Proteome: 2017 Metrics of the Human Proteome Project.

    PubMed

    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.

  9. Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery.

    PubMed

    Prieto, DaRue A; Chan, King C; Johann, Donald J; Ye, Xiaoying; Whitely, Gordon; Blonder, Josip

    2017-01-01

    The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

  10. Top-down Proteomics in Health and Disease: Challenges and Opportunities

    PubMed Central

    Gregorich, Zachery R.; Ge, Ying

    2014-01-01

    Proteomics is essential for deciphering how molecules interact as a system and for understanding the functions of cellular systems in human disease; however, the unique characteristics of the human proteome, which include a high dynamic range of protein expression and extreme complexity due to a plethora of post-translational modifications (PTMs) and sequence variations, make such analyses challenging. An emerging “top-down” mass spectrometry (MS)-based proteomics approach, which provides a “bird’s eye” view of all proteoforms, has unique advantages for the assessment of PTMs and sequence variations. Recently, a number of studies have showcased the potential of top-down proteomics for unraveling of disease mechanisms and discovery of new biomarkers. Nevertheless, the top-down approach still faces significant challenges in terms of protein solubility, separation, and the detection of large intact proteins, as well as the under-developed data analysis tools. Consequently, new technological developments are urgently needed to advance the field of top-down proteomics. Herein, we intend to provide an overview of the recent applications of top-down proteomics in biomedical research. Moreover, we will outline the challenges and opportunities facing top-down proteomics strategies aimed at understanding and diagnosing human diseases. PMID:24723472

  11. Instant Integrated Ultradeep Quantitative-structural Membrane Proteomics Discovered Post-translational Modification Signatures for Human Cys-loop Receptor Subunit Bias*

    PubMed Central

    Zhang, Xi

    2016-01-01

    Neurotransmitter ligand-gated ion channels (LGICs) are widespread and pivotal in brain functions. Unveiling their structure-function mechanisms is crucial to drive drug discovery, and demands robust proteomic quantitation of expression, post-translational modifications (PTMs) and dynamic structures. Yet unbiased digestion of these modified transmembrane proteins—at high efficiency and peptide reproducibility—poses the obstacle. Targeting both enzyme-substrate contacts and PTMs for peptide formation and detection, we devised flow-and-detergent-facilitated protease and de-PTM digestions for deep sequencing (FDD) method that combined omni-compatible detergent, tandem immobilized protease/PNGase columns, and Cys-selective reduction/alkylation, to achieve streamlined ultradeep peptide preparation within minutes not days, at high peptide reproducibility and low abundance-bias. FDD transformed enzyme-protein contacts into equal catalytic travel paths through enzyme-excessive columns regardless of protein abundance, removed products instantly preventing inhibition, tackled intricate structures via sequential multiple micro-digestions along the flow, and precisely controlled peptide formation by flow rate. Peptide-stage reactions reduced steric bias; low contamination deepened MS/MS scan; distinguishing disulfide from M oxidation and avoiding gain/loss artifacts unmasked protein-endogenous oxidation states. Using a recent interactome of 285-kDa human GABA type A receptor, this pilot study validated FDD platform's applicability to deep sequencing (up to 99% coverage), H/D-exchange and TMT-based structural mapping. FDD discovered novel subunit-specific PTM signatures, including unusual nontop-surface N-glycosylations, that may drive subunit biases in human Cys-loop LGIC assembly and pharmacology, by redefining subunit/ligand interfaces and connecting function domains. PMID:27073180

  12. Multiple testing corrections in quantitative proteomics: A useful but blunt tool.

    PubMed

    Pascovici, Dana; Handler, David C L; Wu, Jemma X; Haynes, Paul A

    2016-09-01

    Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Proteomics for understanding miRNA biology

