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.

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).

Shotgun proteomics of plant plasma membrane and microdomain proteins using nano-LC-MS/MS.

PubMed

Takahashi, Daisuke; Li, Bin; Nakayama, Takato; Kawamura, Yukio; Uemura, Matsuo

2014-01-01

Shotgun proteomics allows the comprehensive analysis of proteins extracted from plant cells, subcellular organelles, and membranes. Previously, two-dimensional gel electrophoresis-based proteomics was used for mass spectrometric analysis of plasma membrane proteins. In order to get comprehensive proteome profiles of the plasma membrane including highly hydrophobic proteins with a number of transmembrane domains, a mass spectrometry-based shotgun proteomics method using nano-LC-MS/MS for proteins from the plasma membrane proteins and plasma membrane microdomain fraction is described. The results obtained are easily applicable to label-free protein semiquantification.

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 ...

Preprocessing and Analysis of LC-MS-Based Proteomic Data

PubMed Central

Tsai, Tsung-Heng; Wang, Minkun; Ressom, Habtom W.

2016-01-01

Liquid chromatography coupled with mass spectrometry (LC-MS) has been widely used for profiling protein expression levels. This chapter is focused on LC-MS data preprocessing, which is a crucial step in the analysis of LC-MS based proteomics. We provide a high-level overview, highlight associated challenges, and present a step-by-step example for analysis of data from LC-MS based untargeted proteomic study. Furthermore, key procedures and relevant issues with the subsequent analysis by multiple reaction monitoring (MRM) are discussed. PMID:26519169

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

PubMed Central

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

2008-01-01

Background Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. Results We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. Conclusion The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field. PMID:19087345

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.

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.

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.

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

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

PubMed Central

Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P.; Monroe, Matthew E.; Orton, Daniel J.; Ibrahim, Yehia M.; Gritsenko, Marina A.; Clauss, Therese R. W.; Shukla, Anil K.; Moore, Ronald J.; Purvine, Samuel O.; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S.; Smith, Richard D.

2016-01-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. PMID:27670688

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.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

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.

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.

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

Cancer.gov

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

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.

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

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

PubMed

Burnum-Johnson, Kristin E; Nie, Song; Casey, Cameron P; Monroe, Matthew E; Orton, Daniel J; Ibrahim, Yehia M; Gritsenko, Marina A; Clauss, Therese R W; Shukla, Anil K; Moore, Ronald J; Purvine, Samuel O; Shi, Tujin; Qian, Weijun; Liu, Tao; Baker, Erin S; Smith, Richard D

2016-12-01

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Effect of Genetic Database Comprehensiveness on Fractional Proteomics of Escherichia coli O157:H7

DTIC Science & Technology

2014-01-01

proteins would be observed in the extracellular fraction. 15. SUBJECT TERMS Escherichia coli O157:H7 Liquid chromatography Mass spectrometry...Preparation ...............1 2.2 Liquid Chromatography /Mass Spectrometry Sample Preparation ....................2 2.3 Liquid Chromatography /Mass... Chromatography /Mass Spectrometry Sample Preparation. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-MS/MS) in a similar

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

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.

File formats commonly used in mass spectrometry proteomics.

PubMed

Deutsch, Eric W

2012-12-01

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

TUBEs-Mass Spectrometry for Identification and Analysis of the Ubiquitin-Proteome.

PubMed

Azkargorta, Mikel; Escobes, Iraide; Elortza, Felix; Matthiesen, Rune; Rodríguez, Manuel S

2016-01-01

Mass spectrometry (MS) has become the method of choice for the large-scale analysis of protein ubiquitylation. There exist a number of proposed methods for mapping ubiquitin sites, each with different pros and cons. We present here a protocol for the MS analysis of the ubiquitin-proteome captured by TUBEs and subsequent data analysis. Using dedicated software and algorithms, specific information on the presence of ubiquitylated peptides can be obtained from the MS search results. In addition, a quantitative and functional analysis of the ubiquitylated proteins and their interacting partners helps to unravel the biological and molecular processes they are involved in.

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.

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

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

PODCAST: From Lost in Translation to Paradise Found: Enabling Protein Biomarker Method Transfer by Mass Spectrometry | Office of Cancer Clinical Proteomics Research

Cancer.gov

Translation of novel biomarkers into clinical care for the evaluation of therapeutic safety and efficacy has been slow, partly attributable to the cost and complexity of immunoassay development.  The potential for liquid chromatography-tandem mass spectrometry (LC-MS/MS) to streamline the translation of novel protein biomarkers is profound.  Drs. Henry Rodriguez and Andrew Hoofnagle discuss what the future may be for clinical proteomics. This is an American Association for Clinical Chemistry (AACC) podcast.

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.

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

Application of Tandem Two-Dimensional Mass Spectrometry for Top-Down Deep Sequencing of Calmodulin

NASA Astrophysics Data System (ADS)

Floris, Federico; Chiron, Lionel; Lynch, Alice M.; Barrow, Mark P.; Delsuc, Marc-André; O'Connor, Peter B.

2018-06-01

Two-dimensional mass spectrometry (2DMS) involves simultaneous acquisition of the fragmentation patterns of all the analytes in a mixture by correlating their precursor and fragment ions by modulating precursor ions systematically through a fragmentation zone. Tandem two-dimensional mass spectrometry (MS/2DMS) unites the ultra-high accuracy of Fourier transform ion cyclotron resonance (FT-ICR) MS/MS and the simultaneous data-independent fragmentation of 2DMS to achieve extensive inter-residue fragmentation of entire proteins. 2DMS was recently developed for top-down proteomics (TDP), and applied to the analysis of calmodulin (CaM), reporting a cleavage coverage of about 23% using infrared multiphoton dissociation (IRMPD) as fragmentation technique. The goal of this work is to expand the utility of top-down protein analysis using MS/2DMS in order to extend the cleavage coverage in top-down proteomics further into the interior regions of the protein. In this case, using MS/2DMS, the cleavage coverage of CaM increased from 23% to 42%.

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.

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

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.

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.

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

File Formats Commonly Used in Mass Spectrometry Proteomics*

PubMed Central

Deutsch, Eric W.

2012-01-01

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

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

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...

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

Application of Tandem Two-Dimensional Mass Spectrometry for Top-Down Deep Sequencing of Calmodulin.

PubMed

Floris, Federico; Chiron, Lionel; Lynch, Alice M; Barrow, Mark P; Delsuc, Marc-André; O'Connor, Peter B

2018-06-04

Two-dimensional mass spectrometry (2DMS) involves simultaneous acquisition of the fragmentation patterns of all the analytes in a mixture by correlating their precursor and fragment ions by modulating precursor ions systematically through a fragmentation zone. Tandem two-dimensional mass spectrometry (MS/2DMS) unites the ultra-high accuracy of Fourier transform ion cyclotron resonance (FT-ICR) MS/MS and the simultaneous data-independent fragmentation of 2DMS to achieve extensive inter-residue fragmentation of entire proteins. 2DMS was recently developed for top-down proteomics (TDP), and applied to the analysis of calmodulin (CaM), reporting a cleavage coverage of about ~23% using infrared multiphoton dissociation (IRMPD) as fragmentation technique. The goal of this work is to expand the utility of top-down protein analysis using MS/2DMS in order to extend the cleavage coverage in top-down proteomics further into the interior regions of the protein. In this case, using MS/2DMS, the cleavage coverage of CaM increased from ~23% to ~42%. Graphical Abstract Two-dimensional mass spectrometry, when applied to primary fragment ions from the source, allows deep-sequencing of the protein calmodulin.

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.

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.

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.

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

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

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

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

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.

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.

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.

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.

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.

Mass spectrometry and renal calculi

PubMed Central

Purcarea, VL; Sisu, I; Sisu, E

2010-01-01

The present review represents a concise and complete survey of the literature covering 2004–2009, concerning the mass spectrometric techniques involved in the structural investigation of renal calculi. After a short presentation of the fundamental mass spectrometric techniques (MALDI–TOF, QTOF, MS–MS) as well as hyphenated methods (GC–MS, LC–MS, CE–MS), an extensive study of the urinary proteome analysis as well as the detection and quantification by mass spectrometry of toxins, drugs and metabolites from renal calculi is presented. PMID:20968197

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

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.

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

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.

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.

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.

[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.

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

Top-down proteomic identification of bacterial protein biomarkers and toxins using MALDI-TOF-TOF-MS/MS and post-source decay

USDA-ARS?s Scientific Manuscript database

Matrix-assisted laser desorption/ionization time-of-flight-time-of-flight mass spectrometry(MALDI-TOF-TOF-MS)has provided new capabilities for the rapid identification of digested and non-digested proteins. The tandem (MS/MS) capability of TOF-TOF instruments allows precursor ion selection/isolation...

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.

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.

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

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.

Unlocking the proteomic information encoded in MALDI-TOF-MS data used for microbial identification and characterization

USDA-ARS?s Scientific Manuscript database

Introduction: Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS)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 ...

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.

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

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

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.

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

PubMed

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

2013-01-04

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

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.

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

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.

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

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.

Analysis of proteomic differences between liquefied after-cataracts and normal lenses using two-dimensional gel electrophoresis and mass spectrometry

PubMed Central

Ge, Jia-Jia; Huang, Yu-Sen

2017-01-01

AIM To analyze and identify the proteomic differences between liquefied after-cataracts and normal lenses by means of liquefied chromatography-tandem mass spectrometry (LC-MS/MS). METHODS Three normal lenses and three liquefied after-cataracts were exposed to depolymerizing reagents to extract the total proteins. Protein concentrations were separated using two-dimensional gel electrophoresis (2-DE). The digitized images obtained with a GS-800 scanner were then analyzed with PDQuest7.0 software to detect the differentially-expressed protein spots. These protein spots were cut from the gel using a proteome work spot cutter and subjected to in-gel digestion with trypsin. The digested peptide separation was conducted by LC-MS/MS. RESULTS The 2-DE maps showed that lens proteins were in a pH range of 3-10 with a relative molecular weight of 21-70 kD. The relative molecular weight of the more abundant proteins was localized at 25-50 kD, and the isoelectric points were found to lie between PI 4-9. The maps also showed that the protein level within the liquefied after-cataracts was at 29 points and significantly lower than in normal lenses. The 29 points were identified by LC-MS/MS, and ten of these proteins were identified by mass spectrometry and database queries: beta-crystallin B1, glyceraldehyde-3-phosphate dehydrogenase, carbonyl reductase (NADPH) 1, cDNA FLJ55253, gamma-crystallin D, GAS2-like protein 3, sorbitol dehydrogenase, DNA FLJ60282, phosphoglycerate kinase, and filensin. CONCLUSION The level of the ten proteins may play an important role in the development of liquefied after-cataracts. PMID:28944190

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

Proteomics in Heart Failure: Top-down or Bottom-up?

PubMed Central

Gregorich, Zachery R.; Chang, Ying-Hua; Ge, Ying

2014-01-01

Summary The pathophysiology of heart failure (HF) is diverse, owing to multiple etiologies and aberrations in a number of cellular processes. Therefore, it is essential to understand how defects in the molecular pathways that mediate cellular responses to internal and external stressors function as a system to drive the HF phenotype. Mass spectrometry (MS)-based proteomics strategies have great potential for advancing our understanding of disease mechanisms at the systems level because proteins are the effector molecules for all cell functions and, thus, are directly responsible for determining cell phenotype. Two MS-based proteomics strategies exist: peptide-based bottom-up and protein-based top-down proteomics—each with its own unique strengths and weaknesses for interrogating the proteome. In this review, we will discuss the advantages and disadvantages of bottom-up and top-down MS for protein identification, quantification, and the analysis of post-translational modifications, as well as highlight how both of these strategies have contributed to our understanding of the molecular and cellular mechanisms underlying HF. Additionally, the challenges associated with both proteomics approaches will be discussed and insights will be offered regarding the future of MS-based proteomics in HF research. PMID:24619480

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

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.

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.

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…

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

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

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.

Analysis of proteins using DIGE and MALDI mass spectrometry

EPA Science Inventory

In this work the sensitivity of the quantitative proteomics approach 2D-DIGE/MS (twoDimensional Difference Gel Electrophoresis / Mass Spectrometry) was tested by detecting decreasing amounts of a specific protein at the low picomole and sub-picomole range. Sensitivity of the 2D-D...

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

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

"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.

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

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

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

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.

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.

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.

Proteomic profiling of human pleural effusion using two-dimensional nano liquid chromatography tandem mass spectrometry.

PubMed

Tyan, Yu-Chang; Wu, Hsin-Yi; Lai, Wu-Wei; Su, Wu-Chou; Liao, Pao-Chi

2005-01-01

Pleural effusion, an accumulation of pleural fluid, contains proteins originated from plasma filtrate and, especially when tissues are damaged, parenchyma interstitial spaces of lungs and/or other organs. This study details protein profiles in human pleural effusion from 43 lung adenocarcinoma patients by a two-dimensional nano-high performance liquid chromatography electrospray ionization tandem mass spectrometry (2D nano-HPLC-ESI-MS/MS) system. The experimental results revealed the identification of 1415 unique proteins from human pleural effusion. Among these 124 proteins identified with higher confidence levels, some proteins have not been reported in plasma and may represent proteins specifically present in pleural effusion. These proteins are valuable for mass identification of differentially expressed proteins involved in proteomics database and screening biomarker to further study in human lung adenocarcinoma. The significance of the use of proteomics analysis of human pleural fluid for the search of new lung cancer marker proteins, and for their simultaneous display and analysis in patients suffering from lung disorders has been examined.

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.

Hydrophobic Interaction Chromatography for Bottom-Up Proteomics Analysis of Single Proteins and Protein Complexes.

PubMed

Rackiewicz, Michal; Große-Hovest, Ludger; Alpert, Andrew J; Zarei, Mostafa; Dengjel, Jörn

2017-06-02

Hydrophobic interaction chromatography (HIC) is a robust standard analytical method to purify proteins while preserving their biological activity. It is widely used to study post-translational modifications of proteins and drug-protein interactions. In the current manuscript we employed HIC to separate proteins, followed by bottom-up LC-MS/MS experiments. We used this approach to fractionate antibody species followed by comprehensive peptide mapping as well as to study protein complexes in human cells. HIC-reversed-phase chromatography (RPC)-mass spectrometry (MS) is a powerful alternative to fractionate proteins for bottom-up proteomics experiments making use of their distinct hydrophobic properties.

RAPID AND AUTOMATED PROCESSING OF MALDI-FTICR/MS DATA FOR N-METABOLIC LABELING IN A SHOTGUN PROTEOMICS ANALYSIS.

PubMed

Jing, Li; Amster, I Jonathan

2009-10-15

Offline high performance liquid chromatography combined with matrix assisted laser desorption and Fourier transform ion cyclotron resonance mass spectrometry (HPLC-MALDI-FTICR/MS) provides the means to rapidly analyze complex mixtures of peptides, such as those produced by proteolytic digestion of a proteome. This method is particularly useful for making quantitative measurements of changes in protein expression by using (15)N-metabolic labeling. Proteolytic digestion of combined labeled and unlabeled proteomes produces complex mixtures that with many mass overlaps when analyzed by HPLC-MALDI-FTICR/MS. A significant challenge to data analysis is the matching of pairs of peaks which represent an unlabeled peptide and its labeled counterpart. We have developed an algorithm and incorporated it into a compute program which significantly accelerates the interpretation of (15)N metabolic labeling data by automating the process of identifying unlabeled/labeled peak pairs. The algorithm takes advantage of the high resolution and mass accuracy of FTICR mass spectrometry. The algorithm is shown to be able to successfully identify the (15)N/(14)N peptide pairs and calculate peptide relative abundance ratios in highly complex mixtures from the proteolytic digest of a whole organism protein extract.

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

Optimization of Statistical Methods Impact on Quantitative Proteomics Data.

PubMed

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

2015-10-02

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

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.

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

PubMed

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

2017-06-01

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

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.

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.

A Robust Two-Dimensional Separation for Top-Down Tandem Mass Spectrometry of the Low-Mass Proteome

PubMed Central

Lee, Ji Eun; Kellie, John F.; Tran, John C.; Tipton, Jeremiah D.; Catherman, Adam D.; Thomas, Haylee M.; Ahlf, Dorothy R.; Durbin, Kenneth R.; Vellaichamy, Adaikkalam; Ntai, Ioanna; Marshall, Alan G.; Kelleher, Neil L.

2010-01-01

For fractionation of intact proteins by molecular weight (MW), a sharply improved two-dimensional (2D) separation is presented to drive reproducible and robust fractionation before top-down mass spectrometry of complex mixtures. The “GELFrEE” (i.e., gel-eluted liquid fraction entrapment electrophoresis) approach is implemented by use of Tris-glycine and Tris-tricine gel systems applied to human cytosolic and nuclear extracts from HeLa S3 cells, to achieve a MW-based fractionation of proteins from 5 to >100 kDa in 1 h. For top-down tandem mass spectroscopy (MS/MS) of the low-mass proteome (5–25 kDa), between 5 and 8 gel-elution (GE) fractions are sampled by nanocapillary-LC-MS/MS with 12 or 14.5 tesla Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers. Single injections give about 40 detectable proteins, about half of which yield automated ProSight identifications. Reproducibility metrics of the system are presented, along with comparative analysis of protein targets in mitotic versus asynchronous cells. We forward this basic 2D approach to facilitate wider implementation of top-down mass spectrometry and a variety of other protein separation and/or characterization approaches. PMID:19747844

Detection of Biomarkers of Pathogenic Naegleria fowleri Through Mass Spectrometry and Proteomics

PubMed Central

Moura, Hercules; Izquierdo, Fernando; Woolfitt, Adrian R.; Wagner, Glauber; Pinto, Tatiana; del Aguila, Carmen; Barr, John R.

2017-01-01

Emerging methods based on mass spectrometry (MS) can be used in the rapid identification of microorganisms. Thus far, these practical and rapidly evolving methods have mainly been applied to characterize prokaryotes. We applied matrix-assisted laser-desorption-ionization-time-of-flight mass spectrometry MALDI-TOF MS in the analysis of whole cells of 18 N. fowleri isolates belonging to three genotypes. Fourteen originated from the cerebrospinal fluid or brain tissue of primary amoebic meningoencephalitis patients and four originated from water samples of hot springs, rivers, lakes or municipal water supplies. Whole Naegleria trophozoites grown in axenic cultures were washed and mixed with MALDI matrix. Mass spectra were acquired with a 4700 TOF-TOF instrument. MALDI-TOF MS yielded consistent patterns for all isolates examined. Using a combination of novel data processing methods for visual peak comparison, statistical analysis and proteomics database searching we were able to detect several biomarkers that can differentiate all species and isolates studied, along with common biomarkers for all N. fowleri isolates. Naegleria fowleri could be easily separated from other species within the genus Naegleria. A number of peaks detected were tentatively identified. MALDI-TOF MS fingerprinting is a rapid, reproducible, high-throughput alternative method for identifying Naegleria isolates. This method has potential for studying eukaryotic agents. PMID:25231600

Combining Capillary Electrophoresis with Mass Spectrometry for Applications in Proteomics

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

Simpson, David C.; Smith, Richard D.

2005-04-01

Throughout the field of global proteomics, ranging from simple organism studies to human medical applications, the high sample complexity creates demands for improved separations and analysis techniques. Furthermore, with increased organism complexity, the correlation between proteome and genome becomes less certain due to extensive mRNA processing prior to translation. In this way, the same DNA sequence can potentially code for regions in a number of distinct proteins; quantitative differences in expression (or abundance) between these often-related species are of significant interest. Well-established proteomics techniques, which use genomic information to identify peptides that originate from protease digestion, often cannot easily distinguishmore » between such gene products; intact protein-level analyses are required to complete the picture, particularly for identifying post-translational modifications. While chromatographic techniques are currently better suited to peptide analysis, capillary electrophoresis (CE) in combination with mass spectrometry (MS) may become important for intact protein analysis. This review focuses on CE/MS instrumentation and techniques showing promise for such applications, highlighting those with greatest potential. Reference will also be made to developments relevant to peptide-level analyses for use in time- or sample-limited situations.« less

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

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

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.

Saliva analysis by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) in orthodontic treatment: first pilot study.

PubMed

Ciavarella, Domenico; Mastrovincenzo, Mario; D'Onofrio, Valentina; Chimenti, Claudio; Parziale, Vincenzo; Barbato, Ersilia; Lo Muzio, Lorenzo

2011-11-01

SELDI-TOF-MS (Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry) allows the generation of an accurate protein profile from minimal amounts of biological samples and may executes proteomic profile of saliva. The aim of this work is to compare the proteomic profile of saliva of patients in orthodontic treatment to the beginning of treatment and after three months by using the surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. Saliva was collected from 14 patients, between the 11 and 17 years, to the beginning of the orthodontic treatment and after three months. Specimens were centrifuged (10 min, 13000 x g); the Q10 ProteinChips were prepared according to the manufacturer's instructions and were loaded with the supernatants. A saturated solution of sinapinic acid was used as energy-absorbing matrix. The analysis was performed in a m/z range from 2500 to 25000 Da, and the proteomic profiles were compared by a specific data analysis software. Saliva (5 mL) was collected by spitting directly into a clean 15 mL conical tube. The samples were then aliquotted and stored at -80°C until use. Profile of saliva of patients before orthodontic treatment present a number of peaks different respect profile of saliva after three months of treatment. The average intensities of peaks at m/z 3372, 5232, 4045 and 10128 were significantly higher after three months then at beginning of treatment in the same patients and among these one. The Roc Plot has demonstrated high sensitivity and specificity. Many differences were noted in salivary proteomic profile obtained using the SELDI-TOF-MS technology in patients in orthodontic treatment to beginning and after three months. These data suggest that the proteomic analysis of saliva is a promising new tool for a non-invasive study of oral mucosa and bone changes. Copyright © 2011 Società Italiana di Ortodonzia SIDO. Published by Elsevier Srl. All rights reserved.

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

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.

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.

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

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

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.

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.

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

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.

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.

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.

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.

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.

Mass spectrometry (LC-MS/MS) identified proteomic biosignatures of breast cancer in proximal fluid.

PubMed

Whelan, Stephen A; He, Jianbo; Lu, Ming; Souda, Puneet; Saxton, Romaine E; Faull, Kym F; Whitelegge, Julian P; Chang, Helena R

2012-10-05

We have begun an early phase of biomarker discovery in three clinically important types of breast cancer using a panel of human cell lines: HER2 positive, hormone receptor positive and HER2 negative, and triple negative (HER2-, ER-, PR-). We identified and characterized the most abundant secreted, sloughed, or leaked proteins released into serum free media from these breast cancer cell lines using a combination of protein fractionation methods before LC-MS/MS mass spectrometry analysis. A total of 249 proteins were detected in the proximal fluid of 7 breast cancer cell lines. The expression of a selected group of high abundance and/or breast cancer-specific potential biomarkers including thromobospondin 1, galectin-3 binding protein, cathepsin D, vimentin, zinc-α2-glycoprotein, CD44, and EGFR from the breast cancer cell lines and in their culture media were further validated by Western blot analysis. Interestingly, mass spectrometry identified a cathepsin D protein single-nucleotide polymorphism (SNP) by alanine to valine replacement from the MCF-7 breast cancer cell line. Comparison of each cell line media proteome displayed unique and consistent biosignatures regardless of the individual group classifications, demonstrating the potential for stratification of breast cancer. On the basis of the cell line media proteome, predictive Tree software was able to categorize each cell line as HER2 positive, HER2 negative, and hormone receptor positive and triple negative based on only two proteins, muscle fructose 1,6-bisphosphate aldolase and keratin 19. In addition, the predictive Tree software clearly identified MCF-7 cell line overexpresing the HER2 receptor with the SNP cathepsin D biomarker.

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

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.

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.

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

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/

Synthetic Peptide Arrays for Pathway-Level Protein Monitoring by Liquid Chromatography-Tandem Mass Spectrometry*

PubMed Central

Hewel, Johannes A.; Liu, Jian; Onishi, Kento; Fong, Vincent; Chandran, Shamanta; Olsen, Jonathan B.; Pogoutse, Oxana; Schutkowski, Mike; Wenschuh, Holger; Winkler, Dirk F. H.; Eckler, Larry; Zandstra, Peter W.; Emili, Andrew

2010-01-01

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including “label-free” quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations. PMID:20467045

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

Using ProHits to store, annotate and analyze affinity purification - mass spectrometry (AP-MS) data

PubMed Central

Liu, Guomin; Zhang, Jianping; Choi, Hyungwon; Lambert, Jean-Philippe; Srikumar, Tharan; Larsen, Brett; Nesvizhskii, Alexey I.; Raught, Brian; Tyers, Mike; Gingras, Anne-Claude

2012-01-01

Affinity purification coupled with mass spectrometry (AP-MS) is a robust technique used to identify protein-protein interactions. With recent improvements in sample preparation, and dramatic advances in MS instrumentation speed and sensitivity, this technique is becoming more widely used throughout the scientific community. To meet the needs of research groups both large and small, we have developed software solutions for tracking, scoring and analyzing AP-MS data. Here, we provide details for the installation and utilization of ProHits, a Laboratory Information Management System designed specifically for AP-MS interaction proteomics. This protocol explains: (i) how to install the complete ProHits system, including modules for the management of mass spectrometry files and the analysis of interaction data, and (ii) alternative options for the use of pre-existing search results in simpler versions of ProHits, including a virtual machine implementation of our ProHits Lite software. We also describe how to use the main features of the software to analyze AP-MS data. PMID:22948730

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

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.

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.

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

Antibodies as means for selective mass spectrometry.

PubMed

Boström, Tove; Takanen, Jenny Ottosson; Hober, Sophia

2016-05-15

For protein analysis of biological samples, two major strategies are used today; mass spectrometry (MS) and antibody-based methods. Each strategy offers advantages and drawbacks. However, combining the two using an immunoenrichment step with MS analysis brings together the benefits of each method resulting in increased sensitivity, faster analysis and possibility of higher degrees of multiplexing. The immunoenrichment can be performed either on protein or peptide level and quantification standards can be added in order to enable determination of the absolute protein concentration in the sample. The combination of immunoenrichment and MS holds great promise for the future in both proteomics and clinical diagnostics. This review describes different setups of immunoenrichment coupled to mass spectrometry and how these can be utilized in various applications. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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.

Detection of biomarkers of pathogenic Naegleria fowleri through mass spectrometry and proteomics.

PubMed

Moura, Hercules; Izquierdo, Fernando; Woolfitt, Adrian R; Wagner, Glauber; Pinto, Tatiana; del Aguila, Carmen; Barr, John R

2015-01-01

Emerging methods based on mass spectrometry (MS) can be used in the rapid identification of microorganisms. Thus far, these practical and rapidly evolving methods have mainly been applied to characterize prokaryotes. We applied matrix-assisted laser-desorption-ionization-time-of-flight mass spectrometry MALDI-TOF MS in the analysis of whole cells of 18 N. fowleri isolates belonging to three genotypes. Fourteen originated from the cerebrospinal fluid or brain tissue of primary amoebic meningoencephalitis patients and four originated from water samples of hot springs, rivers, lakes or municipal water supplies. Whole Naegleria trophozoites grown in axenic cultures were washed and mixed with MALDI matrix. Mass spectra were acquired with a 4700 TOF-TOF instrument. MALDI-TOF MS yielded consistent patterns for all isolates examined. Using a combination of novel data processing methods for visual peak comparison, statistical analysis and proteomics database searching we were able to detect several biomarkers that can differentiate all species and isolates studied, along with common biomarkers for all N. fowleri isolates. Naegleria fowleri could be easily separated from other species within the genus Naegleria. A number of peaks detected were tentatively identified. MALDI-TOF MS fingerprinting is a rapid, reproducible, high-throughput alternative method for identifying Naegleria isolates. This method has potential for studying eukaryotic agents. © 2014 The Author(s) Journal of Eukaryotic Microbiology © 2014 International Society of Protistologists.

