MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

PubMed Central

Hartler, Jürgen; Thallinger, Gerhard G; Stocker, Gernot; Sturn, Alexander; Burkard, Thomas R; Körner, Erik; Rader, Robert; Schmidt, Andreas; Mechtler, Karl; Trajanoski, Zlatko

2007-01-01

Background The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. Results We have developed the MAss SPECTRometry Analysis System (MASPECTRAS), a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo) relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI). Analysis modules include: 1) import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2) peptide validation, 3) clustering of proteins based on Markov Clustering and multiple alignments; and 4) quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio). The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE). MASPECTRAS is freely available at Conclusion Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community. PMID:17567892

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 the much lower effects of pMRTP aerosol than cigarette smoke on the mouse lung proteome. The combined analysis of 2D-PAGE and LC-MS/MS data identified an effect of cigarette smoke on the proteasome and actin cytoskeleton in the lung. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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.

Microfluidic-Mass Spectrometry Interfaces for Translational Proteomics.

PubMed

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

2017-10-01

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

Mass spectrometry-based proteomic exploration of the human immune system: focus on the inflammasome, global protein secretion, and T cells.

PubMed

Nyman, Tuula A; Lorey, Martina B; Cypryk, Wojciech; Matikainen, Sampsa

2017-05-01

The immune system is our defense system against microbial infections and tissue injury, and understanding how it works in detail is essential for developing drugs for different diseases. Mass spectrometry-based proteomics can provide in-depth information on the molecular mechanisms involved in immune responses. Areas covered: Summarized are the key immunology findings obtained with MS-based proteomics in the past five years, with a focus on inflammasome activation, global protein secretion, mucosal immunology, immunopeptidome and T cells. Special focus is on extracellular vesicle-mediated protein secretion and its role in immune responses. Expert commentary: Proteomics is an essential part of modern omics-scale immunology research. To date, MS-based proteomics has been used in immunology to study protein expression levels, their subcellular localization, secretion, post-translational modifications, and interactions in immune cells upon activation by different stimuli. These studies have made major contributions to understanding the molecular mechanisms involved in innate and adaptive immune responses. New developments in proteomics offer constantly novel possibilities for exploring the immune system. Examples of these techniques include mass cytometry and different MS-based imaging approaches which can be widely used in immunology.

Why proteomics is not the new genomics and the future of mass spectrometry in cell biology.

PubMed

Sidoli, Simone; Kulej, Katarzyna; Garcia, Benjamin A

2017-01-02

Mass spectrometry (MS) is an essential part of the cell biologist's proteomics toolkit, allowing analyses at molecular and system-wide scales. However, proteomics still lag behind genomics in popularity and ease of use. We discuss key differences between MS-based -omics and other booming -omics technologies and highlight what we view as the future of MS and its role in our increasingly deep understanding of cell biology. © 2017 Sidoli et al.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

Evaluation of different multidimensional LC-MS/MS pipelines for iTRAQ-based proteomic analysis of potato tubers in response to cold storage

USDA-ARS?s Scientific Manuscript database

Cold-induced sweetening in potato tubers is a costly problem for food industry. To systematically identify the proteins associated with this process, we employed a comparative proteomics approach using isobaric, stable isotope coded labels to compare the proteomes of potato tubers after 0 and 5 mont...

Simple Sodium Dodecyl Sulfate-Assisted Sample Preparation Method for LC-MS-based Proteomic Applications

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

Zhou, Jianying; Dann, Geoffrey P.; Shi, Tujin

2012-03-10

Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for highly efficient biological sample extraction; however, SDS presents a significant challenge to LC-MS-based proteomic analyses due to its severe interference with reversed-phase LC separations and electrospray ionization interfaces. This study reports a simple SDS-assisted proteomic sample preparation method facilitated by a novel peptide-level SDS removal protocol. After SDS-assisted protein extraction and digestion, SDS was effectively (>99.9%) removed from peptides through ion substitution-mediated DS- precipitation with potassium chloride (KCl) followed by {approx}10 min centrifugation. Excellent peptide recovery (>95%) was observed for less than 20 {mu}g of peptides.more » Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage from this SDS-assisted protocol was comparable to or better than those obtained from other standard proteomic preparation methods in both mammalian tissues and bacterial samples. These results suggest that this SDS-assisted protocol is a practical, simple, and broadly applicable proteomic sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.« less

A New Mass Spectrometry-compatible Degradable Surfactant for Tissue Proteomics

PubMed Central

Chang, Ying-Hua; Gregorich, Zachery R.; Chen, Albert J.; Hwang, Leekyoung; Guner, Huseyin; Yu, Deyang; Zhang, Jianyi; Ge, Ying

2015-01-01

Tissue proteomics is increasingly recognized for its role in biomarker discovery and disease mechanism investigation. However, protein solubility remains a significant challenge in mass spectrometry (MS)-based tissue proteomics. Conventional surfactants such as sodium dodecyl sulfate (SDS), the preferred surfactant for protein solubilization, are not compatible with MS. Herein, we have screened a library of surfactant-like compounds and discovered an MS-compatible degradable surfactant (MaSDeS) for tissue proteomics that solubilizes all categories of proteins with performance comparable to SDS. The use of MaSDeS in the tissue extraction significantly improves the total number of protein identifications from commonly used tissues, including tissue from the heart, liver, and lung. Notably, MaSDeS significantly enriches membrane proteins, which are often under-represented in proteomics studies. The acid degradable nature of MaSDeS makes it amenable for high-throughput mass spectrometry-based proteomics. In addition, the thermostability of MaSDeS allows for its use in experiments requiring high temperature to facilitate protein extraction and solubilization. Furthermore, we have shown that MaSDeS outperforms the other MS-compatible surfactants in terms of overall protein solubility and the total number of identified proteins in tissue proteomics. Thus, the use of MaSDeS will greatly advance tissue proteomics and realize its potential in basic biomedical and clinical research. MaSDeS could be utilized in a variety of proteomics studies as well as general biochemical and biological experiments that employ surfactants for protein solubilization. PMID:25589168

High-field asymmetric waveform ion mobility spectrometry for mass spectrometry-based proteomics.

PubMed

Swearingen, Kristian E; Moritz, Robert L

2012-10-01

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve the detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, the authors review recent developments in LC-FAIMS-MS and its application to MS-based proteomics.

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses*

PubMed Central

Rudnick, Paul A.; Clauser, Karl R.; Kilpatrick, Lisa E.; Tchekhovskoi, Dmitrii V.; Neta, Pedatsur; Blonder, Nikša; Billheimer, Dean D.; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Ham, Amy-Joan L.; Jaffe, Jacob D.; Kinsinger, Christopher R.; Mesri, Mehdi; Neubert, Thomas A.; Schilling, Birgit; Tabb, David L.; Tegeler, Tony J.; Vega-Montoto, Lorenzo; Variyath, Asokan Mulayath; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Paulovich, Amanda G.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Tempst, Paul; Liebler, Daniel C.; Stein, Stephen E.

2010-01-01

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications. PMID:19837981

Comparison of sample preparation techniques and data analysis for the LC-MS/MS-based identification of proteins in human follicular fluid.

PubMed

Lehmann, Roland; Schmidt, André; Pastuschek, Jana; Müller, Mario M; Fritzsche, Andreas; Dieterle, Stefan; Greb, Robert R; Markert, Udo R; Slevogt, Hortense

2018-06-25

The proteomic analysis of complex body fluids by liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis requires the selection of suitable sample preparation techniques and optimal parameter settings in data analysis software packages to obtain reliable results. Proteomic analysis of follicular fluid, as a representative of a complex body fluid similar to serum or plasma, is difficult as it contains a vast amount of high abundant proteins and a variety of proteins with different concentrations. However, the accessibility of this complex body fluid for LC-MS/MS analysis is an opportunity to gain insights into the status, the composition of fertility-relevant proteins including immunological factors or for the discovery of new diagnostic and prognostic markers for, for example, the treatment of infertility. In this study, we compared different sample preparation methods (FASP, eFASP and in-solution digestion) and three different data analysis software packages (Proteome Discoverer with SEQUEST, Mascot and MaxQuant with Andromeda) combined with semi- and full-tryptic databank search options to obtain a maximum coverage of the follicular fluid proteome. We found that the most comprehensive proteome coverage is achieved by the eFASP sample preparation method using SDS in the initial denaturing step and the SEQUEST-based semi-tryptic data analysis. In conclusion, we have developed a fractionation-free methodical workflow for in depth LC-MS/MS-based analysis for the standardized investigation of human follicle fluid as an important representative of a complex body fluid. Taken together, we were able to identify a total of 1392 proteins in follicular fluid. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Improving mass measurement accuracy in mass spectrometry based proteomics by combining open source tools for chromatographic alignment and internal calibration.

PubMed

Palmblad, Magnus; van der Burgt, Yuri E M; Dalebout, Hans; Derks, Rico J E; Schoenmaker, Bart; Deelder, André M

2009-05-02

Accurate mass determination enhances peptide identification in mass spectrometry based proteomics. We here describe the combination of two previously published open source software tools to improve mass measurement accuracy in Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS). The first program, msalign, aligns one MS/MS dataset with one FTICRMS dataset. The second software, recal2, uses peptides identified from the MS/MS data for automated internal calibration of the FTICR spectra, resulting in sub-ppm mass measurement errors.

YPED: An Integrated Bioinformatics Suite and Database for Mass Spectrometry-based Proteomics Research

PubMed Central

Colangelo, Christopher M.; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L.; Carriero, Nicholas J.; Gulcicek, Erol E.; Lam, TuKiet T.; Wu, Terence; Bjornson, Robert D.; Bruce, Can; Nairn, Angus C.; Rinehart, Jesse; Miller, Perry L.; Williams, Kenneth R.

2015-01-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry (LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED’s database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. PMID:25712262

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

PubMed

Colangelo, Christopher M; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L; Carriero, Nicholas J; Gulcicek, Erol E; Lam, TuKiet T; Wu, Terence; Bjornson, Robert D; Bruce, Can; Nairn, Angus C; Rinehart, Jesse; Miller, Perry L; Williams, Kenneth R

2015-02-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

PubMed

Griss, Johannes; Jones, Andrew R; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G; Salek, Reza M; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; Del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-10-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience*

PubMed Central

Griss, Johannes; Jones, Andrew R.; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G.; Salek, Reza M.; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-01-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. PMID:24980485

High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) for Mass Spectrometry-Based Proteomics

PubMed Central

Swearingen, Kristian E.; Moritz, Robert L.

2013-01-01

SUMMARY High field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, we review recent developments in LC-FAIMS-MS and its application to MS-based proteomics. PMID:23194268

Multiplexed Post-Experimental Monoisotopic Mass Refinement ( m PE-MMR) to Increase Sensitivity and Accuracy in Peptide Identifications from Tandem Mass Spectra of Cofragmentation

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

Madar, Inamul Hasan; Ko, Seung-Ik; Kim, Hokeun

Mass spectrometry (MS)-based proteomics, which uses high-resolution hybrid mass spectrometers such as the quadrupole-orbitrap mass spectrometer, can yield tens of thousands of tandem mass (MS/MS) spectra of high resolution during a routine bottom-up experiment. Despite being a fundamental and key step in MS-based proteomics, the accurate determination and assignment of precursor monoisotopic masses to the MS/MS spectra remains difficult. The difficulties stem from imperfect isotopic envelopes of precursor ions, inaccurate charge states for precursor ions, and cofragmentation. We describe a composite method of utilizing MS data to assign accurate monoisotopic masses to MS/MS spectra, including those subject to cofragmentation. Themore » method, “multiplexed post-experiment monoisotopic mass refinement” (mPE-MMR), consists of the following: multiplexing of precursor masses to assign multiple monoisotopic masses of cofragmented peptides to the corresponding multiplexed MS/MS spectra, multiplexing of charge states to assign correct charges to the precursor ions of MS/ MS spectra with no charge information, and mass correction for inaccurate monoisotopic peak picking. When combined with MS-GF+, a database search algorithm based on fragment mass difference, mPE-MMR effectively increases both sensitivity and accuracy in peptide identification from complex high-throughput proteomics data compared to conventional methods.« less

State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics.

PubMed

Gopal, Judy; Muthu, Manikandan; Chun, Se-Chul; Wu, Hui-Fen

2015-06-01

Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Assembling proteomics data as a prerequisite for the analysis of large scale experiments

PubMed Central

Schmidt, Frank; Schmid, Monika; Thiede, Bernd; Pleißner, Klaus-Peter; Böhme, Martina; Jungblut, Peter R

2009-01-01

Background Despite the complete determination of the genome sequence of a huge number of bacteria, their proteomes remain relatively poorly defined. Beside new methods to increase the number of identified proteins new database applications are necessary to store and present results of large- scale proteomics experiments. Results In the present study, a database concept has been developed to address these issues and to offer complete information via a web interface. In our concept, the Oracle based data repository system SQL-LIMS plays the central role in the proteomics workflow and was applied to the proteomes of Mycobacterium tuberculosis, Helicobacter pylori, Salmonella typhimurium and protein complexes such as 20S proteasome. Technical operations of our proteomics labs were used as the standard for SQL-LIMS template creation. By means of a Java based data parser, post-processed data of different approaches, such as LC/ESI-MS, MALDI-MS and 2-D gel electrophoresis (2-DE), were stored in SQL-LIMS. A minimum set of the proteomics data were transferred in our public 2D-PAGE database using a Java based interface (Data Transfer Tool) with the requirements of the PEDRo standardization. Furthermore, the stored proteomics data were extractable out of SQL-LIMS via XML. Conclusion The Oracle based data repository system SQL-LIMS played the central role in the proteomics workflow concept. Technical operations of our proteomics labs were used as standards for SQL-LIMS templates. Using a Java based parser, post-processed data of different approaches such as LC/ESI-MS, MALDI-MS and 1-DE and 2-DE were stored in SQL-LIMS. Thus, unique data formats of different instruments were unified and stored in SQL-LIMS tables. Moreover, a unique submission identifier allowed fast access to all experimental data. This was the main advantage compared to multi software solutions, especially if personnel fluctuations are high. Moreover, large scale and high-throughput experiments must be managed in a comprehensive repository system such as SQL-LIMS, to query results in a systematic manner. On the other hand, these database systems are expensive and require at least one full time administrator and specialized lab manager. Moreover, the high technical dynamics in proteomics may cause problems to adjust new data formats. To summarize, SQL-LIMS met the requirements of proteomics data handling especially in skilled processes such as gel-electrophoresis or mass spectrometry and fulfilled the PSI standardization criteria. The data transfer into a public domain via DTT facilitated validation of proteomics data. Additionally, evaluation of mass spectra by post-processing using MS-Screener improved the reliability of mass analysis and prevented storage of data junk. PMID:19166578

Recent development of mass spectrometry and proteomics applications in identification and typing of bacteria.

PubMed

Cheng, Keding; Chui, Huixia; Domish, Larissa; Hernandez, Drexler; Wang, Gehua

2016-04-01

Identification and typing of bacteria occupy a large fraction of time and work in clinical microbiology laboratories. With the certification of some MS platforms in recent years, more applications and tests of MS-based diagnosis methods for bacteria identification and typing have been created, not only on well-accepted MALDI-TOF-MS-based fingerprint matches, but also on solving the insufficiencies of MALDI-TOF-MS-based platforms and advancing the technology to areas such as targeted MS identification and typing of bacteria, bacterial toxin identification, antibiotics susceptibility/resistance tests, and MS-based diagnostic method development on unique bacteria such as Clostridium and Mycobacteria. This review summarizes the recent development in MS platforms and applications in bacteria identification and typing of common pathogenic bacteria. © 2016 The Authors. PROTEOMICS - Clinical Applications Published by WILEY-VCH Verlag GmbH & Co. KGaA.

Comet: an open-source MS/MS sequence database search tool.

PubMed

Eng, Jimmy K; Jahan, Tahmina A; Hoopmann, Michael R

2013-01-01

Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open-source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Conventional-Flow Liquid Chromatography-Mass Spectrometry for Exploratory Bottom-Up Proteomic Analyses.

PubMed

Lenčo, Juraj; Vajrychová, Marie; Pimková, Kristýna; Prokšová, Magdaléna; Benková, Markéta; Klimentová, Jana; Tambor, Vojtěch; Soukup, Ondřej

2018-04-17

Due to its sensitivity and productivity, bottom-up proteomics based on liquid chromatography-mass spectrometry (LC-MS) has become the core approach in the field. The de facto standard LC-MS platform for proteomics operates at sub-μL/min flow rates, and nanospray is required for efficiently introducing peptides into a mass spectrometer. Although this is almost a "dogma", this view is being reconsidered in light of developments in highly efficient chromatographic columns, and especially with the introduction of exceptionally sensitive MS instruments. Although conventional-flow LC-MS platforms have recently penetrated targeted proteomics successfully, their possibilities in discovery-oriented proteomics have not yet been thoroughly explored. Our objective was to determine what are the extra costs and what optimization and adjustments to a conventional-flow LC-MS system must be undertaken to identify a comparable number of proteins as can be identified on a nanoLC-MS system. We demonstrate that the amount of a complex tryptic digest needed for comparable proteome coverage can be roughly 5-fold greater, providing the column dimensions are properly chosen, extra-column peak dispersion is minimized, column temperature and flow rate are set to levels appropriate for peptide separation, and the composition of mobile phases is fine-tuned. Indeed, we identified 2 835 proteins from 2 μg of HeLa cells tryptic digest separated during a 60 min gradient at 68 μL/min on a 1.0 mm × 250 mm column held at 55 °C and using an aqua-acetonitrile mobile phases containing 0.1% formic acid, 0.4% acetic acid, and 3% dimethyl sulfoxide. Our results document that conventional-flow LC-MS is an attractive alternative for bottom-up exploratory proteomics.

Advances in microscale separations towards nanoproteomics applications

DOE PAGES

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

2017-07-21

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. But, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1 μg total proteins (e.g., cellular heterogeneity in tissue pathologies). We review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, andmore » their contributions towards nanoproteomics applications.« less

Advances in microscale separations towards nanoproteomics applications

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

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

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. But, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1 μg total proteins (e.g., cellular heterogeneity in tissue pathologies). We review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, andmore » their contributions towards nanoproteomics applications.« less

Pressurized Pepsin Digestion in Proteomics

PubMed Central

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

2011-01-01

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

A novel algorithm for validating peptide identification from a shotgun proteomics search engine.

PubMed

Jian, Ling; Niu, Xinnan; Xia, Zhonghang; Samir, Parimal; Sumanasekera, Chiranthani; Mu, Zheng; Jennings, Jennifer L; Hoek, Kristen L; Allos, Tara; Howard, Leigh M; Edwards, Kathryn M; Weil, P Anthony; Link, Andrew J

2013-03-01

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has revolutionized the proteomics analysis of complexes, cells, and tissues. In a typical proteomic analysis, the tandem mass spectra from a LC-MS/MS experiment are assigned to a peptide by a search engine that compares the experimental MS/MS peptide data to theoretical peptide sequences in a protein database. The peptide spectra matches are then used to infer a list of identified proteins in the original sample. However, the search engines often fail to distinguish between correct and incorrect peptides assignments. In this study, we designed and implemented a novel algorithm called De-Noise to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. The novel algorithm uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Using proteomics data generated on different types of mass spectrometers, we optimized the De-Noise algorithm on the basis of the resolution and mass accuracy of the mass spectrometer employed in the LC-MS/MS experiment. Our results demonstrate De-Noise improves peptide identification compared to other methods used to process the peptide sequence matches assigned by SEQUEST. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.

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

PubMed Central

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

2014-01-01

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

Capillary electrophoresis interfaced with a mass spectrometer (CE-MS): technical considerations and applicability for biomarker studies in animals.

PubMed

Albalat, Amaya; Husi, Holger; Siwy, Justyna; Nally, Jarlath E; McLauglin, Mark; Eckersall, Peter D; Mullen, William

2014-02-01

Proteomics is a growing field that has the potential to be applied to many biology-related disciplines. However, the study of the proteome has proven to be very challenging due to its high level of complexity when compared to genome and transcriptome data. In order to analyse this level of complexity, high resolution separation of peptides/proteins are needed together with high resolution analysers. Currently, liquid chromatography and capillary electrophoresis (CE) are the two most widely used separation techniques that can be coupled on-line with a mass spectrometer (MS). In CE, proteins/ peptides are separated according to their size, charge and shape leading to high resolving power. Although further progress in the area of sensitivity, throughput and proteome coverage are expected, MS-based proteomics have developed to a level at which they are habitually applied to study a wide range of biological questions. The aim of this review is to present CE-MS as a proteomic analytical platform for biomarker research that could be used in farm animal and veterinary studies. This is a MS-analytical platform that has been widely used for biomarker research in the biomedical field but its application in animal proteomic studies is relatively novel. The review will focus on introducing the CE-MS platform and the primary considerations for its application to biomarker research. Furthermore, current applications but more importantly potential application in the field of farm animals and veterinary science will be presented and discussed.

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

PubMed Central

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

2016-01-01

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

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

PubMed

Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D; Rodland, Karin D; Camp, David G

2016-01-01

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Evaluation of comprehensive multidimensional separations using reversed-phase, reversed-phase liquid chromatography/mass spectrometry for shotgun proteomics.

PubMed

Nakamura, Tatsuji; Kuromitsu, Junro; Oda, Yoshiya

2008-03-01

Two-dimensional liquid-chromatographic (LC) separation followed by mass spectrometric (MS) analysis was examined for the identification of peptides in complex mixtures as an alternative to widely used two-dimensional gel electrophoresis followed by MS analysis for use in proteomics. The present method involves the off-line coupling of a narrow-bore, polymer-based, reversed-phase column using an acetonitrile gradient in an alkaline mobile phase in the first dimension with octadecylsilanized silica (ODS)-based nano-LC/MS in the second dimension. After the first separation, successive fractions were acidified and dried off-line, then loaded on the second dimension column. Both columns separate peptides according to hydrophobicity under different pH conditions, but more peptides were identified than with the conventional technique for shotgun proteomics, that is, the combination of a strong cation exchange column with an ODS column, and the system was robust because no salts were included in the mobile phases. The suitability of the method for proteomics measurements was evaluated.

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

Intact mass detection, interpretation, and visualization to automate Top-Down proteomics on a large scale

PubMed Central

Durbin, Kenneth R.; Tran, John C.; Zamdborg, Leonid; Sweet, Steve M. M.; Catherman, Adam D.; Lee, Ji Eun; Li, Mingxi; Kellie, John F.; Kelleher, Neil L.

2011-01-01

Applying high-throughput Top-Down MS to an entire proteome requires a yet-to-be-established model for data processing. Since Top-Down is becoming possible on a large scale, we report our latest software pipeline dedicated to capturing the full value of intact protein data in automated fashion. For intact mass detection, we combine algorithms for processing MS1 data from both isotopically resolved (FT) and charge-state resolved (ion trap) LC-MS data, which are then linked to their fragment ions for database searching using ProSight. Automated determination of human keratin and tubulin isoforms is one result. Optimized for the intricacies of whole proteins, new software modules visualize proteome-scale data based on the LC retention time and intensity of intact masses and enable selective detection of PTMs to automatically screen for acetylation, phosphorylation, and methylation. Software functionality was demonstrated using comparative LC-MS data from yeast strains in addition to human cells undergoing chemical stress. We further these advances as a key aspect of realizing Top-Down MS on a proteomic scale. PMID:20848673

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 article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. © 2013.

Striking against bioterrorism with advanced proteomics and reference methods.

PubMed

Armengaud, Jean

2017-01-01

The intentional use by terrorists of biological toxins as weapons has been of great concern for many years. Among the numerous toxins produced by plants, animals, algae, fungi, and bacteria, ricin is one of the most scrutinized by the media because it has already been used in biocrimes and acts of bioterrorism. Improving the analytical toolbox of national authorities to monitor these potential bioweapons all at once is of the utmost interest. MS/MS allows their absolute quantitation and exhibits advantageous sensitivity, discriminative power, multiplexing possibilities, and speed. In this issue of Proteomics, Gilquin et al. (Proteomics 2017, 17, 1600357) present a robust multiplex assay to quantify a set of eight toxins in the presence of a complex food matrix. This MS/MS reference method is based on scheduled SRM and high-quality standards consisting of isotopically labeled versions of these toxins. Their results demonstrate robust reliability based on rather loose scheduling of SRM transitions and good sensitivity for the eight toxins, lower than their oral median lethal doses. In the face of an increased threat from terrorism, relevant reference assays based on advanced proteomics and high-quality companion toxin standards are reliable and firm answers. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A multi-center study benchmarks software tools for label-free proteome quantification

PubMed Central

Gillet, Ludovic C; Bernhardt, Oliver M.; MacLean, Brendan; Röst, Hannes L.; Tate, Stephen A.; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I.; Aebersold, Ruedi; Tenzer, Stefan

2016-01-01

The consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra), a method that uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test datasets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation windows setups. For consistent evaluation we developed LFQbench, an R-package to calculate metrics of precision and accuracy in label-free quantitative MS, and report the identification performance, robustness and specificity of each software tool. Our reference datasets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics. PMID:27701404

A multicenter study benchmarks software tools for label-free proteome quantification.

PubMed

Navarro, Pedro; Kuharev, Jörg; Gillet, Ludovic C; Bernhardt, Oliver M; MacLean, Brendan; Röst, Hannes L; Tate, Stephen A; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I; Aebersold, Ruedi; Tenzer, Stefan

2016-11-01

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

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.

Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML database--Xindice.

PubMed

Li, Feng; Li, Maoyu; Xiao, Zhiqiang; Zhang, Pengfei; Li, Jianling; Chen, Zhuchu

2006-01-11

Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database. The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database. Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at http://www.xyproteomics.org/.

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.

A Bayesian algorithm for detecting differentially expressed proteins and its application in breast cancer research

NASA Astrophysics Data System (ADS)

Santra, Tapesh; Delatola, Eleni Ioanna

2016-07-01

Presence of considerable noise and missing data points make analysis of mass-spectrometry (MS) based proteomic data a challenging task. The missing values in MS data are caused by the inability of MS machines to reliably detect proteins whose abundances fall below the detection limit. We developed a Bayesian algorithm that exploits this knowledge and uses missing data points as a complementary source of information to the observed protein intensities in order to find differentially expressed proteins by analysing MS based proteomic data. We compared its accuracy with many other methods using several simulated datasets. It consistently outperformed other methods. We then used it to analyse proteomic screens of a breast cancer (BC) patient cohort. It revealed large differences between the proteomic landscapes of triple negative and Luminal A, which are the most and least aggressive types of BC. Unexpectedly, majority of these differences could be attributed to the direct transcriptional activity of only seven transcription factors some of which are known to be inactive in triple negative BC. We also identified two new proteins which significantly correlated with the survival of BC patients, and therefore may have potential diagnostic/prognostic values.

Expert system for computer-assisted annotation of MS/MS spectra.

PubMed

Neuhauser, Nadin; Michalski, Annette; Cox, Jürgen; Mann, Matthias

2012-11-01

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions.

Expert System for Computer-assisted Annotation of MS/MS Spectra*

PubMed Central

Neuhauser, Nadin; Michalski, Annette; Cox, Jürgen; Mann, Matthias

2012-01-01

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions. PMID:22888147

An accurate proteomic quantification method: fluorescence labeling absolute quantification (FLAQ) using multidimensional liquid chromatography and tandem mass spectrometry.

PubMed

Liu, Junyan; Liu, Yang; Gao, Mingxia; Zhang, Xiangmin

2012-08-01

A facile proteomic quantification method, fluorescent labeling absolute quantification (FLAQ), was developed. Instead of using MS for quantification, the FLAQ method is a chromatography-based quantification in combination with MS for identification. Multidimensional liquid chromatography (MDLC) with laser-induced fluorescence (LIF) detection with high accuracy and tandem MS system were employed for FLAQ. Several requirements should be met for fluorescent labeling in MS identification: Labeling completeness, minimum side-reactions, simple MS spectra, and no extra tandem MS fragmentations for structure elucidations. A fluorescence dye, 5-iodoacetamidofluorescein, was finally chosen to label proteins on all cysteine residues. The fluorescent dye was compatible with the process of the trypsin digestion and MALDI MS identification. Quantitative labeling was achieved with optimization of reacting conditions. A synthesized peptide and model proteins, BSA (35 cysteines), OVA (five cysteines), were used for verifying the completeness of labeling. Proteins were separated through MDLC and quantified based on fluorescent intensities, followed by MS identification. High accuracy (RSD% < 1.58) and wide linearity of quantification (1-10(5) ) were achieved by LIF detection. The limit of quantitation for the model protein was as low as 0.34 amol. Parts of proteins in human liver proteome were quantified and demonstrated using FLAQ. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultrahigh pressure fast size exclusion chromatography for top-down proteomics.

PubMed

Chen, Xin; Ge, Ying

2013-09-01

Top-down MS-based proteomics has gained a solid growth over the past few years but still faces significant challenges in the LC separation of intact proteins. In top-down proteomics, it is essential to separate the high mass proteins from the low mass species due to the exponential decay in S/N as a function of increasing molecular mass. SEC is a favored LC method for size-based separation of proteins but suffers from notoriously low resolution and detrimental dilution. Herein, we reported the use of ultrahigh pressure (UHP) SEC for rapid and high-resolution separation of intact proteins for top-down proteomics. Fast separation of intact proteins (6-669 kDa) was achieved in < 7 min with high resolution and high efficiency. More importantly, we have shown that this UHP-SEC provides high-resolution separation of intact proteins using a MS-friendly volatile solvent system, allowing the direct top-down MS analysis of SEC-eluted proteins without an additional desalting step. Taken together, we have demonstrated that UHP-SEC is an attractive LC strategy for the size separation of proteins with great potential for top-down proteomics. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MS Data Miner: a web-based software tool to analyze, compare, and share mass spectrometry protein identifications.

PubMed

Dyrlund, Thomas F; Poulsen, Ebbe T; Scavenius, Carsten; Sanggaard, Kristian W; Enghild, Jan J

2012-09-01

Data processing and analysis of proteomics data are challenging and time consuming. In this paper, we present MS Data Miner (MDM) (http://sourceforge.net/p/msdataminer), a freely available web-based software solution aimed at minimizing the time required for the analysis, validation, data comparison, and presentation of data files generated in MS software, including Mascot (Matrix Science), Mascot Distiller (Matrix Science), and ProteinPilot (AB Sciex). The program was developed to significantly decrease the time required to process large proteomic data sets for publication. This open sourced system includes a spectra validation system and an automatic screenshot generation tool for Mascot-assigned spectra. In addition, a Gene Ontology term analysis function and a tool for generating comparative Excel data reports are included. We illustrate the benefits of MDM during a proteomics study comprised of more than 200 LC-MS/MS analyses recorded on an AB Sciex TripleTOF 5600, identifying more than 3000 unique proteins and 3.5 million peptides. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant.

PubMed

Kovalchik, Kevin A; Moggridge, Sophie; Chen, David D Y; Morin, Gregg B; Hughes, Christopher S

2018-06-01

Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the "raw" MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS 1 , MS 2 , and MS 3 metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags.

Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.

PubMed

Li, Ming; Gray, William; Zhang, Haixia; Chung, Christine H; Billheimer, Dean; Yarbrough, Wendell G; Liebler, Daniel C; Shyr, Yu; Slebos, Robbert J C

2010-08-06

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher's Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples.

Comparative Shotgun Proteomics Using Spectral Count Data and Quasi-Likelihood Modeling

PubMed Central

2010-01-01

Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples. PMID:20586475

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.

Image analysis tools and emerging algorithms for expression proteomics

PubMed Central

English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

2012-01-01

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

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

PubMed

Jiménez, Rafael C; Vizcaíno, Juan Antonio

2013-01-01

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

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

Functional protease profiling for diagnosis of malignant disease.

PubMed

Findeisen, Peter; Neumaier, Michael

2012-01-01

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

CPTAC Assay Portal: a repository of targeted proteomic assays

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

Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.

2014-06-27

To address these issues, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as a public repository of well-characterized quantitative, MS-based, targeted proteomic assays. The purpose of the CPTAC Assay Portal is to facilitate widespread adoption of targeted MS assays by disseminating SOPs, reagents, and assay characterization data for highly characterized assays. A primary aim of the NCI-supported portal is to bring together clinicians or biologists and analytical chemists to answer hypothesis-driven questions using targeted, MS-based assays. Assay content is easily accessed through queries and filters, enabling investigatorsmore » to find assays to proteins relevant to their areas of interest. Detailed characterization data are available for each assay, enabling researchers to evaluate assay performance prior to launching the assay in their own laboratory.« less

A Researcher's Guide to Mass Spectrometry-Based Proteomics

PubMed Central

Savaryn, John P.; Toby, Timothy K.; Kelleher, Neil L.

2016-01-01

Mass spectrometry (MS) is widely recognized as a powerful analytical tool for molecular research. MS is used by researchers around the globe to identify, quantify, and characterize biomolecules like proteins from any number of biological conditions or sample types. As instrumentation has advanced, and with the coupling of liquid chromatography (LC) for high-throughput LC-MS/MS, a proteomics experiment measuring hundreds to thousands of proteins/protein groups is now commonplace. While expert practitioners who best understand the operation of LC-MS systems tend to have strong backgrounds in physics and engineering, consumers of proteomics data and technology are not exposed to the physio-chemical principles underlying the information they seek. Since articles and reviews tend not to focus on bridging this divide, our goal here is to span this gap and translate MS ion physics into language intuitive to the general reader active in basic or applied biomedical research. Here, we visually describe what happens to ions as they enter and move around inside a mass spectrometer. We describe basic MS principles, including electric current, ion optics, ion traps, quadrupole mass filters, and Orbitrap FT-analyzers. PMID:27553853

Mass spectrometric identification of proteins in complex post-genomic projects. Soluble proteins of the metabolically versatile, denitrifying 'Aromatoleum' sp. strain EbN1.

PubMed

Hufnagel, Peter; Rabus, Ralf

2006-01-01

The rapidly developing proteomics technologies help to advance the global understanding of physiological and cellular processes. The lifestyle of a study organism determines the type and complexity of a given proteomic project. The complexity of this study is characterized by a broad collection of pathway-specific subproteomes, reflecting the metabolic versatility as well as the regulatory potential of the aromatic-degrading, denitrifying bacterium 'Aromatoleum' sp. strain EbN1. Differences in protein profiles were determined using a gel-based approach. Protein identification was based on a progressive application of MALDI-TOF-MS, MALDI-TOF-MS/MS and LC-ESI-MS/MS. This progression was result-driven and automated by software control. The identification rate was increased by the assembly of a project-specific list of background signals that was used for internal calibration of the MS spectra, and by the combination of two search engines using a dedicated MetaScoring algorithm. In total, intelligent bioinformatics could increase the identification yield from 53 to 70% of the analyzed 5,050 gel spots; a total of 556 different proteins were identified. MS identification was highly reproducible: most proteins were identified more than twice from parallel 2DE gels with an average sequence coverage of >50% and rather restrictive score thresholds (Mascot >or=95, ProFound >or=2.2, MetaScore >or=97). The MS technologies and bioinformatics tools that were implemented and integrated to handle this complex proteomic project are presented. In addition, we describe the basic principles and current developments of the applied technologies and provide an overview over the current state of microbial proteome research. Copyright (c) 2006 S. Karger AG, Basel.

A liquid chromatography-tandem mass spectrometry-based targeted proteomics assay for monitoring P-glycoprotein levels in human breast tissue.

PubMed

Yang, Ting; Chen, Fei; Xu, Feifei; Wang, Fengliang; Xu, Qingqing; Chen, Yun

2014-09-25

P-glycoprotein (P-gp) can efflux drugs from cancer cells, and its overexpression is commonly associated with multi-drug resistance (MDR). Thus, the accurate quantification of P-gp would help predict the response to chemotherapy and for prognosis of breast cancer patients. An advanced liquid chromatography-tandem mass spectrometry (LC/MS/MS)-based targeted proteomics assay was developed and validated for monitoring P-gp levels in breast tissue. Tryptic peptide 368IIDNKPSIDSYSK380 was selected as a surrogate analyte for quantification, and immuno-depleted tissue extract was used as a surrogate matrix. Matched pairs of breast tissue samples from 60 patients who were suspected to have drug resistance were subject to analysis. The levels of P-gp were quantified. Using data from normal tissue, we suggested a P-gp reference interval. The experimental values of tumor tissue samples were compared with those obtained from Western blotting and immunohistochemistry (IHC). The result indicated that the targeted proteomics approach was comparable to IHC but provided a lower limit of quantification (LOQ) and could afford more reliable results at low concentrations than the other two methods. LC/MS/MS-based targeted proteomics may allow the quantification of P-gp in breast tissue in a more accurate manner. Copyright © 2014 Elsevier B.V. All rights reserved.

Informed-Proteomics: open-source software package for top-down proteomics

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

Park, Jungkap; Piehowski, Paul D.; Wilkins, Christopher

Top-down proteomics involves the analysis of intact proteins. This approach is very attractive as it allows for analyzing proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms, proteolytic processing or their combinations collectively called proteoforms. Moreover, the quality of the top-down LC-MS/MS datasets is rapidly increasing due to advances in the liquid chromatography and mass spectrometry instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compare to the more conventional bottom-up data. To take full advantage of the increasing quality of the top-down LC-MS/MS datasets there is an urgent needmore » to develop algorithms and software tools for confident proteoform identification and quantification. In this study we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.« less

Global iTRAQ-based proteomic profiling of Toxoplasma gondii oocysts during sporulation.

PubMed

Zhou, Chun-Xue; Zhu, Xing-Quan; Elsheikha, Hany M; He, Shuai; Li, Qian; Zhou, Dong-Hui; Suo, Xun

2016-10-04

Toxoplasma gondii is a medically and economically important protozoan parasite. However, the molecular mechanisms of its sporulation remain largely unknown. Here, we applied iTRAQ coupled with 2D LC-MS/MS proteomic analysis to investigate the proteomic expression profile of T. gondii oocysts during sporulation. Of the 2095 non-redundant proteins identified, 587 were identified as differentially expressed proteins (DEPs). Based on Gene Ontology enrichment and KEGG pathway analyses the majority of these DEPs were found related to the metabolism of amino acids, carbon and energy. Protein interaction network analysis generated by STRING identified ATP-citrate lyase (ACL), GMP synthase, IMP dehydrogenase (IMPDH), poly (ADP-ribose) glycohydrolase (PARG), and bifunctional dihydrofolate reductase-thymidylate synthase (DHFR-TS) as the top five hubs. We also identified 25 parasite virulence factors that were expressed at relatively high levels in sporulated oocysts compared to non-sporulated oocysts, which might contribute to the infectivity of mature oocysts. Considering the importance of oocysts in the dissemination of toxoplasmosis these findings may help in the search of protein targets with a key role in infectiousness and ecological success of oocysts, creating new opportunities for the development of better means for disease prevention. The development of new preventative interventions against T. gondii infection relies on an improved understanding of the proteome and chemical pathways of this parasite. To identify proteins required for the development of environmentally resistant and infective T. gondii oocysts, we compared the proteome of non-sporulated (immature) oocysts with the proteome of sporulated (mature, infective) oocysts. iTRAQ 2D-LC-MS/MS analysis revealed proteomic changes that distinguish non-sporulated from sporulated oocysts. Many of the differentially expressed proteins were involved in metabolic pathways and 25 virulence factors were identified upregulated in the sporulated oocysts. This work provides the first quantitative characterization of the proteomic variations that occur in T. gondii oocyst stage during sporulation. Copyright © 2016. Published by Elsevier B.V.

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

PubMed Central

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

2007-01-01

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

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.

HTAPP: High-Throughput Autonomous Proteomic Pipeline

PubMed Central

Yu, Kebing; Salomon, Arthur R.

2011-01-01

Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic datasets is critically important. The high-throughput autonomous proteomic pipeline (HTAPP) described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is comprised of software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of HTAPP focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples. PMID:20336676

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics*

PubMed Central

Cai, Wenxuan; Guner, Huseyin; Gregorich, Zachery R.; Chen, Albert J.; Ayaz-Guner, Serife; Peng, Ying; Valeja, Santosh G.; Liu, Xiaowen; Ge, Ying

2016-01-01

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics. PMID:26598644

Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

PubMed Central

Imperlini, Esther; Santorelli, Lucia; Orrù, Stefania; Scolamiero, Emanuela; Ruoppolo, Margherita

2016-01-01

Organic acidemias (OAs) are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA), neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS-) based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs. PMID:27403441

A two-dimensional proteome map of the aflatoxigenic fungus Aspergillus flavus.

PubMed

Pechanova, Olga; Pechan, Tibor; Rodriguez, Jose M; Williams, W Paul; Brown, Ashli E

2013-05-01

The filamentous fungus Aspergillus flavus is an opportunistic soil-borne pathogen that produces aflatoxins, the most potent naturally occurring carcinogenic compounds known. This work represents the first gel-based profiling analysis of A. flavus proteome and establishes a 2D proteome map. Using 2DE and MALDI-TOF-MS/MS, we identified 538 mycelial proteins of the aflatoxigenic strain NRRL 3357, the majority of which were functionally annotated as related to various cellular metabolic and biosynthetic processes. Additionally, a few enzymes from the aflatoxin synthesis pathway were also identified. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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, including the analysis of post-translational modifications, and the design of MS-based assays for validation of differentially expressed proteins in large datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Coupling Capillary Zone Electrophoresis to a Q Exactive HF Mass Spectrometer for Top-down Proteomics: 580 Proteoform Identifications from Yeast.

PubMed

Zhao, Yimeng; Sun, Liangliang; Zhu, Guijie; Dovichi, Norman J

2016-10-07

We used reversed-phase liquid chromatography to separate the yeast proteome into 23 fractions. These fractions were then analyzed using capillary zone electrophoresis (CZE) coupled to a Q-Exactive HF mass spectrometer using an electrokinetically pumped sheath flow interface. The parameters of the mass spectrometer were first optimized for top-down proteomics using a mixture of seven model proteins; we observed that intact protein mode with a trapping pressure of 0.2 and normalized collision energy of 20% produced the highest intact protein signals and most protein identifications. Then, we applied the optimized parameters for analysis of the fractionated yeast proteome. From this, 580 proteoforms and 180 protein groups were identified via database searching of the MS/MS spectra. This number of proteoform identifications is two times larger than that of previous CZE-MS/MS studies. An additional 3,243 protein species were detected based on the parent ion spectra. Post-translational modifications including N-terminal acetylation, signal peptide removal, and oxidation were identified.

Time Series Proteome Profiling

PubMed Central

Formolo, Catherine A.; Mintz, Michelle; Takanohashi, Asako; Brown, Kristy J.; Vanderver, Adeline; Halligan, Brian; Hathout, Yetrib

2014-01-01

This chapter provides a detailed description of a method used to study temporal changes in the endoplasmic reticulum (ER) proteome of fibroblast cells exposed to ER stress agents (tunicamycin and thapsigargin). Differential stable isotope labeling by amino acids in cell culture (SILAC) is used in combination with crude ER fractionation, SDS–PAGE and LC-MS/MS to define altered protein expression in tunicamycin or thapsigargin treated cells versus untreated cells. Treated and untreated cells are harvested at different time points, mixed at a 1:1 ratio and processed for ER fractionation. Samples containing labeled and unlabeled proteins are separated by SDS–PAGE, bands are digested with trypsin and the resulting peptides analyzed by LC-MS/MS. Proteins are identified using Bioworks software and the Swiss-Prot data-base, whereas ratios of protein expression between treated and untreated cells are quantified using ZoomQuant software. Data visualization is facilitated by GeneSpring software. proteomics PMID:21082445

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-12-16

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

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

PubMed

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

2016-09-01

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

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

PubMed

Hamzeiy, Hamid; Cox, Jürgen

2017-02-01

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

Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

DOE PAGES

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.; ...

2017-09-01

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here in this study, we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap),more » leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. Finally, the present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.« less

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

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

Cancer.gov

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory colon study data. The goal of the study is to analyze the proteomes of approximately 100 confirmatory colon tumor patients, which includes tumor and adjacent normal samples, with liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic and phosphoproteomic profiling.

Integrative proteomics, genomics, and translational immunology approaches reveal mutated forms of Proteolipid Protein 1 (PLP1) and mutant-specific immune response in multiple sclerosis.

PubMed

Qendro, Veneta; Bugos, Grace A; Lundgren, Debbie H; Glynn, John; Han, May H; Han, David K

2017-03-01

In order to gain mechanistic insights into multiple sclerosis (MS) pathogenesis, we utilized a multi-dimensional approach to test the hypothesis that mutations in myelin proteins lead to immune activation and central nervous system autoimmunity in MS. Mass spectrometry-based proteomic analysis of human MS brain lesions revealed seven unique mutations of PLP1; a key myelin protein that is known to be destroyed in MS. Surprisingly, in-depth genomic analysis of two MS patients at the genomic DNA and mRNA confirmed mutated PLP1 in RNA, but not in the genomic DNA. Quantification of wild type and mutant PLP RNA levels by qPCR further validated the presence of mutant PLP RNA in the MS patients. To seek evidence linking mutations in abundant myelin proteins and immune-mediated destruction of myelin, specific immune response against mutant PLP1 in MS patients was examined. Thus, we have designed paired, wild type and mutant peptide microarrays, and examined antibody response to multiple mutated PLP1 in sera from MS patients. Consistent with the idea of different patients exhibiting unique mutation profiles, we found that 13 out of 20 MS patients showed antibody responses against specific but not against all the mutant-PLP1 peptides. Interestingly, we found mutant PLP-directed antibody response against specific mutant peptides in the sera of pre-MS controls. The results from integrative proteomic, genomic, and immune analyses reveal a possible mechanism of mutation-driven pathogenesis in human MS. The study also highlights the need for integrative genomic and proteomic analyses for uncovering pathogenic mechanisms of human diseases. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The diverse and expanding role of mass spectrometry in structural and molecular biology.

PubMed

Lössl, Philip; van de Waterbeemd, Michiel; Heck, Albert Jr

2016-12-15

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

Standardization approaches in absolute quantitative proteomics with mass spectrometry.

PubMed

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

2017-07-31

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

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

PubMed

Hoopmann, Michael R; Moritz, Robert L

2013-02-01

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

AT_CHLORO, a comprehensive chloroplast proteome database with subplastidial localization and curated information on envelope proteins.

PubMed

Ferro, Myriam; Brugière, Sabine; Salvi, Daniel; Seigneurin-Berny, Daphné; Court, Magali; Moyet, Lucas; Ramus, Claire; Miras, Stéphane; Mellal, Mourad; Le Gall, Sophie; Kieffer-Jaquinod, Sylvie; Bruley, Christophe; Garin, Jérôme; Joyard, Jacques; Masselon, Christophe; Rolland, Norbert

2010-06-01

Recent advances in the proteomics field have allowed a series of high throughput experiments to be conducted on chloroplast samples, and the data are available in several public databases. However, the accurate localization of many chloroplast proteins often remains hypothetical. This is especially true for envelope proteins. We went a step further into the knowledge of the chloroplast proteome by focusing, in the same set of experiments, on the localization of proteins in the stroma, the thylakoids, and envelope membranes. LC-MS/MS-based analyses first allowed building the AT_CHLORO database (http://www.grenoble.prabi.fr/protehome/grenoble-plant-proteomics/), a comprehensive repertoire of the 1323 proteins, identified by 10,654 unique peptide sequences, present in highly purified chloroplasts and their subfractions prepared from Arabidopsis thaliana leaves. This database also provides extensive proteomics information (peptide sequences and molecular weight, chromatographic retention times, MS/MS spectra, and spectral count) for a unique chloroplast protein accurate mass and time tag database gathering identified peptides with their respective and precise analytical coordinates, molecular weight, and retention time. We assessed the partitioning of each protein in the three chloroplast compartments by using a semiquantitative proteomics approach (spectral count). These data together with an in-depth investigation of the literature were compiled to provide accurate subplastidial localization of previously known and newly identified proteins. A unique knowledge base containing extensive information on the proteins identified in envelope fractions was thus obtained, allowing new insights into this membrane system to be revealed. Altogether, the data we obtained provide unexpected information about plastidial or subplastidial localization of some proteins that were not suspected to be associated to this membrane system. The spectral counting-based strategy was further validated as the compartmentation of well known pathways (for instance, photosynthesis and amino acid, fatty acid, or glycerolipid biosynthesis) within chloroplasts could be dissected. It also allowed revisiting the compartmentation of the chloroplast metabolism and functions.