    PubMed Central

    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

  14. Structural Proteomics of Herpesviruses

    PubMed Central

    Leroy, Baptiste; Gillet, Laurent; Vanderplasschen, Alain; Wattiez, Ruddy

    2016-01-01

    Herpesviruses are highly prevalent viruses associated with numerous pathologies both in animal and human populations. Until now, most of the strategies used to prevent or to cure these infections have been unsuccessful because these viruses have developed numerous immune evasion mechanisms. Therefore, a better understanding of their complex lifecycle is needed. In particular, while the genome of numerous herpesviruses has been sequenced, the exact composition of virions remains unknown for most of them. Mass spectrometry has recently emerged as a central method and has permitted fundamental discoveries in virology. Here, we review mass spectrometry-based approaches that have recently allowed a better understanding of the composition of the herpesvirus virion. In particular, we describe strategies commonly used for proper sample preparation and fractionation to allow protein localization inside the particle but also to avoid contamination by nonstructural proteins. A collection of other important data regarding post-translational modifications or the relative abundance of structural proteins is also described. This review also discusses the poorly studied importance of host proteins in herpesvirus structural proteins and the necessity to develop a quantitative workflow to better understand the dynamics of the structural proteome. In the future, we hope that this collaborative effort will assist in the development of new strategies to fight these infections. PMID:26907323

  15. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

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

    Wang, Hui; Shi, Tujin; Qian, Wei-Jun

    2015-12-04

    Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances inmore » LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.« less

  16. Proteomics in biomanufacturing control: Protein dynamics of CHO-K1 cells and conditioned media during apoptosis and necrosis.

    PubMed

    Albrecht, Simone; Kaisermayer, Christian; Gallagher, Clair; Farrell, Amy; Lindeberg, Anna; Bones, Jonathan

    2018-06-01

    Cell viability has a critical impact on product quantity and quality during the biomanufacturing of therapeutic proteins. An advanced understanding of changes in the cellular and conditioned media proteomes upon cell stress and death is therefore needed for improved bioprocess control. Here, a high pH/low pH reversed phase data independent 2D-LC-MS E discovery proteomics platform was applied to study the cellular and conditioned media proteomes of CHO-K1 apoptosis and necrosis models where cell death was induced by staurosporine exposure or aeration shear in a benchtop bioreactor, respectively. Functional classification of gene ontology terms related to molecular functions, biological processes, and cellular components revealed both cell death independent and specific features. In addition, label free quantitation using the Hi3 approach resulted in a comprehensive shortlist of 23 potential cell viability marker proteins with highest abundance and a significant increase in the conditioned media upon induction of cell death, including proteins related to cellular stress response, signal mediation, cytoskeletal organization, cell differentiation, cell interaction as well as metabolic and proteolytic enzymes which are interesting candidates for translating into targeted analysis platforms for monitoring bioprocessing response and increasing process control. © 2018 Wiley Periodicals, Inc.

  17. Quantitative proteomic analysis of amniocytes reveals potentially dysregulated molecular networks in Down syndrome

    PubMed Central

    2013-01-01

    Background Down syndrome (DS), caused by an extra copy of chromosome 21, affects 1 in 750 live births and is characterized by cognitive impairment and a constellation of congenital defects. Currently, little is known about the molecular pathogenesis and no direct genotype-phenotype relationship has yet been confirmed. Since DS amniocytes are expected to have a distinct biological behaviour compared to normal amniocytes, we hypothesize that relative quantification of proteins produced from trisomy and euploid (chromosomally normal) amniocytes will reveal dysregulated molecular pathways. Results Chromosomally normal- and Trisomy 21-amniocytes were quantitatively analyzed by using Stable Isotope Labeling of Amino acids in Cell culture and tandem mass spectrometry. A total of 4919 unique proteins were identified from the supernatant and cell lysate proteome. More specifically, 4548 unique proteins were identified from the lysate, and 91% of these proteins were quantified based on MS/MS spectra ratios of peptides containing isotope-labeled amino acids. A total of 904 proteins showed significant differential expression and were involved in 25 molecular pathways, each containing a minimum of 16 proteins. Sixty of these proteins consistently showed aberrant expression from trisomy 21 affected amniocytes, indicating their potential role in DS pathogenesis. Nine proteins were analyzed with a multiplex selected reaction monitoring assay in an independent set of Trisomy 21-amniocyte samples and two of them (SOD1 and NES) showed a consistent differential expression. Conclusions The most extensive proteome of amniocytes and amniotic fluid has been generated and differentially expressed proteins from amniocytes with Trisomy 21 revealed molecular pathways that seem to be most significantly affected by the presence of an extra copy of chromosome 21. PMID:23394617

  18. Triple SILAC quantitative proteomic analysis reveals differential abundance of cell signaling proteins between normal and lung cancer-derived exosomes.