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

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.

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.

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

Protein-phosphotyrosine proteome profiling by superbinder-SH2 domain affinity purification mass spectrometry, sSH2-AP-MS.

PubMed

Tong, Jiefei; Cao, Biyin; Martyn, Gregory D; Krieger, Jonathan R; Taylor, Paul; Yates, Bradley; Sidhu, Sachdev S; Li, Shawn S C; Mao, Xinliang; Moran, Michael F

2017-03-01

Recently, "superbinder" SH2 domain variants with three amino acid substitutions (sSH2) were reported to have 100-fold or greater affinity for protein-phosphotyrosine (pY) than natural SH2 domains. Here we report a protocol in which His-tagged Src sSH2 efficiently captures pY-peptides from protease-digested HeLa cell total protein extracts. Affinity purification of pY-peptides by this method shows little bias for pY-proximal amino acid sequences, comparable to that achieved by using antibodies to pY, but with equal or higher yield. Superbinder-SH2 affinity purification mass spectrometry (sSH2-AP-MS) therefore provides an efficient and economical approach for unbiased pY-directed phospho-proteome profiling without the use of antibodies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

pyQms enables universal and accurate quantification of mass spectrometry data.

PubMed

Leufken, Johannes; Niehues, Anna; Sarin, L Peter; Wessel, Florian; Hippler, Michael; Leidel, Sebastian A; Fufezan, Christian

2017-10-01

Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

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

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.

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.

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.

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.

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.

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

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

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.

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.

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

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.

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.

Matrix-Assisted Laser Desorption Ionization–Time of Flight (MALDI-TOF) Mass Spectrometry for Detection of Antibiotic Resistance Mechanisms: from Research to Routine Diagnosis

PubMed Central

Chudáčková, Eva; Walková, Radka

2013-01-01

Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) has been successfully applied as an identification procedure in clinical microbiology and has been widely used in routine laboratory practice because of its economical and diagnostic benefits. The range of applications of MALDI-TOF MS has been growing constantly, from rapid species identification to labor-intensive proteomic studies of bacterial physiology. The purpose of this review is to summarize the contribution of the studies already performed with MALDI-TOF MS concerning antibiotic resistance and to analyze future perspectives in this field. We believe that current research should continue in four main directions, including the detection of antibiotic modifications by degrading enzymes, the detection of resistance mechanism determinants through proteomic studies of multiresistant bacteria, and the analysis of modifications of target sites, such as ribosomal methylation. The quantification of antibiotics is suggested as a new approach to study influx and efflux in bacterial cells. The results of the presented studies demonstrate that MALDI-TOF MS is a relevant tool for the detection of antibiotic resistance and opens new avenues for both clinical and experimental microbiology. PMID:23297261

Proteome analysis of an ectomycorrhizal fungus Boletus edulis under salt shock.

PubMed

Liang, Yu; Chen, Hui; Tang, Mingjuan; Shen, Shihua

2007-08-01

Soil salinization has become a severe global problem and salinity is one of the most severe abiotic stresses inhibiting growth and survival of mycorrhizal fungi and their host plants. Salinity tolerance of ectomycorrhizal fungi and survival of ectomycorrhizal inocula is essential to reforestation and ecosystem restoration in saline areas. Proteomic changes of an ectomycorrhizal fungus, Boletus edulis, when exposed to salt stress conditions (4% NaCl, w/v) were determined using two-dimensional electrophoresis (2DE) and mass spectrometry (MS) techniques. Twenty-two protein spots, 14 upregulated and 8 downregulated, were found changed under salt stress conditions. Sixteen changed protein spots were identified by nanospray ESI Q-TOF MS/MS and liquid chromatography MS/MS. These proteins were involved in biosynthesis of methionine and S-adenosylmethionine, glycolysis, DNA repair, cell cycle control, and general stress tolerance, and their possible functions in salinity adaptation of Boletus edulis were discussed.

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.

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.

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

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

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.

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

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

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

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

Hooked differential mobility spectrometry apparatus and method therefore

DOEpatents

Shvartsburg, Alexandre A [Richland, WA; Tang, Keqi [Richland, WA; Ibrahim, Yehia M [Richland, WA; Smith, Richard D [Richland, WA

2009-02-17

Disclosed are a device and method for improved interfacing of differential mobility spectrometry (DMS) or field asymmetric waveform ion mobility spectrometry (FAIMS) analyzers of substantially planar geometry to subsequent or preceding instrument stages. Interfacing is achieved using curved DMS elements, where a thick ion beam emitted by planar DMS analyzers or injected into them for ion filtering is compressed to the gap median by DMS ion focusing effect in a spatially inhomogeneous electric field. Resulting thinner beams are more effectively transmitted through necessarily constrained conductance limit apertures to subsequent instrument stages operated at a pressure lower than DMS, and/or more effectively injected into planar DMS analyzers. The technology is synergetic with slit apertures, slit aperture/ion funnels, and high-pressure ion funnel interfaces known in the art which allow for increasing cross-sectional area of MS inlets. The invention may be used in integrated analytical platforms, including, e.g., DMS/MS, LC/DMS/MS, and DMS/IMS/MS that could replace and/or enhance current LC/MS methods, e.g., for proteomics research.

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

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.

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.

Native Mass Spectrometry: What is in the Name?

NASA Astrophysics Data System (ADS)

Leney, Aneika C.; Heck, Albert J. R.

2017-01-01

Electrospray ionization mass spectrometry (ESI-MS) is nowadays one of the cornerstones of biomolecular mass spectrometry and proteomics. Advances in sample preparation and mass analyzers have enabled researchers to extract much more information from biological samples than just the molecular weight. In particular, relevant for structural biology, noncovalent protein-protein and protein-ligand complexes can now also be analyzed by MS. For these types of analyses, assemblies need to be retained in their native quaternary state in the gas phase. This initial small niche of biomolecular mass spectrometry, nowadays often referred to as "native MS," has come to maturation over the last two decades, with dozens of laboratories using it to study mostly protein assemblies, but also DNA and RNA-protein assemblies, with the goal to define structure-function relationships. In this perspective, we describe the origins of and (re)define the term native MS, portraying in detail what we meant by "native MS," when the term was coined and also describing what it does (according to us) not entail. Additionally, we describe a few examples highlighting what native MS is, showing its successes to date while illustrating the wide scope this technology has in solving complex biological questions.

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

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

PubMed

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

2011-01-01

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

Spatially Directed Proteomics of the Human Lens Outer Cortex Reveals an Intermediate Filament Switch Associated With the Remodeling Zone

PubMed Central

Wenke, Jamie L.; McDonald, W. Hayes; Schey, Kevin L.

2016-01-01

Purpose To quantify protein changes in the morphologically distinct remodeling zone (RZ) and adjacent regions of the human lens outer cortex using spatially directed quantitative proteomics. Methods Lightly fixed human lens sections were deparaffinized and membranes labeled with fluorescent wheat germ agglutinin (WGA-TRITC). Morphology directed laser capture microdissection (LCM) was used to isolate tissue from four distinct regions of human lens outer cortex: differentiating zone (DF), RZ, transition zone (TZ), and inner cortex (IC). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) of the plasma membrane fraction from three lenses (21-, 22-, and 27-year) revealed changes in major cytoskeletal proteins including vimentin, filensin, and phakinin. Peptides from proteins of interest were quantified using multiple reaction monitoring (MRM) mass spectrometry and isotopically-labeled internal peptide standards. Results Results revealed an intermediate filament switch from vimentin to beaded filament proteins filensin and phakinin that occurred at the RZ. Several other cytoskeletal proteins showed significant changes between regions, while most crystallins remained unchanged. Targeted proteomics provided accurate, absolute quantification of these proteins and confirmed vimentin, periplakin, and periaxin decrease from the DF to the IC, while filensin, phakinin, and brain acid soluble protein 1 (BASP1) increase significantly at the RZ. Conclusions Mass spectrometry-compatible fixation and morphology directed laser capture enabled proteomic analysis of narrow regions in the human lens outer cortex. Results reveal dramatic cytoskeletal protein changes associated with the RZ, suggesting that one role of these proteins is in membrane deformation and/or the establishment of ball and socket joints in the human RZ. PMID:27537260

Bacteriophage cell lysis of Shiga toxin-producing Escherichia coli for top-down proteomic identification of Shiga toxin 1 & 2 using matrix-assisted laser desorption/ionization tandem time-of-light mass spectrometry

USDA-ARS?s Scientific Manuscript database

RATIONALE: Analysis of bacteria by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) often relies upon sample preparation methods that result in cell lysis, e.g. bead-beating. However, Shiga toxin-producing Escherichia coli (STEC) can undergo bacteriophage...

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.

Guidelines for reporting quantitative mass spectrometry based experiments in proteomics.

PubMed

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

2013-12-16

Mass spectrometry is already a well-established protein identification tool and recent methodological and technological developments have also made possible the extraction of quantitative data of protein abundance in large-scale studies. Several strategies for absolute and relative quantitative proteomics and the statistical assessment of quantifications are possible, each having specific measurements and therefore, different data analysis workflows. The guidelines for Mass Spectrometry Quantification allow the description of a wide range of quantitative approaches, including labeled and label-free techniques and also targeted approaches such as Selected Reaction Monitoring (SRM). The HUPO Proteomics Standards Initiative (HUPO-PSI) has invested considerable efforts to improve the standardization of proteomics data handling, representation and sharing through the development of data standards, reporting guidelines, controlled vocabularies and tooling. In this manuscript, we describe a key output from the HUPO-PSI-namely the MIAPE Quant guidelines, which have developed in parallel with the corresponding data exchange format mzQuantML [1]. The MIAPE Quant guidelines describe the HUPO-PSI proposal concerning the minimum information to be reported when a quantitative data set, derived from mass spectrometry (MS), is submitted to a database or as supplementary information to a journal. The guidelines have been developed with input from a broad spectrum of stakeholders in the proteomics field to represent a true consensus view of the most important data types and metadata, required for a quantitative experiment to be analyzed critically or a data analysis pipeline to be reproduced. It is anticipated that they will influence or be directly adopted as part of journal guidelines for publication and by public proteomics databases and thus may have an impact on proteomics laboratories across the world. This article is part of a Special Issue entitled: Standardization and Quality Control. Copyright © 2013 Elsevier B.V. All rights reserved.

PROTEOMIC ANALYSIS OF ALLERGENS FROM METARHIZIUM ANISOPLIAE

EPA Science Inventory

Introduction

The goal of this project is the identification and characterization of allergens from the fungus Metarhizium anisopliae, using mass spectrometry (MS). The US EPA, under the "Children at Risk" program, is currently addressing the problem of indoor fungal bioaer...

PROTEOMIC ANALYSIS OF ALLERGENS FROM METARHIZIUM ANISOPLIEA

EPA Science Inventory

The goal of this project is the identification and characterization of allergens from the fungus M. Anisopliae, using mass spectrometry (MS). The US EPA, under the "Children at Risk" program, is currently addressing the problem of indoor fungal bioaerosol contamination. One of ...

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.

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.

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

PubMed Central

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

2016-01-01

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

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

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.

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

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.

Purification and proteomic analysis of plant plasma membranes.

PubMed

Alexandersson, Erik; Gustavsson, Niklas; Bernfur, Katja; Karlsson, Adine; Kjellbom, Per; Larsson, Christer

2008-01-01

All techniques needed for proteomic analyses of plant plasma membranes are described in detail, from isolation of plasma membranes to protein identification by mass spectrometry (MS). Plasma membranes are isolated by aqueous two-phase partitioning yielding vesicles with a cytoplasmic side-in orientation and a purity of about 95%. These vesicles are turned inside-out by treatment with Brij 58, which removes soluble contaminating proteins enclosed in the vesicles as well as loosely attached proteins. The final plasma membrane preparation thus retains all integral proteins and many peripheral proteins. Proteins are separated by one-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE), and protein bands are excised and digested with trypsin. Peptides in tryptic digests are separated by nanoflow liquid chromatography and either fed directly into an ESI-MS or spotted onto matrix-assisted laser desorption ionization (MALDI) plates for analysis with MALDI-MS. Finally, data processing and database searching are used for protein identification to define a plasma membrane proteome.

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

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

PubMed Central

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

2014-01-01

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

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.

A PROTEOMIC (SELDI-TOF-MS) APPROACH TO ESTROGEN AGONIST SCREENING

EPA Science Inventory

A small fish model and surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI) were used to investigate plasma protein expression as a means to screen chemicals for estrogenic activity. Adult male sheepshead minnows (Cyprinodon variegatus) were place...

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

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.

Urea free and more efficient sample preparation method for mass spectrometry based protein identification via combining the formic acid-assisted chemical cleavage and trypsin digestion.

PubMed

Wu, Shuaibin; Yang, Kaiguang; Liang, Zhen; Zhang, Lihua; Zhang, Yukui

2011-10-30

A formic acid (FA)-assisted sample preparation method was presented for protein identification via mass spectrometry (MS). Detailedly, an aqueous solution containing 2% FA and dithiothreitol was selected to perform protein denaturation, aspartic acid (D) sites cleavage and disulfide linkages reduction simultaneously at 108°C for 2h. Subsequently, FA wiped off via vacuum concentration. Finally, iodoacetamide (IAA) alkylation and trypsin digestion could be performed ordinally. A series of model proteins (BSA, β-lactoglobulin and apo-Transferrin) were treated respectively using such method, followed by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The identified peptide number was increased by ∼ 80% in comparison with the conventional urea-assisted sample preparation method. Moreover, BSA identification was achieved efficiently down to femtomole (25 ± 0 sequence coverage and 16 ± 1 peptides) via such method. In contrast, there were not peptides identified confidently via the urea-assisted method before desalination via the C18 zip tip. The absence of urea in this sample preparation method was an advantage for the more favorable digestion and MALDI-TOF MS analysis. The performances of two methods for the real sample (rat liver proteome) were also compared, followed by a nanoflow reversed-phase liquid chromatography with electrospray ionization tandem mass spectrometry system analysis. As a result, 1335 ± 43 peptides were identified confidently (false discovery rate <1%) via FA-assisted method, corresponding to 295 ± 12 proteins (of top match=1 and requiring 2 unique peptides at least). In contrast, there were only 1107 ± 16 peptides (corresponding to 231 ± 10 proteins) obtained from the conventional urea-assisted method. It was serving as a more efficient protein sample preparation method for researching specific proteomes better, and providing assistance to develop other proteomics analysis methods, such as, peptide quantitative analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

An LC-IMS-MS Platform Providing Increased Dynamic Range for High-Throughput Proteomic Studies

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

Baker, Erin Shammel; Livesay, Eric A.; Orton, Daniel J.

2010-02-05

A high-throughput approach and platform using 15 minute reversed-phase capillary liquid chromatography (RPLC) separations in conjunction with ion mobility spectrometry-mass spectrometry (IMS-MS) measurements was evaluated for the rapid analysis of complex proteomics samples. To test the separation quality of the short LC gradient, a sample was prepared by spiking twenty reference peptides at varying concentrations from 1 ng/mL to 10 µg/mL into a tryptic digest of mouse blood plasma and analyzed with both a LC-Linear Ion Trap Fourier Transform (FT) MS and LC-IMS-TOF MS. The LC-FT MS detected thirteen out of the twenty spiked peptides that had concentrations ≥100 ng/mL.more » In contrast, the drift time selected mass spectra from the LC-IMS-TOF MS analyses yielded identifications for nineteen of the twenty peptides with all spiking level present. The greater dynamic range of the LC-IMS-TOF MS system could be attributed to two factors. First, the LC-IMS-TOF MS system enabled drift time separation of the low concentration spiked peptides from the high concentration mouse peptide matrix components, reducing signal interference and background, and allowing species to be resolved that would otherwise be obscured by other components. Second, the automatic gain control (AGC) in the linear ion trap of the hybrid FT MS instrument limits the number of ions that are accumulated to reduce space charge effects, but in turn limits the achievable dynamic range compared to the TOF detector.« less

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.

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

Comparative Proteomic Analysis of Three Gelatinous Chinese Medicines and Their Authentications by Tryptic-digested Peptides Profiling using Matrix-assisted Laser Desorption/Ionization-time of Flight/Time of Flight Mass Spectrometry.

PubMed

Yang, Huan; Zheng, Jie; Wang, Hai-Yan; Li, Nan; Yang, Ya-Ya; Shen, Yu-Ping

2017-01-01

Gelatinous Chinese medicines (GCMs) including Asini Corii Colla, Testudinis Carapacis ET Plastri Colla, and Cervi Cornus Colla, were made from reptile shell or mammalian skin or deer horn, and consumed as a popular tonic, as well as hemopoietic and hemostatic agents. Misuse of them would not exert their functions, and fake or adulterate products have caused drug market disorder and affected food and drug safety. GCMs are rich in denatured proteins, but insufficient in available DNA fragments, hence commonly used cytochrome c oxidase I barcoding was not successful for their authentication. In this study, we performed comparative proteomic analysis of them and their animal origins to identify the composition of intrinsic proteins for the first time. A reliable and convenient approach was proposed for their authentication, by the incorporation of sodium dodecyl sulfate-polyacrylamide gel electrophoresis, two-dimensional electrophoresis, and matrix-assisted laser desorption/ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF-MS). A total of 26 proteins were identified from medicinal parts of original animals, and GCMs proteins presented in a dispersive manner in electrophoresis analyses due to complicated changes in the structure of original proteins caused by long-term decoction and the addition of ingredients during their manufacturing. In addition, by comparison of MALDI-TOF/TOF-MS profiling, 19 signature peptide fragments originated from the protein of GCM products were selected according to criteria. These could assist in the discrimination and identification of adulterates of GCMs and other ACMs for their form of raw medicinal material, the pulverized, and even the complex. Comparative proteomic analysis of three gelatinous Chinese medicines was conducted, and their authentications were based on tryptic-digested peptides profiling using matrix-assisted laser desorption/ionization-time of flight/time of flight mass spectrometry. Abbreviations used: GCMs: Gelatinous Chinese medicines, COI: Cytochrome c oxidase I, SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, MALDI-TOF/TOF-MS: Matrix-assisted laser desorption/ionization-time of flight/time of flight mass spectrometry, LC: Liquid chromatography, ChP: Chinese Pharmacopoeia, HPLC: High performance liquid chromatography, LC-ESI + -MS: Liquid chromatography-electro spray ionization-mass spectrometry, IEF: isoelectric focusing, HCCA: α-Cyano-4-hydroxycinnamic acid.

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.

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.

JAMSS: proteomics mass spectrometry simulation in Java.

PubMed

Smith, Rob; Prince, John T

2015-03-01

Countless proteomics data processing algorithms have been proposed, yet few have been critically evaluated due to lack of labeled data (data with known identities and quantities). Although labeling techniques exist, they are limited in terms of confidence and accuracy. In silico simulators have recently been used to create complex data with known identities and quantities. We propose Java Mass Spectrometry Simulator (JAMSS): a fast, self-contained in silico simulator capable of generating simulated MS and LC-MS runs while providing meta information on the provenance of each generated signal. JAMSS improves upon previous in silico simulators in terms of its ease to install, minimal parameters, graphical user interface, multithreading capability, retention time shift model and reproducibility. The simulator creates mzML 1.1.0. It is open source software licensed under the GPLv3. The software and source are available at https://github.com/optimusmoose/JAMSS. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Challenges and Opportunities for Biological Mass Spectrometry Core Facilities in the Developing World.

PubMed

Bell, Liam; Calder, Bridget; Hiller, Reinhard; Klein, Ashwil; Soares, Nelson C; Stoychev, Stoyan H; Vorster, Barend C; Tabb, David L

2018-04-01

The developing world is seeing rapid growth in the availability of biological mass spectrometry (MS), particularly through core facilities. As proteomics and metabolomics becomes locally feasible for investigators in these nations, application areas associated with high burden in these nations, such as infectious disease, will see greatly increased research output. This article evaluates the rapid growth of MS in South Africa (currently approaching 20 laboratories) as a model for establishing MS core facilities in other nations of the developing world. Facilities should emphasize new services rather than new instruments. The reduction of the delays associated with reagent and other supply acquisition would benefit both facilities and the users who make use of their services. Instrument maintenance and repair, often mediated by an in-country business for an international vendor, is also likely to operate on a slower schedule than in the wealthiest nations. A key challenge to facilities in the developing world is educating potential facility users in how best to design experiments for proteomics and metabolomics, what reagents are most likely to introduce problematic artifacts, and how to interpret results from the facility. Here, we summarize the experience of 6 different institutions to raise the level of biological MS available to researchers in South Africa.

Discovering Mercury Protein Modifications in Whole Proteomes Using Natural Isotope Distributions Observed in Liquid Chromatography-Tandem Mass Spectrometry

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

Polacco, Benjamin J.; Purvine, Samuel O.; Zink, Erika M.

2011-08-01

The identification of peptides that result from post-translational modifications is critical for understanding normal pathways of cellular regulation as well as identifying damage from, or exposures to xenobiotics, i.e. the exposome. However, because of their low abundance in proteomes, effective detection of modified peptides by mass spectrometry (MS) typically requires enrichment to eliminate false identifications. We present a new method for confidently identifying peptides with mercury (Hg)-containing adducts that is based on the influence of mercury’s seven stable isotopes on peptide isotope distributions detected by high-resolution MS. Using a pure protein and E. coli cultures exposed to phenyl mercuric acetate,more » we show the pattern of peak heights in isotope distributions from primary MS single scans efficiently identified Hg adducts in data from chromatographic separation coupled with tandem mass spectrometry with sensitivity and specificity greater than 90%. Isotope distributions are independent of peptide identifications based on peptide fragmentation (e.g. by SEQUEST), so both methods can be combined to eliminate false positives. Summing peptide isotope distributions across multiple scans improved specificity to 99.4% and sensitivity above 95%, affording identification of an unexpected Hg modification. We also illustrate the theoretical applicability of the method for detection of several less common elements including the essential element, selenium, as selenocysteine in peptides.« less

Development and Applications of Liquid Sample Desorption Electrospray Ionization Mass Spectrometry

NASA Astrophysics Data System (ADS)

Zheng, Qiuling; Chen, Hao

2016-06-01

Desorption electrospray ionization mass spectrometry (DESI-MS) is a recent advance in the field of analytical chemistry. This review surveys the development of liquid sample DESI-MS (LS-DESI-MS), a variant form of DESI-MS that focuses on fast analysis of liquid samples, and its novel analy-tical applications in bioanalysis, proteomics, and reaction kinetics. Due to the capability of directly ionizing liquid samples, liquid sample DESI (LS-DESI) has been successfully used to couple MS with various analytical techniques, such as microfluidics, microextraction, electrochemistry, and chromatography. This review also covers these hyphenated techniques. In addition, several closely related ionization methods, including transmission mode DESI, thermally assisted DESI, and continuous flow-extractive DESI, are briefly discussed. The capabilities of LS-DESI extend and/or complement the utilities of traditional DESI and electrospray ionization and will find extensive and valuable analytical application in the future.

Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

PubMed

Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

2013-01-04

Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Metaproteomics as a Complementary Approach to Gut Microbiota in Health and Disease

NASA Astrophysics Data System (ADS)

Petriz, Bernardo A.; Franco, Octávio L.

2017-01-01

Classic studies on phylotype profiling are limited to the identification of microbial constituents, where information is lacking about the molecular interaction of these bacterial communities with the host genome and the possible outcomes in host biology. A range of OMICs approaches have provided great progress linking the microbiota to health and disease. However, the investigation of this context through proteomic mass spectrometry-based tools is still being improved. Therefore, metaproteomics or community proteogenomics has emerged as a complementary approach to metagenomic data, as a field in proteomics aiming to perform large-scale characterization of proteins from environmental microbiota such as the human gut. The advances in molecular separation methods coupled with mass spectrometry (e.g. LC-MS/MS) and proteome bioinformatics have been fundamental in these novel large-scale metaproteomic studies, which have further been performed in a wide range of samples including soil, plant and human environments. Metaproteomic studies will make major progress if a comprehensive database covering the genes and expresses proteins from all gut microbial species is developed. To this end, we here present some of the main limitations of metaproteomic studies in complex microbiota environments such as the gut, also addressing the up-to-date pipelines in sample preparation prior to fractionation/separation and mass spectrometry analysis. In addition, a novel approach to the limitations of metagenomic databases is also discussed. Finally, prospects are addressed regarding the application of metaproteomic analysis using a unified host-microbiome gene database and other meta-OMICs platforms.

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.

Serum biomarkers of Burkholderia mallei infection elucidated by proteomic imaging of skin and lung abscesses.

PubMed

Glaros, Trevor G; Blancett, Candace D; Bell, Todd M; Natesan, Mohan; Ulrich, Robert G

2015-01-01

The bacterium Burkholderia mallei is the etiological agent of glanders, a highly contagious, often fatal zoonotic infectious disease that is also a biodefense concern. Clinical laboratory assays that analyze blood or other biological fluids are the highest priority because these specimens can be collected with minimal risk to the patient. However, progress in developing sensitive assays for monitoring B. mallei infection is hampered by a shortage of useful biomarkers. Reasoning that there should be a strong correlation between the proteomes of infected tissues and circulating serum, we employed imaging mass spectrometry (IMS) of thin-sectioned tissues from Chlorocebus aethiops (African green) monkeys infected with B. mallei to localize host and pathogen proteins that were associated with abscesses. Using laser-capture microdissection of specific regions identified by IMS and histology within the tissue sections, a more extensive proteomic analysis was performed by a technique that combined the physical separation capabilities of liquid chromatography (LC) with the sensitive mass analysis capabilities of mass spectrometry (LC-MS/MS). By examining standard formalin-fixed, paraffin-embedded tissue sections, this strategy resulted in the identification of several proteins that were associated with lung and skin abscesses, including the host protein calprotectin and the pathogen protein GroEL. Elevated levels of calprotectin detected by ELISA and antibody responses to GroEL, measured by a microarray of the bacterial proteome, were subsequently detected in the sera of C. aethiops, Macaca mulatta, and Macaca fascicularis primates infected with B. mallei. Our results demonstrate that a combination of multidimensional MS analysis of traditional histology specimens with high-content protein microarrays can be used to discover lead pairs of host-pathogen biomarkers of infection that are identifiable in biological fluids.

Identification of serum biomarkers in dogs naturally infected with Babesia canis canis using a proteomic approach

PubMed Central

2014-01-01

Background Canine babesiosis is a tick-borne disease that is caused by the haemoprotozoan parasites of the genus Babesia. There are limited data on serum proteomics in dogs, and none of the effect of babesiosis on the serum proteome. The aim of this study was to identify the potential serum biomarkers of babesiosis using proteomic techniques in order to increase our understanding about disease pathogenesis. Results Serum samples were collected from 25 dogs of various breeds and sex with naturally occurring babesiosis caused by B. canis canis. Blood was collected on the day of admission (day 0), and subsequently on the 1st and 6th day of treatment. Two-dimensional electrophoresis (2DE) of pooled serum samples of dogs with naturally occurring babesiosis (day 0, day 1 and day 6) and healthy dogs were run in triplicate. 2DE image analysis showed 64 differentially expressed spots with p ≤ 0.05 and 49 spots with fold change ≥2. Six selected spots were excised manually and subjected to trypsin digest prior to identification by electrospray ionisation mass spectrometry on an Amazon ion trap tandem mass spectrometry (MS/MS). Mass spectrometry data was processed using Data Analysis software and the automated Matrix Science Mascot Daemon server. Protein identifications were assigned using the Mascot search engine to interrogate protein sequences in the NCBI Genbank database. A number of differentially expressed serum proteins involved in inflammation mediated acute phase response, complement and coagulation cascades, apolipoproteins and vitamin D metabolism pathway were identified in dogs with babesiosis. Conclusions Our findings confirmed two dominant pathogenic mechanisms of babesiosis, haemolysis and acute phase response. These results may provide possible serum biomarker candidates for clinical monitoring of babesiosis and this study could serve as the basis for further proteomic investigations in canine babesiosis. PMID:24885808

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

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

Reagent for Evaluating Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) Performance in Bottom-Up Proteomic Experiments.