Making proteomics data accessible and reusable: Current state of proteomics databases and repositories

PubMed Central

Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio

2015-01-01

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. PMID:25158685

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

PubMed

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

2007-01-01

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

Advances in microscale separations towards nanoproteomics applications

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

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

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

Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

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

Zhu, Ying; Zhao, Rui; Piehowski, Paul D.

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading tomore » a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.« less

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification.

PubMed

Gao, Jing; Zhong, Shaoyun; Zhou, Yanting; He, Han; Peng, Shuying; Zhu, Zhenyun; Liu, Xing; Zheng, Jing; Xu, Bin; Zhou, Hu

2017-06-06

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

Effects of Three Commonly-used Diuretics on the Urinary Proteome

PubMed Central

Li, Xundou; Zhao, Mindi; Li, Menglin; Jia, Lulu; Gao, Youhe

2014-01-01

Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography–tandem mass spectrometry (LC–MS/MS). Based on the criteria of P ⩽ 0.05, a fold change ⩾2, a spectral count ⩾5, and false positive rate (FDR) ⩽1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC–MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. PMID:24508280

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer

DOE PAGES

Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...

2017-07-19

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

[Progress in the spectral library based protein identification strategy].

PubMed

Yu, Derui; Ma, Jie; Xie, Zengyan; Bai, Mingze; Zhu, Yunping; Shu, Kunxian

2018-04-25

Exponential growth of the mass spectrometry (MS) data is exhibited when the mass spectrometry-based proteomics has been developing rapidly. It is a great challenge to develop some quick, accurate and repeatable methods to identify peptides and proteins. Nowadays, the spectral library searching has become a mature strategy for tandem mass spectra based proteins identification in proteomics, which searches the experiment spectra against a collection of confidently identified MS/MS spectra that have been observed previously, and fully utilizes the abundance in the spectrum, peaks from non-canonical fragment ions, and other features. This review provides an overview of the implement of spectral library search strategy, and two key steps, spectral library construction and spectral library searching comprehensively, and discusses the progress and challenge of the library search strategy.

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

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

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

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

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

PubMed

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

2016-01-01

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

GeLC-MS-based proteomics of Chromobacterium violaceum: comparison of proteome changes elicited by hydrogen peroxide

PubMed Central

Lima, D. C.; Duarte, F. T.; Medeiros, V. K. S.; Carvalho, P. C.; Nogueira, F. C. S.; Araujo, G. D. T.; Domont, G. B.; Batistuzzo de Medeiros, S. R.

2016-01-01

Chromobacterium violaceum is a free-living bacillus with several genes that enables it survival under different harsh environments such as oxidative and temperature stresses. Here we performed a label-free quantitative proteomic study to unravel the molecular mechanisms that enable C. violaceum to survive oxidative stress. To achieve this, total proteins extracted from control and C. violaceum cultures exposed during two hours with 8 mM hydrogen peroxide were analyzed using GeLC-MS proteomics. Analysis revealed that under the stress condition, the bacterium expressed proteins that protected it from the damage caused by reactive oxygen condition and decreasing the abundance of proteins responsible for bacterial growth and catabolism. GeLC-MS proteomics analysis provided an overview of the metabolic pathways involved in the response of C. violaceum to oxidative stress ultimately aggregating knowledge of the response of this organism to environmental stress. This study identified approximately 1500 proteins, generating the largest proteomic coverage of C. violaceum so far. We also detected proteins with unknown function that we hypothesize to be part of new mechanisms related to oxidative stress defense. Finally, we identified the mechanism of clustered regularly interspaced short palindromic repeats (CRISPR), which has not yet been reported for this organism. PMID:27321545

GeLC-MS-based proteomics of Chromobacterium violaceum: comparison of proteome changes elicited by hydrogen peroxide.

PubMed

Lima, D C; Duarte, F T; Medeiros, V K S; Carvalho, P C; Nogueira, F C S; Araujo, G D T; Domont, G B; Batistuzzo de Medeiros, S R

2016-06-20

Chromobacterium violaceum is a free-living bacillus with several genes that enables it survival under different harsh environments such as oxidative and temperature stresses. Here we performed a label-free quantitative proteomic study to unravel the molecular mechanisms that enable C. violaceum to survive oxidative stress. To achieve this, total proteins extracted from control and C. violaceum cultures exposed during two hours with 8 mM hydrogen peroxide were analyzed using GeLC-MS proteomics. Analysis revealed that under the stress condition, the bacterium expressed proteins that protected it from the damage caused by reactive oxygen condition and decreasing the abundance of proteins responsible for bacterial growth and catabolism. GeLC-MS proteomics analysis provided an overview of the metabolic pathways involved in the response of C. violaceum to oxidative stress ultimately aggregating knowledge of the response of this organism to environmental stress. This study identified approximately 1500 proteins, generating the largest proteomic coverage of C. violaceum so far. We also detected proteins with unknown function that we hypothesize to be part of new mechanisms related to oxidative stress defense. Finally, we identified the mechanism of clustered regularly interspaced short palindromic repeats (CRISPR), which has not yet been reported for this organism.

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

PubMed

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

2016-07-01

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

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

PubMed Central

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

2015-01-01

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

Proteome-Wide Profiling of Targets of Cysteine reactive Small Molecules by Using Ethynyl Benziodoxolone Reagents.

PubMed

Abegg, Daniel; Frei, Reto; Cerato, Luca; Prasad Hari, Durga; Wang, Chao; Waser, Jerome; Adibekian, Alexander

2015-09-07

In this study, we present a highly efficient method for proteomic profiling of cysteine residues in complex proteomes and in living cells. Our method is based on alkynylation of cysteines in complex proteomes using a "clickable" alkynyl benziodoxolone bearing an azide group. This reaction proceeds fast, under mild physiological conditions, and with a very high degree of chemoselectivity. The formed azide-capped alkynyl-cysteine adducts are readily detectable by LC-MS/MS, and can be further functionalized with TAMRA or biotin alkyne via CuAAC. We demonstrate the utility of alkynyl benziodoxolones for chemical proteomics applications by identifying the proteomic targets of curcumin, a diarylheptanoid natural product that was and still is part of multiple human clinical trials as anticancer agent. Our results demonstrate that curcumin covalently modifies several key players of cellular signaling and metabolism, most notably the enzyme casein kinase I gamma. We anticipate that this new method for cysteine profiling will find broad application in chemical proteomics and drug discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultraviolet photodissociation enhances top-down mass spectrometry as demonstrated on green fluorescent protein variants.

PubMed

Dang, Xibei; Young, Nicolas L

2014-05-01

Ultraviolet photodissociation (UVPD) is a compelling fragmentation technique with great potential to enhance proteomics generally and top-down MS specifically. In this issue, Cannon et al. (Proteomics 2014, 14, XXXX-XXXX) use UVPD to perform top-down MS on several sequence variants of green fluorescent protein and compare the results to CID, higher energy collision induced dissociation, and electron transfer dissociation. As compared to the other techniques UVPD produces a wider variety of fragment ion types that are relatively evenly distributed across the protein sequences. Overall, their results demonstrate enhanced sequence coverage and higher confidence in sequence assignment via UVPD MS. Based on these and other recent results UVPD is certain to become an increasingly widespread and valuable tool for top-down proteomics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system

PubMed Central

Droit, Arnaud; Hunter, Joanna M; Rouleau, Michèle; Ethier, Chantal; Picard-Cloutier, Aude; Bourgais, David; Poirier, Guy G

2007-01-01

Background In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools. Description We herein describe "PARPs database," a data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics. PARPs database is a web-based tool whose features include experiment annotation, protein database searching, protein sequence management, as well as data-mining of the peptides and proteins identified. Conclusion Using this pipeline, we have successfully identified several interactions of biological significance between PARP-1 and other proteins, namely RFC-1, 2, 3, 4 and 5. PMID:18093328

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

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome

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

Wang, Hong; Yang, Yanling; Li, Yuxin

2015-02-06

Development of high resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse phase column (100 μm x 150 cm) coupled with Q Exactive MS. The column was capable of achieving a peak capacity of approximately 700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was about 6 micrograms of peptides, although the column allowed loading as many as 20 micrograms. Gas phasemore » fractionation of peptide ions further increased the number of peptide identification by ~10%. Moreover, the combination of basic pH LC pre-fractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a postmortem brain sample of Alzheimer’s disease. As deep RNA sequencing of the same specimen suggested that ~16,000 genes were expressed, current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.« less

Making proteomics data accessible and reusable: current state of proteomics databases and repositories.

PubMed

Perez-Riverol, Yasset; Alpi, Emanuele; Wang, Rui; Hermjakob, Henning; Vizcaíno, Juan Antonio

2015-03-01

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data. © 2014 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2011-06-01

spectroscopy-based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and...will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr. Michael Kennedy, Miami University. Changes in proteomic profiles will be...based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and

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.

Low-Molecular-Weight Plasma Proteome Analysis Using Top-Down Mass Spectrometry.

PubMed

Cheon, Dong Huey; Yang, Eun Gyeong; Lee, Cheolju; Lee, Ji Eun

2017-01-01

While human plasma has a wealth of diagnostic information regarding the state of the human body in heath and disease, low molecular weight (LMW) proteome (<30 kDa) has been shown to contain a rich source of diagnostic biomarkers. Here we describe a protocol for top-down proteomic analysis to identify and characterize the LMW proteoforms present in four types of human plasma samples without immunoaffinity depletion and with depletion of the top two, six, and seven high-abundance proteins. Each type of plasma sample was first fractionated based on molecular weight using gel-eluted liquid fraction entrapment electrophoresis (GELFrEE). Then, the GELFrEE fractions containing up to 30 kDa were subjected to nanocapillary-LC-MS/MS, and the high-resolution MS and MS/MS data were processed using ProSightPC software. As a result, a total of 442 LMW proteins and cleaved products, including those with posttranslational modifications (PTMs) and single amino acid variations (SAAVs), were identified with a threshold E-value of 1 × 10 -4 from the four types of plasma samples.

Deep coverage of the beer proteome.

PubMed

Grochalová, Martina; Konečná, Hana; Stejskal, Karel; Potěšil, David; Fridrichová, Danuše; Srbová, Eva; Ornerová, Kateřina; Zdráhal, Zbyněk

2017-06-06

We adopted an approach based on peptide immobilized pH gradient-isoelectric focusing (IPG-IEF) separation, coupled with LC-MS/MS, in order to maximize coverage of the beer proteome. A lager beer brewed using traditional Czech technology was degassed, desalted and digested. Tryptic peptides were separated by isoelectric focusing on an immobilized pH gradient strip and, after separation, the gel strip was divided into seven equally sized parts. Peptides extracted from gel fractions were analyzed by LC-MS/MS. This approach resulted in a three-fold increase in the number of proteins identified (over 1700) when compared to analysis of unfractionated beer processed by a filter-aided sample preparation (FASP). Over 1900 protein groups (PGs) in total were identified by both approaches. The study significantly extends knowledge about the beer proteome and demonstrates its complexity. Detailed knowledge of the protein content, especially gluten proteins, will enhance the evaluation of potential health risks related to beer consumption (coeliac disease) and will contribute to improving beer quality. Copyright © 2017 Elsevier B.V. All rights reserved.

Combination of Bottom-up 2D-LC-MS and Semi-top-down GelFree-LC-MS Enhances Coverage of Proteome and Low Molecular Weight Short Open Reading Frame Encoded Peptides of the Archaeon Methanosarcina mazei.

PubMed

Cassidy, Liam; Prasse, Daniela; Linke, Dennis; Schmitz, Ruth A; Tholey, Andreas

2016-10-07

The recent discovery of an increasing number of small open reading frames (sORF) creates the need for suitable analytical technologies for the comprehensive identification of the corresponding gene products. For biological and functional studies the knowledge of the entire set of proteins and sORF gene products is essential. Consequently in the present study we evaluated analytical approaches that will allow for simultaneous analysis of widest parts of the proteome together with the predicted sORF. We performed a full proteome analysis of the methane producing archaeon Methanosarcina mazei strain Gö1 cytosolic proteome using a high/low pH reversed phase LC-MS bottom-up approach. The second analytical approach was based on semi-top-down strategy, encompassing a separation at intact protein level using a GelFree system, followed by digestion and LC-MS analysis. A high overlap in identified proteins was found for both approaches yielding the most comprehensive coverage of the cytosolic proteome of this organism achieved so far. The application of the second approach in combination with an adjustment of the search criteria for database searches further led to a significant increase of sORF peptide identifications, finally allowing to detect and identify 28 sORF gene products.

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.

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.

Transcriptome and proteomic analysis of mango (Mangifera indica Linn) fruits.

PubMed

Wu, Hong-xia; Jia, Hui-min; Ma, Xiao-wei; Wang, Song-biao; Yao, Quan-sheng; Xu, Wen-tian; Zhou, Yi-gang; Gao, Zhong-shan; Zhan, Ru-lin

2014-06-13

Here we used Illumina RNA-seq technology for transcriptome sequencing of a mixed fruit sample from 'Zill' mango (Mangifera indica Linn) fruit pericarp and pulp during the development and ripening stages. RNA-seq generated 68,419,722 sequence reads that were assembled into 54,207 transcripts with a mean length of 858bp, including 26,413 clusters and 27,794 singletons. A total of 42,515(78.43%) transcripts were annotated using public protein databases, with a cut-off E-value above 10(-5), of which 35,198 and 14,619 transcripts were assigned to gene ontology terms and clusters of orthologous groups respectively. Functional annotation against the Kyoto Encyclopedia of Genes and Genomes database identified 23,741(43.79%) transcripts which were mapped to 128 pathways. These pathways revealed many previously unknown transcripts. We also applied mass spectrometry-based transcriptome data to characterize the proteome of ripe fruit. LC-MS/MS analysis of the mango fruit proteome was using tandem mass spectrometry (MS/MS) in an LTQ Orbitrap Velos (Thermo) coupled online to the HPLC. This approach enabled the identification of 7536 peptides that matched 2754 proteins. Our study provides a comprehensive sequence for a systemic view of transcriptome during mango fruit development and the most comprehensive fruit proteome to date, which are useful for further genomics research and proteomic studies. Our study provides a comprehensive sequence for a systemic view of both the transcriptome and proteome of mango fruit, and a valuable reference for further research on gene expression and protein identification. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

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

CAPER 3.0: A Scalable Cloud-Based System for Data-Intensive Analysis of Chromosome-Centric Human Proteome Project Data Sets.

PubMed

Yang, Shuai; Zhang, Xinlei; Diao, Lihong; Guo, Feifei; Wang, Dan; Liu, Zhongyang; Li, Honglei; Zheng, Junjie; Pan, Jingshan; Nice, Edouard C; Li, Dong; He, Fuchu

2015-09-04

The Chromosome-centric Human Proteome Project (C-HPP) aims to catalog genome-encoded proteins using a chromosome-by-chromosome strategy. As the C-HPP proceeds, the increasing requirement for data-intensive analysis of the MS/MS data poses a challenge to the proteomic community, especially small laboratories lacking computational infrastructure. To address this challenge, we have updated the previous CAPER browser into a higher version, CAPER 3.0, which is a scalable cloud-based system for data-intensive analysis of C-HPP data sets. CAPER 3.0 uses cloud computing technology to facilitate MS/MS-based peptide identification. In particular, it can use both public and private cloud, facilitating the analysis of C-HPP data sets. CAPER 3.0 provides a graphical user interface (GUI) to help users transfer data, configure jobs, track progress, and visualize the results comprehensively. These features enable users without programming expertise to easily conduct data-intensive analysis using CAPER 3.0. Here, we illustrate the usage of CAPER 3.0 with four specific mass spectral data-intensive problems: detecting novel peptides, identifying single amino acid variants (SAVs) derived from known missense mutations, identifying sample-specific SAVs, and identifying exon-skipping events. CAPER 3.0 is available at http://prodigy.bprc.ac.cn/caper3.

P-MartCancer: A New Online Platform to Access CPTAC Datasets and Enable New Analyses | Office of Cancer Clinical Proteomics Research

Cancer.gov

The November 1, 2017 issue of Cancer Research is dedicated to a collection of computational resource papers in genomics, proteomics, animal models, imaging, and clinical subjects for non-bioinformaticists looking to incorporate computing tools into their work. Scientists at Pacific Northwest National Laboratory have developed P-MartCancer, an open, web-based interactive software tool that enables statistical analyses of peptide or protein data generated from mass-spectrometry (MS)-based global proteomics experiments.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

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.

A new calibrant for MALDI-TOF-TOF-PSD-MS/MS of non-digested proteins for top-down proteomic analysis

USDA-ARS?s Scientific Manuscript database

RATIONALE: Matrix-assisted laser desorption/ionization (MALDI) time-of-flight-time-of-flight (TOF-TOF) tandem mass spectrometry (MS/MS) has seen increasing use for post-source decay (PSD)-MS/MS analysis of non-digested protein ions for top-down proteomic identification. However, there is no commonl...

SILAC-Based Comparative Proteomic Analysis of Lysosomes from Mammalian Cells Using LC-MS/MS.

PubMed

Thelen, Melanie; Winter, Dominic; Braulke, Thomas; Gieselmann, Volkmar

2017-01-01

Mass spectrometry-based proteomics of lysosomal proteins has led to significant advances in understanding lysosomal function and pathology. The ever-increasing sensitivity and resolution of mass spectrometry in combination with labeling procedures which allow comparative quantitative proteomics can be applied to shed more light on the steadily increasing range of lysosomal functions. In addition, investigation of alterations in lysosomal protein composition in the many lysosomal storage diseases may yield further insights into the molecular pathology of these disorders. Here, we describe a protocol which allows to determine quantitative differences in the lysosomal proteome of cells which are genetically and/or biochemically different or have been exposed to certain stimuli. The method is based on stable isotope labeling of amino acids in cell culture (SILAC). Cells are exposed to superparamagnetic iron oxide particles which are endocytosed and delivered to lysosomes. After homogenization of cells, intact lysosomes are rapidly enriched by passing the cell homogenates over a magnetic column. Lysosomes are eluted after withdrawal of the magnetic field and subjected to mass spectrometry.

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

Non-gel Based Proteomics to Study Steroid Receptor Agonists in the Fathead Minnow

EPA Science Inventory

Toxicoproteomics is an emerging field that is greatly enabled by non-gel based methods using LC MS/MS for biomarker discovery and characterization for endocrine disrupting chemicals. Using iTRAQ (isobaric tagging for relative and absolute quantitation), we quantified a diverse r...

Simultaneous quantification of protein phosphorylation sites using liquid chromatography-tandem mass spectrometry-based targeted proteomics: a linear algebra approach for isobaric phosphopeptides.

PubMed

Xu, Feifei; Yang, Ting; Sheng, Yuan; Zhong, Ting; Yang, Mi; Chen, Yun

2014-12-05

As one of the most studied post-translational modifications (PTM), protein phosphorylation plays an essential role in almost all cellular processes. Current methods are able to predict and determine thousands of phosphorylation sites, whereas stoichiometric quantification of these sites is still challenging. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted proteomics is emerging as a promising technique for site-specific quantification of protein phosphorylation using proteolytic peptides as surrogates of proteins. However, several issues may limit its application, one of which relates to the phosphopeptides with different phosphorylation sites and the same mass (i.e., isobaric phosphopeptides). While employment of site-specific product ions allows for these isobaric phosphopeptides to be distinguished and quantified, site-specific product ions are often absent or weak in tandem mass spectra. In this study, linear algebra algorithms were employed as an add-on to targeted proteomics to retrieve information on individual phosphopeptides from their common spectra. To achieve this simultaneous quantification, a LC-MS/MS-based targeted proteomics assay was first developed and validated for each phosphopeptide. Given the slope and intercept of calibration curves of phosphopeptides in each transition, linear algebraic equations were developed. Using a series of mock mixtures prepared with varying concentrations of each phosphopeptide, the reliability of the approach to quantify isobaric phosphopeptides containing multiple phosphorylation sites (≥ 2) was discussed. Finally, we applied this approach to determine the phosphorylation stoichiometry of heat shock protein 27 (HSP27) at Ser78 and Ser82 in breast cancer cells and tissue samples.

Toward the Standardization of Mitochondrial Proteomics: The Italian Mitochondrial Human Proteome Project Initiative.

PubMed

Alberio, Tiziana; Pieroni, Luisa; Ronci, Maurizio; Banfi, Cristina; Bongarzone, Italia; Bottoni, Patrizia; Brioschi, Maura; Caterino, Marianna; Chinello, Clizia; Cormio, Antonella; Cozzolino, Flora; Cunsolo, Vincenzo; Fontana, Simona; Garavaglia, Barbara; Giusti, Laura; Greco, Viviana; Lucacchini, Antonio; Maffioli, Elisa; Magni, Fulvio; Monteleone, Francesca; Monti, Maria; Monti, Valentina; Musicco, Clara; Petrosillo, Giuseppe; Porcelli, Vito; Saletti, Rosaria; Scatena, Roberto; Soggiu, Alessio; Tedeschi, Gabriella; Zilocchi, Mara; Roncada, Paola; Urbani, Andrea; Fasano, Mauro

2017-12-01

The Mitochondrial Human Proteome Project aims at understanding the function of the mitochondrial proteome and its crosstalk with the proteome of other organelles. Being able to choose a suitable and validated enrichment protocol of functional mitochondria, based on the specific needs of the downstream proteomics analysis, would greatly help the researchers in the field. Mitochondrial fractions from ten model cell lines were prepared using three enrichment protocols and analyzed on seven different LC-MS/MS platforms. All data were processed using neXtProt as reference database. The data are available for the Human Proteome Project purposes through the ProteomeXchange Consortium with the identifier PXD007053. The processed data sets were analyzed using a suite of R routines to perform a statistical analysis and to retrieve subcellular and submitochondrial localizations. Although the overall number of identified total and mitochondrial proteins was not significantly dependent on the enrichment protocol, specific line to line differences were observed. Moreover, the protein lists were mapped to a network representing the functional mitochondrial proteome, encompassing mitochondrial proteins and their first interactors. More than 80% of the identified proteins resulted in nodes of this network but with a different ability in coisolating mitochondria-associated structures for each enrichment protocol/cell line pair.

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

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

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

2011-02-01

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

Comparison of Grain Proteome Profiles of Four Brazilian Common Bean (Phaseolus vulgaris L.) Cultivars.

PubMed

Rossi, Gabriela Barbosa; Valentim-Neto, Pedro Alexandre; Blank, Martina; Faria, Josias Correa de; Arisi, Ana Carolina Maisonnave

2017-08-30

Common bean (Phaseolus vulgaris L.) is a source of proteins for about one billion people worldwide. In Brazil, 'BRS Sublime', 'BRS Vereda', 'BRS Esteio', and 'BRS Estilo' cultivars were developed by Embrapa to offer high yield to farmers and excellent quality to final consumers. In this work, grain proteomes of these common bean cultivars were compared based on two-dimensional gel electrophoresis (2-DE) and tandem mass spectrometry (MS/MS). Principal component analysis (PCA) was applied to compare 349 matched spots in these cultivars proteomes, and all cultivars were clearly separated in PCA plot. Thirty-two differentially accumulated proteins were identified by MS. Storage proteins such as phaseolins, legumins, and lectins were the most abundant, and novel proteins were also identified. We have built a useful platform that could be used to analyze other Brazilian cultivars and genotypes of common beans.

MALDI versus ESI: The Impact of the Ion Source on Peptide Identification.

PubMed

Nadler, Wiebke Maria; Waidelich, Dietmar; Kerner, Alexander; Hanke, Sabrina; Berg, Regina; Trumpp, Andreas; Rösli, Christoph

2017-03-03

For mass spectrometry-based proteomic analyses, electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) are the commonly used ionization techniques. To investigate the influence of the ion source on peptide detection in large-scale proteomics, an optimized GeLC/MS workflow was developed and applied either with ESI/MS or with MALDI/MS for the proteomic analysis of different human cell lines of pancreatic origin. Statistical analysis of the resulting data set with more than 72 000 peptides emphasized the complementary character of the two methods, as the percentage of peptides identified with both approaches was as low as 39%. Significant differences between the resulting peptide sets were observed with respect to amino acid composition, charge-related parameters, hydrophobicity, and modifications of the detected peptides and could be linked to factors governing the respective ion yields in ESI and MALDI.

Advanced Mass Spectrometric Methods for the Rapid and Quantitative Characterization of Proteomes

DOE PAGES

Smith, Richard D.

2002-01-01

Progress is reviewedmore » towards the development of a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness and throughput of proteomic measurements based upon the use of high performance separations and mass spectrometry. The approach uses high accuracy mass measurements from Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate peptide ‘accurate mass tags’ (AMTs) produced by global protein enzymatic digestions for a specific organism, tissue or cell type from ‘potential mass tags’ tentatively identified using conventional tandem mass spectrometry (MS/MS). This provides the basis for subsequent measurements without the need for MS/ MS. High resolution capillary liquid chromatography separations combined with high sensitivity, and high resolution accurate FTICR measurements are shown to be capable of characterizing peptide mixtures of more than 10 5 components. The strategy has been initially demonstrated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, high sensitivity, and the capability for stableisotope labeling methods for precise relative protein abundance measurements. Abbreviations : LC, liquid chromatography; FTICR, Fourier transform ion cyclotron resonance; AMT, accurate mass tag; PMT, potential mass tag; MMA, mass measurement accuracy; MS, mass spectrometry; MS/MS, tandem mass spectrometry; ppm, parts per million.« less

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

PubMed

Wiśniewski, Jacek R; Mann, Matthias

2016-07-01

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

Effects of three commonly-used diuretics on the urinary proteome.

PubMed

Li, Xundou; Zhao, Mindi; Li, Menglin; Jia, Lulu; Gao, Youhe

2014-06-01

Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the criteria of P≤0.05, a fold change ≥2, a spectral count ≥5, and false positive rate (FDR) ≤1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC-MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. Copyright © 2014. Production and hosting by Elsevier Ltd.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

PubMed

Cho, Jin-Young; Lee, Hyoung-Joo; Jeong, Seul-Ki; Paik, Young-Ki

2017-12-01

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

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

PubMed

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

2012-03-06

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

Achievements and perspectives of top-down proteomics.

PubMed

Armirotti, Andrea; Damonte, Gianluca

2010-10-01

Over the last years, top-down (TD) MS has gained a remarkable space in proteomics, rapidly trespassing the limit between a promising approach and a solid, established technique. Several research groups worldwide have implemented TD analysis in their routine work on proteomics, deriving structural information on proteins with the level of accuracy that is impossible to achieve with classical bottom-up approaches. Complete maps of PTMs and assessment of single aminoacid polymorphisms are only a few of the results that can be obtained with this technique. Despite some existing technical and economical limitations, TD analysis is at present the most powerful instrument for MS-based proteomics and its implementation in routine workflow is a rapidly approaching turning point in proteomics. In this review article, the state-of-the-art of TD approach is described along with its major advantages and drawbacks and the most recent trends in TD analysis are discussed. References for all the covered topics are reported in the text, with the aim to support both newcomers and mass spectrometrists already introduced to TD proteomics.

Sample handling for mass spectrometric proteomic investigations of human sera.

PubMed

West-Nielsen, Mikkel; Høgdall, Estrid V; Marchiori, Elena; Høgdall, Claus K; Schou, Christian; Heegaard, Niels H H

2005-08-15

Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers while less effort has been invested in devising standard procedures for sample preparation and storage in relation to model building based on complex sets of mass spectrometric (MS) data. Thus, development of standardized methods for collection and storage of patient samples together with standards for transportation and handling of samples are needed. This requires knowledge about how sample processing affects MS-based proteome analyses and thereby how nonbiological biased classification errors are avoided. In this study, we characterize the effects of sample handling, including clotting conditions, storage temperature, storage time, and freeze/thaw cycles, on MS-based proteomics of human serum by using principal components analysis, support vector machine learning, and clustering methods based on genetic algorithms as class modeling and prediction methods. Using spiking to artificially create differentiable sample groups, this integrated approach yields data that--even when working with sample groups that differ more than may be expected in biological studies--clearly demonstrate the need for comparable sampling conditions for samples used for modeling and for the samples that are going into the test set group. Also, the study emphasizes the difference between class prediction and class comparison studies as well as the advantages and disadvantages of different modeling methods.

Molecular Simulation-Based Structural Prediction of Protein Complexes in Mass Spectrometry: The Human Insulin Dimer

PubMed Central

Li, Jinyu; Rossetti, Giulia; Dreyer, Jens; Raugei, Simone; Ippoliti, Emiliano; Lüscher, Bernhard; Carloni, Paolo

2014-01-01

Protein electrospray ionization (ESI) mass spectrometry (MS)-based techniques are widely used to provide insight into structural proteomics under the assumption that non-covalent protein complexes being transferred into the gas phase preserve basically the same intermolecular interactions as in solution. Here we investigate the applicability of this assumption by extending our previous structural prediction protocol for single proteins in ESI-MS to protein complexes. We apply our protocol to the human insulin dimer (hIns2) as a test case. Our calculations reproduce the main charge and the collision cross section (CCS) measured in ESI-MS experiments. Molecular dynamics simulations for 0.075 ms show that the complex maximizes intermolecular non-bonded interactions relative to the structure in water, without affecting the cross section. The overall gas-phase structure of hIns2 does exhibit differences with the one in aqueous solution, not inferable from a comparison with calculated CCS. Hence, care should be exerted when interpreting ESI-MS proteomics data based solely on NMR and/or X-ray structural information. PMID:25210764

Trimethylation enhancement using diazomethane (TrEnDi): rapid on-column quaternization of peptide amino groups via reaction with diazomethane significantly enhances sensitivity in mass spectrometry analyses via a fixed, permanent positive charge.

PubMed

Wasslen, Karl V; Tan, Le Hoa; Manthorpe, Jeffrey M; Smith, Jeffrey C

2014-04-01

Defining cellular processes relies heavily on elucidating the temporal dynamics of proteins. To this end, mass spectrometry (MS) is an extremely valuable tool; different MS-based quantitative proteomics strategies have emerged to map protein dynamics over the course of stimuli. Herein, we disclose our novel MS-based quantitative proteomics strategy with unique analytical characteristics. By passing ethereal diazomethane over peptides on strong cation exchange resin within a microfluidic device, peptides react to contain fixed, permanent positive charges. Modified peptides display improved ionization characteristics and dissociate via tandem mass spectrometry (MS(2)) to form strong a2 fragment ion peaks. Process optimization and determination of reactive functional groups enabled a priori prediction of MS(2) fragmentation patterns for modified peptides. The strategy was tested on digested bovine serum albumin (BSA) and successfully quantified a peptide that was not observable prior to modification. Our method ionizes peptides regardless of proton affinity, thus decreasing ion suppression and permitting predictable multiple reaction monitoring (MRM)-based quantitation with improved sensitivity.

Glycoproteins Enrichment and LC-MS/MS Glycoproteomics in Central Nervous System Applications.

PubMed

Zhu, Rui; Song, Ehwang; Hussein, Ahmed; Kobeissy, Firas H; Mechref, Yehia

2017-01-01

Proteins and glycoproteins play important biological roles in central nervous systems (CNS). Qualitative and quantitative evaluation of proteins and glycoproteins expression in CNS is critical to reveal the inherent biomolecular mechanism of CNS diseases. This chapter describes proteomic and glycoproteomic approaches based on liquid chromatography/tandem mass spectrometry (LC-MS or LC-MS/MS) for the qualitative and quantitative assessment of proteins and glycoproteins expressed in CNS. Proteins and glycoproteins, extracted by a mass spectrometry friendly surfactant from CNS samples, were subjected to enzymatic (tryptic) digestion and three down-stream analyses: (1) a nano LC system coupled with a high-resolution MS instrument to achieve qualitative proteomic profile, (2) a nano LC system combined with a triple quadrupole MS to quantify identified proteins, and (3) glycoprotein enrichment prior to LC-MS/MS analysis. Enrichment techniques can be applied to improve coverage of low abundant glycopeptides/glycoproteins. An example described in this chapter is hydrophilic interaction liquid chromatographic (HILIC) enrichment to capture glycopeptides, allowing efficient removal of peptides. The combination of three LC-MS/MS-based approaches is capable of the investigation of large-scale proteins and glycoproteins from CNS with an in-depth coverage, thus offering a full view of proteins and glycoproteins changes in CNS.

The quest of the human proteome and the missing proteins: digging deeper.

PubMed

Reddy, Panga Jaipal; Ray, Sandipan; Srivastava, Sanjeeva

2015-05-01

Given the diverse range of transcriptional and post-transcriptional mechanisms of gene regulation, the estimates of the human proteome is likely subject to scientific surprises as the field of proteomics has gained momentum worldwide. In this regard, the establishment of the "Human Proteome Draft" using high-resolution mass spectrometry (MS), tissue microarrays, and immunohistochemistry by three independent research groups (laboratories of Pandey, Kuster, and Uhlen) accelerated the pace of proteomics research. The Chromosome Centric Human Proteome Project (C-HPP) has taken initiative towards the completion of the Human Proteome Project (HPP) so as to understand the proteomics correlates of common complex human diseases and biological diversity, not to mention person-to-person and population differences in response to drugs, nutrition, vaccines, and other health interventions and host-environment interactions. Although high-resolution MS-based and antibody microarray approaches have shown enormous promises, we are still unable to map the whole human proteome due to the presence of numerous "missing proteins." In December 2014, at the Indian Institute of Technology Bombay, Mumbai the 6(th) Annual Meeting of the Proteomics Society, India (PSI) and the International Proteomics Conference was held. As part of this interdisciplinary summit, a panel discussion session on "The Quest of the Human Proteome and Missing Proteins" was organized. Eminent scientists in the field of proteomics and systems biology, including Akhilesh Pandey, Gilbert S. Omenn, Mark S. Baker, and Robert L. Mortiz, shed light on different aspects of the human proteome drafts and missing proteins. Importantly, the possible reasons for the "missing proteins" in shotgun MS workflow were identified and debated by experts as low tissue expression, lack of enzymatic digestion site, or protein lost during extraction, among other contributing factors. To capture the missing proteins, the experts' collective view was to study the wider tissue range with multiple digesting enzymes and follow targeted proteomics workflow in particular. On the innovation trajectory from the proteomics laboratory to novel proteomics diagnostics and therapeutics in society, we will also need new conceptual frames for translation science and innovation strategy in proteomics. These will embody both technical as well as rigorous social science and humanities considerations to understand the correlates of the proteome from cell to society.

jPOSTrepo: an international standard data repository for proteomes

PubMed Central

Okuda, Shujiro; Watanabe, Yu; Moriya, Yuki; Kawano, Shin; Yamamoto, Tadashi; Matsumoto, Masaki; Takami, Tomoyo; Kobayashi, Daiki; Araki, Norie; Yoshizawa, Akiyasu C.; Tabata, Tsuyoshi; Sugiyama, Naoyuki; Goto, Susumu; Ishihama, Yasushi

2017-01-01

Major advancements have recently been made in mass spectrometry-based proteomics, yielding an increasing number of datasets from various proteomics projects worldwide. In order to facilitate the sharing and reuse of promising datasets, it is important to construct appropriate, high-quality public data repositories. jPOSTrepo (https://repository.jpostdb.org/) has successfully implemented several unique features, including high-speed file uploading, flexible file management and easy-to-use interfaces. This repository has been launched as a public repository containing various proteomic datasets and is available for researchers worldwide. In addition, our repository has joined the ProteomeXchange consortium, which includes the most popular public repositories such as PRIDE in Europe for MS/MS datasets and PASSEL for SRM datasets in the USA. Later MassIVE was introduced in the USA and accepted into the ProteomeXchange, as was our repository in July 2016, providing important datasets from Asia/Oceania. Accordingly, this repository thus contributes to a global alliance to share and store all datasets from a wide variety of proteomics experiments. Thus, the repository is expected to become a major repository, particularly for data collected in the Asia/Oceania region. PMID:27899654

Protein expression profiles of human lymph and plasma mapped by 2D-DIGE and 1D SDS–PAGE coupled with nanoLC–ESI–MS/MS bottom-up proteomics

PubMed Central

Clement, Cristina C.; Aphkhazava, David; Nieves, Edward; Callaway, Myrasol; Olszewski, Waldemar; Rotzschke, Olaf; Santambrogio, Laura

2013-01-01

In this study a proteomic approach was used to define the protein content of matched samples of afferent prenodal lymph and plasma derived from healthy volunteers. The analysis was performed using two analytical methodologies coupled with nanoliquid chromatography-tandem mass spectrometry: one-dimensional gel electrophoresis (1DEF nanoLC Orbitrap–ESI–MS/MS), and two-dimensional fluorescence difference-in-gel electrophoresis (2D-DIGE nanoLC–ESI–MS/MS). The 253 significantly identified proteins (p<0.05), obtained from the tandem mass spectrometry data, were further analyzed with pathway analysis (IPA) to define the functional signature of prenodal lymph and matched plasma. The 1DEF coupled with nanoLC–MS–MS revealed that the common proteome between the two biological fluids (144 out of 253 proteins) was dominated by complement activation and blood coagulation components, transporters and protease inhibitors. The enriched proteome of human lymph (72 proteins) consisted of products derived from the extracellular matrix, apoptosis and cellular catabolism. In contrast, the enriched proteome of human plasma (37 proteins) consisted of soluble molecules of the coagulation system and cell–cell signaling factors. The functional networks associated with both common and source-distinctive proteomes highlight the principal biological activity of these immunologically relevant body fluids. PMID:23202415

MassSieve: Panning MS/MS peptide data for proteins

PubMed Central

Slotta, Douglas J.; McFarland, Melinda A.; Markey, Sanford P.

2010-01-01

We present MassSieve, a Java-based platform for visualization and parsimony analysis of single and comparative LC-MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC-MS/MS-based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments. PMID:20564260

Systematic Characterization of the Murine Mitochondrial Proteome Using Functionally Validated Cardiac Mitochondria

PubMed Central

Zhang, Jun; Li, Xiaohai; Mueller, Michael; Wang, Yueju; Zong, Chenggong; Deng, Ning; Vondriska, Thomas M.; Liem, David A.; Yang, Jeong-In; Korge, Paavo; Honda, Henry; Weiss, James N.; Apweiler, Rolf; Ping, Peipei

2009-01-01

Mitochondria play essential roles in cardiac pathophysiology and the murine model has been extensively used to investigate cardiovascular diseases. In the present study, we characterized murine cardiac mitochondria using an LC/MS/MS approach. We extracted and purified cardiac mitochondria; validated their functionality to ensure the final preparation contains necessary components to sustain their normal function; and subjected these validated organelles to LC/MS/MS-based protein identification. A total of 940 distinct proteins were identified from murine cardiac mitochondria, among which, 480 proteins were not previously identified by major proteomic profiling studies. The 940 proteins consist of functional clusters known to support oxidative phosphorylation, metabolism and biogenesis. In addition, there are several other clusters--including proteolysis, protein folding, and reduction/oxidation signaling-which ostensibly represent previously under-appreciated tasks of cardiac mitochondria. Moreover, many identified proteins were found to occupy other subcellular locations, including cytoplasm, ER, and golgi, in addition to their presence in the mitochondria. These results provide a comprehensive picture of the murine cardiac mitochondrial proteome and underscore tissue- and species-specification. Moreover, the use of functionally intact mitochondria insures that the proteomic observations in this organelle are relevant to its normal biology and facilitates decoding the interplay between mitochondria and other organelles. PMID:18348319

Open source libraries and frameworks for mass spectrometry based proteomics: A developer's perspective☆

PubMed Central

Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

2014-01-01

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. PMID:23467006

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective.

PubMed

Perez-Riverol, Yasset; Wang, Rui; Hermjakob, Henning; Müller, Markus; Vesada, Vladimir; Vizcaíno, Juan Antonio

2014-01-01

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. Copyright © 2013 Elsevier B.V. All rights reserved.

Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics

DOE PAGES

Webb-Robertson, Bobbie-Jo M.; Wiberg, Holli K.; Matzke, Melissa M.; ...

2015-04-09

In this review, we apply selected imputation strategies to label-free liquid chromatography–mass spectrometry (LC–MS) proteomics datasets to evaluate the accuracy with respect to metrics of variance and classification. We evaluate several commonly used imputation approaches for individual merits and discuss the caveats of each approach with respect to the example LC–MS proteomics data. In general, local similarity-based approaches, such as the regularized expectation maximization and least-squares adaptive algorithms, yield the best overall performances with respect to metrics of accuracy and robustness. However, no single algorithm consistently outperforms the remaining approaches, and in some cases, performing classification without imputation sometimes yieldedmore » the most accurate classification. Thus, because of the complex mechanisms of missing data in proteomics, which also vary from peptide to protein, no individual method is a single solution for imputation. In summary, on the basis of the observations in this review, the goal for imputation in the field of computational proteomics should be to develop new approaches that work generically for this data type and new strategies to guide users in the selection of the best imputation for their dataset and analysis objectives.« less

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.

BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics.

PubMed

Avtonomov, Dmitry M; Raskind, Alexander; Nesvizhskii, Alexey I

2016-08-05

Mass spectrometry (MS) coupled to liquid chromatography (LC) is a commonly used technique in metabolomic and proteomic research. As the size and complexity of LC-MS-based experiments grow, it becomes increasingly more difficult to perform quality control of both raw data and processing results. In a practical setting, quality control steps for raw LC-MS data are often overlooked, and assessment of an experiment's success is based on some derived metrics such as "the number of identified compounds". The human brain interprets visual data much better than plain text, hence the saying "a picture is worth a thousand words". Here, we present the BatMass software package, which allows for performing quick quality control of raw LC-MS data through its fast visualization capabilities. It also serves as a testbed for developers of LC-MS data processing algorithms by providing a data access library for open mass spectrometry file formats and a means of visually mapping processing results back to the original data. We illustrate the utility of BatMass with several use cases of quality control and data exploration.

BatMass: a Java software platform for LC/MS data visualization in proteomics and metabolomics

PubMed Central

Avtonomov, Dmitry; Raskind, Alexander; Nesvizhskii, Alexey I.

2017-01-01

Mass spectrometry (MS) coupled to liquid chromatography (LC) is a commonly used technique in metabolomic and proteomic research. As the size and complexity of LC/MS based experiments grow, it becomes increasingly more difficult to perform quality control of both raw data and processing results. In a practical setting, quality control steps for raw LC/MS data are often overlooked and assessment of an experiment's success is based on some derived metrics such as “the number of identified compounds”. Human brain interprets visual data much better than plain text, hence the saying “a picture is worth a thousand words”. Here we present BatMass software package which allows to perform quick quality control of raw LC/MS data through its fast visualization capabilities. It also serves as a testbed for developers of LC/MS data processing algorithms by providing a data access library for open mass spectrometry file formats and a means of visually mapping processing results back to the original data. We illustrate the utility of BatMass with several use cases of quality control and data exploration. PMID:27306858

Investigating the macropinocytic proteome of Dictyostelium amoebae by high-resolution mass spectrometry.

PubMed

Journet, Agnès; Klein, Gérard; Brugière, Sabine; Vandenbrouck, Yves; Chapel, Agnès; Kieffer, Sylvie; Bruley, Christophe; Masselon, Christophe; Aubry, Laurence

2012-01-01

The cellular slime mold Dictyostelium discoideum is a soil-living eukaryote, which feeds on microorganisms engulfed by phagocytosis. Axenic laboratory strains have been produced that are able to use liquid growth medium internalized by macropinocytosis as the source of food. To better define the macropinocytosis process, we established the inventory of proteins associated with this pathway using mass spectrometry-based proteomics. Using a magnetic purification procedure and high-performance LC-MS/MS proteome analysis, a list of 2108 non-redundant proteins was established, of which 24% featured membrane-spanning domains. Bioinformatics analyses indicated that the most abundant proteins were linked to signaling, vesicular trafficking and the cytoskeleton. The present repertoire validates our purification method and paves the way for a future proteomics approach to study the dynamics of macropinocytosis. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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

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.

Definitive screening design enables optimization of LC-ESI-MS/MS parameters in proteomics.

PubMed

Aburaya, Shunsuke; Aoki, Wataru; Minakuchi, Hiroyoshi; Ueda, Mitsuyoshi

2017-12-01

In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC-ESI-MS/MS to comprehensively identify these peptides. However, there are many parameters for LC-ESI-MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC-ESI-MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC-ESI-MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC-ESI-MS/MS systems.

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.

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.

The Human Skeletal Muscle Proteome Project: a reappraisal of the current literature

PubMed Central

Gonzalez‐Freire, Marta; Semba, Richard D.; Ubaida‐Mohien, Ceereena; Fabbri, Elisa; Scalzo, Paul; Højlund, Kurt; Dufresne, Craig; Lyashkov, Alexey

2016-01-01

Abstract Skeletal muscle is a large organ that accounts for up to half the total mass of the human body. A progressive decline in muscle mass and strength occurs with ageing and in some individuals configures the syndrome of ‘sarcopenia’, a condition that impairs mobility, challenges autonomy, and is a risk factor for mortality. The mechanisms leading to sarcopenia as well as myopathies are still little understood. The Human Skeletal Muscle Proteome Project was initiated with the aim to characterize muscle proteins and how they change with ageing and disease. We conducted an extensive review of the literature and analysed publically available protein databases. A systematic search of peer‐reviewed studies was performed using PubMed. Search terms included ‘human’, ‘skeletal muscle’, ‘proteome’, ‘proteomic(s)’, and ‘mass spectrometry’, ‘liquid chromatography‐mass spectrometry (LC‐MS/MS)’. A catalogue of 5431 non‐redundant muscle proteins identified by mass spectrometry‐based proteomics from 38 peer‐reviewed scientific publications from 2002 to November 2015 was created. We also developed a nosology system for the classification of muscle proteins based on localization and function. Such inventory of proteins should serve as a useful background reference for future research on changes in muscle proteome assessed by quantitative mass spectrometry‐based proteomic approaches that occur with ageing and diseases. This classification and compilation of the human skeletal muscle proteome can be used for the identification and quantification of proteins in skeletal muscle to discover new mechanisms for sarcopenia and specific muscle diseases that can be targeted for the prevention and treatment. PMID:27897395

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

PubMed

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

2005-09-01

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

Data Independent Acquisition analysis in ProHits 4.0.

PubMed

Liu, Guomin; Knight, James D R; Zhang, Jian Ping; Tsou, Chih-Chiang; Wang, Jian; Lambert, Jean-Philippe; Larsen, Brett; Tyers, Mike; Raught, Brian; Bandeira, Nuno; Nesvizhskii, Alexey I; Choi, Hyungwon; Gingras, Anne-Claude

2016-10-21

Affinity purification coupled with mass spectrometry (AP-MS) is a powerful technique for the identification and quantification of physical interactions. AP-MS requires careful experimental design, appropriate control selection and quantitative workflows to successfully identify bona fide interactors amongst a large background of contaminants. We previously introduced ProHits, a Laboratory Information Management System for interaction proteomics, which tracks all samples in a mass spectrometry facility, initiates database searches and provides visualization tools for spectral counting-based AP-MS approaches. More recently, we implemented Significance Analysis of INTeractome (SAINT) within ProHits to provide scoring of interactions based on spectral counts. Here, we provide an update to ProHits to support Data Independent Acquisition (DIA) with identification software (DIA-Umpire and MSPLIT-DIA), quantification tools (through DIA-Umpire, or externally via targeted extraction), and assessment of quantitative enrichment (through mapDIA) and scoring of interactions (through SAINT-intensity). With additional improvements, notably support of the iProphet pipeline, facilitated deposition into ProteomeXchange repositories and enhanced export and viewing functions, ProHits 4.0 offers a comprehensive suite of tools to facilitate affinity proteomics studies. It remains challenging to score, annotate and analyze proteomics data in a transparent manner. ProHits was previously introduced as a LIMS to enable storing, tracking and analysis of standard AP-MS data. In this revised version, we expand ProHits to include integration with a number of identification and quantification tools based on Data-Independent Acquisition (DIA). ProHits 4.0 also facilitates data deposition into public repositories, and the transfer of data to new visualization tools. Copyright © 2016 Elsevier B.V. All rights reserved.

Mass Spectrometry-based Approaches to Understand the Molecular Basis of Memory

NASA Astrophysics Data System (ADS)

Pontes, Arthur; de Sousa, Marcelo

2016-10-01

The central nervous system is responsible for an array of cognitive functions such as memory, learning, language and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enable the identification and quantification of thousand of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS)-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

Using HPLC-Mass Spectrometry to Teach Proteomics Concepts with Problem-Based Techniques

ERIC Educational Resources Information Center

Short, Michael; Short, Anne; Vankempen, Rachel; Seymour, Michael; Burnatowska-Hledin, Maria

2010-01-01

Practical instruction of proteomics concepts was provided using high-performance liquid chromatography coupled with a mass selective detection system (HPLC-MS) for the analysis of simulated protein digests. The samples were prepared from selected dipeptides in order to facilitate the mass spectral identification. As part of the prelaboratory…

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics

PubMed Central

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms. PMID:23176545

Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics.