    PubMed

    Clark, David J; Fondrie, William E; Yang, Austin; Mao, Li

    2016-02-05

    Exosomes are 30-100 nm sized membrane vesicles released by cells into the extracellular space that mediate intercellular communication via transfer of proteins and other biological molecules. To better understand the role of these microvesicles in lung carcinogenesis, we employed a Triple SILAC quantitative proteomic strategy to examine the differential protein abundance between exosomes derived from an immortalized normal bronchial epithelial cell line and two non-small cell lung cancer (NSCLC) cell lines harboring distinct activating mutations in the cell signaling molecules: Kirsten rat sarcoma viral oncogene homolog (KRAS) or epidermal growth factor receptor (EGFR). In total, we were able to quantify 721 exosomal proteins derived from the three cell lines. Proteins associated with signal transduction, including EGFR, GRB2 and SRC, were enriched in NSCLC exosomes, and could actively regulate cell proliferation in recipient cells. This study's investigation of the NSCLC exosomal proteome has identified enriched protein cargo that can contribute to lung cancer progression, which may have potential clinical implications in biomarker development for patients with NSCLC. The high mortality associated with lung cancer is a result of late-stage diagnosis of the disease. Current screening techniques used for early detection of lung cancer lack the specificity for accurate diagnosis. Exosomes are nano-sized extracellular vesicles, and the increased abundance of select protein cargo in exosomes derived from cancer cells may be used for diagnostic purposes. In this paper, we applied quantitative proteomic analysis to elucidate abundance differences in exosomal protein cargo between two NSCLC cell lines with distinctive oncogene mutations and an immortalized normal bronchial epithelial cell line. This study revealed proteins associated with cell adhesion, the extracellular matrix, and a variety of signaling molecules were enriched in NSCLC exosomes. The present data reveals

  19. Recent advances in proteomics of cereals.

    PubMed

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

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

  20. Quantitative proteomic analysis of human breast epithelial cells with differential telomere length

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

    Yu, Li-Rong; Chan, King C.; Tahara, Hidetoshi

    Telomeres play important functional roles in cell proliferation, cell cycle regulation, and genetic stability, in which telomere length is critical. In this study, quantitative proteome comparisons for the human breast epithelial cells with short and long telomeres (184-hTERT{sub L} vs. 184-hTERT{sub S} and 90P-hTERT{sub L} vs. 90P-hTERT{sub S}), resulting from transfection of the human telomerase reverse transcriptase (hTERT) gene, were performed using cleavable isotope-coded affinity tags. More than 2000 proteins were quantified in each comparative experiment, with approximately 77% of the proteins identified in both analyses. In the cells with long telomeres, significant and consistent alterations were observed in metabolismmore » (amino acid, nucleotide, and lipid metabolism), genetic information transmission (transcription and translation regulation, spliceosome and ribosome complexes), and cell signaling. Interestingly, the DNA excision repair pathway is enhanced, while integrin and its ligands are downregulated in the cells with long telomeres. These results may provide valuable information related to telomere functions.« less

  1. Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

    PubMed Central

    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

  2. The quantitative proteomes of human-induced pluripotent stem cells and embryonic stem cells

    PubMed Central

    Munoz, Javier; Low, Teck Y; Kok, Yee J; Chin, Angela; Frese, Christian K; Ding, Vanessa; Choo, Andre; Heck, Albert J R

    2011-01-01

    Assessing relevant molecular differences between human-induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs) is important, given that such differences may impact their potential therapeutic use. Controversy surrounds recent gene expression studies comparing hiPSCs and hESCs. Here, we present an in-depth quantitative mass spectrometry-based analysis of hESCs, two different hiPSCs and their precursor fibroblast cell lines. Our comparisons confirmed the high similarity of hESCs and hiPSCS at the proteome level as 97.8% of the proteins were found unchanged. Nevertheless, a small group of 58 proteins, mainly related to metabolism, antigen processing and cell adhesion, was found significantly differentially expressed between hiPSCs and hESCs. A comparison of the regulated proteins with previously published transcriptomic studies showed a low overlap, highlighting the emerging notion that differences between both pluripotent cell lines rather reflect experimental conditions than a recurrent molecular signature. PMID:22108792

  3. Directed shotgun proteomics guided by saturated RNA-seq identifies a complete expressed prokaryotic proteome

    PubMed Central

    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

  4. Directed Shotgun Proteomics Guided by Saturated RNA-seq Identifies a Complete Expressed Prokaryotic Proteome

    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 repertoi