PubMed

Beri, Joshua; Rosenblatt, Michael M; Strauss, Ethan; Urh, Marjeta; Bereman, Michael S

2015-12-01

We present a novel proteomic standard for assessing liquid chromatography-tandem mass spectrometry (LC-MS/MS) instrument performance, in terms of chromatographic reproducibility and dynamic range within a single LC-MS/MS injection. The peptide mixture standard consists of six peptides that were specifically synthesized to cover a wide range of hydrophobicities (grand average hydropathy (GRAVY) scores of -0.6 to 1.9). A combination of stable isotope labeled amino acids ((13)C and (15)N) were inserted to create five isotopologues. By combining these isotopologues at different ratios, they span four orders of magnitude within each distinct peptide sequence. Each peptide, from lightest to heaviest, increases in abundance by a factor of 10. We evaluate several metrics on our quadrupole orbitrap instrument using the 6 × 5 LC-MS/MS reference mixture spiked into a complex lysate background as a function of dynamic range, including mass measurement accuracy (MMA) and the linear range of quantitation of MS1 and parallel reaction monitoring experiments. Detection and linearity of the instrument routinely spanned three orders of magnitude across the gradient (500 fmol to 0.5 fmol on column) and no systematic trend was observed for MMA of targeted peptides as a function of abundance by analysis of variance analysis (p = 0.17). Detection and linearity of the fifth isotopologue (i.e., 0.05 fmol on column) was dependent on the peptide and instrument scan type (MS1 vs PRM). We foresee that this standard will serve as a powerful method to conduct both intra-instrument performance monitoring/evaluation, technology development, and inter-instrument comparisons.

Proteome analysis of excretory-secretory proteins of Entamoeba histolytica HM1:IMSS via LC-ESI-MS/MS and LC-MALDI-TOF/TOF.

PubMed

Ujang, Jorim Anak; Kwan, Soon Hong; Ismail, Mohd Nazri; Lim, Boon Huat; Noordin, Rahmah; Othman, Nurulhasanah

2016-01-01

Excretory-secretory (ES) proteins of E. histolytica are thought to play important roles in the host invasion, metabolism, and defence. Elucidation of the types and functions of E. histolytica ES proteins can further our understanding of the disease pathogenesis. Thus, the aim of this study is to use proteomics approach to better understand the complex ES proteins of the protozoa. E. histolytica ES proteins were prepared by culturing the trophozoites in protein-free medium. The ES proteins were identified using two mass spectrometry tools, namely, LC-ESI-MS/MS and LC-MALDI-TOF/TOF. The identified proteins were then classified according to their biological processes, molecular functions, and cellular components using the Panther classification system (PantherDB). A complementary list of 219 proteins was identified; this comprised 201 proteins detected by LC-ESI-MS/MS and 107 proteins by LC-MALDI-TOF/TOF. Of the 219 proteins, 89 were identified by both mass-spectrometry systems, while 112 and 18 proteins were detected exclusively by LC-ESI-MS/MS and LC-MALDI-TOF/TOF respectively. Biological protein functional analysis using PantherDB showed that 27% of the proteins were involved in metabolic processes. Using molecular functional and cellular component analyses, 35% of the proteins were found to be involved in catalytic activity, and 21% were associated with the cell parts. This study showed that complementary use of LC-ESI-MS/MS and LC-MALDI-TOF/TOF has improved the identification of ES proteins. The results have increased our understanding of the types of proteins excreted/secreted by the amoeba and provided further evidence of the involvement of ES proteins in intestinal colonisation and evasion of the host immune system, as well as in encystation and excystation of the parasite.

Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet*

PubMed Central

Keller, Andrew; Bader, Samuel L.; Shteynberg, David; Hood, Leroy; Moritz, Robert L.

2015-01-01

Proteomics by mass spectrometry technology is widely used for identifying and quantifying peptides and proteins. The breadth and sensitivity of peptide detection have been advanced by the advent of data-independent acquisition mass spectrometry. Analysis of such data, however, is challenging due to the complexity of fragment ion spectra that have contributions from multiple co-eluting precursor ions. We present SWATHProphet software that identifies and quantifies peptide fragment ion traces in data-independent acquisition data, provides accurate probabilities to ensure results are correct, and automatically detects and removes contributions to quantitation originating from interfering precursor ions. Integration in the widely used open source Trans-Proteomic Pipeline facilitates subsequent analyses such as combining results of multiple data sets together for improved discrimination using iProphet and inferring sample proteins using ProteinProphet. This novel development should greatly help make data-independent acquisition mass spectrometry accessible to large numbers of users. PMID:25713123

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.

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

Nanospray FAIMS Fractionation Provides Significant Increases in Proteome Coverage of Unfractionated Complex Protein Digests*

PubMed Central

Swearingen, Kristian E.; Hoopmann, Michael R.; Johnson, Richard S.; Saleem, Ramsey A.; Aitchison, John D.; Moritz, Robert L.

2012-01-01

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that can be used to reduce sample complexity and increase dynamic range in tandem mass spectrometry experiments. FAIMS fractionates ions in the gas-phase according to characteristic differences in mobilities in electric fields of different strengths. Undesired ion species such as solvated clusters and singly charged chemical background ions can be prevented from reaching the mass analyzer, thus decreasing chemical noise. To date, there has been limited success using the commercially available Thermo Fisher FAIMS device with both standard ESI and nanoLC-MS. We have modified a Thermo Fisher electrospray source to accommodate a fused silica pulled tip capillary column for nanospray ionization, which will enable standard laboratories access to FAIMS technology. Our modified source allows easily obtainable stable spray at flow rates of 300 nL/min when coupled with FAIMS. The modified electrospray source allows the use of sheath gas, which provides a fivefold increase in signal obtained when nanoLC is coupled to FAIMS. In this work, nanoLC-FAIMS-MS and nanoLC-MS were compared by analyzing a tryptic digest of a 1:1 mixture of SILAC-labeled haploid and diploid yeast to demonstrate the performance of nanoLC-FAIMS-MS, at different compensation voltages, for post-column fractionation of complex protein digests. The effective dynamic range more than doubled when FAIMS was used. In total, 10,377 unique stripped peptides and 1649 unique proteins with SILAC ratios were identified from the combined nanoLC-FAIMS-MS experiments, compared with 6908 unique stripped peptides and 1003 unique proteins with SILAC ratios identified from the combined nanoLC-MS experiments. This work demonstrates how a commercially available FAIMS device can be combined with nanoLC to improve proteome coverage in shotgun and targeted type proteomics experiments. PMID:22186714

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.

Proteomics, lipidomics, metabolomics: a mass spectrometry tutorial from a computer scientist's point of view.

PubMed

Smith, Rob; Mathis, Andrew D; Ventura, Dan; Prince, John T

2014-01-01

For decades, mass spectrometry data has been analyzed to investigate a wide array of research interests, including disease diagnostics, biological and chemical theory, genomics, and drug development. Progress towards solving any of these disparate problems depends upon overcoming the common challenge of interpreting the large data sets generated. Despite interim successes, many data interpretation problems in mass spectrometry are still challenging. Further, though these challenges are inherently interdisciplinary in nature, the significant domain-specific knowledge gap between disciplines makes interdisciplinary contributions difficult. This paper provides an introduction to the burgeoning field of computational mass spectrometry. We illustrate key concepts, vocabulary, and open problems in MS-omics, as well as provide invaluable resources such as open data sets and key search terms and references. This paper will facilitate contributions from mathematicians, computer scientists, and statisticians to MS-omics that will fundamentally improve results over existing approaches and inform novel algorithmic solutions to open problems.

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.

A Catalog of Proteins Expressed in the AG Secreted Fluid during the Mature Phase of the Chinese Mitten Crabs (Eriocheir sinensis)

PubMed Central

He, Lin; Li, Qing; Liu, Lihua; Wang, Yuanli; Xie, Jing; Yang, Hongdan; Wang, Qun

2015-01-01

The accessory gland (AG) is an important component of the male reproductive system of arthropods, its secretions enhance fertility, some AG proteins bind to the spermatozoa and affect its function and properties. Here we report the first comprehensive catalog of the AG secreted fluid during the mature phase of the Chinese mitten crab (Eriocheir sinensis). AG proteins were separated by one-dimensional gel electrophoresis and analyzed by reverse phase high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS). Altogether, the mass spectra of 1173 peptides were detected (1067 without decoy and contaminants) which allowed for the identification of 486 different proteins annotated upon the NCBI database (http://www.ncbi.nlm.nih.gov/) and our transcritptome dataset. The mass spectrometry proteomics data have been deposited at the ProteomeXchange with identifier PXD000700. An extensive description of the AG proteome will help provide the basis for a better understanding of a number of reproductive mechanisms, including potentially spermatophore breakdown, dynamic functional and morphological changes in sperm cells and sperm acrosin enzyme vitality. Thus, the comprehensive catalog of proteins presented here can serve as a valuable reference for future studies of sperm maturation and regulatory mechanisms involved in crustacean reproduction. PMID:26305468

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

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.

Proteome reference maps of Medicago truncatula embryogenic cell cultures generated from single protoplasts.

PubMed

Imin, Nijat; De Jong, Femke; Mathesius, Ulrike; van Noorden, Giel; Saeed, Nasir A; Wang, Xin-Ding; Rose, Ray J; Rolfe, Barry G

2004-07-01

Using a combination of two-dimensional gel electrophoresis (2-DE) protein mapping and mass spectrometry (MS) analysis, we have established proteome reference maps of Medicago truncatula embryogenic tissue culture cells. The cultures were generated from single protoplasts, which provided a relatively homogeneous cell population. We used these to analyze protein expression at the globular stages of somatic embryogenesis, which is the earliest morphogenetic embryonic stage. Over 3000 proteins could reproducibly be resolved over a pI range of 4-11. Three hundred and twelve protein spots were extracted from colloidal Coomassie Blue-stained 2-DE gels and analyzed by matrix-assisted laser desorption/ionization-time of flight MS analysis and tandem MS sequencing. This enabled the identification of 169 protein spots representing 128 unique gene products using a publicly available expressed sequence tag database and the MASCOT search engine. These reference maps will be valuable for the investigation of the molecular events which occur during somatic embryogenesis in M. truncatula. The proteome reference maps and supplementary materials will be available and updated for public access at http://semele.anu.edu.au/.

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

Parallel Exploration of Interaction Space by BioID and Affinity Purification Coupled to Mass Spectrometry.

PubMed

Hesketh, Geoffrey G; Youn, Ji-Young; Samavarchi-Tehrani, Payman; Raught, Brian; Gingras, Anne-Claude

2017-01-01

Complete understanding of cellular function requires knowledge of the composition and dynamics of protein interaction networks, the importance of which spans all molecular cell biology fields. Mass spectrometry-based proteomics approaches are instrumental in this process, with affinity purification coupled to mass spectrometry (AP-MS) now widely used for defining interaction landscapes. Traditional AP-MS methods are well suited to providing information regarding the temporal aspects of soluble protein-protein interactions, but the requirement to maintain protein-protein interactions during cell lysis and AP means that both weak-affinity interactions and spatial information is lost. A more recently developed method called BioID employs the expression of bait proteins fused to a nonspecific biotin ligase, BirA*, that induces in vivo biotinylation of proximal proteins. Coupling this method to biotin affinity enrichment and mass spectrometry negates many of the solubility and interaction strength issues inherent in traditional AP-MS methods, and provides unparalleled spatial context for protein interactions. Here we describe the parallel implementation of both BioID and FLAG AP-MS allowing simultaneous exploration of both spatial and temporal aspects of protein interaction networks.

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.

New serum biomarkers for detection of tuberculosis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Liu, Ji-Yan; Jin, Lei; Zhao, Meng-Yuan; Zhang, Xin; Liu, Chi-Bo; Zhang, Yu-Xiang; Li, Fu-Jian; Zhou, Jian-Min; Wang, Hua-Jun; Li, Ji-Cheng

2011-10-01

New technologies for the early detection of tuberculosis (TB) are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. The aim of the present study was to screen for the potential protein biomarkers in serum for the diagnosis of TB using proteomic fingerprint technology. Proteomic fingerprint technology combining protein chips with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to profile the serum proteins from 50 patients with TB, 25 patients with lung disease other than TB, and 25 healthy volunteers. The protein fingerprint expression of all the serum samples and the resulting profiles between TB and control groups were analyzed with the Biomarker Wizard system. A total of 30 discriminating m/z peaks were detected that were related to TB (p<0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the three biomarkers (2024, 8007, and 8598 Da) generated excellent separation between the TB and control groups. The sensitivity was 84.0% and the specificity was 86.0%. Blind test data indicated a sensitivity of 80.0% and a specificity of 84.2%. The data suggested a potential application of SELDI-TOF MS as an effective technology to profile serum proteome, and with pattern analysis, a diagnostic model comprising three potential biomarkers was indicated to differentiate people with TB and healthy controls rapidly and precisely.

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

Comparison of Normal and Breast Cancer Cell lines using Proteome, Genome and Interactome data

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

Patwardhan, Anil J.; Strittmatter, Eric F.; Camp, David G.

2005-12-01

Normal and cancer cell line proteomes were profiled using high throughput mass spectrometry techniques. Application of both protein-level and peptide-level sample fractionation combined with LC-MS/MS analysis enabled the confident identification of 2,235 unmodified proteins representing a broad range of functional and compartmental classes. An iterative multi-step search strategy was used to identify post-translational modifications and detected several proteins that are preferentially modified in cancer cells. Information regarding both unmodified and modified protein forms was combined with publicly available gene expression and protein-protein interaction data. The resulting integrated dataset revealed several functionally related proteins that are differentially regulated between normal andmore » cancer cell lines.« less

From Marine Venoms to Drugs: Efficiently Supported by a Combination of Transcriptomics and Proteomics

PubMed Central

Xie, Bing; Huang, Yu; Baumann, Kate; Fry, Bryan Grieg; Shi, Qiong

2017-01-01

The potential of marine natural products to become new drugs is vast; however, research is still in its infancy. The chemical and biological diversity of marine toxins is immeasurable and as such an extraordinary resource for the discovery of new drugs. With the rapid development of next-generation sequencing (NGS) and liquid chromatography–tandem mass spectrometry (LC-MS/MS), it has been much easier and faster to identify more toxins and predict their functions with bioinformatics pipelines, which pave the way for novel drug developments. Here we provide an overview of related bioinformatics pipelines that have been supported by a combination of transcriptomics and proteomics for identification and function prediction of novel marine toxins. PMID:28358320

From Marine Venoms to Drugs: Efficiently Supported by a Combination of Transcriptomics and Proteomics.

PubMed

Xie, Bing; Huang, Yu; Baumann, Kate; Fry, Bryan Grieg; Shi, Qiong

2017-03-30

The potential of marine natural products to become new drugs is vast; however, research is still in its infancy. The chemical and biological diversity of marine toxins is immeasurable and as such an extraordinary resource for the discovery of new drugs. With the rapid development of next-generation sequencing (NGS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS), it has been much easier and faster to identify more toxins and predict their functions with bioinformatics pipelines, which pave the way for novel drug developments. Here we provide an overview of related bioinformatics pipelines that have been supported by a combination of transcriptomics and proteomics for identification and function prediction of novel marine toxins.

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.

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

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.

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

Baker, Erin Shammel; Burnum-Johnson, Kristin E.; Jacobs, Jon M.

Rapid diagnosis of disease states using less invasive, safer, and more clinically acceptable approaches than presently employed is an imperative goal for the field of medicine. While mass spectrometry (MS)-based proteomics approaches have attempted to meet these objectives, challenges such as the enormous dynamic range of protein concentrations in clinically relevant biofluid samples coupled with the need to address human biodiversity have slowed their employment. Herein, we report on the use of a new platform that addresses these challenges by coupling technical advances in rapid gas phase multiplexed ion mobility spectrometry (IMS) separations [1, 2] with liquid chromatography (LC) andmore » MS to dramatically increase measurement sensitivity and throughput, further enabling future MS-based clinical applications. An initial application of the LC-IMS-MS platform for the analysis of blood serum samples from stratified post-liver transplant patients with recurrent fibrosis progression illustrates its potential utility for disease characterization and use in personalized medicine [3, 4].« less

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

PubMed Central

Patel, Bhavinkumar B.; Kelsen, Steven G.; Braverman, Alan; Swinton, Derrick J.; Gafken, Philip R.; Jones, Lisa A.; Lane, William S.; Neveu, John M.; Leung, Hon-Chiu E.; Shaffer, Scott A.; Leszyk, John D.; Stanley, Bruce A.; Fox, Todd E.; Stanley, Anne; Hall, Michael J.; Hampel, Heather; South, Christopher D.; de la Chapelle, Albert; Burt, Randall W.; Jones, David A.; Kopelovich, Levy; Yeung, Anthony T.

2013-01-01

Plasma proteomic experiments performed rapidly and economically using several of the latest high-resolution mass spectrometers were compared. Four quantitative hyperfractionated plasma proteomics experiments were analyzed in replicates by two AB SCIEX TripleTOF 5600 and three Thermo Scientific Orbitrap (Elite/LTQ-Orbitrap Velos/Q Exactive) instruments. Each experiment compared two iTRAQ isobaric-labeled immunodepleted plasma proteomes, provided as 30 labeled peptide fractions. 480 LC-MS/MS runs delivered >250 GB of data in two months. Several analysis algorithms were compared. At 1 % false discovery rate, the relative comparative findings concluded that the Thermo Scientific Q Exactive Mass Spectrometer resulted in the highest number of identified proteins and unique sequences with iTRAQ quantitation. The confidence of iTRAQ fold-change for each protein is dependent on the overall ion statistics (Mascot Protein Score) attainable by each instrument. The benchmarking also suggested how to further improve the mass spectrometry parameters and HPLC conditions. Our findings highlight the special challenges presented by the low abundance peptide ions of iTRAQ plasma proteome because the dynamic range of plasma protein abundance is uniquely high compared with cell lysates, necessitating high instrument sensitivity. PMID:24004147

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

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

Tabb, David L.; Wang, Xia; Carr, Steven A.

2016-03-04

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilarmore » workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation. From these assessments we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61-93% of the time. When comparing across different instruments and quantitative technologies, differential genes were reproduced by other data sets from 67-99% of the time. Projecting gene differences to biological pathways and networks increased the similarities. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.« less

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

PubMed

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

2013-11-19

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

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

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

Targeted Approach for Proteomic Analysis of a Hidden Membrane Protein.

PubMed

Martins-Marques, Tania; Anjo, Sandra I; Ribeiro-Rodrigues, Teresa; Manadas, Bruno; Girao, Henrique

2017-01-01

Given the properties of plasma membrane proteins, namely, their hydrophobicity, low solubility, and high resistance to digestion and extraction, their identification by traditional mass spectrometry (MS) has been a challenging task. Hence, proteomic studies involving the transmembrane protein connexin43 (Cx43) are scarce. Additionally, studies demonstrating the presence of proteins embedded in the lipid bilayer of extracellular vesicles (EVs) are difficult to perform and require specific changes and fine adjustments in the experimental and technical procedure to allow their detection by MS. In this review, we provide a detailed description of the protocol we have used to detect Cx43 in EVs of human peripheral blood. This includes some of the modifications that we have introduced in order to improve the detection of Cx43 in EVs, including an optimization of vesicle isolation, Cx43 purification, MS acquisition data, and further analysis.

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

PubMed

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

2016-08-01

Quantitative mass spectrometry data necessitates an analytical pipeline that captures the accuracy and comprehensiveness of the experiments. Currently, data analysis is often coupled to specific software packages, which restricts the analysis to a given workflow and precludes a more thorough characterization of the data by other complementary tools. To address this, we have developed PyQuant, a cross-platform mass spectrometry data quantification application that is compatible with existing frameworks and can be used as a stand-alone quantification tool. PyQuant supports most types of quantitative mass spectrometry data including SILAC, NeuCode, (15)N, (13)C, or (18)O and chemical methods such as iTRAQ or TMT and provides the option of adding custom labeling strategies. In addition, PyQuant can perform specialized analyses such as quantifying isotopically labeled samples where the label has been metabolized into other amino acids and targeted quantification of selected ions independent of spectral assignment. PyQuant is capable of quantifying search results from popular proteomic frameworks such as MaxQuant, Proteome Discoverer, and the Trans-Proteomic Pipeline in addition to several standalone search engines. We have found that PyQuant routinely quantifies a greater proportion of spectral assignments, with increases ranging from 25-45% in this study. Finally, PyQuant is capable of complementing spectral assignments between replicates to quantify ions missed because of lack of MS/MS fragmentation or that were omitted because of issues such as spectra quality or false discovery rates. This results in an increase of biologically useful data available for interpretation. In summary, PyQuant is a flexible mass spectrometry data quantification platform that is capable of interfacing with a variety of existing formats and is highly customizable, which permits easy configuration for custom analysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

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

Proteomic analysis of protein deposits on worn daily wear silicone hydrogel contact lenses

PubMed Central

Wei, Xiaojia; Aliwarga, Yulina; Carnt, Nicole A.; Garrett, Qian; Willcox, Mark D.P.

2008-01-01

Purpose Previous studies have demonstrated deposition of tear proteins onto worn contact lenses. In this study, we used proteomic techniques to analyze the protein deposits extracted from worn daily wear silicone hydrogel contact lenses in combination with different lens care solutions. Methods Worn lenses were collected and protein deposits extracted using urea and surfactant. Protein extracts were desalted, concentrated, and then separated using one-dimensional gel electrophoresis. Individual protein components in extracts were identified using liquid chromatography combined with tandem mass spectrometry (LC-MS-MS) after trypsin digestion. Results One-dimensional gel electrophoresis revealed that lysozyme and other small proteins (around 20 kDa) were the most abundant proteins in the extracts. LC-MS-MS revealed a wide array of proteins in lens extracts with lysozyme and lipocalin 1 being the most commonly identified in deposit extracts. Conclusions Worn contact lenses deposit a wide array of proteins from tear film and other sources. Protein deposit profiles varied and were specific for each contact lens material. PMID:18989384

Metabolomic Insight into Lipid and Protein Profile in Diabetes Using Mass Spectrometry.

PubMed

Bukowiecka-Matusiak, Malgorzata; Chmielewska-Kassassir, Malgorzata; Szczesna, Dorota; Wozniak, Lucyna A

2016-01-01

In recent years, metabolomics has become a necessary tool for understanding the impact of external and pathological factors on the operation of biological systems. The first reports of metabolomics date back to the 1970s, however, the area only began to develop dynamically at the beginning of this century and has proved effective only during the present decade. The five primary tools used in this form of analysis are NMR spectrometry, HPLC, TLC-UV, GC-MS and LC-MS/MS, with MS as the most universal approach, particularly when used together with chromatographic separation and NMR. Diabetes mellitus type 2 (T2DM) is a rapidly growing problem with global consequences. The metabolomic approach has been extensively applied to examining T2DM, insulin resistance and obesity, not only to assess the development of the disease, but also to discover its potential biomarkers. The presented review summarizes current studies on lipidomic and proteomic profiles in the context of different types of diabetes mellitus disease (T1DM, T2DM and GDM), as determined by chromatography-coupled mass spectrometry.

A compatible exon-exon junction database for the identification of exon skipping events using tandem mass spectrum data.

PubMed

Mo, Fan; Hong, Xu; Gao, Feng; Du, Lin; Wang, Jun; Omenn, Gilbert S; Lin, Biaoyang

2008-12-16

Alternative splicing is an important gene regulation mechanism. It is estimated that about 74% of multi-exon human genes have alternative splicing. High throughput tandem (MS/MS) mass spectrometry provides valuable information for rapidly identifying potentially novel alternatively-spliced protein products from experimental datasets. However, the ability to identify alternative splicing events through tandem mass spectrometry depends on the database against which the spectra are searched. We wrote scripts in perl, Bioperl, mysql and Ensembl API and built a theoretical exon-exon junction protein database to account for all possible combinations of exons for a gene while keeping the frame of translation (i.e., keeping only in-phase exon-exon combinations) from the Ensembl Core Database. Using our liver cancer MS/MS dataset, we identified a total of 488 non-redundant peptides that represent putative exon skipping events. Our exon-exon junction database provides the scientific community with an efficient means to identify novel alternatively spliced (exon skipping) protein isoforms using mass spectrometry data. This database will be useful in annotating genome structures using rapidly accumulating proteomics data.

Proteomics in Diagnostic Pathology

PubMed Central

Chaurand, Pierre; Sanders, Melinda E.; Jensen, Roy A.; Caprioli, Richard M.

2004-01-01

Direct tissue profiling and imaging mass spectrometry (MS) provide a molecular assessment of numerous expressed proteins within a tissue sample. MALDI MS (matrix-assisted laser desorption ionization) analysis of thin tissue sections results in the visualization of 500 to 1000 individual protein signals in the molecular weight range from 2000 to over 200,000. These signals directly correlate with protein distribution within a specific region of the tissue sample. The systematic investigation of the section allows the construction of ion density maps, or specific molecular images, for virtually every signal detected in the analysis. Ultimately, hundreds of images, each at a specific molecular weight, may be obtained. To date, profiling and imaging MS has been applied to multiple diseased tissues, including human non-small cell lung tumors, gliomas, and breast tumors. Interrogation of the resulting complex MS data sets using modern biocomputational tools has resulted in identification of both disease-state and patient-prognosis specific protein patterns. These studies suggest that such proteomic information will become more and more important in assessing disease progression, prognosis, and drug efficacy. Molecular histology has been known for some time and its value clear in the field of pathology. Imaging mass spectrometry brings a new dimension of molecular data, one focusing on the disease phenotype. The present article reviews the state of the art of the technology and its complementarity with traditional histopathological analyses. PMID:15466373

Species-specific identification of collagen components in Colla corii asini using a nano-liquid chromatography tandem mass spectrometry proteomics approach.

PubMed

Li, Xue; Shi, Feng; Gong, Liping; Hang, Baojian; Li, Daoyuan; Chi, Lianli

2017-01-01

Colla corii asini (CCA) is a protein-based traditional Chinese medicine made from donkey skins. Because it has the ability to nourish blood, its demand is increasing rapidly. The shortage of donkey skins increases the risk of the adulteration of CCA products with other animal skins. To ensure the drug efficacy and safety of CCA products, a proteomics technique was applied to reveal proteins in the skins of donkey, horse, cattle, and pig. Species-specific peptides for each animal species were predicted using bioinformatics, and their presence in the skins and gelatin samples was examined by nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS). One unique marker peptide for each animal species was selected to develop an LC-MS/MS multiple reaction monitoring method. The capability of this method to identify donkey, horse, cattle, and pig materials was demonstrated by analyzing in-house-made donkey gelatins containing different amounts of other animal skins and commercial CCA products. The adulteration of non-donkey species could be sensitively detected at a low level of 0.5%. Hybrid animals, such as mules and hinnies, were also differentiated from donkeys. We provide a practical tool for the quality control of CCA products. The strategy can also be used to study other important traditional Chinese medicines which contain animal proteins.

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

Compositional complexity of the mitochondrial proteome of a unicellular eukaryote (Acanthamoeba castellanii, supergroup Amoebozoa) rivals that of animals, fungi, and plants.