PubMed

Mani, D R; Abbatiello, Susan E; Carr, Steven A

2012-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms.

Proteome-based bacterial identification using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS): A revolutionary shift in clinical diagnostic microbiology.

PubMed

Nomura, Fumio

2015-06-01

Rapid and accurate identification of microorganisms, a prerequisite for appropriate patient care and infection control, is a critical function of any clinical microbiology laboratory. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a quick and reliable method for identification of microorganisms, including bacteria, yeast, molds, and mycobacteria. Indeed, there has been a revolutionary shift in clinical diagnostic microbiology. In the present review, the state of the art and advantages of MALDI-TOF MS-based bacterial identification are described. The potential of this innovative technology for use in strain typing and detection of antibiotic resistance is also discussed. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

How many proteins can be identified in a 2DE gel spot within an analysis of a complex human cancer tissue proteome?

PubMed

Zhan, Xianquan; Yang, Haiyan; Peng, Fang; Li, Jianglin; Mu, Yun; Long, Ying; Cheng, Tingting; Huang, Yuda; Li, Zhao; Lu, Miaolong; Li, Na; Li, Maoyu; Liu, Jianping; Jungblut, Peter R

2018-04-01

Two-dimensional gel electrophoresis (2DE) in proteomics is traditionally assumed to contain only one or two proteins in each 2DE spot. However, 2DE resolution is being complemented by the rapid development of high sensitivity mass spectrometers. Here we compared MALDI-MS, LC-Q-TOF MS and LC-Orbitrap Velos MS for the identification of proteins within one spot. With LC-Orbitrap Velos MS each Coomassie Blue-stained 2DE spot contained an average of at least 42 and 63 proteins/spot in an analysis of a human glioblastoma proteome and a human pituitary adenoma proteome, respectively, if a single gel spot was analyzed. If a pool of three matched gel spots was analyzed this number further increased up to an average of 230 and 118 proteins/spot for glioblastoma and pituitary adenoma proteome, respectively. Multiple proteins per spot confirm the necessity of isotopic labeling in large-scale quantification of different protein species in a proteome. Furthermore, a protein abundance analysis revealed that most of the identified proteins in each analyzed 2DE spot were low-abundance proteins. Many proteins were present in several of the analyzed spots showing the ability of 2DE-MS to separate at the protein species level. Therefore, 2DE coupled with high-sensitivity LC-MS has a clearly higher sensitivity as expected until now to detect, identify and quantify low abundance proteins in a complex human proteome with an estimated resolution of about 500 000 protein species. This clearly exceeds the resolution power of bottom-up LC-MS investigations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes

NASA Astrophysics Data System (ADS)

Li, Huilin; Nguyen, Hong Hanh; Ogorzalek Loo, Rachel R.; Campuzano, Iain D. G.; Loo, Joseph A.

2018-02-01

Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8 MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation.

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.

MAPA distinguishes genotype-specific variability of highly similar regulatory protein isoforms in potato tuber.

PubMed

Hoehenwarter, Wolfgang; Larhlimi, Abdelhalim; Hummel, Jan; Egelhofer, Volker; Selbig, Joachim; van Dongen, Joost T; Wienkoop, Stefanie; Weckwerth, Wolfram

2011-07-01

Mass Accuracy Precursor Alignment is a fast and flexible method for comparative proteome analysis that allows the comparison of unprecedented numbers of shotgun proteomics analyses on a personal computer in a matter of hours. We compared 183 LC-MS analyses and more than 2 million MS/MS spectra and could define and separate the proteomic phenotypes of field grown tubers of 12 tetraploid cultivars of the crop plant Solanum tuberosum. Protein isoforms of patatin as well as other major gene families such as lipoxygenase and cysteine protease inhibitor that regulate tuber development were found to be the primary source of variability between the cultivars. This suggests that differentially expressed protein isoforms modulate genotype specific tuber development and the plant phenotype. We properly assigned the measured abundance of tryptic peptides to different protein isoforms that share extensive stretches of primary structure and thus inferred their abundance. Peptides unique to different protein isoforms were used to classify the remaining peptides assigned to the entire subset of isoforms based on a common abundance profile using multivariate statistical procedures. We identified nearly 4000 proteins which we used for quantitative functional annotation making this the most extensive study of the tuber proteome to date.

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.

Comprehensive Analysis of Proteomic Differences between Escherichia coli K-12 and B Strains Using Multiplexed Isobaric Tandem Mass Tag (TMT) Labeling.

PubMed

Han, Mee-Jung

2017-11-28

The Escherichia coli K-12 and B strains are among the most frequently used bacterial hosts for scientific research and biotechnological applications. However, omics analyses have revealed that E. coli K-12 and B exhibit notably different genotypic and phenotypic attributes, even though they were derived from the same ancestor. In a previous study, we identified a limited number of proteins from the two strains using two-dimensional gel electrophoresis and tandem mass spectrometry (MS/MS). In this study, an in-depth analysis of the physiological behavior of the E. coli K-12 and B strains at the proteomic level was performed using six-plex isobaric tandem mass tag-based quantitative MS. Additionally, the best lysis buffer for increasing the efficiency of protein extraction was selected from three tested buffers prior to the quantitative proteomic analysis. This study identifies the largest number of proteins in the two E. coli strains reported to date and is the first to show the dynamics of these proteins. Notable differences in proteins associated with key cellular properties, including some metabolic pathways, the biosynthesis and degradation of amino acids, membrane integrity, cellular tolerance, and motility, were found between the two representative strains. Compared with previous studies, these proteomic results provide a more holistic view of the overall state of E. coli cells based on a single proteomic study and reveal significant insights into why the two strains show distinct phenotypes. Additionally, the resulting data provide in-depth information that will help fine-tune processes in the future.

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

Enhancing Bottom-up and Top-down Proteomic Measurements with Ion Mobility Separations

DOE PAGES

Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; ...

2015-07-03

Proteomic measurements with greater throughput, sensitivity and additional structural information enhance the in-depth characterization of complex mixtures and targeted studies with additional information and higher confidence. While liquid chromatography separation coupled with mass spectrometry (LC-MS) measurements have provided information on thousands of proteins in different sample types, the additional of another rapid separation stage providing structural information has many benefits for analyses. Technical advances in ion funnels and multiplexing have enabled ion mobility separations to be easily and effectively coupled with LC-MS proteomics to enhance the information content of measurements. Finally, herein, we report on applications illustrating increased sensitivity, throughput,more » and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.« less

Label-Free Proteomic Identification of Endogenous, Insulin-Stimulated Interaction Partners of Insulin Receptor Substrate-1

NASA Astrophysics Data System (ADS)

Geetha, Thangiah; Langlais, Paul; Luo, Moulun; Mapes, Rebekka; Lefort, Natalie; Chen, Shu-Chuan; Mandarino, Lawrence J.; Yi, Zhengping

2011-03-01

Protein-protein interactions are key to most cellular processes. Tandem mass spectrometry (MS/MS)-based proteomics combined with co-immunoprecipitation (CO-IP) has emerged as a powerful approach for studying protein complexes. However, a majority of systematic proteomics studies on protein-protein interactions involve the use of protein overexpression and/or epitope-tagged bait proteins, which might affect binding stoichiometry and lead to higher false positives. Here, we report an application of a straightforward, label-free CO-IP-MS/MS method, without the use of protein overexpression or protein tags, to the investigation of changes in the abundance of endogenous proteins associated with a bait protein, which is in this case insulin receptor substrate-1 (IRS-1), under basal and insulin stimulated conditions. IRS-1 plays a central role in the insulin signaling cascade. Defects in the protein-protein interactions involving IRS-1 may lead to the development of insulin resistance and type 2 diabetes. HPLC-ESI-MS/MS analyses identified eleven novel endogenous insulin-stimulated IRS-1 interaction partners in L6 myotubes reproducibly, including proteins play an important role in protein dephosphorylation [protein phosphatase 1 regulatory subunit 12A, (PPP1R12A)], muscle contraction and actin cytoskeleton rearrangement, endoplasmic reticulum stress, and protein folding, as well as protein synthesis. This novel application of label-free CO-IP-MS/MS quantification to assess endogenous interaction partners of a specific protein will prove useful for understanding how various cell stimuli regulate insulin signal transduction.

Proteomics of Skeletal Muscle: Focus on Insulin Resistance and Exercise Biology

PubMed Central

Deshmukh, Atul S.

2016-01-01

Skeletal muscle is the largest tissue in the human body and plays an important role in locomotion and whole body metabolism. It accounts for ~80% of insulin stimulated glucose disposal. Skeletal muscle insulin resistance, a primary feature of Type 2 diabetes, is caused by a decreased ability of muscle to respond to circulating insulin. Physical exercise improves insulin sensitivity and whole body metabolism and remains one of the most promising interventions for the prevention of Type 2 diabetes. Insulin resistance and exercise adaptations in skeletal muscle might be a cause, or consequence, of altered protein expressions profiles and/or their posttranslational modifications (PTMs). Mass spectrometry (MS)-based proteomics offer enormous promise for investigating the molecular mechanisms underlying skeletal muscle insulin resistance and exercise-induced adaptation; however, skeletal muscle proteomics are challenging. This review describes the technical limitations of skeletal muscle proteomics as well as emerging developments in proteomics workflow with respect to samples preparation, liquid chromatography (LC), MS and computational analysis. These technologies have not yet been fully exploited in the field of skeletal muscle proteomics. Future studies that involve state-of-the-art proteomics technology will broaden our understanding of exercise-induced adaptations as well as molecular pathogenesis of insulin resistance. This could lead to the identification of new therapeutic targets. PMID:28248217

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.

rTANDEM, an R/Bioconductor package for MS/MS protein identification.

PubMed

Fournier, Frédéric; Joly Beauparlant, Charles; Paradis, René; Droit, Arnaud

2014-08-01

rTANDEM is an R/Bioconductor package that interfaces the X!Tandem protein identification algorithm. The package can run the multi-threaded algorithm on proteomic data files directly from R. It also provides functions to convert search parameters and results to/from R as well as functions to manipulate parameters and automate searches. An associated R package, shinyTANDEM, provides a web-based graphical interface to visualize and interpret the results. Together, those two packages form an entry point for a general MS/MS-based proteomic pipeline in R/Bioconductor. rTANDEM and shinyTANDEM are distributed in R/Bioconductor, http://bioconductor.org/packages/release/bioc/. The packages are under open licenses (GPL-3 and Artistice-1.0). frederic.fournier@crchuq.ulaval.ca or arnaud.droit@crchuq.ulaval.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Proteomic analysis of the Theileria annulata schizont

PubMed Central

Witschi, M.; Xia, D.; Sanderson, S.; Baumgartner, M.; Wastling, J.M.; Dobbelaere, D.A.E.

2013-01-01

The apicomplexan parasite, Theileria annulata, is the causative agent of tropical theileriosis, a devastating lymphoproliferative disease of cattle. The schizont stage transforms bovine leukocytes and provides an intriguing model to study host/pathogen interactions. The genome of T. annulata has been sequenced and transcriptomic data are rapidly accumulating. In contrast, little is known about the proteome of the schizont, the pathogenic, transforming life cycle stage of the parasite. Using one-dimensional (1-D) gel LC-MS/MS, a proteomic analysis of purified T. annulata schizonts was carried out. In whole parasite lysates, 645 proteins were identified. Proteins with transmembrane domains (TMDs) were under-represented and no proteins with more than four TMDs could be detected. To tackle this problem, Triton X-114 treatment was applied, which facilitates the extraction of membrane proteins, followed by 1-D gel LC-MS/MS. This resulted in the identification of an additional 153 proteins. Half of those had one or more TMD and 30 proteins with more than four TMDs were identified. This demonstrates that Triton X-114 treatment can provide a valuable additional tool for the identification of new membrane proteins in proteomic studies. With two exceptions, all proteins involved in glycolysis and the citric acid cycle were identified. For at least 29% of identified proteins, the corresponding transcripts were not present in the existing expressed sequence tag databases. The proteomics data were integrated into the publicly accessible database resource at EuPathDB (www.eupathdb.org) so that mass spectrometry-based protein expression evidence for T. annulata can be queried alongside transcriptional and other genomics data available for these parasites. PMID:23178997

Interlaboratory Study Characterizing a Yeast Performance Standard for Benchmarking LC-MS Platform Performance*

PubMed Central

Paulovich, Amanda G.; Billheimer, Dean; Ham, Amy-Joan L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Tabb, David L.; Wang, Pei; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Clauser, Karl R.; Kinsinger, Christopher R.; Schilling, Birgit; Tegeler, Tony J.; Variyath, Asokan Mulayath; Wang, Mu; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fenyo, David; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Mesri, Mehdi; Neubert, Thomas A.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Stein, Stephen E.; Tempst, Paul; Liebler, Daniel C.

2010-01-01

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize preanalytical and analytical variation in comparative proteomics experiments. PMID:19858499

Ecto-Fc MS identifies ligand-receptor interactions through extracellular domain Fc fusion protein baits and shotgun proteomic analysis

PubMed Central

Savas, Jeffrey N.; De Wit, Joris; Comoletti, Davide; Zemla, Roland; Ghosh, Anirvan

2015-01-01

Ligand-receptor interactions represent essential biological triggers which regulate many diverse and important cellular processes. We have developed a discovery-based proteomic biochemical protocol which couples affinity purification with multidimensional liquid chromatographic tandem mass spectrometry (LCLC-MS/MS) and bioinformatic analysis. Compared to previous approaches, our analysis increases sensitivity, shortens analysis duration, and boosts comprehensiveness. In this protocol, receptor extracellular domains are fused with the Fc region of IgG to generate fusion proteins that are purified from transfected HEK293T cells. These “ecto-Fcs” are coupled to protein A beads and serve as baits for binding assays with prey proteins extracted from rodent brain. After capture, the affinity purified proteins are digested into peptides and comprehensively analyzed by LCLC-MS/MS with ion trap mass spectrometers. In four working days, this protocol can generate shortlists of candidate ligand-receptor protein-protein interactions. Our “Ecto-Fc MS” approach outperforms antibody-based approaches and provides a reproducible and robust framework to identify extracellular ligand – receptor interactions. PMID:25101821

A proteomic analysis of the chromoplasts isolated from sweet orange fruits [Citrus sinensis (L.) Osbeck].

PubMed

Zeng, Yunliu; Pan, Zhiyong; Ding, Yuduan; Zhu, Andan; Cao, Hongbo; Xu, Qiang; Deng, Xiuxin

2011-11-01

Here, a comprehensive proteomic analysis of the chromoplasts purified from sweet orange using Nycodenz density gradient centrifugation is reported. A GeLC-MS/MS shotgun approach was used to identify the proteins of pooled chromoplast samples. A total of 493 proteins were identified from purified chromoplasts, of which 418 are putative plastid proteins based on in silico sequence homology and functional analyses. Based on the predicted functions of these identified plastid proteins, a large proportion (∼60%) of the chromoplast proteome of sweet orange is constituted by proteins involved in carbohydrate metabolism, amino acid/protein synthesis, and secondary metabolism. Of note, HDS (hydroxymethylbutenyl 4-diphosphate synthase), PAP (plastid-lipid-associated protein), and psHSPs (plastid small heat shock proteins) involved in the synthesis or storage of carotenoid and stress response are among the most abundant proteins identified. A comparison of chromoplast proteomes between sweet orange and tomato suggested a high level of conservation in a broad range of metabolic pathways. However, the citrus chromoplast was characterized by more extensive carotenoid synthesis, extensive amino acid synthesis without nitrogen assimilation, and evidence for lipid metabolism concerning jasmonic acid synthesis. In conclusion, this study provides an insight into the major metabolic pathways as well as some unique characteristics of the sweet orange chromoplasts at the whole proteome level.

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

PubMed

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

2017-07-03

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

Elucidating the fungal stress response by proteomics.

PubMed

Kroll, Kristin; Pähtz, Vera; Kniemeyer, Olaf

2014-01-31

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

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

PubMed Central

Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent

2016-01-01

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778

Pyteomics--a Python framework for exploratory data analysis and rapid software prototyping in proteomics.

PubMed

Goloborodko, Anton A; Levitsky, Lev I; Ivanov, Mark V; Gorshkov, Mikhail V

2013-02-01

Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python.org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com.

Performance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap Instrument

PubMed Central

Shen, Shichen; Sheng, Quanhu; Shyr, Yu; Qu, Jun

2016-01-01

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. To date, these different MS2 strategies and the optimal data interpretation approach for each have not been adequately evaluated. This study comprehensively investigated the four MS2 strategies: HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection), HCD-IT (HCD with ion trap, IT), CID-IT (collision-induced-dissociation with IT) and CID-OT on Orbitrap Fusion. To achieve extensive comparison and identify the optimal data interpretation method for each technique, several search engines (SEQUEST and Mascot) and post-processing methods (score-based, PeptideProphet, and Percolator) were assessed for all techniques for the analysis of a human cell proteome. It was found that divergent conclusions could be made from the same dataset when different data interpretation approaches were used and therefore requiring a relatively fair comparison among techniques. Percolator was chosen for comparison of techniques because it performs the best among all search engines and MS2 strategies. For the analysis of human cell proteome using individual MS2 strategies, the highest number of identifications was achieved by HCD-OT, followed by HCD-IT and CID-IT. Based on these results, we concluded that a relatively fair platform for data interpretation is necessary to avoid divergent conclusions from the same dataset, and HCD-OT and HCD-IT may be preferable for protein/peptide identification using Orbitrap Fusion. PMID:27472422

PROTICdb: a web-based application to store, track, query, and compare plant proteome data.

PubMed

Ferry-Dumazet, Hélène; Houel, Gwenn; Montalent, Pierre; Moreau, Luc; Langella, Olivier; Negroni, Luc; Vincent, Delphine; Lalanne, Céline; de Daruvar, Antoine; Plomion, Christophe; Zivy, Michel; Joets, Johann

2005-05-01

PROTICdb is a web-based application, mainly designed to store and analyze plant proteome data obtained by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and mass spectrometry (MS). The purposes of PROTICdb are (i) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements, and (ii) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of post-translational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs of image analysis and MS identification software, or by filling web forms. 2-D PAGE annotated maps can be displayed, queried, and compared through a graphical interface. Links to external databases are also available. Quantitative data can be easily exported in a tabulated format for statistical analyses. PROTICdb is based on the Oracle or the PostgreSQL Database Management System and is freely available upon request at the following URL: http://moulon.inra.fr/ bioinfo/PROTICdb.

A decade of plant proteomics and mass spectrometry: translation of technical advancements to food security and safety issues.

PubMed

Agrawal, Ganesh Kumar; Sarkar, Abhijit; Righetti, Pier Giorgio; Pedreschi, Romina; Carpentier, Sebastien; Wang, Tai; Barkla, Bronwyn J; Kohli, Ajay; Ndimba, Bongani Kaiser; Bykova, Natalia V; Rampitsch, Christof; Zolla, Lello; Rafudeen, Mohamed Suhail; Cramer, Rainer; Bindschedler, Laurence Veronique; Tsakirpaloglou, Nikolaos; Ndimba, Roya Janeen; Farrant, Jill M; Renaut, Jenny; Job, Dominique; Kikuchi, Shoshi; Rakwal, Randeep

2013-01-01

Tremendous progress in plant proteomics driven by mass spectrometry (MS) techniques has been made since 2000 when few proteomics reports were published and plant proteomics was in its infancy. These achievements include the refinement of existing techniques and the search for new techniques to address food security, safety, and health issues. It is projected that in 2050, the world's population will reach 9-12 billion people demanding a food production increase of 34-70% (FAO, 2009) from today's food production. Provision of food in a sustainable and environmentally committed manner for such a demand without threatening natural resources, requires that agricultural production increases significantly and that postharvest handling and food manufacturing systems become more efficient requiring lower energy expenditure, a decrease in postharvest losses, less waste generation and food with longer shelf life. There is also a need to look for alternative protein sources to animal based (i.e., plant based) to be able to fulfill the increase in protein demands by 2050. Thus, plant biology has a critical role to play as a science capable of addressing such challenges. In this review, we discuss proteomics especially MS, as a platform, being utilized in plant biology research for the past 10 years having the potential to expedite the process of understanding plant biology for human benefits. The increasing application of proteomics technologies in food security, analysis, and safety is emphasized in this review. But, we are aware that no unique approach/technology is capable to address the global food issues. Proteomics-generated information/resources must be integrated and correlated with other omics-based approaches, information, and conventional programs to ensure sufficient food and resources for human development now and in the future. © 2013 Wiley Periodicals, Inc.

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

Song, Ehwang; Gao, Yuqian; Wu, Chaochao

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

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).

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

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 different workflows, for detection of variant proteins with different absolute expression levels and fold change values. The dataset presented here can be useful for tuning software tool parameters, and also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Proteomics of eukaryotic microorganisms: The medically and biotechnologically important fungal genus Aspergillus.

PubMed

Kniemeyer, Olaf

2011-08-01

Fungal species of the genus Aspergillus play significant roles as model organisms in basic research, as "cell factories" for the production of organic acids, pharmaceuticals or industrially important enzymes and as pathogens causing superficial and invasive infections in animals and humans. The release of the genome sequences of several Aspergillus sp. has paved the way for global analyses of protein expression in Aspergilli including the characterisation of proteins, which have not designated any function. With the application of proteomic methods, particularly 2-D gel and LC-MS/MS-based methods, first insights into the composition of the proteome of Aspergilli under different growth and stress conditions could be gained. Putative targets of global regulators led to the improvement of industrially relevant Aspergillus strains and so far not described Aspergillus antigens have already been discovered. Here, I review the recent proteome data generated for the species Aspergillus nidulans, Aspergillus fumigatus, Aspergillus niger, Aspergillus terreus, Aspergillus flavus and Aspergillus oryzae. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mass spectrometry-based proteomics: basic principles and emerging technologies and directions.

PubMed

Van Riper, Susan K; de Jong, Ebbing P; Carlis, John V; Griffin, Timothy J

2013-01-01

As the main catalytic and structural molecules within living systems, proteins are the most likely biomolecules to be affected by radiation exposure. Proteomics, the comprehensive characterization of proteins within complex biological samples, is therefore a research approach ideally suited to assess the effects of radiation exposure on cells and tissues. For comprehensive characterization of proteomes, an analytical platform capable of quantifying protein abundance, identifying post-translation modifications and revealing members of protein complexes on a system-wide level is necessary. Mass spectrometry (MS), coupled with technologies for sample fractionation and automated data analysis, provides such a versatile and powerful platform. In this chapter we offer a view on the current state of MS-proteomics, and focus on emerging technologies within three areas: (1) New instrumental methods; (2) New computational methods for peptide identification; and (3) Label-free quantification. These emerging technologies should be valuable for researchers seeking to better understand biological effects of radiation on living systems.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.

PubMed

Zhu, Ying; Piehowski, Paul D; Zhao, Rui; Chen, Jing; Shen, Yufeng; Moore, Ronald J; Shukla, Anil K; Petyuk, Vladislav A; Campbell-Thompson, Martha; Mathews, Clayton E; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

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.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

DOE PAGES

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui; ...

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data.

PubMed

Tu, Chengjian; Sheng, Quanhu; Li, Jun; Ma, Danjun; Shen, Xiaomeng; Wang, Xue; Shyr, Yu; Yi, Zhengping; Qu, Jun

2015-11-06

The two key steps for analyzing proteomic data generated by high-resolution MS are database searching and postprocessing. While the two steps are interrelated, studies on their combinatory effects and the optimization of these procedures have not been adequately conducted. Here, we investigated the performance of three popular search engines (SEQUEST, Mascot, and MS Amanda) in conjunction with five filtering approaches, including respective score-based filtering, a group-based approach, local false discovery rate (LFDR), PeptideProphet, and Percolator. A total of eight data sets from various proteomes (e.g., E. coli, yeast, and human) produced by various instruments with high-accuracy survey scan (MS1) and high- or low-accuracy fragment ion scan (MS2) (LTQ-Orbitrap, Orbitrap-Velos, Orbitrap-Elite, Q-Exactive, Orbitrap-Fusion, and Q-TOF) were analyzed. It was found combinations involving Percolator achieved markedly more peptide and protein identifications at the same FDR level than the other 12 combinations for all data sets. Among these, combinations of SEQUEST-Percolator and MS Amanda-Percolator provided slightly better performances for data sets with low-accuracy MS2 (ion trap or IT) and high accuracy MS2 (Orbitrap or TOF), respectively, than did other methods. For approaches without Percolator, SEQUEST-group performs the best for data sets with MS2 produced by collision-induced dissociation (CID) and IT analysis; Mascot-LFDR gives more identifications for data sets generated by higher-energy collisional dissociation (HCD) and analyzed in Orbitrap (HCD-OT) and in Orbitrap Fusion (HCD-IT); MS Amanda-Group excels for the Q-TOF data set and the Orbitrap Velos HCD-OT data set. Therefore, if Percolator was not used, a specific combination should be applied for each type of data set. Moreover, a higher percentage of multiple-peptide proteins and lower variation of protein spectral counts were observed when analyzing technical replicates using Percolator-associated combinations; therefore, Percolator enhanced the reliability for both identification and quantification. The analyses were performed using the specific programs embedded in Proteome Discoverer, Scaffold, and an in-house algorithm (BuildSummary). These results provide valuable guidelines for the optimal interpretation of proteomic results and the development of fit-for-purpose protocols under different situations.

Application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in Alzheimer's disease.

PubMed

Grela, Agatha; Turek, Agata; Piekoszewski, Wojciech

2012-02-11

Alzheimer's disease is becoming an increasing problem in our aging society. According to our knowledge, so far, no effective pharmacotherapy to cure the cause of the disease has been developed. Therefore, early diagnosis is needed, which will result in implementation of a drug therapy aimed at decreasing and/or inhibiting disease development. Mass spectrometry techniques (MS) have a wide range of applications in proteomics and the search for biomarkers of neurodegenerative disorders, opening new possibilities in diagnostics. Identification of proteins in body fluids (like cerebrospinal fluid or blood) is possible due to MS spectra analysis. The detected changes in protein concentrations are connected with pathological states in an organism and, therefore, can be regarded as biomarkers. Developing procedures for proteome analysis might result in fast diagnosis, as well as creating better suited pharmaceuticals. This paper reviews the search of biomarkers in cerebrospinal fluid and blood. Later on, the use of matrix-assisted-laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in proteomics, focusing on blood-related biomarkers, is discussed. The aim of the work is also to highlight the advantages and disadvantages of MALDI-TOF-based analyses.

Gel-based and gel-free proteomic analysis of Nicotiana tabacum trichomes identifies proteins involved in secondary metabolism and in the (a)biotic stress response.

PubMed

Van Cutsem, Emmanuel; Simonart, Géraldine; Degand, Hervé; Faber, Anne-Marie; Morsomme, Pierre; Boutry, Marc

2011-02-01

Nicotiana tabacum leaves are covered by trichomes involved in the secretion of large amounts of secondary metabolites, some of which play a major role in plant defense. However, little is known about the metabolic pathways that operate in these structures. We undertook a proteomic analysis of N. tabacum trichomes in order to identify their protein complement. Efficient trichome isolation was obtained by abrading frozen leaves. After homogenization, soluble proteins and a microsomal fraction were prepared by centrifugation. Gel-based and gel-free proteomic analyses were then performed. 2-DE analysis of soluble proteins led to the identification of 1373 protein spots, which were digested and analyzed by MS/MS, leading to 680 unique identifications. Both soluble proteins and microsomal fraction were analyzed by LC MALDI-MS/MS after trypsin digestion, leading to 858 identifications, many of which had not been identified after 2-DE, indicating that the two methods complement each other. Many enzymes putatively involved in secondary metabolism were identified, including enzymes involved in the synthesis of terpenoid precursors and in acyl sugar production. Several transporters were also identified, some of which might be involved in secondary metabolite transport. Various (a)biotic stress response proteins were also detected, supporting the role of trichomes in plant defense. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

UV irradiation-induced methionine oxidation in human skin keratins: Mass spectrometry-based non-invasive proteomic analysis.

PubMed

Lee, Seon Hwa; Matsushima, Keita; Miyamoto, Kohei; Oe, Tomoyuki

2016-02-05

Ultraviolet (UV) radiation is the major environmental factor that causes oxidative skin damage. Keratins are the main constituents of human skin and have been identified as oxidative target proteins. We have recently developed a mass spectrometry (MS)-based non-invasive proteomic methodology to screen oxidative modifications in human skin keratins. Using this methodology, UV effects on methionine (Met) oxidation in human skin keratins were investigated. The initial screening revealed that Met(259), Met(262), and Met(296) in K1 keratin were the most susceptible oxidation sites upon UVA (or UVB) irradiation of human tape-stripped skin. Subsequent liquid chromatography/electrospray ionization-MS and tandem MS analyses confirmed amino acid sequences and oxidation sites of tryptic peptides D(290)VDGAYMTK(298) (P1) and N(258)MQDMVEDYR(267) (P2). The relative oxidation levels of P1 and P2 increased in a time-dependent manner upon UVA irradiation. Butylated hydroxytoluene was the most effective antioxidant for artifactual oxidation of Met residues. The relative oxidation levels of P1 and P2 after UVA irradiation for 48 h corresponded to treatment with 100mM hydrogen peroxide for 15 min. In addition, Met(259) was oxidized by only UVA irradiation. The Met sites identified in conjunction with the current proteomic methodology can be used to evaluate skin damage under various conditions of oxidative stress. We demonstrated that the relative Met oxidation levels in keratins directly reflected UV-induced damages to human tape-stripped skin. Human skin proteins isolated by tape stripping were analyzed by MS-based non-invasive proteomic methodology. Met(259), Met(262), and Met(296) in K1 keratin were the most susceptible oxidation sites upon UV irradiation. Met(259) was oxidized by only UVA irradiation. Quantitative LC/ESI-SRM/MS analyses confirmed a time-dependent increase in the relative oxidation of target peptides (P1 and P2) containing these Met residues, upon UVA irradiation of isolated human skin. The relative oxidation levels of P1 and P2 along with the current proteomic methodology could be applied to the assessment of oxidative stress levels in skin after exposure to sunlight. Copyright © 2015 Elsevier B.V. All rights reserved.

MALDI-TOF MS of Trichoderma: A model system for the identification of microfungi

USDA-ARS?s Scientific Manuscript database

This investigation aimed to assess whether MALDI-TOF MS analysis of proteomics could be applied to the study of Trichoderma, a fungal genus selected because it includes many species and is phylogenetically well defined. We also investigated whether MALDI-TOF MS analysis of proteomics would reveal ap...

Proteomic Analysis of the Human Skin Proteome after In Vivo Treatment with Sodium Dodecyl Sulphate

PubMed Central

Parkinson, Erika; Skipp, Paul; Aleksic, Maja; Garrow, Andrew; Dadd, Tony; Hughes, Michael; Clough, Geraldine; O′Connor, C. David

2014-01-01

Background Skin has a variety of functions that are incompletely understood at the molecular level. As the most accessible tissue in the body it often reveals the first signs of inflammation or infection and also represents a potentially valuable source of biomarkers for several diseases. In this study we surveyed the skin proteome qualitatively using gel electrophoresis, liquid chromatography tandem mass spectrometry (GeLC-MS/MS) and quantitatively using an isobaric tagging strategy (iTRAQ) to characterise the response of human skin following exposure to sodium dodecyl sulphate (SDS). Results A total of 653 skin proteins were assigned, 159 of which were identified using GeLC-MS/MS and 616 using iTRAQ, representing the most comprehensive proteomic study in human skin tissue. Statistical analysis of the available iTRAQ data did not reveal any significant differences in the measured skin proteome after 4 hours exposure to the model irritant SDS. Conclusions This study represents the first step in defining the critical response to an irritant at the level of the proteome and provides a valuable resource for further studies at the later stages of irritant exposure. PMID:24849295

Liquid Chromatography Mass Spectrometry-Based Proteomics: Biological and Technological Aspects

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

Karpievitch, Yuliya V.; Polpitiya, Ashoka D.; Anderson, Gordon A.

2010-12-01

Mass spectrometry-based proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. Though recent years have seen a tremendous improvement in instrument performance and the computational tools used, significant challenges remain, and there are many opportunities for statisticians to make important contributions. In the most widely used "bottom-up" approach to proteomics, complex mixtures of proteins are first subjected to enzymatic cleavage, the resulting peptide products are separated based on chemical or physical properties and analyzed using a mass spectrometer. The two fundamental challenges in the analysis of bottom-up MS-based proteomics are: (1) Identifying themore » proteins that are present in a sample, and (2) Quantifying the abundance levels of the identified proteins. Both of these challenges require knowledge of the biological and technological context that gives rise to observed data, as well as the application of sound statistical principles for estimation and inference. We present an overview of bottom-up proteomics and outline the key statistical issues that arise in protein identification and quantification.« less

Using the CPTAC Assay Portal to identify and implement highly characterized targeted proteomics assays

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

Whiteaker, Jeffrey R.; Halusa, Goran; Hoofnagle, Andrew N.

2016-02-12

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative tomore » other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and post-translational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.« less

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays.

PubMed

Whiteaker, Jeffrey R; Halusa, Goran N; Hoofnagle, Andrew N; Sharma, Vagisha; MacLean, Brendan; Yan, Ping; Wrobel, John A; Kennedy, Jacob; Mani, D R; Zimmerman, Lisa J; Meyer, Matthew R; Mesri, Mehdi; Boja, Emily; Carr, Steven A; Chan, Daniel W; Chen, Xian; Chen, Jing; Davies, Sherri R; Ellis, Matthew J C; Fenyö, David; Hiltke, Tara; Ketchum, Karen A; Kinsinger, Chris; Kuhn, Eric; Liebler, Daniel C; Liu, Tao; Loss, Michael; MacCoss, Michael J; Qian, Wei-Jun; Rivers, Robert; Rodland, Karin D; Ruggles, Kelly V; Scott, Mitchell G; Smith, Richard D; Thomas, Stefani; Townsend, R Reid; Whiteley, Gordon; Wu, Chaochao; Zhang, Hui; Zhang, Zhen; Rodriguez, Henry; Paulovich, Amanda G

2016-01-01

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

LC-MS/MS Identification of Species-Specific Muscle Peptides in Processed Animal Proteins.

PubMed

Marchis, Daniela; Altomare, Alessandra; Gili, Marilena; Ostorero, Federica; Khadjavi, Amina; Corona, Cristiano; Ru, Giuseppe; Cappelletti, Benedetta; Gianelli, Silvia; Amadeo, Francesca; Rumio, Cristiano; Carini, Marina; Aldini, Giancarlo; Casalone, Cristina

2017-12-06

An innovative analytical strategy has been applied to identify signature peptides able to distinguish among processed animal proteins (PAPs) derived from bovine, pig, fish, and milk products. Proteomics was first used to elucidate the proteome of each source. Starting from the identified proteins and using a funnel based approach, a set of abundant and well characterized peptides with suitable physical-chemical properties (signature peptides) and specific for each source was selected. An on-target LC-ESI-MS/MS method (MRM mode) was set up using standard peptides and was then applied to selectively identify the PAP source and also to distinguish proteins from bovine carcass and milk proteins. We believe that the method described meets the request of the European Commission which has developed a strategy for gradually lifting the "total ban" toward "species to species ban", therefore requiring official methods for species-specific discrimination in feed.

Metabolome and proteome profiling of complex I deficiency induced by rotenone.

PubMed

Gielisch, Ina; Meierhofer, David

2015-01-02

Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.

PubMed

Severi, Leda; Losi, Lorena; Fonda, Sergio; Taddia, Laura; Gozzi, Gaia; Marverti, Gaetano; Magni, Fulvio; Chinello, Clizia; Stella, Martina; Sheouli, Jalid; Braicu, Elena I; Genovese, Filippo; Lauriola, Angela; Marraccini, Chiara; Gualandi, Alessandra; D'Arca, Domenico; Ferrari, Stefania; Costi, Maria P

2018-01-01

Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuest™ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.

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.

NOVEL METHODS FOR TARGET PROTEIN IDENTIFICATION USING IMMUNOPRECIPITATION - LC/MS/MS

EPA Science Inventory

Proteomics provides a powerful approach to screen and analyze responses to environmental exposures which induce alterations in protein expression, phosphorylation. ubiquitinylation, oxidation. and modulation of general proteome function. Post-translational modifications (PTM) of ...

Performance Evaluation of the Q Exactive HF-X for Shotgun Proteomics.

PubMed

Kelstrup, Christian D; Bekker-Jensen, Dorte B; Arrey, Tabiwang N; Hogrebe, Alexander; Harder, Alexander; Olsen, Jesper V

2018-01-05

Progress in proteomics is mainly driven by advances in mass spectrometric (MS) technologies. Here we benchmarked the performance of the latest MS instrument in the benchtop Orbitrap series, the Q Exactive HF-X, against its predecessor for proteomics applications. A new peak-picking algorithm, a brighter ion source, and optimized ion transfers enable productive MS/MS acquisition above 40 Hz at 7500 resolution. The hardware and software improvements collectively resulted in improved peptide and protein identifications across all comparable conditions, with an increase of up to 50 percent at short LC-MS gradients, yielding identification rates of more than 1000 unique peptides per minute. Alternatively, the Q Exactive HF-X is capable of achieving the same proteome coverage as its predecessor in approximately half the gradient time or at 10-fold lower sample loads. The Q Exactive HF-X also enables rapid phosphoproteomics with routine analysis of more than 5000 phosphopeptides with short single-shot 15 min LC-MS/MS measurements, or 16 700 phosphopeptides quantified across ten conditions in six gradient hours using TMT10-plex and offline peptide fractionation. Finally, exciting perspectives for data-independent acquisition are highlighted with reproducible identification of 55 000 unique peptides covering 5900 proteins in half an hour of MS analysis.

Current trends in mass spectrometry of peptides and proteins: Application to veterinary and sports-doping control.

PubMed

van den Broek, Irene; Blokland, Marco; Nessen, Merel A; Sterk, Saskia

2015-01-01

Detection of misuse of peptides and proteins as growth promoters is a major issue for sport and food regulatory agencies. The limitations of current analytical detection strategies for this class of compounds, in combination with their efficacy in growth-promoting effects, make peptide and protein drugs highly susceptible to abuse by either athletes or farmers who seek for products to illicitly enhance muscle growth. Mass spectrometry (MS) for qualitative analysis of peptides and proteins is well-established, particularly due to tremendous efforts in the proteomics community. Similarly, due to advancements in targeted proteomic strategies and the rapid growth of protein-based biopharmaceuticals, MS for quantitative analysis of peptides and proteins is becoming more widely accepted. These continuous advances in MS instrumentation and MS-based methodologies offer enormous opportunities for detection and confirmation of peptides and proteins. Therefore, MS seems to be the method of choice to improve the qualitative and quantitative analysis of peptide and proteins with growth-promoting properties. This review aims to address the opportunities of MS for peptide and protein analysis in veterinary control and sports-doping control with a particular focus on detection of illicit growth promotion. An overview of potential peptide and protein targets, including their amino acid sequence characteristics and current MS-based detection strategies is, therefore, provided. Furthermore, improvements of current and new detection strategies with state-of-the-art MS instrumentation are discussed for qualitative and quantitative approaches. © 2013 Wiley Periodicals, Inc.

Silencing of high-mobility group box 2 (HMGB2) modulates cisplatin and 5-fluorouracil sensitivity in head and neck squamous cell carcinoma.

PubMed

Syed, Nazia; Chavan, Sandip; Sahasrabuddhe, Nandini A; Renuse, Santosh; Sathe, Gajanan; Nanjappa, Vishalakshi; Radhakrishnan, Aneesha; Raja, Remya; Pinto, Sneha M; Srinivasan, Anand; Prasad, T S Keshava; Srikumar, Kotteazeth; Gowda, Harsha; Santosh, Vani; Sidransky, David; Califano, Joseph A; Pandey, Akhilesh; Chatterjee, Aditi

2015-01-01

Dysregulation of protein expression is associated with most diseases including cancer. MS-based proteomic analysis is widely employed as a tool to study protein dysregulation in cancers. Proteins that are differentially expressed in head and neck squamous cell carcinoma (HNSCC) cell lines compared to the normal oral cell line could serve as biomarkers for patient stratification. To understand the proteomic complexity in HNSCC, we carried out iTRAQ-based MS analysis on a panel of HNSCC cell lines in addition to a normal oral keratinocyte cell line. LC-MS/MS analysis of total proteome of the HNSCC cell lines led to the identification of 3263 proteins, of which 185 proteins were overexpressed and 190 proteins were downregulated more than twofold in at least two of the three HNSCC cell lines studied. Among the overexpressed proteins, 23 proteins were related to DNA replication and repair. These included high-mobility group box 2 (HMGB2) protein, which was overexpressed in all three HNSCC lines studied. Overexpression of HMGB2 has been reported in various cancers, yet its role in HNSCC remains unclear. Immunohistochemical labeling of HMGB2 in a panel of HNSCC tumors using tissue microarrays revealed overexpression in 77% (54 of 70) of tumors. The HMGB proteins are known to bind to DNA structure resulting from cisplatin-DNA adducts and affect the chemosensitivity of cells. We observed that siRNA-mediated silencing of HMGB2 increased the sensitivity of the HNSCC cell lines to cisplatin and 5-FU. We hypothesize that targeting HMGB2 could enhance the efficacy of existing chemotherapeutic regimens for treatment of HNSCC. All MS data have been deposited in the ProteomeXchange with identifier PXD000737 (http://proteomecentral.proteomexchange.org/dataset/PXD000737). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomics identifies the composition and manufacturing recipe of the 2500-year old sourdough bread from Subeixi cemetery in China.

PubMed

Shevchenko, Anna; Yang, Yimin; Knaust, Andrea; Thomas, Henrik; Jiang, Hongen; Lu, Enguo; Wang, Changsui; Shevchenko, Andrej

2014-06-13

We report on the geLC-MS/MS proteomics analysis of cereals and cereal food excavated in Subeixi cemetery (500-300BC) in Xinjiang, China. Proteomics provided direct evidence that at the Subexi sourdough bread was made from barley and broomcorn millet by leavening with a renewable starter comprising baker's yeast and lactic acid bacteria. The baking recipe and flour composition indicated that barley and millet bread belonged to the staple food already in the first millennium BC and suggested the role of Turpan basin as a major route for cultural communication between Western and Eastern Eurasia in antiquity. This article is part of a Special Issue entitled: Proteomics of non-model organisms. We demonstrate that organic residues of thousand year old foods unearthed by archeological excavations can be analyzed by geLC-MS/MS proteomics with good representation of protein source organisms and coverage of sequences of identified proteins. In-depth look into the foods proteome identifies the food type and its individual ingredients, reveals ancient food processing technologies, projects their social and economic impact and provides evidence of intercultural communication between ancient populations. Proteomics analysis of ancient organic residues is direct, quantitative and informative and therefore has the potential to develop into a valuable, generally applicable tool in archaeometry. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2013. Published by Elsevier B.V.

sapFinder: an R/Bioconductor package for detection of variant peptides in shotgun proteomics experiments.

PubMed

Wen, Bo; Xu, Shaohang; Sheynkman, Gloria M; Feng, Qiang; Lin, Liang; Wang, Quanhui; Xu, Xun; Wang, Jun; Liu, Siqi

2014-11-01

Single nucleotide variations (SNVs) located within a reading frame can result in single amino acid polymorphisms (SAPs), leading to alteration of the corresponding amino acid sequence as well as function of a protein. Accurate detection of SAPs is an important issue in proteomic analysis at the experimental and bioinformatic level. Herein, we present sapFinder, an R software package, for detection of the variant peptides based on tandem mass spectrometry (MS/MS)-based proteomics data. This package automates the construction of variation-associated databases from public SNV repositories or sample-specific next-generation sequencing (NGS) data and the identification of SAPs through database searching, post-processing and generation of HTML-based report with visualized interface. sapFinder is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at http://bioconductor.org/packages/devel/bioc/html/sapFinder.html and are provided under a GPL-2 license. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Defining the proteome of human iris, ciliary body, retinal pigment epithelium, and choroid.

PubMed

Zhang, Pingbo; Kirby, David; Dufresne, Craig; Chen, Yan; Turner, Randi; Ferri, Sara; Edward, Deepak P; Van Eyk, Jennifer E; Semba, Richard D

2016-04-01

The iris is a fine structure that controls the amount of light that enters the eye. The ciliary body controls the shape of the lens and produces aqueous humor. The retinal pigment epithelium and choroid (RPE/choroid) are essential in supporting the retina and absorbing light energy that enters the eye. Proteins were extracted from iris, ciliary body, and RPE/choroid tissues of eyes from five individuals and fractionated using SDS-PAGE. After in-gel digestion, peptides were analyzed using LC-MS/MS on an Orbitrap Elite mass spectrometer. In iris, ciliary body, and RPE/choroid, we identified 2959, 2867, and 2755 nonredundant proteins with peptide and protein false-positive rates of <0.1% and <1%, respectively. Forty-three unambiguous protein isoforms were identified in iris, ciliary body, and RPE/choroid. Four "missing proteins" were identified in ciliary body based on ≥2 proteotypic peptides. The mass spectrometric proteome database of the human iris, ciliary body, and RPE/choroid may serve as a valuable resource for future investigations of the eye in health and disease. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001424 and PXD002194. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Differential expression profiling of serum proteins and metabolites for biomarker discovery

NASA Astrophysics Data System (ADS)

Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.

2004-11-01

A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.

Species Identification of Archaeological Skin Objects from Danish Bogs: Comparison between Mass Spectrometry-Based Peptide Sequencing and Microscopy-Based Methods

PubMed Central

Brandt, Luise Ørsted; Schmidt, Anne Lisbeth; Mannering, Ulla; Sarret, Mathilde; Kelstrup, Christian D.; Olsen, Jesper V.; Cappellini, Enrico

2014-01-01

Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC – AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029. PMID:25260035

Advances in Proteomics Data Analysis and Display Using an Accurate Mass and Time Tag Approach

PubMed Central

Zimmer, Jennifer S.D.; Monroe, Matthew E.; Qian, Wei-Jun; Smith, Richard D.

2007-01-01

Proteomics has recently demonstrated utility in understanding cellular processes on the molecular level as a component of systems biology approaches and for identifying potential biomarkers of various disease states. The large amount of data generated by utilizing high efficiency (e.g., chromatographic) separations coupled to high mass accuracy mass spectrometry for high-throughput proteomics analyses presents challenges related to data processing, analysis, and display. This review focuses on recent advances in nanoLC-FTICR-MS-based proteomics approaches and the accompanying data processing tools that have been developed to display and interpret the large volumes of data being produced. PMID:16429408

Optimized approaches for quantification of drug transporters in tissues and cells by MRM proteomics.

PubMed

Prasad, Bhagwat; Unadkat, Jashvant D

2014-07-01

Drug transporter expression in tissues (in vivo) usually differs from that in cell lines used to measure transporter activity (in vitro). Therefore, quantification of transporter expression in tissues and cell lines is important to develop scaling factor for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated drug disposition. Since traditional immunoquantification methods are semiquantitative, targeted proteomics is now emerging as a superior method to quantify proteins, including membrane transporters. This superiority is derived from the selectivity, precision, accuracy, and speed of analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode. Moreover, LC-MS/MS proteomics has broader applicability because it does not require selective antibodies for individual proteins. There are a number of recent research and review papers that discuss the use of LC-MS/MS for transporter quantification. Here, we have compiled from the literature various elements of MRM proteomics to provide a comprehensive systematic strategy to quantify drug transporters. This review emphasizes practical aspects and challenges in surrogate peptide selection, peptide qualification, peptide synthesis and characterization, membrane protein isolation, protein digestion, sample preparation, LC-MS/MS parameter optimization, method validation, and sample analysis. In particular, bioinformatic tools used in method development and sample analysis are discussed in detail. Various pre-analytical and analytical sources of variability that should be considered during transporter quantification are highlighted. All these steps are illustrated using P-glycoprotein (P-gp) as a case example. Greater use of quantitative transporter proteomics will lead to a better understanding of the role of drug transporters in drug disposition.

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

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

Simulation of two dimensional electrophoresis and tandem mass spectrometry for teaching proteomics.

PubMed

Fisher, Amanda; Sekera, Emily; Payne, Jill; Craig, Paul

2012-01-01

In proteomics, complex mixtures of proteins are separated (usually by chromatography or electrophoresis) and identified by mass spectrometry. We have created 2DE Tandem MS, a computer program designed for use in the biochemistry, proteomics, or bioinformatics classroom. It contains two simulations-2D electrophoresis and tandem mass spectrometry. The two simulations are integrated together and are designed to teach the concept of proteome analysis of prokaryotic and eukaryotic organisms. 2DE-Tandem MS can be used as a freestanding simulation, or in conjunction with a wet lab, to introduce proteomics in the undergraduate classroom. 2DE Tandem MS is a free program available on Sourceforge at https://sourceforge.net/projects/jbf/. It was developed using Java Swing and functions in Mac OSX, Windows, and Linux, ensuring that every student sees a consistent and informative graphical user interface no matter the computer platform they choose. Java must be installed on the host computer to run 2DE Tandem MS. Example classroom exercises are provided in the Supporting Information. Copyright © 2012 Wiley Periodicals, Inc.

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

PubMed

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

2015-01-01

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

A robust mass spectrometry method for rapid profiling of erythrocyte ghost membrane proteomes.

PubMed

Fye, Haddy K S; Mrosso, Paul; Bruce, Lesley; Thézénas, Marie-Laëtitia; Davis, Simon; Fischer, Roman; Rwegasira, Gration L; Makani, Julie; Kessler, Benedikt M

2018-01-01

Red blood cell (RBC) physiology is directly linked to many human disorders associated with low tissue oxygen levels or anemia including chronic obstructive pulmonary disease, congenital heart disease, sleep apnea and sickle cell anemia. Parasites such as Plasmodium spp. and phylum Apicomplexa directly target RBCs, and surface molecules within the RBC membrane are critical for pathogen interactions. Proteomics of RBC membrane 'ghost' fractions has therefore been of considerable interest, but protocols described to date are either suboptimal or too extensive to be applicable to a larger set of clinical cohorts. Here, we describe an optimised erythrocyte isolation protocol from blood, tested for various storage conditions and explored using different fractionation conditions for isolating ghost RBC membranes. Liquid chromatography mass spectrometry (LC-MS) analysis on a Q-Exactive Orbitrap instrument was used to profile proteins isolated from the comparative conditions. Data analysis was run on the MASCOT and MaxQuant platforms to assess their scope and diversity. The results obtained demonstrate a robust method for membrane enrichment enabling consistent MS based characterisation of > 900 RBC membrane proteins in single LC-MS/MS analyses. Non-detergent based membrane solubilisation methods using the tissue and supernatant fractions of isolated ghost membranes are shown to offer effective haemoglobin removal as well as diverse recovery including erythrocyte membrane proteins of high and low abundance. The methods described in this manuscript propose a medium to high throughput framework for membrane proteome profiling by LC-MS of potential applicability to larger clinical cohorts in a variety of disease contexts.

Proteomics to study DNA-bound and chromatin-associated gene regulatory complexes

PubMed Central

Wierer, Michael; Mann, Matthias

2016-01-01

High-resolution mass spectrometry (MS)-based proteomics is a powerful method for the identification of soluble protein complexes and large-scale affinity purification screens can decode entire protein interaction networks. In contrast, protein complexes residing on chromatin have been much more challenging, because they are difficult to purify and often of very low abundance. However, this is changing due to recent methodological and technological advances in proteomics. Proteins interacting with chromatin marks can directly be identified by pulldowns with synthesized histone tails containing posttranslational modifications (PTMs). Similarly, pulldowns with DNA baits harbouring single nucleotide polymorphisms or DNA modifications reveal the impact of those DNA alterations on the recruitment of transcription factors. Accurate quantitation – either isotope-based or label free – unambiguously pinpoints proteins that are significantly enriched over control pulldowns. In addition, protocols that combine classical chromatin immunoprecipitation (ChIP) methods with mass spectrometry (ChIP-MS) target gene regulatory complexes in their in-vivo context. Similar to classical ChIP, cells are crosslinked with formaldehyde and chromatin sheared by sonication or nuclease digested. ChIP-MS baits can be proteins in tagged or endogenous form, histone PTMs, or lncRNAs. Locus-specific ChIP-MS methods would allow direct purification of a single genomic locus and the proteins associated with it. There, loci can be targeted either by artificial DNA-binding sites and corresponding binding proteins or via proteins with sequence specificity such as TAL or nuclease deficient Cas9 in combination with a specific guide RNA. We predict that advances in MS technology will soon make such approaches generally applicable tools in epigenetics. PMID:27402878

Proteomic platform for the identification of proteins in olive (Olea europaea) pulp.

PubMed

Capriotti, Anna Laura; Cavaliere, Chiara; Foglia, Patrizia; Piovesana, Susy; Samperi, Roberto; Stampachiacchiere, Serena; Laganà, Aldo

2013-10-24

The nutritional and cancer-protective properties of the oil extracted mechanically from the ripe fruits of Olea europaea trees are attracting constantly more attention worldwide. The preparation of high-quality protein samples from plant tissues for proteomic analysis poses many challenging problems. In this study we employed a proteomic platform based on two different extraction methods, SDS and CHAPS based protocols, followed by two precipitation protocols, TCA/acetone and MeOH precipitation, in order to increase the final number of identified proteins. The use of advanced MS techniques in combination with the Swissprot and NCBI Viridiplantae databases and TAIR10 Arabidopsis database allowed us to identify 1265 proteins, of which 22 belong to O. europaea. The application of this proteomic platform for protein extraction and identification will be useful also for other proteomic studies on recalcitrant plant/fruit tissues. Copyright © 2013. Published by Elsevier B.V.

Proteomics of Plant Pathogenic Fungi

PubMed Central

González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V.

2010-01-01

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection. PMID:20589070

Proteomics of plant pathogenic fungi.

PubMed

González-Fernández, Raquel; Prats, Elena; Jorrín-Novo, Jesús V

2010-01-01

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

Next-generation sequencing-based transcriptomic and proteomic analysis of the common reed, Phragmites australis (Poaceae), reveals genes involved in invasiveness and rhizome specificity.

PubMed

He, Ruifeng; Kim, Min-Jeong; Nelson, William; Balbuena, Tiago S; Kim, Ryan; Kramer, Robin; Crow, John A; May, Greg D; Thelen, Jay J; Soderlund, Carol A; Gang, David R

2012-02-01

The common reed (Phragmites australis), one of the most widely distributed of all angiosperms, uses its rhizomes (underground stems) to invade new territory, making it one of the most successful weedy species worldwide. Characterization of the rhizome transcriptome and proteome is needed to identify candidate genes and proteins involved in rhizome growth, development, metabolism, and invasiveness. We employed next-generation sequencing technologies including 454 and Illumina platforms to characterize the reed rhizome transcriptome and used quantitative proteomics techniques to identify the rhizome proteome. Combining 336514 Roche 454 Titanium reads and 103350802 Illumina paired-end reads in a de novo hybrid assembly yielded 124450 unique transcripts with an average length of 549 bp, of which 54317 were annotated. Rhizome-specific and differentially expressed transcripts were identified between rhizome apical tips (apical meristematic region) and rhizome elongation zones. A total of 1280 nonredundant proteins were identified and quantified using GeLC-MS/MS based label-free proteomics, where 174 and 77 proteins were preferentially expressed in the rhizome elongation zone and apical tip tissues, respectively. Genes involved in allelopathy and in controlling development and potentially invasiveness were identified. In addition to being a valuable sequence and protein data resource for studying plant rhizome species, our results provide useful insights into identifying specific genes and proteins with potential roles in rhizome differentiation, development, and function.

A proteomic analysis of the chromoplasts isolated from sweet orange fruits [Citrus sinensis (L.) Osbeck

PubMed Central

Zeng, Yunliu; Pan, Zhiyong; Ding, Yuduan; Zhu, Andan; Cao, Hongbo; Xu, Qiang; Deng, Xiuxin

2011-01-01

Here, a comprehensive proteomic analysis of the chromoplasts purified from sweet orange using Nycodenz density gradient centrifugation is reported. A GeLC-MS/MS shotgun approach was used to identify the proteins of pooled chromoplast samples. A total of 493 proteins were identified from purified chromoplasts, of which 418 are putative plastid proteins based on in silico sequence homology and functional analyses. Based on the predicted functions of these identified plastid proteins, a large proportion (∼60%) of the chromoplast proteome of sweet orange is constituted by proteins involved in carbohydrate metabolism, amino acid/protein synthesis, and secondary metabolism. Of note, HDS (hydroxymethylbutenyl 4-diphosphate synthase), PAP (plastid-lipid-associated protein), and psHSPs (plastid small heat shock proteins) involved in the synthesis or storage of carotenoid and stress response are among the most abundant proteins identified. A comparison of chromoplast proteomes between sweet orange and tomato suggested a high level of conservation in a broad range of metabolic pathways. However, the citrus chromoplast was characterized by more extensive carotenoid synthesis, extensive amino acid synthesis without nitrogen assimilation, and evidence for lipid metabolism concerning jasmonic acid synthesis. In conclusion, this study provides an insight into the major metabolic pathways as well as some unique characteristics of the sweet orange chromoplasts at the whole proteome level. PMID:21841170

Benzoate-mediated changes on expression profile of soluble proteins in Serratia sp. DS001.

PubMed

Pandeeti, E V P; Chinnaboina, M R; Siddavattam, D

2009-05-01

To assess differences in protein expression profile associated with shift in carbon source from succinate to benzoate in Serratia sp. DS001 using a proteomics approach. A basic proteome map was generated for the soluble proteins extracted from Serratia sp. DS001 grown in succinate and benzoate. The differently and differentially expressed proteins were identified using ImageMaster 2D Platinum software (GE Healthcare). The identity of the proteins was determined by employing MS or MS/MS. Important enzymes such as Catechol 1,2 dioxygenase and transcriptional regulators that belong to the LysR superfamily were identified. Nearly 70 proteins were found to be differentially expressed when benzoate was used as carbon source. Based on the protein identity and degradation products generated from benzoate it is found that ortho pathway is operational in Serratia sp. DS001. Expression profile of the soluble proteins associated with shift in carbon source was mapped. The study also elucidates degradation pathway of benzoate in Serratia sp. DS001 by correlating the proteomics data with the catabolites of benzoate.

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

PubMed Central

Xu, Huajun; Zheng, Xiaojiao; Jia, Wei; Yin, Shankai

2015-01-01

Abstract Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA. PMID:26448002

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.

PubMed

Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei

2012-12-01

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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

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

2011-12-01

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

"Polymeromics": Mass spectrometry based strategies in polymer science toward complete sequencing approaches: a review.

PubMed

Altuntaş, Esra; Schubert, Ulrich S

2014-01-15

Mass spectrometry (MS) is the most versatile and comprehensive method in "OMICS" sciences (i.e. in proteomics, genomics, metabolomics and lipidomics). The applications of MS and tandem MS (MS/MS or MS(n)) provide sequence information of the full complement of biological samples in order to understand the importance of the sequences on their precise and specific functions. Nowadays, the control of polymer sequences and their accurate characterization is one of the significant challenges of current polymer science. Therefore, a similar approach can be very beneficial for characterizing and understanding the complex structures of synthetic macromolecules. MS-based strategies allow a relatively precise examination of polymeric structures (e.g. their molar mass distributions, monomer units, side chain substituents, end-group functionalities, and copolymer compositions). Moreover, tandem MS offer accurate structural information from intricate macromolecular structures; however, it produces vast amount of data to interpret. In "OMICS" sciences, the software application to interpret the obtained data has developed satisfyingly (e.g. in proteomics), because it is not possible to handle the amount of data acquired via (tandem) MS studies on the biological samples manually. It can be expected that special software tools will improve the interpretation of (tandem) MS output from the investigations of synthetic polymers as well. Eventually, the MS/MS field will also open up for polymer scientists who are not MS-specialists. In this review, we dissect the overall framework of the MS and MS/MS analysis of synthetic polymers into its key components. We discuss the fundamentals of polymer analyses as well as recent advances in the areas of tandem mass spectrometry, software developments, and the overall future perspectives on the way to polymer sequencing, one of the last Holy Grail in polymer science. Copyright © 2013 Elsevier B.V. All rights reserved.

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

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.

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.

The PROTICdb database for 2-DE proteomics.

PubMed

Langella, Olivier; Zivy, Michel; Joets, Johann

2007-01-01

PROTICdb is a web-based database mainly designed to store and analyze plant proteome data obtained by 2D polyacrylamide gel electrophoresis (2D PAGE) and mass spectrometry (MS). The goals of PROTICdb are (1) to store, track, and query information related to proteomic experiments, i.e., from tissue sampling to protein identification and quantitative measurements; and (2) to integrate information from the user's own expertise and other sources into a knowledge base, used to support data interpretation (e.g., for the determination of allelic variants or products of posttranslational modifications). Data insertion into the relational database of PROTICdb is achieved either by uploading outputs from Mélanie, PDQuest, IM2d, ImageMaster(tm) 2D Platinum v5.0, Progenesis, Sequest, MS-Fit, and Mascot software, or by filling in web forms (experimental design and methods). 2D PAGE-annotated maps can be displayed, queried, and compared through the GelBrowser. Quantitative data can be easily exported in a tabulated format for statistical analyses with any third-party software. PROTICdb is based on the Oracle or the PostgreSQLDataBase Management System (DBMS) and is freely available upon request at http://cms.moulon.inra.fr/content/view/14/44/.

Intact stable isotope labeled plasma proteins from the SILAC-labeled HepG2 secretome.

PubMed

Mangrum, John B; Martin, Erika J; Brophy, Donald F; Hawkridge, Adam M

2015-09-01

The plasma proteome remains an attractive biospecimen for MS-based biomarker discovery studies. The success of these efforts relies on the continued development of quantitative MS-based proteomics approaches. Herein we report the use of the SILAC-labeled HepG2 secretome as a source for stable isotope labeled plasma proteins for quantitative LC-MS/MS measurements. The HepG2 liver cancer cell line secretes the major plasma proteins including serum albumin, apolipoproteins, protease inhibitors, coagulation factors, and transporters that represent some of the most abundant proteins in plasma. The SILAC-labeled HepG2 secretome was collected, spiked into human plasma (1:1 total protein), and then processed for LC-MS/MS analysis. A total of 62 and 56 plasma proteins were quantified (heavy:light (H/L) peptide pairs) from undepleted and depleted (serum albumin and IgG), respectively, with log2 H/L = ± 6. Major plasma proteins quantified included albumin, apolipoproteins (e.g., APOA1, APOA2, APOA4, APOB, APOC3, APOE, APOH, and APOM), protease inhibitors (e.g., A2M and SERPINs), coagulation factors (e.g., Factor V, Factor X, fibrinogen), and transport proteins (e.g., TTR). The average log2 H/L values for shared plasma proteins in both undepleted and depleted plasma samples were 0.43 and 0.44, respectively. This work further expands the SILAC strategy into MS-based biomarker discovery of clinical biospecimens. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enrichment of low molecular weight serum proteins using acetonitrile precipitation for mass spectrometry based proteomic analysis.

PubMed

Kay, Richard; Barton, Chris; Ratcliffe, Lucy; Matharoo-Ball, Balwir; Brown, Pamela; Roberts, Jane; Teale, Phil; Creaser, Colin

2008-10-01

A rapid acetonitrile (ACN)-based extraction method has been developed that reproducibly depletes high abundance and high molecular weight proteins from serum prior to mass spectrometric analysis. A nanoflow liquid chromatography/tandem mass spectrometry (nano-LC/MS/MS) multiple reaction monitoring (MRM) method for 57 high to medium abundance serum proteins was used to characterise the ACN-depleted fraction after tryptic digestion. Of the 57 targeted proteins 29 were detected and albumin, the most abundant protein in serum and plasma, was identified as the 20th most abundant protein in the extract. The combination of ACN depletion and one-dimensional nano-LC/MS/MS enabled the detection of the low abundance serum protein, insulin-like growth factor-I (IGF-I), which has a serum concentration in the region of 100 ng/mL. One-dimensional sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) analysis of the depleted serum showed no bands corresponding to proteins of molecular mass over 75 kDa after extraction, demonstrating the efficiency of the method for the depletion of high molecular weight proteins. Total protein analysis of the ACN extracts showed that approximately 99.6% of all protein is removed from the serum. The ACN-depletion strategy offers a viable alternative to the immunochemistry-based protein-depletion techniques commonly used for removing high abundance proteins from serum prior to MS-based proteomic analyses.

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).

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.

Difference gel electrophoresis (DiGE) identifies differentially expressed proteins in endoscopically-collected pancreatic fluid

PubMed Central

Paulo, Joao A.; Lee, Linda S.; Banks, Peter A.; Steen, Hanno; Conwell, Darwin L.

2012-01-01

Alterations in the pancreatic fluid proteome of individuals with chronic pancreatitis may offer insights into the development and progression of the disease. The endoscopic pancreas function test (ePFT) can safely collect large volumes of pancreatic fluid that are potentially amenable to proteomic analyses using difference gel electrophoresis (DiGE) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Pancreatic fluid was collected endoscopically using the ePFT method following secretin stimulation from three individuals with severe chronic pancreatitis and three chronic abdominal pain controls. The fluid was processed to minimize protein degradation and the protein profiles of each cohort, as determined by DiGE and LC-MS/MS, were compared. This DiGE-LC-MS/MS analysis reveals proteins that are differentially expressed in chronic pancreatitis compared to chronic abdominal pain controls. Proteins with higher abundance in pancreatic fluid from chronic pancreatitis individuals include: actin, desmoplankin, alpha-1-antitrypsin, SNC73, and serotransferrin. Those of relatively lower abundance include carboxypeptidase B, lipase, alpha-1-antichymotrypsin, alpha-2-macroglobulin, Arp2/3 subunit 4, glyceraldehyde-3-phosphate dehydrogenase, and protein disulfide isomerase. Endoscopic collection (ePFT) in tandem with DiGE-LC-MS/MS is a suitable approach for pancreatic fluid proteome analysis, however, further optimization of our protocol, as outlined herein, may improve proteome coverage in future analyses. PMID:21792986

Highly efficient peptide separations in proteomics. Part 2: bi- and multidimensional liquid-based separation techniques.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Tuytten, Robin; Verleysen, Katleen; Kas, Koen; François, Isabelle; Sandra, Pat

2009-04-15

Multidimensional liquid-based separation techniques are described for maximizing the resolution of the enormous number of peptides generated upon tryptic digestion of proteomes, and hence, reduce the spatial and temporal complexity of the sample to a level that allows successful mass spectrometric analysis. This review complements the previous contribution on unidimensional high performance liquid chromatography (HPLC). Both chromatography and electrophoresis will be discussed albeit with reversed-phase HPLC (RPLC) as the final separation dimension prior to MS analysis.

Overview of the HUPO Plasma Proteome Project: Results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database

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

Omenn, Gilbert; States, David J.; Adamski, Marcin

2005-08-13

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anticoagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics. med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasetsmore » had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.« less

Proteomic profile of serum of pregnant women carring a fetus with Down syndrome using nano uplc Q-tof ms/ms technology.

PubMed

López Uriarte, Graciela Arelí; Burciaga Flores, Carlos Horacio; Torres de la Cruz, Víctor Manuel; Medina Aguado, María Magdalena; Gómez Puente, Viviana Maricela; Romero Gutiérrez, Liliana Nayeli; Martínez de Villarreal, Laura Elia

2018-06-01

Prenatal diagnosis of Down syndrome (DS) is based on the calculated risk of maternal age, biochemical and ultrasonographic markers and recently by cfDNA. Differences in proteomic profiles may give an opportunity to find new biomarkers. Characterize proteome of serum of mothers carrying DS fetus. Blood serum samples of three groups of women were obtained, (a) 10 non-pregnant, (b) 10 pregnant with healthy fetus by ultrasound evaluation, (c) nine pregnant with DS fetus. Sample preparation was as follows: Albumin/IgG depletion, desalting, and trypsin digestion; the process was performed in nanoUPLC MS/MS. Data analysis was made with Mass Lynx 4.1 and ProteinLynx Global Server 3.0, peptide and protein recognition by MASCOT algorithm and UNIPROT-Swissprot database. Each group showed different protein profiles. Some proteins were shared between groups. Only sera from pregnant women showed proteins related to immune and clot pathways. Mothers with DS fetus had 42 specific proteins. We found a different serum protein profile in mothers carrying DS fetuses that do not reflect expression of genes in the extra chromosome. Further studies will be necessary to establish the role of these proteins in aneuploid fetus and analyze their possible use as potential biomarkers.

Mass Spectrometry Based Proteomic Analysis of Salivary Glands of Urban Malaria Vector Anopheles stephensi

PubMed Central

Vijay, Sonam

2014-01-01

Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE), ion trap liquid chromatography mass spectrometry (LC/MS/MS), and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes. PMID:25126571

Mass spectrometry based proteomic analysis of salivary glands of urban malaria vector Anopheles stephensi.

PubMed

Vijay, Sonam; Rawat, Manmeet; Sharma, Arun

2014-01-01

Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE), ion trap liquid chromatography mass spectrometry (LC/MS/MS), and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes.

P2P proteomics -- data sharing for enhanced protein identification

PubMed Central

2012-01-01

Background In order to tackle the important and challenging problem in proteomics of identifying known and new protein sequences using high-throughput methods, we propose a data-sharing platform that uses fully distributed P2P technologies to share specifications of peer-interaction protocols and service components. By using such a platform, information to be searched is no longer centralised in a few repositories but gathered from experiments in peer proteomics laboratories, which can subsequently be searched by fellow researchers. Methods The system distributively runs a data-sharing protocol specified in the Lightweight Communication Calculus underlying the system through which researchers interact via message passing. For this, researchers interact with the system through particular components that link to database querying systems based on BLAST and/or OMSSA and GUI-based visualisation environments. We have tested the proposed platform with data drawn from preexisting MS/MS data reservoirs from the 2006 ABRF (Association of Biomolecular Resource Facilities) test sample, which was extensively tested during the ABRF Proteomics Standards Research Group 2006 worldwide survey. In particular we have taken the data available from a subset of proteomics laboratories of Spain's National Institute for Proteomics, ProteoRed, a network for the coordination, integration and development of the Spanish proteomics facilities. Results and Discussion We performed queries against nine databases including seven ProteoRed proteomics laboratories, the NCBI Swiss-Prot database and the local database of the CSIC/UAB Proteomics Laboratory. A detailed analysis of the results indicated the presence of a protein that was supported by other NCBI matches and highly scored matches in several proteomics labs. The analysis clearly indicated that the protein was a relatively high concentrated contaminant that could be present in the ABRF sample. This fact is evident from the information that could be derived from the proposed P2P proteomics system, however it is not straightforward to arrive to the same conclusion by conventional means as it is difficult to discard organic contamination of samples. The actual presence of this contaminant was only stated after the ABRF study of all the identifications reported by the laboratories. PMID:22293032

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

Webb-Robertson, Bobbie-Jo M.; Wiberg, Holli K.; Matzke, Melissa M.

In this review, we apply selected imputation strategies to label-free liquid chromatography–mass spectrometry (LC–MS) proteomics datasets to evaluate the accuracy with respect to metrics of variance and classification. We evaluate several commonly used imputation approaches for individual merits and discuss the caveats of each approach with respect to the example LC–MS proteomics data. In general, local similarity-based approaches, such as the regularized expectation maximization and least-squares adaptive algorithms, yield the best overall performances with respect to metrics of accuracy and robustness. However, no single algorithm consistently outperforms the remaining approaches, and in some cases, performing classification without imputation sometimes yieldedmore » the most accurate classification. Thus, because of the complex mechanisms of missing data in proteomics, which also vary from peptide to protein, no individual method is a single solution for imputation. In summary, on the basis of the observations in this review, the goal for imputation in the field of computational proteomics should be to develop new approaches that work generically for this data type and new strategies to guide users in the selection of the best imputation for their dataset and analysis objectives.« less

Comparative proteomics analysis of placenta from pregnant women with intrahepatic cholestasis of pregnancy.

PubMed

Zhang, Ting; Guo, Yueshuai; Guo, Xuejiang; Zhou, Tao; Chen, Daozhen; Xiang, Jingying; Zhou, Zuomin

2013-01-01

Intrahepatic cholestasis of pregnancy (ICP) usually occurs in the third trimester and associated with increased risks in fetal complications. Currently, the exact cause of this disease is unknown. In this study we aim to investigate the potential proteins in placenta, which may participate in the molecular mechanisms of ICP-related fetal complications using iTRAQ-based proteomics approach. The iTRAQ analysis combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to separate differentially expressed placental proteins from 4 pregnant women with ICP and 4 healthy pregnant women. Bioinformatics analysis was used to find the relative processes that these differentially expressed proteins were involved in. Three apoptosis related proteins ERp29, PRDX6 and MPO that resulted from iTRAQ-based proteomics were further verified in placenta by Western blotting and immunohistochemistry. Placental apoptosis was also detected by TUNEL assay. Proteomics results showed there were 38 differentially expressed proteins from pregnant women with ICP and healthy pregnant women, 29 were upregulated and 9 were downregulated in placenta from pregnant women with ICP. Bioinformatics analysis showed most of the identified proteins was functionally related to specific cell processes, including apoptosis, oxidative stress, lipid metabolism. The expression levels of ERp29, PRDX6 and MPO were consistent with the proteomics data. The apoptosis index in placenta from ICP patients was significantly increased. This preliminary work provides a better understanding of the proteomic alterations of placenta from pregnant women with ICP and may provide us some new insights into the pathophysiology and potential novel treatment targets for ICP.

Strain-resolved microbial community proteomics reveals simultaneous aerobic and anaerobic function during gastrointestinal tract colonization of a preterm infant

DOE PAGES

Brooks, Brandon; Mueller, R. S.; Young, Jacque C.; ...

2015-07-01

While there has been growing interest in the gut microbiome in recent years, it remains unclear whether closely related species and strains have similar or distinct functional roles and if organisms capable of both aerobic and anaerobic growth do so simultaneously. To investigate these questions, we implemented a high-throughput mass spectrometry-based proteomics approach to identify proteins in fecal samples collected on days of life 13 21 from an infant born at 28 weeks gestation. No prior studies have coupled strain-resolved community metagenomics to proteomics for such a purpose. Sequences were manually curated to resolve the genomes of two strains ofmore » Citrobacter that were present during the later stage of colonization. Proteome extracts from fecal samples were processed via a nano-2D-LC-MS/MS and peptides were identified based on information predicted from the genome sequences for the dominant organisms, Serratia and the two Citrobacter strains. These organisms are facultative anaerobes, and proteomic information indicates the utilization of both aerobic and anaerobic metabolisms throughout the time series. This may indicate growth in distinct niches within the gastrointestinal tract. We uncovered differences in the physiology of coexisting Citrobacter strains, including differences in motility and chemotaxis functions. Additionally, for both Citrobacter strains we resolved a community-essential role in vitamin metabolism and a predominant role in propionate production. Finally, in this case study we detected differences between genome abundance and activity levels for the dominant populations. This underlines the value in layering proteomic information over genetic potential.« less

Top-down proteomic identification of Shiga toxin 2 subtypes from Shiga toxin-producing Escherichia coli by matrix-assisted laser desorption ionization-tandem time of flight mass spectrometry.

PubMed

Fagerquist, Clifton K; Zaragoza, William J; Sultan, Omar; Woo, Nathan; Quiñones, Beatriz; Cooley, Michael B; Mandrell, Robert E

2014-05-01

We have analyzed 26 Shiga toxin-producing Escherichia coli (STEC) strains for Shiga toxin 2 (Stx2) production using matrix-assisted laser desorption ionization (MALDI)-tandem time of flight (TOF-TOF) tandem mass spectrometry (MS/MS) and top-down proteomic analysis. STEC strains were induced to overexpress Stx2 by overnight culturing on solid agar supplemented with either ciprofloxacin or mitomycin C. Harvested cells were lysed by bead beating, and unfractionated bacterial cell lysates were ionized by MALDI. The A2 fragment of the A subunit and the mature B subunit of Stx2 were analyzed by MS/MS. Sequence-specific fragment ions were used to identify amino acid subtypes of Stx2 using top-down proteomic analysis using software developed in-house at the U.S. Department of Agriculture (USDA). Stx2 subtypes (a, c, d, f, and g) were identified on the basis of the mass of the A2 fragment and the B subunit as well as from their sequence-specific fragment ions by MS/MS (postsource decay). Top-down proteomic identification was in agreement with DNA sequencing of the full Stx2 operon (stx2) for all strains. Top-down results were also compared to a bioassay using a Vero-d2EGFP cell line. Our results suggest that top-down proteomic identification is a rapid, highly specific technique for distinguishing Stx2 subtypes.

Top-Down Proteomic Identification of Shiga Toxin 2 Subtypes from Shiga Toxin-Producing Escherichia coli by Matrix-Assisted Laser Desorption Ionization–Tandem Time of Flight Mass Spectrometry

PubMed Central

Zaragoza, William J.; Sultan, Omar; Woo, Nathan; Quiñones, Beatriz; Cooley, Michael B.; Mandrell, Robert E.

2014-01-01

We have analyzed 26 Shiga toxin-producing Escherichia coli (STEC) strains for Shiga toxin 2 (Stx2) production using matrix-assisted laser desorption ionization (MALDI)–tandem time of flight (TOF-TOF) tandem mass spectrometry (MS/MS) and top-down proteomic analysis. STEC strains were induced to overexpress Stx2 by overnight culturing on solid agar supplemented with either ciprofloxacin or mitomycin C. Harvested cells were lysed by bead beating, and unfractionated bacterial cell lysates were ionized by MALDI. The A2 fragment of the A subunit and the mature B subunit of Stx2 were analyzed by MS/MS. Sequence-specific fragment ions were used to identify amino acid subtypes of Stx2 using top-down proteomic analysis using software developed in-house at the U.S. Department of Agriculture (USDA). Stx2 subtypes (a, c, d, f, and g) were identified on the basis of the mass of the A2 fragment and the B subunit as well as from their sequence-specific fragment ions by MS/MS (postsource decay). Top-down proteomic identification was in agreement with DNA sequencing of the full Stx2 operon (stx2) for all strains. Top-down results were also compared to a bioassay using a Vero-d2EGFP cell line. Our results suggest that top-down proteomic identification is a rapid, highly specific technique for distinguishing Stx2 subtypes. PMID:24584253

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-08-01

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

neXtProt: organizing protein knowledge in the context of human proteome projects.

PubMed

Gaudet, Pascale; Argoud-Puy, Ghislaine; Cusin, Isabelle; Duek, Paula; Evalet, Olivier; Gateau, Alain; Gleizes, Anne; Pereira, Mario; Zahn-Zabal, Monique; Zwahlen, Catherine; Bairoch, Amos; Lane, Lydie

2013-01-04

About 5000 (25%) of the ~20400 human protein-coding genes currently lack any experimental evidence at the protein level. For many others, there is only little information relative to their abundance, distribution, subcellular localization, interactions, or cellular functions. The aim of the HUPO Human Proteome Project (HPP, www.thehpp.org ) is to collect this information for every human protein. HPP is based on three major pillars: mass spectrometry (MS), antibody/affinity capture reagents (Ab), and bioinformatics-driven knowledge base (KB). To meet this objective, the Chromosome-Centric Human Proteome Project (C-HPP) proposes to build this catalog chromosome-by-chromosome ( www.c-hpp.org ) by focusing primarily on proteins that currently lack MS evidence or Ab detection. These are termed "missing proteins" by the HPP consortium. The lack of observation of a protein can be due to various factors including incorrect and incomplete gene annotation, low or restricted expression, or instability. neXtProt ( www.nextprot.org ) is a new web-based knowledge platform specific for human proteins that aims to complement UniProtKB/Swiss-Prot ( www.uniprot.org ) with detailed information obtained from carefully selected high-throughput experiments on genomic variation, post-translational modifications, as well as protein expression in tissues and cells. This article describes how neXtProt contributes to prioritize C-HPP efforts and integrates C-HPP results with other research efforts to create a complete human proteome catalog.

Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

PubMed

Giménez, Estela; Gay, Marina; Vilaseca, Marta

2017-01-30

Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

Trauma-associated Human Neutrophil Alterations Revealed by Comparative Proteomics Profiling

PubMed Central

Zhou, Jian-Ying; Krovvidi, Ravi K.; Gao, Yuqian; Gao, Hong; Petritis, Brianne O.; De, Asit; Miller-Graziano, Carol; Bankey, Paul E.; Petyuk, Vladislav A.; Nicora, Carrie D.; Clauss, Therese R; Moore, Ronald J.; Shi, Tujin; Brown, Joseph N.; Kaushal, Amit; Xiao, Wenzhong; Davis, Ronald W.; Maier, Ronald V.; Tompkins, Ronald G.; Qian, Wei-Jun; Camp, David G.; Smith, Richard D.

2013-01-01

PURPOSE Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown. EXPERIMENTAL DESIGN We applied 2D-LC-MS/MS based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls. RESULTS A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways. CONCLUSIONS AND CLINICAL RELEVANCE Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs. PMID:23589343

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.

Three dimensional liquid chromatography coupling ion exchange chromatography/hydrophobic interaction chromatography/reverse phase chromatography for effective protein separation in top-down proteomics.

PubMed

Valeja, Santosh G; Xiu, Lichen; Gregorich, Zachery R; Guner, Huseyin; Jin, Song; Ge, Ying

2015-01-01

To address the complexity of the proteome in mass spectrometry (MS)-based top-down proteomics, multidimensional liquid chromatography (MDLC) strategies that can effectively separate proteins with high resolution and automation are highly desirable. Although various MDLC methods that can effectively separate peptides from protein digests exist, very few MDLC strategies, primarily consisting of 2DLC, are available for intact protein separation, which is insufficient to address the complexity of the proteome. We recently demonstrated that hydrophobic interaction chromatography (HIC) utilizing a MS-compatible salt can provide high resolution separation of intact proteins for top-down proteomics. Herein, we have developed a novel 3DLC strategy by coupling HIC with ion exchange chromatography (IEC) and reverse phase chromatography (RPC) for intact protein separation. We demonstrated that a 3D (IEC-HIC-RPC) approach greatly outperformed the conventional 2D IEC-RPC approach. For the same IEC fraction (out of 35 fractions) from a crude HEK 293 cell lysate, a total of 640 proteins were identified in the 3D approach (corresponding to 201 nonredundant proteins) as compared to 47 in the 2D approach, whereas simply prolonging the gradients in RPC in the 2D approach only led to minimal improvement in protein separation and identifications. Therefore, this novel 3DLC method has great potential for effective separation of intact proteins to achieve deep proteome coverage in top-down proteomics.

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.

Proteogenomics approaches for studying cancer biology and their potential in the identification of acute myeloid leukemia biomarkers.

PubMed

Hernandez-Valladares, Maria; Vaudel, Marc; Selheim, Frode; Berven, Frode; Bruserud, Øystein

2017-08-01

Mass spectrometry (MS)-based proteomics has become an indispensable tool for the characterization of the proteome and its post-translational modifications (PTM). In addition to standard protein sequence databases, proteogenomics strategies search the spectral data against the theoretical spectra obtained from customized protein sequence databases. Up to date, there are no published proteogenomics studies on acute myeloid leukemia (AML) samples. Areas covered: Proteogenomics involves the understanding of genomic and proteomic data. The intersection of both datatypes requires advanced bioinformatics skills. A standard proteogenomics workflow that could be used for the study of AML samples is described. The generation of customized protein sequence databases as well as bioinformatics tools and pipelines commonly used in proteogenomics are discussed in detail. Expert commentary: Drawing on evidence from recent cancer proteogenomics studies and taking into account the public availability of AML genomic data, the interpretation of present and future MS-based AML proteomic data using AML-specific protein sequence databases could discover new biological mechanisms and targets in AML. However, proteogenomics workflows including bioinformatics guidelines can be challenging for the wide AML research community. It is expected that further automation and simplification of the bioinformatics procedures might attract AML investigators to adopt the proteogenomics strategy.

Hair-bundle proteomes of avian and mammalian inner-ear utricles

PubMed Central

Wilmarth, Phillip A.; Krey, Jocelyn F.; Shin, Jung-Bum; Choi, Dongseok; David, Larry L.; Barr-Gillespie, Peter G.

2015-01-01

Examination of multiple proteomics datasets within or between species increases the reliability of protein identification. We report here proteomes of inner-ear hair bundles from three species (chick, mouse, and rat), which were collected on LTQ or LTQ Velos ion-trap mass spectrometers; the constituent proteins were quantified using MS2 intensities, which are the summed intensities of all peptide fragmentation spectra matched to a protein. The data are available via ProteomeXchange with identifiers PXD002410 (chick LTQ), PXD002414 (chick Velos), PXD002415 (mouse Velos), and PXD002416 (rat LTQ). The two chick bundle datasets compared favourably to a third, already-described chick bundle dataset, which was quantified using MS1 peak intensities, the summed intensities of peptides identified by high-resolution mass spectrometry (PXD000104; updated analysis in PXD002445). The mouse bundle dataset described here was comparable to a different mouse bundle dataset quantified using MS1 intensities (PXD002167). These six datasets will be useful for identifying the core proteome of vestibular hair bundles. PMID:26645194

Label-free quantitative proteomic analysis of human plasma-derived microvesicles to find protein signatures of abdominal aortic aneurysms.

PubMed

Martinez-Pinna, Roxana; Gonzalez de Peredo, Anne; Monsarrat, Bernard; Burlet-Schiltz, Odile; Martin-Ventura, Jose Luis

2014-08-01

To find potential biomarkers of abdominal aortic aneurysms (AAA), we performed a differential proteomic study based on human plasma-derived microvesicles. Exosomes and microparticles isolated from plasma of AAA patients and control subjects (n = 10 each group) were analyzed by a label-free quantitative MS-based strategy. Homemade and publicly available software packages have been used for MS data analysis. The application of two kinds of bioinformatic tools allowed us to find differential protein profiles from AAA patients. Some of these proteins found by the two analysis methods belong to main pathological mechanisms of AAA such as oxidative stress, immune-inflammation, and thrombosis. Data analysis from label-free MS-based experiments requires the use of sophisticated bioinformatic approaches to perform quantitative studies from complex protein mixtures. The application of two of these bioinformatic tools provided us a preliminary list of differential proteins found in plasma-derived microvesicles not previously associated to AAA, which could help us to understand the pathological mechanisms related to this disease. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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 the false positives and the false discovery rate of the datasets. The results presented here prove that a post-test filter applying a reasonable effect size and signal level thresholds helps to increase the reproducibility of statistical results in comparative proteomic analysis. Furthermore, the implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of results obtained among independent laboratories and MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Identification of IGFBP2 and IGFBP3 As Compensatory Biomarkers for CA19-9 in Early-Stage Pancreatic Cancer Using a Combination of Antibody-Based and LC-MS/MS-Based Proteomics

PubMed Central

Yoneyama, Toshihiro; Ohtsuki, Sumio; Honda, Kazufumi; Kobayashi, Makoto; Iwasaki, Motoki; Uchida, Yasuo; Okusaka, Takuji; Nakamori, Shoji; Shimahara, Masashi; Ueno, Takaaki; Tsuchida, Akihiko; Sata, Naohiro; Ioka, Tatsuya; Yasunami, Yohichi; Kosuge, Tomoo; Kaneda, Takashi; Kato, Takao; Yagihara, Kazuhiro; Fujita, Shigeyuki; Huang, Wilber; Yamada, Tesshi; Tachikawa, Masanori; Terasaki, Tetsuya

2016-01-01

Pancreatic cancer is one of the most lethal tumors, and reliable detection of early-stage pancreatic cancer and risk diseases for pancreatic cancer is essential to improve the prognosis. As 260 genes were previously reported to be upregulated in invasive ductal adenocarcinoma of pancreas (IDACP) cells, quantification of the corresponding proteins in plasma might be useful for IDACP diagnosis. Therefore, the purpose of the present study was to identify plasma biomarkers for early detection of IDACP by using two proteomics strategies: antibody-based proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. Among the 260 genes, we focused on 130 encoded proteins with known function for which antibodies were available. Twenty-three proteins showed values of the area under the curve (AUC) of more than 0.8 in receiver operating characteristic (ROC) analysis of reverse-phase protein array (RPPA) data of IDACP patients compared with healthy controls, and these proteins were selected as biomarker candidates. We then used our high-throughput selected reaction monitoring or multiple reaction monitoring (SRM/MRM) methodology, together with an automated sample preparation system, micro LC and auto analysis system, to quantify these candidate proteins in plasma from healthy controls and IDACP patients on a large scale. The results revealed that insulin-like growth factor-binding protein (IGFBP)2 and IGFBP3 have the ability to discriminate IDACP patients at an early stage from healthy controls, and IGFBP2 appeared to be increased in risk diseases of pancreatic malignancy, such as intraductal papillary mucinous neoplasms (IPMNs). Furthermore, diagnosis of IDACP using the combination of carbohydrate antigen 19–9 (CA19-9), IGFBP2 and IGFBP3 is significantly more effective than CA19-9 alone. This suggests that IGFBP2 and IGFBP3 may serve as compensatory biomarkers for CA19-9. Early diagnosis with this marker combination may improve the prognosis of IDACP patients. PMID:27579675

Highly efficient peptide separations in proteomics Part 1. Unidimensional high performance liquid chromatography.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Verleysen, Katleen; Kas, Koen; Sandra, Pat

2008-04-15

Sample complexity and dynamic range constitute enormous challenges in proteome analysis. The back-end technology in typical proteomics platforms, namely mass spectrometry (MS), can only tolerate a certain complexity, has a limited dynamic range per spectrum and is very sensitive towards ion suppression. Therefore, component overlap has to be minimized for successful mass spectrometric analysis and subsequent protein identification and quantification. The present review describes the advances that have been made in liquid-based separation techniques with focus on the recent developments to boost the resolving power. The review is divided in two parts; the first part deals with unidimensional liquid chromatography and the second part with bi- and multidimensional liquid-based separation techniques. Part 1 mainly focuses on reversed-phase HPLC due to the fact that it is and will, in the near future, remain the technique of choice to be hyphenated with MS. The impact of increasing the column length, decreasing the particle diameter, replacing the traditional packed beds by monolithics, amongst others, is described. The review is complemented with data obtained in the laboratories of the authors.

Elucidating structural and molecular mechanisms of β-arrestin-biased agonism at GPCRs via MS-based proteomics.

PubMed

Xiao, Kunhong; Sun, Jinpeng

2018-01-01

The discovery of β-arrestin-dependent GPCR signaling has led to an exciting new field in GPCR pharmacology: to develop "biased agonists" that can selectively target a specific downstream signaling pathway that elicits beneficial therapeutic effects without activating other pathways that elicit negative side effects. This new trend in GPCR drug discovery requires us to understand the structural and molecular mechanisms of β-arrestin-biased agonism, which largely remain unclear. We have used cutting-edge mass spectrometry (MS)-based proteomics, combined with systems, chemical and structural biology to study protein function, macromolecular interaction, protein expression and posttranslational modifications in the β-arrestin-dependent GPCR signaling. These high-throughput proteomic studies have provided a systems view of β-arrestin-biased agonism from several perspectives: distinct receptor phosphorylation barcode, multiple receptor conformations, distinct β-arrestin conformations, and ligand-specific signaling. The information obtained from these studies offers new insights into the molecular basis of GPCR regulation by β-arrestin and provides a potential platform for developing novel therapeutic interventions through GPCRs. Copyright © 2017 Elsevier Inc. All rights reserved.

Proteomics-based compositional analysis of complex cellulase-hemicellulase mixtures.

PubMed

Chundawat, Shishir P S; Lipton, Mary S; Purvine, Samuel O; Uppugundla, Nirmal; Gao, Dahai; Balan, Venkatesh; Dale, Bruce E

2011-10-07

Efficient deconstruction of cellulosic biomass to fermentable sugars for fuel and chemical production is accomplished by a complex mixture of cellulases, hemicellulases, and accessory enzymes (e.g., >50 extracellular proteins). Cellulolytic enzyme mixtures, produced industrially mostly using fungi like Trichoderma reesei, are poorly characterized in terms of their protein composition and its correlation to hydrolytic activity on cellulosic biomass. The secretomes of commercial glycosyl hydrolase-producing microbes was explored using a proteomics approach with high-throughput quantification using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Here, we show that proteomics-based spectral counting approach is a reasonably accurate and rapid analytical technique that can be used to determine protein composition of complex glycosyl hydrolase mixtures that also correlates with the specific activity of individual enzymes present within the mixture. For example, a strong linear correlation was seen between Avicelase activity and total cellobiohydrolase content. Reliable, quantitative and cheaper analytical methods that provide insight into the cellulosic biomass degrading fungal and bacterial secretomes would lead to further improvements toward commercialization of plant biomass-derived fuels and chemicals.

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

PubMed

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

Detecting trace components in liquid chromatography/mass spectrometry data sets with two-dimensional wavelets

NASA Astrophysics Data System (ADS)

Compton, Duane C.; Snapp, Robert R.

2007-09-01

TWiGS (two-dimensional wavelet transform with generalized cross validation and soft thresholding) is a novel algorithm for denoising liquid chromatography-mass spectrometry (LC-MS) data for use in "shot-gun" proteomics. Proteomics, the study of all proteins in an organism, is an emerging field that has already proven successful for drug and disease discovery in humans. There are a number of constraints that limit the effectiveness of liquid chromatography-mass spectrometry (LC-MS) for shot-gun proteomics, where the chemical signals are typically weak, and data sets are computationally large. Most algorithms suffer greatly from a researcher driven bias, making the results irreproducible and unusable by other laboratories. We thus introduce a new algorithm, TWiGS, that removes electrical (additive white) and chemical noise from LC-MS data sets. TWiGS is developed to be a true two-dimensional algorithm, which operates in the time-frequency domain, and minimizes the amount of researcher bias. It is based on the traditional discrete wavelet transform (DWT), which allows for fast and reproducible analysis. The separable two-dimensional DWT decomposition is paired with generalized cross validation and soft thresholding. The Haar, Coiflet-6, Daubechie-4 and the number of decomposition levels are determined based on observed experimental results. Using a synthetic LC-MS data model, TWiGS accurately retains key characteristics of the peaks in both the time and m/z domain, and can detect peaks from noise of the same intensity. TWiGS is applied to angiotensin I and II samples run on a LC-ESI-TOF-MS (liquid-chromatography-electrospray-ionization) to demonstrate its utility for the detection of low-lying peaks obscured by noise.

A Framework for Intelligent Data Acquisition and Real-Time Database Searching for Shotgun Proteomics*

PubMed Central

Graumann, Johannes; Scheltema, Richard A.; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-01-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides “on-the-fly” within 30 ms, well within the time constraints of a shotgun fragmentation “topN” method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available. PMID:22171319

Proteomics of rice and Cochliobolus miyabeanus fungal interaction: insight into proteins at intracellular and extracellular spaces.

PubMed

Kim, Jin Yeong; Wu, Jingni; Kwon, Soon Jae; Oh, Haram; Lee, So Eui; Kim, Sang Gon; Wang, Yiming; Agrawal, Ganesh Kumar; Rakwal, Randeep; Kang, Kyu Young; Ahn, Il-Pyung; Kim, Beom-Gi; Kim, Sun Tae

2014-10-01

Necrotrophic fungal pathogen Cochliobolus miyabeanus causes brown spot disease in rice leaves upon infection, resulting in critical rice yield loss. To better understand the rice-C. miyabeanus interaction, we employed proteomic approaches to establish differential proteomes of total and secreted proteins from the inoculated leaves. The 2DE approach after PEG-fractionation of total proteins coupled with MS (MALDI-TOF/TOF and nESI-LC-MS/MS) analyses led to identification of 49 unique proteins out of 63 differential spots. SDS-PAGE in combination with nESI-LC-MS/MS shotgun approach was applied to identify secreted proteins in the leaf apoplast upon infection and resulted in cataloging of 501 unique proteins, of which 470 and 31 proteins were secreted from rice and C. miyabeanus, respectively. Proteins mapped onto metabolic pathways implied their reprogramming upon infection. The enzymes involved in Calvin cycle and glycolysis decreased in their protein abundance, whereas enzymes in the TCA cycle, amino acids, and ethylene biosynthesis increased. Differential proteomes also generated distribution of identified proteins in the intracellular and extracellular spaces, providing a better insight into defense responses of proteins in rice against C. miyabeanus. Established proteome of the rice-C. miyabeanus interaction serves not only as a good resource for the scientific community but also highlights its significance from biological aspects. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

Proteomic analysis of sweet algerian apricot kernels (Prunus armeniaca L.) by combinatorial peptide ligand libraries and LC-MS/MS.