PubMed

Gawryluk, Ryan M R; Chisholm, Kenneth A; Pinto, Devanand M; Gray, Michael W

2014-09-23

We present a combined proteomic and bioinformatic investigation of mitochondrial proteins from the amoeboid protist Acanthamoeba castellanii, the first such comprehensive investigation in a free-living member of the supergroup Amoebozoa. This protist was chosen both for its phylogenetic position (as a sister to animals and fungi) and its ecological ubiquity and physiological flexibility. We report 1033 A. castellanii mitochondrial protein sequences, 709 supported by mass spectrometry data (676 nucleus-encoded and 33 mitochondrion-encoded), including two previously unannotated mtDNA-encoded proteins, which we identify as highly divergent mitochondrial ribosomal proteins. Other notable findings include duplicate proteins for all of the enzymes of the tricarboxylic acid (TCA) cycle-which, along with the identification of a mitochondrial malate synthase-isocitrate lyase fusion protein, suggests the interesting possibility that the glyoxylate cycle operates in A. castellanii mitochondria. Additionally, the A. castellanii genome encodes an unusually high number (at least 29) of mitochondrion-targeted pentatricopeptide repeat (PPR) proteins, organellar RNA metabolism factors in other organisms. We discuss several key mitochondrial pathways, including DNA replication, transcription and translation, protein degradation, protein import and Fe-S cluster biosynthesis, highlighting similarities and differences in these pathways in other eukaryotes. In compositional and functional complexity, the mitochondrial proteome of A. castellanii rivals that of multicellular eukaryotes. Comprehensive proteomic surveys of mitochondria have been undertaken in a limited number of predominantly multicellular eukaryotes. This phylogenetically narrow perspective constrains and biases our insights into mitochondrial function and evolution, as it neglects protists, which account for most of the evolutionary and functional diversity within eukaryotes. We report here the first comprehensive investigation of the mitochondrial proteome in a member (A. castellanii) of the eukaryotic supergroup Amoebozoa. Through a combination of tandem mass spectrometry (MS/MS) and in silico data mining, we have retrieved 1033 candidate mitochondrial protein sequences, 709 having MS support. These data were used to reconstruct the metabolic pathways and protein complexes of A. castellanii mitochondria, and were integrated with data from other characterized mitochondrial proteomes to augment our understanding of mitochondrial proteome evolution. Our results demonstrate the power of combining direct proteomic and bioinformatic approaches in the discovery of novel mitochondrial proteins, both nucleus-encoded and mitochondrion-encoded, and highlight the compositional complexity of the A. castellanii mitochondrial proteome, which rivals that of animals, fungi and plants. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Rapid Assessment of Contaminants and Interferences in Mass Spectrometry Data Using Skyline

NASA Astrophysics Data System (ADS)

Rardin, Matthew J.

2018-04-01

Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g., detergents) necessitating a variety of sample cleanup procedures. Efforts to understand and mitigate sample contamination are a continual source of disruption with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, I developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows rapid assessment of sample integrity and indicates potential sources of contamination. [Figure not available: see fulltext.

Evaluation of two-dimensional electrophoresis and liquid chromatography – tandem mass spectrometry for tissue-specific protein profiling of laser-microdissected plant samples

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

Schad, Martina; Lipton, Mary S.; Giavalisco, Patrick

2005-07-14

Laser microdissection (LM) allows the collection of homogeneous tissue- and cell specific plant samples. The employment of this technique with subsequent protein analysis has thus far not been reported for plant tissues, probably due to the difficulties associated with defining a reasonable cellular morphology and, in parallel, allowing efficient protein extraction from tissue samples. The relatively large sample amount needed for successful proteome analysis is an additional issue that complicates protein profiling on a tissue- or even cell-specific level. In contrast to transcript profiling that can be performed from very small sample amounts due to efficient amplification strategies, there ismore » as yet no amplification procedure for proteins available. In the current study, we compared different tissue preparation techniques prior to LM/laser pressure catapulting (LMPC) with respect to their suitability for protein retrieval. Cryosectioning was identified as the best compromise between tissue morphology and effective protein extraction. After collection of vascular bundles from Arabidopsis thaliana stem tissue by LMPC, proteins were extracted and subjected to protein analysis, either by classical two-dimensional gel electrophoresis (2-DE), or by high-efficiency liquid chromatography (LC) in conjunction with tandem mass spectrometry (MS/MS). Our results demonstrate that both methods can be used with LMPC collected plant material. But because of the significantly lower sample amount required for LC-MS/MS than for 2-DE, the combination of LMPC and LC-MS/MS has a higher potential to promote comprehensive proteome analysis of specific plant tissues.« less

Comprehensive proteomic analysis of mineral nanoparticles derived from human body fluids and analyzed by liquid chromatography-tandem mass spectrometry.

PubMed

Martel, Jan; Young, David; Young, Andrew; Wu, Cheng-Yeu; Chen, Chi-De; Yu, Jau-Song; Young, John D

2011-11-01

Mineralo-protein nanoparticles (NPs) formed spontaneously in the body have been associated with ectopic calcifications seen in atherosclerosis, chronic degenerative diseases, and kidney stone formation. Synthetic NPs are also known to become coated with proteins when they come in contact with body fluids. Identifying the proteins found in NPs should help unravel how NPs are formed in the body and how NPs in general, be they synthetic or naturally formed, interact within the body. Here, we developed a proteomic approach based on liquid chromatography (LC) and tandem mass spectrometry (MS/MS) to determine the protein composition of carbonate-apatite NPs derived from human body fluids (serum, urine, cerebrospinal fluid, ascites, pleural effusion, and synovial fluid). LC-MS/MS provided not only an efficient and comprehensive determination of the protein constituents, but also a semiquantitative ranking of the identified proteins. Notably, the identified NP proteins mirrored the protein composition of the contacting body fluids, with albumin, fetuin-A, complement C3, α-1-antitrypsin, prothrombin, and apolipoproteins A1 and B-100 being consistently associated with the particles. Since several coagulation factors, calcification inhibitors, complement proteins, immune regulators, protease inhibitors, and lipid/molecule carriers can all become NP constituents, our results suggest that mineralo-protein complexes may interface with distinct biochemical pathways in the body depending on their protein composition. We propose that LC-MS/MS be used to characterize proteins found in both synthetic and natural NPs. Copyright © 2011 Elsevier Inc. All rights reserved.

Identification of Potential Biomarkers for Rhegmatogenous Retinal Detachment Associated with Choroidal Detachment by Vitreous iTRAQ-Based Proteomic Profiling

PubMed Central

Wu, Zhifeng; Ding, Nannan; Yu, Mengxi; Wang, Ke; Luo, Shasha; Zou, Wenjun; Zhou, Ying; Yan, Biao; Jiang, Qin

2016-01-01

Rhegmatogenous retinal detachment associated with choroidal detachment (RRDCD) is a complicated and serious type of rhegmatogenous retinal detachment (RRD). In this study, we identified differentially expressed proteins in the vitreous humors of RRDCD and RRD using isobaric tags for relative and absolute quantitation (iTRAQ) combined with nano-liquid chromatography-electrospray ion trap-mass spectrometry-mass spectrometry (nano-LC-ESI-MS/MS) and bioinformatic analysis. Our result shows that 103 differentially expressed proteins, including 54 up-regulated and 49 down-regulated proteins were identified in RRDCD. Gene ontology (GO) analysis suggested that most of the differentially expressed proteins were extracellular．The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis suggested that proteins related to complement and coagulation cascades were significantly enriched. iTRAQ-based proteomic profiling reveals that complement and coagulation cascades and inflammation may play important roles in the pathogenesis of RRDCD. This study may provide novel insights into the pathogenesis of RRDCD and offer potential opportunities for the diagnosis and treatment of RRDCD. PMID:27941623

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

PubMed

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

2016-10-18

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

An evaluation of coral lophelia pertusa mucus as an analytical matrix for environmental monitoring: A preliminary proteomic study.

PubMed

Provan, Fiona; Nilsen, Mari Mæland; Larssen, Eivind; Uleberg, Kai-Erik; Sydnes, Magne O; Lyng, Emily; Øysæd, Kjell Birger; Baussant, Thierry

2016-01-01

For the environmental monitoring of coral, mucus appears to be an appropriate biological matrix due to its array of functions in coral biology and the non-intrusive manner in which it can be collected. The aim of the present study was to evaluate the feasibility of using mucus of the stony coral Lophelia pertusa (L. pertusa) as an analytical matrix for discovery of biomarkers used for environmental monitoring. More specifically, to assess whether a mass-spectrometry-based proteomic approach can be applied to characterize the protein composition of coral mucus and changes related to petroleum discharges at the seafloor. Surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS) screening analyses of orange and white L. pertusa showed that the mucosal protein composition varies significantly with color phenotype, a pattern not reported prior to this study. Hence, to reduce variability from phenotype difference, L. pertusa white individuals only were selected to characterize in more detail the basal protein composition in mucus using liquid chromatography, mass spectrometry, mass spectrometry (LC-MS/MS). In total, 297 proteins were identified in L. pertusa mucus of unexposed coral individuals. Individuals exposed to drill cuttings in the range 2 to 12 mg/L showed modifications in coral mucus protein composition compared to unexposed corals. Although the results were somewhat inconsistent between individuals and require further validation in both the lab and the field, this study demonstrated preliminary encouraging results for discovery of protein markers in coral mucus that might provide more comprehensive insight into potential consequences attributed to anthropogenic stressors and may be used in future monitoring of coral health.

A Century of Progress in Molecular Mass Spectrometry

NASA Astrophysics Data System (ADS)

McLafferty, Fred W.

2011-07-01

The first mass spectrum of a molecule was measured by J.J. Thomson in 1910. Mass spectrometry (MS) soon became crucial to the study of isotopes and atomic weights and to the development of atomic weapons for World War II. Its notable applications to molecules began with the quantitative analysis of light hydrocarbons during World War II. When I joined the Dow Chemical Company in 1950, MS was not favored by organic chemists. This situation improved only with an increased understanding of gaseous ion chemistry, which was obtained through the use of extensive reference data. Gas chromatography-MS was developed in 1956, and tandem MS was first used a decade later. In neutralization-reionization MS, an unusual, unstable species is prepared by ion-beam neutralization and characterized by reionization. Electrospray ionization of a protein mixture produces its corresponding ionized molecules. In top-down proteomics, ions from an individual component can be mass separated and subjected to collision-activated and electron-capture dissociation to provide extensive sequence information.

Evaluation of SDS depletion using an affinity spin column and IMS-MS detection

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

Hengel, Shawna M.; Floyd, Erica A.; Baker, Erin Shammel

2012-11-01

While the use of detergents is necessary for a variety of protein isolation preparation protocols, often prior to mass spectral (MS) analysis, they are not compatible with MS analysis due to ion suppression and adduct formation. This manuscript describes optimization of detergent removal, using commercially available SDS depletion spin columns containing an affinity resin, providing for both increased protein recovery and thorough SDS removal. Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) allowed for a concurrent analysis of both analyte and detergent. In the case of both proteins and peptides, higher detergent concentrations than previously reported provided an increase ofmore » sample recovery; however there was a limit as SDS was detected by IMS-MS at higher levels of SDS indicating incomplete detergent depletion. The results also suggest optimal conditions for SDS removal are dependent on the sample concentration. Overall, this study provides a useful guide for proteomic studies where SDS is required for efficient sample preparation.« less

Proteomic Profiling of the Pituitary Gland in Studies of Psychiatric Disorders.

PubMed

Krishnamurthy, Divya; Rahmoune, Hassan; Guest, Paul C

2017-01-01

Psychiatric disorders have been associated with perturbations of the hypothalamic-pituitary-adrenal axis. Therefore, proteomic studies of the pituitary gland have the potential to provide new insights into the underlying pathways affected in these conditions as well as identify new biomarkers or targets for use in developing improved medications. This chapter describes a protocol for preparation of pituitary protein extracts followed by characterization of the pituitary proteome by label-free liquid chromatography-tandem mass spectrometry in expression mode (LC-MS E ). The main focus was on establishing a method for identifying the major pituitary hormones and accessory proteins as many of these have already been implicated in psychiatric diseases.

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

Milk Bottom-Up Proteomics: Method Optimization

PubMed Central

Vincent, Delphine; Ezernieks, Vilnis; Elkins, Aaron; Nguyen, Nga; Moate, Peter J.; Cocks, Benjamin G.; Rochfort, Simone

2016-01-01

Milk is a complex fluid whose proteome displays a diverse set of proteins of high abundance such as caseins and medium to low abundance whey proteins such as ß-lactoglobulin, lactoferrin, immunoglobulins, glycoproteins, peptide hormones, and enzymes. A sample preparation method that enables high reproducibility and throughput is key in reliably identifying proteins present or proteins responding to conditions such as a diet, health or genetics. Using skim milk samples from Jersey and Holstein-Friesian cows, we compared three extraction procedures which have not previously been applied to samples of cows' milk. Method A (urea) involved a simple dilution of the milk in a urea-based buffer, method B (TCA/acetone) involved a trichloroacetic acid (TCA)/acetone precipitation, and method C (methanol/chloroform) involved a tri-phasic partition method in chloroform/methanol solution. Protein assays, SDS-PAGE profiling, and trypsin digestion followed by nanoHPLC-electrospray ionization-tandem mass spectrometry (nLC-ESI-MS/MS) analyses were performed to assess their efficiency. Replicates were used at each analytical step (extraction, digestion, injection) to assess reproducibility. Mass spectrometry (MS) data are available via ProteomeXchange with identifier PXD002529. Overall 186 unique accessions, major and minor proteins, were identified with a combination of methods. Method C (methanol/chloroform) yielded the best resolved SDS-patterns and highest protein recovery rates, method A (urea) yielded the greatest number of accessions, and, of the three procedures, method B (TCA/acetone) was the least compatible of all with a wide range of downstream analytical procedures. Our results also highlighted breed differences between the proteins in milk of Jersey and Holstein-Friesian cows. PMID:26793233

The advancement of chemical cross-linking and mass spectrometry for structural proteomics: from single proteins to protein interaction networks.

PubMed

Sinz, Andrea

2014-12-01

During the last 15 years, chemical cross-linking combined with mass spectrometry (MS) and computational modeling has advanced from investigating 3D-structures of isolated proteins to deciphering protein interaction networks. In this article, the author discusses the advent, the development and the current status of the chemical cross-linking/MS strategy in the context of recent technological developments. A direct way to probe in vivo protein-protein interactions is by site-specific incorporation of genetically encoded photo-reactive amino acids or by non-directed incorporation of photo-reactive amino acids. As the chemical cross-linking/MS approach allows the capture of transient and weak interactions, it has the potential to become a routine technique for unraveling protein interaction networks in their natural cellular environment.

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.

Mass spectrometric determination of early and advanced glycation in biology.

PubMed

Rabbani, Naila; Ashour, Amal; Thornalley, Paul J

2016-08-01

Protein glycation in biological systems occurs predominantly on lysine, arginine and N-terminal residues of proteins. Major quantitative glycation adducts are found at mean extents of modification of 1-5 mol percent of proteins. These are glucose-derived fructosamine on lysine and N-terminal residues of proteins, methylglyoxal-derived hydroimidazolone on arginine residues and N(ε)-carboxymethyl-lysine residues mainly formed by the oxidative degradation of fructosamine. Total glycation adducts of different types are quantified by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring mode. Metabolism of glycated proteins is followed by LC-MS/MS of glycation free adducts as minor components of the amino acid metabolome. Glycated proteins and sites of modification within them - amino acid residues modified by the glycating agent moiety - are identified and quantified by label-free and stable isotope labelling with amino acids in cell culture (SILAC) high resolution mass spectrometry. Sites of glycation by glucose and methylglyoxal in selected proteins are listed. Key issues in applying proteomics techniques to analysis of glycated proteins are: (i) avoiding compromise of analysis by formation, loss and relocation of glycation adducts in pre-analytic processing; (ii) specificity of immunoaffinity enrichment procedures, (iii) maximizing protein sequence coverage in mass spectrometric analysis for detection of glycation sites, and (iv) development of bioinformatics tools for prediction of protein glycation sites. Protein glycation studies have important applications in biology, ageing and translational medicine - particularly on studies of obesity, diabetes, cardiovascular disease, renal failure, neurological disorders and cancer. Mass spectrometric analysis of glycated proteins has yet to find widespread use clinically. Future use in health screening, disease diagnosis and therapeutic monitoring, and drug and functional food development is expected. A protocol for high resolution mass spectrometry proteomics of glycated proteins is given.

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.

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).

Proteomic Biomarkers for Acute Interstitial Lung Disease in Gefitinib-Treated Japanese Lung Cancer Patients

PubMed Central

Kawakami, Takao; Nagasaka, Keiko; Takami, Sachiko; Wada, Kazuya; Tu, Hsiao-Kun; Otsuji, Makiko; Kyono, Yutaka; Dobashi, Tae; Komatsu, Yasuhiko; Kihara, Makoto; Akimoto, Shingo; Peers, Ian S.; South, Marie C.; Higenbottam, Tim; Fukuoka, Masahiro; Nakata, Koichiro; Ohe, Yuichiro; Kudoh, Shoji; Clausen, Ib Groth; Nishimura, Toshihide; Marko-Varga, György; Kato, Harubumi

2011-01-01

Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10−25), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control. PMID:21799770

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

Comparative Proteomic Analysis of Hymenolepis diminuta Cysticercoid and Adult Stages

PubMed Central

Sulima, Anna; Savijoki, Kirsi; Bień, Justyna; Näreaho, Anu; Sałamatin, Rusłan; Conn, David Bruce; Młocicki, Daniel

2018-01-01

Cestodiases are common parasitic diseases of animals and humans. As cestodes have complex lifecycles, hexacanth larvae, metacestodes (including cysticercoids), and adults produce proteins allowing them to establish invasion and to survive in the hostile environment of the host. Hymenolepis diminuta is the most commonly used model cestode in experimental parasitology. The aims of the present study were to perform a comparative proteomic analysis of two consecutive developmental stages of H. diminuta (cysticercoid and adult) and to distinguish proteins which might be characteristic for each of the stages from those shared by both stages. Somatic proteins of H. diminuta were isolated from 6-week-old cysticercoids and adult tapeworms. Cysticercoids were obtained from experimentally infected beetles, Tenebrio molitor, whereas adult worms were collected from experimentally infected rats. Proteins were separated by GeLC-MS/MS (one dimensional gel electrophoresis coupled with liquid chromatography and tandem mass spectrometry). Additionally protein samples were digested in-liquid and identified by LC-MS/MS. The identified proteins were classified according to molecular function, cellular components and biological processes. Our study showed a number of differences and similarities in the protein profiles of cysticercoids and adults; 233 cysticercoid and 182 adult proteins were identified. From these proteins, 131 were present only in the cysticercoid and 80 only in the adult stage samples. Both developmental stages shared 102 proteins; among which six represented immunomodulators and one is a potential drug target. In-liquid digestion and LC-MS/MS complemented and confirmed some of the GeLC-MS/MS identifications. Possible roles and functions of proteins identified with both proteomic approaches are discussed. PMID:29379475

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

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

Proteome analysis of bell pepper (Capsicum annuum L.) chromoplasts.

PubMed

Siddique, Muhammad Asim; Grossmann, Jonas; Gruissem, Wilhelm; Baginsky, Sacha

2006-12-01

We report a comprehensive proteome analysis of chromoplasts from bell pepper (Capsicum annuum L.). The combination of a novel strategy for database-independent detection of proteins from tandem mass spectrometry (MS/MS) data with standard database searches allowed us to identify 151 proteins with a high level of confidence. These include several well-known plastid proteins but also novel proteins that were not previously reported from other plastid proteome studies. The majority of the identified proteins are active in plastid carbohydrate and amino acid metabolism. Among the most abundant individual proteins are capsanthin/capsorubin synthase and fibrillin, which are involved in the synthesis and storage of carotenoids that accumulate to high levels in chromoplasts. The relative abundances of the identified chromoplast proteins differ remarkably compared with their abundances in other plastid types, suggesting a chromoplast-specific metabolic network. Our results provide an overview of the major metabolic pathways active in chromoplasts and extend existing knowledge about prevalent metabolic activities of different plastid types.

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

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.

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.

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

PubMed

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

2006-05-01

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

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

Tools for monitoring system suitability in LC MS/MS centric proteomic experiments.

PubMed

Bereman, Michael S

2015-03-01

With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1.

PubMed

Yi, Zhou; Manil-Ségalen, Marion; Sago, Laila; Glatigny, Annie; Redeker, Virginie; Legouis, Renaud; Mucchielli-Giorgi, Marie-Hélène

2016-05-06

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

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.

Towards a Proteomic Catalogue and Differential Annotation of Salivary Gland Proteins in Blood Fed Malaria Vector Anopheles culicifacies by Mass Spectrometry.

PubMed

Rawal, Ritu; Vijay, Sonam; Kadian, Kavita; Singh, Jagbir; Pande, Veena; Sharma, Arun

2016-01-01

In order to understand the importance of functional proteins in mosquito behavior, following blood meal, a baseline proteomic dataset is essential for providing insights into the physiology of blood feeding. Therefore, in this study as first step, in solution and 1-D electrophoresis digestion approach combined with tandem mass spectrometry (nano LC-MS/MS) and computational bioinformatics for data mining was used to prepare a baseline proteomic catalogue of salivary gland proteins of sugar fed An. culicifacies mosquitoes. A total of 106 proteins were identified and analyzed by SEQUEST algorithm against mosquito protein database from Uniprot/NCBI. Importantly, D7r1, D7r2, D7r4, salivary apyrase, anti-platelet protein, calreticulin, antigen 5 family proteins were identified and grouped on the basis of biological and functional roles. Secondly, differential protein expression and annotations between salivary glands of sugar fed vs blood fed mosquitoes was analyzed using 2-Delectrophoresis combined with MALDI-TOF mass spectrometry. The alterations in the differential expression of total 38 proteins was observed out of which 29 proteins like beclin-1, phosphorylating proteins, heme oxygenase 1, ferritin, apoptotic proteins, coagulation and immunity like, serine proteases, serpins, c-type lectin and protein in regulation of blood feeding behavior were found to be up regulated while 9 proteins related to blood feeding, juvenile hormone epoxide hydrolase ii, odorant binding proteins and energy metabolic enzymes were found to be down regulated. To our knowledge, this study provides a first time baseline proteomic dataset and functional annotations of An. culicifacies salivary gland proteins that may be involved during the blood feeding. Identification of differential salivary proteins between sugar fed and blood fed mosquitoes and their plausible role may provide insights into the physiological processes associated with feeding behavior and sporozoite transmission during the process of blood feeding.

Towards a Proteomic Catalogue and Differential Annotation of Salivary Gland Proteins in Blood Fed Malaria Vector Anopheles culicifacies by Mass Spectrometry

PubMed Central

Rawal, Ritu; Vijay, Sonam; Kadian, Kavita; Singh, Jagbir; Pande, Veena; Sharma, Arun

2016-01-01

In order to understand the importance of functional proteins in mosquito behavior, following blood meal, a baseline proteomic dataset is essential for providing insights into the physiology of blood feeding. Therefore, in this study as first step, in solution and 1-D electrophoresis digestion approach combined with tandem mass spectrometry (nano LC-MS/MS) and computational bioinformatics for data mining was used to prepare a baseline proteomic catalogue of salivary gland proteins of sugar fed An. culicifacies mosquitoes. A total of 106 proteins were identified and analyzed by SEQUEST algorithm against mosquito protein database from Uniprot/NCBI. Importantly, D7r1, D7r2, D7r4, salivary apyrase, anti-platelet protein, calreticulin, antigen 5 family proteins were identified and grouped on the basis of biological and functional roles. Secondly, differential protein expression and annotations between salivary glands of sugar fed vs blood fed mosquitoes was analyzed using 2-Delectrophoresis combined with MALDI-TOF mass spectrometry. The alterations in the differential expression of total 38 proteins was observed out of which 29 proteins like beclin-1, phosphorylating proteins, heme oxygenase 1, ferritin, apoptotic proteins, coagulation and immunity like, serine proteases, serpins, c-type lectin and protein in regulation of blood feeding behavior were found to be up regulated while 9 proteins related to blood feeding, juvenile hormone epoxide hydrolase ii, odorant binding proteins and energy metabolic enzymes were found to be down regulated. To our knowledge, this study provides a first time baseline proteomic dataset and functional annotations of An. culicifacies salivary gland proteins that may be involved during the blood feeding. Identification of differential salivary proteins between sugar fed and blood fed mosquitoes and their plausible role may provide insights into the physiological processes associated with feeding behavior and sporozoite transmission during the process of blood feeding. PMID:27602567

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.

Proteomic analysis of Arabidopsis thaliana (L.) Heynh responses to a generalist sucking pest (Myzus persicae Sulzer).

PubMed

Truong, D-H; Bauwens, J; Delaplace, P; Mazzucchelli, G; Lognay, G; Francis, F

2015-11-01

Herbivorous insects can cause severe cellular changes to plant foliage following infestations, depending on feeding behaviour. Here, a proteomic study was conducted to investigate the influence of green peach aphid (Myzus persicae Sulzer) as a polyphagous pest on the defence response of Arabidopsis thaliana (L.) Heynh after aphid colony establishment on the host plant (3 days). Analysis of about 574 protein spots on 2-DE gels revealed 31 differentially expressed protein spots. Twenty out of these 31 differential proteins were selected for analysis by mass spectrometry. In 12 of the 20 analysed spots, we identified seven and nine proteins using MALDI-TOF-MS and LC-ESI-MS/MS, respectively. Of the analysed spots, 25% contain two proteins. Different metabolic pathways were modulated in Arabidopsis leaves according to aphid feeding: most corresponded to carbohydrate, amino acid and energy metabolism, photosynthesis, defence response and translation. This paper has established a survey of early alterations induced in the proteome of Arabidopsis by M. persicae aphids. It provides valuable insights into the complex responses of plants to biological stress, particularly for herbivorous insects with sucking feeding behaviour. © 2015 German Botanical Society and The Royal Botanical Society of the Netherlands.

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

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

Proteomic Analysis of Cerebrospinal Fluid in a Fulminant Case of Multiple Sclerosis

PubMed Central

Füvesi, Judit; Hanrieder, Jörg; Bencsik, Krisztina; Rajda, Cecilia; Kovács, S. Krisztián; Kaizer, László; Beniczky, Sándor; Vécsei, László; Bergquist, Jonas

2012-01-01

Multiple Sclerosis (MS) is a chronic disease, but in rare fulminant cases rapid progression may lead to death shortly after diagnosis. Currently there is no diagnostic test to predict disease course. The aim of this study was to identify potential biomarkers/proteins related to rapid progression. We present the case history of a 15-year-old male MS patient. Cerebrospinal fluid (CSF) was taken at diagnosis and at the time of rapid progression leading to the patient’s death. Using isobaric tag labeling and nanoflow liquid chromatography in conjunction with matrix assisted laser desorption/ionization time of flight tandem mass spectrometry we quantitatively analyzed the protein content of two CSF samples from the patient with fulminant MS as well as one relapsing-remitting (RR) MS patient and one control headache patient, whose CSF analysis was normal. Seventy-eight proteins were identified and seven proteins were found to be more abundant in both fulminant MS samples but not in the RR MS sample compared to the control. These proteins are involved in the immune response, blood coagulation, cell proliferation and cell adhesion. In conclusion, in this pilot study we were able to show differences in the CSF proteome of a rapidly progressing MS patient compared to a more typical clinical form of MS and a control subject. PMID:22837721

Proteomics of Dense Core Secretory Vesicles Reveal Distinct Protein Categories for Secretion of Neuroeffectors for Cell-Cell Communication

PubMed Central

Wegrzyn, Jill L.; Bark, Steven J.; Funkelstein, Lydiane; Mosier, Charles; Yap, Angel; Kazemi-Esfarjani, Parasa; La Spada, Albert; Sigurdson, Christina; O’Connor, Daniel T.; Hook, Vivian

2010-01-01

Regulated secretion of neurotransmitters and neurohumoural factors from dense core secretory vesicles provides essential neuroeffectors for cell-cell communication in the nervous and endocrine systems. This study provides comprehensive proteomic characterization of the categories of proteins in chromaffin dense core secretory vesicles that participate in cell-cell communication from the adrenal medulla. Proteomic studies were conducted by nano-HPLC Chip MS/MS tandem mass spectrometry. Results demonstrate that these secretory vesicles contain proteins of distinct functional categories consisting of neuropeptides and neurohumoural factors, protease systems, neurotransmitter enzymes and transporters, receptors, enzymes for biochemical processes, reduction/oxidation regulation, ATPases, protein folding, lipid biochemistry, signal transduction, exocytosis, calcium regulation, as well as structural and cell adhesion proteins. The secretory vesicle proteomic data identified 371 distinct proteins in the soluble fraction and 384 distinct membrane proteins, for a total of 686 distinct secretory vesicle proteins. Notably, these proteomic analyses illustrate the presence of several neurological disease-related proteins in these secretory vesicles, including huntingtin interacting protein, cystatin C, ataxin 7, and prion protein. Overall, these findings demonstrate that multiple protein categories participate in dense core secretory vesicles for production, storage, and secretion of bioactive neuroeffectors for cell-cell communication in health and disease. PMID:20695487

Implementation of statistical process control for proteomic experiments via LC MS/MS.

PubMed

Bereman, Michael S; Johnson, Richard; Bollinger, James; Boss, Yuval; Shulman, Nick; MacLean, Brendan; Hoofnagle, Andrew N; MacCoss, Michael J

2014-04-01

Statistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. A tool has been developed termed Statistical Process Control in Proteomics (SProCoP) which implements aspects of SPC (e.g., control charts and Pareto analysis) into the Skyline proteomics software. It monitors five quality control metrics in a shotgun or targeted proteomic workflow. None of these metrics require peptide identification. The source code, written in the R statistical language, runs directly from the Skyline interface, which supports the use of raw data files from several of the mass spectrometry vendors. It provides real time evaluation of the chromatographic performance (e.g., retention time reproducibility, peak asymmetry, and resolution), and mass spectrometric performance (targeted peptide ion intensity and mass measurement accuracy for high resolving power instruments) via control charts. Thresholds are experiment- and instrument-specific and are determined empirically from user-defined quality control standards that enable the separation of random noise and systematic error. Finally, Pareto analysis provides a summary of performance metrics and guides the user to metrics with high variance. The utility of these charts to evaluate proteomic experiments is illustrated in two case studies.

[Search for potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry].

PubMed

Shevchenko, V E; Arnotskaia, N E; Ogorodnikova, E V; Davydov, M M; Ibraev, M A; Turkin, I N; Davydov, M I

2014-01-01

Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1-17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.

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

PubMed

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

2016-01-01

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

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.

Identification and Characterization of Human Proteoforms by Top-Down LC-21 Tesla FT-ICR Mass Spectrometry.

PubMed

Anderson, Lissa C; DeHart, Caroline J; Kaiser, Nathan K; Fellers, Ryan T; Smith, Donald F; Greer, Joseph B; LeDuc, Richard D; Blakney, Greg T; Thomas, Paul M; Kelleher, Neil L; Hendrickson, Christopher L

2017-02-03

Successful high-throughput characterization of intact proteins from complex biological samples by mass spectrometry requires instrumentation capable of high mass resolving power, mass accuracy, sensitivity, and spectral acquisition rate. These limitations often necessitate the performance of hundreds of LC-MS/MS experiments to obtain reasonable coverage of the targeted proteome, which is still typically limited to molecular weights below 30 kDa. The National High Magnetic Field Laboratory (NHMFL) recently installed a 21 T FT-ICR mass spectrometer, which is part of the NHMFL FT-ICR User Facility and available to all qualified users. Here we demonstrate top-down LC-21 T FT-ICR MS/MS of intact proteins derived from human colorectal cancer cell lysate. We identified a combined total of 684 unique protein entries observed as 3238 unique proteoforms at a 1% false discovery rate, based on rapid, data-dependent acquisition of collision-induced and electron-transfer dissociation tandem mass spectra from just 40 LC-MS/MS experiments. Our identifications included 372 proteoforms with molecular weights over 30 kDa detected at isotopic resolution, which substantially extends the accessible mass range for high-throughput top-down LC-MS/MS.

Open tubular lab-on-column/mass spectrometry for targeted proteomics of nanogram sample amounts.

PubMed

Hustoft, Hanne Kolsrud; Vehus, Tore; Brandtzaeg, Ole Kristian; Krauss, Stefan; Greibrokk, Tyge; Wilson, Steven Ray; Lundanes, Elsa

2014-01-01

A novel open tubular nanoproteomic platform featuring accelerated on-line protein digestion and high-resolution nano liquid chromatography mass spectrometry (LC-MS) has been developed. The platform features very narrow open tubular columns, and is hence particularly suited for limited sample amounts. For enzymatic digestion of proteins, samples are passed through a 20 µm inner diameter (ID) trypsin + endoproteinase Lys-C immobilized open tubular enzyme reactor (OTER). Resulting peptides are subsequently trapped on a monolithic pre-column and transferred on-line to a 10 µm ID porous layer open tubular (PLOT) liquid chromatography LC separation column. Wnt/ß-catenein signaling pathway (Wnt-pathway) proteins of potentially diagnostic value were digested+detected in targeted-MS/MS mode in small cell samples and tumor tissues within 120 minutes. For example, a potential biomarker Axin1 was identifiable in just 10 ng of sample (protein extract of ∼1,000 HCT15 colon cancer cells). In comprehensive mode, the current OTER-PLOT set-up could be used to identify approximately 1500 proteins in HCT15 cells using a relatively short digestion+detection cycle (240 minutes), outperforming previously reported on-line digestion/separation systems. The platform is fully automated utilizing common commercial instrumentation and parts, while the reactor and columns are simple to produce and have low carry-over. These initial results point to automated solutions for fast and very sensitive MS based proteomics, especially for samples of limited size.

Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome.

PubMed

Chetwynd, Andrew J; David, Arthur; Hill, Elizabeth M; Abdul-Sada, Alaa

2014-10-01

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra-high-pressure liquid chromatography-nanoelectrospray ionization-time-of-flight MS (nUHPLC-nESI-TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC-ESI-TOFMS, nUHPLC-nESI-TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000-fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC-nESI-TOFMS, supporting implementation of this platform as a novel approach for high-throughput (xeno)metabolomics. Copyright © 2014 John Wiley & Sons, Ltd.

Separation and identification of Musa acuminate Colla (banana) leaf proteins by two-dimensional gel electrophoresis and mass spectrometry.

PubMed

Lu, Y; Qi, Y X; Zhang, H; Zhang, H Q; Pu, J J; Xie, Y X

2013-12-19

To establish a proteomic reference map of Musa acuminate Colla (banana) leaf, we separated and identified leaf proteins using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Tryptic digests of 44 spots were subjected to peptide mass fingerprinting (PMF) by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS. Three spots that were not identified by MALDI-TOF MS analysis were identified by searching against the NCBInr, SwissProt, and expressed sequence tag (EST) databases. We identified 41 unique proteins. The majority of the identified leaf proteins were found to be involved in energy metabolism. The results indicate that 2D-PAGE is a sensitive and powerful technique for the separation and identification of Musa leaf proteins. A summary of the identified proteins and their putative functions is discussed.

Evolution of Orbitrap Mass Spectrometry Instrumentation

NASA Astrophysics Data System (ADS)

Eliuk, Shannon; Makarov, Alexander

2015-07-01

We discuss the evolution of OrbitrapTM mass spectrometry (MS) from its birth in the late 1990s to its current role as one of the most prominent techniques for MS. The Orbitrap mass analyzer is the first high-performance mass analyzer that employs trapping of ions in electrostatic fields. Tight integration with the ion injection process enables the high-resolution, mass accuracy, and sensitivity that have become essential for addressing analytical needs in numerous areas of research, as well as in routine analysis. We examine three major families of instruments (related to the LTQ Orbitrap, Q Exactive, and Orbitrap Fusion mass spectrometers) in the context of their historical development over the past ten eventful years. We discuss as well future trends and perspectives of Orbitrap MS. We illustrate the compelling potential of Orbitrap-based mass spectrometers as (ultra) high-resolution platforms, not only for high-end proteomic applications, but also for routine targeted analysis.

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

Kyle, Jennifer E.; Zhang, Xing; Weitz, Karl K.

Understanding how biological molecules are generated, metabolized and eliminated in living systems is important for interpreting processes such as immune response and disease pathology. While genomic and proteomic studies have provided vast amounts of information over the last several decades, interest in lipidomics has also grown due to improved analytical technologies revealing altered lipid metabolism in type 2 diabetes, cancer, and lipid storage disease. Liquid chromatography and mass spectrometry (LC-MS) measurements are currently the dominant approach for characterizing the lipidome by providing detailed information on the spatial and temporal composition of lipids. However, interpreting lipids’ biological roles is challenging duemore » to the existence of numerous structural and stereoisomers (i.e. distinct acyl chain and double-bond positions), which are unresolvable using present LC-MS approaches. Here we show that combining structurally-based ion mobility spectrometry (IMS) with LC-MS measurements distinguishes lipid isomers and allows insight into biological and disease processes.« less

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.

Analysis of Proteins, Protein Complexes, and Organellar Proteomes Using Sheathless Capillary Zone Electrophoresis - Native Mass Spectrometry

NASA Astrophysics Data System (ADS)

Belov, Arseniy M.; Viner, Rosa; Santos, Marcia R.; Horn, David M.; Bern, Marshall; Karger, Barry L.; Ivanov, Alexander R.

2017-12-01

Native mass spectrometry (MS) is a rapidly advancing field in the analysis of proteins, protein complexes, and macromolecular species of various types. The majority of native MS experiments reported to-date has been conducted using direct infusion of purified analytes into a mass spectrometer. In this study, capillary zone electrophoresis (CZE) was coupled online to Orbitrap mass spectrometers using a commercial sheathless interface to enable high-performance separation, identification, and structural characterization of limited amounts of purified proteins and protein complexes, the latter with preserved non-covalent associations under native conditions. The performance of both bare-fused silica and polyacrylamide-coated capillaries was assessed using mixtures of protein standards known to form non-covalent protein-protein and protein-ligand complexes. High-efficiency separation of native complexes is demonstrated using both capillary types, while the polyacrylamide neutral-coated capillary showed better reproducibility and higher efficiency for more complex samples. The platform was then evaluated for the determination of monoclonal antibody aggregation and for analysis of proteomes of limited complexity using a ribosomal isolate from E. coli. Native CZE-MS, using accurate single stage and tandem-MS measurements, enabled identification of proteoforms and non-covalent complexes at femtomole levels. This study demonstrates that native CZE-MS can serve as an orthogonal and complementary technique to conventional native MS methodologies with the advantages of low sample consumption, minimal sample processing and losses, and high throughput and sensitivity. This study presents a novel platform for analysis of ribosomes and other macromolecular complexes and organelles, with the potential for discovery of novel structural features defining cellular phenotypes (e.g., specialized ribosomes). [Figure not available: see fulltext.

Integration of electrochemistry with ultra-performance liquid chromatography/mass spectrometry.

PubMed

Cai, Yi; Zheng, Qiuling; Liu, Yong; Helmy, Roy; Loo, Joseph A; Chen, Hao

2015-01-01

This study presents the development of ultra-performance liquid chromatography (UPLC) mass spectrometry (MS) combined with electrochemistry (EC) for the first time and its application for the structural analysis of proteins/peptides that contain disulfide bonds. In our approach, a protein/peptide mixture sample undergoes a fast UPLC separation and subsequent electrochemical reduction in an electrochemical flow cell followed by online MS and tandem mass spectrometry (MS/MS) analyses. The electrochemical cell is coupled to the mass spectrometer using our recently developed desorption electrospray ionization (DESI) interface. Using this UPLC/EC/DESI-MS method, peptides that contain disulfide bonds can be differentiated from those without disulfide bonds, as the former are electroactive and reducible. MS/MS analysis of the disulfide-reduced peptide ions provides increased information on the sequence and disulfide-linkage pattern. In a reactive DESI- MS detection experiment in which a supercharging reagent was used to dope the DESI spray solvent, increased charging was obtained for the UPLC-separated proteins. Strikingly, upon online electrolytic reduction, supercharged proteins (e.g., α-lactalbumin) showed even higher charging, which will be useful in top- down protein structure MS analysis as increased charges are known to promote protein ion dissociation. Also, the separation speed and sensitivity are enhanced by approximately 1(~)2 orders of magnitude by using UPLC for the liquid chromatography (LC)/EC/MS platform, in comparison to the previously used high- performance liquid chromatography (HPLC). This UPLC/EC/DESI-MS method combines the power of fast UPLC separation, fast electrochemical conversion, and online MS structural analysis for a potentially valuable tool for proteomics research and bioanalysis.

Proteome data to explore the impact of pBClin15 on Bacillus cereus ATCC 14579.

PubMed

Madeira, Jean-Paul; Alpha-Bazin, Béatrice; Armengaud, Jean; Omer, Hélène; Duport, Catherine

2016-09-01

This data article reports changes in the cellular and exoproteome of B. cereus cured from pBClin15.Time-course changes of proteins were assessed by high-throughput nanoLC-MS/MS. We report all the peptides and proteins identified and quantified in B. cereus with and without pBClin15. Proteins were classified into functional groups using the information available in the KEGG classification and we reported their abundance in term of normalized spectral abundance factor. The repertoire of experimentally confirmed proteins of B. cereus presented here is the largest ever reported, and provides new insights into the interplay between pBClin15 and its host B. cereus ATCC 14579. The data reported here is related to a published shotgun proteomics analysis regarding the role of pBClin15, "Deciphering the interactions between the Bacillus cereus linear plasmid, pBClin15, and its host by high-throughput comparative proteomics" Madeira et al. [1]. All the associated mass spectrometry data have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (http://www.ebi.ac.uk/pride/), with the dataset identifier PRIDE: PXD001568, PRIDE: PXD002788 and PRIDE: PXD002789.

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.

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

PubMed Central

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

2011-01-01

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

Proteome screening of pleural effusions identifies IL1A as a diagnostic biomarker for non-small cell lung cancer.

PubMed

Li, Yuanyuan; Lian, Hengning; Jia, Qingzhu; Wan, Ying

2015-02-06

Non-small cell lung cancer (NSCLC) is a common malignant disease, and in ~10-20% of patients, pleural effusion is the first symptom. The pleural effusion proteome contains information on pulmonary disease that directly or indirectly reflects pathophysiological status. However, the proteome of pleural effusion in NSCLC patients is not well understood, nor is the variability in protein composition between malignant and benign pleural effusions. Here, we investigated the different proteins in pleural effusions from NSCLC and tuberculosis (TB) patients by using nano-scale liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. In total, 363 proteins were identified in the NSCLC pleural effusion proteome with a low false discovery rate (<1%), and 199 proteins were unique to NSCLC. The proteins in the NSCLC patients' pleural effusion were involved in cell adhesion, proteolysis, and cell migration. Furthermore, interleukin 1 alpha (IL1A), a protein that regulates tumor growth, angiogenesis, and metastasis, was significantly more abundant in the NSCLC group compared to the TB group, a finding that was validated with an ELISA assay. Copyright © 2014 Elsevier Inc. All rights reserved.

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.

PubMed

Hoffman, Melissa A; Fang, Bin; Haura, Eric B; Rix, Uwe; Koomen, John M

2018-01-05

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

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

PubMed

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

2018-04-15

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

Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment

PubMed Central

Dasari, Surendra; Chambers, Matthew C.; Martinez, Misti A.; Carpenter, Kristin L.; Ham, Amy-Joan L.; Vega-Montoto, Lorenzo J.; Tabb, David L.

2012-01-01

Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines. PMID:22217208

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

PubMed

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

2006-09-01

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

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.

A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma.

PubMed

Ahn, Yeong Hee; Shin, Park Min; Oh, Na Ree; Park, Gun Wook; Kim, Hoguen; Yoo, Jong Shin

2012-09-18

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

PubMed Central

Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

2013-01-01

Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

Efficient Analysis of Mass Spectrometry Data Using the Isotope Wavelet

NASA Astrophysics Data System (ADS)

Hussong, Rene; Tholey, Andreas; Hildebrandt, Andreas

2007-09-01

Mass spectrometry (MS) has become today's de-facto standard for high-throughput analysis in proteomics research. Its applications range from toxicity analysis to MS-based diagnostics. Often, the time spent on the MS experiment itself is significantly less than the time necessary to interpret the measured signals, since the amount of data can easily exceed several gigabytes. In addition, automated analysis is hampered by baseline artifacts, chemical as well as electrical noise, and an irregular spacing of data points. Thus, filtering techniques originating from signal and image analysis are commonly employed to address these problems. Unfortunately, smoothing, base-line reduction, and in particular a resampling of data points can affect important characteristics of the experimental signal. To overcome these problems, we propose a new family of wavelet functions based on the isotope wavelet, which is hand-tailored for the analysis of mass spectrometry data. The resulting technique is theoretically well-founded and compares very well with standard peak picking tools, since it is highly robust against noise spoiling the data, but at the same time sufficiently sensitive to detect even low-abundant peptides.

High resolution mass spectrometric brain proteomics by MALDI-FTICR-MS combined with determination of P, S, Cu, Zn and Fe by LA-ICP-MS

NASA Astrophysics Data System (ADS)

Becker, J. Susanne; Zoriy, Miroslav; Przybylski, Michael; Becker, J. Sabine

2007-03-01

The combination of atomic and molecular mass spectrometric methods was applied for characterization and identification of several human proteins from Alzheimer's diseased brain. A brain protein mixture was separated by two-dimensional (2D) gel electrophoresis and the protein spots were fast screened by microlocal analysis using LA-ICP-MS (laser ablation inductively coupled plasma mass spectrometry) in respect to phosphorus, sulfur, copper, zinc and iron content. Five selected protein spots in 2D gel containing these elements were investigated after tryptic digestion by matrix assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS). Than element concentrations (P, Cu, Zn and Fe) were determined in three identified human brain proteins by LA-ICP-MS in the 2D gel. Results of structure analysis of human brain proteins by MALDI-FTICR-MS were combined with those of the direct determination of phosphorus, copper, zinc and iron concentrations in protein spots with LA-ICP-MS. From the results of atomic and molecular mass spectrometric techniques the human brain proteins were characterized in respect to their structure, sequence, phosphorylation state and metal content as well.

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

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

Serum protein profiling and proteomics in autistic spectrum disorder using magnetic bead-assisted mass spectrometry.

PubMed

Taurines, Regina; Dudley, Edward; Conner, Alexander C; Grassl, Julia; Jans, Thomas; Guderian, Frank; Mehler-Wex, Claudia; Warnke, Andreas; Gerlach, Manfred; Thome, Johannes

2010-04-01

The pathophysiology of autistic spectrum disorder (ASD) is not fully understood and there are no diagnostic or predictive biomarkers. Proteomic profiling has been used in the past for biomarker research in several non-psychiatric and psychiatric disorders and could provide new insights, potentially presenting a useful tool for generating such biomarkers in autism. Serum protein pre-fractionation with C8-magnetic beads and protein profiling by matrix-assisted laser desorption/ionisation-time of flight-mass spectrometry (MALDI-ToF-MS) were used to identify possible differences in protein profiles in patients and controls. Serum was obtained from 16 patients (aged 8-18) and age-matched controls. Three peaks in the MALDI-ToF-MS significantly differentiated the ASD sample from the control group. Sub-grouping the ASD patients into children with and without comorbid Attention Deficit and Hyperactivity Disorder, ADHD (ASD/ADHD+ patients, n = 9; ASD/ADHD- patients, n = 7), one peak distinguished the ASD/ADHD+ patients from controls and ASD/ADHD- patients. Our results suggest that altered protein levels in peripheral blood of patients with ASD might represent useful biomarkers for this devastating psychiatric disorder.

A HUPO test sample study reveals common problems in mass spectrometry-based proteomics

PubMed Central

Bell, Alexander W.; Deutsch, Eric W.; Au, Catherine E.; Kearney, Robert E.; Beavis, Ron; Sechi, Salvatore; Nilsson, Tommy; Bergeron, John J.M.

2009-01-01

We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics. PMID:19448641

Global proteome profiling of dental cementum under experimentally-induced apposition.

PubMed

Salmon, Cristiane R; Giorgetti, Ana Paula O; Paes Leme, Adriana Franco; Domingues, Romênia R; Sallum, Enilson Antonio; Alves, Marcelo C; Kolli, Tamara N; Foster, Brian L; Nociti, Francisco H

2016-06-01

Dental cementum (DC) covers the tooth root and has important functions in tooth attachment and position. DC can be lost to disease, and regeneration is currently unpredictable due to limited understanding of DC formation. This study used a model of experimentally-induced apposition (EIA) in mice to identify proteins associated with new DC formation. Mandibular first molars were induced to super-erupt for 6 and 21days after extracting opposing maxillary molars. Decalcified and formalin-fixed paraffin-embedded mandible sections were prepared for laser capture microdissection. Microdissected protein extracts were analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), and the data submitted to repeated measure ANOVA test (RM-ANOVA, alpha=5%). A total of 519 proteins were identified, with 97 (18.6%) proteins found exclusively in EIA sites and 50 (9.6%) proteins exclusively expressed in control sites. Fifty six (10.7%) proteins were differentially regulated by RM-ANOVA (p<0.05), with 24 regulated by the exclusive effect of EIA (12 proteins) or the interaction between EIA and time (12 proteins), including serpin 1a, procollagen C-endopeptidase enhancer, tenascin X (TNX), and asporin (ASPN). In conclusion, proteomic analysis demonstrated significantly altered protein profile in DC under EIA, providing new insights on DC biology and potential candidates for tissue engineering applications. Dental cementum (DC) is a mineralized tissue that covers the tooth root surface and has important functions in tooth attachment and position. DC and other periodontal tissues can be lost to disease, and regeneration is currently unpredictable due to lack of understanding of DC formation. This study used a model of experimentally-induced apposition (EIA) in mice to promote new cementum formation, followed by laser capture microdissection (LCM) and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) proteomic analysis. This approach identified proteins associated with new cementum formation that may be targets for promoting cementum regeneration. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Identification of Phosphorylated Proteins on a Global Scale.

PubMed

Iliuk, Anton

2018-05-31

Liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) has enabled researchers to analyze complex biological samples with unprecedented depth. It facilitates the identification and quantification of modifications within thousands of proteins in a single large-scale proteomic experiment. Analysis of phosphorylation, one of the most common and important post-translational modifications, has particularly benefited from such progress in the field. Here, detailed protocols are provided for a few well-regarded, common sample preparation methods for an effective phosphoproteomic experiment. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

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.

Current controlled vocabularies are insufficient to uniquely map molecular entities to mass spectrometry signal.

PubMed

Smith, Rob; Taylor, Ryan M; Prince, John T

2015-01-01

The comparison of analyte mass spectrometry precursor (MS1) signal is central to many proteomic (and other -omic) workflows. Standard vocabularies for mass spectrometry exist and provide good coverage for most experimental applications yet are insufficient for concise and unambiguous description of data concepts spanning the range of signal provenance from a molecular perspective (e.g. from charged peptides down to fine isotopes). Without a standard unambiguous nomenclature, literature searches, algorithm reproducibility and algorithm evaluation for MS-omics data processing are nearly impossible. We show how terms from current official ontologies are too vague or ambiguous to explicitly map molecular entities to MS signals and we illustrate the inconsistency and ambiguity of current colloquially used terms. We also propose a set of terms for MS1 signal that uniquely, succinctly and intuitively describe data concepts spanning the range of signal provenance from full molecule downs to fine isotopes. We suggest that additional community discussion of these terms should precede any further standardization efforts. We propose a novel nomenclature that spans the range of the required granularity to describe MS data processing from the perspective of the molecular provenance of the MS signal. The proposed nomenclature provides a chain of succinct and unique terms spanning the signal created by a charged molecule down through each of its constituent subsignals. We suggest that additional community discussion of these terms should precede any further standardization efforts.

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.

Analytical Utility of Mass Spectral Binning in Proteomic Experiments by SPectral Immonium Ion Detection (SPIID)*

PubMed Central

Kelstrup, Christian D.; Frese, Christian; Heck, Albert J. R.; Olsen, Jesper V.; Nielsen, Michael L.

2014-01-01

Unambiguous identification of tandem mass spectra is a cornerstone in mass-spectrometry-based proteomics. As the study of post-translational modifications (PTMs) by means of shotgun proteomics progresses in depth and coverage, the ability to correctly identify PTM-bearing peptides is essential, increasing the demand for advanced data interpretation. Several PTMs are known to generate unique fragment ions during tandem mass spectrometry, the so-called diagnostic ions, which unequivocally identify a given mass spectrum as related to a specific PTM. Although such ions offer tremendous analytical advantages, algorithms to decipher MS/MS spectra for the presence of diagnostic ions in an unbiased manner are currently lacking. Here, we present a systematic spectral-pattern-based approach for the discovery of diagnostic ions and new fragmentation mechanisms in shotgun proteomics datasets. The developed software tool is designed to analyze large sets of high-resolution peptide fragmentation spectra independent of the fragmentation method, instrument type, or protease employed. To benchmark the software tool, we analyzed large higher-energy collisional activation dissociation datasets of samples containing phosphorylation, ubiquitylation, SUMOylation, formylation, and lysine acetylation. Using the developed software tool, we were able to identify known diagnostic ions by comparing histograms of modified and unmodified peptide spectra. Because the investigated tandem mass spectra data were acquired with high mass accuracy, unambiguous interpretation and determination of the chemical composition for the majority of detected fragment ions was feasible. Collectively we present a freely available software tool that allows for comprehensive and automatic analysis of analogous product ions in tandem mass spectra and systematic mapping of fragmentation mechanisms related to common amino acids. PMID:24895383

Comparative proteomic study on Brassica hexaploid and its parents provides new insights into the effects of polyploidization.