PubMed

Ghorab, Hamida; Lammi, Carmen; Arnoldi, Anna; Kabouche, Zahia; Aiello, Gilda

2018-01-15

An investigation on the proteome of the sweet kernel of apricot, based on equalisation with combinatorial peptide ligand libraries (CPLLs), SDS-PAGE, nLC-ESI-MS/MS, and database search, permitted identifying 175 proteins. Gene ontology analysis indicated that their main molecular functions are in nucleotide binding (20.9%), hydrolase activities (10.6%), kinase activities (7%), and catalytic activity (5.6%). A protein-protein association network analysis using STRING software permitted to build an interactomic map of all detected proteins, characterised by 34 interactions. In order to forecast the potential health benefits deriving from the consumption of these proteins, the two most abundant, i.e. Prunin 1 and 2, were enzymatically digested in silico predicting 10 and 14 peptides, respectively. Searching their sequences in the database BIOPEP, it was possible to suggest a variety of bioactivities, including dipeptidyl peptidase-IV (DPP-IV) and angiotensin converting enzyme I (ACE) inhibition, glucose uptake stimulation and antioxidant properties. Copyright © 2017 Elsevier Ltd. All rights reserved.

A proteomics assay to detect eight CBRN-relevant toxins in food.

PubMed

Gilquin, Benoit; Jaquinod, Michel; Louwagie, Mathilde; Kieffer-Jaquinod, Sylvie; Kraut, Alexandra; Ferro, Myriam; Becher, François; Brun, Virginie

2017-01-01

A proteomics assay was set up to analyze food substrates for eight toxins of the CBRN (chemical, biological, radiological and nuclear) threat, namely ricin, Clostridium perfringens epsilon toxin (ETX), Staphylococcus aureus enterotoxins (SEA, SEB and SED), shigatoxins from Shigella dysenteriae and entero-hemorragic Escherichia coli strains (STX1 and STX2) and Campylobacter jejuni cytolethal distending toxin (CDT). The assay developed was based on an antibody-free sample preparation followed by bottom-up LC-MS/MS analysis operated in targeted mode. Highly specific detection and absolute quantification were obtained using isotopically labeled proteins (PSAQ standards) spiked into the food matrix. The sensitivity of the assay for the eight toxins was lower than the oral LD50 which would likely be used in a criminal contamination of food supply. This assay should be useful in monitoring biological threats. In the public-health domain, it opens the way for multiplex investigation of food-borne toxins using targeted LC-MS/MS. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomics data repositories: Providing a safe haven for your data and acting as a springboard for further research

PubMed Central

Vizcaíno, Juan Antonio; Foster, Joseph M.; Martens, Lennart

2010-01-01

Despite the fact that data deposition is not a generalised fact yet in the field of proteomics, several mass spectrometry (MS) based proteomics repositories are publicly available for the scientific community. The main existing resources are: the Global Proteome Machine Database (GPMDB), PeptideAtlas, the PRoteomics IDEntifications database (PRIDE), Tranche, and NCBI Peptidome. In this review the capabilities of each of these will be described, paying special attention to four key properties: data types stored, applicable data submission strategies, supported formats, and available data mining and visualization tools. Additionally, the data contents from model organisms will be enumerated for each resource. There are other valuable smaller and/or more specialized repositories but they will not be covered in this review. Finally, the concept behind the ProteomeXchange consortium, a collaborative effort among the main resources in the field, will be introduced. PMID:20615486

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

Denef, Vincent; Shah, Manesh B; Verberkmoes, Nathan C

The recent surge in microbial genomic sequencing, combined with the development of high-throughput liquid chromatography-mass-spectrometry-based (LC/LC-MS/MS) proteomics, has raised the question of the extent to which genomic information of one strain or environmental sample can be used to profile proteomes of related strains or samples. Even with decreasing sequencing costs, it remains impractical to obtain genomic sequence for every strain or sample analyzed. Here, we evaluate how shotgun proteomics is affected by amino acid divergence between the sample and the genomic database using a probability-based model and a random mutation simulation model constrained by experimental data. To assess the effectsmore » of nonrandom distribution of mutations, we also evaluated identification levels using in silico peptide data from sequenced isolates with average amino acid identities (AAI) varying between 76 and 98%. We compared the predictions to experimental protein identification levels for a sample that was evaluated using a database that included genomic information for the dominant organism and for a closely related variant (95% AAI). The range of models set the boundaries at which half of the proteins in a proteomic experiment can be identified to be 77-92% AAI between orthologs in the sample and database. Consistent with this prediction, experimental data indicated loss of half the identifiable proteins at 90% AAI. Additional analysis indicated a 6.4% reduction of the initial protein coverage per 1% amino acid divergence and total identification loss at 86% AAI. Consequently, shotgun proteomics is capable of cross-strain identifications but avoids most crossspecies false positives.« less

Proteomic Cinderella: Customized analysis of bulky MS/MS data in one night.

PubMed

Kiseleva, Olga; Poverennaya, Ekaterina; Shargunov, Alexander; Lisitsa, Andrey

2018-02-01

Proteomic challenges, stirred up by the advent of high-throughput technologies, produce large amount of MS data. Nowadays, the routine manual search does not satisfy the "speed" of modern science any longer. In our work, the necessity of single-thread analysis of bulky data emerged during interpretation of HepG2 proteome profiling results for proteoforms searching. We compared the contribution of each of the eight search engines (X!Tandem, MS-GF[Formula: see text], MS Amanda, MyriMatch, Comet, Tide, Andromeda, and OMSSA) integrated in an open-source graphical user interface SearchGUI ( http://searchgui.googlecode.com ) into total result of proteoforms identification and optimized set of engines working simultaneously. We also compared the results of our search combination with Mascot results using protein kit UPS2, containing 48 human proteins. We selected combination of X!Tandem, MS-GF[Formula: see text] and OMMSA as the most time-efficient and productive combination of search. We added homemade java-script to automatize pipeline from file picking to report generation. These settings resulted in rise of the efficiency of our customized pipeline unobtainable by manual scouting: the analysis of 192 files searched against human proteome (42153 entries) downloaded from UniProt took 11[Formula: see text]h.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Proteomics Analysis of Bladder Cancer Exosomes*

PubMed Central

Welton, Joanne L.; Khanna, Sanjay; Giles, Peter J.; Brennan, Paul; Brewis, Ian A.; Staffurth, John; Mason, Malcolm D.; Clayton, Aled

2010-01-01

Exosomes are nanometer-sized vesicles, secreted by various cell types, present in biological fluids that are particularly rich in membrane proteins. Ex vivo analysis of exosomes may provide biomarker discovery platforms and form non-invasive tools for disease diagnosis and monitoring. These vesicles have never before been studied in the context of bladder cancer, a major malignancy of the urological tract. We present the first proteomics analysis of bladder cancer cell exosomes. Using ultracentrifugation on a sucrose cushion, exosomes were highly purified from cultured HT1376 bladder cancer cells and verified as low in contaminants by Western blotting and flow cytometry of exosome-coated beads. Solubilization in a buffer containing SDS and DTT was essential for achieving proteomics analysis using an LC-MALDI-TOF/TOF MS approach. We report 353 high quality identifications with 72 proteins not previously identified by other human exosome proteomics studies. Overrepresentation analysis to compare this data set with previous exosome proteomics studies (using the ExoCarta database) revealed that the proteome was consistent with that of various exosomes with particular overlap with exosomes of carcinoma origin. Interrogating the Gene Ontology database highlighted a strong association of this proteome with carcinoma of bladder and other sites. The data also highlighted how homology among human leukocyte antigen haplotypes may confound MASCOT designation of major histocompatability complex Class I nomenclature, requiring data from PCR-based human leukocyte antigen haplotyping to clarify anomalous identifications. Validation of 18 MS protein identifications (including basigin, galectin-3, trophoblast glycoprotein (5T4), and others) was performed by a combination of Western blotting, flotation on linear sucrose gradients, and flow cytometry, confirming their exosomal expression. Some were confirmed positive on urinary exosomes from a bladder cancer patient. In summary, the exosome proteomics data set presented is of unrivaled quality. The data will aid in the development of urine exosome-based clinical tools for monitoring disease and will inform follow-up studies into varied aspects of exosome manufacture and function. PMID:20224111

The Use of Ammonium Formate as a Mobile-Phase Modifier for LC-MS/MS Analysis of Tryptic Digests

PubMed Central

Johnson, Darryl; Boyes, Barry; Orlando, Ron

2013-01-01

A major challenge facing current mass spectrometry (MS)-based proteomics research is the large concentration range displayed in biological systems, which far exceeds the dynamic range of commonly available mass spectrometers. One approach to overcome this limitation is to improve online reversed-phase liquid chromatography (RP-LC) separation methodologies. LC mobile-phase modifiers are used to improve peak shape and increase sample load tolerance. Trifluoroacetic acid (TFA) is a commonly used mobile-phase modifier, as it produces peptide separations that are far superior to other additives. However, TFA leads to signal suppression when incorporated with electrospray ionization (ESI), and thus, other modifiers, such as formic acid (FA), are used for LC-MS applications. FA exhibits significantly less signal suppression, but is not as effective of a modifier as TFA. An alternative mobile-phase modifier is the combination of FA and ammonium formate (AF), which has been shown to improve peptide separations. The ESI-MS compatibility of this modifier has not been investigated, particularly for proteomic applications. This work compares the separation metrics of mobile phases modified with FA and FA/AF and explores the use of FA/AF for the LC-MS analysis of tryptic digests. Standard tryptic-digest peptides were used for comparative analysis of peak capacity and sample load tolerance. The compatibility of FA/AF in proteomic applications was examined with the analysis of soluble proteins from canine prostate carcinoma tissue. Overall, the use of FA/AF improved online RP-LC separations and led to significant increases in peptide identifications with improved protein sequence coverage. PMID:24294112

The use of ammonium formate as a mobile-phase modifier for LC-MS/MS analysis of tryptic digests.

PubMed

Johnson, Darryl; Boyes, Barry; Orlando, Ron

2013-12-01

A major challenge facing current mass spectrometry (MS)-based proteomics research is the large concentration range displayed in biological systems, which far exceeds the dynamic range of commonly available mass spectrometers. One approach to overcome this limitation is to improve online reversed-phase liquid chromatography (RP-LC) separation methodologies. LC mobile-phase modifiers are used to improve peak shape and increase sample load tolerance. Trifluoroacetic acid (TFA) is a commonly used mobile-phase modifier, as it produces peptide separations that are far superior to other additives. However, TFA leads to signal suppression when incorporated with electrospray ionization (ESI), and thus, other modifiers, such as formic acid (FA), are used for LC-MS applications. FA exhibits significantly less signal suppression, but is not as effective of a modifier as TFA. An alternative mobile-phase modifier is the combination of FA and ammonium formate (AF), which has been shown to improve peptide separations. The ESI-MS compatibility of this modifier has not been investigated, particularly for proteomic applications. This work compares the separation metrics of mobile phases modified with FA and FA/AF and explores the use of FA/AF for the LC-MS analysis of tryptic digests. Standard tryptic-digest peptides were used for comparative analysis of peak capacity and sample load tolerance. The compatibility of FA/AF in proteomic applications was examined with the analysis of soluble proteins from canine prostate carcinoma tissue. Overall, the use of FA/AF improved online RP-LC separations and led to significant increases in peptide identifications with improved protein sequence coverage.

Recent advances in mass spectrometry-based approaches for proteomics and biologics: Great contribution for developing therapeutic antibodies.

PubMed

Iwamoto, Noriko; Shimada, Takashi

2018-05-01

Since the turn of the century, mass spectrometry (MS) technologies have continued to improve dramatically, and advanced strategies that were impossible a decade ago are increasingly becoming available. The basic characteristics behind these advancements are MS resolution, quantitative accuracy, and information science for appropriate data processing. The spectral data from MS contain various types of information. The benefits of improving the resolution of MS data include accurate molecular structural-derived information, and as a result, we can obtain a refined biomolecular structure determination in a sequential and large-scale manner. Moreover, in MS data, not only accurate structural information but also the generated ion amount plays an important rule. This progress has greatly contributed a research field that captures biological events as a system by comprehensively tracing the various changes in biomolecular dynamics. The sequential changes of proteome expression in biological pathways are very essential, and the amounts of the changes often directly become the targets of drug discovery or indicators of clinical efficacy. To take this proteomic approach, it is necessary to separate the individual MS spectra derived from each biomolecule in the complexed biological samples. MS itself is not so infinite to perform the all peak separation, and we should consider improving the methods for sample processing and purification to make them suitable for injection into MS. The above-described characteristics can only be achieved using MS with any analytical instrument. Moreover, MS is expected to be applied and expand into many fields, not only basic life sciences but also forensic medicine, plant sciences, materials, and natural products. In this review, we focus on the technical fundamentals and future aspects of the strategies for accurate structural identification, structure-indicated quantitation, and on the challenges for pharmacokinetics of high-molecular-weight protein biopharmaceuticals. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Suberoylanilide hydroxamic acid treatment reveals crosstalks among proteome, ubiquitylome and acetylome in non-small cell lung cancer A549 cell line.

PubMed

Wu, Quan; Cheng, Zhongyi; Zhu, Jun; Xu, Weiqing; Peng, Xiaojun; Chen, Chuangbin; Li, Wenting; Wang, Fengsong; Cao, Lejie; Yi, Xingling; Wu, Zhiwei; Li, Jing; Fan, Pingsheng

2015-03-31

Suberoylanilide hydroxamic acid (SAHA) is a well-known histone deacetylase (HDAC) inhibitor and has been used as practical therapy for breast cancer and non-small cell lung cancer (NSCLC). It is previously demonstrated that SAHA treatment could extensively change the profile of acetylome and proteome in cancer cells. However, little is known about the impact of SAHA on other protein modifications and the crosstalks among different modifications and proteome, hindering the deep understanding of SAHA-mediated cancer therapy. In this work, by using SILAC technique, antibody-based affinity enrichment and high-resolution LC-MS/MS analysis, we investigated quantitative proteome, acetylome and ubiquitylome as well as crosstalks among the three datasets in A549 cells toward SAHA treatment. In total, 2968 proteins, 1099 acetylation sites and 1012 ubiquitination sites were quantified in response to SAHA treatment, respectively. With the aid of intensive bioinformatics, we revealed that the proteome and ubiquitylome were negatively related upon SAHA treatment. Moreover, the impact of SAHA on acetylome resulted in 258 up-regulated and 99 down-regulated acetylation sites at the threshold of 1.5 folds. Finally, we identified 55 common sites with both acetylation and ubiquitination, among which ubiquitination level in 43 sites (78.2%) was positive related to acetylation level.

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

PubMed

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

2018-03-20

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

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.

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

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/.

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.

Proteomic profile of the skin mucus of farmed gilthead seabream (Sparus aurata).

PubMed

Jurado, Juan; Fuentes-Almagro, Carlos A; Guardiola, Francisco Antonio; Cuesta, Alberto; Esteban, Ma Ángeles; Prieto-Álamo, María-José

2015-04-29

Fish skin mucus is the first line of defense against infections and it discriminates between pathogenic and commensal bacterial strains. Mucus composition varies amongst fish species and is influenced by endogenous and exogenous factors. This study describes the first proteome map of the epidermal mucus of farmed gilthead seabream (Sparus aurata). We used an integrative proteomic approach by combining a label-free procedure (LC-MS/MS) with the classical 2-DE-PMF-MS/MS methodology. The identified mucosal proteins were clustered in four groups according to their biological functions. Structural proteins (actins, keratins, tubulins, tropomyosin, cofilin-2 and filamin-A) and metabolic proteins (ribosomal proteins, proteasomal subunits, NACA, VCP, histones, NDPK, transferrin, glycolytic enzymes, ATP synthase components, beta-globin, Apo-A1 and FABP7) were the best represented functional categories. We also found proteins involved in stress response (WAP65, HSPC70, Cu,Zn-SOD, and PRDX1 and PRDX2) and signal transduction (PP2A 65kDa regulatory subunit, 14-3-3 protein beta/alpha, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, RhoGDI and PEBP1). Most of the identified proteins address different aspects of the innate immune response. Additionally, we analyzed bacterial peptides identified in the skin mucus of healthy S. aurata. These results revealed that genera belonging to the Lactobacillales order constitute the most abundant microorganism populations in this habitat. This work shows that proteomic methods can be used to characterize fish skin mucus. Using a coupled approach of LC-MS/MS and a 2-DE-PMF-MS/MS, we have obtained the first comprehensive view of the skin mucosal proteome of S. aurata, a fish species that is economically relevant for Mediterranean aquaculture. We identified a panel of proteins involved in a variety of biological functions, particularly in the innate immune response. Furthermore, to our knowledge, this is the first time a proteomic approach has been used to examine the microbiota in the skin mucus of a fish species. Overall, these results support further immunological researches in S. aurata and are relevant for the culture of this important fish species. Copyright © 2015 Elsevier B.V. All rights reserved.

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue.

PubMed

Röwer, Claudia; Vissers, Johannes P C; Koy, Cornelia; Kipping, Marc; Hecker, Michael; Reimer, Toralf; Gerber, Bernd; Thiesen, Hans-Jürgen; Glocker, Michael O

2009-12-01

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.

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.

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

PubMed Central

Han, Mee-Jung; Lee, Sang Yup

2006-01-01

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

Could transformation mechanisms of acetylase-harboring pMdT1 plasmid be evaluated through proteomic tools in Escherichia coli?

PubMed

Magalhães, Pedro; Pinto, Luís; Gonçalves, Alexandre; Araújo, José Eduardo; Santos, Hugo M; Capelo, José Luis; Saénz, Yolanda; de Toro, María; Torres, Carmen; Chambon, Christophe; Hébraud, Michel; Poeta, Patrícia; Igrejas, Gilberto

2016-08-11

Escherichia coli is a commensal microorganism of the gastrointestinal tract of animals and humans and it is an excellent model organism for the study of antibiotic resistance mechanisms. The resistance transmission and other characteristics of bacteria are based on different types of gene transfer occurring throughout the bacterial evolution. One of which is horizontal gene transfer that allows us to understand the ability of bacteria to acquire new genes. One dimensional and two dimensional electrophoresis (2-DE) techniques were performed in order to identify and characterize the proteome of two E. coli strains: Electromax DH10B, a transformation-ready strain; and TF-Se20, the Electromax DH10B that contains the aac(6')-Ib-cr4-harboring pMdT1 plasmid. After 2-DE and subsequent analysis by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS), it was possible to identify 76 distinct proteins on the TF-Se20 strain, whereas 71 had a known function. From Electromax DH10B strain, 72 different proteins were identified of which 71 were associated with a biological process. The protein of interest, aminoglycoside N-(6')-acetyltransferase type 1, was identified by MALDI-TOF MS. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) technique was performed to determine its sequence. Seventy six percent of the acetylase sequence was reconstructed only in the TF-Se20 strain, representing the single protein associated to antibiotic resistance. MALDI-TOF MS and LC-MS/MS approaches allowed us to determine the total proteome of both strains, as well as the acetylase sequence. Both of them enhance the ability to obtain more accurate information about the mechanisms of antimicrobial resistance. The pMdT1 plasmid brings a new perspective in understanding the metabolic processes that lead to antibiotic resistance. This study highlights the importance of proteomics and bioinformatics in understanding mechanisms of gene transfer and antibiotic resistance. These two approaches allow to compare the protein expression in different samples, as well as different biological processes related to each protein. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Progress in Top-Down Proteomics and the Analysis of Proteoforms

PubMed Central

Toby, Timothy K.; Fornelli, Luca; Kelleher, Neil L.

2017-01-01

From a molecular perspective, enactors of function in biology are intact proteins that can be variably modified at the genetic, transcriptional, or post-translational level. Over the past 30 years, mass spectrometry (MS) has become a powerful method for the analysis of proteomes. Prevailing bottom-up proteomics operates at the level of the peptide, leading to issues with protein inference, connectivity, and incomplete sequence/modification information. Top-down proteomics (TDP), alternatively, applies MS at the proteoform level to analyze intact proteins with diverse sources of intramolecular complexity preserved during analysis. Fortunately, advances in prefractionation workflows, MS instrumentation, and dissociation methods for whole-protein ions have helped TDP emerge as an accessible and potentially disruptive modality with increasingly translational value. In this review, we discuss technical and conceptual advances in TDP, along with the growing power of proteoform-resolved measurements in clinical and translational research. PMID:27306313

Virtual Labs in proteomics: new E-learning tools.

PubMed

Ray, Sandipan; Koshy, Nicole Rachel; Reddy, Panga Jaipal; Srivastava, Sanjeeva

2012-05-17

Web-based educational resources have gained enormous popularity recently and are increasingly becoming a part of modern educational systems. Virtual Labs are E-learning platforms where learners can gain the experience of practical experimentation without any direct physical involvement on real bench work. They use computerized simulations, models, videos, animations and other instructional technologies to create interactive content. Proteomics being one of the most rapidly growing fields of the biological sciences is now an important part of college and university curriculums. Consequently, many E-learning programs have started incorporating the theoretical and practical aspects of different proteomic techniques as an element of their course work in the form of Video Lectures and Virtual Labs. To this end, recently we have developed a Virtual Proteomics Lab at the Indian Institute of Technology Bombay, which demonstrates different proteomics techniques, including basic and advanced gel and MS-based protein separation and identification techniques, bioinformatics tools and molecular docking methods, and their applications in different biological samples. This Tutorial will discuss the prominent Virtual Labs featuring proteomics content, including the Virtual Proteomics Lab of IIT-Bombay, and E-resources available for proteomics study that are striving to make proteomic techniques and concepts available and accessible to the student and research community. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 14). Details can be found at: http://www.proteomicstutorials.org/. Copyright © 2012 Elsevier B.V. All rights reserved.

Top-down proteomics for the analysis of proteolytic events - Methods, applications and perspectives.

PubMed

Tholey, Andreas; Becker, Alexander

2017-11-01

Mass spectrometry based proteomics is an indispensable tool for almost all research areas relevant for the understanding of proteolytic processing, ranging from the identification of substrates, products and cleavage sites up to the analysis of structural features influencing protease activity. The majority of methods for these studies are based on bottom-up proteomics performing analysis at peptide level. As this approach is characterized by a number of pitfalls, e.g. loss of molecular information, there is an ongoing effort to establish top-down proteomics, performing separation and MS analysis both at intact protein level. We briefly introduce major approaches of bottom-up proteomics used in the field of protease research and highlight the shortcomings of these methods. We then discuss the present state-of-the-art of top-down proteomics. Together with the discussion of known challenges we show the potential of this approach and present a number of successful applications of top-down proteomics in protease research. This article is part of a Special Issue entitled: Proteolysis as a Regulatory Event in Pathophysiology edited by Stefan Rose-John. Copyright © 2017 Elsevier B.V. All rights reserved.

Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

PubMed

Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

2017-01-31

An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the metabolic disorders using high resolution mass spectrometry.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

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

PubMed Central

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

2015-01-01

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

Selection of Collision Energies in Proteomics Mass Spectrometry Experiments for Best Peptide Identification: Study of Mascot Score Energy Dependence Reveals Double Optimum.

PubMed

Révész, Ágnes; Rokob, Tibor András; Jeanne Dit Fouque, Dany; Turiák, Lilla; Memboeuf, Antony; Vékey, Károly; Drahos, László

2018-05-04

Collision energy is a key parameter determining the information content of beam-type collision induced dissociation tandem mass spectrometry (MS/MS) spectra, and its optimal choice largely affects successful peptide and protein identification in MS-based proteomics. For an MS/MS spectrum, quality of peptide match based on sequence database search, often characterized in terms of a single score, is a complex function of spectrum characteristics, and its collision energy dependence has remained largely unexplored. We carried out electrospray ionization-quadrupole-time of flight (ESI-Q-TOF)-MS/MS measurements on 2807 peptides from tryptic digests of HeLa and E. coli at 21 different collision energies. Agglomerative clustering of the resulting Mascot score versus energy curves revealed that only few of them display a single, well-defined maximum; rather, they feature either a broad plateau or two clear peaks. Nonlinear least-squares fitting of one or two Gaussian functions allowed the characteristic energies to be determined. We found that the double peaks and the plateaus in Mascot score can be associated with the different energy dependence of b- and y-type fragment ion intensities. We determined that the energies for optimum Mascot scores follow separate linear trends for the unimodal and bimodal cases with rather large residual variance even after differences in proton mobility are taken into account. This leaves room for experiment optimization and points to the possible influence of further factors beyond m/ z.

Complementarity of SOMAscan to LC-MS/MS and RNA-seq for quantitative profiling of human embryonic and mesenchymal stem cells.

PubMed

Billing, Anja M; Ben Hamidane, Hisham; Bhagwat, Aditya M; Cotton, Richard J; Dib, Shaima S; Kumar, Pankaj; Hayat, Shahina; Goswami, Neha; Suhre, Karsten; Rafii, Arash; Graumann, Johannes

2017-01-06

Dynamic range limitations are challenging to proteomics, particularly in clinical samples. Affinity proteomics partially overcomes this, yet suffers from dependence on reagent quality. SOMAscan, an aptamer-based platform for over 1000 proteins, avoids that issue using nucleic acid binders. Targets include low expressed proteins not easily accessible by other approaches. Here we report on the potential of SOMAscan for the study of differently sourced mesenchymal stem cells (MSC) in comparison to LC-MS/MS and RNA sequencing. While targeting fewer analytes, SOMAscan displays high precision and dynamic range coverage, allowing quantification of proteins not measured by the other platforms. Expression between cell types (ESC and MSC) was compared across techniques and uncovered the expected large differences. Sourcing was investigated by comparing subtypes: bone marrow-derived, standard in clinical studies, and ESC-derived MSC, thought to hold similar potential but devoid of inter-donor variability and proliferating faster in vitro. We confirmed subtype-equivalency, as well as vesicle and extracellular matrix related processes in MSC. In contrast, the proliferative nature of ESC was captured less by SOMAscan, where nuclear proteins are underrepresented. The complementary of SOMAscan allowed the comprehensive exploration of CD markers and signaling molecules, not readily accessible otherwise and offering unprecedented potential in subtype characterization. Mesenchymal stem cells (MSC) represent promising stem cell-derived therapeutics as indicated by their application in >500 clinical trials currently registered with the NIH. Tissue-derived MSC require invasive harvesting and imply donor-to-donor differences, to which embryonic stem cell (ESC)-derived MSC may provide an alternative and thus warrant thorough characterization. In continuation of our previous study where we compared in depth embryonic stem cells (ESC) and MSC from two sources (bone marrow and ESC-derived), we included the aptamer-based SOMAscan assay, complementing LC-MS/MS and RNA-seq data. Furthermore, SOMAscan, a targeted proteomics platform developed for analyzing clinical samples, has been benchmarked against established analytical platforms (LC-MS/MS and RNA-seq) using stem cell comparisons as a model. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Transcript and proteomic analysis of developing white lupin (Lupinus albus L.) roots

PubMed Central

Tian, Li; Peel, Gregory J; Lei, Zhentian; Aziz, Naveed; Dai, Xinbin; He, Ji; Watson, Bonnie; Zhao, Patrick X; Sumner, Lloyd W; Dixon, Richard A

2009-01-01

Background White lupin (Lupinus albus L.) roots efficiently take up and accumulate (heavy) metals, adapt to phosphate deficiency by forming cluster roots, and secrete antimicrobial prenylated isoflavones during development. Genomic and proteomic approaches were applied to identify candidate genes and proteins involved in antimicrobial defense and (heavy) metal uptake and translocation. Results A cDNA library was constructed from roots of white lupin seedlings. Eight thousand clones were randomly sequenced and assembled into 2,455 unigenes, which were annotated based on homologous matches in the NCBInr protein database. A reference map of developing white lupin root proteins was established through 2-D gel electrophoresis and peptide mass fingerprinting. High quality peptide mass spectra were obtained for 170 proteins. Microsomal membrane proteins were separated by 1-D gel electrophoresis and identified by LC-MS/MS. A total of 74 proteins were putatively identified by the peptide mass fingerprinting and the LC-MS/MS methods. Genomic and proteomic analyses identified candidate genes and proteins encoding metal binding and/or transport proteins, transcription factors, ABC transporters and phenylpropanoid biosynthetic enzymes. Conclusion The combined EST and protein datasets will facilitate the understanding of white lupin's response to biotic and abiotic stresses and its utility for phytoremediation. The root ESTs provided 82 perfect simple sequence repeat (SSR) markers with potential utility in breeding white lupin for enhanced agronomic traits. PMID:19123941

Post-translational modification of human heat shock factors and their functions: a recent update by proteomic approach.

PubMed

Xu, Yan-Ming; Huang, Dong-Yang; Chiu, Jen-Fu; Lau, Andy T Y

2012-05-04

Heat shock factors (HSFs) are vital for modulating stress and heat shock-related gene expression in cells. The activity of HSFs is controlled largely by post-translational modifications (PTMs). For example, basal phosphorylation of HSF1 on three serine sites suppresses the heat shock response, and hyperphosphorylation of HSF1 on several other serine and threonine sites by stress-activated kinases results in its activation, while acetylation on K80 inhibits its DNA-binding ability. Sumoylation of HSF2 on K82 regulates its DNA-binding ability, whereas sumoylation of HSF4B on K293 represses its transcriptional activity. With the advancement of proteomic technology, novel PTM sites on various HSFs have been identified with the use of tandem mass spectrometry (MS/MS), but the functions of many of these PTMs are still unclear. Yet, it should be noted that the discovery of these novel PTM sites provided the necessary evidence for the existence of these PTM marks in vivo. Followed by subsequent functional analysis, this would ultimately lead to a better understanding of these PTM marks. MS/MS-based proteomic approach is becoming a gold standard in PTM validation in the field of life science. Here, the recent literature of all known PTMs reported on human HSFs and the resulting functions will be discussed.

Two-dimensional electrophoretic profiling of normal human kidney glomerulus proteome and construction of an extensible markup language (XML)-based database.

PubMed

Yoshida, Yutaka; Miyazaki, Kenji; Kamiie, Junichi; Sato, Masao; Okuizumi, Seiji; Kenmochi, Akihisa; Kamijo, Ken'ichi; Nabetani, Takuji; Tsugita, Akira; Xu, Bo; Zhang, Ying; Yaoita, Eishin; Osawa, Tetsuo; Yamamoto, Tadashi

2005-03-01

To contribute to physiology and pathophysiology of the glomerulus of human kidney, we have launched a proteomic study of human glomerulus, and compiled a profile of proteins expressed in the glomerulus of normal human kidney by two-dimensional gel electrophoresis (2-DE) and identification with matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and/or liquid chromatography-tandem mass spectrometry (LC-MS/MS). Kidney cortices with normal appearance were obtained from patients under surgical nephrectomy due to renal tumor, and glomeruli were highly purified by a standard sieving method followed by picking-up under a phase-contrast microscope. The glomerular proteins were separated by 2-DE with 24 cm immobilized pH gradient strips in the 3-10 range in the first dimension and 26 x 20 cm sodium dodecyl sulfate polyacrylamide electrophoresis gels of 12.5% in the second dimension. Gels were silver-stained, and valid spots were processed for identification through an integrated robotic system that consisted of a spot picker, an in-gel digester, and a MALDI-TOF MS and / or a LC-MS/MS. From 2-DE gel images of glomeruli of four subjects with no apparent pathologic manifestations, a synthetic gel image of normal glomerular proteins was created. The synthetic gel image contained 1713 valid spots, of which 1559 spots were commonly observed in the respective 2-DE gels. Among the 1559 spots, 347 protein spots, representing 212 proteins, have so far been identified, and used for the construction of an extensible markup language (XML)-based database. The database is deposited on a web site (http://www.sw.nec.co.jp/bio/rd/hgldb/index.html) in a form accessible to researchers to contribute to proteomic studies of human glomerulus in health and disease.

Simultaneous Detection of Human C-Terminal p53 Isoforms by Single Template Molecularly Imprinted Polymers (MIPs) Coupled with Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)-Based Targeted Proteomics.

PubMed

Jiang, Wenting; Liu, Liang; Chen, Yun

2018-03-06

Abnormal expression of C-terminal p53 isoforms α, β, and γ can cause the development of cancers including breast cancer. To date, much evidence has demonstrated that these isoforms can differentially regulate target genes and modulate their expression. Thus, quantification of individual isoforms may help to link clinical outcome to p53 status and to improve cancer patient treatment. However, there are few studies on accurate determination of p53 isoforms, probably due to sequence homology of these isoforms and also their low abundance. In this study, a targeted proteomics assay combining molecularly imprinted polymers (MIPs) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed for simultaneous quantification of C-terminal p53 isoforms. Isoform-specific surrogate peptides (i.e., KPLDGEYFTLQIR (peptide-α) for isoform α, KPLDGEYFTLQDQTSFQK (peptide-β) for isoform β, and KPLDGEYFTLQMLLDLR (peptide-γ) for isoform γ) were first selected and used in both MIPs enrichment and mass spectrometric detection. The common sequence KPLDGEYFTLQ of these three surrogate peptides was used as single template in MIPs. In addition to optimization of imprinting conditions and characterization of the prepared MIPs, binding affinity and cross-reactivity of the MIPs for each surrogate peptide were also evaluated. As a result, a LOQ of 5 nM was achieved, which was >15-fold more sensitive than that without MIPs. Finally, the assay was validated and applied to simultaneous quantitative analysis of C-terminal p53 isoforms α, β, and γ in several human breast cell lines (i.e., MCF-10A normal cells, MCF-7 and MDA-MB-231 cancer cells, and drug-resistant MCF-7/ADR cancer cells). This study is among the first to employ single template MIPs and cross-reactivity phenomenon to select isoform-specific surrogate peptides and enable simultaneous quantification of protein isoforms in LC-MS/MS-based targeted proteomics.

PRIDE Inspector Toolsuite: Moving Toward a Universal Visualization Tool for Proteomics Data Standard Formats and Quality Assessment of ProteomeXchange Datasets.

PubMed

Perez-Riverol, Yasset; Xu, Qing-Wei; Wang, Rui; Uszkoreit, Julian; Griss, Johannes; Sanchez, Aniel; Reisinger, Florian; Csordas, Attila; Ternent, Tobias; Del-Toro, Noemi; Dianes, Jose A; Eisenacher, Martin; Hermjakob, Henning; Vizcaíno, Juan Antonio

2016-01-01

The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE.The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX "complete" submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

PRIDE Inspector Toolsuite: Moving Toward a Universal Visualization Tool for Proteomics Data Standard Formats and Quality Assessment of ProteomeXchange Datasets*

PubMed Central

Perez-Riverol, Yasset; Xu, Qing-Wei; Wang, Rui; Uszkoreit, Julian; Griss, Johannes; Sanchez, Aniel; Reisinger, Florian; Csordas, Attila; Ternent, Tobias; del-Toro, Noemi; Dianes, Jose A.; Eisenacher, Martin; Hermjakob, Henning; Vizcaíno, Juan Antonio

2016-01-01

The original PRIDE Inspector tool was developed as an open source standalone tool to enable the visualization and validation of mass-spectrometry (MS)-based proteomics data before data submission or already publicly available in the Proteomics Identifications (PRIDE) database. The initial implementation of the tool focused on visualizing PRIDE data by supporting the PRIDE XML format and a direct access to private (password protected) and public experiments in PRIDE. The ProteomeXchange (PX) Consortium has been set up to enable a better integration of existing public proteomics repositories, maximizing its benefit to the scientific community through the implementation of standard submission and dissemination pipelines. Within the Consortium, PRIDE is focused on supporting submissions of tandem MS data. The increasing use and popularity of the new Proteomics Standards Initiative (PSI) data standards such as mzIdentML and mzTab, and the diversity of workflows supported by the PX resources, prompted us to design and implement a new suite of algorithms and libraries that would build upon the success of the original PRIDE Inspector and would enable users to visualize and validate PX “complete” submissions. The PRIDE Inspector Toolsuite supports the handling and visualization of different experimental output files, ranging from spectra (mzML, mzXML, and the most popular peak lists formats) and peptide and protein identification results (mzIdentML, PRIDE XML, mzTab) to quantification data (mzTab, PRIDE XML), using a modular and extensible set of open-source, cross-platform libraries. We believe that the PRIDE Inspector Toolsuite represents a milestone in the visualization and quality assessment of proteomics data. It is freely available at http://github.com/PRIDE-Toolsuite/. PMID:26545397

Time-resolved cellular effects induced by TcdA from Clostridium difficile.

PubMed

Jochim, Nelli; Gerhard, Ralf; Just, Ingo; Pich, Andreas

2014-05-30

The anaerobe Clostridium difficile is a common pathogen that causes infection of the colon leading to diarrhea or pseudomembranous colitis. Its major virulence factors are toxin A (TcdA) and toxin B (TcdB), which specifically inactivate small GTPases by glucosylation leading to reorganization of the cytoskeleton and finally to cell death. In the present work a quantitative proteome analysis using the isotope-coded protein label (ICPL) approach was conducted to investigate proteome changes in the colon cell line Caco-2 after treatment with recombinant wild-type TcdA (rTcdA-wt) or a glucosyltransferase-deficient mutant TcdA (rTcdA-mut). Proteins from crude cell lysates or cellular subfractions were identified by liquid chromatography/electrospray ionization mass spectrometry (LC/ESI-MS). Two time points (5 h, 24 h) of toxin treatment were analyzed and about 4000 proteins were identified in each case. After 5 h treatment with rTcdA-wt, 150 proteins had a significantly altered abundance; rTcdA-mut caused regulation of 50 proteins at this time point. After 24 h treatment with rTcdA-wt changes in abundance of 61 proteins were observed, but no changes in protein abundance were detected after 24 h if cells were treated with rTcdA-mut. TcdA affected several proteins involved in signaling events, cytoskeleton and cell-cell contact organization, translation, and metabolic processes. The ICPL-dependent quantification was verified by label-free targeted MS techniques based on multiple reaction monitoring (MRM) and triple quadrupole mass spectrometry. LC/MS-based proteome analyses and the ICPL approach revealed comprehensive and reproducible proteome date and provided new insights into the cellular effects of clostridial glucosylating toxins (CGT). Copyright © 2014 John Wiley & Sons, Ltd.

Study of rat hypothalamic proteome by HPLC/ESI ion trap and HPLC/ESI-Q-TOF MS.

PubMed

Iqbal, Javed; Li, Wang; Ullah, Kaleem; Hasan, Murtaza; Linna, Guo; Awan, Umer; Zhang, Yongqian; Batool, Sajida; Qing, Hong; Deng, Yulin

2013-08-01

The proteomic profile of hypothalamus, a key organ of CNS, is explored here by employing two widely used MS techniques, i.e. HPLC/ESI-ion trap and HPLC/ESI-quadrupole-TOF MS. Strong cation exchange is used for the fractionation of peptides and protein search engine MASCOT is employed for data query. One hundred and thirty six proteins with 10 973 peptides were identified by HPLC/ESI-ion trap MS, while 140 proteins with 32 183 peptides were characterized by HPLC/ESI-quadrupole-TOF MS. Among the total 198 proteins identified in both experiments, 78 proteins were common in both sets of conditions. The rest of the 120 proteins were identified distinctly in both MS strategies, i.e. 58 unique proteins were found using the quadrupole-TOF while 62 were found with the HPLC/ESI-ion trap. Moreover, these proteins were classified into groups based on their functions performed in the body. Results presented here identified some important signal and cellular defense proteins inevitable for survival in stressed conditions. Additionally, it is also shown that any single MS strategy is not reliable for good results due to loss of data depending on sensitivity of the instrument used. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative Proteomic Analysis of Optimal Cutting Temperature (OCT) Embedded Core-Needle Biopsy of Lung Cancer

NASA Astrophysics Data System (ADS)

Zhao, Xiaozheng; Huffman, Kenneth E.; Fujimoto, Junya; Canales, Jamie Rodriguez; Girard, Luc; Nie, Guangjun; Heymach, John V.; Wistuba, Igacio I.; Minna, John D.; Yu, Yonghao

2017-10-01

With recent advances in understanding the genomic underpinnings and oncogenic drivers of pathogenesis in different subtypes, it is increasingly clear that proper pretreatment diagnostics are essential for the choice of appropriate treatment options for non-small cell lung cancer (NSCLC). Tumor tissue preservation in optimal cutting temperature (OCT) compound is commonly used in the surgical suite. However, proteins recovered from OCT-embedded specimens pose a challenge for LC-MS/MS experiments, due to the large amounts of polymers present in OCT. Here we present a simple workflow for whole proteome analysis of OCT-embedded NSCLC tissue samples, which involves a simple trichloroacetic acid precipitation step. Comparisons of protein recovery between frozen versus OCT-embedded tissue showed excellent consistency with more than 9200 proteins identified. Using an isobaric labeling strategy, we quantified more than 5400 proteins in tumor versus normal OCT-embedded core needle biopsy samples. Gene ontology analysis indicated that a number of proliferative as well as squamous cell carcinoma (SqCC) marker proteins were overexpressed in the tumor, consistent with the patient's pathology based diagnosis of "poorly differentiated SqCC". Among the most downregulated proteins in the tumor sample, we noted a number of proteins with potential immunomodulatory functions. Finally, interrogation of the aberrantly expressed proteins using a candidate approach and cross-referencing with publicly available databases led to the identification of potential druggable targets in DNA replication and DNA damage repair pathways. We conclude that our approach allows LC-MS/MS proteomic analyses on OCT-embedded lung cancer specimens, opening the way to bring powerful proteomics into the clinic. [Figure not available: see fulltext.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) platform as a major advance in overall sensitivity. NanoPOTS dramatically enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive LC-MS, nanoPOTS allows identification of ~1500 to ~3,000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runsmore » algorithm of MaxQuant, >3000 proteins were consistently identified from as few as 10 cells. Furthermore, we demonstrate robust quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Ultra-sensitive high performance liquid chromatography-laser-induced fluorescence based proteomics for clinical applications.

PubMed

Patil, Ajeetkumar; Bhat, Sujatha; Pai, Keerthilatha M; Rai, Lavanya; Kartha, V B; Chidangil, Santhosh

2015-09-08

An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper. In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Automation of nanoflow liquid chromatography-tandem mass spectrometry for proteome analysis by using a strong cation exchange trap column.

PubMed

Jiang, Xiaogang; Feng, Shun; Tian, Ruijun; Han, Guanghui; Jiang, Xinning; Ye, Mingliang; Zou, Hanfa

2007-02-01

An approach was developed to automate sample introduction for nanoflow LC-MS/MS (microLC-MS/MS) analysis using a strong cation exchange (SCX) trap column. The system consisted of a 100 microm id x 2 cm SCX trap column and a 75 microm id x 12 cm C18 RP analytical column. During the sample loading step, the flow passing through the SCX trap column was directed to waste for loading a large volume of sample at high flow rate. Then the peptides bound on the SCX trap column were eluted onto the RP analytical column by a high salt buffer followed by RP chromatographic separation of the peptides at nanoliter flow rate. It was observed that higher performance of separation could be achieved with the system using SCX trap column than with the system using C18 trap column. The high proteomic coverage using this approach was demonstrated in the analysis of tryptic digest of BSA and yeast cell lysate. In addition, this system was also applied to two-dimensional separation of tryptic digest of human hepatocellular carcinoma cell line SMMC-7721 for large scale proteome analysis. This system was fully automated and required minimum changes on current microLC-MS/MS system. This system represented a promising platform for routine proteome analysis.

Combining high-throughput MALDI-TOF mass spectrometry and isoelectric focusing gel electrophoresis for virtual 2D gel-based proteomics.

PubMed

Lohnes, Karen; Quebbemann, Neil R; Liu, Kate; Kobzeff, Fred; Loo, Joseph A; Ogorzalek Loo, Rachel R

2016-07-15

The virtual two-dimensional gel electrophoresis/mass spectrometry (virtual 2D gel/MS) technology combines the premier, high-resolution capabilities of 2D gel electrophoresis with the sensitivity and high mass accuracy of mass spectrometry (MS). Intact proteins separated by isoelectric focusing (IEF) gel electrophoresis are imaged from immobilized pH gradient (IPG) polyacrylamide gels (the first dimension of classic 2D-PAGE) by matrix-assisted laser desorption/ionization (MALDI) MS. Obtaining accurate intact masses from sub-picomole-level proteins embedded in 2D-PAGE gels or in IPG strips is desirable to elucidate how the protein of one spot identified as protein 'A' on a 2D gel differs from the protein of another spot identified as the same protein, whenever tryptic peptide maps fail to resolve the issue. This task, however, has been extremely challenging. Virtual 2D gel/MS provides access to these intact masses. Modifications to our matrix deposition procedure improve the reliability with which IPG gels can be prepared; the new procedure is described. Development of this MALDI MS imaging (MSI) method for high-throughput MS with integrated 'top-down' MS to elucidate protein isoforms from complex biological samples is described and it is demonstrated that a 4-cm IPG gel segment can now be imaged in approximately 5min. Gel-wide chemical and enzymatic methods with further interrogation by MALDI MS/MS provide identifications, sequence-related information, and post-translational/transcriptional modification information. The MSI-based virtual 2D gel/MS platform may potentially link the benefits of 'top-down' and 'bottom-up' proteomics. Copyright © 2016 Elsevier Inc. All rights reserved.

An Integrated Proteomics and Bioinformatics Approach Reveals the Anti-inflammatory Mechanism of Carnosic Acid

PubMed Central

Wang, Li-Chao; Wei, Wen-Hui; Zhang, Xiao-Wen; Liu, Dan; Zeng, Ke-Wu; Tu, Peng-Fei

2018-01-01

Drastic macrophages activation triggered by exogenous infection or endogenous stresses is thought to be implicated in the pathogenesis of various inflammatory diseases. Carnosic acid (CA), a natural phenolic diterpene extracted from Salvia officinalis plant, has been reported to possess anti-inflammatory activity. However, its role in macrophages activation as well as potential molecular mechanism is largely unexplored. In the current study, we sought to elucidate the anti-inflammatory property of CA using an integrated approach based on unbiased proteomics and bioinformatics analysis. CA significantly inhibited the robust increase of nitric oxide and TNF-α, downregulated COX2 protein expression, and lowered the transcriptional level of inflammatory genes including Nos2, Tnfα, Cox2, and Mcp1 in LPS-stimulated RAW264.7 cells, a murine model of peritoneal macrophage cell line. The LC-MS/MS-based shotgun proteomics analysis showed CA negatively regulated 217 LPS-elicited proteins which were involved in multiple inflammatory processes including MAPK, nuclear factor (NF)-κB, and FoxO signaling pathways. A further molecular biology analysis revealed that CA effectually inactivated IKKβ/IκB-α/NF-κB, ERK/JNK/p38 MAPKs, and FoxO1/3 signaling pathways. Collectively, our findings demonstrated the role of CA in regulating inflammation response and provide some insights into the proteomics-guided pharmacological mechanism study of natural products. PMID:29713284

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

EPA Science Inventory

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

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

Proteomics with Mass Spectrometry Imaging: Beyond Amyloid Typing.

PubMed

Lavatelli, Francesca; Merlini, Giampaolo

2018-04-01

Detection and typing of amyloid deposits in tissues are two crucial steps in the management of systemic amyloidoses. The presence of amyloid deposits is routinely evaluated through Congo red staining, whereas proteomics is now a mainstay in the identification of the deposited proteins. In article number 1700236, Winter et al. [Proteomics 2017, 17, Issue 22] describe a novel method based on MALDI-MS imaging coupled to ion mobility separation and peptide filtering, to detect the presence of amyloid in histology samples and to identify its composition, while preserving the spatial distribution of proteins in tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Identification of Missing Proteins Defined by Chromosome-Centric Proteome Project in the Cytoplasmic Detergent-Insoluble Proteins.