PubMed

Shen, Yanyue; Zhang, Yu; Zou, Jun; Meng, Jinling; Wang, Jianbo

2015-01-01

Polyploidy has played an important role in promoting plant evolution through genomic merging and doubling. Although genomic and transcriptomic changes have been observed in polyploids, the effects of polyploidization on proteomic divergence are poorly understood. In this study, we reported quantitative analysis of proteomic changes in leaves of Brassica hexaploid and its parents using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with mass spectrometry. A total of 2044 reproducible proteins were quantified by at least two unique peptides. We detected 452 proteins differentially expressed between Brassica hexaploid and its parents, and 100 proteins were non-additively expressed in Brassica hexaploid, which suggested a trend of non-additive protein regulation following genomic merger and doubling. Functional categories of cellular component biogenesis, immune system process, and response to stimulus, were significantly enriched in non-additive proteins, probably providing a driving force for variation and adaptation in allopolyploids. In particular, majority of the total 452 differentially expressed proteins showed expression level dominance of one parental expression, and there was an expression level dominance bias toward the tetraploid progenitor. In addition, the percentage of differentially expressed proteins that matched previously reported differentially genes were relatively low. This study aimed to get new insights into the effects of polyploidization on proteomic divergence. Using iTRAQ LC-MS/MS technology, we identified 452 differentially expressed proteins between allopolyploid and its parents which involved in response to stimulus, multi-organism process, and immune system process, much more than previous studies using 2-DE coupled with mass spectrometry technology. Therefore, our manuscript represents the most comprehensive analysis of protein profiles in allopolyploid and its parents, which will lead to a better understanding of novelty and plasticity of the allopolyploid genomes. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative analysis of inflamed and non-inflamed colon biopsies reveals strong proteomic inflammation profile in patients with ulcerative colitis

PubMed Central

2012-01-01

Background Accurate diagnostic and monitoring tools for ulcerative colitis (UC) are missing. Our aim was to describe the proteomic profile of UC and search for markers associated with disease exacerbation. Therefore, we aimed to characterize specific proteins associated with inflamed colon mucosa from patients with acute UC using mass spectrometry-based proteomic analysis. Methods Biopsies were sampled from rectum, sigmoid colon and left colonic flexure from twenty patients with active proctosigmoiditis and from four healthy controls for proteomics and histology. Proteomic profiles of whole colonic biopsies were characterized using 2D-gel electrophoresis, and peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was applied for identification of differently expressed protein spots. Results A total of 597 spots were annotated by image analysis and 222 of these had a statistically different protein level between inflamed and non-inflamed tissue in the patient group. Principal component analysis clearly grouped non-inflamed samples separately from the inflamed samples indicating that the proteomic signature of colon mucosa with acute UC is strong. Totally, 43 individual protein spots were identified, including proteins involved in energy metabolism (triosephosphate isomerase, glycerol-3-phosphate-dehydrogenase, alpha enolase and L-lactate dehydrogenase B-chain) and in oxidative stress (superoxide dismutase, thioredoxins and selenium binding protein). Conclusions A distinct proteomic profile of inflamed tissue in UC patients was found. Specific proteins involved in energy metabolism and oxidative stress were identified as potential candidate markers for UC. PMID:22726388

Proteomics Analysis of Alfalfa Response to Heat Stress

PubMed Central

Li, Weimin; Wei, Zhenwu; Qiao, Zhihong; Wu, Zinian; Cheng, Lixiang; Wang, Yuyang

2013-01-01

The proteome responses to heat stress have not been well understood. In this study, alfalfa (Medicago sativa L. cv. Huaiyin) seedlings were exposed to 25°C (control) and 40°C (heat stress) in growth chambers, and leaves were collected at 24, 48 and 72 h after treatment, respectively. The morphological, physiological and proteomic processes were negatively affected under heat stress. Proteins were extracted and separated by two-dimensional polyacrylamide gel electrophoresis (2-DE), and differentially expressed protein spots were identified by mass spectrometry (MS). Totally, 81 differentially expressed proteins were identified successfully by MALDI-TOF/TOF. These proteins were categorized into nine classes: including metabolism, energy, protein synthesis, protein destination/storage, transporters, intracellular traffic, cell structure, signal transduction and disease/defence. Five proteins were further analyzed for mRNA levels. The results of the proteomics analyses provide a better understanding of the molecular basis of heat-stress responses in alfalfa. PMID:24324825

Multiplexed data independent acquisition (MSX-DIA) applied by high resolution mass spectrometry improves quantification quality for the analysis of histone peptides

PubMed Central

Sidoli, Simone; Fujiwara, Rina; Garcia, Benjamin A.

2016-01-01

We present the mass spectrometry (MS) based application of the innovative, although scarcely exploited, multiplexed data-independent acquisition (MSX-DIA) for the analysis of histone post-translational modifications (PTMs). Histones are golden standard for complexity in MS based proteomics, due to their large number of combinatorial modifications, leading to isobaric peptides after proteolytic digestion. DIA has thus gained popularity for the purpose as it allows for MS/MS-based quantification without upfront assay development. In this work, we evaluated the performance of traditional DIA versus MSX-DIA in terms of MS/MS spectra quality, instrument scan rate and quantification precision using histones from HeLa cells. We used an MS/MS isolation window of 10 and 6 m/z for DIA and MSX-DIA, respectively. Four MS/MS scans were multiplexed for MSX-DIA. Despite MSX-DIA was programmed to perform 2-fold more MS/MS events than traditional DIA, it acquired on average ~5% more full MS scans, indicating even faster scan rate. Results highlighted an overall decrease of background ion signals using MSX-DIA, and we illustrated specific examples where peptides of different precursor masses were co-fragmented by DIA but not MSX-DIA. Taken together, MSX-DIA proved thus to be a more favorable method for histone analysis in data independent mode. PMID:27193262

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.

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

PubMed Central

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-01-01

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

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

PubMed

Licier, Rígel; Miranda, Eric; Serrano, Horacio

2016-10-17

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

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

Shen, Yufeng; Tolić, Nikola; Piehowski, Paul D.

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

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.

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.

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.

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.

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.

An Interaction Landscape of Ubiquitin Signaling.

PubMed

Zhang, Xiaofei; Smits, Arne H; van Tilburg, Gabrielle B A; Jansen, Pascal W T C; Makowski, Matthew M; Ovaa, Huib; Vermeulen, Michiel

2017-03-02

Intracellular signaling via the covalent attachment of different ubiquitin linkages to protein substrates is fundamental to many cellular processes. Although linkage-selective ubiquitin interactors have been studied on a case-by-case basis, proteome-wide analyses have not been conducted yet. Here, we present ubiquitin interactor affinity enrichment-mass spectrometry (UbIA-MS), a quantitative interaction proteomics method that makes use of chemically synthesized diubiquitin to enrich and identify ubiquitin linkage interactors from crude cell lysates. UbIA-MS reveals linkage-selective diubiquitin interactions in multiple cell types. For example, we identify TAB2 and TAB3 as novel K6 diubiquitin interactors and characterize UCHL3 as a K27-linkage selective interactor that regulates K27 polyubiquitin chain formation in cells. Additionally, we show a class of monoubiquitin and K6 diubiquitin interactors whose binding is induced by DNA damage. We expect that our proteome-wide diubiquitin interaction landscape and established workflows will have broad applications in the ongoing efforts to decipher the complex language of ubiquitin signaling. Copyright © 2017 Elsevier Inc. All rights reserved.

Proteomic analysis of early phase of conidia germination in Aspergillus nidulans.

PubMed

Oh, Young Taek; Ahn, Chun-Seob; Kim, Jeong Geun; Ro, Hyeon-Su; Lee, Chang-Won; Kim, Jae Won

2010-03-01

In order to investigate proteins involved in early phase of conidia germination, proteomic analysis was performed using two-dimensional gel electrophoresis (2D-GE) in conjunction with MALDI-TOF mass spectrometry (MS). The expression levels of 241 proteins varied quantitatively with statistical significance (P<0.05) at the early phase of the germination stage. Out of these 57 were identified by MALDI-TOF MS. Through classification of physiological functions from Conserved Domain Database analysis, among the identified proteins, 21, 13, and 6 proteins were associated with energy metabolism, protein synthesis, and protein folding process, respectively. Interestingly, eight proteins, which are involved in detoxification of reactive oxygen species (ROS) including catalase A, thioredoxin reductase, and mitochondrial peroxiredoxin, were also identified. The expression levels of the genes were further confirmed using Northern blot and reverse transcriptase (RT)-PCR analyses. This study represents the first proteomic analysis of early phase of conidia germination and will contribute to a better understanding of the molecular events involved in conidia germination process. Copyright (c) 2009 Elsevier Inc. All rights reserved.

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.

Characterization and Quantification of Intact 26S Proteasome Proteins by Real-Time Measurement of Intrinsic Fluorescence Prior to Top-down Mass Spectrometry

PubMed Central

Russell, Jason D.; Scalf, Mark; Book, Adam J.; Ladror, Daniel T.; Vierstra, Richard D.; Smith, Lloyd M.; Coon, Joshua J.

2013-01-01

Quantification of gas-phase intact protein ions by mass spectrometry (MS) is impeded by highly-variable ionization, ion transmission, and ion detection efficiencies. Therefore, quantification of proteins using MS-associated techniques is almost exclusively done after proteolysis where peptides serve as proxies for estimating protein abundance. Advances in instrumentation, protein separations, and informatics have made large-scale sequencing of intact proteins using top-down proteomics accessible to the proteomics community; yet quantification of proteins using a top-down workflow has largely been unaddressed. Here we describe a label-free approach to determine the abundance of intact proteins separated by nanoflow liquid chromatography prior to MS analysis by using solution-phase measurements of ultraviolet light-induced intrinsic fluorescence (UV-IF). UV-IF is measured directly at the electrospray interface just prior to the capillary exit where proteins containing at least one tryptophan residue are readily detected. UV-IF quantification was demonstrated using commercially available protein standards and provided more accurate and precise protein quantification than MS ion current. We evaluated the parallel use of UV-IF and top-down tandem MS for quantification and identification of protein subunits and associated proteins from an affinity-purified 26S proteasome sample from Arabidopsis thaliana. We identified 26 unique proteins and quantified 13 tryptophan-containing species. Our analyses discovered previously unidentified N-terminal processing of the β6 (PBF1) and β7 (PBG1) subunit - such processing of PBG1 may generate a heretofore unknown additional protease active site upon cleavage. In addition, our approach permitted the unambiguous identification and quantification both isoforms of the proteasome-associated protein DSS1. PMID:23536786

Characterization and quantification of intact 26S proteasome proteins by real-time measurement of intrinsic fluorescence prior to top-down mass spectrometry.

PubMed

Russell, Jason D; Scalf, Mark; Book, Adam J; Ladror, Daniel T; Vierstra, Richard D; Smith, Lloyd M; Coon, Joshua J

2013-01-01

Quantification of gas-phase intact protein ions by mass spectrometry (MS) is impeded by highly-variable ionization, ion transmission, and ion detection efficiencies. Therefore, quantification of proteins using MS-associated techniques is almost exclusively done after proteolysis where peptides serve as proxies for estimating protein abundance. Advances in instrumentation, protein separations, and informatics have made large-scale sequencing of intact proteins using top-down proteomics accessible to the proteomics community; yet quantification of proteins using a top-down workflow has largely been unaddressed. Here we describe a label-free approach to determine the abundance of intact proteins separated by nanoflow liquid chromatography prior to MS analysis by using solution-phase measurements of ultraviolet light-induced intrinsic fluorescence (UV-IF). UV-IF is measured directly at the electrospray interface just prior to the capillary exit where proteins containing at least one tryptophan residue are readily detected. UV-IF quantification was demonstrated using commercially available protein standards and provided more accurate and precise protein quantification than MS ion current. We evaluated the parallel use of UV-IF and top-down tandem MS for quantification and identification of protein subunits and associated proteins from an affinity-purified 26S proteasome sample from Arabidopsis thaliana. We identified 26 unique proteins and quantified 13 tryptophan-containing species. Our analyses discovered previously unidentified N-terminal processing of the β6 (PBF1) and β7 (PBG1) subunit - such processing of PBG1 may generate a heretofore unknown additional protease active site upon cleavage. In addition, our approach permitted the unambiguous identification and quantification both isoforms of the proteasome-associated protein DSS1.

Comprehensive Analysis of Protein Modifications by Top-down Mass Spectrometry

PubMed Central

Zhang, Han; Ge, Ying

2012-01-01

Mass spectrometry (MS)-based proteomics is playing an increasingly important role in cardiovascular research. Proteomics includes not only identification and quantification of proteins, but also the characterization of protein modifications such as post-translational modifications and sequence variants. The conventional bottom-up approach, involving proteolytic digestion of proteins into small peptides prior to MS analysis, is routinely used for protein identification and quantification with high throughput and automation. Nevertheless, it has limitations in the analysis of protein modifications mainly due to the partial sequence coverage and loss of connections among modifications on disparate portions of a protein. An alternative approach, top-down MS, has emerged as a powerful tool for the analysis of protein modifications. The top-down approach analyzes whole proteins directly, providing a “bird’s eye” view of all existing modifications. Subsequently, each modified protein form can be isolated and fragmented in the mass spectrometer to locate the modification site. The incorporation of the non-ergodic dissociation methods such as electron capture dissociation (ECD) greatly enhances the top-down capabilities. ECD is especially useful for mapping labile post-translational modifications which are well-preserved during the ECD fragmentation process. Top-down MS with ECD has been successfully applied to cardiovascular research with the unique advantages in unraveling the molecular complexity, quantifying modified protein forms, complete mapping of modifications with full sequence coverage, discovering unexpected modifications, and identifying and quantifying positional isomers and determining the order of multiple modifications. Nevertheless, top-down MS still needs to overcome some technical challenges to realize its full potential. Herein, we reviewed the advantages and challenges of top-down methodology with a focus on its application in cardiovascular research. PMID:22187450

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

PubMed

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

2013-01-01

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

Comparative shotgun proteomic analysis of Clostridium acetobutylicum from butanol fermentation using glucose and xylose

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

Sivagnanam, Kumaran; Raghavan, Vijaya G. S.; Shah, Manesh B

2011-01-01

Background: Butanol is a second generation biofuel produced by Clostridium acetobutylicum through acetonebutanol- ethanol (ABE) fermentation process. Shotgun proteomics provides a direct approach to study the whole proteome of an organism in depth. This paper focuses on shotgun proteomic profiling of C. acetobutylicum from ABE fermentation using glucose and xylose to understand the functional mechanisms of C. acetobutylicum proteins involved in butanol production. Results: We identified 894 different proteins in C. acetobutylicum from ABE fermentation process by two dimensional - liquid chromatography - tandem mass spectrometry (2D-LC-MS/MS) method. This includes 717 proteins from glucose and 826 proteins from the xylosemore » substrate. A total of 649 proteins were found to be common and 22 significantly differentially expressed proteins were identified between glucose and xylose substrates. Conclusion: Our results demonstrate that flagellar proteins are highly up-regulated with glucose compared to xylose substrate during ABE fermentation. Chemotactic activity was also found to be lost with the xylose substrate due to the absence of CheW and CheV proteins. This is the first report on the shotgun proteomic analysis of C. acetobutylicum ATCC 824 in ABE fermentation between glucose and xylose substrate from a single time data point and the number of proteins identified here is more than any other study performed on this organism up to this report.« less

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.

Altered proteomic polymorphisms in the caterpillar body and stroma of natural Cordyceps sinensis during maturation.

PubMed

Dong, Yun-Zi; Zhang, Li-Juan; Wu, Zi-Mei; Gao, Ling; Yao, Yi-Sang; Tan, Ning-Zhi; Wu, Jian-Yong; Ni, Luqun; Zhu, Jia-Shi

2014-01-01

To examine the maturational changes in proteomic polymorphisms resulting from differential expression by multiple intrinsic fungi in the caterpillar body and stroma of natural Cordyceps sinensis (Cs), an integrated micro-ecosystem. The surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) biochip technique was used to profile the altered protein compositions in the caterpillar body and stroma of Cs during its maturation. The MS chromatograms were analyzed using density-weighted algorithms to examine the similarities and cluster relationships among the proteomic polymorphisms of the Cs compartments and the mycelial products Hirsutella sinensis (Hs) and Paecilomyces hepiali (Ph). SELDI-TOF MS chromatograms displayed dynamic proteomic polymorphism alterations among samples from the different Cs compartments during maturation. More than 1,900 protein bands were analyzed using density-weighted ZUNIX similarity equations and clustering methods, revealing integral polymorphism similarities of 57.4% between the premature and mature stromata and 42.8% between the premature and mature caterpillar bodies. The across-compartment similarity was low, ranging from 10.0% to 18.4%. Consequently, each Cs compartment (i.e., the stroma and caterpillar body) formed a clustering clade, and the 2 clades formed a Cs cluster. The polymorphic similarities ranged from 0.51% to 1.04% between Hs and the Cs compartments and were 2.8- to 4.8-fold higher (1.92%-4.34%) between Ph and the Cs compartments. The Hs and Ph mycelial samples formed isolated clades outside of the Cs cluster. Proteomic polymorphisms in the caterpillar body and stroma of Cs change dynamically during maturation. The proteomic polymorphisms in Hs and Ph differ from those in Cs, suggesting the presence of multiple Cs-associated fungi and multiple Ophiocordyceps sinensis genotypes with altered differential protein expression in the Cs compartments during maturation. In conjunction with prior mycological and molecular observations, the findings from this proteomic study support the integrated micro-ecosystem hypothesis for natural Cs.

Altered Proteomic Polymorphisms in the Caterpillar Body and Stroma of Natural Cordyceps sinensis during Maturation

PubMed Central

Wu, Zi-Mei; Gao, Ling; Yao, Yi-Sang; Tan, Ning-Zhi; Wu, Jian-Yong; Ni, Luqun; Zhu, Jia-Shi

2014-01-01

Objective To examine the maturational changes in proteomic polymorphisms resulting from differential expression by multiple intrinsic fungi in the caterpillar body and stroma of natural Cordyceps sinensis (Cs), an integrated micro-ecosystem. Methods The surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) biochip technique was used to profile the altered protein compositions in the caterpillar body and stroma of Cs during its maturation. The MS chromatograms were analyzed using density-weighted algorithms to examine the similarities and cluster relationships among the proteomic polymorphisms of the Cs compartments and the mycelial products Hirsutella sinensis (Hs) and Paecilomyces hepiali (Ph). Results: SELDI-TOF MS chromatograms displayed dynamic proteomic polymorphism alterations among samples from the different Cs compartments during maturation. More than 1,900 protein bands were analyzed using density-weighted ZUNIX similarity equations and clustering methods, revealing integral polymorphism similarities of 57.4% between the premature and mature stromata and 42.8% between the premature and mature caterpillar bodies. The across-compartment similarity was low, ranging from 10.0% to 18.4%. Consequently, each Cs compartment (i.e., the stroma and caterpillar body) formed a clustering clade, and the 2 clades formed a Cs cluster. The polymorphic similarities ranged from 0.51% to 1.04% between Hs and the Cs compartments and were 2.8- to 4.8-fold higher (1.92%–4.34%) between Ph and the Cs compartments. The Hs and Ph mycelial samples formed isolated clades outside of the Cs cluster. Conclusion Proteomic polymorphisms in the caterpillar body and stroma of Cs change dynamically during maturation. The proteomic polymorphisms in Hs and Ph differ from those in Cs, suggesting the presence of multiple Cs-associated fungi and multiple Ophiocordyceps sinensis genotypes with altered differential protein expression in the Cs compartments during maturation. In conjunction with prior mycological and molecular observations, the findings from this proteomic study support the integrated micro-ecosystem hypothesis for natural Cs. PMID:25310818

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

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.

Wavelet-Based Peak Detection and a New Charge Inference Procedure for MS/MS Implemented in ProteoWizard’s msConvert

PubMed Central

2015-01-01

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1–100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets. PMID:25411686

Wavelet-based peak detection and a new charge inference procedure for MS/MS implemented in ProteoWizard's msConvert.

PubMed

French, William R; Zimmerman, Lisa J; Schilling, Birgit; Gibson, Bradford W; Miller, Christine A; Townsend, R Reid; Sherrod, Stacy D; Goodwin, Cody R; McLean, John A; Tabb, David L

2015-02-06

We report the implementation of high-quality signal processing algorithms into ProteoWizard, an efficient, open-source software package designed for analyzing proteomics tandem mass spectrometry data. Specifically, a new wavelet-based peak-picker (CantWaiT) and a precursor charge determination algorithm (Turbocharger) have been implemented. These additions into ProteoWizard provide universal tools that are independent of vendor platform for tandem mass spectrometry analyses and have particular utility for intralaboratory studies requiring the advantages of different platforms convergent on a particular workflow or for interlaboratory investigations spanning multiple platforms. We compared results from these tools to those obtained using vendor and commercial software, finding that in all cases our algorithms resulted in a comparable number of identified peptides for simple and complex samples measured on Waters, Agilent, and AB SCIEX quadrupole time-of-flight and Thermo Q-Exactive mass spectrometers. The mass accuracy of matched precursor ions also compared favorably with vendor and commercial tools. Additionally, typical analysis runtimes (∼1-100 ms per MS/MS spectrum) were short enough to enable the practical use of these high-quality signal processing tools for large clinical and research data sets.

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.

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

The protein expression landscape of the Arabidopsis root

PubMed Central

Petricka, Jalean J.; Schauer, Monica A.; Megraw, Molly; Breakfield, Natalie W.; Thompson, J. Will; Georgiev, Stoyan; Soderblom, Erik J.; Ohler, Uwe; Moseley, Martin Arthur; Grossniklaus, Ueli; Benfey, Philip N.

2012-01-01

Because proteins are the major functional components of cells, knowledge of their cellular localization is crucial to gaining an understanding of the biology of multicellular organisms. We have generated a protein expression map of the Arabidopsis root providing the identity and cell type-specific localization of nearly 2,000 proteins. Grouping proteins into functional categories revealed unique cellular functions and identified cell type-specific biomarkers. Cellular colocalization provided support for numerous protein–protein interactions. With a binary comparison, we found that RNA and protein expression profiles are weakly correlated. We then performed peak integration at cell type-specific resolution and found an improved correlation with transcriptome data using continuous values. We performed GeLC-MS/MS (in-gel tryptic digestion followed by liquid chromatography-tandem mass spectrometry) proteomic experiments on mutants with ectopic and no root hairs, providing complementary proteomic data. Finally, among our root hair-specific proteins we identified two unique regulators of root hair development. PMID:22447775

Proteomic study of activated Taenia solium oncospheres

PubMed Central

Santivañez, S.; Hernández-González, A.; Chile, N.; Oleaga, A.; Arana, Y.; Palma, S.; Verastegui, M.; Gonzalez, A.E.; Gilman, R.; Garcia, H.H.; Siles-Lucas, M.

2010-01-01

Taenia solium cysticerci are a major cause of human seizures and epilepsy in the world. In the gastrointestinal tract of infected individuals, taeniid eggs release the oncospheres, which are then activated by intestinal stimuli, getting ready to penetrate the gut wall and reach distant locations where they transform in cysticerci. Information about oncospheral molecules is scarce, and elucidation of the oncosphere proteome could help understanding the host-parasite relationship during the first steps of infection. In this study, using liquid chromatography and tandem mass spectrometry (LC-MS/MS) analysis, we could identify a set of oncospheral proteins involved in adhesion, protein folding, detoxification and proteolysis, among others. In addition, we have characterized one of the identified molecules, the parasite 14-3-3, by immunoblot and immunolocalization. The identification of these oncospheral proteins represents the first step to elucidate their specific roles in the biology of the host-parasite relationship. PMID:20144663

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

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.

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

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

High-throughput sperm differential proteomics suggests that epigenetic alterations contribute to failed assisted reproduction.

PubMed

Azpiazu, Rubén; Amaral, Alexandra; Castillo, Judit; Estanyol, Josep Maria; Guimerà, Marta; Ballescà, Josep Lluís; Balasch, Juan; Oliva, Rafael

2014-06-01

Are there quantitative alterations in the proteome of normozoospermic sperm samples that are able to complete IVF but whose female partner does not achieve pregnancy? Normozoospermic sperm samples with different IVF outcomes (pregnancy versus no pregnancy) differed in the levels of at least 66 proteins. The analysis of the proteome of sperm samples with distinct fertilization capacity using low-throughput proteomic techniques resulted in the detection of a few differential proteins. Current high-throughput mass spectrometry approaches allow the identification and quantification of a substantially higher number of proteins. This was a case-control study including 31 men with normozoospermic sperm and their partners who underwent IVF with successful fertilization recruited between 2007 and 2008. Normozoospermic sperm samples from 15 men whose female partners did not achieve pregnancy after IVF (no pregnancy) and 16 men from couples that did achieve pregnancy after IVF (pregnancy) were included in this study. To perform the differential proteomic experiments, 10 no pregnancy samples and 10 pregnancy samples were separately pooled and subsequently used for tandem mass tags (TMT) protein labelling, sodium dodecyl sulphate-polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry (LC-MS/MS) identification and peak intensity relative protein quantification. Bioinformatic analyses were performed using UniProt Knowledgebase, DAVID and Reactome. Individual samples (n = 5 no pregnancy samples; n = 6 pregnancy samples) and aliquots from the above TMT pools were used for western blotting. By using TMT labelling and LC-MS/MS, we have detected 31 proteins present at lower abundance (ratio no pregnancy/pregnancy < 0.67) and 35 at higher abundance (ratio no pregnancy/pregnancy > 1.5) in the no pregnancy group. Bioinformatic analyses showed that the proteins with differing abundance are involved in chromatin assembly and lipoprotein metabolism (P values < 0.05). In addition, the differential abundance of one of the proteins (SRSF protein kinase 1) was further validated by western blotting using independent samples (P value < 0.01). For individual samples the amount of recovered sperm not used for IVF was low and in most of the cases insufficient for MS analysis, therefore pools of samples had to be used to this end. Alterations in the proteins involved in chromatin assembly and metabolism may result in epigenetic errors during spermatogenesis, leading to inaccurate sperm epigenetic signatures, which could ultimately prevent embryonic development. These sperm proteins may thus possibly have clinical relevance. This work was supported by the Spanish Ministry of Economy and Competitiveness (Ministerio de Economia y Competividad; FEDER BFU 2009-07118 and PI13/00699) and Fundación Salud 2000 SERONO13-015. There are no competing interests to declare.

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

N-linked glycoprotein analysis using dual-extraction ultrahigh-performance liquid chromatography and electrospray tandem mass spectrometry.

PubMed

Siu, S O; Lam, Maggie P Y; Lau, Edward; Yeung, William S B; Cox, David M; Chu, Ivan K

2010-01-01

Although reverse-phase liquid chromatography (RP-LC) is a common technique for peptide separation in shotgun proteomics and glycoproteomics, it often provides unsatisfactory results for the analysis of glycopeptides and glycans. This bias against glycopeptides makes it difficult to study glycoproteins. By coupling mass spectrometry (MS) with a combination of RP-LC and normal-phase (NP)-LC as an integrated front-end separation system, we demonstrate that effective identification and characterization of both peptides and glycopeptides mixtures, and their constituent glycan structures, can be achieved from a single sample injection event.

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.

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

PubMed

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

2015-11-01

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

Exploring the context of the lung proteome within the airway mucosa following allergen challenge.

PubMed

Fehniger, Thomas E; Sato-Folatre, José-Gabriel; Malmström, Johan; Berglund, Magnus; Lindberg, Claes; Brange, Charlotte; Lindberg, Henrik; Marko-Varga, György

2004-01-01

The lung proteome is a dynamic collection of specialized proteins related to pulmonary function. Many cells of different derivations, activation states, and levels of maturity contribute to the changing environment, which produces the lung proteome. Inflammatory cells reacting to environmental challenge, for example from allergens, produce and secrete proteins which have profound effects on both resident and nonresident cells located in airways, alveoli, and the vascular tree which provides blood cells to the parenchyma alveolar bed for gas exchange. In an experimental model of allergic airway inflammation, we have compared control and allergen challenged lung compartments to determine global protein expression patterns using 2D-gel electrophoresis and subsequent spot identification by MS/MS mass spectrometry. We have then specifically isolated the epithelial mucosal layer, which lines conducting airways, from control and allergen challenged lungs, using laser capture technology and performed proteome identification on these selected cell samples. A central component of our investigations has been to contextually relate the histological features of the dynamic pulmonary environment to the changes in protein expression observed following challenge. Our results provide new information of the complexity of the submucosa/epithelium interface and the mechanisms behind the transformation of airway epithelium from normal steady states to functionally activated states.

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

PubMed

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

2016-11-01

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

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

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

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

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

iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates*

PubMed Central

Shteynberg, David; Deutsch, Eric W.; Lam, Henry; Eng, Jimmy K.; Sun, Zhi; Tasman, Natalie; Mendoza, Luis; Moritz, Robert L.; Aebersold, Ruedi; Nesvizhskii, Alexey I.