PubMed

Chen, Yang; Li, Yaxing; Zhong, Jiayong; Zhang, Jing; Chen, Zhipeng; Yang, Lijuan; Cao, Xin; He, Qing-Yu; Zhang, Gong; Wang, Tong

2015-09-04

Finding protein evidence (PE) for protein coding genes is a primary task of the Phase I Chromosome-Centric Human Proteome Project (C-HPP). Currently, there are 2948 PE level 2-4 coding genes per neXtProt, which are deemed missing proteins in the human proteome. As most samples prepared and analyzed in the C-HPP framework were focusing on detergent soluble proteins, we posit that as a natural composition the cytoplasmic detergent-insoluble proteins (DIPs) represent a source of finding missing proteins. We optimized a workflow and separated cytoplasmic DIPs from three human lung and three human hepatoma cell lines via differential speed centrifugation. We verified that the detergent-soluble proteins (DSPs) could be sufficiently depleted and the cytoplasmic DIP isolation was partially reproducible with Spearman r > 0.70 according to two independent SILAC MS experiments. Through label-free MS, we identified 4524 and 4156 DIPs from lung and liver cells, respectively. Among them, a total of 23 missing proteins (22 PE2 and 1 PE4) were identified by MS, and 18 of them had translation evidence; in addition, six PE5 proteins were identified by MS, three with translation evidence. We showed that cytoplasmic DIPs were not an enrichment of transmembrane proteins and were chromosome-, cell type-, and tissue-specific. Furthermore, we demonstrated that DIPs were distinct from DSPs in terms of structural and physical-chemical features. In conclusion, we have found 23 missing proteins and 6 PE5 proteins from the cytoplasmic insoluble proteome that is biologically and physical-chemically different from the soluble proteome, suggesting that cytoplasmic DIPs carry comprehensive and valuable information for finding PE of missing proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001694.

Accurate, Sensitive, and Precise Multiplexed Proteomics Using the Complement Reporter Ion Cluster

DOE PAGES

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

2018-03-09

We present that quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approachmore » (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Furthermore, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.« less

Accurate, Sensitive, and Precise Multiplexed Proteomics Using the Complement Reporter Ion Cluster

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

Sonnett, Matthew; Yeung, Eyan; Wuhr, Martin

We present that quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approachmore » (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Furthermore, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.« less

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

PubMed

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

2005-08-01

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

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 proteomics analysis software. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed Central

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

2015-01-01

Calculating the number of confidently identified proteins and estimating false discovery rate (FDR) is a challenge when analyzing very large proteomic data sets such as entire human proteomes. Biological and technical heterogeneity in proteomic experiments further add to the challenge and there are strong differences in opinion regarding the conceptual validity of a protein FDR and no consensus regarding the methodology for protein FDR determination. There are also limitations inherent to the widely used classic target–decoy strategy that particularly show when analyzing very large data sets and that lead to a strong over-representation of decoy identifications. In this study, we investigated the merits of the classic, as well as a novel target–decoy-based protein FDR estimation approach, taking advantage of a heterogeneous data collection comprised of ∼19,000 LC-MS/MS runs deposited in ProteomicsDB (https://www.proteomicsdb.org). The “picked” protein FDR approach treats target and decoy sequences of the same protein as a pair rather than as individual entities and chooses either the target or the decoy sequence depending on which receives the highest score. We investigated the performance of this approach in combination with q-value based peptide scoring to normalize sample-, instrument-, and search engine-specific differences. The “picked” target–decoy strategy performed best when protein scoring was based on the best peptide q-value for each protein yielding a stable number of true positive protein identifications over a wide range of q-value thresholds. We show that this simple and unbiased strategy eliminates a conceptual issue in the commonly used “classic” protein FDR approach that causes overprediction of false-positive protein identification in large data sets. The approach scales from small to very large data sets without losing performance, consistently increases the number of true-positive protein identifications and is readily implemented in proteomics analysis software. PMID:25987413

QC-ART: A tool for real-time quality control assessment of mass spectrometry-based proteomics data.

PubMed

Stanfill, Bryan A; Nakayasu, Ernesto S; Bramer, Lisa M; Thompson, Allison M; Ansong, Charles K; Clauss, Therese; Gritsenko, Marina A; Monroe, Matthew E; Moore, Ronald J; Orton, Daniel J; Piehowski, Paul D; Schepmoes, Athena A; Smith, Richard D; Webb-Robertson, Bobbie-Jo; Metz, Thomas O

2018-04-17

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected.  In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration.  To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality.  QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis.  We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.

MaRiMba: a software application for spectral library-based MRM transition list assembly.

PubMed

Sherwood, Carly A; Eastham, Ashley; Lee, Lik Wee; Peterson, Amelia; Eng, Jimmy K; Shteynberg, David; Mendoza, Luis; Deutsch, Eric W; Risler, Jenni; Tasman, Natalie; Aebersold, Ruedi; Lam, Henry; Martin, Daniel B

2009-10-01

Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture.

Size-Sorting Combined with Improved Nanocapillary-LC-MS for Identification of Intact Proteins up to 80 kDa

PubMed Central

Vellaichamy, Adaikkalam; Tran, John C.; Catherman, Adam D.; Lee, Ji Eun; Kellie, John F.; Sweet, Steve M.M.; Zamdborg, Leonid; Thomas, Paul M.; Ahlf, Dorothy R.; Durbin, Kenneth R.; Valaskovic, Gary A.; Kelleher, Neil L.

2010-01-01

Despite the availability of ultra-high resolution mass spectrometers, methods for separation and detection of intact proteins for proteome-scale analyses are still in a developmental phase. Here we report robust protocols for on-line LC-MS to drive high-throughput top-down proteomics in a fashion similar to bottom-up. Comparative work on protein standards showed that a polymeric stationary phase led to superior sensitivity over a silica-based medium in reversed-phase nanocapillary-LC, with detection of proteins >50 kDa routinely accomplished in the linear ion trap of a hybrid Fourier-Transform mass spectrometer. Protein identification was enabled by nozzle-skimmer dissociation (NSD) and detection of fragment ions with <5 ppm mass accuracy for highly-specific database searching using custom software. This overall approach led to identification of proteins up to 80 kDa, with 10-60 proteins identified in single LC-MS runs of samples from yeast and human cell lines pre-fractionated by their molecular weight using a gel-based sieving system. PMID:20073486

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 proteins with biomarker potential have been identified and successfully validated. Copyright © 2018 Elsevier B.V. All rights reserved.

Selected reaction monitoring mass spectrometry: a methodology overview.

PubMed

Ebhardt, H Alexander

2014-01-01

Moving past the discovery phase of proteomics, the term targeted proteomics combines multiple approaches investigating a certain set of proteins in more detail. One such targeted proteomics approach is the combination of liquid chromatography and selected or multiple reaction monitoring mass spectrometry (SRM, MRM). SRM-MS requires prior knowledge of the fragmentation pattern of peptides, as the presence of the analyte in a sample is determined by measuring the m/z values of predefined precursor and fragment ions. Using scheduled SRM-MS, many analytes can robustly be monitored allowing for high-throughput sample analysis of the same set of proteins over many conditions. In this chapter, fundaments of SRM-MS are explained as well as an optimized SRM pipeline from assay generation to data analyzed.

Open Source Software Tool Skyline Reaches Key Agreement with Mass Spectrometer Vendors | Office of Cancer Clinical Proteomics Research

Cancer.gov

The full proteomics analysis of a small tumor sample (similar in mass to a few grains of rice) produces well over 500 megabytes of unprocessed "raw" data when analyzed on a mass spectrometer (MS). Thus, for every proteomics experiment there is a vast amount of raw data that must be analyzed and interrogated in order to extract biological information. Moreover, the raw data output from different MS vendors are generally in different formats inhibiting the ability of labs to productively work together.

P7-S Combining Workflow-Based Project Organization with Protein-Dependant Data Retrieval for the Retrieval of Extensive Proteome Information

PubMed Central

Glandorf, J.; Thiele, H.; Macht, M.; Vorm, O.; Podtelejnikov, A.

2007-01-01

In the course of a full-scale proteomics experiment, the handling of the data as well as the retrieval of the relevant information from the results is a major challenge due to the massive amount of generated data (gel images, chromatograms, and spectra) as well as associated result information (sequences, literature, etc.). To obtain meaningful information from these data, one has to filter the results in an easy way. Possibilities to do so can be based on GO terms or structural features such as transmembrane domains, involvement in certain pathways, etc. In this presentation we will show how a combination of a software package with a workflow-based result organization (Bruker ProteinScape) and a protein-centered data-mining software (Proxeon ProteinCenter) can assist in the comparison of the results from large projects, such as comparison of cross-platform results from 2D PAGE/MS with shotgun LC-ESI-MS/MS. We will present differences between different technologies and show how these differences can be easily identified and how they allow us to draw conclusions on the involved technologies.

In-depth proteomic analysis of Varroa destructor: Detection of DWV-complex, ABPV, VdMLV and honeybee proteins in the mite.

PubMed

Erban, Tomas; Harant, Karel; Hubalek, Martin; Vitamvas, Pavel; Kamler, Martin; Poltronieri, Palmiro; Tyl, Jan; Markovic, Martin; Titera, Dalibor

2015-09-11

We investigated pathogens in the parasitic honeybee mite Varroa destructor using nanoLC-MS/MS (TripleTOF) and 2D-E-MS/MS proteomics approaches supplemented with affinity-chromatography to concentrate trace target proteins. Peptides were detected from the currently uncharacterized Varroa destructor Macula-like virus (VdMLV), the deformed wing virus (DWV)-complex and the acute bee paralysis virus (ABPV). Peptide alignments revealed detection of complete structural DWV-complex block VP2-VP1-VP3, VDV-1 helicase and single-amino-acid substitution A/K/Q in VP1, the ABPV structural block VP1-VP4-VP2-VP3 including uncleaved VP4/VP2, and VdMLV coat protein. Isoforms of viral structural proteins of highest abundance were localized via 2D-E. The presence of all types of capsid/coat proteins of a particular virus suggested the presence of virions in Varroa. Also, matches between the MWs of viral structural proteins on 2D-E and their theoretical MWs indicated that viruses were not digested. The absence/scarce detection of non-structural proteins compared with high-abundance structural proteins suggest that the viruses did not replicate in the mite; hence, virions accumulate in the Varroa gut via hemolymph feeding. Hemolymph feeding also resulted in the detection of a variety of honeybee proteins. The advantages of MS-based proteomics for pathogen detection, false-positive pathogen detection, virus replication, posttranslational modifications, and the presence of honeybee proteins in Varroa are discussed.

Proteomic analysis of Pinus radiata needles: 2-DE map and protein identification by LC/MS/MS and substitution-tolerant database searching.

PubMed

Valledor, Luis; Castillejo, Maria A; Lenz, Christof; Rodríguez, Roberto; Cañal, Maria J; Jorrín, Jesús

2008-07-01

Pinus radiata is one of the most economically important forest tree species, with a worldwide production of around 370 million m (3) of wood per year. Current selection of elite trees to be used in conservation and breeding programes requires the physiological and molecular characterization of available populations. To identify key proteins related to tree growth, productivity and responses to environmental factors, a proteomic approach is being utilized. In this paper, we present the first report of the 2-DE protein reference map of physiologically mature P. radiata needles, as a basis for subsequent differential expression proteomic studies related to growth, development, biomass production and responses to stresses. After TCA/acetone protein extraction of needle tissue, 549 +/- 21 well-resolved spots were detected in Coommassie-stained gels within the 5-8 pH and 10-100 kDa M(r) ranges. The analytical and biological variance determined for 450 spots were of 31 and 42%, respectively. After LC/MS/MS analysis of in-gel tryptic digested spots, proteins were identified by using the novel Paragon algorithm that tolerates amino acid substitution in the first-pass search. It allowed the confident identification of 115 out of the 150 protein spots subjected to MS, quite unusual high percentage for a poor sequence database, as is the case of P. radiata. Proteins were classified into 12 or 18 groups based on their corresponding cell component or biological process/pathway categories, respectively. Carbohydrate metabolism and photosynthetic enzymes predominate in the 2-DE protein profile of P. radiata needles.

In-depth proteomic analysis of Varroa destructor: Detection of DWV-complex, ABPV, VdMLV and honeybee proteins in the mite

PubMed Central

Erban, Tomas; Harant, Karel; Hubalek, Martin; Vitamvas, Pavel; Kamler, Martin; Poltronieri, Palmiro; Tyl, Jan; Markovic, Martin; Titera, Dalibor

2015-01-01

We investigated pathogens in the parasitic honeybee mite Varroa destructor using nanoLC-MS/MS (TripleTOF) and 2D-E-MS/MS proteomics approaches supplemented with affinity-chromatography to concentrate trace target proteins. Peptides were detected from the currently uncharacterized Varroa destructor Macula-like virus (VdMLV), the deformed wing virus (DWV)-complex and the acute bee paralysis virus (ABPV). Peptide alignments revealed detection of complete structural DWV-complex block VP2-VP1-VP3, VDV-1 helicase and single-amino-acid substitution A/K/Q in VP1, the ABPV structural block VP1-VP4-VP2-VP3 including uncleaved VP4/VP2, and VdMLV coat protein. Isoforms of viral structural proteins of highest abundance were localized via 2D-E. The presence of all types of capsid/coat proteins of a particular virus suggested the presence of virions in Varroa. Also, matches between the MWs of viral structural proteins on 2D-E and their theoretical MWs indicated that viruses were not digested. The absence/scarce detection of non-structural proteins compared with high-abundance structural proteins suggest that the viruses did not replicate in the mite; hence, virions accumulate in the Varroa gut via hemolymph feeding. Hemolymph feeding also resulted in the detection of a variety of honeybee proteins. The advantages of MS-based proteomics for pathogen detection, false-positive pathogen detection, virus replication, posttranslational modifications, and the presence of honeybee proteins in Varroa are discussed. PMID:26358842

Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: Systematic variation between sample types and calibration of mass spectrometry data

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

Haab, Brian B.; Geierstanger, Bernhard H.; Michailidis, George

2005-08-01

Four different immunoassay and antibody microarray methods performed at four different sites were used to measure the levels of a broad range of proteins (N = 323 assays; 39, 88, 168, and 28 assays at the respective sites; 237 unique analytes) in the human serum and plasma reference specimens distributed by the Plasma Proteome Project (PPP) of the HUPO. The methods provided a means to (1) assess the level of systematic variation in protein abundances associated with blood preparation methods (serum, citrate-anticoagulated-plasma, EDTA-anticoagulated-plasma, or heparin-anticoagulated-plasma) and (2) evaluate the dependence on concentration of MS-based protein identifications from data sets usingmore » the HUPO specimens. Some proteins, particularly cytokines, had highly variable concentrations between the different sample preparations, suggesting specific effects of certain anticoagulants on the stability or availability of these proteins. The linkage of antibody-based measurements from 66 different analytes with the combined MS/MS data from 18 different laboratories showed that protein detection and the quality of MS data increased with analyte concentration. The conclusions from these initial analyses are that the optimal blood preparation method is variable between analytes and that the discovery of blood proteins by MS can be extended to concentrations below the ng/mL range under certain circumstances. Continued developments in antibody-based methods will further advance the scientific goals of the PPP.« less

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.

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

PubMed

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

2014-04-04

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

The gel electrophoresis markup language (GelML) from the Proteomics Standards Initiative.

PubMed

Gibson, Frank; Hoogland, Christine; Martinez-Bartolomé, Salvador; Medina-Aunon, J Alberto; Albar, Juan Pablo; Babnigg, Gyorgy; Wipat, Anil; Hermjakob, Henning; Almeida, Jonas S; Stanislaus, Romesh; Paton, Norman W; Jones, Andrew R

2010-09-01

The Human Proteome Organisation's Proteomics Standards Initiative has developed the GelML (gel electrophoresis markup language) data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for MS data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications.

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

Modified filter-aided sample preparation (FASP) method increases peptide and protein identifications for shotgun proteomics.

PubMed

Ni, Mao-Wei; Wang, Lu; Chen, Wei; Mou, Han-Zhou; Zhou, Jie; Zheng, Zhi-Guo

2017-01-30

Mass spectrometry (MS)-based protein identification depends mainly on protein extraction and digestion. Although sodium dodecyl sulfate (SDS) can preclude enzymatic digestion and interfere with MS analysis, it is still the most widely used surfactant in these steps. To overcome these disadvantages, a SDS-compatible proteomic technique for SDS removal prior to MS-based analyses was developed, namely filter-aided sample preparation (FASP). Herein, based on the effectiveness of sodium deoxycholate and a detergent removal spin column, we developed a modified FASP (mFASP) method and compared its overall performance, total number of peptides and proteins identified for shotgun proteomic experiments with that of the FASP method. Identification of 4570 ± 392 and 9139 ± 317 peptides and description of 862 ± 46 and 1377 ± 33 protein groups with two or more peptides from the ovarian cancer cell line A2780 was accomplished by FASP and mFASP methods, respectively. The mFASP method (21.2 ± 0.2%) had higher average peptide to protein coverage than FASP method (13.2 ± 0.5%). More hydrophobic peptides were identified by mFASP than by FASP, as indicated by the GRAVY score distribution. The reported method enables reliable and efficient identification of proteins and peptides in whole-cell extracts containing SDS. The new approach allows for higher throughput (the simultaneous identification of more proteins), a more comprehensive investigation of proteins, and potentially the discovery of new biomarkers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Contact Us | Office of Cancer Clinical Proteomics Research

Cancer.gov

For more information, please contact: Office of Cancer Clinical Proteomics Research Center for Strategic Scientific Initiatives Office of the Director National Cancer Institute 31 Center Drive, MS 2580 Bethesda, MD 20892-2580 Phone: (240) 781-3370 Email: cancer.proteomics@mail.nih.gov

Changes in the leaf proteome profile of Withania somnifera (L.) Dunal in response to Alternaria alternata infection

PubMed Central

Singh, Varinder; Singh, Baldev; Joshi, Robin; Jaju, Puneet

2017-01-01

Withania somnifera is a high value medicinal plant which is used against large number of ailments. The medicinal properties of the plant attributes to a wide array of important secondary metabolites. The plant is predominantly infected with leaf spot pathogen Alternaria alternata, which leads to substantial biodeterioration of pharmaceutically important metabolites. To develop an effective strategy to combat this disease, proteomics based approach could be useful. Hence, in the present study, three different protein extraction methods tris-buffer based, phenol based and trichloroacetic acid-acetone (TCA-acetone) based method were comparatively evaluated for two-dimensional electrophoresis (2-DE) analysis of W. somnifera. TCA-acetone method was found to be most effective and was further used to identify differentially expressed proteins in response to fungal infection. Thirty-eight differentially expressed proteins were identified by matrix assisted laser desorption/ionization time of flight-mass spectrometry (MALDI TOF/TOF MS/MS). The known proteins were categorized into eight different groups based on their function and maximum proteins belonged to energy and metabolism, cell structure, stress and defense and RNA/DNA categories. Differential expression of some key proteins were also crosschecked at transcriptomic level by using qRT-PCR and were found to be consistent with the 2-DE data. These outcomes enable us to evaluate modifications that take place at the proteomic level during a compatible host pathogen interaction. The comparative proteome analysis conducted in this paper revealed the involvement of many key proteins in the process of pathogenesis and further investigation of these identified proteins could assist in the discovery of new strategies for the development of pathogen resistance in the plant. PMID:28575108

Nuclear proteome analysis of undifferentiated mouse embryonic stem and germ cells.

PubMed

Buhr, Nicolas; Carapito, Christine; Schaeffer, Christine; Kieffer, Emmanuelle; Van Dorsselaer, Alain; Viville, Stéphane

2008-06-01

Embryonic stem cells (ESCs) and embryonic germ cells (EGCs) provide exciting models for understanding the underlying mechanisms that make a cell pluripotent. Indeed, such understanding would enable dedifferentiation and reprogrammation of any cell type from a patient needing a cell therapy treatment. Proteome analysis has emerged as an important technology for deciphering these biological processes and thereby ESC and EGC proteomes are increasingly studied. Nevertheless, their nuclear proteomes have only been poorly investigated up to now. In order to investigate signaling pathways potentially involved in pluripotency, proteomic analyses have been performed on mouse ESC and EGC nuclear proteins. Nuclei from ESCs and EGCs at undifferentiated stage were purified by subcellular fractionation. After 2-D separation, a subtractive strategy (subtracting culture environment contaminating spots) was applied and a comparison of ESC, (8.5 day post coïtum (dpc))-EGC and (11.5 dpc)-EGC specific nuclear proteomes was performed. A total of 33 ESC, 53 (8.5 dpc)-EGC, and 36 (11.5 dpc)-EGC spots were identified by MALDI-TOF-MS and/or nano-LC-MS/MS. This approach led to the identification of two isoforms (with and without N-terminal acetylation) of a known pluripotency marker, namely developmental pluripotency associated 5 (DPPA5), which has never been identified before in 2-D gel-MS studies of ESCs and EGCs. Furthermore, we demonstrated the efficiency of our subtracting strategy, in association with a nuclear subfractionation by the identification of a new protein (protein arginine N-methyltransferase 7; PRMT7) behaving as proteins involved in pluripotency.

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography—Tandem Mass Spectrometry

PubMed Central

Tabb, David L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Variyath, Asokan Mulayath; Ham, Amy-Joan L.; Bunk, David M.; Kilpatrick, Lisa E.; Billheimer, Dean D.; Blackman, Ronald K.; Cardasis, Helene L.; Carr, Steven A.; Clauser, Karl R.; Jaffe, Jacob D.; Kowalski, Kevin A.; Neubert, Thomas A.; Regnier, Fred E.; Schilling, Birgit; Tegeler, Tony J.; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fisher, Susan J.; Gibson, Bradford W.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Steven E.; Tempst, Paul; Paulovich, Amanda G.; Liebler, Daniel C.; Spiegelman, Cliff

2009-01-01

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35–60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies. PMID:19921851

DISCOVERY OF NOVEL GLUCOSE-REGULATED PROTEINS IN ISOLATED HUMAN PANCREATIC ISLETS USING LC-MS/MS-BASED PROTEOMICS

PubMed Central

Schrimpe-Rutledge, Alexandra C.; Fontès, Ghislaine; Gritsenko, Marina A.; Norbeck, Angela D.; Anderson, David J.; Waters, Katrina M.; Adkins, Joshua N.; Smith, Richard D.; Poitout, Vincent; Metz, Thomas O.

2012-01-01

The prevalence of diabetes mellitus is increasing dramatically throughout the world, and the disease has become a major public health issue. The most common form of the disease, type 2 diabetes, is characterized by insulin resistance and insufficient insulin production from the pancreatic beta-cell. Since glucose is the most potent regulator of beta-cell function under physiological conditions, identification of the insulin secretory defect underlying type 2 diabetes requires a better understanding of glucose regulation of human beta-cell function. To this aim, a bottom-up LC-MS/MS-based proteomics approach was used to profile pooled islets from multiple donors under basal (5 mM) or high (15 mM) glucose conditions. Our analysis discovered 256 differentially abundant proteins (~p<0.05) after 24 h of high glucose exposure from more than 4500 identified in total. Several novel glucose-regulated proteins were elevated under high glucose conditions, including regulators of mRNA splicing (Pleiotropic regulator 1), processing (Retinoblastoma binding protein 6), and function (Nuclear RNA export factor 1), in addition to Neuron navigator 1 and Plasminogen activator inhibitor 1. Proteins whose abundances markedly decreased during incubation at 15 mM glucose included Bax inhibitor 1 and Synaptotagmin-17. Up-regulation of Dicer 1 and SLC27A2 and down-regulation of Phospholipase Cβ4 were confirmed by Western blots. Many proteins found to be differentially abundant after high glucose stimulation are annotated as uncharacterized or hypothetical. These findings expand our knowledge of glucose regulation of the human islet proteome and suggest many hitherto unknown responses to glucose that require additional studies to explore novel functional roles. PMID:22578083

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

PubMed Central

2014-01-01

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

CIG-P: Circular Interaction Graph for Proteomics.

PubMed

Hobbs, Christopher K; Leung, Michelle; Tsang, Herbert H; Ebhardt, H Alexander

2014-10-31

A typical affinity purification coupled to mass spectrometry (AP-MS) experiment includes the purification of a target protein (bait) using an antibody and subsequent mass spectrometry analysis of all proteins co-purifying with the bait (aka prey proteins). Like any other systems biology approach, AP-MS experiments generate a lot of data and visualization has been challenging, especially when integrating AP-MS experiments with orthogonal datasets. We present Circular Interaction Graph for Proteomics (CIG-P), which generates circular diagrams for visually appealing final representation of AP-MS data. Through a Java based GUI, the user inputs experimental and reference data as file in csv format. The resulting circular representation can be manipulated live within the GUI before exporting the diagram as vector graphic in pdf format. The strength of CIG-P is the ability to integrate orthogonal datasets with each other, e.g. affinity purification data of kinase PRPF4B in relation to the functional components of the spliceosome. Further, various AP-MS experiments can be compared to each other. CIG-P aids to present AP-MS data to a wider audience and we envision that the tool finds other applications too, e.g. kinase - substrate relationships as a function of perturbation. CIG-P is available under: http://sourceforge.net/projects/cig-p/

Comprehensive Proteomic Analysis of Human Milk-derived Extracellular Vesicles Unveils a Novel Functional Proteome Distinct from Other Milk Components*

PubMed Central

van Herwijnen, Martijn J.C.; Zonneveld, Marijke I.; Goerdayal, Soenita; Nolte – 't Hoen, Esther N.M.; Garssen, Johan; Stahl, Bernd; Maarten Altelaar, A.F.; Redegeld, Frank A.; Wauben, Marca H.M.

2016-01-01

Breast milk contains several macromolecular components with distinctive functions, whereby milk fat globules and casein micelles mainly provide nutrition to the newborn, and whey contains molecules that can stimulate the newborn's developing immune system and gastrointestinal tract. Although extracellular vesicles (EV) have been identified in breast milk, their physiological function and composition has not been addressed in detail. EV are submicron sized vehicles released by cells for intercellular communication via selectively incorporated lipids, nucleic acids, and proteins. Because of the difficulty in separating EV from other milk components, an in-depth analysis of the proteome of human milk-derived EV is lacking. In this study, an extensive LC-MS/MS proteomic analysis was performed of EV that had been purified from breast milk of seven individual donors using a recently established, optimized density-gradient-based EV isolation protocol. A total of 1963 proteins were identified in milk-derived EV, including EV-associated proteins like CD9, Annexin A5, and Flotillin-1, with a remarkable overlap between the different donors. Interestingly, 198 of the identified proteins are not present in the human EV database Vesiclepedia, indicating that milk-derived EV harbor proteins not yet identified in EV of different origin. Similarly, the proteome of milk-derived EV was compared with that of other milk components. For this, data from 38 published milk proteomic studies were combined in order to construct the total milk proteome, which consists of 2698 unique proteins. Remarkably, 633 proteins identified in milk-derived EV have not yet been identified in human milk to date. Interestingly, these novel proteins include proteins involved in regulation of cell growth and controlling inflammatory signaling pathways, suggesting that milk-derived EVs could support the newborn's developing gastrointestinal tract and immune system. Overall, this study provides an expansion of the whole milk proteome and illustrates that milk-derived EV are macromolecular components with a unique functional proteome. PMID:27601599

Cell- and Tissue-based Proteome Profiling and Dual Imaging of Apoptosis Markers with Probes Derived from Venetoclax and Idasanutlin.

PubMed

Li, Zhengqiu; Zhu, Dongsheng; Guo, Haijun; Chang, Yu; Ni, Yun; Li, Lin; Hao, Piliang; Xu, Yong; Ding, Ke

2018-05-16

Venetoclax (ABT-199) and idasanutlin (RG7388) are efficient anticancer drugs targeting two essential apoptosis markers, Bcl2 and MDM2, respectively. Recent studies have shown that the combination of these two drugs leads to remarkable enhancement of anticancer efficacy, both in vitro and in vivo. In an attempt to understand the mechanism of this synergistic effect, competitive affinity-based proteome profiling coupled with bioimaging was employed to characterize their protein targets in the same cancer cell line and tumor tissue. A series of protein hits, including ITPR1, GSR, RER1, PDIA3, Apoa1 and Tnfrsf17 were simultaneously identified by pull-down/LC-MS/MS with the two sets of affinity-based probes. Dual imaging was successfully carried out, simultaneously detecting Bcl2 and MDM2 expression in various cancer cells. This could facilitate the novel diagnostic and therapeutic strategies of dual targeting of Bcl2/MDM2. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

YahO protein as a calibrant for top-down proteomic identification of Shiga toxin using MALDI-TOF-TOF-MS/MS and post-source decay

USDA-ARS?s Scientific Manuscript database

Matrix-assisted laser desorption/ionization tandem time-of-flight (MALDI-TOF-TOF) mass spectrometry is increasingly utilized for rapid top-down proteomic identification of proteins. This identification may involve analysis of either a pure protein or a protein mixture. For analysis of a pure protein...

Seven perspectives on GPCR H/D-exchange proteomics methods

PubMed Central

Zhang, Xi

2017-01-01

Recent research shows surging interest to visualize human G protein-coupled receptor (GPCR) dynamic structures using the bottom-up H/D-exchange (HDX) proteomics technology. This opinion article clarifies critical technical nuances and logical thinking behind the GPCR HDX proteomics method, to help scientists overcome cross-discipline pitfalls, and understand and reproduce the protocol at high quality. The 2010 89% HDX structural coverage of GPCR was achieved with both structural and analytical rigor. This article emphasizes systematically considering membrane protein structure stability and compatibility with chromatography and mass spectrometry (MS) throughout the pipeline, including the effects of metal ions, zero-detergent shock, and freeze-thaws on HDX result rigor. This article proposes to view bottom-up HDX as two steps to guide choices of detergent buffers and chromatography settings: (I) protein HDX labeling in native buffers, and (II) peptide-centric analysis of HDX labels, which applies (a) bottom-up MS/MS to construct peptide matrix and (b) HDX MS to locate and quantify H/D labels. The detergent-low-TCEP digestion method demystified the challenge of HDX-grade GPCR digestion. GPCR HDX proteomics is a structural approach, thus its choice of experimental conditions should let structure lead and digestion follow, not the opposite. PMID:28529698

The mzqLibrary – An open source Java library supporting the HUPO‐PSI quantitative proteomics standard

PubMed Central

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

2015-01-01

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/. PMID:26037908

Proteomics in the study of the molecular taxonomy and epidemiology of bacterial pathogens.

PubMed

Cash, Phillip

2009-06-01

The ability to discriminate bacterial isolates is important for a number of areas of research in Medical Microbiology, particularly in defining bacterial taxonomy and monitoring transmission in epidemiological investigations. Molecular techniques capable of typing bacteria at the level of the genome and proteome are now widely used for these investigations. This review considers two electrophoretic methods for typing bacteria on the basis of their proteomes, namely 1-D SDS-PAGE and 2-DE. The application of these two techniques for bacterial typing is described with reference to two publications that appeared in Electrophoresis [Costa, Electrophoresis 1990, 11, 382-391 and Cash et al., Electrophoresis 1997, 18, 1472-1482]. Even though these methods have been used for nearly 20 years to differentiate bacterial isolates they remain key technologies in proteome-based typing methods. The developments that have arisen from the two key papers are described in order to highlight the advantages and disadvantages in typing bacteria at the level of their proteomes. Some of the difficulties associated with electrophoretic typing methods can be overcome by using non-gel proteomic methods based on MS to provide improved sensitivity and specificity. The application of proteomic methods to investigate bacterial taxonomy, epidemiology and pathogenesis in general has significant potential in furthering our understanding of infectious diseases.

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/.

Combined comparative and chemical proteomics on the mechanisms of levo-tetrahydropalmatine-induced antinociception in the formalin test.

PubMed

Wang, Chen; Zhou, Jiangrui; Wang, Shuowen; Ye, Mingliang; Jiang, Chunlei; Fan, Guorong; Zou, Hanfa

2010-06-04

This study investigated the mechanisms involved in the antinociceptive action induced by levo-tetrahydropalmatine (l-THP) in the formalin test by combined comparative and chemical proteomics. Rats were pretreated with l-THP by the oral route (40 mg/kg) 1 h before formalin injection. The antinociceptive effect of l-THP was shown in the first and second phases of the formalin test. To address the mechanisms by which l-THP inhibits formalin-induced nociception in rats, the combined comparative and chemical proteomics were applied. A novel high-throughput comparative proteomic approach based on 2D-nano-LC-MS/MS was applied to simultaneously evaluate the deregulated proteins involved in the response of l-THP treatment in formalin-induced pain rats. Thousands of proteins were identified, among which 17 proteins survived the stringent filter criteria and were further included for functional discussion. Two proteins (Neurabin-1 and Calcium-dependent secretion activator 1) were randomly selected, and their expression levels were further confirmed by Western Blots. The results matched well with those of proteomics. In the present study, we also described the development and application of l-THP immobilized beads to bind the targets. Following incubation with cellular lysates, the proteome interacting with the fixed l-THP was identified. The results of comparative and chemical proteomics were quite complementary. Although the precise roles of these identified moleculars in l-THP-induced antinociception need further study, the combined results indicated that proteins associated with signal transduction, vesicular trafficking and neurotransmitter release, energy metabolism, and ion transport play important roles in l-THP-induced antinociception in the formalin test.

MicroSPE-nanoLC-ESI-MS/MS Using 10-μm-i.d. Silica-Based Monolithic Columns for Proteomics

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

Luo, Quanzhou; Page, Jason S.; Tang, Keqi

2007-01-01

Silica-based monolithic narrow bore capillary columns (25 cm x 10 µm i.d.) with an integrated nanoESI emitter has been developed to provide high quality and robust microSPE-nanoLC-ESI-MS analyses. The integrated nanoESI emitter adds no dead volume to the LC separation, allowing stable electrospray performance to be obtained at flow rates of ~10 nL/min. In an initial application we identified 5510 unique peptides covering 1443 distinct Shewanella oneidensis proteins from a 300 ng tryptic digest sample in a single 4-h LC-MS/MS analysis using a linear ion trap MS (LTQ). We found the use of an integrated monolithic ESI emitter provided enhancedmore » resistance to clogging and good run-to-run reproducibility.« less

Fractional Analysis of Escherichia coli O157:H7 by Mass Spectrometry-Based Proteomics

DTIC Science & Technology

2012-10-01

column with the Dionex UltiMate 3000 (Thermo Scientific Dionex , Sunnyvale, CA). The resolved peptides were electrosprayed into a linear ion trap MS... chromatography -tandem mass spectrometry, followed by biochemical pathway mapping using the Kyoto Encyclopedia of Genes and Genomes. The fimbriae-specific subset...15. SUBJECT TERMS 3T3 murine fibroblasts Cell toxicity Liquid chromatography Mass spectrometry LC-MS Ricin Ricinus communis

Label-free shotgun proteomics and metabolite analysis reveal a significant metabolic shift during citrus fruit development

PubMed Central

Katz, Ehud; Boo, Kyung Hwan; Kim, Ho Youn; Eigenheer, Richard A.; Phinney, Brett S.; Shulaev, Vladimir; Negre-Zakharov, Florence; Sadka, Avi; Blumwald, Eduardo

2011-01-01

Label-free LC-MS/MS-based shot-gun proteomics was used to quantify the differential protein synthesis and metabolite profiling in order to assess metabolic changes during the development of citrus fruits. Our results suggested the occurrence of a metabolic change during citrus fruit maturation, where the organic acid and amino acid accumulation seen during the early stages of development shifted into sugar synthesis during the later stage of citrus fruit development. The expression of invertases remained unchanged, while an invertase inhibitor was up-regulated towards maturation. The increased expression of sucrose-phosphate synthase and sucrose-6-phosphate phosphatase and the rapid sugar accumulation suggest that sucrose is also being synthesized in citrus juice sac cells during the later stage of fruit development. PMID:21841177

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472.

PubMed

Baraúna, Rafael A; Santos, Agenor V; Graças, Diego A; Santos, Daniel M; Ghilardi, Rubens; Pimenta, Adriano M C; Carepo, Marta S P; Schneider, Maria P C; Silva, Artur

2015-05-01

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field.

Proteomic analysis of single mammalian cells enabled by microfluidic nanodroplet sample preparation and ultrasensitive nanoLC-MS.

PubMed

Zhu, Ying; Clair, Geremy; Chrisler, William; Shen, Yufeng; Zhao, Rui; Shukla, Anil; Moore, Ronald; Misra, Ravi; Pryhuber, Gloria; Smith, Richard; Ansong, Charles; Kelly, Ryan T

2018-05-24

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analysed by ultrasensitive nanoLC-MS. An average of ~670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic approaches and their application to plant gravitropism.

PubMed

Basu, Proma; Luesse, Darron R; Wyatt, Sarah E

2015-01-01

Proteomics is a powerful technique that allows researchers a window into how an organism responds to a mutation, a specific environment, or at a distinct point during development by quantifying relative protein abundance and posttranslational modifications. Here, we describe methods for the proteomic analysis of Arabidopsis thaliana tissue. Extraction protocols are provided for isolation of soluble, plasma membrane, and tonoplast proteins. In addition, basic analysis and quality metrics for MS/MS data are discussed. The protocols outlined have the potential to unlock new avenues of research that are not possible through basic genetics or transcriptomic approaches. By combining proteomic information with known gene regulatory patterns, researchers can gain a complete picture of how molecular pathways, such as those required for gravitropism, are initiated, regulated, and terminated.

Low-molecular-weight color pI markers to monitor on-line the peptide focusing process in OFFGEL fractionation.

PubMed

Michelland, Sylvie; Bourgoin-Voillard, Sandrine; Cunin, Valérie; Tollance, Axel; Bertolino, Pascal; Slais, Karel; Seve, Michel

2017-08-01

High-throughput mass spectrometry-based proteomic analysis requires peptide fractionation to simplify complex biological samples and increase proteome coverage. OFFGEL fractionation technology became a common method to separate peptides or proteins using isoelectric focusing in an immobilized pH gradient. However, the OFFGEL focusing process may be further optimized and controlled in terms of separation time and pI resolution. Here we evaluated OFFGEL technology to separate peptides from different samples in the presence of low-molecular-weight (LMW) color pI markers to visualize the focusing process. LMW color pI markers covering a large pH range were added to the peptide mixture before OFFGEL fractionation using a 24-wells device encompassing the pH range 3-10. We also explored the impact of LMW color pI markers on peptide fractionation labeled previously for iTRAQ. Then, fractionated peptides were separated by RP_HPLC prior to MS analysis using MALDI-TOF/TOF mass spectrometry in MS and MS/MS modes. Here we report the performance of the peptide focusing process in the presence of LMW color pI markers as on-line trackers during the OFFGEL process and the possibility to use them as pI controls for peptide focusing. This method improves the workflow for peptide fractionation in a bottom-up proteomic approach with or without iTRAQ labeling. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry.

PubMed

Planatscher, Hannes; Supper, Jochen; Poetz, Oliver; Stoll, Dieter; Joos, Thomas; Templin, Markus F; Zell, Andreas

2010-06-25

Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency. We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties. For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics.

Tear proteomic analysis of patients with type 2 diabetes and dry eye syndrome by two-dimensional nano-liquid chromatography coupled with tandem mass spectrometry.

PubMed

Li, Bing; Sheng, Minjie; Xie, Liqi; Liu, Feng; Yan, Guoquan; Wang, Weifang; Lin, Anjuan; Zhao, Fei; Chen, Yihui

2014-01-09

Diabetes mellitus has been shown to be associated with and complicated by dry eye syndrome. We sought to examine and compare the tear film proteome of type 2 diabetic patients with or without dry eye syndrome and normal subjects using two-dimensional nano-liquid chromatography coupled with tandem mass spectrometry (MS)-based proteomics. Tears were collected from eight type 2 diabetes patients with dry eye syndrome, eight type 2 diabetes patients without dry eye syndrome, and eight normal subjects. Tear breakup time (BUT) was determined, and tear proteins were prepared and analyzed using two-dimensional strong cation-exchange/reversed-phase nano-scale liquid chromatography MS. All MS/MS spectra were identified by using SEQUEST against the human International Protein Index (IPI) database and the relative abundance of individual proteins was assessed by spectral counting. Tear BUT was significantly lower in patients with diabetes and dry eye syndrome than in patients with diabetes only and normal subjects. Analysis of spectral counts of tear proteins showed that, compared to healthy controls, patients with diabetes and dry eye syndrome had increased expression of apoptosis-related proteins, like annexin A1, and immunity- and inflammation-related proteins, including neutrophil elastase 2 and clusterin, and glycometabolism-related proteins, like apolipoprotein A-II. Dry eye syndrome in diabetic patients is associated with aberrant expression of tear proteins, and the findings could lead to identification of novel pathways for therapeutic targeting and new diagnostic markers.

Proteomic profiling and pathway analysis of the response of rat renal proximal convoluted tubules to metabolic acidosis

PubMed Central

Schauer, Kevin L.; Freund, Dana M.; Prenni, Jessica E.

2013-01-01

Metabolic acidosis is a relatively common pathological condition that is defined as a decrease in blood pH and bicarbonate concentration. The renal proximal convoluted tubule responds to this condition by increasing the extraction of plasma glutamine and activating ammoniagenesis and gluconeogenesis. The combined processes increase the excretion of acid and produce bicarbonate ions that are added to the blood to partially restore acid-base homeostasis. Only a few cytosolic proteins, such as phosphoenolpyruvate carboxykinase, have been determined to play a role in the renal response to metabolic acidosis. Therefore, further analysis was performed to better characterize the response of the cytosolic proteome. Proximal convoluted tubule cells were isolated from rat kidney cortex at various times after onset of acidosis and fractionated to separate the soluble cytosolic proteins from the remainder of the cellular components. The cytosolic proteins were analyzed using two-dimensional liquid chromatography and tandem mass spectrometry (MS/MS). Spectral counting along with average MS/MS total ion current were used to quantify temporal changes in relative protein abundance. In all, 461 proteins were confidently identified, of which 24 exhibited statistically significant changes in abundance. To validate these techniques, several of the observed abundance changes were confirmed by Western blotting. Data from the cytosolic fractions were then combined with previous proteomic data, and pathway analyses were performed to identify the primary pathways that are activated or inhibited in the proximal convoluted tubule during the onset of metabolic acidosis. PMID:23804448

Proteomic profiling of white muscle from freshwater catfish Rita rita.

PubMed

Mohanty, Bimal Prasanna; Mitra, Tandrima; Banerjee, Sudeshna; Bhattacharjee, Soma; Mahanty, Arabinda; Ganguly, Satabdi; Purohit, Gopal Krishna; Karunakaran, Dhanasekar; Mohanty, Sasmita

2015-06-01

Muscle tissues contribute 34-48 % of the total body mass in fish. Proteomic analysis enables better understanding of the skeletal muscle physiology and metabolism. A proteome map reflects the general fingerprinting of the fish species and has the potential to identify novel proteins which could serve as biomarkers for many aspects of aquaculture including fish physiology and growth, flesh quality, food safety and aquatic environmental monitoring. The freshwater catfish Rita rita of the family Bagridae inhabiting the tropical rivers and estuaries is an important food fish with high nutritive value and is also considered a species of choice in riverine pollution monitoring. Omics information that could enhance utility of this species in molecular research is meager. Therefore, in the present study, proteomic analysis of Rita rita muscle has been carried out and functional genomics data have been generated. A reference muscle proteome has been developed, and 23 protein spots, representing 18 proteins, have been identified by MALDI-TOF/TOF-MS and LC-MS/MS. Besides, transcript information on a battery of heat shock proteins (Hsps) has been generated. The functional genomics information generated could act as the baseline data for further molecular research on this species.

Comparison of methods for profiling O-glycosylation: Human Proteome Organisation Human Disease Glycomics/Proteome Initiative multi-institutional study of IgA1.

PubMed

Wada, Yoshinao; Dell, Anne; Haslam, Stuart M; Tissot, Bérangère; Canis, Kévin; Azadi, Parastoo; Bäckström, Malin; Costello, Catherine E; Hansson, Gunnar C; Hiki, Yoshiyuki; Ishihara, Mayumi; Ito, Hiromi; Kakehi, Kazuaki; Karlsson, Niclas; Hayes, Catherine E; Kato, Koichi; Kawasaki, Nana; Khoo, Kay-Hooi; Kobayashi, Kunihiko; Kolarich, Daniel; Kondo, Akihiro; Lebrilla, Carlito; Nakano, Miyako; Narimatsu, Hisashi; Novak, Jan; Novotny, Milos V; Ohno, Erina; Packer, Nicolle H; Palaima, Elizabeth; Renfrow, Matthew B; Tajiri, Michiko; Thomsson, Kristina A; Yagi, Hirokazu; Yu, Shin-Yi; Taniguchi, Naoyuki

2010-04-01

The Human Proteome Organisation Human Disease Glycomics/Proteome Initiative recently coordinated a multi-institutional study that evaluated methodologies that are widely used for defining the N-glycan content in glycoproteins. The study convincingly endorsed mass spectrometry as the technique of choice for glycomic profiling in the discovery phase of diagnostic research. The present study reports the extension of the Human Disease Glycomics/Proteome Initiative's activities to an assessment of the methodologies currently used for O-glycan analysis. Three samples of IgA1 isolated from the serum of patients with multiple myeloma were distributed to 15 laboratories worldwide for O-glycomics analysis. A variety of mass spectrometric and chromatographic procedures representative of current methodologies were used. Similar to the previous N-glycan study, the results convincingly confirmed the pre-eminent performance of MS for O-glycan profiling. Two general strategies were found to give the most reliable data, namely direct MS analysis of mixtures of permethylated reduced glycans in the positive ion mode and analysis of native reduced glycans in the negative ion mode using LC-MS approaches. In addition, mass spectrometric methodologies to analyze O-glycopeptides were also successful.

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

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

PubMed

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

2013-02-01

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

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

PubMed Central

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

2013-01-01

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

Spectroscopic and Statistical Techniques for Information Recovery in Metabonomics and Metabolomics

NASA Astrophysics Data System (ADS)

Lindon, John C.; Nicholson, Jeremy K.

2008-07-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics.

PubMed

Lindon, John C; Nicholson, Jeremy K

2008-01-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

SprayQc: a real-time LC-MS/MS quality monitoring system to maximize uptime using off the shelf components.

PubMed

Scheltema, Richard A; Mann, Matthias

2012-06-01

With the advent of high-throughput mass spectrometry (MS)-based proteomics, the magnitude and complexity of the performed experiments has increased dramatically. Likewise, investments in chromatographic and MS instrumentation are a large proportion of the budget of proteomics laboratories. Guarding measurement quality and maximizing uptime of the LC-MS/MS systems therefore requires constant care despite automated workflows. We describe a real-time surveillance system, called SprayQc, that continuously monitors the status of the peripheral equipment to ensure that operational parameters are within an acceptable range. SprayQc is composed of multiple plug-in software components that use computer vision to analyze electrospray conditions, monitor the chromatographic device for stable backpressure, interact with a column oven to control pressure by temperature, and ensure that the mass spectrometer is still acquiring data. Action is taken when a failure condition has been detected, such as stopping the column oven and the LC flow, as well as automatically notifying the appropriate operator. Additionally, all defined metrics can be recorded synchronized on retention time with the MS acquisition file, allowing for later inspection and providing valuable information for optimization. SprayQc has been extensively tested in our laboratory, supports third-party plug-in development, and is freely available for download from http://sourceforge.org/projects/sprayqc .

A New Algorithm Using Cross-Assignment for Label-Free Quantitation with LC/LTQ-FT MS

PubMed Central

Andreev, Victor P.; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L.

2008-01-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQFT MS mass spectrometer (or other high resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed “cross-assignment”, is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC/MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of E.coli samples spiked with known amounts of non-E.coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC/MS datasets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication. PMID:17441747

A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.

PubMed

Andreev, Victor P; Li, Lingyun; Cao, Lei; Gu, Ye; Rejtar, Tomas; Wu, Shiaw-Lin; Karger, Barry L

2007-06-01

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.

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.

Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry.

PubMed

Röst, Hannes L; Schmitt, Uwe; Aebersold, Ruedi; Malmström, Lars

2015-01-01

In mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size. Here we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data. Our C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS.

Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry

PubMed Central

Röst, Hannes L.; Schmitt, Uwe; Aebersold, Ruedi; Malmström, Lars

2015-01-01

Motivation In mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size. Results Here we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data. Availability Our C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS. PMID:25927999

Visualization of LC-MS/MS proteomics data in MaxQuant.

PubMed

Tyanova, Stefka; Temu, Tikira; Carlson, Arthur; Sinitcyn, Pavel; Mann, Matthias; Cox, Juergen

2015-04-01

Modern software platforms enable the analysis of shotgun proteomics data in an automated fashion resulting in high quality identification and quantification results. Additional understanding of the underlying data can be gained with the help of advanced visualization tools that allow for easy navigation through large LC-MS/MS datasets potentially consisting of terabytes of raw data. The updated MaxQuant version has a map navigation component that steers the users through mass and retention time-dependent mass spectrometric signals. It can be used to monitor a peptide feature used in label-free quantification over many LC-MS runs and visualize it with advanced 3D graphic models. An expert annotation system aids the interpretation of the MS/MS spectra used for the identification of these peptide features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications.

PubMed

Pascal, Bruce D; West, Graham M; Scharager-Tapia, Catherina; Flefil, Ricardo; Moroni, Tina; Martinez-Acedo, Pablo; Griffin, Patrick R; Carvalloza, Anthony C

2015-12-01

The goal in proteomics to identify all peptides in a complex mixture has been largely addressed using various LC MS/MS approaches, such as data dependent acquisition, SRM/MRM, and data independent acquisition instrumentation. Despite these developments, many peptides remain unsequenced, often due to low abundance, poor fragmentation patterns, or data analysis difficulties. Many of the unidentified peptides exhibit strong evidence in high resolution MS(1) data and are frequently post-translationally modified, playing a significant role in biological processes. Proteomics Workbench (PWB) software was developed to automate the detection and visualization of all possible peptides in MS(1) data, reveal candidate peptides not initially identified, and build inclusion lists for subsequent MS(2) analysis to uncover new identifications. We used this software on existing data on the autophagy regulating kinase Ulk1 as a proof of concept for this method, as we had already manually identified a number of phosphorylation sites Dorsey, F. C. et al (J. Proteome. Res. 8(11), 5253-5263 (2009)). PWB found all previously identified sites of phosphorylation. The software has been made freely available at http://www.proteomicsworkbench.com . Graphical Abstract ᅟ.

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

Mass spectrometry and animal science: protein identification strategies and particularities of farm animal species.

PubMed

Soares, Renata; Franco, Catarina; Pires, Elisabete; Ventosa, Miguel; Palhinhas, Rui; Koci, Kamila; Martinho de Almeida, André; Varela Coelho, Ana

2012-07-19

Proteomic approaches are gaining increasing importance in the context of all fields of animal and veterinary sciences, including physiology, productive characterization, and disease/parasite tolerance, among others. Proteomic studies mainly aim the proteome characterization of a certain organ, tissue, cell type or organism, either in a specific condition or comparing protein differential expression within two or more selected situations. Due to the high complexity of samples, usually total protein extracts, proteomics relies heavily on separation procedures, being 2D-electrophoresis and HPLC the most common, as well as on protein identification using mass spectrometry (MS) based methodologies. Despite the increasing importance of MS in the context of animal and veterinary science studies, the usefulness of such tools is still poorly perceived by the animal science community. This is primarily due to the limited knowledge on mass spectrometry by animal scientists. Additionally, confidence and success in protein identification is hindered by the lack of information in public databases for most of farm animal species and their pathogens, with the exception of cattle (Bos taurus), pig (Sus scrofa) and chicken (Gallus gallus). In this article, we will briefly summarize the main methodologies available for protein identification using mass spectrometry providing a case study of specific applications in the field of animal science. We will also address the difficulties inherent to protein identification using MS, with particular reference to experiments using animal species poorly described in public databases. Additionally, we will suggest strategies to increase the rate of successful identifications when working with farm animal species. Copyright © 2012 Elsevier B.V. All rights reserved.

Top-down proteomic identification of Shiga toxin 2 subtypes from Shiga toxin-producing Escherichia coli by Matrix-Assisted Laser Desorption Ionization-Tandem Time of Flight mass spectrometry

USDA-ARS?s Scientific Manuscript database

We have analyzed 26 Shiga toxin-producing Escherichia coli (STEC) strains for Shiga toxin 2 (Stx2) production using matrix-assisted laser desorption/ionization time-of-flight-time-of-flight tandem mass spectrometry (MALDI-TOF-TOF-MS/MS) and top-down proteomic analysis. STEC strains were induced to ...

High-resolution ultrahigh-pressure long column reversed-phase liquid chromatography for top-down proteomics.

PubMed

Shen, Yufeng; Tolić, Nikola; Piehowski, Paul D; Shukla, Anil K; Kim, Sangtae; Zhao, Rui; Qu, Yi; Robinson, Errol; Smith, Richard D; Paša-Tolić, Ljiljana

2017-05-19

Separation of proteoforms for global intact protein analysis (i.e. top-down proteomics) has lagged well behind what is achievable for peptides in traditional bottom-up proteomic approach and is becoming a true bottle neck for top-down proteomics. Herein, we report use of long (≥1M) columns containing short alkyl (C1-C4) bonded phases to achieve high-resolution RPLC for separation of proteoforms. At a specific operation pressure limit (i.e., 96.5MPa or 14Kpsi used in this work), column length was found to be the most important factor for achieving maximal resolution separation of proteins when 1.5-5μm particles were used as packings and long columns provided peak capacities greater than 400 for proteoforms derived from a global cell lysate with molecular weights below 50kDa. Larger proteoforms (50-110kDa) were chromatographed on long RPLC columns and detected by MS; however, they cannot be identified yet by tandem mass spectrometry. Our experimental data further demonstrated that long alkyl (e.g., C8 and C18) bonded particles provided high-resolution RPLC for <10kDa proteoforms, not efficient for separation of global proteoforms. Reversed-phase particles with porous, nonporous, and superficially porous surfaces were systematically investigated for high-resolution RPLC. Pore size (200-400Å) and the surface structure (porous and superficially porous) of particles was found to have minor influences on high-resolution RPLC of proteoforms. RPLC presented herein enabled confident identification of ∼900 proteoforms (1% FDR) for a low-microgram quantity of proteomic samples using a single RPLC-MS/MS analysis. The level of RPLC performance attained in this work is close to that typically realized in bottom-up proteomics, and broadly useful when applying e.g., the single-stage MS accurate mass tag approach, but less effective when combined with current tandem MS. Our initial data indicate that MS detection and fragmentation inefficiencies provided by current high-resolution mass spectrometers are key challenges for characterization of larger proteoforms. Copyright © 2017. Published by Elsevier B.V.

High-resolution ultrahigh-pressure long column reversed-phase liquid chromatography for top-down proteomics

DOE PAGES

Shen, Yufeng; Tolić, Nikola; Piehowski, Paul D.; ...

2017-01-05

Separation of proteoforms for global intact protein analysis (i.e. top-down proteomics) has lagged well behind what is achievable for peptides in traditional bottom-up proteomic approach and is becoming a true bottle neck for top-down proteomics. We report use of long (≥1 M) columns containing short alkyl (C1-C4) bonded phases to achieve high-resolution RPLC for separation of proteoforms. At a specific operation pressure limit (i.e., 96.5 MPa or 14 K psi used in this work), column length was found to be the most important factor for achieving maximal resolution separation of proteins when 1.5–5 μm particles were used as packings andmore » long columns provided peak capacities greater than 400 for proteoforms derived from a global cell lysate with molecular weights below 50 kDa. Furthermore, we chromatographed larger proteoforms (50–110 kDa) on long RPLC columns and detected by MS; however, they cannot be identified yet by tandem mass spectrometry. Our experimental data further demonstrated that long alkyl (e.g., C8 and C18) bonded particles provided high-resolution RPLC for <10 kDa proteoforms, not efficient for separation of global proteoforms. Reversed-phase particles with porous, nonporous, and superficially porous surfaces were systematically investigated for high-resolution RPLC. Pore size (200–400 Å) and the surface structure (porous and superficially porous) of particles was found to have minor influences on high-resolution RPLC of proteoforms. RPLC presented herein enabled confident identification of ~900 proteoforms (1% FDR) for a low-microgram quantity of proteomic samples using a single RPLC–MS/MS analysis. The level of RPLC performance attained in this work is close to that typically realized in bottom-up proteomics, and broadly useful when applying e.g., the single-stage MS accurate mass tag approach, but less effective when combined with current tandem MS. Finally, our initial data indicate that MS detection and fragmentation inefficiencies provided by current high-resolution mass spectrometers are key challenges for characterization of larger proteoforms.« less

Proteomic analysis of urine in rats chronically exposed to fluoride.

PubMed

Kobayashi, Claudia Ayumi Nakai; Leite, Aline de Lima; da Silva, Thelma Lopes; dos Santos, Lucilene Delazari; Nogueira, Fábio César Sousa; Santos, Keity Souza; de Oliveira, Rodrigo Cardoso; Palma, Mario Sérgio; Domont, Gilberto Barbosa; Buzalaf, Marília Afonso Rabelo

2011-01-01

Urine is an ideal source of materials to search for potential disease-related biomarkers as it is produced by the affected tissues and can be easily obtained by noninvasive methods. 2-DE-based proteomic approach was used to better understand the molecular mechanisms of injury induced by fluoride (F(-)) and define potential biomarkers of dental fluorosis. Three groups of weanling male Wistar rats were treated with drinking water containing 0 (control), 5, or 50 ppm F(-) for 60 days (n = 15/group). During the experimental period, the animals were kept individually in metabolic cages, to analyze the water and food consumption, as well as fecal and urinary F(-) excretion. Urinary proteome profiles were examined using 2-DE and Colloidal Coomassie Brilliant Blue staining. A dose-response regarding F(-) intake and excretion was detected. Quantitative intensity analysis revealed 8, 11, and 8 significantly altered proteins between control vs. 5 ppm F(-), control vs. 50 ppm F(-) and 5 ppm F(-) vs. 50 ppm F(-) groups, respectively. Two proteins regulated by androgens (androgen-regulated 20-KDa protein and α-2μ-globulin) and one related to detoxification (aflatoxin-B1-aldehyde-reductase) were identified by MALDI-TOF-TOF MS/MS. Thus, proteomic analysis can help to better understand the mechanisms underlying F(-) toxicity, even in low doses. Copyright © 2010 Wiley Periodicals, Inc.

Proteomic Analysis of Lyme Disease: Global Protein Comparison of Three Strains of Borrelia burgdorferi

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

Jacobs, Jon M.; Yang, Xiaohua; Luft, Benjamin J.

2005-04-01

The Borrelia burgdorferi spirochete is the causative agent of Lyme disease, the most common tick-borne disease in the United States. It has been studied extensively to help understand its pathogenicity of infection and how it can persist in different mammalian hosts. We report the proteomic analysis of the archetype B. burgdorferi B31 strain and two other strains (ND40, and JD-1) having different Borrelia pathotypes using strong cation exchange fractionation of proteolytic peptides followed by high-resolution, reversed phase capillary liquid chromatography coupled with ion trap tandem mass spectrometric (LC-MS/MS) analysis. Protein identification was facilitated by the availability of the complete B31more » genome sequence. A total of 665 Borrelia proteins were identified representing ~38 % coverage of the theoretical B31 proteome. A significant overlap was observed between the identified proteins in direct comparisons between any two strains (>72%), but distinct differences were observed among identified hypothetical and outer membrane proteins of the three strains. Such a concurrent proteomic overview of three Borrelia strains based upon only the B31 genome sequence is shown to provide significant insights into the presence or absence of specific proteins and a broad overall comparison among strains.« less

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

Proteomic analysis of the phytopathogenic soilborne fungus Verticillium dahliae reveals differential protein expression in isolates that differ in aggressiveness.

PubMed

El-Bebany, Ahmed F; Rampitsch, Christof; Daayf, Fouad

2010-01-01

Verticillium dahliae is a soilborne fungus that causes a vascular wilt disease of plants and losses in a broad range of economically important crops worldwide. In this study, we compared the proteomes of highly (Vd1396-9) and weakly (Vs06-14) aggressive isolates of V. dahliae to identify protein factors that may contribute to pathogenicity. Twenty-five protein spots were consistently observed as differential in the proteome profiles of the two isolates. The protein sequences in the spots were identified by LC-ESI-MS/MS and MASCOT database searches. Some of the identified sequences shared homology with fungal proteins that have roles in stress response, colonization, melanin biosynthesis, microsclerotia formation, antibiotic resistance, and fungal penetration. These are important functions for infection of the host and survival of the pathogen in soil. One protein found only in the highly aggressive isolate was identified as isochorismatase hydrolase, a potential plant-defense suppressor. This enzyme may inhibit the production of salicylic acid, which is important for plant defense response signaling. Other sequences corresponding to potential pathogenicity factors were identified in the highly aggressive isolate. This work indicates that, in combination with functional genomics, proteomics-based analyses can provide additional insights into pathogenesis and potential management strategies for this disease.

Proteomic profiling of early degenerative retina of RCS rats.

PubMed

Zhu, Zhi-Hong; Fu, Yan; Weng, Chuan-Huang; Zhao, Cong-Jian; Yin, Zheng-Qin

2017-01-01

To identify the underlying cellular and molecular changes in retinitis pigmentosa (RP). Label-free quantification-based proteomics analysis, with its advantages of being more economic and consisting of simpler procedures, has been used with increasing frequency in modern biological research. Dystrophic RCS rats, the first laboratory animal model for the study of RP, possess a similar pathological course as human beings with the diseases. Thus, we employed a comparative proteomics analysis approach for in-depth proteome profiling of retinas from dystrophic RCS rats and non-dystrophic congenic controls through Linear Trap Quadrupole - orbitrap MS/MS, to identify the significant differentially expressed proteins (DEPs). Bioinformatics analyses, including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation and upstream regulatory analysis, were then performed on these retina proteins. Finally, a Western blotting experiment was carried out to verify the difference in the abundance of transcript factor E2F1. In this study, we identified a total of 2375 protein groups from the retinal protein samples of RCS rats and non-dystrophic congenic controls. Four hundred thirty-four significantly DEPs were selected by Student's t -test. Based on the results of the bioinformatics analysis, we identified mitochondrial dysfunction and transcription factor E2F1 as the key initiation factors in early retinal degenerative process. We showed that the mitochondrial dysfunction and the transcription factor E2F1 substantially contribute to the disease etiology of RP. The results provide a new potential therapeutic approach for this retinal degenerative disease.

Development of an Efficient Protein Extraction Method Compatible with LC-MS/MS for Proteome Mapping in Two Australian Seagrasses Zostera muelleri and Posidonia australis

PubMed Central

Jiang, Zhijian; Kumar, Manoj; Padula, Matthew P.; Pernice, Mathieu; Kahlke, Tim; Kim, Mikael; Ralph, Peter J.

2017-01-01

The availability of the first complete genome sequence of the marine flowering plant Zostera marina (commonly known as seagrass) in early 2016, is expected to significantly raise the impact of seagrass proteomics. Seagrasses are marine ecosystem engineers that are currently declining worldwide at an alarming rate due to both natural and anthropogenic disturbances. Seagrasses (especially species of the genus Zostera) are compromised for proteomic studies primarily due to the lack of efficient protein extraction methods because of their recalcitrant cell wall which is rich in complex polysaccharides and a high abundance of secondary metabolites in their cells. In the present study, three protein extraction methods that are commonly used in plant proteomics i.e., phenol (P); trichloroacetic acid/acetone/SDS/phenol (TASP); and borax/polyvinyl-polypyrrolidone/phenol (BPP) extraction, were evaluated quantitatively and qualitatively based on two dimensional isoelectric focusing (2D-IEF) maps and LC-MS/MS analysis using the two most abundant Australian seagrass species, namely Zostera muelleri and Posidonia australis. All three tested methods produced high quality protein extracts with excellent 2D-IEF maps in P. australis. However, the BPP method produces better results in Z. muelleri compared to TASP and P. Therefore, we further modified the BPP method (M-BPP) by homogenizing the tissue in a modified protein extraction buffer containing both ionic and non-ionic detergents (0.5% SDS; 1.5% Triton X-100), 2% PVPP and protease inhibitors. Further, the extracted proteins were solubilized in 0.5% of zwitterionic detergent (C7BzO) instead of 4% CHAPS. This slight modification to the BPP method resulted in a higher protein yield, and good quality 2-DE maps with a higher number of protein spots in both the tested seagrasses. Further, the M-BPP method was successfully utilized in western-blot analysis of phosphoenolpyruvate carboxylase (PEPC—a key enzyme for carbon metabolism). This optimized protein extraction method will be a significant stride toward seagrass proteome mining and identifying the protein biomarkers to stress response of seagrasses under the scenario of global climate change and anthropogenic perturbations. PMID:28861098

Development of an Efficient Protein Extraction Method Compatible with LC-MS/MS for Proteome Mapping in Two Australian Seagrasses Zostera muelleri and Posidonia australis.

PubMed

Jiang, Zhijian; Kumar, Manoj; Padula, Matthew P; Pernice, Mathieu; Kahlke, Tim; Kim, Mikael; Ralph, Peter J

2017-01-01

The availability of the first complete genome sequence of the marine flowering plant Zostera marina (commonly known as seagrass) in early 2016, is expected to significantly raise the impact of seagrass proteomics. Seagrasses are marine ecosystem engineers that are currently declining worldwide at an alarming rate due to both natural and anthropogenic disturbances. Seagrasses (especially species of the genus Zostera ) are compromised for proteomic studies primarily due to the lack of efficient protein extraction methods because of their recalcitrant cell wall which is rich in complex polysaccharides and a high abundance of secondary metabolites in their cells. In the present study, three protein extraction methods that are commonly used in plant proteomics i.e., phenol (P); trichloroacetic acid/acetone/SDS/phenol (TASP); and borax/polyvinyl-polypyrrolidone/phenol (BPP) extraction, were evaluated quantitatively and qualitatively based on two dimensional isoelectric focusing (2D-IEF) maps and LC-MS/MS analysis using the two most abundant Australian seagrass species, namely Zostera muelleri and Posidonia australis . All three tested methods produced high quality protein extracts with excellent 2D-IEF maps in P. australis . However, the BPP method produces better results in Z. muelleri compared to TASP and P. Therefore, we further modified the BPP method (M-BPP) by homogenizing the tissue in a modified protein extraction buffer containing both ionic and non-ionic detergents (0.5% SDS; 1.5% Triton X-100), 2% PVPP and protease inhibitors. Further, the extracted proteins were solubilized in 0.5% of zwitterionic detergent (C7BzO) instead of 4% CHAPS. This slight modification to the BPP method resulted in a higher protein yield, and good quality 2-DE maps with a higher number of protein spots in both the tested seagrasses. Further, the M-BPP method was successfully utilized in western-blot analysis of phosphoenolpyruvate carboxylase (PEPC-a key enzyme for carbon metabolism). This optimized protein extraction method will be a significant stride toward seagrass proteome mining and identifying the protein biomarkers to stress response of seagrasses under the scenario of global climate change and anthropogenic perturbations.

Liquid-phase-based separation systems for depletion, prefractionation and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis – An update covering the period 2011-2014

PubMed Central

Puangpila, Chanida; Mayadunne, Erandi; Rassi, Ziad El

2015-01-01

This review article expands on the previous one (S. Selvaraju and Z. El Rassi, Electrophoresis 2012, 33, 74-88) by reviewing pertinent literature in the period extending from early 2011 to present. As the previous review article, the present one is concerned with proteomic sample preparation (e.g., depletion of high abundance proteins, reduction of the protein dynamic concentration range, enrichment of a particular sub-proteome), and the subsequent chromatographic and/or electrophoretic pre-fractionation prior to peptide separation and identification by LC-MS/MS. This review article is distinguished from its second version published in Electrophoresis 2012, 33, 74-88 by expanding on capturing/enriching sub-phosphoproteomes by immobilized metal affinity chromatography and metal oxide affinity chromatography. Seventy-seven papers published in the period extending from mid 2011 to the present have been reviewed. By no means this review article is exhaustive, given the fact that its aim is to give a concise treatment of the latest developments in the field. PMID:25287967

Proteomic Data Resources for EDRN Ovary Cancer Researchers within the EDRN — EDRN Public Portal

Cancer.gov

This project will generate a highly valuable data resource and make it available to all EDRN ovarian cancer researchers. The resource will include comprehensive proteomic (tandem mass spectrometry, MS/MS) data generated from plasma samples that have been collected between four months and four years prior to clinical detection of ovarian cancer. These pre-clinical samples, provided from the Beta Carotene and Retinol Efficacy Trial (CARET) prospective study, will be interrogated using IPAS, the proteomic profiling method developed by the Hanash Laboratory and with the quantitative methods developed by the McIntosh laboratory. In addition, we will combine these pre-clinical data with already completed IPAS interrogations of plasma collected at the time of ovarian cancer diagnosis. Thus together we will provide information on both pre-clinical and clinical behavior of a large number of proteins. Based on our preliminary work we are able to quantify over 500 plasma proteins in each of these experiments, many of which are putative ovarian cancer biomarkers, showing the platform is capable of providing useful information regarding biomarker candidates.

Building high-quality assay libraries for targeted analysis of SWATH MS data.

PubMed

Schubert, Olga T; Gillet, Ludovic C; Collins, Ben C; Navarro, Pedro; Rosenberger, George; Wolski, Witold E; Lam, Henry; Amodei, Dario; Mallick, Parag; MacLean, Brendan; Aebersold, Ruedi

2015-03-01

Targeted proteomics by selected/multiple reaction monitoring (S/MRM) or, on a larger scale, by SWATH (sequential window acquisition of all theoretical spectra) MS (mass spectrometry) typically relies on spectral reference libraries for peptide identification. Quality and coverage of these libraries are therefore of crucial importance for the performance of the methods. Here we present a detailed protocol that has been successfully used to build high-quality, extensive reference libraries supporting targeted proteomics by SWATH MS. We describe each step of the process, including data acquisition by discovery proteomics, assertion of peptide-spectrum matches (PSMs), generation of consensus spectra and compilation of MS coordinates that uniquely define each targeted peptide. Crucial steps such as false discovery rate (FDR) control, retention time normalization and handling of post-translationally modified peptides are detailed. Finally, we show how to use the library to extract SWATH data with the open-source software Skyline. The protocol takes 2-3 d to complete, depending on the extent of the library and the computational resources available.

Proteome Speciation by Mass Spectrometry: Characterization of Composite Protein Mixtures in Milk Replacers.

PubMed

Gaspari, Marco; Chiesa, Luca; Nicastri, Annalisa; Gabriele, Caterina; Harper, Valeria; Britti, Domenico; Cuda, Giovanni; Procopio, Antonio

2016-12-06

The ability of tandem mass spectrometry to determine the primary structure of proteolytic peptides can be exploited to trace back the organisms from which the corresponding proteins were extracted. This information can be important when food products, such as protein powders, can be supplemented with lower-quality starting materials. In order to dissect the origin of proteinaceous material composing a given unknown mixture, a two-step database search strategy for bottom-up nanoscale liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) data was implemented. A single nanoLC-MS/MS analysis was sufficient not only to determine the qualitative composition of the mixtures under examination, but also to assess the relative percent composition of the various proteomes, if dedicated calibration curves were previously generated. The approach of two-step database search for qualitative analysis and proteome total ion current (pTIC) calculation for quantitative analysis was applied to several binary and ternary mixtures which mimic the composition of milk replacers typically used in calf feeding.

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.

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.

Multi-profile Bayesian alignment model for LC-MS data analysis with integration of internal standards

PubMed Central

Tsai, Tsung-Heng; Tadesse, Mahlet G.; Di Poto, Cristina; Pannell, Lewis K.; Mechref, Yehia; Wang, Yue; Ressom, Habtom W.

2013-01-01

Motivation: Liquid chromatography-mass spectrometry (LC-MS) has been widely used for profiling expression levels of biomolecules in various ‘-omic’ studies including proteomics, metabolomics and glycomics. Appropriate LC-MS data preprocessing steps are needed to detect true differences between biological groups. Retention time (RT) alignment, which is required to ensure that ion intensity measurements among multiple LC-MS runs are comparable, is one of the most important yet challenging preprocessing steps. Current alignment approaches estimate RT variability using either single chromatograms or detected peaks, but do not simultaneously take into account the complementary information embedded in the entire LC-MS data. Results: We propose a Bayesian alignment model for LC-MS data analysis. The alignment model provides estimates of the RT variability along with uncertainty measures. The model enables integration of multiple sources of information including internal standards and clustered chromatograms in a mathematically rigorous framework. We apply the model to LC-MS metabolomic, proteomic and glycomic data. The performance of the model is evaluated based on ground-truth data, by measuring correlation of variation, RT difference across runs and peak-matching performance. We demonstrate that Bayesian alignment model improves significantly the RT alignment performance through appropriate integration of relevant information. Availability and implementation: MATLAB code, raw and preprocessed LC-MS data are available at http://omics.georgetown.edu/alignLCMS.html Contact: hwr@georgetown.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24013927

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

PubMed

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

2017-01-06

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

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

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

Qian, Chen; Hettich, Robert L.

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

Optimized Extraction Method To Remove Humic Acid Interferences from Soil Samples Prior to Microbial Proteome Measurements

DOE PAGES

Qian, Chen; Hettich, Robert L.

2017-05-24

The microbial composition and their activities in soil environments play a critical role in organic matter transformation and nutrient cycling, perhaps most specifically with respect to impact on plant growth but also more broadly to global impact on carbon and nitrogen-cycling. Liquid chromatography coupled to high performance mass spectrometry provides a powerful approach to characterize soil microbiomes; however, the limited microbial biomass and the presence of abundant interferences in soil samples present major challenges to soil proteome extraction and subsequent MS measurement. To address some of the major issues, we have designed and optimized an experimental method to enhance microbialmore » proteome extraction concomitant with minimizing the soil-borne humic substances co-extraction from soils. Among the range of interferences, humic substances are often the worst in terms of adversely impacting proteome extraction and mass spectrometry measurement. Our approach employs an in-situ detergent-based microbial lysis / TCA precipitation coupled with an additional acidification precipitation step at the peptide level which efficiently removes humic acids. By combing filtration and pH adjustment of the final peptide solution, the remaining humic acids can be differentially precipitated and removed with a membrane filter, thereby leaving much cleaner proteolytic peptide samples for MS measurement. As a result, this modified method is a reliable and straight-forward protein extraction method that efficiently removes soil-borne humic substances without inducing proteome sample loss or reducing or biasing protein identification in mass spectrometry.« less

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 rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies. PMID:23592955

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

PubMed Central

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

2012-01-01

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

mz5: space- and time-efficient storage of mass spectrometry data sets.

PubMed

Wilhelm, Mathias; Kirchner, Marc; Steen, Judith A J; Steen, Hanno

2012-01-01

Across a host of MS-driven-omics fields, researchers witness the acquisition of ever increasing amounts of high throughput MS data and face the need for their compact yet efficiently accessible storage. Addressing the need for an open data exchange format, the Proteomics Standards Initiative and the Seattle Proteome Center at the Institute for Systems Biology independently developed the mzData and mzXML formats, respectively. In a subsequent joint effort, they defined an ontology and associated controlled vocabulary that specifies the contents of MS data files, implemented as the newer mzML format. All three formats are based on XML and are thus not particularly efficient in either storage space requirements or read/write speed. This contribution introduces mz5, a complete reimplementation of the mzML ontology that is based on the efficient, industrial strength storage backend HDF5. Compared with the current mzML standard, this strategy yields an average file size reduction to ∼54% and increases linear read and write speeds ∼3-4-fold. The format is implemented as part of the ProteoWizard project and is available under a permissive Apache license. Additional information and download links are available from http://software.steenlab.org/mz5.

MaRiMba: A Software Application for Spectral Library-Based MRM Transition List Assembly

PubMed Central

Sherwood, Carly A.; Eastham, Ashley; Lee, Lik Wee; Peterson, Amelia; Eng, Jimmy K.; Shteynberg, David; Mendoza, Luis; Deutsch, Eric W.; Risler, Jenni; Tasman, Natalie; Aebersold, Ruedi; Lam, Henry; Martin, Daniel B.

2009-01-01

Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture. PMID:19603829

Unlocking the proteomic information encoded in MALDI-TOF-MS data used for microbial identification and characterization.

PubMed

Fagerquist, Clifton K

2017-01-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is increasingly utilized as a rapid technique to identify microorganisms including pathogenic bacteria. However, little attention has been paid to the significant proteomic information encoded in the MS peaks that collectively constitute the MS 'fingerprint'. This review/perspective is intended to explore this topic in greater detail in the hopes that it may spur interest and further research in this area. Areas covered: This paper examines the recent literature on utilizing MALDI-TOF for bacterial identification. Critical works highlighting protein biomarker identification of bacteria, arguments for and against protein biomarker identification, proteomic approaches to biomarker identification, emergence of MALDI-TOF-TOF platforms and their use for top-down proteomic identification of bacterial proteins, protein denaturation and its effect on protein ion fragmentation, collision cross-sections and energy deposition during desorption/ionization are also explored. Expert commentary: MALDI-TOF and TOF-TOF mass spectrometry platforms will continue to provide chemical analyses that are rapid, cost-effective and high throughput. These instruments have proven their utility in the taxonomic identification of pathogenic bacteria at the genus and species level and are poised to more fully characterize these microorganisms to the benefit of clinical microbiology, food safety and other fields.

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.

Exposure to an extremely low-frequency electromagnetic field only slightly modifies the proteome of Chromobacterium violaceumATCC 12472

PubMed Central

Baraúna, Rafael A.; Santos, Agenor V.; Graças, Diego A.; Santos, Daniel M.; Ghilardi, Rubens; Pimenta, Adriano M. C.; Carepo, Marta S. P.; Schneider, Maria P.C.; Silva, Artur

2015-01-01

Several studies of the physiological responses of different organisms exposed to extremely low-frequency electromagnetic fields (ELF-EMF) have been described. In this work, we report the minimal effects of in situ exposure to ELF-EMF on the global protein expression of Chromobacterium violaceum using a gel-based proteomic approach. The protein expression profile was only slightly altered, with five differentially expressed proteins detected in the exposed cultures; two of these proteins (DNA-binding stress protein, Dps, and alcohol dehydrogenase) were identified by MS/MS. The enhanced expression of Dps possibly helped to prevent physical damage to DNA. Although small, the changes in protein expression observed here were probably beneficial in helping the bacteria to adapt to the stress generated by the electromagnetic field. PMID:26273227

A label-free internal standard method for the differential analysis of bioactive lupin proteins using nano HPLC-Chip coupled with Ion Trap mass spectrometry.

PubMed

Brambilla, Francesca; Resta, Donatella; Isak, Ilena; Zanotti, Marco; Arnoldi, Anna

2009-01-01

Quantitative proteomics based on MS is useful for pointing out the differences in some food proteomes relevant to human nutrition. Stable isotope label-free (SIF) techniques are suitable for comparing an unlimited number of samples by the use of relatively simple experimental workflows. We have developed an internal standard label-free method based on the intensities of peptide precursor ions from MS/MS spectra, collected in data dependent runs, for the simultaneous qualitative characterization and relative quantification of storage proteins of Lupinus albus seeds in protein extracts of four lupin cultivars (cv Adam, Arés, Lucky, Multitalia). The use of an innovative microfluidic system, the HPLC-Chip, coupled with a classical IT mass spectrometer, has allowed a complete qualitative characterization of all proteins. In particular, the homology search mode has permitted to identify single amino acid substitutions in the sequences of vicilins (beta-conglutin precursor and vicilin-like protein). The MS/MS sequencing of substituted peptides confirms the high heterogeneity of vicilins according to the peculiar characteristics of the vicilin-encoding gene family. Two suitable bioinformatics parameters were optimized for the differential analyses of the main bioactive proteins: the "normalized protein average of common reproducible peptides" (N-ACRP) for gamma-conglutin, which is a homogeneous protein, and the "normalized protein mean peptide spectral intensity" (N-MEAN) for the highly heterogenous class of the vicilins.

Comprehensive Analysis of Low-Molecular-Weight Human Plasma Proteome Using Top-Down Mass Spectrometry.

PubMed

Cheon, Dong Huey; Nam, Eun Ji; Park, Kyu Hyung; Woo, Se Joon; Lee, Hye Jin; Kim, Hee Cheol; Yang, Eun Gyeong; Lee, Cheolju; Lee, Ji Eun

2016-01-04

While human plasma serves as a great source for disease diagnosis, low-molecular-weight (LMW) proteome (<30 kDa) has been shown to contain a rich source of diagnostic biomarkers. Here we employ top-down mass spectrometry to analyze the LMW proteoforms present in four types of human plasma samples pooled from three healthy controls (HCs) without immunoaffinity depletion and with depletion of the top two, six, and seven high-abundance proteins. The LMW proteoforms were first fractionated based on molecular weight using gel-eluted liquid fraction entrapment electrophoresis (GELFrEE). Then, the GELFrEE fractions containing up to 30 kDa were subjected to nanocapillary-LC-MS/MS, and the high-resolution MS and MS/MS data were processed using ProSightPC 3.0. As a result, a total of 442 LMW proteins and cleaved products, including those with post-translational modifications and single amino acid variations, were identified. From additional comparative analysis of plasma samples without immunoaffinity depletion between HCs and colorectal cancer (CRC) patients via top-down approach, tens of LMW proteoforms, including platelet factor 4, were found to show >1.5-fold changes between the plasma samples of HCs and CRC patients, and six of the LMW proteins were verified by Western blot analysis.

Recent Achievements in Characterizing the Histone Code and Approaches to Integrating Epigenomics and Systems Biology.

PubMed

Janssen, K A; Sidoli, S; Garcia, B A

2017-01-01

Functional epigenetic regulation occurs by dynamic modification of chromatin, including genetic material (i.e., DNA methylation), histone proteins, and other nuclear proteins. Due to the highly complex nature of the histone code, mass spectrometry (MS) has become the leading technique in identification of single and combinatorial histone modifications. MS has now overcome antibody-based strategies due to its automation, high resolution, and accurate quantitation. Moreover, multiple approaches to analysis have been developed for global quantitation of posttranslational modifications (PTMs), including large-scale characterization of modification coexistence (middle-down and top-down proteomics), which is not currently possible with any other biochemical strategy. Recently, our group and others have simplified and increased the effectiveness of analyzing histone PTMs by improving multiple MS methods and data analysis tools. This review provides an overview of the major achievements in the analysis of histone PTMs using MS with a focus on the most recent improvements. We speculate that the workflow for histone analysis at its state of the art is highly reliable in terms of identification and quantitation accuracy, and it has the potential to become a routine method for systems biology thanks to the possibility of integrating histone MS results with genomics and proteomics datasets. © 2017 Elsevier Inc. All rights reserved.

pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.

PubMed

Zhou, Xie-Xuan; Zeng, Wen-Feng; Chi, Hao; Luo, Chunjie; Liu, Chao; Zhan, Jianfeng; He, Si-Min; Zhang, Zhifei

2017-12-05

In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.

A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease.

PubMed

Skillbäck, Tobias; Mattsson, Niklas; Hansson, Karl; Mirgorodskaya, Ekaterina; Dahlén, Rahil; van der Flier, Wiesje; Scheltens, Philip; Duits, Floor; Hansson, Oskar; Teunissen, Charlotte; Blennow, Kaj; Zetterberg, Henrik; Gobom, Johan

2017-10-17

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

PubMed

Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2015-07-15

Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Affinity proteomics to study endogenous protein complexes: Pointers, pitfalls, preferences and perspectives

PubMed Central

LaCava, John; Molloy, Kelly R.; Taylor, Martin S.; Domanski, Michal; Chait, Brian T.; Rout, Michael P.

2015-01-01

Dissecting and studying cellular systems requires the ability to specifically isolate distinct proteins along with the co-assembled constituents of their associated complexes. Affinity capture techniques leverage high affinity, high specificity reagents to target and capture proteins of interest along with specifically associated proteins from cell extracts. Affinity capture coupled to mass spectrometry (MS)-based proteomic analyses has enabled the isolation and characterization of a wide range of endogenous protein complexes. Here, we outline effective procedures for the affinity capture of protein complexes, highlighting best practices and common pitfalls. PMID:25757543

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

Evaluation of Three Protein-Extraction Methods for Proteome Analysis of Maize Leaf Midrib, a Compound Tissue Rich in Sclerenchyma Cells.

PubMed

Wang, Ning; Wu, Xiaolin; Ku, Lixia; Chen, Yanhui; Wang, Wei

2016-01-01

Leaf morphology is closely related to the growth and development of maize (Zea mays L.) plants and final kernel production. As an important part of the maize leaf, the midrib holds leaf blades in the aerial position for maximum sunlight capture. Leaf midribs of adult plants contain substantial sclerenchyma cells with heavily thickened and lignified secondary walls and have a high amount of phenolics, making protein extraction and proteome analysis difficult in leaf midrib tissue. In the present study, three protein-extraction methods that are commonly used in plant proteomics, i.e., phenol extraction, TCA/acetone extraction, and TCA/acetone/phenol extraction, were qualitatively and quantitatively evaluated based on 2DE maps and MS/MS analysis using the midribs of the 10th newly expanded leaves of maize plants. Microscopy revealed the existence of substantial amounts of sclerenchyma underneath maize midrib epidermises (particularly abaxial epidermises). The spot-number order obtained via 2DE mapping was as follows: phenol extraction (655) > TCA/acetone extraction (589) > TCA/acetone/phenol extraction (545). MS/MS analysis identified a total of 17 spots that exhibited 2-fold changes in abundance among the three methods (using phenol extraction as a control). Sixteen of the proteins identified were hydrophilic, with GRAVY values ranging from -0.026 to -0.487. For all three methods, we were able to obtain high-quality protein samples and good 2DE maps for the maize leaf midrib. However, phenol extraction produced a better 2DE map with greater resolution between spots, and TCA/acetone extraction produced higher protein yields. Thus, this paper includes a discussion regarding the possible reasons for differential protein extraction among the three methods. This study provides useful information that can be used to select suitable protein extraction methods for the proteome analysis of recalcitrant plant tissues that are rich in sclerenchyma cells.

Development of an open source laboratory information management system for 2-D gel electrophoresis-based proteomics workflow

PubMed Central

Morisawa, Hiraku; Hirota, Mikako; Toda, Tosifusa

2006-01-01

Background In the post-genome era, most research scientists working in the field of proteomics are confronted with difficulties in management of large volumes of data, which they are required to keep in formats suitable for subsequent data mining. Therefore, a well-developed open source laboratory information management system (LIMS) should be available for their proteomics research studies. Results We developed an open source LIMS appropriately customized for 2-D gel electrophoresis-based proteomics workflow. The main features of its design are compactness, flexibility and connectivity to public databases. It supports the handling of data imported from mass spectrometry software and 2-D gel image analysis software. The LIMS is equipped with the same input interface for 2-D gel information as a clickable map on public 2DPAGE databases. The LIMS allows researchers to follow their own experimental procedures by reviewing the illustrations of 2-D gel maps and well layouts on the digestion plates and MS sample plates. Conclusion Our new open source LIMS is now available as a basic model for proteome informatics, and is accessible for further improvement. We hope that many research scientists working in the field of proteomics will evaluate our LIMS and suggest ways in which it can be improved. PMID:17018156

Proteomic analysis of ligamentum flavum from patients with lumbar spinal stenosis.

PubMed

Kamita, Masahiro; Mori, Taiki; Sakai, Yoshihito; Ito, Sadayuki; Gomi, Masahiro; Miyamoto, Yuko; Harada, Atsushi; Niida, Shumpei; Yamada, Tesshi; Watanabe, Ken; Ono, Masaya

2015-05-01

Lumbar spinal stenosis (LSS) is a syndromic degenerative spinal disease and is characterized by spinal canal narrowing with subsequent neural compression causing gait disturbances. Although LSS is a major age-related musculoskeletal disease that causes large decreases in the daily living activities of the elderly, its molecular pathology has not been investigated using proteomics. Thus, we used several proteomic technologies to analyze the ligamentum flavum (LF) of individuals with LSS. Using comprehensive proteomics with strong cation exchange fractionation, we detected 1288 proteins in these LF samples. A GO analysis of the comprehensive proteome revealed that more than 30% of the identified proteins were extracellular. Next, we used 2D image converted analysis of LC/MS to compare LF obtained from individuals with LSS to that obtained from individuals with disc herniation (nondegenerative control). We detected 64 781 MS peaks and identified 1675 differentially expressed peptides derived from 286 proteins. We verified four differentially expressed proteins (fibronectin, serine protease HTRA1, tenascin, and asporin) by quantitative proteomics using SRM/MRM. The present proteomic study is the first to identify proteins from degenerated and hypertrophied LF in LSS, which will help in studying LSS. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Introducing AAA-MS, a rapid and sensitive method for amino acid analysis using isotope dilution and high-resolution mass spectrometry.

PubMed

Louwagie, Mathilde; Kieffer-Jaquinod, Sylvie; Dupierris, Véronique; Couté, Yohann; Bruley, Christophe; Garin, Jérôme; Dupuis, Alain; Jaquinod, Michel; Brun, Virginie

2012-07-06

Accurate quantification of pure peptides and proteins is essential for biotechnology, clinical chemistry, proteomics, and systems biology. The reference method to quantify peptides and proteins is amino acid analysis (AAA). This consists of an acidic hydrolysis followed by chromatographic separation and spectrophotometric detection of amino acids. Although widely used, this method displays some limitations, in particular the need for large amounts of starting material. Driven by the need to quantify isotope-dilution standards used for absolute quantitative proteomics, particularly stable isotope-labeled (SIL) peptides and PSAQ proteins, we developed a new AAA assay (AAA-MS). This method requires neither derivatization nor chromatographic separation of amino acids. It is based on rapid microwave-assisted acidic hydrolysis followed by high-resolution mass spectrometry analysis of amino acids. Quantification is performed by comparing MS signals from labeled amino acids (SIL peptide- and PSAQ-derived) with those of unlabeled amino acids originating from co-hydrolyzed NIST standard reference materials. For both SIL peptides and PSAQ standards, AAA-MS quantification results were consistent with classical AAA measurements. Compared to AAA assay, AAA-MS was much faster and was 100-fold more sensitive for peptide and protein quantification. Finally, thanks to the development of a labeled protein standard, we also extended AAA-MS analysis to the quantification of unlabeled proteins.

Simulation of Two Dimensional Electrophoresis and Tandem Mass Spectrometry for Teaching Proteomics

ERIC Educational Resources Information Center

Fisher, Amanda; Sekera, Emily; Payne, Jill; Craig, Paul

2012-01-01

In proteomics, complex mixtures of proteins are separated (usually by chromatography or electrophoresis) and identified by mass spectrometry. We have created 2DE Tandem MS, a computer program designed for use in the biochemistry, proteomics, or bioinformatics classroom. It contains two simulations--2D electrophoresis and tandem mass spectrometry.…

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

A gel-free proteomic-based method for the characterization of Bordetella pertussis clinical isolates

PubMed Central

Williamson, Yulanda M.; Moura, Hercules; Simmons, Kaneatra; Whitmon, Jennifer; Melnick, Nikkol; Rees, Jon; Woolfitt, Adrian; Schieltz, David M.; Tondella, Maria L.; Ades, Edwin; Sampson, Jacquelyn; Carlone, George; Barr, John R.

2017-01-01

Bordetella pertussis (Bp) is the etiologic agent of pertussis or whooping cough, a highly contagious respiratory disease occurring primarily in infants and young children. Although vaccine preventable, pertussis cases have increased over the years leading researchers to re-evaluate vaccine control strategies. Since bacterial outer membrane proteins, comprising the surfaceome, often play roles in pathogenesis and antibody-mediated immunity, three recent Bp circulating isolates were examined using proteomics to identify any potential changes in surface protein expression. Fractions enriched for outer membrane proteins were digested with trypsin and the peptides analyzed by nano liquid chromatography-electrospray ionization-mass spectrometry (nLC-ESI-MS), followed by database analysis to elucidate the surfaceomes of our three Bp isolates. Furthermore, a less labor intensive non-gel based antibody affinity capture technology in conjunction with MS was employed to assess each Bp strains' immunogenic outer membrane proteins. This novel technique is generally applicable allowing for the identification of immunogenic surface expressed proteins on pertussis and other pathogenic bacteria. PMID:22537821

Exploring novel paths towards protein signatures of chronic pain.

PubMed

Gomez-Varela, David; Schmidt, Manuela

2016-01-01

Pain is a major symptom of many medical conditions and the worldwide number one reason for people to seek medical assistance. It affects the quality of life of patients and poses a heavy financial burden on society with high costs of treatment and lost productivity. Furthermore, the treatment of chronic pain presents a big challenge as pain therapeutics often lack efficacy and exhibit minimal safety profiles. The latter can be largely attributed to the fact that current therapies target molecules with key physiological functions throughout the body. In light of these difficulties, the identification of proteins specifically involved in chronic pain states is of paramount importance for designing selective interventions. Several profiling efforts have been employed with the aim to dissect the molecular underpinnings of chronic pain, both on the level of the transcriptome and proteome. However, generated results are often inconsistent and non-overlapping, which is largely due to inherent technical constraints. A potential solution may be offered by emerging strategies capable of performing standardized and reproducible proteome analysis, such as data-independent acquisition-mass spectrometry (DIA-MS). We have recently demonstrated the applicability of DIA-MS to interrogate chronic pain-related proteome alterations in mice. Based on our results, we aim to provide an overview on DIA-MS and its potential to contribute to the comprehensive characterization of molecular signatures underlying pain pathologies. © The Author(s) 2016.

Surface modified capillary electrophoresis combined with in solution isoelectric focusing and MALDI-TOF/TOF MS: a gel-free multidimensional electrophoresis approach for proteomic profiling--exemplified on human follicular fluid.

PubMed

Hanrieder, Jörg; Zuberovic, Aida; Bergquist, Jonas

2009-04-24

Development of miniaturized analytical tools continues to be of great interest to face the challenges in proteomic analysis of complex biological samples such as human body fluids. In the light of these challenges, special emphasis is put on the speed and simplicity of newly designed technological approaches as well as the need for cost efficiency and low sample consumption. In this study, we present an alternative multidimensional bottom-up approach for proteomic profiling for fast, efficient and sensitive protein analysis in complex biological matrices. The presented setup was based on sample pre-fractionation using microscale in solution isoelectric focusing (IEF) followed by tryptic digestion and subsequent capillary electrophoresis (CE) coupled off-line to matrix assisted laser desorption/ionization time of flight tandem mass spectrometry (MALDI TOF MS/MS). For high performance CE-separation, PolyE-323 modified capillaries were applied to minimize analyte-wall interactions. The potential of the analytical setup was demonstrated on human follicular fluid (hFF) representing a typical complex human body fluid with clinical implication. The obtained results show significant identification of 73 unique proteins (identified at 95% significance level), including mostly acute phase proteins but also protein identities that are well known to be extensively involved in follicular development.

Recent development of mass spectrometry and proteomics applications in identification and typing of bacteria

PubMed Central

Chui, Huixia; Domish, Larissa; Hernandez, Drexler; Wang, Gehua

2016-01-01

Identification and typing of bacteria occupy a large fraction of time and work in clinical microbiology laboratories. With the certification of some MS platforms in recent years, more applications and tests of MS‐based diagnosis methods for bacteria identification and typing have been created, not only on well‐accepted MALDI‐TOF‐MS‐based fingerprint matches, but also on solving the insufficiencies of MALDI‐TOF‐MS‐based platforms and advancing the technology to areas such as targeted MS identification and typing of bacteria, bacterial toxin identification, antibiotics susceptibility/resistance tests, and MS‐based diagnostic method development on unique bacteria such as Clostridium and Mycobacteria. This review summarizes the recent development in MS platforms and applications in bacteria identification and typing of common pathogenic bacteria. PMID:26751976

Software Analysis of Uncorrelated MS1 Peaks for Discovery of Post-Translational Modifications

NASA Astrophysics Data System (ADS)

Pascal, Bruce D.; West, Graham M.; Scharager-Tapia, Catherina; Flefil, Ricardo; Moroni, Tina; Martinez-Acedo, Pablo; Griffin, Patrick R.; Carvalloza, Anthony C.

2015-12-01

The goal in proteomics to identify all peptides in a complex mixture has been largely addressed using various LC MS/MS approaches, such as data dependent acquisition, SRM/MRM, and data independent acquisition instrumentation. Despite these developments, many peptides remain unsequenced, often due to low abundance, poor fragmentation patterns, or data analysis difficulties. Many of the unidentified peptides exhibit strong evidence in high resolution MS1 data and are frequently post-translationally modified, playing a significant role in biological processes. Proteomics Workbench (PWB) software was developed to automate the detection and visualization of all possible peptides in MS1 data, reveal candidate peptides not initially identified, and build inclusion lists for subsequent MS2 analysis to uncover new identifications. We used this software on existing data on the autophagy regulating kinase Ulk1 as a proof of concept for this method, as we had already manually identified a number of phosphorylation sites Dorsey, F. C. et al (J. Proteome. Res. 8(11), 5253-5263 (2009)). PWB found all previously identified sites of phosphorylation. The software has been made freely available at http://www.proteomicsworkbench.com .