2011-01-01

The combination of tandem mass spectrometry and sequence database searching is the method of choice for the identification of peptides and the mapping of proteomes. Over the last several years, the volume of data generated in proteomic studies has increased dramatically, which challenges the computational approaches previously developed for these data. Furthermore, a multitude of search engines have been developed that identify different, overlapping subsets of the sample peptides from a particular set of tandem mass spectrometry spectra. We present iProphet, the new addition to the widely used open-source suite of proteomic data analysis tools Trans-Proteomics Pipeline. Applied in tandem with PeptideProphet, it provides more accurate representation of the multilevel nature of shotgun proteomic data. iProphet combines the evidence from multiple identifications of the same peptide sequences across different spectra, experiments, precursor ion charge states, and modified states. It also allows accurate and effective integration of the results from multiple database search engines applied to the same data. The use of iProphet in the Trans-Proteomics Pipeline increases the number of correctly identified peptides at a constant false discovery rate as compared with both PeptideProphet and another state-of-the-art tool Percolator. As the main outcome, iProphet permits the calculation of accurate posterior probabilities and false discovery rate estimates at the level of sequence identical peptide identifications, which in turn leads to more accurate probability estimates at the protein level. Fully integrated with the Trans-Proteomics Pipeline, it supports all commonly used MS instruments, search engines, and computer platforms. The performance of iProphet is demonstrated on two publicly available data sets: data from a human whole cell lysate proteome profiling experiment representative of typical proteomic data sets, and from a set of Streptococcus pyogenes experiments more representative of organism-specific composite data sets. PMID:21876204

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 .

Functional phosphoproteomic mass spectrometry-based approaches

PubMed Central

2012-01-01

Mass Spectrometry (MS)-based phosphoproteomics tools are crucial for understanding the structure and dynamics of signaling networks. Approaches such as affinity purification followed by MS have also been used to elucidate relevant biological questions in health and disease. The study of proteomes and phosphoproteomes as linked systems, rather than research studies of individual proteins, are necessary to understand the functions of phosphorylated and un-phosphorylated proteins under spatial and temporal conditions. Phosphoproteome studies also facilitate drug target protein identification which may be clinically useful in the near future. Here, we provide an overview of general principles of signaling pathways versus phosphorylation. Likewise, we detail chemical phosphoproteomic tools, including pros and cons with examples where these methods have been applied. In addition, basic clues of electrospray ionization and collision induced dissociation fragmentation are detailed in a simple manner for successful phosphoproteomic clinical studies. PMID:23369623

Mass Spectrometric Detection of Botulinum Neurotoxin by Measuring its Activity in Serum and Milk

NASA Astrophysics Data System (ADS)

Kalb, Suzanne R.; Pirkle, James L.; Barr, John R.

Botulinum neurotoxins (BoNTs) are bacterial protein toxins which are considered likely agents for bioterrorism due to their extreme toxicity and high availability. A new mass spectrometry based assay called Endopep MS detects and defines the toxin serotype in clinical and food matrices via toxin activity upon a peptide substrate which mimics the toxin's natural target. Furthermore, the subtype of the toxin is differentiated by employing mass spectrometry based proteomic techniques on the same sample. The Endopep-MS assay selectively detects active BoNT and defines the serotype faster and with sensitivity greater than the mouse bioassay. One 96-well plate can be analyzed in under 7 h. On higher level or "hot" samples, the subtype can then be differentiated in less than 2 h with no need for DNA.

Quantification of proteins in urine samples using targeted mass spectrometry methods.

PubMed

Khristenko, Nina; Domon, Bruno

2015-01-01

Numerous clinical proteomics studies are focused on the development of biomarkers to improve either diagnostics for early disease detection or the monitoring of the response to the treatment. Although, a wealth of biomarker candidates are available, their evaluation and validation in a true clinical setup remains challenging. In biomarkers evaluation studies, a panel of proteins of interest are systematically analyzed in a large cohort of samples. However, in spite of the latest progresses in mass spectrometry, the consistent detection of pertinent proteins in high complex biological samples is still a challenging task. Thus, targeted LC-MS/MS methods are better suited for the systematic analysis of biomarkers rather than shotgun approaches. This chapter describes the workflow used to perform targeted quantitative analyses of proteins in urinary samples. The peptides, as surrogates of the protein of interest, are commonly measured using a triple quadrupole mass spectrometers operated in selected reaction monitoring (SRM) mode. More recently, the advances in targeted LC-MS/MS analysis based on parallel reaction monitoring (PRM) performed on a quadrupole-orbitrap instrument have allowed to increase the specificity and selectivity of the measurements.

Proteomic analysis of exosomes from human neural stem cells by flow field-flow fractionation and nanoflow liquid chromatography-tandem mass spectrometry.

PubMed

Kang, Dukjin; Oh, Sunok; Ahn, Sung-Min; Lee, Bong-Hee; Moon, Myeong Hee

2008-08-01

Exosomes, small membrane vesicles secreted by a multitude of cell types, are involved in a wide range of physiological roles such as intercellular communication, membrane exchange between cells, and degradation as an alternative to lysosomes. Because of the small size of exosomes (30-100 nm) and the limitations of common separation procedures including ultracentrifugation and flow cytometry, size-based fractionation of exosomes has been challenging. In this study, we used flow field-flow fractionation (FlFFF) to fractionate exosomes according to differences in hydrodynamic diameter. The exosome fractions collected from FlFFF runs were examined by transmission electron microscopy (TEM) to morphologically confirm their identification as exosomes. Exosomal lysates of each fraction were digested and analyzed using nanoflow LC-ESI-MS-MS for protein identification. FIFFF, coupled with mass spectrometry, allows nanoscale size-based fractionation of exosomes and is more applicable to primary cells and stem cells since it requires much less starting material than conventional gel-based separation, in-gel digestion and the MS-MS method.

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

PubMed Central

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

2013-01-01

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

IPeak: An open source tool to combine results from multiple MS/MS search engines.

PubMed

Wen, Bo; Du, Chaoqin; Li, Guilin; Ghali, Fawaz; Jones, Andrew R; Käll, Lukas; Xu, Shaohang; Zhou, Ruo; Ren, Zhe; Feng, Qiang; Xu, Xun; Wang, Jun

2015-09-01

Liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post-processing algorithm and multi-search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command-line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml-lib/. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Current controlled vocabularies are insufficient to uniquely map molecular entities to mass spectrometry signal

PubMed Central

2015-01-01

Background The comparison of analyte mass spectrometry precursor (MS1) signal is central to many proteomic (and other -omic) workflows. Standard vocabularies for mass spectrometry exist and provide good coverage for most experimental applications yet are insufficient for concise and unambiguous description of data concepts spanning the range of signal provenance from a molecular perspective (e.g. from charged peptides down to fine isotopes). Without a standard unambiguous nomenclature, literature searches, algorithm reproducibility and algorithm evaluation for MS-omics data processing are nearly impossible. Results We show how terms from current official ontologies are too vague or ambiguous to explicitly map molecular entities to MS signals and we illustrate the inconsistency and ambiguity of current colloquially used terms. We also propose a set of terms for MS1 signal that uniquely, succinctly and intuitively describe data concepts spanning the range of signal provenance from full molecule downs to fine isotopes. We suggest that additional community discussion of these terms should precede any further standardization efforts. We propose a novel nomenclature that spans the range of the required granularity to describe MS data processing from the perspective of the molecular provenance of the MS signal. Conclusions The proposed nomenclature provides a chain of succinct and unique terms spanning the signal created by a charged molecule down through each of its constituent subsignals. We suggest that additional community discussion of these terms should precede any further standardization efforts. PMID:25952148

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.

Enhanced photosynthesis and redox energy production contribute to salinity tolerance in Dunaliella as revealed by homology-based proteomics.

PubMed

Liska, Adam J; Shevchenko, Andrej; Pick, Uri; Katz, Adriana

2004-09-01

Salinity is a major limiting factor for the proliferation of plants and inhibits central metabolic activities such as photosynthesis. The halotolerant green alga Dunaliella can adapt to hypersaline environments and is considered a model photosynthetic organism for salinity tolerance. To clarify the molecular basis for salinity tolerance, a proteomic approach has been applied for identification of salt-induced proteins in Dunaliella. Seventy-six salt-induced proteins were selected from two-dimensional gel separations of different subcellular fractions and analyzed by mass spectrometry (MS). Application of nanoelectrospray mass spectrometry, combined with sequence-similarity database-searching algorithms, MS BLAST and MultiTag, enabled identification of 80% of the salt-induced proteins. Salinity stress up-regulated key enzymes in the Calvin cycle, starch mobilization, and redox energy production; regulatory factors in protein biosynthesis and degradation; and a homolog of a bacterial Na(+)-redox transporters. The results indicate that Dunaliella responds to high salinity by enhancement of photosynthetic CO(2) assimilation and by diversion of carbon and energy resources for synthesis of glycerol, the osmotic element in Dunaliella. The ability of Dunaliella to enhance photosynthetic activity at high salinity is remarkable because, in most plants and cyanobacteria, salt stress inhibits photosynthesis. The results demonstrated the power of MS BLAST searches for the identification of proteins in organisms whose genomes are not known and paved the way for dissecting molecular mechanisms of salinity tolerance in algae and higher plants.

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.

The secreted salivary proteome of the pea aphid Acyrthosiphon pisum characterised by mass spectrometry.

PubMed

Carolan, James C; Fitzroy, Carol I J; Ashton, Peter D; Douglas, Angela E; Wilkinson, Thomas L

2009-05-01

Nine proteins secreted in the saliva of the pea aphid Acyrthosiphon pisum were identified by a proteomics approach using GE-LC-MS/MS and LC-MS/MS, with reference to EST and genomic sequence data for A. pisum. Four proteins were identified by their sequences: a homolog of angiotensin-converting enzyme (an M2 metalloprotease), an M1 zinc-dependant metalloprotease, a glucose-methanol-choline (GMC)-oxidoreductase and a homolog to regucalcin (also known as senescence marker protein 30). The other five proteins are not homologous to any previously described sequence and included an abundant salivary protein (represented by ACYPI009881), with a predicted length of 1161 amino acids and high serine, tyrosine and cysteine content. A. pisum feeds on plant phloem sap and the metalloproteases and regucalcin (a putative calcium-binding protein) are predicted determinants of sustained feeding, by inactivation of plant protein defences and inhibition of calcium-mediated occlusion of phloem sieve elements, respectively. The amino acid composition of ACYPI009881 suggests a role in the aphid salivary sheath that protects the aphid mouthparts from plant defences, and the oxidoreductase may promote gelling of the sheath protein or mediate oxidative detoxification of plant allelochemicals. Further salivary proteins are expected to be identified as more sensitive MS technologies are developed.

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.

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.

[Proteome analysis on interaction between Anoectochilus roxburghii and Mycorrhizal fungus].

PubMed

Gao, Chuan; Guo, Shun-Xing; Zhang, Jing; Chen, Juan; Zhang, Li-Chun

2012-12-01

To study the mechanism of plant growing promoted by Mycorrhizal fungus through the difference of proteomes. The differential proteomes between uninoculated and inoculated endophytic fungi, Epulorhiza sp. on Anoectochilus roxburghii were analyzed by two-dimensional gel electrophoresis and MALDI-TOF/TOF mass spectrum. Twenty-seven protein spots were analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Twenty-two candidate proteins were identified by database comparisons. The function of these proteins mostly involved in signal transduction, metabolic regulation, as well as photosynthesis and substance metabolism. The results indicate that the regulator control system of plant is influenced by fungi action, and the positive regulation improves substance metabolism and photosynthesis, which results in strong plant and higher resistance. It is also deduced that silent genes may exist in endosymbiosis plants.

Infrared Mass Spectrometry for Environmental and Biomedical Applications

NASA Astrophysics Data System (ADS)

Baltz-Knorr, M. L.; Papantonakis, M. R.; Ermer Haglund, D. R., Jr.

2000-11-01

Matrix-assisted laser desorption and ionization (MALDI) mass spectrometry (MS) using a tunable, ultrashort pulse, mid-infrared free electron laser (FEL) has many applications for both environmental and biomedical research. Environmentally, the characterization of stored nuclear materials has been an important area of research. We are developing a method to determine nuclear tank waste constituents using MALDI MS. This includes desorption and ionization of small organic molecules from sodium nitrate solids and slurries (similar to the salt cake found in some tanks) and also from traditional MALDI matrices. Important aspects of the technique are that it does not produce a secondary waste stream and it is potentially field-deployable using solid-state lasers. Biomedically, the ability to do proteomics is being enhanced by the sensitivity and mass accuracy provided by MALDI MS. We are using MALDI MS to identify proteins embedded in liquid matrix materials, which provide a more natural environment for the biomolecules. We are also working on coupling MALDI MS to traditional protein identification and sequencing techniques for rapid analysis of large numbers of proteins. Research supported by the Office of Naval Research and the U.S. Department of Energy

Mass Spectrometry Data Collection in Parallel at Multiple Core Facilities Operating TripleTOF 5600 and Orbitrap Elite/Velos Pro/Q Exactive Mass Spectrometers

PubMed Central

Jones, K.; Kim, K.; Patel, B.; Kelsen, S.; Braverman, A.; Swinton, D.; Gafken, P.; Jones, L.; Lane, W.; Neveu, J.; Leung, H.; Shaffer, S.; Leszyk, J.; Stanley, B.; Fox, T.; Stanley, A.; Yeung, Anthony

2013-01-01

Proteomic research can benefit from simultaneous access to multiple cutting-edge mass spectrometers. 18 core facilities responded to our investigators seeking service through the ABRF Discussion Forum. Five of the facilities selected completed four plasma proteomics experiments as routine fee-for-service. Each biological experiment entailed an iTRAQ 4-plex proteome comparison of immunodepleted plasma provided as 30 labeled-peptide fractions. Identical samples were analyzed by two AB SCIEX TripleTOF 5600 and three Thermo Orbitrap (Elite/Velos Pro/Q Exactive) instruments. 480 LC-MS/MS runs delivered >250 GB of data over two months. We compare herein routine service analyses of three peptide fractions of different peptide abundance. Data files from each instrument were studied to develop optimal analysis parameters to compare with default parameters in Mascot Distiller 2.4, ProteinPilot 4.5 beta, AB Sciex MS Data Converter 1.3 beta, and Proteome Discover 1.3. Peak-picking for TripleTOFs was best by ProteinPilot 4.5 beta while Mascot Distiller and Proteome Discoverer were comparable for the Orbitraps. We compared protein identification and quantitation in SwissProt 2012_07 database by Mascot Server 2.4.01 versus ProteinPilot. By all search methods, more proteins, up to two fold, were identified using the Q Exactive than others. Q Exactive excelled also at the number of unique significant peptide ion sequences. However, software-dependent impact on subsequent interpretation, due to peptide modifications, can be critical. These findings may have special implications for iTRAQ plasma proteomics. For the low abundance peptide ions, the slope of the dynamic range drop-off in the plasma proteome is uniquely sharp compared with cell lysates. Our study provides data for testable improvements in the operation of these mass spectrometers. More importantly, we have demonstrated a new affordable expedient workflow for investigators to perform proteomic experiments through the ABRF infrastructure. (We acknowledge John Cottrell for optimizing the peak-picking parameters for Mascot Distiller).

Shiga toxin 2 subtypes of enterohemorrhagic E. coli O157:H- E32511 analyzed by RT-qPCR and top-down proteomics using MALDI-TOF-TOF-MS

USDA-ARS?s Scientific Manuscript database

We have measured the relative abundance of the B-subunits and mRNA transcripts of two Stx2 subtypes present in Shiga toxin-producing Escherichia coli (STEC) O157:H- strain E32511 using matrix-assisted laser desorption/ionization time-of-flight-time-of-flight tandem mass spectrometry (MALDI-TOF-TOF-M...

Mass spectrometry-based proteomics for translational research: a technical overview.

PubMed

Paulo, Joao A; Kadiyala, Vivek; Banks, Peter A; Steen, Hanno; Conwell, Darwin L

2012-03-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.

Mass Spectrometry-Based Proteomics for Translational Research: A Technical Overview

PubMed Central

Paulo, Joao A.; Kadiyala, Vivek; Banks, Peter A.; Steen, Hanno; Conwell, Darwin L.

2012-01-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease. PMID:22461744

Preserved Proteins from Extinct Bison latifrons Identified by Tandem Mass Spectrometry; Hydroxylysine Glycosides are a Common Feature of Ancient Collagen*

PubMed Central

Hill, Ryan C.; Wither, Matthew J.; Nemkov, Travis; Barrett, Alexander; D'Alessandro, Angelo; Dzieciatkowska, Monika; Hansen, Kirk C.

2015-01-01

Bone samples from several vertebrates were collected from the Ziegler Reservoir fossil site, in Snowmass Village, Colorado, and processed for proteomics analysis. The specimens come from Pleistocene megafauna Bison latifrons, dating back ∼120,000 years. Proteomics analysis using a simplified sample preparation procedure and tandem mass spectrometry (MS/MS) was applied to obtain protein identifications. Several bioinformatics resources were used to obtain peptide identifications based on sequence homology to extant species with annotated genomes. With the exception of soil sample controls, all samples resulted in confident peptide identifications that mapped to type I collagen. In addition, we analyzed a specimen from the extinct B. latifrons that yielded peptide identifications mapping to over 33 bovine proteins. Our analysis resulted in extensive fibrillar collagen sequence coverage, including the identification of posttranslational modifications. Hydroxylysine glucosylgalactosylation, a modification thought to be involved in collagen fiber formation and bone mineralization, was identified for the first time in an ancient protein dataset. Meta-analysis of data from other studies indicates that this modification may be common in well-preserved prehistoric samples. Additional peptide sequences from extracellular matrix (ECM) and non-ECM proteins have also been identified for the first time in ancient tissue samples. These data provide a framework for analyzing ancient protein signatures in well-preserved fossil specimens, while also contributing novel insights into the molecular basis of organic matter preservation. As such, this analysis has unearthed common posttranslational modifications of collagen that may assist in its preservation over time. The data are available via ProteomeXchange with identifier PXD001827. PMID:25948757

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

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/.

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis*

PubMed Central

Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics. PMID:22261725

MS-REDUCE: an ultrafast technique for reduction of big mass spectrometry data for high-throughput processing.

PubMed

Awan, Muaaz Gul; Saeed, Fahad

2016-05-15

Modern proteomics studies utilize high-throughput mass spectrometers which can produce data at an astonishing rate. These big mass spectrometry (MS) datasets can easily reach peta-scale level creating storage and analytic problems for large-scale systems biology studies. Each spectrum consists of thousands of peaks which have to be processed to deduce the peptide. However, only a small percentage of peaks in a spectrum are useful for peptide deduction as most of the peaks are either noise or not useful for a given spectrum. This redundant processing of non-useful peaks is a bottleneck for streaming high-throughput processing of big MS data. One way to reduce the amount of computation required in a high-throughput environment is to eliminate non-useful peaks. Existing noise removing algorithms are limited in their data-reduction capability and are compute intensive making them unsuitable for big data and high-throughput environments. In this paper we introduce a novel low-complexity technique based on classification, quantization and sampling of MS peaks. We present a novel data-reductive strategy for analysis of Big MS data. Our algorithm, called MS-REDUCE, is capable of eliminating noisy peaks as well as peaks that do not contribute to peptide deduction before any peptide deduction is attempted. Our experiments have shown up to 100× speed up over existing state of the art noise elimination algorithms while maintaining comparable high quality matches. Using our approach we were able to process a million spectra in just under an hour on a moderate server. The developed tool and strategy has been made available to wider proteomics and parallel computing community and the code can be found at https://github.com/pcdslab/MSREDUCE CONTACT: : fahad.saeed@wmich.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

The impact of different ale brewer's yeast strains on the proteome of immature beer.

PubMed

Berner, Torben Sune; Jacobsen, Susanne; Arneborg, Nils

2013-09-30

It is well known that brewer's yeast affects the taste and aroma of beer. However, the influence of brewer's yeast on the protein composition of beer is currently unknown. In this study, changes of the proteome of immature beer, i.e. beer that has not been matured after fermentation, by ale brewer's yeast strains with different abilities to degrade fermentable sugars were investigated. Beers were fermented from standard hopped wort (13° Plato) using two ale brewer's yeast (Saccharomyces cerevisiae) strains with different attenuation degrees. Both immature beers had the same alcohol and protein concentrations. Immature beer and unfermented wort proteins were analysed by 2-DE and compared in order to determine protein changes arising from fermentation. Distinct protein spots in the beer and wort proteomes were identified using Matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and MS/MS and revealed common beer proteins, such as lipid transfer proteins (LTP1 and LTP2), protein Z and amylase-protease inhibitors. During fermentation, two protein spots, corresponding to LTP2, disappeared, while three protein spots were exclusively found in beer. These three proteins, all derived from yeast, were identified as cell wall associated proteins, that is Exg1 (an exo-β-1,3-glucanase), Bgl2 (an endo-β-1,2-glucanase), and Uth1 (a cell wall biogenesis protein). Yeast strain dependent changes in the immature beer proteome were identified, i.e. Bgl2 was present in beer brewed with KVL011, while lacking in WLP001 beer.

The impact of different ale brewer’s yeast strains on the proteome of immature beer

PubMed Central

2013-01-01

Background It is well known that brewer’s yeast affects the taste and aroma of beer. However, the influence of brewer’s yeast on the protein composition of beer is currently unknown. In this study, changes of the proteome of immature beer, i.e. beer that has not been matured after fermentation, by ale brewer’s yeast strains with different abilities to degrade fermentable sugars were investigated. Results Beers were fermented from standard hopped wort (13° Plato) using two ale brewer’s yeast (Saccharomyces cerevisiae) strains with different attenuation degrees. Both immature beers had the same alcohol and protein concentrations. Immature beer and unfermented wort proteins were analysed by 2-DE and compared in order to determine protein changes arising from fermentation. Distinct protein spots in the beer and wort proteomes were identified using Matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and MS/MS and revealed common beer proteins, such as lipid transfer proteins (LTP1 and LTP2), protein Z and amylase-protease inhibitors. During fermentation, two protein spots, corresponding to LTP2, disappeared, while three protein spots were exclusively found in beer. These three proteins, all derived from yeast, were identified as cell wall associated proteins, that is Exg1 (an exo-β-1,3-glucanase), Bgl2 (an endo-β-1,2-glucanase), and Uth1 (a cell wall biogenesis protein). Conclusion Yeast strain dependent changes in the immature beer proteome were identified, i.e. Bgl2 was present in beer brewed with KVL011, while lacking in WLP001 beer. PMID:24079909

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

Proteomics of exhaled breath: methodological nuances and pitfalls.

PubMed

Kurova, Viktoria S; Anaev, Eldar C; Kononikhin, Alexey S; Fedorchenko, Kristina Yu; Popov, Igor A; Kalupov, Timothey L; Bratanov, Dmitriy O; Nikolaev, Eugenie N; Varfolomeev, Sergey D

2009-01-01

The analysis of exhaled breath condensate (EBC) can be an alternative to traditional endoscopic sampling of lower respiratory tract secretions. This is a simple non-invasive method of diagnosing respiratory diseases, in particular, respiratory inflammatory processes. Samples were collected with a special device-condenser (ECoScreen, VIASYS Healthcare, Germany), then treated with trypsin according to the proteomics protocol for standard protein mixtures and analyzed by nanoflow high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) with a 7-Tesla Finnigan LTQ-FT mass spectrometer (Thermo Electron, Germany). Mascot software (Matrixscience) was used for screening the database NCBInr for proteins corresponding to the peptide maps that were obtained. EBCs from 17 young healthy non-smoking donors were collected. Different methods for concentrating protein were compared in order to optimize EBC preparations for proteomic analysis. The procedure that was chosen allowed identification of proteins exhaled by healthy people. The major proteins in the condensates were cytoskeletal keratins. Another 12 proteins were identified in EBC from healthy non-smokers. Some keratins were found in the ambient air and may be considered exogenous components of exhaled air. Knowledge of the normal proteome of exhaled breath allows one to look for biomarkers of different disease states in EBC. Proteins in ambient air can be identified in the respiratory tract and should be excluded from the analysis of the proteome of EBC. The results obtained allowed us to choose the most effective procedure of sample preparation when working with samples containing very low protein concentrations.

Activation of Human Peripheral Blood Eosinophils by Cytokines in a Comparative Time-Course Proteomic/Phosphoproteomic Study.

PubMed

Soman, Kizhake V; Stafford, Susan J; Pazdrak, Konrad; Wu, Zheng; Luo, Xuemei; White, Wendy I; Wiktorowicz, John E; Calhoun, William J; Kurosky, Alexander

2017-08-04

Activated eosinophils contribute to airway dysfunction and tissue remodeling in asthma and thus are considered to be important factors in asthma pathology. We report here comparative proteomic and phosphoproteomic changes upon activation of eosinophils using eight cytokines individually and in selected cytokine combinations in time-course reactions. Differential protein and phosphoprotein expressions were determined by mass spectrometry after 2-dimensional gel electrophoresis (2DGE) and by LC-MS/MS. We found that each cytokine-stimulation produced significantly different changes in the eosinophil proteome and phosphoproteome, with phosphoproteomic changes being more pronounced and having an earlier onset. Furthermore, we observed that IL-5, GM-CSF, and IL-3 showed the greatest change in protein expression and phosphorylation, and this expression differed markedly from those of the other five cytokines evaluated. Comprehensive univariate and multivariate statistical analyses were employed to evaluate the comparative results. We also monitored eosinophil activation using flow cytometry (FC) analysis of CD69. In agreement with our proteomic studies, FC indicated that IL-5, GM-CSF, and IL-3 were more effective than the other five cytokines studied in stimulating a cell surface CD69 increase indicative of eosinophil activation. Moreover, selected combinations of cytokines revealed proteomic patterns with many proteins in common with single cytokine expression patterns but also showed a greater effect of the two cytokines employed, indicating a more complex signaling pathway that was reflective of a more typical inflammatory pathology.

Shotgun proteomics approach to characterizing the embryonic proteome of the silkworm, Bombyx mori, at labrum appearance stage.

PubMed

Li, J-Y; Chen, X; Hosseini Moghaddam, S H; Chen, M; Wei, H; Zhong, B-X

2009-10-01

The shotgun approach has gained considerable acknowledgement in recent years as a dominant strategy in proteomics. We observed a dramatic increase of specific protein spots in two-dimensional electrophoresis (2-DE) gels of the silkworm (Bombyx mori) embryo at labrum appearance, a characteristic stage during embryonic development of silkworm which is involved with temperature increase by silkworm raiser. We employed shotgun liquid chromatography tandem mass spectrometry (LC-MS/MS) technology to analyse the proteome of B. mori embryos at this stage. A total of 2168 proteins were identified with an in-house database. Approximately 47% of them had isoelectric point (pI) values distributed theoretically in the range pI 5-7 and approximately 60% of them had molecular weights of 15-45 kDa. Furthermore, 111 proteins had an pI greater than 10 and were difficult to separate by 2-DE. Many important functional proteins related to embryonic development, stress response, DNA transcription/translation, cell growth, proliferation and differentiation, organogenesis and reproduction were identified. Among them proteins related to nervous system development were noticeable. All known heat shock proteins (HSPs) were detected in this developmental stage of B. mori embryo. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed energetic metabolism at this stage. These results were expected to provide more information for proteomic monitoring of the insect embryo and better understanding of the spatiotemporal expression of genes during embryonic developmental processes.

Proteomics study of extracellular fibrinolytic proteases from Bacillus licheniformis RO3 and Bacillus pumilus 2.g isolated from Indonesian fermented food

NASA Astrophysics Data System (ADS)

Nur Afifah, Diana; Rustanti, Ninik; Anjani, Gemala; Syah, Dahrul; Yanti; Suhartono, Maggy T.

2017-02-01

This paper presents the proteomics study which includes separation, identification and characterization of proteins. The experiment on Indonesian fermented food such as extracellular fibrinolytic protease from Bacillus licheniformis RO3 and Bacillus pumilus 2.g isolated from red oncom and tempeh gembus was conducted. The experimental works comprise the following steps: (1) a combination of one- and two-dimensional electrophoresis analysis, (2) mass spectrometry analysis using MALDI-TOF-MS and (3) investigation using protein database. The result suggested that there were new two protein fractions of B. licheniformis RO3 and three protein fractions of B. pumilus 2.g. These result has not been previously reported.

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.

Compartment-resolved Proteomic Analysis of Mouse Aorta during Atherosclerotic Plaque Formation Reveals Osteoclast-specific Protein Expression.

PubMed

Wierer, Michael; Prestel, Matthias; Schiller, Herbert B; Yan, Guangyao; Schaab, Christoph; Azghandi, Sepiede; Werner, Julia; Kessler, Thorsten; Malik, Rainer; Murgia, Marta; Aherrahrou, Zouhair; Schunkert, Heribert; Dichgans, Martin; Mann, Matthias

2018-02-01

Atherosclerosis leads to vascular lesions that involve major rearrangements of the vascular proteome, especially of the extracellular matrix (ECM). Using single aortas from ApoE knock out mice, we quantified formation of plaques by single-run, high-resolution mass spectrometry (MS)-based proteomics. To probe localization on a proteome-wide scale we employed quantitative detergent solubility profiling. This compartment- and time-resolved resource of atherogenesis comprised 5117 proteins, 182 of which changed their expression status in response to vessel maturation and atherosclerotic plaque development. In the insoluble ECM proteome, 65 proteins significantly changed, including relevant collagens, matrix metalloproteinases and macrophage derived proteins. Among novel factors in atherosclerosis, we identified matrilin-2, the collagen IV crosslinking enzyme peroxidasin as well as the poorly characterized MAM-domain containing 2 (Mamdc2) protein as being up-regulated in the ECM during atherogenesis. Intriguingly, three subunits of the osteoclast specific V-ATPase complex were strongly increased in mature plaques with an enrichment in macrophages thus implying an active de-mineralization function. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Compartment-resolved Proteomic Analysis of Mouse Aorta during Atherosclerotic Plaque Formation Reveals Osteoclast-specific Protein Expression*

PubMed Central

Wierer, Michael; Prestel, Matthias; Schiller, Herbert B.; Yan, Guangyao; Schaab, Christoph; Azghandi, Sepiede; Werner, Julia; Kessler, Thorsten; Malik, Rainer; Murgia, Marta; Aherrahrou, Zouhair; Schunkert, Heribert; Dichgans, Martin; Mann, Matthias

2018-01-01

Atherosclerosis leads to vascular lesions that involve major rearrangements of the vascular proteome, especially of the extracellular matrix (ECM). Using single aortas from ApoE knock out mice, we quantified formation of plaques by single-run, high-resolution mass spectrometry (MS)-based proteomics. To probe localization on a proteome-wide scale we employed quantitative detergent solubility profiling. This compartment- and time-resolved resource of atherogenesis comprised 5117 proteins, 182 of which changed their expression status in response to vessel maturation and atherosclerotic plaque development. In the insoluble ECM proteome, 65 proteins significantly changed, including relevant collagens, matrix metalloproteinases and macrophage derived proteins. Among novel factors in atherosclerosis, we identified matrilin-2, the collagen IV crosslinking enzyme peroxidasin as well as the poorly characterized MAM-domain containing 2 (Mamdc2) protein as being up-regulated in the ECM during atherogenesis. Intriguingly, three subunits of the osteoclast specific V-ATPase complex were strongly increased in mature plaques with an enrichment in macrophages thus implying an active de-mineralization function. PMID:29208753

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

PubMed

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

2013-10-04

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

Quantitative proteomic analysis of Pseudomonas pseudoalcaligenes CECT5344 in response to industrial cyanide-containing wastewaters using Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS)

PubMed Central

Ibáñez, María Isabel; Cabello, Purificación; Luque-Almagro, Víctor Manuel; Sáez, Lara P.; Olaya, Alfonso; Sánchez de Medina, Verónica; Luque de Castro, María Dolores; Moreno-Vivián, Conrado; Roldán, María Dolores

2017-01-01

Biological treatments to degrade cyanide are a powerful technology for cyanide removal from industrial wastewaters. It has been previously demonstrated that the alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 is able to use free cyanide and several metal−cyanide complexes as the sole nitrogen source. In this work, the strain CECT5344 has been used for detoxification of the different chemical forms of cyanide that are present in alkaline wastewaters from the jewelry industry. This liquid residue also contains large concentrations of metals like iron, copper and zinc, making this wastewater even more toxic. To elucidate the molecular mechanisms involved in the bioremediation process, a quantitative proteomic analysis by LC-MS/MS has been carried out in P. pseudoalcaligenes CECT5344 cells grown with the jewelry residue as sole nitrogen source. Different proteins related to cyanide and cyanate assimilation, as well as other proteins involved in transport and resistance to metals were induced by the cyanide-containing jewelry residue. GntR-like regulatory proteins were also induced by this industrial residue and mutational analysis revealed that GntR-like regulatory proteins may play a role in the regulation of cyanide assimilation in P. pseudoalcaligenes CECT5344. The strain CECT5344 has been used in a batch reactor to remove at pH 9 the different forms of cyanide present in industrial wastewaters from the jewelry industry (0.3 g/L, ca. 12 mM total cyanide, including both free cyanide and metal−cyanide complexes). This is the first report describing the biological removal at alkaline pH of such as elevated concentration of cyanide present in a heterogeneous mixture from an industrial source. PMID:28253357

Quantitative proteomic analysis of Pseudomonas pseudoalcaligenes CECT5344 in response to industrial cyanide-containing wastewaters using Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS).

PubMed

Ibáñez, María Isabel; Cabello, Purificación; Luque-Almagro, Víctor Manuel; Sáez, Lara P; Olaya, Alfonso; Sánchez de Medina, Verónica; Luque de Castro, María Dolores; Moreno-Vivián, Conrado; Roldán, María Dolores

2017-01-01

Biological treatments to degrade cyanide are a powerful technology for cyanide removal from industrial wastewaters. It has been previously demonstrated that the alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 is able to use free cyanide and several metal-cyanide complexes as the sole nitrogen source. In this work, the strain CECT5344 has been used for detoxification of the different chemical forms of cyanide that are present in alkaline wastewaters from the jewelry industry. This liquid residue also contains large concentrations of metals like iron, copper and zinc, making this wastewater even more toxic. To elucidate the molecular mechanisms involved in the bioremediation process, a quantitative proteomic analysis by LC-MS/MS has been carried out in P. pseudoalcaligenes CECT5344 cells grown with the jewelry residue as sole nitrogen source. Different proteins related to cyanide and cyanate assimilation, as well as other proteins involved in transport and resistance to metals were induced by the cyanide-containing jewelry residue. GntR-like regulatory proteins were also induced by this industrial residue and mutational analysis revealed that GntR-like regulatory proteins may play a role in the regulation of cyanide assimilation in P. pseudoalcaligenes CECT5344. The strain CECT5344 has been used in a batch reactor to remove at pH 9 the different forms of cyanide present in industrial wastewaters from the jewelry industry (0.3 g/L, ca. 12 mM total cyanide, including both free cyanide and metal-cyanide complexes). This is the first report describing the biological removal at alkaline pH of such as elevated concentration of cyanide present in a heterogeneous mixture from an industrial source.

Evaluation of sample preparation methods for the analysis of papaya leaf proteins through two-dimensional gel electrophoresis.

PubMed

Rodrigues, Silas Pessini; Ventura, José Aires; Zingali, R B; Fernandes, P M B

2009-01-01

A variety of sample preparation protocols for plant proteomic analysis using two-dimensional gel electrophoresis (2-DE) have been reported. However, they usually have to be adapted and further optimised for the analysis of plant species not previously studied. This work aimed to evaluate different sample preparation protocols for analysing Carica papaya L. leaf proteins through 2-DE. Four sample preparation methods were tested: (1) phenol extraction and methanol-ammonium acetate precipitation; (2) no precipitation fractionation; and the traditional trichloroacetic acid-acetone precipitation either (3) with or (4) without protein fractionation. The samples were analysed for their compatibility with SDS-PAGE (1-DE) and 2-DE. Fifteen selected protein spots were trypsinised and analysed by matrix-assisted laser desorption/ionisation time-of-flight tandem mass spectrometry (MALDI-TOF-MS/MS), followed by a protein search using the NCBInr database to accurately identify all proteins. Methods number 3 and 4 resulted in large quantities of protein with good 1-DE separation and were chosen for 2-DE analysis. However, only the TCA method without fractionation (no. 4) proved to be useful. Spot number and resolution advances were achieved, which included having an additional solubilisation step in the conventional TCA method. Moreover, most of the theoretical and experimental protein molecular weight and pI data had similar values, suggesting good focusing and, most importantly, limited protein degradation. The described sample preparation method allows the proteomic analysis of papaya leaves by 2-DE and mass spectrometry (MALDI-TOF-MS/MS). The methods presented can be a starting point for the optimisation of sample preparation protocols for other plant species.

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/.

Mass spectrometry as a tool for studying autism spectrum disorder.

PubMed

Woods, Alisa G; Ngounou Wetie, Armand G; Sokolowska, Izabela; Russell, Stefanie; Ryan, Jeanne P; Michel, Tanja Maria; Thome, Johannes; Darie, Costel C

2013-01-01

Autism spectrum disorders (ASDs) are increasing in incidence but have an incompletely understood etiology. Tools for uncovering clues to the cause of ASDs and means for diagnoses are valuable to the field. Mass Spectrometry (MS) has been a useful method for evaluating differences between individuals with ASDs versus matched controls. Different biological substances can be evaluated using MS, including urine, blood, saliva, and hair. This technique has been used to evaluate relatively unsupported hypotheses based on introduction of exogenous factors, such as opiate and heavy metal excretion theories of ASDs. MS has also been used to support disturbances in serotonin-related molecules, which have been more consistently observed in ASDs. Serotonergic system markers, markers for oxidative stress, cholesterol system disturbances, peptide hypo-phosphorylation and methylation have been measured using MS in ASDs, although further analyses with larger numbers of subjects are needed (as well as consideration of behavioral data). Refinements in MS and data analysis are ongoing, allowing for the possibility that future studies examining body fluids and specimens from ASD subjects could continue to yield novel insights. This review summarizes MS investigations that have been conducted to study ASD to date and provides insight into future promising applications for this technique, with focus on proteomic studies.

Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experiments

PubMed Central

Nesvizhskii, Alexey I.

2013-01-01

Analysis of protein interaction networks and protein complexes using affinity purification and mass spectrometry (AP/MS) is among most commonly used and successful applications of proteomics technologies. One of the foremost challenges of AP/MS data is a large number of false positive protein interactions present in unfiltered datasets. Here we review computational and informatics strategies for detecting specific protein interaction partners in AP/MS experiments, with a focus on incomplete (as opposite to genome-wide) interactome mapping studies. These strategies range from standard statistical approaches, to empirical scoring schemes optimized for a particular type of data, to advanced computational frameworks. The common denominator among these methods is the use of label-free quantitative information such as spectral counts or integrated peptide intensities that can be extracted from AP/MS data. We also discuss related issues such as combining multiple biological or technical replicates, and dealing with data generated using different tagging strategies. Computational approaches for benchmarking of scoring methods are discussed, and the need for generation of reference AP/MS datasets is highlighted. Finally, we discuss the possibility of more extended modeling of experimental AP/MS data, including integration with external information such as protein interaction predictions based on functional genomics data. PMID:22611043

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

PubMed

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

2016-10-26

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

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

PubMed Central

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

2016-01-01

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

A proteomics performance standard to support measurement quality in proteomics.

PubMed

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

2012-04-01

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

NITPICK: peak identification for mass spectrometry data.

PubMed

Renard, Bernhard Y; Kirchner, Marc; Steen, Hanno; Steen, Judith A J; Hamprecht, Fred A

2008-08-28

The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments. This contribution proposes a sparse template regression approach to peak picking called NITPICK. NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra. NITPICK is based on fractional averaging, a novel extension to Senko's well-known averaging model, and on a modified version of sparse, non-negative least angle regression, for which a suitable, statistically motivated early stopping criterion has been derived. The strength of NITPICK is the deconvolution of overlapping mixture mass spectra. Extensive comparative evaluation has been carried out and results are provided for simulated and real-world data sets. NITPICK outperforms pepex, to date the only alternate, publicly available, non-greedy feature extraction routine. NITPICK is available as software package for the R programming language and can be downloaded from (http://hci.iwr.uni-heidelberg.de/mip/proteomics/).

Qupe--a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments.

PubMed

Albaum, Stefan P; Neuweger, Heiko; Fränzel, Benjamin; Lange, Sita; Mertens, Dominik; Trötschel, Christian; Wolters, Dirk; Kalinowski, Jörn; Nattkemper, Tim W; Goesmann, Alexander

2009-12-01

The goal of present -omics sciences is to understand biological systems as a whole in terms of interactions of the individual cellular components. One of the main building blocks in this field of study is proteomics where tandem mass spectrometry (LC-MS/MS) in combination with isotopic labelling techniques provides a common way to obtain a direct insight into regulation at the protein level. Methods to identify and quantify the peptides contained in a sample are well established, and their output usually results in lists of identified proteins and calculated relative abundance values. The next step is to move ahead from these abstract lists and apply statistical inference methods to compare measurements, to identify genes that are significantly up- or down-regulated, or to detect clusters of proteins with similar expression profiles. We introduce the Rich Internet Application (RIA) Qupe providing comprehensive data management and analysis functions for LC-MS/MS experiments. Starting with the import of mass spectra data the system guides the experimenter through the process of protein identification by database search, the calculation of protein abundance ratios, and in particular, the statistical evaluation of the quantification results including multivariate analysis methods such as analysis of variance or hierarchical cluster analysis. While a data model to store these results has been developed, a well-defined programming interface facilitates the integration of novel approaches. A compute cluster is utilized to distribute computationally intensive calculations, and a web service allows to interchange information with other -omics software applications. To demonstrate that Qupe represents a step forward in quantitative proteomics analysis an application study on Corynebacterium glutamicum has been carried out. Qupe is implemented in Java utilizing Hibernate, Echo2, R and the Spring framework. We encourage the usage of the RIA in the sense of the 'software as a service' concept, maintained on our servers and accessible at the following location: http://qupe.cebitec.uni-bielefeld.de. Supplementary data are available at Bioinformatics online.

Data Generated by Quantitative Liquid Chromatography-Mass Spectrometry Proteomics Are Only the Start and Not the Endpoint: Optimization of Quantitative Concatemer-Based Measurement of Hepatic Uridine-5'-Diphosphate-Glucuronosyltransferase Enzymes with Reference to Catalytic Activity.

PubMed

Achour, Brahim; Dantonio, Alyssa; Niosi, Mark; Novak, Jonathan J; Al-Majdoub, Zubida M; Goosen, Theunis C; Rostami-Hodjegan, Amin; Barber, Jill

2018-06-01

Quantitative proteomic methods require optimization at several stages, including sample preparation, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and data analysis, with the final analysis stage being less widely appreciated by end-users. Previously reported measurement of eight uridine-5'-diphospho-glucuronosyltransferases (UGT) generated by two laboratories [using stable isotope-labeled (SIL) peptides or quantitative concatemer (QconCAT)] reflected significant disparity between proteomic methods. Initial analysis of QconCAT data showed lack of correlation with catalytic activity for several UGTs (1A4, 1A6, 1A9, 2B15) and moderate correlations for UGTs 1A1, 1A3, and 2B7 ( R s = 0.40-0.79, P < 0.05; R 2 = 0.30); good correlations were demonstrated between cytochrome P450 activities and abundances measured in the same experiments. Consequently, a systematic review of data analysis, starting from unprocessed LC-MS/MS data, was undertaken, with the aim of improving accuracy, defined by correlation against activity. Three main criteria were found to be important: choice of monitored peptides and fragments, correction for isotope-label incorporation, and abundance normalization using fractional protein mass. Upon optimization, abundance-activity correlations improved significantly for six UGTs ( R s = 0.53-0.87, P < 0.01; R 2 = 0.48-0.73); UGT1A9 showed moderate correlation ( R s = 0.47, P = 0.02; R 2 = 0.34). No spurious abundance-activity relationships were identified. However, methods remained suboptimal for UGT1A3 and UGT1A9; here hydrophobicity of standard peptides is believed to be limiting. This commentary provides a detailed data analysis strategy and indicates, using examples, the significance of systematic data processing following acquisition. The proposed strategy offers significant improvement on existing guidelines applicable to clinically relevant proteins quantified using QconCAT. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

Proteomics analysis of tissue samples from patients with squamous cell carcinoma of the penis and positive to human papillomavirus.

PubMed

Koifman, Leandro; Ornellas, Paulo; Ornellas, Antonio Augusto; Pereira, Denise de Abreu; Zingali, Benedeta Russolina; Cavalcanti, Silvia Maria Baeta; Afonso, Larissa Alves; Sandim, Vanessa; Alves, Gilda

2015-01-01

The aim of this study was to identify possible protein biomarkers and/or candidates for therapeutic targets in tissues of patients with SCCP, infected by HPV, applying one dimensional electrophoresis (1DE), followed by direct mass spectrometry (MS) analysis. Tissues from 10 HPV positive patients with SCCP and from 10 patients with HPV negative non-tumorous penile foreskins were analyzed applying 1D electrophoresis, followed by analysis with direct mass spectrometry (MS). Sixty-three different proteins were identified in the first group and 50 in the second group. Recognition was possible for 28 proteins exclusively detected in Group 1 and 21 proteins presented only in Group 2. Some proteins in the first group are directly involved in the development of other types of cancer, and therefore, suitable for analysis. Complement C3 protein is a strong candidate for evaluating SCCP patients.

Urinary Proteomic Biomarkers for Diagnosis and Risk Stratification of Autosomal Dominant Polycystic Kidney Disease: A Multicentric Study

PubMed Central

Kistler, Andreas D.; Serra, Andreas L.; Siwy, Justyna; Poster, Diane; Krauer, Fabienne; Torres, Vicente E.; Mrug, Michal; Grantham, Jared J.; Bae, Kyongtae T.; Bost, James E.; Mullen, William; Wüthrich, Rudolf P.; Mischak, Harald; Chapman, Arlene B.

2013-01-01

Treatment options for autosomal dominant polycystic kidney disease (ADPKD) will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS), we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI). The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV) based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001) with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD. PMID:23326375

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.

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.

Directed proteomic analysis of the human nucleolus.

PubMed

Andersen, Jens S; Lyon, Carol E; Fox, Archa H; Leung, Anthony K L; Lam, Yun Wah; Steen, Hanno; Mann, Matthias; Lamond, Angus I

2002-01-08

The nucleolus is a subnuclear organelle containing the ribosomal RNA gene clusters and ribosome biogenesis factors. Recent studies suggest it may also have roles in RNA transport, RNA modification, and cell cycle regulation. Despite over 150 years of research into nucleoli, many aspects of their structure and function remain uncharacterized. We report a proteomic analysis of human nucleoli. Using a combination of mass spectrometry (MS) and sequence database searches, including online analysis of the draft human genome sequence, 271 proteins were identified. Over 30% of the nucleolar proteins were encoded by novel or uncharacterized genes, while the known proteins included several unexpected factors with no previously known nucleolar functions. MS analysis of nucleoli isolated from HeLa cells in which transcription had been inhibited showed that a subset of proteins was enriched. These data highlight the dynamic nature of the nucleolar proteome and show that proteins can either associate with nucleoli transiently or accumulate only under specific metabolic conditions. This extensive proteomic analysis shows that nucleoli have a surprisingly large protein complexity. The many novel factors and separate classes of proteins identified support the view that the nucleolus may perform additional functions beyond its known role in ribosome subunit biogenesis. The data also show that the protein composition of nucleoli is not static and can alter significantly in response to the metabolic state of the cell.

Data file of a deep proteome analysis of the prefrontal cortex in aged mice with progranulin deficiency or neuronal overexpression of progranulin.

PubMed

Heidler, Juliana; Hardt, Stefanie; Wittig, Ilka; Tegeder, Irmgard

2016-12-01

Progranulin deficiency is associated with neurodegeneration in humans and in mice. The mechanisms likely involve progranulin-promoted removal of protein waste via autophagy. We performed a deep proteomic screen of the pre-frontal cortex in aged (13-15 months) female progranulin-deficient mice (GRN -/- ) and mice with inducible neuron-specific overexpression of progranulin (SLICK-GRN-OE) versus the respective control mice. Proteins were extracted and analyzed per liquid chromatography/mass spectrometry (LC/MS) on a Thermo Scientific™ Q Exactive Plus equipped with an ultra-high performance liquid chromatography unit and a Nanospray Flex Ion-Source. Full Scan MS-data were acquired using Xcalibur and raw files were analyzed using the proteomics software Max Quant. The mouse reference proteome set from uniprot (June 2015) was used to identify peptides and proteins. The DiB data file is a reduced MaxQuant output and includes peptide and protein identification, accession numbers, protein and gene names, sequence coverage and label free quantification (LFQ) values of each sample. Differences in protein expression in genotypes are presented in "Progranulin overexpression in sensory neurons attenuates neuropathic pain in mice: Role of autophagy" (C. Altmann, S. Hardt, C. Fischer, J. Heidler, H.Y. Lim, A. Haussler, B. Albuquerque, B. Zimmer, C. Moser, C. Behrends, F. Koentgen, I. Wittig, M.H. Schmidt, A.M. Clement, T. Deller, I. Tegeder, 2016) [1].

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.

Quantitative high-throughput profiling of snake venom gland transcriptomes and proteomes (Ovophis okinavensis and Protobothrops flavoviridis)

PubMed Central

2013-01-01

Background Advances in DNA sequencing and proteomics have facilitated quantitative comparisons of snake venom composition. Most studies have employed one approach or the other. Here, both Illumina cDNA sequencing and LC/MS were used to compare the transcriptomes and proteomes of two pit vipers, Protobothrops flavoviridis and Ovophis okinavensis, which differ greatly in their biology. Results Sequencing of venom gland cDNA produced 104,830 transcripts. The Protobothrops transcriptome contained transcripts for 103 venom-related proteins, while the Ovophis transcriptome contained 95. In both, transcript abundances spanned six orders of magnitude. Mass spectrometry identified peptides from 100% of transcripts that occurred at higher than contaminant (e.g. human keratin) levels, including a number of proteins never before sequenced from snakes. These transcriptomes reveal fundamentally different envenomation strategies. Adult Protobothrops venom promotes hemorrhage, hypotension, incoagulable blood, and prey digestion, consistent with mammalian predation. Ovophis venom composition is less readily interpreted, owing to insufficient pharmacological data for venom serine and metalloproteases, which comprise more than 97.3% of Ovophis transcripts, but only 38.0% of Protobothrops transcripts. Ovophis venom apparently represents a hybrid strategy optimized for frogs and small mammals. Conclusions This study illustrates the power of cDNA sequencing combined with MS profiling. The former quantifies transcript composition, allowing detection of novel proteins, but cannot indicate which proteins are actually secreted, as does MS. We show, for the first time, that transcript and peptide abundances are correlated. This means that MS can be used for quantitative, non-invasive venom profiling, which will be beneficial for studies of endangered species. PMID:24224955

Proteomics analysis in frozen horse mackerel previously high-pressure processed.

PubMed

Pazos, Manuel; Méndez, Lucía; Vázquez, Manuel; Aubourg, Santiago P

2015-10-15

The effect of high-pressure processing (HPP) (150, 300 and 450 MPa for 0, 2.5 and 5 min) on total sodium dodecyl sulphate (SDS)-soluble and sarcoplasmic proteins in frozen (-10 °C for 3 months) horse mackerel (Trachurus trachurus) was evaluated. Proteomics tools based on image analysis of SDS-PAGE protein gels and protein identification by tandem mass spectrometry (MS/MS) were applied. Although total SDS-soluble fraction indicated no important changes induced by HPP, this processing modified the 1-D SDS-PAGE sarcoplasmic patterns in a direct-dependent manner and exerted a selective effect on particular proteins depending on processing conditions. Thus, application of the highest pressure (450 MPa) provoked a significant degradation of phosphoglycerate mutase 2, glycogen phosphorylase muscle form, pyruvate kinase muscle isozyme, beta-enolase and triosephosphate isomerase and phosphoglucomutase-1. Conversely, protein bands assigned to tropomyosin alpha-1 chain, fast myotomal muscle troponin T and parvalbumin beta 2 increased their intensity after applying a 450-MPa processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Application of a Three-Step Proteome Analysis for Identification of New Biomarkers of Pancreatic Cancer

PubMed Central

Abulaizi, Mayinuer; Tomonaga, Takeshi; Satoh, Mamoru; Sogawa, Kazuyuki; Matsushita, Kazuyuki; Kodera, Yoshio; Obul, Jurat; Takano, Shigetsugu; Yoshitomi, Hideyuki; Miyazaki, Masaru; Nomura, Fumio

2011-01-01

We searched for novel tumor markers of pancreatic cancer by three-step serum proteome analysis. Twelve serum abundant proteins were depleted using immunoaffinity columns followed by fractionation by reverse-phase high-performance liquid chromatography. Proteins in each fraction were separated by two-dimensional gel electrophoresis. Then the gel was stained by Coomassie Brilliant Blue. Protein spots in which the expression levels were significantly different between cancer and normal control were identified by LC-MS/MS. One hundred and two spots were upregulated, and 84 spots were downregulated in serum samples obtained from patients with pancreatic cancers, and 58 proteins were identified by mass spectrometry. These candidate proteins were validated using western blot analysis and enzyme-linked immunosorbent assay (ELISA). As a result of these validation process, we could confirm that the serum levels of apolipoprotein A-IV, vitamin D-binding protein, plasma retinol-binding protein 4, and tetranectin were significantly decreased in patients with pancreatic cancer. PMID:22091389

ITRAQ-based quantitative proteomic analysis of Cynops orientalis limb regeneration.

PubMed

Tang, Jie; Yu, Yuan; Zheng, Hanxue; Yin, Lu; Sun, Mei; Wang, Wenjun; Cui, Jihong; Liu, Wenguang; Xie, Xin; Chen, Fulin

2017-09-22

Salamanders regenerate their limbs after amputation. However, the molecular mechanism of this unique regeneration remains unclear. In this study, isobaric tags for relative and absolute quantification (iTRAQ) coupled with liquid chromatography tandem mass spectrometry (LC-MS/MS) was employed to quantitatively identify differentially expressed proteins in regenerating limbs 3, 7, 14, 30 and 42 days post amputation (dpa). Of 2636 proteins detected in total, 253 proteins were differentially expressed during different regeneration stages. Among these proteins, Asporin, Cadherin-13, Keratin, Collagen alpha-1(XI) and Titin were down-regulated. CAPG, Coronin-1A, AnnexinA1, Cathepsin B were up-regulated compared with the control. The identified proteins were further analyzed to obtain information about their expression patterns and functions in limb regeneration. Functional analysis indicated that the differentially expressed proteins were associated with wound healing, immune response, cellular process, metabolism and binding. This work indicated that significant proteome alternations occurred during salamander limb regeneration. The results may provide fundamental knowledge to understand the mechanism of limb regeneration.

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