The Pacific Northwest National Laboratory library of bacterial and archaeal proteomic biodiversity

DOE PAGES

Payne, Samuel H.; Monroe, Matthew E.; Overall, Christopher C.; ...

2015-08-18

This dataset deposition announces the submission to public repositories of the PNNL Biodiversity Library, a large collection of global proteomics data for 112 bacterial and archaeal organisms. The data comprises 35,162 tandem mass spectrometry (MS/MS) datasets from ~10 years of research. All data has been searched, annotated and organized in a consistent manner to promote reuse by the community. Protein identifications were cross-referenced with KEGG functional annotations which allows for pathway oriented investigation. We present the data as a freely available community resource. A variety of data re-use options are described for computational modeling, proteomics assay design and bioengineering. Instrumentmore » data and analysis files are available at ProteomeXchange via the MassIVE partner repository under the identifiers PXD001860 and MSV000079053.« less

The Pacific Northwest National Laboratory library of bacterial and archaeal proteomic biodiversity

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

Payne, Samuel H.; Monroe, Matthew E.; Overall, Christopher C.

This dataset deposition announces the submission to public repositories of the PNNL Biodiversity Library, a large collection of global proteomics data for 112 bacterial and archaeal organisms. The data comprises 35,162 tandem mass spectrometry (MS/MS) datasets from ~10 years of research. All data has been searched, annotated and organized in a consistent manner to promote reuse by the community. Protein identifications were cross-referenced with KEGG functional annotations which allows for pathway oriented investigation. We present the data as a freely available community resource. A variety of data re-use options are described for computational modeling, proteomics assay design and bioengineering. Instrumentmore » data and analysis files are available at ProteomeXchange via the MassIVE partner repository under the identifiers PXD001860 and MSV000079053.« less

Proteomic analysis of three gonad types of swamp eel reveals genes differentially expressed during sex reversal.

PubMed

Sheng, Yue; Zhao, Wei; Song, Ying; Li, Zhigang; Luo, Majing; Lei, Quan; Cheng, Hanhua; Zhou, Rongjia

2015-05-18

A variety of mechanisms are engaged in sex determination in vertebrates. The teleost fish swamp eel undergoes sex reversal naturally and is an ideal model for vertebrate sexual development. However, the importance of proteome-wide scanning for gonad reversal was not previously determined. We report a 2-D electrophoresis analysis of three gonad types of proteomes during sex reversal. MS/MS analysis revealed a group of differentially expressed proteins during ovary to ovotestis to testis transformation. Cbx3 is up-regulated during gonad reversal and is likely to have a role in spermatogenesis. Rab37 is down-regulated during the reversal and is mainly associated with oogenesis. Both Cbx3 and Rab37 are linked up in a protein network. These datasets in gonadal proteomes provide a new resource for further studies in gonadal development.

Analysis of PNGase F-resistant N-glycopeptides using SugarQb for Proteome Discoverer 2.1 reveals cryptic substrate specificities.

PubMed

Stadlmann, Johannes; Hoi, David M; Taubenschmid, Jasmin; Mechtler, Karl; Penninger, Josef M

2018-05-18

SugarQb (www.imba.oeaw.ac.at/sugarqb) is a freely available collection of computational tools for the automated identification of intact glycopeptides from high-resolution HCD MS/MS data-sets in the Proteome Discoverer environment. We report the migration of SugarQb to the latest and free version of Proteome Discoverer 2.1, and apply it to the analysis of PNGase F-resistant N-glycopeptides from mouse embryonic stem cells. The analysis of intact glycopeptides highlights unexpected technical limitations to PNGase F-dependent glycoproteomic workflows at the proteome level, and warrants a critical re-interpretation of seminal data-sets in the context of N-glycosylation-site prediction. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A peptide resource for the analysis of Staphylococcus aureus in host-pathogen interaction studies.

PubMed

Depke, Maren; Michalik, Stephan; Rabe, Alexander; Surmann, Kristin; Brinkmann, Lars; Jehmlich, Nico; Bernhardt, Jörg; Hecker, Michael; Wollscheid, Bernd; Sun, Zhi; Moritz, Robert L; Völker, Uwe; Schmidt, Frank

2015-11-01

Staphylococcus aureus is an opportunistic human pathogen, which can cause life-threatening disease. Proteome analyses of the bacterium can provide new insights into its pathophysiology and important facets of metabolic adaptation and, thus, aid the recognition of targets for intervention. However, the value of such proteome studies increases with their comprehensiveness. We present an MS-driven, proteome-wide characterization of the strain S. aureus HG001. Combining 144 high precision proteomic data sets, we identified 19 109 peptides from 2088 distinct S. aureus HG001 proteins, which account for 72% of the predicted ORFs. Peptides were further characterized concerning pI, GRAVY, and detectability scores in order to understand the low peptide coverage of 8.7% (19 109 out of 220 245 theoretical peptides). The high quality peptide-centric spectra have been organized into a comprehensive peptide fragmentation library (SpectraST) and used for identification of S. aureus-typic peptides in highly complex host-pathogen interaction experiments, which significantly improved the number of identified S. aureus proteins compared to a MASCOT search. This effort now allows the elucidation of crucial pathophysiological questions in S. aureus-specific host-pathogen interaction studies through comprehensive proteome analysis. The S. aureus-specific spectra resource developed here also represents an important spectral repository for SRM or for data-independent acquisition MS approaches. All MS data have been deposited in the ProteomeXchange with identifier PXD000702 (http://proteomecentral.proteomexchange.org/dataset/PXD000702). © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

HIV-1 Vpr modulates macrophage metabolic pathways: a SILAC-based quantitative analysis.

PubMed

Barrero, Carlos A; Datta, Prasun K; Sen, Satarupa; Deshmane, Satish; Amini, Shohreh; Khalili, Kamel; Merali, Salim

2013-01-01

Human immunodeficiency virus type 1 encoded viral protein Vpr is essential for infection of macrophages by HIV-1. Furthermore, these macrophages are resistant to cell death and are viral reservoir. However, the impact of Vpr on the macrophage proteome is yet to be comprehended. The goal of the present study was to use a stable-isotope labeling by amino acids in cell culture (SILAC) coupled with mass spectrometry-based proteomics approach to characterize the Vpr response in macrophages. Cultured human monocytic cells, U937, were differentiated into macrophages and transduced with adenovirus construct harboring the Vpr gene. More than 600 proteins were quantified in SILAC coupled with LC-MS/MS approach, among which 136 were significantly altered upon Vpr overexpression in macrophages. Quantified proteins were selected and clustered by biological functions, pathway and network analysis using Ingenuity computational pathway analysis. The proteomic data illustrating increase in abundance of enzymes in the glycolytic pathway (pentose phosphate and pyruvate metabolism) was further validated by western blot analysis. In addition, the proteomic data demonstrate down regulation of some key mitochondrial enzymes such as glutamate dehydrogenase 2 (GLUD2), adenylate kinase 2 (AK2) and transketolase (TKT). Based on these observations we postulate that HIV-1 hijacks the macrophage glucose metabolism pathway via the Vpr-hypoxia inducible factor 1 alpha (HIF-1 alpha) axis to induce expression of hexokinase (HK), glucose-6-phosphate dehyrogenase (G6PD) and pyruvate kinase muscle type 2 (PKM2) that facilitates viral replication and biogenesis, and long-term survival of macrophages. Furthermore, dysregulation of mitochondrial glutamate metabolism in macrophages can contribute to neurodegeneration via neuroexcitotoxic mechanisms in the context of NeuroAIDS.

Translational value of liquid chromatography coupled with tandem mass spectrometry-based quantitative proteomics for in vitro-in vivo extrapolation of drug metabolism and transport and considerations in selecting appropriate techniques.

PubMed

Al Feteisi, Hajar; Achour, Brahim; Rostami-Hodjegan, Amin; Barber, Jill

2015-01-01

Drug-metabolizing enzymes and transporters play an important role in drug absorption, distribution, metabolism and excretion and, consequently, they influence drug efficacy and toxicity. Quantification of drug-metabolizing enzymes and transporters in various tissues is therefore essential for comprehensive elucidation of drug absorption, distribution, metabolism and excretion. Recent advances in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) have improved the quantification of pharmacologically relevant proteins. This report presents an overview of mass spectrometry-based methods currently used for the quantification of drug-metabolizing enzymes and drug transporters, mainly focusing on applications and cost associated with various quantitative strategies based on stable isotope-labeled standards (absolute quantification peptide standards, quantification concatemers, protein standards for absolute quantification) and label-free analysis. In mass spectrometry, there is no simple relationship between signal intensity and analyte concentration. Proteomic strategies are therefore complex and several factors need to be considered when selecting the most appropriate method for an intended application, including the number of proteins and samples. Quantitative strategies require appropriate mass spectrometry platforms, yet choice is often limited by the availability of appropriate instrumentation. Quantitative proteomics research requires specialist practical skills and there is a pressing need to dedicate more effort and investment to training personnel in this area. Large-scale multicenter collaborations are also needed to standardize quantitative strategies in order to improve physiologically based pharmacokinetic models.

A Robust Two-Dimensional Separation of Intact Proteins for Bottom-Up Tandem Mass Spectrometry of the Human CSF Proteome

PubMed Central

Bora, Adriana; Anderson, Carol; Bachani, Muznabanu; Nath, Avindra; Cotter, Robert J.

2012-01-01

The cerebrospinal fluid (CSF) is produced in the brain by cells in the choroid plexus at a rate of 500mL/day. It is the only body fluid in direct contact with the brain. Thus, any changes in the CSF composition will reflect pathological processes and make CSF a potential source of biomarkers for different disease states. Proteomics offers a comprehensive view of the proteins found in CSF. In this study, we use a recently developed non-gel based method of sample preparation of CSF followed by liquid chromatography high accuracy mass spectrometry (LC-MS) for MS and MS/MS analyses, allowing unambiguous identification of peptides/proteins. Gel-eluted liquid fraction entrapment electrophoresis (Gelfree) is used to separate a CSF complex protein mixture in 12 user-selectable liquid-phase molecular weight fractions. Using this high throughput workflow we have been able to separate CSF intact proteins over a broad mass range 3.5 kDa-100 kDa with high resolution between 15 kDa and 100 kDa in 2 hours and 40 min. We have completely eliminated albumin and were able to interrogate the low abundance CSF proteins in a highly reproducible manner from different CSF samples in the same time. Using LC-MS as a downstream analysis, we identified 368 proteins using MidiTrap G-10 desalting columns and 166 proteins (including 57 unique proteins) using Zeba spin columns with 5% false discovery rate (FDR). Prostaglandin D2 synthase, Chromogranin A, Apolipoprotein E, Chromogranin B, Secretogranin III, Cystatin C, VGF nerve growth factor, Cadherin 2 are a few of the proteins that were characterized. The Gelfree-LC-MS is a robust method for the analysis of the human proteome that we will use to develop biomarkers for several neurodegenerative diseases and to quantitate these markers using multiple reaction monitoring. PMID:22537003

STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.

PubMed

Piehowski, Paul D; Petyuk, Vladislav A; Sandoval, John D; Burnum, Kristin E; Kiebel, Gary R; Monroe, Matthew E; Anderson, Gordon A; Camp, David G; Smith, Richard D

2013-03-01

For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative Network-Based Recovery Analysis and Proteomic Profiling of Neurological Changes in Valproic Acid-Treated Mice

PubMed Central

2013-01-01

Despite its prominence for characterization of complex mixtures, LC–MS/MS frequently fails to identify many proteins. Network-based analysis methods, based on protein–protein interaction networks (PPINs), biological pathways, and protein complexes, are useful for recovering non-detected proteins, thereby enhancing analytical resolution. However, network-based analysis methods do come in varied flavors for which the respective efficacies are largely unknown. We compare the recovery performance and functional insights from three distinct instances of PPIN-based approaches, viz., Proteomics Expansion Pipeline (PEP), Functional Class Scoring (FCS), and Maxlink, in a test scenario of valproic acid (VPA)-treated mice. We find that the most comprehensive functional insights, as well as best non-detected protein recovery performance, are derived from FCS utilizing real biological complexes. This outstrips other network-based methods such as Maxlink or Proteomics Expansion Pipeline (PEP). From FCS, we identified known biological complexes involved in epigenetic modifications, neuronal system development, and cytoskeletal rearrangements. This is congruent with the observed phenotype where adult mice showed an increase in dendritic branching to allow the rewiring of visual cortical circuitry and an improvement in their visual acuity when tested behaviorally. In addition, PEP also identified a novel complex, comprising YWHAB, NR1, NR2B, ACTB, and TJP1, which is functionally related to the observed phenotype. Although our results suggest different network analysis methods can produce different results, on the whole, the findings are mutually supportive. More critically, the non-overlapping information each provides can provide greater holistic understanding of complex phenotypes. PMID:23557376

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) analysis can contribute to clinical practice with more sensitive biomarkers, thus complementing cytohistological studies in order to aid in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. Here we report a panel of candidate protein biomarkers for adenocarcinoma in BALF. Forty-four proteins showed a fold-change higher than 3.75 among adenocarcinoma patients compared with controls. This report is the first DIA-based quantitative proteomics study to use bronchoalveolar lavage fluid (BALF) as a matrix for discovering potential biomarkers. The results are encouraging in terms of the number of identified and quantified proteins, demonstrating that the analysis of BALF proteins by a SWATH approach is a useful method for the discovery of potential biomarkers of pulmonary diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

Highly efficient proteome analysis with combination of protein pre-fractionation by preparative microscale solution isoelectric focusing and identification by μRPLC-MS/MS with serially coupled long microcolumn.

PubMed

Tao, Dingyin; Sun, Liangliang; Zhu, Guijie; Liang, Yu; Liang, Zhen; Zhang, Lihua; Zhang, Yukui

2011-01-01

To improve the efficiency of proteome analysis, a strategy with the combination of protein pre-fractionation by preparative microscale solution isoelectric focusing, peptide separation by μRPLC with serially coupled long microcolumn and protein identification by ESI-MS/MS was proposed. By preparative microscale solution isoelectric focusing technique, proteins extracted from whole cell lysates of Escherichia coli were fractionated into five chambers divided by isoelectric membranes, respectively with pH range from 3.0 to 4.6, 4.6 to 5.4, 5.4 to 6.2, 6.2 to 7.0 and 7.0 to 10.0. Compared to the traditional on-gel IFF, the protein recovery could be obviously improved to over 95%. Subsequently, the enriched and fractionated proteins in each chamber were digested, and further separated by a 30-cm long serially coupled RP microcolumn. Through the detection by ESI-MS/MS, about 200 proteins were identified in each fraction, and in total 835 proteins were identified even with one-dimensional μRPLC-MS/MS system. All these results demonstrate that by such a combination strategy, highly efficient proteome analysis could be achieved, not only due to the in-solution protein enrichment and pre-fractionation with improved protein recovery but also owing to the increased separation capacity of serially coupled long μRPLC columns. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comprehensive Proteomic Analysis of Human Milk-derived Extracellular Vesicles Unveils a Novel Functional Proteome Distinct from Other Milk Components.

PubMed

van Herwijnen, Martijn J C; Zonneveld, Marijke I; Goerdayal, Soenita; Nolte-'t Hoen, Esther N M; Garssen, Johan; Stahl, Bernd; Maarten Altelaar, A F; Redegeld, Frank A; Wauben, Marca H M

2016-11-01

Breast milk contains several macromolecular components with distinctive functions, whereby milk fat globules and casein micelles mainly provide nutrition to the newborn, and whey contains molecules that can stimulate the newborn's developing immune system and gastrointestinal tract. Although extracellular vesicles (EV) have been identified in breast milk, their physiological function and composition has not been addressed in detail. EV are submicron sized vehicles released by cells for intercellular communication via selectively incorporated lipids, nucleic acids, and proteins. Because of the difficulty in separating EV from other milk components, an in-depth analysis of the proteome of human milk-derived EV is lacking. In this study, an extensive LC-MS/MS proteomic analysis was performed of EV that had been purified from breast milk of seven individual donors using a recently established, optimized density-gradient-based EV isolation protocol. A total of 1963 proteins were identified in milk-derived EV, including EV-associated proteins like CD9, Annexin A5, and Flotillin-1, with a remarkable overlap between the different donors. Interestingly, 198 of the identified proteins are not present in the human EV database Vesiclepedia, indicating that milk-derived EV harbor proteins not yet identified in EV of different origin. Similarly, the proteome of milk-derived EV was compared with that of other milk components. For this, data from 38 published milk proteomic studies were combined in order to construct the total milk proteome, which consists of 2698 unique proteins. Remarkably, 633 proteins identified in milk-derived EV have not yet been identified in human milk to date. Interestingly, these novel proteins include proteins involved in regulation of cell growth and controlling inflammatory signaling pathways, suggesting that milk-derived EVs could support the newborn's developing gastrointestinal tract and immune system. Overall, this study provides an expansion of the whole milk proteome and illustrates that milk-derived EV are macromolecular components with a unique functional proteome. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Peptidomics of Three Bothrops Snake Venoms: Insights Into the Molecular Diversification of Proteomes and Peptidomes*

PubMed Central

Tashima, Alexandre K.; Zelanis, André; Kitano, Eduardo S.; Ianzer, Danielle; Melo, Robson L.; Rioli, Vanessa; Sant'anna, Sávio S.; Schenberg, Ana C. G.; Camargo, Antônio C. M.; Serrano, Solange M. T.

2012-01-01

Snake venom proteomes/peptidomes are highly complex and maintenance of their integrity within the gland lumen is crucial for the expression of toxin activities. There has been considerable progress in the field of venom proteomics, however, peptidomics does not progress as fast, because of the lack of comprehensive venom sequence databases for analysis of MS data. Therefore, in many cases venom peptides have to be sequenced manually by MS/MS analysis or Edman degradation. This is critical for rare snake species, as is the case of Bothrops cotiara (BC) and B. fonsecai (BF), which are regarded as near threatened with extinction. In this study we conducted a comprehensive analysis of the venom peptidomes of BC, BF, and B. jararaca (BJ) using a combination of solid-phase extraction and reversed-phase HPLC to fractionate the peptides, followed by nano-liquid chromatography-tandem MS (LC-MS/MS) or direct infusion electrospray ionization-(ESI)-MS/MS or MALDI-MS/MS analyses. We detected marked differences in the venom peptidomes and identified peptides ranging from 7 to 39 residues in length by de novo sequencing. Forty-four unique sequences were manually identified, out of which 30 are new peptides, including 17 bradykinin-potentiating peptides, three poly-histidine-poly-glycine peptides and interestingly, 10 l-amino acid oxidase fragments. Some of the new bradykinin-potentiating peptides display significant bradykinin potentiating activity. Automated database search revealed fragments from several toxins in the peptidomes, mainly from l-amino acid oxidase, and allowed the determination of the peptide bond specificity of proteinases and amino acid occurrences for the P4-P4′ sites. We also demonstrate that the venom lyophilization/resolubilization process greatly increases the complexity of the peptidome because of the imbalance caused to the venom proteome and the consequent activity of proteinases on venom components. The use of proteinase inhibitors clearly showed different outcomes in the peptidome characterization and suggested that degradomic-peptidomic analysis of snake venoms is highly sensitive to the conditions of sampling procedures. PMID:22869554

Development of a Trypanosoma cruzi strain typing assay using MS2 peptide spectral libraries (Tc-STAMS2)

PubMed Central

de Oliveira, Gilberto Santos; Kawahara, Rebeca; Rosa-Fernandes, Livia; Avila, Carla Cristi; Teixeira, Marta M. G.; Larsen, Martin R.

2018-01-01

Background Chagas disease also known as American trypanosomiasis is caused by the protozoan Trypanosoma cruzi. Over the last 30 years, Chagas disease has expanded from a neglected parasitic infection of the rural population to an urbanized chronic disease, becoming a potentially emergent global health problem. T. cruzi strains were assigned to seven genetic groups (TcI-TcVI and TcBat), named discrete typing units (DTUs), which represent a set of isolates that differ in virulence, pathogenicity and immunological features. Indeed, diverse clinical manifestations (from asymptomatic to highly severe disease) have been attempted to be related to T.cruzi genetic variability. Due to that, several DTU typing methods have been introduced. Each method has its own advantages and drawbacks such as high complexity and analysis time and all of them are based on genetic signatures. Recently, a novel method discriminated bacterial strains using a peptide identification-free, genome sequence-independent shotgun proteomics workflow. Here, we aimed to develop a Trypanosoma cruzi Strain Typing Assay using MS/MS peptide spectral libraries, named Tc-STAMS2. Methods/Principal findings The Tc-STAMS2 method uses shotgun proteomics combined with spectral library search to assign and discriminate T. cruzi strains independently on the genome knowledge. The method is based on the construction of a library of MS/MS peptide spectra built using genotyped T. cruzi reference strains. For identification, the MS/MS peptide spectra of unknown T. cruzi cells are identified using the spectral matching algorithm SpectraST. The Tc-STAMS2 method allowed correct identification of all DTUs with high confidence. The method was robust towards different sample preparations, length of chromatographic gradients and fragmentation techniques. Moreover, a pilot inter-laboratory study showed the applicability to different MS platforms. Conclusions and significance This is the first study that develops a MS-based platform for T. cruzi strain typing. Indeed, the Tc-STAMS2 method allows T. cruzi strain typing using MS/MS spectra as discriminatory features and allows the differentiation of TcI-TcVI DTUs. Similar to genomic-based strategies, the Tc-STAMS2 method allows identification of strains within DTUs. Its robustness towards different experimental and biological variables makes it a valuable complementary strategy to the current T. cruzi genotyping assays. Moreover, this method can be used to identify DTU-specific features correlated with the strain phenotype. PMID:29608573

Development of a Trypanosoma cruzi strain typing assay using MS2 peptide spectral libraries (Tc-STAMS2).

PubMed

de Oliveira, Gilberto Santos; Kawahara, Rebeca; Rosa-Fernandes, Livia; Mule, Simon Ngao; Avila, Carla Cristi; Teixeira, Marta M G; Larsen, Martin R; Palmisano, Giuseppe

2018-04-01

Chagas disease also known as American trypanosomiasis is caused by the protozoan Trypanosoma cruzi. Over the last 30 years, Chagas disease has expanded from a neglected parasitic infection of the rural population to an urbanized chronic disease, becoming a potentially emergent global health problem. T. cruzi strains were assigned to seven genetic groups (TcI-TcVI and TcBat), named discrete typing units (DTUs), which represent a set of isolates that differ in virulence, pathogenicity and immunological features. Indeed, diverse clinical manifestations (from asymptomatic to highly severe disease) have been attempted to be related to T.cruzi genetic variability. Due to that, several DTU typing methods have been introduced. Each method has its own advantages and drawbacks such as high complexity and analysis time and all of them are based on genetic signatures. Recently, a novel method discriminated bacterial strains using a peptide identification-free, genome sequence-independent shotgun proteomics workflow. Here, we aimed to develop a Trypanosoma cruzi Strain Typing Assay using MS/MS peptide spectral libraries, named Tc-STAMS2. The Tc-STAMS2 method uses shotgun proteomics combined with spectral library search to assign and discriminate T. cruzi strains independently on the genome knowledge. The method is based on the construction of a library of MS/MS peptide spectra built using genotyped T. cruzi reference strains. For identification, the MS/MS peptide spectra of unknown T. cruzi cells are identified using the spectral matching algorithm SpectraST. The Tc-STAMS2 method allowed correct identification of all DTUs with high confidence. The method was robust towards different sample preparations, length of chromatographic gradients and fragmentation techniques. Moreover, a pilot inter-laboratory study showed the applicability to different MS platforms. This is the first study that develops a MS-based platform for T. cruzi strain typing. Indeed, the Tc-STAMS2 method allows T. cruzi strain typing using MS/MS spectra as discriminatory features and allows the differentiation of TcI-TcVI DTUs. Similar to genomic-based strategies, the Tc-STAMS2 method allows identification of strains within DTUs. Its robustness towards different experimental and biological variables makes it a valuable complementary strategy to the current T. cruzi genotyping assays. Moreover, this method can be used to identify DTU-specific features correlated with the strain phenotype.

Distinct changes in the proteome profile of endometrial tissues in polycystic ovary syndrome compared with healthy fertile women.

PubMed

Amjadi, Fatemehsadat; Mehdizadeh, Mehdi; Ashrafi, Mahnaz; Nasrabadi, Davood; Taleahmad, Sara; Mirzaei, Mehdi; Gupta, Vivek; Salekdeh, Ghasem Hosseini; Aflatoonian, Reza

2018-04-21

What is the molecular basis of infertility related to uterine dysfunction in women with polycystic ovary syndrome (PCOS)? In this study, differences in protein expression between PCOS and normal endometrium were identified using a proteomic approach based on two-dimensional electrophoresis (2-DE) coupled with mass spectrometry (MS). The proteome of endometrium were analysed during the proliferative (on day 2 or 3 before ovulation, n = 6) and luteal phases (on day 3-5 after ovulation, n = 6) from healthy women and PCOS patients (12-14 days after spontaneous bleeding, n = 12). The differentially expressed proteins were categorized based on the biological process using the DAVID bioinformatics resources. Over 803 reproducible protein spots were detected on gels, and 150 protein spots showed different intensities between PCOS and normal women during the proliferative and luteal phases. MS analysis detected 70 proteins out of 150 spots. For four of the 70 proteins, 14-3-3 protein, annexin A5, SERPINA1 and cathepsin D, 2-DE results were validated and localized by Western blot and immunohistochemistry, respectively, and their gene expression profiles were confirmed by real-time quantitative PCR. The obtained results corresponded to the proteomic analysis. The differentially expressed proteins identified are known to be involved in apoptosis, oxidative stress, inflammation and the cytoskeleton. The processes related to the differentially expressed proteins play important roles in fecundity and fecundability. The present study may reveal the cause of various endometrial aberrations as a limiting factor for achieving pregnancy in PCOS women. Copyright © 2018 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Proteomic profiling of early degenerative retina of RCS rats

PubMed Central

Zhu, Zhi-Hong; Fu, Yan; Weng, Chuan-Huang; Zhao, Cong-Jian; Yin, Zheng-Qin

2017-01-01

AIM To identify the underlying cellular and molecular changes in retinitis pigmentosa (RP). METHODS Label-free quantification-based proteomics analysis, with its advantages of being more economic and consisting of simpler procedures, has been used with increasing frequency in modern biological research. Dystrophic RCS rats, the first laboratory animal model for the study of RP, possess a similar pathological course as human beings with the diseases. Thus, we employed a comparative proteomics analysis approach for in-depth proteome profiling of retinas from dystrophic RCS rats and non-dystrophic congenic controls through Linear Trap Quadrupole - orbitrap MS/MS, to identify the significant differentially expressed proteins (DEPs). Bioinformatics analyses, including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation and upstream regulatory analysis, were then performed on these retina proteins. Finally, a Western blotting experiment was carried out to verify the difference in the abundance of transcript factor E2F1. RESULTS In this study, we identified a total of 2375 protein groups from the retinal protein samples of RCS rats and non-dystrophic congenic controls. Four hundred thirty-four significantly DEPs were selected by Student's t-test. Based on the results of the bioinformatics analysis, we identified mitochondrial dysfunction and transcription factor E2F1 as the key initiation factors in early retinal degenerative process. CONCLUSION We showed that the mitochondrial dysfunction and the transcription factor E2F1 substantially contribute to the disease etiology of RP. The results provide a new potential therapeutic approach for this retinal degenerative disease. PMID:28730077

A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis.

PubMed

Liu, Gang; Cheng, Kai; Lo, Chi Y; Li, Jun; Qu, Jun; Neelamegham, Sriram

2017-11-01

Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MS n proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MS n data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MS n spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Mass Spectrometry-Based GPCR Proteomics: Comprehensive Characterization of the Human Cannabinoid 1 Receptor

PubMed Central

Zvonok, Nikolai; Xu, Wei; Williams, John; Janero, David R.; Krishnan, Srinivasan C.; Makriyannis, Alexandros

2013-01-01

The human cannabinoid 1 receptor (hCB1), a ubiquitous G protein-coupled receptor (GPCR), transmits cannabinergic signals that participate in diverse (patho)physiological processes. Pharmacotherapeutic hCB1 targeting is considered a tractable approach for treating such prevalent diseases as obesity, mood disorders, and drug addiction. The hydrophobic nature of the transmembrane helices of hCB1 presents a formidable difficulty to its direct structural analysis. Comprehensive experimental characterization of functional hCB1 by mass spectrometry (MS) is essential to the targeting of affinity probes that can be used to define directly hCB1 binding domains using a ligand-assisted experimental approach. Such information would greatly facilitate the rational design of hCB1-selective agonists/antagonists with therapeutic potential. We report the first high-coverage MS analysis of the primary sequence of the functional hCB1 receptor, one of the few such comprehensive MS-based analyses of any GPCR. Recombinant C-terminal hexa-histidine-tagged hCB1 (His6-hCB1) was expressed in cultured insect (Spodoptera frugiperda) cells, solubilized by a procedure devised to enhance receptor purity following metal-affinity chromatography, desalted by buffer exchange, and digested in solution with (chymo)-trypsin. “Bottom-up” nanoLC-MS/MS of the (chymo)tryptic digests afforded a degree of overall hCB1 coverage (>94%) thus far reported for only two other GPCRs. This MS-compatible procedure devised for His6-hCB1 sample preparation, incorporating in-solution (chymo)trypsin digestion in the presence of a low concentration of CYMAL-5 detergent, may be applicable to the MS-based proteomic characterization of other GPCRs. This work should help enable future ligand-assisted structural characterization of hCB1 binding motifs at the amino-acid level using rationally designed and targeted covalent cannabinergic probes. PMID:20131867

Characterization of the Proteome of Theobroma cacao Beans by Nano-UHPLC-ESI MS/MS.

PubMed

Scollo, Emanuele; Neville, David; Oruna-Concha, M Jose; Trotin, Martine; Cramer, Rainer

2018-02-01

Cocoa seed storage proteins play an important role in flavour development as aroma precursors are formed from their degradation during fermentation. Major proteins in the beans of Theobroma cacao are the storage proteins belonging to the vicilin and albumin classes. Although both these classes of proteins have been extensively characterized, there is still limited information on the expression and abundance of other proteins present in cocoa beans. This work is the first attempt to characterize the whole cocoa bean proteome by nano-UHPLC-ESI MS/MS analysis using tryptic digests of cocoa bean protein extracts. The results of this analysis show that >1000 proteins could be identified using a species-specific Theobroma cacao database. The majority of the identified proteins were involved with metabolism and energy. Additionally, a significant number of the identified proteins were linked to protein synthesis and processing. Several proteins were also involved with plant response to stress conditions and defence. Albumin and vicilin storage proteins showed the highest intensity values among all detected proteins, although only seven entries were identified as storage proteins. A comparison of MS/MS data searches carried out against larger non-specific databases confirmed that using a species-specific database can increase the number of identified proteins, and at the same time reduce the number of false positives. The results of this work will be useful in developing tools that can allow the comparison of the proteomic profile of cocoa beans from different genotypes and geographic origins. Data are available via ProteomeXchange with identifier PXD005586. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparative proteomic analysis reveals alterations in development and photosynthesis-related proteins in diploid and triploid rice.

PubMed

Wang, Shuzhen; Chen, Wenyue; Yang, Changdeng; Yao, Jian; Xiao, Wenfei; Xin, Ya; Qiu, Jieren; Hu, Weimin; Yao, Haigen; Ying, Wu; Fu, Yaping; Tong, Jianxin; Chen, Zhongzhong; Ruan, Songlin; Ma, Huasheng

2016-09-13

Polyploidy has pivotal influences on rice (Oryza sativa L.) morphology and physiology, and is very important for understanding rice domestication and improving agricultural traits. Diploid (DP) and triploid (TP) rice shows differences in morphological parameters, such as plant height, leaf length, leaf width and the physiological index of chlorophyll content. However, the underlying mechanisms determining these morphological differences are remain to be defined. To better understand the proteomic changes between DP and TP, tandem mass tags (TMT) mass spectrometry (MS)/MS was used to detect the significant changes to protein expression between DP and TP. Results indicated that both photosynthesis and metabolic pathways were highly significantly associated with proteomic alteration between DP and TP based on biological process and pathway enrichment analysis, and 13 higher abundance chloroplast proteins involving in these two pathways were identified in TP. Quantitative real-time PCR analysis demonstrated that 5 of the 13 chloroplast proteins ATPF, PSAA, PSAB, PSBB and RBL in TP were higher abundance compared with those in DP. This study integrates morphology, physiology and proteomic profiling alteration of DP and TP to address their underlying different molecular mechanisms. Our finding revealed that ATPF, PSAA, PSAB, PSBB and RBL can induce considerable expression changes in TP and may affect the development and growth of rice through photosynthesis and metabolic pathways.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments.

PubMed

MacLean, Brendan; Tomazela, Daniela M; Shulman, Nicholas; Chambers, Matthew; Finney, Gregory L; Frewen, Barbara; Kern, Randall; Tabb, David L; Liebler, Daniel C; MacCoss, Michael J

2010-04-01

Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. It is open source and freely available for academic and commercial use. The Skyline user interface simplifies the development of mass spectrometer methods and the analysis of data from targeted proteomics experiments performed using selected reaction monitoring (SRM). Skyline supports using and creating MS/MS spectral libraries from a wide variety of sources to choose SRM filters and verify results based on previously observed ion trap data. Skyline exports transition lists to and imports the native output files from Agilent, Applied Biosystems, Thermo Fisher Scientific and Waters triple quadrupole instruments, seamlessly connecting mass spectrometer output back to the experimental design document. The fast and compact Skyline file format is easily shared, even for experiments requiring many sample injections. A rich array of graphs displays results and provides powerful tools for inspecting data integrity as data are acquired, helping instrument operators to identify problems early. The Skyline dynamic report designer exports tabular data from the Skyline document model for in-depth analysis with common statistical tools. Single-click, self-updating web installation is available at http://proteome.gs.washington.edu/software/skyline. This web site also provides access to instructional videos, a support board, an issues list and a link to the source code project.

Heat-Treatment-Responsive Proteins in Different Developmental Stages of Tomato Pollen Detected by Targeted Mass Accuracy Precursor Alignment (tMAPA).

PubMed

Chaturvedi, Palak; Doerfler, Hannes; Jegadeesan, Sridharan; Ghatak, Arindam; Pressman, Etan; Castillejo, Maria Angeles; Wienkoop, Stefanie; Egelhofer, Volker; Firon, Nurit; Weckwerth, Wolfram

2015-11-06

Recently, we have developed a quantitative shotgun proteomics strategy called mass accuracy precursor alignment (MAPA). The MAPA algorithm uses high mass accuracy to bin mass-to-charge (m/z) ratios of precursor ions from LC-MS analyses, determines their intensities, and extracts a quantitative sample versus m/z ratio data alignment matrix from a multitude of samples. Here, we introduce a novel feature of this algorithm that allows the extraction and alignment of proteotypic peptide precursor ions or any other target peptide from complex shotgun proteomics data for accurate quantification of unique proteins. This strategy circumvents the problem of confusing the quantification of proteins due to indistinguishable protein isoforms by a typical shotgun proteomics approach. We applied this strategy to a comparison of control and heat-treated tomato pollen grains at two developmental stages, post-meiotic and mature. Pollen is a temperature-sensitive tissue involved in the reproductive cycle of plants and plays a major role in fruit setting and yield. By LC-MS-based shotgun proteomics, we identified more than 2000 proteins in total for all different tissues. By applying the targeted MAPA data-processing strategy, 51 unique proteins were identified as heat-treatment-responsive protein candidates. The potential function of the identified candidates in a specific developmental stage is discussed.

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.

Genome-wide identification of the subcellular localization of the Escherichia coli B proteome using experimental and computational methods.

PubMed

Han, Mee-Jung; Yun, Hongseok; Lee, Jeong Wook; Lee, Yu Hyun; Lee, Sang Yup; Yoo, Jong-Shin; Kim, Jin Young; Kim, Jihyun F; Hur, Cheol-Goo

2011-04-01

Escherichia coli K-12 and B strains have most widely been employed for scientific studies as well as industrial applications. Recently, the complete genome sequences of two representative descendants of E. coli B strains, REL606 and BL21(DE3), have been determined. Here, we report the subproteome reference maps of E. coli B REL606 by analyzing cytoplasmic, periplasmic, inner and outer membrane, and extracellular proteomes based on the genome information using experimental and computational approaches. Among the total of 3487 spots, 651 proteins including 410 non-redundant proteins were identified and characterized by 2-DE and LC-MS/MS; they include 440 cytoplasmic, 45 periplasmic, 50 inner membrane, 61 outer membrane, and 55 extracellular proteins. In addition, subcellular localizations of all 4205 ORFs of E. coli B were predicted by combined computational prediction methods. The subcellular localizations of 1812 (43.09%) proteins of currently unknown function were newly assigned. The results of computational prediction were also compared with the experimental results, showing that overall precision and recall were 92.16 and 92.16%, respectively. This work represents the most comprehensive analyses of the subproteomes of E. coli B, and will be useful as a reference for proteome profiling studies under various conditions. The complete proteome data are available online (http://ecolib.kaist.ac.kr). Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The proteome pattern cGvHD_MS14 allows early and accurate prediction of chronic GvHD after allogeneic stem cell transplantation.

PubMed

Weissinger, E M; Human, C; Metzger, J; Hambach, L; Wolf, D; Greinix, H T; Dickinson, A M; Mullen, W; Jonigk, D; Kuzmina, Z; Kreipe, H; Schweier, P; Böhm, O; Türüchanow, I; Ihlenburg-Schwarz, D; Raad, J; Durban, A; Schiemann, M; Könecke, C; Diedrich, H; Holler, E; Beutel, G; Krauter, J; Ganser, A; Stadler, M

2017-03-01

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) may be curative, but is associated with significant morbidity and mortality. Chronic graft-versus-host disease (cGvHD), characterized by inflammation and fibrosis of multiple target organs, considerably contributes to the morbidity and mortality even years after allo-HSCT. Diagnosis of cGvHD is based on clinical features and histology of biopsies. Here, we report the generation of a urinary cGvHD-specific proteome-pattern (cGvHD_MS14) established by capillary electrophoresis-mass spectrometry to predict onset and severity of cGvHD as an unbiased laboratory test. cGvHD_MS14 was evaluated on samples from 412 patients collected prospectively in four transplant centers. Sensitivity and specificity was 84 and 76% by cGvHD_MS14 classification. Sensitivity further increased to 93% by combination of cGvHD_MS14 with relevant clinical variables to a logistic regression model. cGvHD was predicted up to 55 days prior to clinical diagnosis. Acute GvHD is not recognized by cGvHD_MS14. cGvHD_MS14 consists of 14 differentially excreted peptides, six of those have been sequenced to date and are fragments from thymosin β-4, eukaryotic translation initiation factor 4γ2, fibrinogen β-chain or collagens. In conclusion, the cGvHD_MS14-pattern allows early, highly sensitive and specific prediction of cGvHD as an independent diagnostic criterion of clinical diagnosis potentially allowing early therapeutic intervention.

A Comparative Analysis of Computational Approaches to Relative Protein Quantification Using Peptide Peak Intensities in Label-free LC-MS Proteomics Experiments

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

Matzke, Melissa M.; Brown, Joseph N.; Gritsenko, Marina A.

2013-02-01

Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred frommore » one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.« less

A new dimethyl labeling-based SID-MRM-MS method and its application to three proteases involved in insulin maturation.

PubMed

Cheng, Dongwan; Zheng, Li; Hou, Junjie; Wang, Jifeng; Xue, Peng; Yang, Fuquan; Xu, Tao

2015-01-01

The absolute quantification of target proteins in proteomics involves stable isotope dilution coupled with multiple reactions monitoring mass spectrometry (SID-MRM-MS). The successful preparation of stable isotope-labeled internal standard peptides is an important prerequisite for the SID-MRM absolute quantification methods. Dimethyl labeling has been widely used in relative quantitative proteomics and it is fast, simple, reliable, cost-effective, and applicable to any protein sample, making it an ideal candidate method for the preparation of stable isotope-labeled internal standards. MRM mass spectrometry is of high sensitivity, specificity, and throughput characteristics and can quantify multiple proteins simultaneously, including low-abundance proteins in precious samples such as pancreatic islets. In this study, a new method for the absolute quantification of three proteases involved in insulin maturation, namely PC1/3, PC2 and CPE, was developed by coupling a stable isotope dimethyl labeling strategy for internal standard peptide preparation with SID-MRM-MS quantitative technology. This method offers a new and effective approach for deep understanding of the functional status of pancreatic β cells and pathogenesis in diabetes.

Comparative Proteomic Analysis of Two Varieties of Genetically Modified (GM) Embrapa 5.1 Common Bean (Phaseolus vulgaris L.) and Their Non-GM Counterparts.

PubMed

Balsamo, Geisi M; Valentim-Neto, Pedro A; Mello, Carla S; Arisi, Ana C M

2015-12-09

The genetically modified (GM) common bean event Embrapa 5.1 was commercially approved in Brazil in 2011; it is resistant to golden mosaic virus infection. In the present work grain proteome profiles of two Embrapa 5.1 common bean varieties, Pérola and Pontal, and their non-GM counterparts were compared by two-dimensional gel electrophoresis (2-DE) followed by mass spectrometry (MS). Analyses detected 23 spots differentially accumulated between GM Pérola and non-GM Pérola and 21 spots between GM Pontal and non-GM Pontal, although they were not the same proteins in Pérola and Pontal varieties, indicating that the variability observed may not be due to the genetic transformation. Among them, eight proteins were identified in Pérola varieties, and four proteins were identified in Pontal. Moreover, we applied principal component analysis (PCA) on 2-DE data, and variation between varieties was explained in the first two principal components. This work provides a first 2-DE-MS/MS-based analysis of Embrapa 5.1 common bean grains.

Systematic assessment of survey scan and MS2-based abundance strategies for label-free quantitative proteomics using high-resolution MS data.

PubMed

Tu, Chengjian; Li, Jun; Sheng, Quanhu; Zhang, Ming; Qu, Jun

2014-04-04

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R(2) > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery.

Systematic Assessment of Survey Scan and MS2-Based Abundance Strategies for Label-Free Quantitative Proteomics Using High-Resolution MS Data

PubMed Central

2015-01-01

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R2 > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery. PMID:24635752

Mass spectrometry data from label-free quantitative proteomic analysis of harmless and pathogenic strains of infectious microalgae, Prototheca spp.

PubMed

Murugaiyan, Jayaseelan; Eravci, Murat; Weise, Christoph; Roesler, Uwe

2017-06-01

Here, we provide the dataset associated with our research article 'label-free quantitative proteomic analysis of harmless and pathogenic strains of infectious microalgae, Prototheca spp.' (Murugaiyan et al., 2017) [1]. This dataset describes liquid chromatography-mass spectrometry (LC-MS)-based protein identification and quantification of a non-infectious strain, Prototheca zopfii genotype 1 and two strains associated with severe and mild infections, respectively, P. zopfii genotype 2 and Prototheca blaschkeae . Protein identification and label-free quantification was carried out by analysing MS raw data using the MaxQuant-Andromeda software suit. The expressional level differences of the identified proteins among the strains were computed using Perseus software and the results were presented in [1]. This DiB provides the MaxQuant output file and raw data deposited in the PRIDE repository with the dataset identifier PXD005305.

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

Simplifying the human serum proteome for discriminating patients with bipolar disorder of other psychiatry conditions.

PubMed

de Jesus, Jemmyson Romário; Galazzi, Rodrigo Moretto; de Lima, Tatiani Brenelli; Banzato, Cláudio Eduardo Muller; de Almeida Lima E Silva, Luiz Fernando; de Rosalmeida Dantas, Clarissa; Gozzo, Fábio Cézar; Arruda, Marco Aurélio Zezzi

2017-12-01

An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Proteome-wide analysis of Anopheles culicifacies mosquito midgut: new insights into the mechanism of refractoriness.

PubMed

Vijay, Sonam; Rawal, Ritu; Kadian, Kavita; Singh, Jagbir; Adak, Tridibesh; Sharma, Arun

2018-05-08

Midgut invasion, a major bottleneck for malaria parasites transmission is considered as a potential target for vector-parasite interaction studies. New intervention strategies are required to explore the midgut proteins and their potential role in refractoriness for malaria control in Anopheles mosquitoes. To better understand the midgut functional proteins of An. culicifacies susceptible and refractory species, proteomic approaches coupled with bioinformatics analysis is an effective means in order to understand the mechanism of refractoriness. In the present study, an integrated in solution- in gel trypsin digestion approach, along with Isobaric tag for relative and absolute quantitation (iTRAQ)-Liquid chromatography/Mass spectrometry (LC/MS/MS) and data mining were performed to identify the proteomic profile and differentially expressed proteins in Anopheles culicifacies susceptible species A and refractory species B. Shot gun proteomics approaches led to the identification of 80 proteins in An. culicifacies susceptible species A and 92 in refractory species B and catalogue was prepared. iTRAQ based proteomic analysis identified 48 differentially expressed proteins from total 130 proteins. Of these, 41 were downregulated and 7 were upregulated in refractory species B in comparison to susceptible species A. We report that the altered midgut proteins identified in naturally refractory mosquitoes are involved in oxidative phosphorylation, antioxidant and proteolysis process that may suggest their role in parasite growth inhibition. Furthermore, real time polymerase chain reaction (PCR) analysis of few proteins indicated higher expression of iTRAQ upregulated protein in refractory species than susceptible species. This study elucidates the first proteome of the midguts of An. culicifacies sibling species that attempts to analyze unique proteogenomic interactions to provide insights for better understanding of the mechanism of refractoriness. Functional implications of these upregulated proteins in refractory species may reflect the phenotypic characteristics of the mosquitoes and will improve our understandings of blood meal digestion process, parasite vector interactions and proteomes of other vectors of human diseases for development of novel vector control strategies.

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

The Escherichia coli O157:H7 bovine rumen fluid proteome reflects adaptive bacterial responses.

PubMed

Kudva, Indira T; Stanton, Thaddeus B; Lippolis, John D

2014-02-21

To obtain insights into Escherichia coli O157:H7 (O157) survival mechanisms in the bovine rumen, we defined the growth characteristics and proteome of O157 cultured in rumen fluid (RF; pH 6.0-7.2 and low volatile fatty acid content) obtained from rumen-fistulated cattle fed low protein content "maintenance diet" under diverse in vitro conditions. Bottom-up proteomics (LC-MS/MS) of whole cell-lysates of O157 cultured under anaerobic conditions in filter-sterilized RF (fRF; devoid of normal ruminal microbiota) and nutrient-depleted and filtered RF (dRF) resulted in an anaerobic O157 fRF-and dRF-proteome comprising 35 proteins functionally associated with cell structure, motility, transport, metabolism and regulation, but interestingly, not with O157 virulence. Shotgun proteomics-based analysis using isobaric tags for relative and absolute quantitation used to further study differential protein expression in unfiltered RF (uRF; RF containing normal rumen microbial flora) complemented these results. Our results indicate that in the rumen, the first anatomical compartment encountered by this human pathogen within the cattle gastrointestinal tract (GIT), O157 initiates a program of specific gene expression that enables it to adapt to the in vivo environment, and successfully transit to its colonization sites in the bovine GIT. Further experiments in vitro using uRF from animals fed different diets and with additional O157 strains, and in vivo using rumen-fistulated cattle will provide a comprehensive understanding of the adaptive mechanisms involved, and help direct evolution of novel modalities for blocking O157 infection of cattle.

Biomarker Candidates of Chlamydophila pneumoniae Proteins and Protein Fragments Identified by Affinity-Proteomics Using FTICR-MS and LC-MS/MS

NASA Astrophysics Data System (ADS)

Susnea, Iuliana; Bunk, Sebastian; Wendel, Albrecht; Hermann, Corinna; Przybylski, Michael

2011-04-01

We report here an affinity-proteomics approach that combines 2D-gel electrophoresis and immunoblotting with high performance mass spectrometry to the identification of both full length protein antigens and antigenic fragments of Chlamydophila pneumoniae (C. pneumoniae). The present affinity-mass spectrometry approach effectively utilized high resolution FTICR mass spectrometry and LC-tandem-MS for protein identification, and enabled the identification of several new highly antigenic C. pneumoniae proteins that were not hitherto reported or previously detected only in other Chlamydia species, such as Chlamydia trachomatis. Moreover, high resolution affinity-MS provided the identification of several neo-antigenic protein fragments containing N- and C-terminal, and central domains such as fragments of the membrane protein Pmp21 and the secreted chlamydial proteasome-like factor (Cpaf), representing specific biomarker candidates.